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Faculty / Organisational entity
- Kaiserslautern - Fachbereich Mathematik (1052)
- Kaiserslautern - Fachbereich Informatik (752)
- Kaiserslautern - Fachbereich Maschinenbau und Verfahrenstechnik (298)
- Kaiserslautern - Fachbereich Physik (293)
- Fraunhofer (ITWM) (205)
- Kaiserslautern - Fachbereich Chemie (116)
- Kaiserslautern - Fachbereich Elektrotechnik und Informationstechnik (115)
- Kaiserslautern - Fachbereich Biologie (98)
- Kaiserslautern - Fachbereich Sozialwissenschaften (76)
- Kaiserslautern - Fachbereich Wirtschaftswissenschaften (36)
The aim of this dissertation is to explain processes in recruitment by gaining a better understanding of how perceptions evolve and how recruitment outcomes and perceptions are influenced. To do so, this dissertation takes a closer look at the formation of fit perceptions, the effects of top employer awards on pre-hire recruitment outcomes, and on how perceptions about external sources are influenced.
In this work a 3-dimensional contact elasticity problem for a thin fiber and a rigid foundation is studied. We describe the contact condition by a linear Robin-condition (by meaning of the penalized and linearized non-penetration and friction conditions).
The dimension of the problem is reduced by an asymptotic approach. Scaling the Robin parameters appropriately we obtain a recurrent chain of Neumann type boundary value problems which are considered only in the microscopic scale. The problem for the leading term is a homogeneous Neumann problem, hence the leading term depends only on the slow variable. This motivates the choice of a multiplicative ansatz in the asymptotic expansion.
The theoretical results are illustrated with numerical examples performed with a commercial finite-element software-tool.
The Lagrangian field-antifield formalism of Batalin and Vilkovisky (BV) is used to investigate the application of the collec- tive coordinate method to soliton quantisation. In field theories with soliton solutions, the Gaussian fluctuation operator has zero modes due to the breakdown of global symmetries of the Lagrangian in the soliton solutions. It is shown how Noether identities and local symmetries of the Lagrangian arise when collective coordinates are introduced in order to avoid divergences related to these zero modes. This transformation to collective and fluctuation degrees of freedom is interpreted as a canonical transformation in the symplectic field-antifield space which induces a time-local gauge symmetry. Separating the corresponding Lagrangian path integral of the BV scheme in lowest order into harmonic quantum fluctuations and a free motion of the collective coordinate with the classical mass of the soliton, we show how the BV approach clarifies the relation between zero modes, collective coordinates, gauge invariance and the center- of-mass motion of classical solutions in quantum fields. Finally, we apply the procedure to the reduced nonlinear O(3) oe-model.^L
Laser-based powder bed fusion (L-PBF) is a promising technology for the production of near net–shaped metallic components. The high surface roughness and the comparatively low-dimensional accuracy of such components, however, usually require a finishing by a subtractive process such as milling or grinding in order to meet the requirements of the application. Materials manufactured via L-PBF are characterized by a unique microstructure and anisotropic material properties. These specific properties could also affect the subtractive processes themselves. In this paper, the effect of L-PBF on the machinability of the aluminum alloy AlSi10Mg is explored when milling. The chips, the process forces, the surface morphology, the microhardness, and the burr formation are analyzed in dependence on the manufacturing parameter settings used for L-PBF and the direction of feed motion of the end mill relative to the build-up direction of the parts. The results are compared with a conventionally cast AlSi10Mg. The analysis shows that L-PBF influences the machinability. Differences between the reference and the L-PBF AlSi10Mg were observed in the chip form, the process forces, the surface morphology, and the burr formation. The initial manufacturing method of the part thus needs to be considered during the design of the finishing process to achieve suitable results.
Based on experiences from an autonomous mobile robot project called MOBOT -III, we found hard realtime-constraints for the operating-system-design. ALBATROSS is "A flexible multi-tasking and realtime network-operatingsystem-kernel", not limited to mobile- robot-projects only, but which might be useful also wherever you have to guarantee a high reliability of a realtime-system. The focus in this article is on a communication-scheme fulfilling the demanded (hard realtime-) assurances although not implying time-delays or jitters on the critical informationchannels. The central chapters discuss a locking-free shared buffer management, without the need for interrupts and a way to arrange the communication architecture in order to produce minimal protocol-overhead and short cycle-times. Most of the remaining communication-capacity (if there is any) is used for redundant transfers, increasing the reliability of the whole system. ALBATROSS is actually implemented on a multi-processor VMEbus-system.
This paper refers to the problem of adaptability over an infinite period of time, regarding dynamic networks. A never ending flow of examples have to be clustered, based on a distance measure. The developed model is based on the self-organizing feature maps of Kohonen [6], [7] and some adaptations by Fritzke [3]. The problem of dynamic surface classification is embedded in the SPIN project, where sub-symbolic abstractions, based on a 3-d scanned environment is being done.
The problem to be discussed here, is the usage of neural network clustering techniques on a mobile robot, in order to build qualitative topologic environment maps. This has to be done in realtime, i.e. the internal world model has to be adapted by the flow of sensor- samples without the possibility to stop this data-flow.Our experiments are done in a simulation environment as well as on a robot, called ALICE.
Based on the experiences from an autonomous mobile robot project called MOBOT-III, we found hard realtime-constraints for the operating- system-design. ALBATROSS is "A flexible multi-tasking and realtime network-operating-system-kernel". The focusin this article is on a communication-scheme fulfilling the previous demanded assurances. The centralchapters discuss the shared buffer management and the way to design the communication architecture.Some further aspects beside the strict realtime-requirements like the possibilities to control and watch a running system, are mentioned. ALBATROSS is actually implemented on a multi-processor VMEbus-system.
Based on the idea of using topologic feature-mapsinstead of geometric environment maps in practical mobile robot tasks, we show an applicable way tonavigate on such topologic maps. The main features regarding this kind of navigation are: handling of very inaccurate position (and orientation) information as well as implicit modelling of complex kinematics during an adaptation phase. Due to the lack of proper a-priori knowledge, a re-inforcement based model is used for the translation of navigator commands to motor actions. Instead of employing a backpropagation network for the cen-tral associative memory module (attaching actionprobabilities to sensor situations resp. navigatorcommands) a much faster dynamic cell structure system based on dynamic feature maps is shown. Standard graph-search heuristics like A* are applied in the planning phase.
SPIN-NFDS Learning and Preset Knowledge for Surface Fusion - A Neural Fuzzy Decision System -
(1993)
The problem to be discussed in this paper may be characterized in short by the question: "Are these two surface fragments belonging together (i.e. belonging to the same surface)?" The presented techniques try to benefit from some predefined knowledge as well as from the possibility to refine and adapt this knowledge according to a (changing) real environment, resulting in a combination of fuzzy-decision systems and neural networks. The results are encouraging (fast convergence speed, high accuracy), and the model might be used for a wide range of applications. The general frame surrounding the work in this paper is the SPIN- project, where emphasis is on sub-symbolic abstractions, based on a 3-d scanned environment.
This article will discuss a qualitative, topological and robust world-modelling technique with special regard to navigation-tasks for mobile robots operating in unknownenvironments. As a central aspect, the reliability regarding error-tolerance and stability will be emphasized. Benefits and problems involved in exploration, as well as in navigation tasks, are discussed. The proposed method demands very low constraints for the kind and quality of the employed sensors as well as for the kinematic precision of the utilized mobile platform. Hard real-time constraints can be handled due to the low computational complexity. The principal discussions are supported by real-world experiments with the mobile robot
Self-localization in unknown environments respectively correlation of current and former impressions of the world is an essential ability for most mobile robots. The method,proposed in this article is the construction of a qualitative, topological world model as a basis for self-localization. As a central aspect the reliability regarding error-tolerance and stability will be emphasized. The proposed techniques demand very low constraints for the kind and quality of the employed sensors as well as for the kinematic precisionof the utilized mobile platform. Hard real-time constraints can be handled due to the low computational complexity. The principal discussions are supported by real-world experiments with the mobile robot.
Visual Search has been investigated by many researchers inspired by the biological fact, that the sensory elements on the mammal retina are not equably distributed. Therefore the focus of attention (the area of the retina with the highest density of sensory elements) has to be directed in a way to efficiently gather data according to certain criteria. The work discussed in this article concentrates on applying a laser range finder instead of a silicon retina. The laser range finder is maximal focused at any time, but therefore a low resolution total-scene-image, available with camera-like devices from scratch on, cannot be used here. By adapting a couple of algorithms, the edge-scanning module steering the laser range finder is able to trace a detected edge. Based on the data scanned so far , two questions have to be answered. First: "Should the actual (edge-) scanning be interrupted in order to give another area of interest a chance of being investigated?" and second: "Where to start a new edge-scanning, after being interrupted?". These two decision-problems might be solved by a range of decision systems. The correctness of the decisions depends widely on the actual environment and the underlying rules may not be well initialized with a-priori knowledge. So we will present a version of a reinforcement decision system together with an overall scheme for efficiently controlling highly focused devices.
World models for mobile robots as introduced in many projects, are mostly redundant regarding similar situations detected in different places. The present paper proposes a method for dynamic generation of a minimal world model based on these redundancies. The technique is an extention of the qualitative topologic world modelling methods. As a central aspect the reliability regarding errortolerance and stability will be emphasized. The proposed technique demands very low constraints on the kind and quality of the employed sensors as well as for the kinematic precision of the utilized mobile platform. Hard realtime constraints can be handled due to the low computational complexity. The principal discussions are supported by real-world experiments with the mobile robot "
ALICE
(1994)
Matter-wave Optics of Dark-state Polaritons: Applications to Interferometry and Quantum Information
(2006)
The present work "Materwave Optics with Dark-state Polaritons: Applications to Interferometry and Quantum Information" deals in a broad sense with the subject of dark-states and in particular with the so-called dark-state polaritons introduced by M. Fleischhauer and M. D. Lukin. The dark-state polaritons can be regarded as a combined excitation of electromagnetic fields and spin/matter-waves. Within the framework of this thesis the special optical properties of the combined excitation are studied. On one hand a new procedure to spatially manipulate and to increase the excitation density of stored photons is described and on the other hand the properties are used to construct a new type of Sagnac Hybrid interferometer. The thesis is devided into four parts. In the introduction all notions necessary to understand the work are described, e.g.: electromagnetically induced transparency (EIT), dark-state polaritons and the Sagnac effect. The second chapter considers the method developed by A. Andre and M. D. Lukin to create stationary light pulses in specially dressed EIT-media. In a first step a set of field equations is derived and simplified by introducing a new set of normal modes. The absorption of one of the normal modes leads to the phenomenon of pulse-matching for the other mode and thereby to a diffusive spreading of its field envelope. All these considerations are based on a homogeneous field setup of the EIT preparation laser. If this restriction is dismissed one finds that a drift motion is superimposed to the diffusive spreading. By choosing a special laser configuration the drift motion can be tailored such that an effective force is created that counteracts the spreading. Moreover, the force can not only be strong enough to compensate the diffusive spreading but also to exceed this dynamics and hence to compress the field envelope of the excitation. The compression can be discribed using a Fokker-Planck equation of the Ornstein-Uhlenbeck type. The investigations show that the compression leads to an excitation of higher-order modes which decay very fast. In the last section of the chapter this exciation will be discussed in more detail and conditions will be given how the excitation of higher-order modes can be avoided or even suppressed. All results given in the chapter are supported by numerical simulatons. In the third chapter the matterwave optical properties of the dark-state polaritons will be studied. They will be used to construct a light-matterwave hybrid Sagnac interferometer. First the principle setup of such an interferometer will be sketched and the relevant equations of motion of light-matter interaction in a rotating frame will be derived. These form the basis of the following considerations of the dark-state polariton dynamics with and without the influence of external trapping potentials on the matterwave part of the polariton. It will be shown that a sensitivity enhancement compared to a passive laser gyroscope can be anticipated if the gaseous medium is initially in a superfluid quantum state in a ring-trap configuration. To achieve this enhancement a simultaneous coherence and momentum transfer is furthermore necessary. In the last part of the chapter the quantum sensitivity limit of the hybrid interferometer is derived using the one-particle density matrix equations incorporating the motion of the particles. To this end the Maxwell-Bloch equations are considered perturbatively in the rotation rate of the noninertial frame of reference and the susceptibility of the considered 3-level \(\Lambda\)-type system is derived in arbitrary order of the probe-field. This is done to determine the optimum operation point. With its help the anticipated quantum sensitivity of the light-matterwave hybrid Sagnac interferometer is calculated at the shot-noise limit and the results are compared to state-of-the-art laser and matterwave Sagnac interferometers. The last chapter of the thesis originates from a joint theoretical and experimental project with the AG Bergmann. This chapter does no longer consider the dark-state polaritons of the last two chapters but deals with the more general concept of dark states and in particular with the transient velocity selective dark states as introduced by E. Arimondo et al. In the experiment we could for the first time measure these states. The chapter starts with an introduction into the concept of velocity selective dark states as they occur in a \(\Lambda\)-configuration. Then we introduce the transient velocity selective dark-states as they occur in an particular extension of the \(\Lambda\)-system. For later use in the simulations the relevant equations of motion are derived in detail. The simulations are based on the solution of the generalized optical Bloch equations. Finally the experimental setup and procedure are explained and the theoretical and experimental results are compared.
