Refine
Year of publication
- 2018 (90) (remove)
Document Type
- Doctoral Thesis (51)
- Article (28)
- Conference Proceeding (5)
- Master's Thesis (3)
- Preprint (3)
Language
- English (90) (remove)
Has Fulltext
- yes (90)
Keywords
- Visualization (3)
- Evaluation (2)
- classification (2)
- iron (2)
- machine learning (2)
- 1D-CFD (1)
- 2D-CFD (1)
- ADAS (1)
- Addukt (1)
- Algorithmic Differentiation (1)
- Amination (1)
- Artificial Intelligence (1)
- Assessment (1)
- Association (1)
- Asymptotic Analysis (1)
- Atom-Photon-Wechselwirkung (1)
- Automatische Differentiation (1)
- Benzol (1)
- Biomarker (1)
- Bluetooth (1)
- Boolean networks (1)
- Bose-Einstein-Kondensation (1)
- Brandenburg-Lubuskie (1)
- Caching (1)
- Collaboration (1)
- Computational Fluid Dynamics (1)
- Computer Supported Cooperative Work (1)
- Concepts & Principles (1)
- Corridors (1)
- Cross-border regions (1)
- Cross-border transport (1)
- Cyanobacteria (1)
- Cyphochilus (1)
- DFT calculation (1)
- DRAM (1)
- Decision Support Systems (1)
- Diskrete Fourier-Transformation (1)
- Elastizität (1)
- Environmental inequality (1)
- European Pollutant Release and Transfer Register (E-PRTR) (1)
- European Territorial Cooperation (1)
- European Union (1)
- European Union policy-making (1)
- European integration (1)
- Europeanisation (1)
- Europäische Territoriale Zusammenarbeit (1)
- Evolutionary Algorithm (1)
- FFT (1)
- Flüssig-Flüssig-Extraktion (1)
- GAT-1 (1)
- GAT-3 (1)
- Geographic Information System (GIS) (1)
- Geoinformationssystem (1)
- German census (1)
- GlyT1 (1)
- Greater Region Saar-Lor-Lux+ (1)
- Großregion Saar-Lor-Lux+ (1)
- Harmonische Analyse (1)
- Hippocampus (1)
- Homogenisierung <Mathematik> (1)
- Hydrodynamics (1)
- Hydrodynamik (1)
- IRMPD (1)
- Identification (1)
- Industrial air pollution (1)
- Inferior colliculus (1)
- Interaction (1)
- Klassifikation (1)
- Kognitives Lernen (1)
- Lernen (1)
- Leukämie (1)
- Lineare partielle Differentialgleichung (1)
- Linked Data (1)
- Lippmann-Schwinger equation (1)
- Liquid-Liquid Extraction (1)
- Liquid-liquid extraction (1)
- Machine Learning (1)
- Manufacturing (1)
- Mass transfer (1)
- Measurement (1)
- Menschenmenge (1)
- Metabolismus (1)
- Metal-Free (1)
- Mikrostruktur (1)
- Multi-Variate Data (1)
- Nanocomposite (1)
- Network inference (1)
- Netzwerk (1)
- Node-Link Diagram (1)
- Numerical Analysis (1)
- Numerische Strömungssimulation (1)
- Optimal Control (1)
- Oxidant Evolution (1)
- PSPICE (1)
- Partial Differential Equations (1)
- Performance (1)
- Photon-Photon-Wechselwirkung (1)
- Physics Education Research (1)
- Physikdidaktik (1)
- Planning Support Systems (1)
- Policy implementation (1)
- Population balances (1)
- Populationsbilanzen (1)
- Prior knowledge (1)
- Process Data (1)
- Proteine (1)
- Prozessvisualisierung (1)
- Reactive extraction (1)
- Reaktivextraktion (1)
- Research Methodology (1)
- Reverse Engineering (1)
- SM-SQMOM (1)
- SOEP (1)
- SPARQL (1)
- SPARQL query learning (1)
- SQMOM (1)
- Semantic Web (1)
- Serumalbumine (1)
- Simulation (1)
- Smartphone (1)
- Smartwatch (1)
- Soft Spaces (1)
- Spatial regression models (1)
- Steady state (1)
- Stoffaustausch (1)
- Systemdesign (1)
- Thermoset (1)
- Time series data (1)
- Toxizität (1)
- Trans-European Transport Networks (1)
- Transeuropäische Verkehrsnetze (1)
- Transient state (1)
- Umweltgerechtigkeit (1)
- Undergraduate Students (1)
- Visualisierung (1)
- WiFi (1)
- Wissensrepräsentation (1)
- ab initio (1)
- acetate (1)
- adolescents (1)
- algebroid curve (1)
- alpha shape method (1)
- anharmonic CH modes (1)
- anharmonic vibrations (1)
- artificial intelligence (1)
- associations (1)
- assymmetric carboxylate stretch vibrations (1)
- basic carboxylates (1)
- benzene (1)
- biomarker (1)
- biomimetics (1)
- biosensors (1)
- canonical ideal (1)
- carboxylate bridge (1)
- carboxylates (1)
- changepoint test (1)
- characterization of Structures (1)
- chromium (1)
- collaborative mobile sensing (1)
- collision induced dissociation (1)
- combination band (1)
- composites (1)
- coordinative flexibility (1)
- crash application (1)
- crowd condition estimation (1)
- crowd density estimation (1)
- crowd scanning (1)
- crowd sensing (1)
- cumulative IRMPD (1)
- curve singularity (1)
- cutting simulation (1)
- data sets (1)
- dataset (1)
- duality (1)
- dynamic fracture mechanics (1)
- embedding (1)
- end-to-end learning (1)
- endomorphism ring (1)
- environment perception (1)
- evolutionary algorithm (1)
- fermi resonance (1)