To continue reducing voltage in scaled technologies, both circuit and architecture-level resiliency techniques are needed to tolerate process-induced defects, variation, and aging in SRAM cells. Many different resiliency schemes have been proposed and evaluated, but most prior results focus on voltage reduction instead of energy reduction. At the circuit level, device cell architectures and assist techniques have been shown to lower Vmin for SRAM, while at the architecture level, redundancy and cache disable techniques have been used to improve resiliency at low voltages. This paper presents a unified study of error tolerance for both circuit and architecture techniques and estimates their area and energy overheads. Optimal techniques are selected by evaluating both the error-correcting abilities at low supplies and the overheads of each technique in a 28nm. The results can be applied to many of the emerging memory technologies.
Abstract: We calculate exact analytical expressions for O(alpha s) 3-jet and O (alpha^2 s ) 4-jet cross sections in polarized deep inelastic lepton nucleon scattering. Introducing an invariant jet definition scheme, we present differential distributions of 3- and 4-jet cross sections in the basic kinematical variables x and W^2 as well as total jet cross sections and show their dependence on the chosen spin-dependent (polarized) parton distributions. Noticebly differences in the predictions are found for the two extreme choices, i.e. a large negative sea-quark density or a large positive gluon density. Therefore, it may be possible to discriminate between different parametrizations of polarized parton densities, and hence between the different physical pictures of the proton spin underlying these parametrizations.
A series of (oligo)phenthiazines, thiazolium salts and sulfonic acid functionalized organic/inorganic hybrid materials were synthesized. The organic groups were covalently bound on the inorganic surface through reactions of organosilane precursors with TEOS or with the silanol groups of material surface. These synthetic methods are called the co-condensation process and the post grafting. The structures and the textural parameters of the generated hybrid materials were characterized by XRD, N2 adsorption-desorption measurements, SEM and TEM. The incorporations of the organic groups were verified by elemental analysis, thermogravimetric analysis, FT-IR, UV-Vis, EPR, CV, as well as by 13C CP-MAS NMR and 29Si CP-MAS NMR spectroscopy. Introduction of various organic groups endow different phsysical, chemical properties to these hybrid materials. The (oligo)phenothiazines provide a group of novel redox acitive hybrid materials with special electronic and optic properties. The thiazolium salts modified materials were applied as heterogenized organo catalysts for the benzoin condensation and the cross-coupling of aldehydes with acylimines to yield a-amido ketones. The sulfonic acid containing materials can not only be used as Broensted acid catalysts, but also can serve as ion exchangable supports for further modifications and applications.
Nanoparticle-Filled Thermoplastics and Thermoplastic Elastomer: Structure-Property Relationships
(2012)
The present work focuses on the structure-property relationships of
particulate-filled thermoplastics and thermoplastic elastomer (TPE). In this work
two thermoplastics and one TPE were used as polymer matrices, i.e. amorphous
bisphenol-A polycarbonate (PC), semi-crystalline isotactic polypropylene (iPP),
and a block copolymer poly(butylene terephthalate)-block-poly(tetramethylene
glycol) TPE(PBT-PTMG). For PC, a selected type of various Aerosil® nano-SiO2
types was used as filler to improve the thermal and mechanical properties by
maintaining the transparency of PC matrix. Different types of SiO2 and TiO2
nanoparticles with different surface polarity were used for iPP. The goal was to
examine the influence of surface polarity and chemical nature of nanoparticles on
the thermal, mechanical and morphological properties of iPP composites. For
TPE(PBT-PTMG), three TiO2 particles were used, i.e. one grade with hydroxyl
groups on the particle surface and the other two grades are surface-modified with
metal and metal oxides, respectively. The influence of primary size and dispersion
quality of TiO2 particles on the properties of TPE(PBT-PTMG)/TiO2 composites
were determined and discussed.
All polymer composites were produced by direct melt blending in a twin-screw
extruder via masterbatch technique. The dispersion of particles was examined by
using scanning electron microscopy (SEM) and micro-computerized tomography
(μCT). The thermal and crystalline properties of polymer composites were characterized by using thermogravimetric analysis (TGA) and differential
scanning calorimetry (DSC). The mechanical and thermomechanical properties
were determined by using mechanical tensile testing, compact tension and
Charpy impact as well as dynamic-mechanical thermal analysis (DMTA).
The SEM results show that the unpolar-surface modified nanoparticles are better
dispersed in polymer matrices as iPP than polar-surface nanoparticles, especially
in case of using Aeroxide® TiO2 nanoparticles. The Aeroxide® TiO2 nanoparticles
with a polar surface due to Ti-OH groups result in a very high degree of
agglomeration in both iPP and TPE matrices because of strong van der Waals
interactions among particles (hydrogen bonding). Compared to unmodified
Aeroxide® TiO2 nanoparticles, the other grades of surface modified TiO2 particles
are very homogenously dispersed in used iPP and TPE(PBT-PTMG). The
incorporation of SiO2 nanoparticles into bisphenol-A PC significantly increases
the mechanical properties of PC/SiO2 nanocomposites, particularly the resistance
against environmental stress crazing (ESC). However, the transparency of
PC/SiO2 nanocomposites decreases with increasing nanoparticle content and
size due to a mismatch of infractive indices of PC and SiO2 particles. The different
surface polarity of nanoparticles in iPP shows evident influence on properties of
iPP composites. Among iPP/SiO2 nanocomposites, the nanocomposite
containing SiO2 nanoparticles with a higher degree of hydrophobicity shows
improved fracture and impact toughness compared to the other iPP/SiO2
composites. The TPE(PBT-PTMG)/TiO2 composites show much better thermal and mechanical properties than neat TPE(PBT-PTMG) due to strong chemical
interactions between polymer matrix and TiO2 particles. In addition, better
dispersion quality of TiO2 particles in used TPE(PBT-PTMG) leads to dramatically
improved mechanical properties of TPE(PBT-PTMG)/TiO2 composites.
Planar force or pressure is a fundamental physical aspect during any people-vs-people and people-vs-environment activities and interactions. It is as significant as the more established linear and angular acceleration (usually acquired by inertial measurement units). There have been several studies involving planar pressure in the discipline of activity recognition, as reviewed in the first chapter. These studies have shown that planar pressure is a promising sensing modality for activity recognition. However, they still take a niche part in the entire discipline, using ad hoc systems and data analysis methods. Mostly these studies were not followed by further elaborative works. The situation calls for a general framework that can help push planar pressure sensing into the mainstream.
This dissertation systematically investigates using planar pressure distribution sensing technology for ubiquitous and wearable activity recognition purposes. We propose a generic Textile Pressure Mapping (TPM) Framework, which encapsulates (1) design knowledge and guidelines, (2) a multi-layered tool including hardware, software and algorithms, and (3) an ensemble of empirical study examples. Through validation with various empirical studies, the unified TPM framework covers the full scope of application recognition, including the ambient, object, and wearable subspaces.
The hardware part constructs a general architecture and implementations in the large-scale and mobile directions separately. The software toolkit consists of four heterogeneous tiers: driver, data processing, machine learning, visualization/feedback. The algorithm chapter describes generic data processing techniques and a unified TPM feature set. The TPM framework offers a universal solution for other researchers and developers to evaluate TPM sensing modality in their application scenarios.
The significant findings from the empirical studies have shown that TPM is a versatile sensing modality. Specifically, in the ambient subspace, a sports mat or carpet with TPM sensors embedded underneath can distinguish different sports activities or different people's gait based on the dynamic change of body-print; a pressure sensitive tablecloth can detect various dining actions by the force propagated from the cutlery through the plates to the tabletop. In the object subspace, swirl office chairs with TPM sensors under the cover can be used to detect the seater's real-time posture; TPM can be used to detect emotion-related touch interactions for smart objects, toys or robots. In the wearable subspace, TPM sensors can be used to perform pressure-based mechanomyography to detect muscle and body movement; it can also be tailored to cover the surface of a soccer shoe to distinguish different kicking angles and intensities.
All the empirical evaluations have resulted in accuracies well-above the chance level of the corresponding number of classes, e.g., the `swirl chair' study has classification accuracy of 79.5% out of 10 posture classes and in the `soccer shoe' study the accuracy is 98.8% among 17 combinations of angle and intensity.
We propose and study a strongly coupled PDE-ODE system with tissue-dependent degenerate diffusion and haptotaxis that can serve as a model prototype for cancer cell invasion through the
extracellular matrix. We prove the global existence of weak solutions and illustrate the model behaviour by numerical simulations for a two-dimensional setting.
We propose and study a strongly coupled PDE-ODE-ODE system modeling cancer cell invasion through a tissue network
under the go-or-grow hypothesis asserting that cancer cells can either move or proliferate. Hence our setting features
two interacting cell populations with their mutual transitions and involves tissue-dependent degenerate diffusion and
haptotaxis for the moving subpopulation. The proliferating cells and the tissue evolution are characterized by way of ODEs
for the respective densities. We prove the global existence of weak solutions and illustrate the model behaviour by
numerical simulations in a two-dimensional setting.
Whole-body vibrations (WBV) have adverse effects on ride comfort and human health. Suspension seats have an important influence on the WBV severity. In this study, WBV were measured on a medium-sized compact wheel loader (CWL) in its typical operations. The effect of short-term exposure to the WBV on the ride comfort was evaluated according to ISO 2631-1:1985 and ISO 2631-1:1997. ISO 2631-1:1997 and ISO 2631-5:2004 were adopted to evaluate the effect of long-term exposure to the WBV on the human health. Reasons for the different evaluation results obtained according to ISO 2631-1:1997 and ISO 2631-5:2004 were explained in this study. The WBV measurements were carried out in cases where the driver wore a lap belt or a four-point seat harness and in the case where the driver did not wear any safety belt. The seat effective amplitude transmissibility (SEAT) and the seat transmissibility in the frequency domain in these three cases were analyzed to investigate the effect of a safety belt on the seat transmissibility. Seat tests were performed on a multi-axis shaking table in laboratory to study the dynamic behavior of a suspension seat under the vibration excitations measured on the CWL. The WBV intensity was reduced by optimizing the vertical and the longitudinal seat suspension systems with the help of computational simulations. For the optimization multi-body models of the seat-dummy system in the laboratory seat tests and the seat-driver system in the field vibration measurements were built and validated.
A new method is used to investigate the tunneling between two weakly-linked Bose-Einstein con- densates confined in double-well potential traps. The nonlinear interaction between the atoms in each well contributes to a finite chemical potential, which, with consideration of periodic instantons, leads to a remarkably high tunneling frequency. This result can be used to interpret the newly found Macroscopic Quantum Self Trapping (MQST) effect. Also a new kind of first-order crossover between different regions is predicted.
The main purpose of the study was to improve the physical properties of the modelling of compressed materials, especially fibrous materials. Fibrous materials are finding increasing application in the industries. And most of the materials are compressed for different applications. For such situation, we are interested in how the fibre arranged, e.g. with which distribution. For given materials it is possible to obtain a three-dimensional image via micro computed tomography. Since some physical parameters, e.g. the fibre lengths or the directions for points in the fibre, can be checked under some other methods from image, it is beneficial to improve the physical properties by changing the parameters in the image.
In this thesis, we present a new maximum-likelihood approach for the estimation of parameters of a parametric distribution on the unit sphere, which is various as some well known distributions, e.g. the von-Mises Fisher distribution or the Watson distribution, and for some models better fit. The consistency and asymptotic normality of the maximum-likelihood estimator are proven. As the second main part of this thesis, a general model of mixtures of these distributions on a hypersphere is discussed. We derive numerical approximations of the parameters in an Expectation Maximization setting. Furthermore we introduce a non-parametric estimation of the EM algorithm for the mixture model. Finally, we present some applications to the statistical analysis of fibre composites.
In recent years, nanofiller-reinforced polymer composites have attracted considerable
interest from numerous researchers, since they can offer unique mechanical,
electrical, optical and thermal properties compared to the conventional polymer
composites filled with micron-sized particles or short fibers. With this background, the
main objective of the present work was to investigate the various mechanical
properties of polymer matrices filled with different inorganic rigid nanofillers, including
SiOB2B, TiOB2B, AlB2BOB3B and multi-walled carbon nanotubes (MWNT). Further, special
attention was paid to the fracture behaviours of the polymer nanocomposites. The
polymer matrices used in this work contained two types of epoxy resin (cycloaliphatic
and bisphenol-F) and two types of thermoplastic polymer (polyamide 66 and isotactic
polypropylene).
The epoxy-based nanocomposites (filled with nano-SiOB2B) were formed in situ by a
special sol-gel technique supplied by nanoresins AG. Excellent nanoparticle
dispersion was achieved even at rather high particle loading. The almost
homogeneously distributed nanoparticles can improve the elastic modulus and
fracture toughness (characterized by KBICB and GBICB) simultaneously. According to
dynamic mechanical and thermal analysis (DMTA), the nanosilica particles in epoxy
resins possessed considerable "effective volume fraction" in comparison with their
actual volume fraction, due to the presence of the interphase. Moreover, AFM and
high-resolution SEM observations also suggested that the nanosilica particles were
coated with a polymer layer and therefore a core-shell structure of particle-matrix was
expected. Furthermore, based on SEM fractography, several toughening
mechanisms were considered to be responsible for the improvement in toughness,
which included crack deflection, crack pinning/bowing and plastic deformation of
matrix induced by nanoparticles.
The PA66 or iPP-based nanocomposites were fabricated by a conventional meltextrusion
technique. Here, the nanofiller content was set constant as 1 vol.%. Relatively good particle dispersion was found, though some small aggregates still
existed. The elastic modulus of both PA66 and iPP was moderately improved after
incorporation of the nanofillers. The fracture behaviours of these materials were
characterized by an essential work fracture (EWF) approach. In the case of PA66
system, the EWF experiments were carried out over a broad temperature range
(23~120 °C). It was found that the EWF parameters exhibited high temperature
dependence. At most testing temperatures, a small amount of nanoparticles could
produce obvious toughening effects at the cost of reduction in plastic deformation of
the matrix. In light of SEM fractographs and crack opening tip (COD) analysis, the
crack blunting induced by nanoparticles might be the major source of this toughening.
The fracture behaviours of PP filled with MWNTs were investigated over a broad
temperature range (-196~80 °C) in terms of notched impact resistance. It was found
that MWNTs could enhance the notched impact resistance of PP matrix significantly
once the testing temperature was higher than the glass transition temperature (TBgB) of
neat PP. At the relevant temperature range, the longer the MWNTs, the better was
the impact resistance. SEM observation revealed three failure modes of nanotubes:
nanotube bridging, debonding/pullout and fracture. All of them would contribute to
impact toughness to a degree. Moreover, the nanotube fracture was considered as
the major failure mode. In addition, the smaller spherulites induced by the nanotubes
would also benefit toughness.
Nowadays, accounting, charging and billing users' network resource consumption are commonly used for the purpose of facilitating reasonable network usage, controlling congestion, allocating cost, gaining revenue, etc. In traditional IP traffic accounting systems, IP addresses are used to identify the corresponding consumers of the network resources. However, there are some situations in which IP addresses cannot be used to identify users uniquely, for example, in multi-user systems. In these cases, network resource consumption can only be ascribed to the owners of these hosts instead of corresponding real users who have consumed the network resources. Therefore, accurate accountability in these systems is practically impossible. This is a flaw of the traditional IP address based IP traffic accounting technique. This dissertation proposes a user based IP traffic accounting model which can facilitate collecting network resource usage information on the basis of users. With user based IP traffic accounting, IP traffic can be distinguished not only by IP addresses but also by users. In this dissertation, three different schemes, which can achieve the user based IP traffic accounting mechanism, are discussed in detail. The inband scheme utilizes the IP header to convey the user information of the corresponding IP packet. The Accounting Agent residing in the measured host intercepts IP packets passing through it. Then it identifies the users of these IP packets and inserts user information into the IP packets. With this mechanism, a meter located in a key position of the network can intercept the IP packets tagged with user information, extract not only statistic information, but also IP addresses and user information from the IP packets to generate accounting records with user information. The out-of-band scheme is a contrast scheme to the in-band scheme. It also uses an Accounting Agent to intercept IP packets and identify the users of IP traffic. However, the user information is transferred through a separated channel, which is different from the corresponding IP packets' transmission. The Multi-IP scheme provides a different solution for identifying users of IP traffic. It assigns each user in a measured host a unique IP address. Through that, an IP address can be used to identify a user uniquely without ambiguity. This way, traditional IP address based accounting techniques can be applied to achieve the goal of user based IP traffic accounting. In this dissertation, a user based IP traffic accounting prototype system developed according to the out-of-band scheme is also introduced. The application of user based IP traffic accounting model in the distributed computing environment is also discussed.
Conditional Compilation (CC) is frequently used as a variation mechanism in software product lines (SPLs). However, as a SPL evolves the variable code realized by CC erodes in the sense that it becomes overly complex and difficult to understand and maintain. As a result, the SPL productivity goes down and puts expected advantages more and more at risk. To investigate the variability erosion and keep the productivity above a sufficiently good level, in this paper we 1) investigate several erosion symptoms in an industrial SPL; 2) present a variability improvement process that includes two major improvement strategies. While one strategy is to optimize variable code within the scope of CC, the other strategy is to transition CC to a new variation mechanism called Parameterized Inclusion. Both of these two improvement strategies can be conducted automatically, and the result of CC optimization is provided. Related issues such as applicability and cost of the improvement are also discussed.
As a Software Product Line (SPL) evolves with increasing number of features and feature values, the feature correlations become extremely intricate, and the specifications of these correlations tend to be either incomplete or inconsistent with their realizations, causing misconfigurations in practice. In order to guide product configuration processes, we present a solution framework to recover complex feature correlations from existing product configurations. These correlations are further pruned automatically and validated by domain experts. During implementation, we use association mining techniques to automatically extract strong association rules as potential feature correlations. This approach is evaluated using a large-scale industrial SPL in the embedded system domain, and finally we identify a large number of complex feature correlations.
This thesis is devoted to deal with the stochastic optimization problems in various situations with the aid of the Martingale method. Chapter 2 discusses the Martingale method and its applications to the basic optimization problems, which are well addressed in the literature (for example, [15], [23] and [24]). In Chapter 3, we study the problem of maximizing expected utility of real terminal wealth in the presence of an index bond. Chapter 4, which is a modification of the original research paper joint with Korn and Ewald [39], investigates an optimization problem faced by a DC pension fund manager under inflationary risk. Although the problem is addressed in the context of a pension fund, it presents a way of how to deal with the optimization problem, in the case there is a (positive) endowment. In Chapter 5, we turn to a situation where the additional income, other than the income from returns on investment, is gained by supplying labor. Chapter 6 concerns a situation where the market considered is incomplete. A trick of completing an incomplete market is presented there. The general theory which supports the discussion followed is summarized in the first chapter.
In this work, we analyze two important and simple models of short rates, namely Vasicek and CIR models. The models are described and then the sensitivity of the models with respect to changes in the parameters are studied. Finally, we give the results for the estimation of the model parameters by using two different ways.
Automata theory has given rise to a variety of automata models that consist
of a finite-state control and an infinite-state storage mechanism. The aim
of this work is to provide insights into how the structure of the storage
mechanism influences the expressiveness and the analyzability of the
resulting model. To this end, it presents generalizations of results about
individual storage mechanisms to larger classes. These generalizations
characterize those storage mechanisms for which the given result remains
true and for which it fails.
In order to speak of classes of storage mechanisms, we need an overarching
framework that accommodates each of the concrete storage mechanisms we wish
to address. Such a framework is provided by the model of valence automata,
in which the storage mechanism is represented by a monoid. Since the monoid
serves as a parameter to specifying the storage mechanism, our aim
translates into the question: For which monoids does the given
(automata-theoretic) result hold?
As a first result, we present an algebraic characterization of those monoids
over which valence automata accept only regular languages. In addition, it
turns out that for each monoid, this is the case if and only if valence
grammars, an analogous grammar model, can generate only context-free
languages.
Furthermore, we are concerned with closure properties: We study which
monoids result in a Boolean closed language class. For every language class
that is closed under rational transductions (in particular, those induced by
valence automata), we show: If the class is Boolean closed and contains any
non-regular language, then it already includes the whole arithmetical
hierarchy.
This work also introduces the class of graph monoids, which are defined by
finite graphs. By choosing appropriate graphs, one can realize a number of
prominent storage mechanisms, but also combinations and variants thereof.
Examples are pushdowns, counters, and Turing tapes. We can therefore relate
the structure of the graphs to computational properties of the resulting
storage mechanisms.
In the case of graph monoids, we study (i) the decidability of the emptiness
problem, (ii) which storage mechanisms guarantee semilinear Parikh images,
(iii) when silent transitions (i.e. those that read no input) can be
avoided, and (iv) which storage mechanisms permit the computation of
downward closures.
These lecture notes give a completely self-contained introduction to the control theory of linear time-invariant systems. No prior knowledge is requried apart from linear algebra and some basic familiarity with ordinary differential equations. Thus, the course is suited for students of mathematics in their second or third year, and for theoretically inclined engineering students. Because of its appealing simplicity and elegance, the behavioral approch has been adopted to a large extend. A short list of recommended text books on the subject has been added, as a suggestion for further reading.
Algebraic Systems Theory
(2004)
Control systems are usually described by differential equations, but their properties of interest are most naturally expressed in terms of the system trajectories, i.e., the set of all solutions to the equations. This is the central idea behind the so-called "behavioral approach" to systems and control theory. On the other hand, the manipulation of linear systems of differential equations can be formalized using algebra, more precisely, module theory and homological methods ("algebraic analysis"). The relationship between modules and systems is very rich, in fact, it is a categorical duality in many cases of practical interest. This leads to algebraic characterizations of structural systems properties such as autonomy, controllability, and observability. The aim of these lecture notes is to investigate this module-system correspondence. Particular emphasis is put on the application areas of one-dimensional rational systems (linear ODE with rational coefficients), and multi-dimensional constant systems (linear PDE with constant coefficients).
In this paper mathematical models for liquid films generated by impinging jets are discussed. Attention is stressed to the interaction of the liquid film with some obstacle. S. G. Taylor [Proc. R. Soc. London Ser. A 253, 313 (1959)] found that the liquid film generated by impinging jets is very sensitive to properties of the wire which was used as an obstacle. The aim of this presentation is to propose a modification of the Taylor's model, which allows to simulate the film shape in cases, when the angle between jets is different from 180°. Numerical results obtained by discussed models give two different shapes of the liquid film similar as in Taylors experiments. These two shapes depend on the regime: either droplets are produced close to the obstacle or not. The difference between two regimes becomes larger if the angle between jets decreases. Existence of such two regimes can be very essential for some applications of impinging jets, if the generated liquid film can have a contact with obstacles.
Continuum Mechanical Modeling of Dry Granular Systems: From Dilute Flow to Solid-Like Behavior
(2014)
In this thesis, we develop a granular hydrodynamic model which covers the three principal regimes observed in granular systems, i.e. the dilute flow, the dense flow and the solid-like regime. We start from a kinetic model valid at low density and extend its validity to the granular solid-like behavior. Analytical and numerical results show that this model reproduces a lot of complex phenomena like for instance slow viscoplastic motion, critical states and the pressure dip in sand piles. Finally we formulate a 1D version of the full model and develop a numerical method to solve it. We present two numerical examples, a filling simulation and the flow on an inclined plane where the three regimes are included.
Granular systems in solid-like state exhibit properties like stiffness
dependence on stress, dilatancy, yield or incremental non-linearity
that can be described within the continuum mechanical framework.
Different constitutive models have been proposed in the literature either based on relations between some components of the stress tensor or on a quasi-elastic description. After a brief description of these
models, the hyperelastic law recently proposed by Jiang and Liu [1]
will be investigated. In this framework, the stress-strain relation is
derived from an elastic strain energy density where the stable proper-
ties are linked to a Drucker-Prager yield criteria. Further, a numerical method based on the finite element discretization and Newton-
Raphson iterations is presented to solve the force balance equation.
The 2D numerical examples presented in this work show that the stress
distributions can be computed not only for triangular domains, as previoulsy done in the literature, but also for more complex geometries.