- finite element method (1)
- formate (1)
- fragmentation channel (1)
- functional data (1)
- functional time series (1)
- good semigroup (1)
- graph embedding (1)
- hexadiendiale (1)
- homogenization (1)
- hybrid structure (1)
- impedance spectroscopy (1)
- infrared spectroscopy (1)
- inhibitory synaptic transmission (1)
- inverse coordination (1)
- ion-sensitive field-effect transistor (1)
- leukemia (1)
- linked data (1)
- metabolism (1)
- metal organic frameworks (1)
- micromechanics (1)
- molecular dynamics simulation (1)
- muconaldehyde (1)
- multi-object tracking (1)
- normalization (1)
- open dissipative quantum systems (1)
- overtone (1)
- oxo centered transition metal complexes (1)
- partial hydrolysis (1)
- participatory sensing (1)
- particle finite element method (1)
- pattern (1)
- phase field model (1)
- photon Bose-Einstein condensate (1)
- photon-photon interaction (1)
- posture (1)
- protein adducts (1)
- protein analysis (1)
- protein conjugate (1)
- pulsed and stirred columns (1)
- pulsierte und gerührte Kolonen (1)
- quasihomogeneity (1)
- readout system (1)
- sampling (1)
- semantic web (1)
- semigroup of values (1)
- serum albumin (1)
- silicon nanowire (1)
- solid-solid phase transition (1)
- spatial planning (1)
- stationary sensing (1)
- stationär (1)
- stimulus response data (1)
- surface (1)
- symmetrc carboxylate stretch vibrations (1)
- tailored disorder (1)
- toxicity (1)
- training (1)
- transient (1)
- transition metal complexes (1)
- translation invariant spaces (1)
- transport (1)
- white beetles (1)
- wireless signal (1)
Faculty / Organisational entity
- Kaiserslautern - Fachbereich Informatik (18)
- Kaiserslautern - Fachbereich Mathematik (18)
- Kaiserslautern - Fachbereich Maschinenbau und Verfahrenstechnik (13)
- Kaiserslautern - Fachbereich Biologie (11)
- Kaiserslautern - Fachbereich Elektrotechnik und Informationstechnik (7)
- Kaiserslautern - Fachbereich Physik (7)
- Kaiserslautern - Fachbereich Sozialwissenschaften (6)
- Kaiserslautern - Fachbereich Chemie (5)
- Kaiserslautern - Fachbereich Wirtschaftswissenschaften (3)
- Kaiserslautern - Fachbereich Raum- und Umweltplanung (2)
The research problem is that the land-use (re-)planning process in the existing Egyptian cities
does not attain sustainability. This is because of the unfulfillment of essential principles within
their land-use structures, lack of harmony between the added and old parts in the cities, and
other reasons. This leads to the need for developing an assessment system, which is a
computational spatial planning support system-SPSS. This SPSS is used for identifying the
degree of sustainability attainment in land-uses plans, predicting probable problems, and
suggesting modifications in the evaluated plans.
The main goal is to design the SPSS for supporting sustainability in the Egyptian cities. The
secondary goals are: studying the Egyptian planning and administrative systems for designing
the technical and administrative frameworks for the SPSS, the development of an assessment
model from the SPSS for assessing sustainability in land-use structures of urban areas, as well
as the identification of the improvements required in the model and the recommendations for
developing the SPSS.
The theoretical part aims to design each of the administrative and technical frameworks of the
SPSS. This requires studying each of the main planning approaches, the sustainability in urban
land-use planning, and the significance of using efficient assessment tools for evaluating the
sustainability in this process. The added value of the planning support systems-PSSs for
planning and their role in supporting sustainability attainment in urban land-use planning are
discussed. Then, a group of previous examples in the sustainability assessment from various
countries (developed and developing countries) are selected, which have used various
assessment tools. This is to extract some learned lessons to be guides for the SPSS. And so,
the comprehensive technical framework for the SPSS is designed, which includes the suggested
methods and techniques that perform various stages of the assessment process.
The Egyptian context is studied regarding the planning and administration systems within the
Egyptian cities, as well as the spatial and administrative problems facing the sustainable
development. And so, the administrative framework for the SPSS is identified, which includes
the entities that should be involved in the assessment process.