If the slope of the heap is greater than a critical value, numerical instabilities appear and no elastic solution can be found, as predicted by
the theory. As main result, the dependence of the material parameter
Xi on the maximum angle of repose is established.
Today, information systems are often distributed to achieve high availability and low latency.
These systems can be realized by building on a highly available database to manage the distribution of data.
However, it is well known that high availability and low latency are not compatible with strong consistency guarantees.
For application developers, the lack of strong consistency on the database layer can make it difficult to reason about their programs and ensure that applications work as intended.
We address this problem from the perspective of formal verification.
We present a specification technique, which allows specifying functional properties of the application.
In addition to data invariants, we support history properties.
These let us express relations between events, including invocations of the application API and operations on the database.
To address the verification problem, we have developed a proof technique that handles concurrency using invariants and thereby reduces the problem to sequential verification.
The underlying system semantics, technique and its soundness proof are all formalized in the interactive theorem prover Isabelle/HOL.
Additionally, we have developed a tool named Repliss which uses the proof technique to enable partially automated verification and testing of applications.
For verification, Repliss generates verification conditions via symbolic execution and then uses an SMT solver to discharge them.
Wireless LANs operating within unlicensed frequency bands require random access schemes such as CSMA/ CA, so that wireless networks from different administrative domains (for example wireless community networks) may co-exist without central coordination, even when they happen to operate on the same radio channel. Yet, it is evident that this Jack of coordination leads to an inevitable loss in efficiency due to contention on the MAC layer. The interesting question is, which efficiency may be gained by adding coordination to existing, unrelated wireless networks, for example by self-organization. In this paper, we present a methodology based on a mathematical programming formulation to determine the
parameters (assignment of stations to access points, signal strengths and channel assignment of both access points and stations) for a scenario of co-existing CSMA/ CA-based wireless networks, such that the contention between these networks is minimized. We demonstrate how it is possible to solve this discrete, non-linear optimization problem exactly for small
problems. For larger scenarios, we present a genetic algorithm specifically tuned for finding near-optimal solutions, and compare its results to theoretical lower bounds. Overall, we provide a benchmark on the minimum contention problem for coordination mechanisms in CSMA/CA-based wireless networks.
Fucoidans are multifunctional marine macromolecules that are subjected to numerous and various downstream processes during their production. These processes were considered the most important abiotic factors affecting fucoidan chemical skeletons, quality, physicochemical properties, biological properties and industrial applications. Since a universal protocol for fucoidans production has not been established yet, all the currently used processes were presented and justified. The current article complements our previous articles in the fucoidans field, provides an updated overview regarding the different downstream processes, including pre-treatment, extraction, purification and enzymatic modification processes, and shows the recent non-traditional applications of fucoidans in relation to their characters.
Fucoidan is a class of biopolymers mainly found in brown seaweeds. Due to its diverse medical importance, homogenous supply as well as a GMP-compliant product is of a special interest. Therefore, in addition to optimization of its extraction and purification from classical resources, other techniques were tried (e.g., marine tissue culture and heterologous expression of enzymes involved in its biosynthesis). Results showed that 17.5% (w/w) crude fucoidan after pre-treatment and extraction was obtained from the brown macroalgae F. vesiculosus. Purification by affinity chromatography improved purity relative to the commercial purified product. Furthermore, biological investigations revealed improved anti-coagulant and anti-viral activities compared with crude fucoidan. Furthermore, callus-like and protoplast cultures as well as bioreactor cultivation were developed from F. vesiculosus representing a new horizon to produce fucoidan biotechnologically. Moreover, heterologous expression of several enzymes involved in its biosynthesis by E. coli (e.g., FucTs and STs) demonstrated the possibility to obtain active enzymes that could be utilized in enzymatic in vitro synthesis of fucoidan. All these competitive techniques could provide the global demands from fucoidan.
Background: The positive effect of carbohydrates from commercial beverages on soccer-specific exercise has been clearly demonstrated. However, no study is available that uses a home-mixed beverage in a test where technical skills were required. Methods: Nine subjects participated vol-untarily in this double-blind, randomized, placebo-controlled crossover study. On three testing days, the subjects performed six Hoff tests with a 3-min active break as a preload and then the Yo-Yo Intermittent Running Test Level 1 (Yo-Yo IR1) until exhaustion. On test days 2 and 3, the subjects received either a 69 g carbohydrate-containing drink (syrup–water mixture) or a carbo-hydrate-free drink (aromatic water). Beverages were given in several doses of 250 mL each: 30 min before and immediately before the exercise and after 18 and 39 min of exercise. The primary target parameters were the running performance in the Hoff test and Yo-Yo IR1, body mass and heart rate. Statistical differences between the variables of both conditions were analyzed using paired samples t-tests. Results: The maximum heart rate in Yo-Yo IR1 showed significant differ-ences (syrup: 191.1 ± 6.2 bpm; placebo: 188.0 ± 6.89 bpm; t(6) = −2.556; p = 0.043; dz = 0.97). The running performance in Yo-Yo IR1 under the condition syrup significantly increased by 93.33 ± 84.85 m (0–240 m) on average (p = 0.011). Conclusions: The intake of a syrup–water mixture with a total of 69 g carbohydrates leads to an increase in high-intensive running performance after soccer specific loads. Therefore, the intake of carbohydrate solutions is recommended for intermit-tent loads and should be increasingly considered by coaches and players.
The fifth generation mobile networks (5G) will incorporate novel technologies such as network programmability and virtualization enabled by Software-Defined Networking (SDN) and Network Function Virtualization (NFV) paradigms, which have recently attracted major
interest from both academic and industrial stakeholders.
Building on these concepts, Network Slicing raised as the main driver of a novel business model where mobile operators may open, i.e., “slice”, their infrastructure to new business players and offer independent, isolated and self-contained sets of network functions
and physical/virtual resources tailored to specific services requirements. While Network Slicing has the potential to increase the revenue sources of service providers, it involves a number of technical challenges that must be carefully addressed.
End-to-end (E2E) network slices encompass time and spectrum resources in the radio access network (RAN), transport resources on the fronthauling/backhauling links, and computing and storage resources at core and edge data centers. Additionally, the vertical service requirements’ heterogeneity (e.g., high throughput, low latency, high reliability) exacerbates the need for novel orchestration solutions able to manage end-to-end network slice resources across different domains, while satisfying stringent service level agreements and specific traffic requirements. An end-to-end network slicing orchestration solution shall i) admit network slice requests
such that the overall system revenues are maximized, ii) provide the required resources across different network domains to fulfill the Service Level Agreements (SLAs) iii) dynamically adapt the resource allocation based on the real-time traffic load, endusers’ mobility and instantaneous wireless channel statistics. Certainly, a mobile network represents a fast-changing scenario characterized by complex
spatio-temporal relationship connecting end-users’ traffic demand with social activities and economy. Legacy models that aim at providing dynamic resource allocation based on traditional traffic demand forecasting techniques fail to capture these important aspects.
To close this gap, machine learning-aided solutions are quickly arising as promising technologies to sustain, in a scalable manner, the set of operations required by the network slicing context. How to implement such resource allocation schemes among slices, while
trying to make the most efficient use of the networking resources composing the mobile infrastructure, are key problems underlying the network slicing paradigm, which will be addressed in this thesis.
On the Extended Finite Element Method for the Elasto-Plastic Deformation of Heterogeneous Materials
(2015)
This thesis is concerned with the extended finite element method (XFEM) for deformation analysis of three-dimensional heterogeneous materials. Using the "enhanced abs enrichment" the XFEM is able to reproduce kinks in the displacements and therewith jumps in the strains within elements of the underlying tetrahedral finite element mesh. A complex model for the micro structure reconstruction of aluminum matrix composite AMC225xe and the modeling of its macroscopic thermo-mechanical plastic deformation behavior is presented, using the XFEM. Additionally, a novel stabilization algorithm is introduced for the XFEM. This algorithm requires preprocessing only.
This paper aims to improve the traditional calibration method for reconfigurable self-X (self-calibration, self-healing, self-optimize, etc.) sensor interface readout circuit for industry 4.0. A cost-effective test stimulus is applied to the device under test, and the transient response of the system is analyzed to correlate the circuit's characteristics parameters. Due to complexity in the search and objective space of the smart sensory electronics, a novel experience replay particle swarm optimization (ERPSO) algorithm is being proposed and proved a better-searching capability than some currently well-known PSO algorithms. The newly proposed ERPSO expanded the selection producer of the classical PSO by introducing an experience replay buffer (ERB) intending to reduce the probability of trapping into the local minima. The ERB reflects the archive of previously visited global best particles, while its selection is based upon an adaptive epsilon greedy method in the velocity updating model. The performance of the proposed ERPSO algorithm is verified by using eight different popular benchmarking functions. Furthermore, an extrinsic evaluation of the ERPSO algorithm is also examined on a reconfigurable wide swing indirect current-feedback instrumentation amplifier (CFIA). For the later test, we proposed an efficient optimization procedure by using total harmonic distortion analyses of CFIA output to reduce the total number of measurements and save considerable optimization time and cost. The proposed optimization methodology is roughly 3 times faster than the classical optimization process. The circuit is implemented by using Cadence design tools and CMOS 0.35 µm technology from Austria Microsystems (AMS). The efficiency and robustness are the key features of the proposed methodology toward implementing reliable sensory electronic systems for industry 4.0 applications.
This article proposes a new clock-dependent gain-scheduled dynamic output feedback controller for delayed linear parameter varying systems with piecewise constant parameters. The proposed controller guarantees ℒ2-performance. By employing a clock-dependent Lyapunov–Krasovskii functional, a sufficient condition for the existence of the controller is provided in terms of clock- and parameter-dependent linear matrix inequalities. A case study on output feedback control of delayed switched systems is also provided. To illustrate the efficacy of the result, it is applied to a practical VTOL helicopter model.
In recent years, the concept of a centralized drainage system that connect an entire city to one single treatment plant is increasingly being questioned in terms of the costs, reliability, and environmental impacts. This study introduces an optimization approach based on decentralization in order to develop a cost-effective and sustainable sewage collection system. For this purpose, a new algorithm based on the growing spanning tree algorithm is developed for decentralized layout generation and treatment plant allocation. The trade-off between construction and operation costs, resilience, and the degree of centralization is a multiobjective problem that consists of two subproblems: the layout of the networks and the hydraulic design. The innovative characteristics of the proposed framework are that layout and hydraulic designs are solved simultaneously, three objectives are optimized together, and the entire problem solving process is self-adaptive. The model is then applied to a real case study. The results show that finding an optimum degree of centralization could reduce not only the network’s costs by 17.3%, but could also increase its structural resilience significantly compared to fully centralized networks.
With the technological advancement in the field of robotics, it is now quite practical to acknowledge the actuality of social robots being a part of human's daily life in the next decades. Concerning HRI, the basic expectations from a social robot are to perceive words, emotions, and behaviours, in order to draw several conclusions and adapt its behaviour to realize natural HRI. Henceforth, assessment of human personality traits is essential to bring a sense of appeal and acceptance towards the robot during interaction.
Knowledge of human personality is highly relevant as far as natural and efficient HRI is concerned. The idea is taken from human behaviourism, with humans behaving differently based on the personality trait of the communicating partners. This thesis contributes to the development of personality trait assessment system for intelligent human-robot interaction.
The personality trait assessment system is organized in three separate levels. The first level, known as perceptual level, is responsible for enabling the robot to perceive, recognize and understand human actions in the surrounding environment in order to make sense of the situation. Using psychological concepts and theories, several percepts have been extracted. A study has been conducted to validate the significance of these percepts towards personality traits.
The second level, known as affective level, helps the robot to connect the knowledge acquired in the first level to make higher order evaluations such as assessment of human personality traits. The affective system of the robot is responsible for analysing human personality traits. To the best of our knowledge, this thesis is the first work in the field of human-robot interaction that presents an automatic assessment of human personality traits in real-time using visual information. Using psychology and cognitive studies, many theories has been studied. Two theories have been been used to build the personality trait assessment system: Big Five personality traits assessment and temperament framework for personality traits assessment.
By using the information from the perceptual and affective level, the last level, known as behavioural level, enables the robot to synthesize an appropriate behaviour adapted to human personality traits. Multiple experiments have been conducted with different scenarios. It has been shown that the robot, ROBIN, assesses personality traits correctly during interaction and uses the similarity-attraction principle to behave with similar personality type. For example, if the person is found out to be extrovert, the robot also behaves like an extrovert. However, it also uses the complementary attraction theory to adapt its behaviour and complement the personality of the interaction partner. For example, if the person is found out to be self-centred, the robot behaves like an agreeable in order to flourish human-robot interaction.
The paper focuses on the problem of trajectory planning of flexible redundant robot manipulators (FRM) in joint space. Compared to irredundant flexible manipulators, FRMs present additional possibilities in trajectory planning due to their kinematics redundancy. A trajectory planning method to minimize vibration of FRMs is presented based on Genetic Algorithms (GAs). Kinematics redundancy is integrated into the presented method as a planning variable. Quadrinomial and quintic polynomials are used to describe the segments which connect the initial, intermediate, and final points in joint space. The trajectory planning of FRMs is formulated as a problem of optimization with constraints. A planar FRM with three flexible links is used in simulation. A case study shows that the method is applicable.
Point-to-Point Trajectory Planning of Flexible Redundant Robot Manipulators Using Genetic Algorithms
(2001)
The paper focuses on the problem of point-to-point trajectory planning for flexible redundant robot manipulators (FRM) in joint space. Compared with irredundant flexible manipulators, a FRM possesses additional possibilities during point-to-point trajectory planning due to its kinematics redundancy. A trajectory planning method to minimize vibration and/or executing time of a point-to-point motion is presented for FRM based on Genetic Algorithms (GAs). Kinematics redundancy is integrated into the presented method as planning variables. Quadrinomial and quintic polynomial are used to describe the segments that connect the initial, intermediate, and final points in joint space. The trajectory planning of FRM is formulated as a problem of optimization with constraints. A planar FRM with three flexible links is used in simulation. Case studies show that the method is applicable.
The vibration induced in a deformable object upon automatic handling by robot manipulators can often be bothersome. This paper presents a force/torque sensor-based method for handling deformable linear objects (DLOs) in a manner suitable to eliminate acute vibration. An adjustment-motion that can be attached to the end of an arbitrary end-effector's trajectory is employed to eliminate vibration of deformable objects. Differently from model-based methods, the presented sensor-based method does not employ any information from previous motions. The adjustment-motion is generated automatically by analyzing data from a force/torque sensor mounted on the robot wrist. Template matching technique is used to find out the matching point between the vibrational signal of the DLO and a template. Experiments are conducted to test the new method under various conditions. Results demonstrate the effectiveness of the sensor-based adjustment-motion.
Manipulating Deformable Linear Objects: Attachable Adjustment-Motions for Vibration Reduction
(2001)
This paper addresses the problem of handling deformable linear objects (DLOs) in a suitable way to avoid acute vibration. Different types of adjustment-motions that eliminate vibration of deformable objects and can be attached to the end of an arbitrary end-effector trajectory are presented. For describing the dynamics of deformable linear objects, the finite element method is used to derive the dynamic differential equations. Genetic algorithm is used to find the optimal adjustment motion for each simulation example. Experiments are conducted to verify the presented manipulating method.
Manipulating Deformable Linear Objects: Model-Based Adjustment-Motion for Vibration Reduction
(2001)
This paper addresses the problem of handling deformable linear objects (DLOs) in a suitable way to avoid acute vibration. An adjustment-motion that eliminates vibration of DLOs and can be attached to the end of any arbitrary end-effector's trajectory is presented, based on the concept of open-loop control. The presented adjustment-motion is a kind of agile end-effector motion with limited scope. To describe the dynamics of deformable linear objects, the finite element method is used to derive the dynamic differential equations. Genetic algorithm is used to find the optimal adjustment-motion for each simulation example. In contrast to previous approaches, the presented method can be treated as one of the manipulation skills and can be applied to different cases without major changes to the method.
It is difficult for robots to handle a vibrating deformable object. Even for human beings it is a high-risk operation to, for example, insert a vibrating linear object into a small hole. However, fast manipulation using a robot arm is not just a dream; it may be achieved if some important features of the vibration are detected online. In this paper, we present an approach for fast manipulation using a force/torque sensor mounted on the robot's wrist. Template matching method is employed to recognize the vibrational phase of the deformable objects. Therefore, a fast manipulation can be performed with a high success rate, even if there is acute vibration. Experiments inserting a deformable object into a hole are conducted to test the presented method. Results demonstrate that the presented sensor-based online fast manipulation is feasible.
This thesis focuses on novel methods to establish the utility of wearable devices along with machine learning and pattern recognition methods for formal education and address the open research questions posed by existing methods. Firstly, state-of-the-art methods are proposed to analyse the cognitive activities in the learning process, i.e., reading, writing, and their correlation. Furthermore, this thesis presents real-time applications in wearable space as an experimental tool in Physics education, and an air-writing system.
There are two critical components in analysing the reading behaviour, i.e., WHERE a person looks at (gaze analysis) and WHAT a person looks at (content analysis). This thesis proposes novel methods to classify the reading content to address the WHAT AT component. The proposed methods are based on a hybrid approach, which fuses the traditional computer vision methods with deep neural networks. These methods, when evaluated on publicly available datasets, yield state-of-the-art results to define the structure of the document images. Moreover, extensive efforts were made to refine and correct ICDAR2017-POD dataset along with a completely new FFD dataset.
Traditionally, handwriting research focuses on character and number recognition without looking into the type of writing, i.e. text, math, and drawing. This thesis reports multiple contributions for on-line handwriting classification. First, it presents a public dataset for on-line handwriting classification OnTabWriter, collected using iPen and an iPad. In addition, a new feature set is introduced for on-line handwriting classification to establish the benchmark on the proposed dataset to classify handwriting as plain text, mathematical expression, and plot/graph. An ablation study is made to evaluate the performance of the proposed feature set in comparison to existing feature sets. Lastly, this thesis evaluates the importance of context for on-line handwriting classification.
Analysing reading and writing activities individually is not enough to provide insights to identify the student's expertise unless their correlations are analysed. This thesis presents a study where reading data from wearable eye-trackers and writing data from sensor pen are analysed together in correlation to correlate the expertise of the users in Physics education with their actual knowledge. Initial results show a strong correlation between individual's expertise and understanding of the subject.
Augmented reality & virtual applications can play a vital role in making classroom environments more interactive and engaging both for teachers and learners. To validate the hypothesis, different applications are developed and evaluated. First, smart glasses are used as an experimental tool in Physics education to help the learners perform experiments by providing assistance and feedback on head mounted display in understanding acoustics concepts. Second, a real-time application of air-writing with the finger on an imaginary canvas using a single IMU as the FAirWrite system is also presented. FAirWrite system is further equipped with DL methods to classify the air-written characters.
This master thesis presents a collection of architectural design patterns for safety-critical systems deployed on public cloud infrastructure. The research aims to enhance system reliability, mitigate risks, and improve overall performance in safety-critical applications. The study follows a systematic approach, considering multiple safety-critical use cases and prioritizing factors such as timing constraints and system resilience. The railway signaling system, particularly the moving block computation, is selected as the most suitable use case due to its ability to tolerate response delays and re-request computations. The thesis addresses four research questions concerning the deployment of safety-critical systems to the public cloud, existing fault-tolerance methods in the cloud, identification of relevant design patterns, and the applicability of design patterns in various safety-critical systems.
The study identifies and review's fault tolerance methods and cloud failure modes, which serve as a basis for identifying design patterns. The Structured What-If Technique (SWIFT) is utilized to analyze prospective hazards and recommend actions, which are then mapped onto design patterns for wide applicability across different projects. Each design pattern presents a problem statement, guidelines for implementation, and associated benefits and drawbacks.
The contribution of this thesis lies in the development of a valuable resource for architects and engineers working on safety-critical systems in the cloud. The design patterns offer practical solutions and a framework for the design and implementation of robust and secure systems. Detailed documentation, including context, benefits, drawbacks, and practical examples, facilitates understanding and adoption.
In conclusion, this thesis contributes to the advancement of safety and reliability in cloud-based safety-critical systems by providing architectural design patterns. Future research should focus on integrating security aspects, gathering diverse use cases, and validating the patterns in practical settings. Continued exploration and refinement of the design patterns will lead to more robust solutions for meeting the needs and challenges of safety-critical applications in various contexts.
As a consequence of the real estate market crash after 2008, large investors invested a significant amount of wealth into single-family houses to construct a portfolio of rental dwellings, whose income is securitized in the capital. In some local housing markets, these investors own remarkable numbers of single-family houses. Furthermore, their trading activities have resulted in a new investment strategy, which exacerbates property wealth concentration and polarization. This new investment strategy and its portfolio optimization inspire curiosity about its influence on housing markets. This paper first aims to find an optimal portfolio strategy by employing an expected utility optimization from the terminal wealth, which adopts a stochastic model that includes a variety of economic states to estimate house prices. Second, it aims to analyze the effect of large investors on the housing market. The results show the investment strategies of large investors depend on the balance among economic state, maintenance cost, rental income, interest rate and investment willingness of large investors to housing and their effect depends on the state of the economy.
Load modeling is one of the crucial tasks for improving smart grids’ energy efficiency. Among many alternatives, machine learning-based load models have become popular in applications and have shown outstanding performance in recent years. The performance of these models highly relies on data quality and quantity available for training. However, gathering a sufficient amount of high-quality data is time-consuming and extremely expensive. In the last decade, Generative Adversarial Networks (GANs) have demonstrated their potential to solve the data shortage problem by generating synthetic data by learning from recorded/empirical data. Educated synthetic datasets can reduce prediction error of electricity consumption when combined with empirical data. Further, they can be used to enhance risk management calculations. Therefore, we propose RCGAN, TimeGAN, CWGAN, and RCWGAN which take individual electricity consumption data as input to provide synthetic data in this study. Our work focuses on one dimensional times series, and numerical experiments on an empirical dataset show that GANs are indeed able to generate synthetic data with realistic appearance.
Recent studies on the environmental performance of additive manufacturing (AM) have shown that AM exhibits both complex potentials and challenges at different life stages compared to conventional manufacturing. To assess and ensure the environmental benefits of AM during the design phase, an eco-design approach is required. Existing eco-design for AM approaches described in the literature mainly focus on the use of lifecycle assessment (LCA) to analyze the environmental impacts of AM-specific design solutions. However, since LCA requires a full-process chain model and detailed inventory data, it can only be performed after the design process or in a subsequent design stage. To integrate evaluation activities into the middle stage of the design process, energy performance assessment can be used as an alternative evaluation tool in eco-design for AM. However, the literature still lacks an eco-design for AM method based on energy performance quantification and assessment. By addressing this research problem, this dissertation contributes to the development of a holistic framework to implement eco-design for AM using energy performance assessment. This framework consists of the following three parts: a simulation tool for energy prediction in the design phase; an energy performance assessment model for AM; and a method for carrying out activities in eco-design for AM. To demonstrate the feasibility of the proposed method, three use cases are performed. Based on these use cases, it is concluded that with the use of the proposed method, AM designers will be able to select and develop optimal design solutions based on the energy performance of AM in the middle design stage.
Distributed Optimization of Constraint-Coupled Systems via Approximations of the Dual Function
(2024)
This thesis deals with the distributed optimization of constraint-coupled systems. This problem class is often encountered in systems consisting of multiple individual subsystems, which are coupled through shared limited resources. The goal is to optimize each subsystem in a distributed manner while still ensuring that system-wide constraints are satisfied. By introducing dual variables for the system-wide constraints the system-wide problem can be decomposed into individual subproblems. These resulting subproblems can then be coordinated by iteratively adapting the dual variables. This thesis presents two new algorithms that exploit the properties of the dual optimization problem. Both algorithms compute a quadratic surrogate function of the dual function in each iteration, which is optimized to adapt the dual variables. The Quadratically Approximated Dual Ascent (QADA) algorithm computes the surrogate function by solving a regression problem, while the Quasi-Newton Dual Ascent (QNDA) algorithm updates the surrogate function iteratively via a quasi-Newton scheme. Both algorithms employ cutting planes to take the nonsmoothness of the dual function into account. The proposed algorithms are compared to algorithms from the literature on a large number of different benchmark problems, showing superior performance in most cases. In addition to general convex and mixed-integer optimization problems, dual decomposition-based distributed optimization is applied to distributed model predictive control and distributed K-means clustering problems.
Machining is very common in industry, e.g. automotive industry and aerospace industry, which is a nonlinear dynamic problem including large deformations, large strain, large strain rates and high temperatures, that implies some difficulties for numerical methods such as Finite element method. One way to simulate such kind of problems is the Particle Finite Element Method (PFEM) which combines the advantages of continuum mechanics and discrete modeling techniques. In this work we introduce an improved PFEM called the Adaptive Particle Finite Element Method (A-PFEM). The A-PFEM introduces particles and removes wrong elements along the numerical simulation to improve accuracy, precision, decrease computing time and resolve the phenomena that take place in machining in multiple scales. At the end of this paper, some examples are present to show the performance of the A-PFEM.
Abstract: We present experimental and theoretical results of a detailed study of laser-induced continuum structures (LICS) in the photoionization continuum of helium out of the metastable state 2s^1 S_0. The continuum dressing with a 1064 nm laser, couples the same region of the continuum to the 4s^1 S_0 state. The experimental data, presented for a range of intensities, show pronounced ionization suppression (by asmuch as 70% with respect to the far-from-resonance value) as well as enhancement, in a Beutler-Fano resonance profile. This ionization suppression is a clear indication of population trapping mediated by coupling to a contiuum. We present experimental results demonstrating the effect of pulse delay upon the LICS, and for the behavior of LICS for both weak and strong probe pulses. Simulations based upon numerical solution of the Schrödinger equation model the experimental results. The atomic parameters (Rabi frequencies and Stark shifts) are calculated using a simple model-potential method for the computation of the needed wavefunctions. The simulations of the LICS profiles are in excellent agreement with experiment. We also present an analytic formulation of pulsed LICS. We show that in the case of a probe pulse shorter than the dressing one the LICS profile is the convolution of the power spectra of the probe pulse with the usual Fano profile of stationary LICS. We discuss some consequences of deviation from steady-state theory.
This work introduces a promising concept for the preparation of new nano-sized receptors. Mixed monolayer protected gold nanoparticles (AuNPs) for low molecular weight compounds were prepared featuring functional groups on their surfaces. It has been shown that these AuNPs can engage in interactions with peptides in aqueous media. Quantitative binding information was obtained from DOSY-NMR titrations indicating that nanoparticles containing a combination of three orthogonal functional groups are more efficient in binding to dipeptides than mono or difunctionalised analogues. The strategy is highly modular and easily allows adapting the receptor selectivity to a
given substrate by varying the type, number, and ratio of binding sites on the nanoparticle
surface.
The safety of embedded systems is becoming more and more important nowadays. Fault Tree Analysis (FTA) is a widely used technique for analyzing the safety of embedded systems. A standardized tree-like structure called a Fault Tree (FT) models the failures of the systems. The Component Fault Tree (CFT) provides an advanced modeling concept for adapting the traditional FTs to the hierarchical architecture model in system design. Minimal Cut Set (MCS) analysis is a method that works for qualitative analysis based on the FTs. Each MCS represents a minimal combination of component failures of a system called basic events, which may together cause the top-level system failure. The ordinary representations of MCSs consist of plain text and data tables with little additional supporting visual and interactive information. Importance analysis based on FTs or CFTs estimates the contribution of each potential basic event to a top-level system failure. The resulting importance values of basic events are typically represented in summary views, e.g., data tables and histograms. There is little visual integration between these forms and the FT (or CFT) structure. The safety of a system can be improved using an iterative process, called the safety improvement process, based on FTs taking relevant constraints into account, e.g., cost. Typically, relevant data regarding the safety improvement process are presented across multiple views with few interactive associations. In short, the ordinary representation concepts cannot effectively facilitate these analyses.
We propose a set of visualization approaches for addressing the issues above mentioned in order to facilitate those analyses in terms of the representations.
Contribution:
1. To support the MCS analysis, we propose a matrix-based visualization that allows detailed data of the MCSs of interest to be viewed while maintaining a satisfactory overview of a large number of MCSs for effective navigation and pattern analysis. Engineers can also intuitively analyze the influence of MCSs of a CFT.
2. To facilitate the importance analysis based on the CFT, we propose a hybrid visualization approach that combines the icicle-layout-style architectural views with the CFT structure. This approach facilitates to identify the vulnerable components taking the hierarchies of system architecture into account and investigate the logical failure propagation of the important basic events.
3. We propose a visual safety improvement process that integrates an enhanced decision tree with a scatter plot. This approach allows one to visually investigate the detailed data related to individual steps of the process while maintaining the overview of the process. The approach facilitates to construct and analyze improvement solutions of the safety of a system.
Using our visualization approaches, the MCS analysis, the importance analysis, and the safety improvement process based on the CFT can be facilitated.
The noise issue in manufacturing system is widely discussed from legal and health aspects. Regarding the existing laws and guidelines, various investigation methods are implemented in industry. The sound pressure level can be measured and reduced by using established approaches in reality. However, a straightforward and low cost approach to study noise issue using existing digital factory models is not found.
This thesis attempts to develop a novel concept for sound pressure level investigation in a virtual environment. With this, the factory planners are able to investigate the noise issue during factory design and layout planning phase.
Two computer aided tools are used in this approach: acoustic simulation and virtual reality (VR). The former enables the planner to simulate the sound pressure level by given factory layout and facility sound features. And the latter provides a visualization environment to view and explore the simulation results. The combination of these two powerful tools provides the planners a new possibility to analyze the noise in a factory.
To validate the simulations, the acoustic measurements are implemented in a real factory. Sound pressure level and sound intensity are determined respectively. Furthermore, a software tool is implemented using the introduced concept and approach. With this software, the simulation results are represented in a Cave Automatic Virtual Environment (CAVE).
This thesis describes the development of the approach, the measurement of sound features, the design of visualization framework, and the implementation of VR software. Based on this know-how, the industry users are able to design their own method and software for noise investigation and analysis.
The broad engineering applications of polymers and composites have become the
state of the art due to their numerous advantages over metals and alloys, such as
lightweight, easy processing and manufacturing, as well as acceptable mechanical
properties. However, a general deficiency of thermoplastics is their relatively poor
creep resistance, impairing service durability and safety, which is a significant barrier
to further their potential applications. In recent years, polymer nanocomposites have
been increasingly focused as a novel field in materials science. There are still many
scientific questions concerning these materials leading to the optimal property
combinations. The major task of the current work is to study the improved creep
resistance of thermoplastics filled with various nanoparticles and multi-walled carbon
nanotubes.
A systematic study of three different nanocomposite systems by means of
experimental observation and modeling and prediction was carried out. In the first
part, a nanoparticle/PA system was prepared to undergo creep tests under different
stress levels (20, 30, 40 MPa) at various temperatures (23, 50, 80 °C). The aim was
to understand the effect of different nanoparticles on creep performance. 1 vol. % of
300 nm and 21 nm TiO2 nanoparticles and nanoclay was considered. Surface
modified 21 nm TiO2 particles were also investigated. Static tensile tests were
conducted at those temperatures accordingly. It was found that creep resistance was
significantly enhanced to different degrees by the nanoparticles, without sacrificing
static tensile properties. Creep was characterized by isochronous stress-strain curves,
creep rate, and creep compliance under different temperatures and stress levels.
Orientational hardening, as well as thermally and stress activated processes were
briefly introduced to further understanding of the creep mechanisms of these
nanocomposites. The second material system was PP filled with 1 vol. % 300 nm and 21 nm TiO2
nanoparticles, which was used to obtain more information about the effect of particle
size on creep behavior based on another matrix material with much lower Tg. It was
found especially that small nanoparticles could significantly improve creep resistance.
Additionally, creep lifetime under high stress levels was noticeably extended by
smaller nanoparticles. The improvement in creep resistance was attributed to a very
dense network formed by the small particles that effectively restricted the mobility of
polymer chains. Changes in the spherulite morphology and crystallinity in specimens
before and after creep tests confirmed this explanation.
In the third material system, the objective was to explore the creep behavior of PP
reinforced with multi-walled carbon nanotubes. Short and long aspect ratio nanotubes
with 1 vol. % were used. It was found that nanotubes markedly improved the creep
resistance of the matrix, with reduced creep deformation and rate. In addition, the
creep lifetime of the composites was dramatically extended by 1,000 % at elevated
temperatures. This enhancement contributed to efficient load transfer between
carbon nanotubes and surrounding polymer chains.
Finally, a modeling analysis and prediction of long-term creep behaviors presented a
comprehensive understanding of creep in the materials studied here. Both the
Burgers model and Findley power law were applied to satisfactorily simulate the
experimental data. The parameter analysis based on Burgers model provided an
explanation of structure-to-property relationships. Due to their intrinsic difference, the
power law was more capable of predicting long-term behaviors than Burgers model.
The time-temperature-stress superposition principle was adopted to predict long-term
creep performance based on the short-term experimental data, to make it possible to
forecast the future performance of materials.
Radiotherapy is one of the major forms in cancer treatment. The patient is irradiated with high-energetic photons or charged particles with the primary goal of delivering sufficiently high doses to the tumor tissue while simultaneously sparing the surrounding healthy tissue. The inverse search for the treatment plan giving the desired dose distribution is done by means of numerical optimization [11, Chapters 3-5]. For this purpose, the aspects of dose quality in the tissue are modeled as criterion functions, whose mathematical properties also affect the type of the corresponding optimization problem. Clinical practice makes frequent use of criteria that incorporate volumetric and spatial information about the shape of the dose distribution. The resulting optimization problems are of global type by empirical knowledge and typically computed with generic global solver concepts, see for example [16]. The development of good global solvers to compute radiotherapy optimization problems is an important topic of research in this application, however, the structural properties of the underlying criterion functions are typically not taken into account in this context.
Recently, phase field modeling of fatigue fracture has gained a lot of attention from many researches and studies, since the fatigue damage of structures is a crucial issue in mechanical design. Differing from traditional phase field fracture models, our approach considers not only the elastic strain energy and crack surface energy, additionally, we introduce a fatigue energy contribution into the regularized energy density function caused by cyclic load. Comparing to other type of fracture phenomenon, fatigue damage occurs only after a large number of load cycles. It requires a large computing effort in a computer simulation. Furthermore, the choice of the cycle number increment is usually determined by a compromise between simulation time and accuracy. In this work, we propose an efficient phase field method for cyclic fatigue propagation that only requires moderate computational cost without sacrificing accuracy. We divide the entire fatigue fracture simulation into three stages and apply different cycle number increments in each damage stage. The basic concept of the algorithm is to associate the cycle number increment with the damage increment of each simulation iteration. Numerical examples show that our method can effectively predict the phenomenon of fatigue crack growth and reproduce fracture patterns.
In the last decades, the phase field method has drawn much attention for its application in fracture mechanics because it offers a simple unified framework for crack propagation. The core idea of phase field models for fracture is to introduce a continuous scalar field representing the discontinuous crack. Recently, a phase field model for fatigue has been proposed along this path. The fatigue failure differs from the other fracture scenarios since cracks only occur after a considerable number of load cycles. As fracturing happens, changes of the material microstructure are involved, which causes the evolution of the structural configuration. Thus, a new mathematical description not based on traditional spatial coordinates but the material manifold is desired, which will serve as an elegant analysis tool to understand the energetic forces for crack propagation. Configurational forces are a suitable choice for this purpose, as they describe the energetic driving forces associated with phenomena changing the material itself. In this work, we present a phase field model for fatigue. Furthermore, the phase field fatigue model is analyzed within the concept of configurational forces, which provides a straightforward way to understand the phase field simulations of fatigue fracture.
Phospho-regulation of the Shugoshin - Condensin interaction at the centromere in budding yeast
(2020)
Correct bioriented attachment of sister chromatids to the mitotic spindle is essential for chromosome segregation. In budding yeast, the conserved protein shugoshin (Sgo1) contributes to biorientation by recruiting the protein phosphatase PP2A-Rts1 and the condensin complex to centromeres. Using peptide prints, we identified a Serine-Rich Motif (SRM) of Sgo1 that mediates the interaction with condensin and is essential for centromeric condensin recruitment and the establishment of biorientation. We show that the interaction is regulated via phosphorylation within the SRM and we determined the phospho-sites using mass spectrometry. Analysis of the phosphomimic and phosphoresistant mutants revealed that SRM phosphorylation disrupts the shugoshin–condensin interaction. We present evidence that Mps1, a central kinase in the spindle assembly checkpoint, directly phosphorylates Sgo1 within the SRM to regulate the interaction with condensin and thereby condensin localization to centromeres. Our findings identify novel mechanisms that control shugoshin activity at the centromere in budding yeast.
Estimation and Portfolio Optimization with Expert Opinions in Discrete-time Financial Markets
(2021)
In this thesis, we mainly discuss the problem of parameter estimation and
portfolio optimization with partial information in discrete-time. In the portfolio optimization problem, we specifically aim at maximizing the utility of
terminal wealth. We focus on the logarithmic and power utility functions. We consider expert opinions as another observation in addition to stock returns to improve estimation of drift and volatility parameters at different times and for the purpose of asset optimization.
In the first part, we assume that the drift term has a fixed distribution, and
the volatility term is constant. We use the Kalman filter to combine the two
types of observations. Moreover, we discuss how to transform this problem
into a non-linear problem of Gaussian noise when the expert opinion is uniformly distributed. The generalized Kalman filter is used to estimate the parameters in this problem.
In the second part, we assume that drift and volatility of asset returns are both driven by a Markov chain. We mainly use the change-of-measure technique to estimate various values required by the EM algorithm. In addition,
we focus on different ways to combine the two observations, expert opinions and asset returns. First, we use the linear combination method. At the same time, we discuss how to use a logistic regression model to quantify expert
opinions. Second, we consider that expert opinions follow a mixed Dirichlet distribution. Under this assumption, we use another probability measure to
estimate the unnormalized filters, needed for the EM algorithm.
In the third part, we assume that expert opinions follow a mixed Dirichlet distribution and focus on how we can obtain approximate optimal portfolio
strategies in different observation settings. We claim the approximate strategies from the dynamic programming equations in different settings and analyze the dependence on the discretization step. Finally we compute different
observation settings in a simulation study.
Elastomers and their various composites, and blends are frequently used as engineering working parts subjected to rolling friction movements. This fact already substantiates the importance of a study addressing the rolling tribological properties of elastomers and their compounds. It is worth noting that until now the research and development works on the friction and wear of rubber materials were mostly focused on abrasion and to lesser extent on sliding type of loading. As the tribological knowledge acquired with various counterparts, excluding rubbers, can hardly be adopted for those with rubbers, there is a substantial need to study the latter. Therefore, the present work was aimed at investigating the rolling friction and wear properties of different kinds of elastomers against steel under unlubricated condition. In the research the rolling friction and wear properties of various rubber materials were studied in home-made rolling ball-on-plate test configurations under dry condition. The materials inspected were ethylene/propylene/diene rubber (EPDM) without and with carbon black (EPDM_CB), hydrogenated acrylonitrile/butadiene rubber (HNBR) without and with carbon black/silica/multiwall carbon nanotube (HNBR_CB/silica/MWCNT), rubber-rubber hybrid (HNBR and fluororubber (HNBR-FKM)) and rubber-thermoplastic blend (HNBR and cyclic butylene terephthalate oligomers (HNBR-CBT)). The dominant wear mechanisms were investigated by scanning electron microscopy (SEM), and analyzed as a function of composition and testing conditions. Differential scanning calorimetry (DSC), dynamic-mechanical thermal analysis (DMTA), atomic force microscopy (AFM), and transmission electron microscopy (TEM) along with other auxiliary measurements, were adopted to determine the phase structure and network-related properties of the rubber systems. The changes of the friction and wear as a function of type and amount of the additives were explored. The friction process of selected rubbers was also modelled by making use of the finite element method (FEM). The results show that incorporation of filler enhanced generally the wear resistance, hardness, stiffness (storage modulus), and apparent crosslinking of the related rubbers (EPDM-, HNBR- and HNBR-FKM based ones), but did not affect their glass transition temperature. Filling of rubbers usually reduced the coefficient of friction (COF). However, the tribological parameters strongly depended also on the test set-up and test duration. High wear loss was noticed for systems showing the occurrence of Schallamach-type wavy pattern. The blends HNBR-FKM and HNBR-CBT were two-phase structured. In HNBR-FKM, the FKM was dispersed in form of large microscaled domains in the HNBR matrix. This phase structure did not change by incorporation of MWCNT. It was established that the MWCNT was preferentially embedded in the HNBR matrix. Blending HNBR with FKM reduced the stiffness and degree of apparent crosslinking of the blend, which was traced to the dilution of the cure recipe with FKM. The coefficient of friction increased with increasing FKM opposed to the expectation. On the other hand, the specific wear rate (Ws) changed marginally with increasing content of FKM. In HNBR-CBT hybrids the HNBR was the matrix, irrespective to the rather high CBT content. Both the partly and mostly polymerized CBT ((p)CBT and pCBT, respectively) in the hybrids worked as active filler and thus increased the stiffness and hardness. The COF and Ws decreased with increasing CBT content. The FEM results in respect to COF achieved on systems possessing very different structures and thus properties (EPDM_30CB, HNBR-FKM 100-100 and HNBR-(p)CBT 100-100, respectively) were in accordance with the experimental results. This verifies that FEM can be properly used to consider the complex viscoelastic behaviour of rubber materials under dry rolling condition.
Indoor positioning system (IPS) is becoming more and more popular in recent years in industrial, scientific and medical areas. The rapidly growing demand of accurate position information attracts much attention and effort in developing various kinds of positioning systems that are characterized by parameters like accuracy,robustness,
latency, cost, etc. These systems have been successfully used in many applications such as automation in manufacturing, patient tracking in hospital, action detection for human-machine interacting and so on.
The different performance requirements in various applications lead to existence of greatly diverse technologies, which can be categorized into two groups: inertial positioning(involving momentum sensors embedded on the object device to be located) and external sensing (geometry estimation based on signal measurement). In positioning
systems based on external sensing, the input signal used for locating refers to many sources, such as visual or infrared signal in optical methods, sound or ultra-sound in acoustic methods and radio frequency based methods. This dissertation gives a recapitulative survey of a number of existence popular solutions for indoor positioning systems. Basic principles of individual technologies are demonstrated and discussed. By comparing the performances like accuracy, robustness, cost, etc., a comprehensive review of the properties of each technologies is presented, which concludes a guidance for designing a location sensing systems for indoor applications. This thesis will lately focus on presenting the development of a high precision IPS
prototype system based on RF signal from the concept aspect to the implementation up to evaluation. Developing phases related to this work include positioning scenario, involved technologies, hardware development, algorithms development, firmware generation, prototype evaluation, etc.. The developed prototype is a narrow band RF system, and it is suitable for a flexible frequency selection in UHF (300MHz3GHz) and SHF (3GHz30GHz) bands, enabling this technology to meet broad service preferences. The fundamental of the proposed system classified itself as a hyperbolic position fix system, which estimates a location by solving non-linear equations derived from time difference of arrival (TDoA) measurements. As the positioning accuracy largely depends on the temporal resolution of the signal acquisition, a dedicated RF front-end system is developed to achieve a time resolution in range of multiple picoseconds down to less than 1 pico second. On the algorithms aspect, two processing units: TDoA estimator and the Hyperbolic equations solver construct the digital signal processing system. In order to implement a real-time positioning system, the processing system is implemented on a FPGA platform. Corresponding firmware is generated from the algorithms modeled in MATLAB/Simulink, using the high level synthesis (HLS) tool HDL Coder. The prototype system is evaluated and an accuracy of better than 1 cm is achieved. A better performance is potential feasible by manipulating some of the controlling conditions such as ADC sampling rate, ADC resolution, interpolation process, higher frequency, more stable antenna, etc. Although the proposed system is initially dedicated to indoor applications, it could also be a competitive candidate for an outdoor positioning service.
Global trends such as climate change and the scarcity of sustainable raw materials require adaptive, more flexible and resource-saving wastewater infrastructures for rural areas. Since 2018, in the community Reinighof, an isolated site in the countryside of Rhineland Palatinate (Germany), an autarkic, decentralized wastewater treatment and phosphorus recovery concept has been developed, implemented and tested. While feces are composted, an easy-to-operate system for producing struvite as a mineral fertilizer was developed and installed to recover phosphorus from urine. The nitrogen-containing supernatant of this process stage is treated in a special soil filter and afterwards discharged to a constructed wetland for grey water treatment, followed by an evaporation pond. To recover more than 90% of the phosphorus contained in the urine, the influence of the magnesium source, the dosing strategy, the molar ratio of Mg:P and the reaction and sedimentation time were investigated. The results show that, with a long reaction time of 1.5 h and a molar ratio of Mg:P above 1.3, constraints concerning magnesium source can be overcome and a stable process can be achieved even under varying boundary conditions. Within the special soil filter, the high ammonium nitrogen concentrations of over 3000 mg/L in the supernatant of the struvite reactor were considerably reduced. In the effluent of the following constructed wetland for grey water treatment, the ammonium-nitrogen concentrations were below 1 mg/L. This resource efficient decentralized wastewater treatment is self-sufficient, produces valuable fertilizer and does not need a centralized wastewater system as back up. It has high potential to be transferred to other rural communities.
This paper discusses the problem of automatic off-line programming and motion planning for industrial robots. At first, a new concept consisting of three steps is proposed. The first step, a new method for on-line motion planning is introduced. The motion planning method is based on the A*-search algorithm and works in the implicit configuration space. During searching, the collisions are detected in the explicitly represented Cartesian workspace by hierarchical distance computation. In the second step, the trajectory planner has to transform the path into a time and energy optimal robot program. The practical application of these two steps strongly depends on the method for robot calibration with high accuracy, thus, mapping the virtual world onto the real world, which is discussed in the third step.
This paper presents a new approach to parallel motion planning for industrial robot arms with six degrees of freedom in an on-line given 3D environment. The method is based on the A-search algorithm and needs no essential off-line computations. The algorithm works in an implicitly descrete configuration space. Collisions are detected in the Cartesian workspace by hierarchical distance computation based on the given CAD model. By decomposing the 6D configuration space into hypercubes and cyclically mapping them onto multiple processing units, a good load distribution can be achieved. We have implemented the parallel motion planner on a workstation cluster with 9 PCs and tested the planner for several benchmark environments. With optimal discretisation, the new approach usually shows linear speedups. In on-line provided environments with static obstacles, the parallel planning times are only a few seconds.
A practical distributed planning and control system for industrial robots is presented. The hierarchical concept consists of three independent levels. Each level is modularly implemented and supplies an application interface (API) to the next higher level. At the top level, we propose an automatic motion planner. The motion planner is based on a best-first search algorithm and needs no essential off-line computations. At the middle level, we propose a PC-based robot control architecture, which can easily be adapted to any industrial kinematics and application. Based on a client/server-principle, the control unit estab-lishes an open user interface for including application specific programs. At the bottom level, we propose a flexible and modular concept for the integration of the distributed motion control units based on the CAN bus. The concept allows an on-line adaptation of the control parameters according to the robot's configuration. This implies high accuracy for the path execution and improves the overall system performance.
This paper presents a new approach to parallel motion planning for industrial robot arms with six degrees of freedom in an on-line given 3D environment. The method is based on the A*-search algorithm and needs no essential off-line computations. The algorithm works in an implicitly descrete configuration space. Collisions are detected in the cartesian workspace by hierarchical distance computation based on the given CAD model. By decomposing the 6D configuration space into hypercubes and cyclically mapping them onto multiple processing units, a good load distribution can be achieved. We have implemented the parallel motion planner on a workstation cluster with 9 PCs and tested the planner for several benchmark environments. With optimal discretisation, the new approach usually shows linear, and sometimes even superlinear speedups. In on-line provided environments with static obstacles, the parallel planning times are only a few seconds.
A new problem for the automated off-line programming of industrial robot application is investigated. The Multi-Goal Path Planning is to find the collision-free path connecting a set of goal poses and minimizing e.g. the total path length. Our solution is based on an earlier reported path planner for industrial robot arms with 6 degrees-of-freedom in an on-line given 3D environment. To control the path planner, four different goal selection methods are introduced and compared. While the Random and the Nearest Pair Selection methods can be used with any path planner, the Nearest Goal and the Adaptive Pair Selection method are favorable for our planner. With the latter two goal selection methods, the Multi-Goal Path Planning task can be significantly accelerated, because they are able to automatically solve the simplest path planning problems first. Summarizing, compared to Random or Nearest Pair Selection, this new Multi-Goal Path Planning approach results in a further cost reduction of the programming phase.
This article presents contributions in the field of path planning for industrial robots with 6 degrees of freedom. This work presents the results of our research in the last 4 years at the Institute for Process Control and Robotics at the University of Karlsruhe. The path planning approach we present works in an implicit and discretized C-space. Collisions are detected in the Cartesian workspace by a hierarchical distance computation. The method is based on the A* search algorithm and needs no essential off-line computation. A new optimal discretization method leads to smaller search spaces, thus speeding up the planning. For a further acceleration, the search was parallelized. With a static load distribution good speedups can be achieved. By extending the algorithm to a bidirectional search, the planner is able to automatically select the easier search direction. The new dynamic switching of start and goal leads finally to the multi-goal path planning, which is able to compute a collision-free path between a set of goal poses (e.g., spot welding points) while minimizing the total path length.
The objective of this thesis consists in developing systematic event-triggered control designs for specified event generators, which is an important alternative to the traditional periodic sampling control. Sporadic sampling inherently arising in event-triggered control is determined by the event-triggering conditions. This feature invokes the desire of
finding new control theory as the traditional sampled-data theory in computer control.
Developing controller coupling with the applied event-triggering condition to maximize the control performance is the essence for event-triggered control design. In the design the stability of the control system needs to be ensured with the first priority. Concerning variant control aims they should be clearly incorporated in the design procedures. Considering applications in embedded control systems efficient implementation requires a low complexity of embedded software architectures. The thesis targets at offering such a design to further complete the theory of event-triggered control designs.
An interrupter for use in a daisy-chained VME bus interrupt system has beendesigned and implemented as an asynchronous sequential circuit. The concur-rency of the processes posed a design problem that was solved by means of asystematic design procedure that uses Petri nets for specifying system and in-terrupter behaviour, and for deriving a primitive flow table. Classical designand additional measures to cope with non-fundamental mode operation yieldeda coded state-machine representation. This was implemented on a GAL 22V10,chosen for its hazard-preventing structure and for rapid prototyping in studentlaboratories.
In response priming experiments, a participant has to respond as quickly and as accurately as possible to a target stimulus preceded by a prime. The prime and the target can either be mapped to the same response (consistent trial) or to different responses (inconsistent trial). Here, we investigate the effects of two sequential primes (each one either consistent or inconsistent) followed by one target in a response priming experiment. We employ discrete-time hazard functions of response occurrence and conditional accuracy functions to explore the temporal dynamics of sequential motor activation. In two experiments (small-N design, 12 participants, 100 trials per cell and subject), we find that (1) the earliest responses are controlled exclusively by the first prime if primes are presented in quick succession, (2) intermediate responses reflect competition between primes, with the second prime increasingly dominating the response as its time of onset is moved forward, and (3) only the slowest responses are clearly controlled by the target. The current study provides evidence that sequential primes meet strict criteria for sequential response activation. Moreover, it suggests that primes can influence responses out of a memory buffer when they are presented so early that participants are forced to delay their responses.
Agricultural intensification has increased substantially in the last century to meet the globally growing demand for food, fodder, and bioenergy, thus agricultural cropland became the largest terrestrial biome globally. Pesticides became a central tool to this intensification strategy, thus pesticide application rose drastically over the last sixty years to secure or increase crop yields. However, pesticides are by design biologically active and known to contaminate non-target ecosystems, thereby adversely affecting their function or structure. Even though ecotoxicological knowledge about probable fate and effects has grown, little remains known about the spatiotemporal occurrence, potential effects, and risk drivers of pesticides on larger, i.e. macro, scales.
Consequently, the thesis gathered primarily pesticide exposure data via meta-analysis and from public monitoring databases to describe (i) detailed risks in aquatic ecosystems, (ii) the underlying risk drivers, (iii) associated spatiotemporal trends, (iv) the effect of land use and land-protection and (v) the protectiveness of regulatory frameworks. First, a meta-analysis of insecticides occurring in US surface waters (n = 5,817, 259 studies) revealed large-scale risks for aquatic ecosystems based on the exceedance of regulatory threshold levels (RTL) and identified high-risk substances, particularly pyrethroids, with increasing application trends (publication I). Following this, spatiotemporal factors driving insecticide risks were identified via model-building demonstrating that toxicity-weighted pesticide use was the primary driver in surface waters with subsequent model application generating a spatially comprehensive risk assessment for the United States (publication II). The toxicity-weighted pesticide use was subsequently expanded to an ongoing project covering additional species groups and all pesticides used in the US from 1992 – 2016, highlighting a drastic shift of toxic pressures from vertebrates to aquatic invertebrates. Large-scale monitoring data from European surface waters (n > 8.3 million) of 352 organic chemicals identified pesticides as the main class or organic contaminants causing risks in aquatic ecosystems. Additional analyses established links between agricultural intensity and resulting environmental risks for aquatic invertebrates and plants on this macro scale (publication III). Finally, high-resolution monitoring data from Saxony, Germany, provided, for the first time, detailed insights into the occurrence and resulting risks of organic contaminants (primarily pesticides) in protected surface waters of nature conservation areas (publication IV).
In summary, the thesis gathered and used large-scale datasets to analyze the impact of agricultural intensification – and later anthropogenic land use – on ecosystems to reduce knowledge deficits in ecotoxicology on macro scales. Insecticides were shown to be important and spatially extensive agents of impairments to surface water quality and being directly linked to their use in respective landscapes. Changes in the pesticide use composition over time shifted environmental risks from vertebrates to other central species groups (e.g. aquatic invertebrates), highlighting a new challenge to the integrity of aquatic environments. The thesis provided novel insights into contaminants' individual risk characteristics, their interaction with various spatiotemporal drivers and their relevance on various macro scales. Overall, a discrepancy remains evident between estimated environmental impacts of pesticides derived during regulatory approval processes contrasted by a posteriori field measurements detailing larger than assumed adverse exposures and effects. This discrepancy led to pesticides being the most impactful chemical stressor for aquatic ecosystems compared to other organic contaminants on a continental scale; a threat that even increased for some species groups. The extensive use of pesticides has reached levels where even strictly protected surface waters in Germany are regularly exposed adversely, hence threatening conservation areas’ function as ecological refugia. Taken together, the thesis provides new macro-scale evidence regarding the contribution of pesticides (and associated drivers) to large-scale changes in biological systems evidenced over the last decades, underlining their likely contribution to the ongoing freshwater biodiversity crisis globally. Particularly agricultural systems will require substantial changes going forward to protect or reestablish the integrity of aquatic ecosystems and their provision of vital ecological services.
On the Complexity of the Uncapacitated Single Allocation p-Hub Median Problem with Equal Weights
(2007)
The Super-Peer Selection Problem is an optimization problem in network topology construction. It may be cast as a special case of a Hub Location Problem, more exactly an Uncapacitated Single Allocation p-Hub Median Problem with equal weights. We show that this problem is still NP-hard by reduction from Max Clique.
Surface wetting can be described by using phase field models [1]. In these models, often either the contact angle or the surface tensions between the solid and the fluid are prescribed directly on the wall in order to represent the solid-fluid interaction. However, the interaction of the wall and the fluid are not strictly local. The influence of the wall, which can be described by wall potentials [2], reaches out into the fluid, which is the reason for the formation of adsorbate layers. The investigation shows how such a wall potential can be included into a phase field model of wetting. It is found that by considering this energy contribution, the model is able to capture the adsorbate layer.
In this thesis, a new concept to prove Mosco convergence of gradient-type Dirichlet forms within the \(L^2\)-framework of K.~Kuwae and T.~Shioya for varying reference measures is developed.
The goal is, to impose as little additional conditions as possible on the sequence of reference measure \({(\mu_N)}_{N\in \mathbb N}\), apart from weak convergence of measures.
Our approach combines the method of Finite Elements from numerical analysis with the topic of Mosco convergence.
We tackle the problem first on a finite-dimensional substructure of the \(L^2\)-framework, which is induced by finitely many basis functions on the state space \(\mathbb R^d\).
These are shifted and rescaled versions of the archetype tent function \(\chi^{(d)}\).
For \(d=1\) the archetype tent function is given by
\[\chi^{(1)}(x):=\big((-x+1)\land(x+1)\big)\lor 0,\quad x\in\mathbb R.\]
For \(d\geq 2\) we define a natural generalization of \(\chi^{(1)}\) as
\[\chi^{(d)}(x):=\Big(\min_{i,j\in\{1,\dots,d\}}\big(\big\{1+x_i-x_j,1+x_i,1-x_i\big\}\big)\Big)_+,\quad x\in\mathbb R^d.\]
Our strategy to obtain Mosco convergence of
\(\mathcal E^N(u,v)=\int_{\mathbb R^d}\langle\nabla u,\nabla v\rangle_\text{euc}d\mu_N\) towards \(\mathcal E(u,v)=\int_{\mathbb R^d}\langle\nabla u,\nabla v\rangle_\text{euc}d\mu\) for \(N\to\infty\)
involves as a preliminary step to restrict those bilinear forms to arguments \(u,v\) from the vector space spanned by the finite family \(\{\chi^{(d)}(\frac{\,\cdot\,}{r}-\alpha)\) \(|\alpha\in Z\}\) for
a finite index set \(Z\subset\mathbb Z^d\) and a scaling parameter \(r\in(0,\infty)\).
In a diagonal procedure, we consider a zero-sequence of scaling parameters and a sequence of index sets exhausting \(\mathbb Z^d\).
The original problem of Mosco convergence, \(\mathcal E^N\) towards \(\mathcal E\) w.r.t.~arguments \(u,v\) form the respective minimal closed form domains extending the pre-domain \(C_b^1(\mathbb R^d)\), can be solved
by such a diagonal procedure if we ask for some additional conditions on the Radon-Nikodym derivatives \(\rho_N(x)=\frac{d\mu_N(x)}{d x}\), \(N\in\mathbb N\). The essential requirement reads
\[\frac{1}{(2r)^d}\int_{[-r,r]^d}|\rho_N(x)- \rho_N(x+y)|d y \quad \overset{r\to 0}{\longrightarrow} \quad 0 \quad \text{in } L^1(d x),\,
\text{uniformly in } N\in\mathbb N.\]
As an intermediate step towards a setting with an infinite-dimensional state space, we let $E$ be a Suslin space and analyse the Mosco convergence of
\(\mathcal E^N(u,v)=\int_E\int_{\mathbb R^d}\langle\nabla_x u(z,x),\nabla_x v(z,x)\rangle_\text{euc}d\mu_N(z,x)\) with reference measure \(\mu_N\) on \(E\times\mathbb R^d\) for \(N\in\mathbb N\).
The form \(\mathcal E^N\) can be seen as a superposition of gradient-type forms on \(\mathbb R^d\).
Subsequently, we derive an abstract result on Mosco convergence for classical gradient-type Dirichlet forms
\(\mathcal E^N(u,v)=\int_E\langle \nabla u,\nabla v\rangle_Hd\mu_N\) with reference measure \(\mu_N\) on a Suslin space $E$ and a tangential Hilbert space \(H\subseteq E\).
The preceding analysis of superposed gradient-type forms can be used on the component forms \(\mathcal E^{N}_k\), which provide the decomposition
\(\mathcal E^{N}=\sum_k\mathcal E^{N}_k\). The index of the component \(k\) runs over a suitable orthonormal basis of admissible elements in \(H\).
For the asymptotic form \(\mathcal E\) and its component forms \(\mathcal E^k\), we have to assume \(D(\mathcal E)=\bigcap_kD(\mathcal E^k)\) regarding their domains, which is equivalent to the Markov uniqueness of \(\mathcal E\).
The abstract results are tested on an example from statistical mechanics.
Under a scaling limit, tightness of the family of laws for a microscopic dynamical stochastic interface model over \((0,1)^d\) is shown and its asymptotic Dirichlet form identified.
The considered model is based on a sequence of weakly converging Gaussian measures \({(\mu_N)}_{N\in\mathbb N}\) on \(L^2((0,1)^d)\), which are
perturbed by a class of physically relevant non-log-concave densities.
Phase velocities of surface acoustic waves in several boron nitride films were investigated by Brillouin light scattering. In the case of films with predominantly hexagonal crystal structure, grown under conditions close to the nucleation threshold of cubic BN, four independent elastic constants have been determined from the dispersion of the Rayleigh and the first Sezawa mode. The large elastic anisotropy of up to c11/c33 = 0.1 is attributed to a pronounced texture with the c-axes of the crystallites parallel to the film plane. In the case of cubic BN films the dispersion of the Rayleigh wave provides evidence for the existence of a more compliant layer at the substrate-film interface. The observed broadening of the Rayleigh mode is identified to be caused by the film morphology.
Hexagonal BN films have been deposited by rf-magnetron sputtering with simultaneous ion plating. The elastic properties of the films grown on silicon substrates under identical coating conditions have been de-termined by Brillouin light scattering from thermally excited surface phonons. Four of the five independent elastic constants of the deposited material are found to be c11 = 65 GPa, c13 = 7 GPa, c33 = 92 GPa and c44 = 53 GPa exhibiting an elastic anisotropy c11/c33 of 0.7. The Young's modulus determined with load indenta-tion is distinctly larger than the corresponding value taken from Brillouin light scattering. This discrepancy is attributed to the specific morphology of the material with nanocrystallites embedded in an amorphous matrix.