The empirical part focuses on the design of a selected assessment model from the
comprehensive technical framework of the SPSS to be established as a minimized version from
it. This model is programmed in the form of a new toolbox within the ArcGIS™ software through
geoscripting using Python programming language to be applied for assessing the sustainability
attainment in the land-use structure of urban areas. The required assessing criteria for the model
specialized for the Egyptian and German cities are identified, for applying it on German and
Egyptian study areas.
The conclusions regarding each of PSSs, the Egyptian local administration and planning
systems, sustainability attainment in the land-use planning process in Egyptian Cities, as well as
the proposed SPSS and the developed toolbox are drawn. The recommendations are regarding
each of challenges facing the development and application of PSSs, the Egyptian local
administration and planning systems, the spatial problems in Egyptian cities, the establishment
of the SPSS, and the application of the toolbox. The future agenda is in the fields of sustainable urban land-use planning, planning support science, and the development process in the
Egyptian cities.
Background: Aneuploidy, or abnormal chromosome numbers, severely alters cell physiology and is widespread in
cancers and other pathologies. Using model cell lines engineered to carry one or more extra chromosomes, it has
been demonstrated that aneuploidy per se impairs proliferation, leads to proteotoxic as well as replication stress
and triggers conserved transcriptome and proteome changes.
Results: In this study, we analysed for the first time miRNAs and demonstrate that their expression is altered in
response to chromosome gain. The miRNA deregulation is independent of the identity of the extra chromosome
and specific to individual cell lines. By cross-omics analysis we demonstrate that although the deregulated miRNAs
differ among individual aneuploid cell lines, their known targets are predominantly associated with cell development,
growth and proliferation, pathways known to be inhibited in response to chromosome gain. Indeed, we show that up
to 72% of these targets are downregulated and the associated miRNAs are overexpressed in aneuploid cells, suggesting
that the miRNA changes contribute to the global transcription changes triggered by aneuploidy. We identified
hsa-miR-10a-5p to be overexpressed in majority of aneuploid cells. Hsa-miR-10a-5p enhances translation of a
subset of mRNAs that contain so called 5’TOP motif and we show that its upregulation in aneuploids provides
resistance to starvation-induced shut down of ribosomal protein translation.
Conclusions: Our work suggests that the changes of the microRNAome contribute on one hand to the adverse
effects of aneuploidy on cell physiology, and on the other hand to the adaptation to aneuploidy by supporting
translation under adverse conditions.
Keywords: Aneuploidy, Cancer, miRNA, miR-10a-5p, Trisomy
Poor posture in childhood and adolescence is held responsible for the occurrence
of associated disorders in adult age. This study aimed to verify whether body
posture in adolescence can be enhanced through the improvement of neuromuscular
performance, attained by means of targeted strength, stretch, and body perception
training, and whether any such improvement might also transition into adulthood. From
a total of 84 volunteers, the posture development of 67 adolescents was checked
annually between the age of 14 and 20 based on index values in three posture
situations. 28 adolescents exercised twice a week for about 2 h up to the age of 18, 24
adolescents exercised continually up to the age of 20. Both groups practiced other
additional sports for about 1.8 h/week. Fifteen persons served as a non-exercising
control group, practicing optional sports of about 1.8 h/week until the age of 18,
after that for 0.9 h/week. Group allocation was not random, but depended on the
participants’ choice. A linear mixed model was used to analyze the development
of posture indexes among the groups and over time and the possible influence of
anthropometric parameters (weight, size), of optional athletic activity and of sedentary
behavior. The post hoc pairwise comparison was performed applying the Scheffé test.
The significance level was set at 0.05. The group that exercised continually (TR20)
exhibited a significant posture parameter improvement in all posture situations from
the 2nd year of exercising on. The group that terminated their training when reaching
adulthood (TR18) retained some improvements, such as conscious straightening of the
body posture. In other posture situations (habitual, closed eyes), their posture results
declined again from age 18. The effect sizes determined were between Eta² = 0.12 and
Eta² = 0.19 and represent moderate to strong effects. The control group did not exhibit
any differences. Anthropometric parameters, additional athletic activities and sedentary
behavior did not influence the posture parameters significantly. An additional athletic
training of 2 h per week including elements for improved body perception seems to
have the potential to improve body posture in symptom free male adolescents and
young adults.
In this study, the dependence of the cyclic deformation behavior on the surface morphology of metastable austenitic HSD® 600 TWinning Induced Plasticity (TWIP) steel was investigated. This steel—with the alloying concept Mn-Al-Si—shows a fully austenitic microstructure with deformation-induced twinning at ambient temperature. Four different surface morphologies were analyzed: as-received with a so-called rolling skin, after up milling, after down milling, and a reference morphology achieved by polishing. The morphologies were characterized by X-Ray Diffraction (XRD), Focused Ion Beam (FIB), Scanning Electron Microscopy (SEM) as well as confocal microscopy methods and show significant differences in initial residual stresses, phase fractions, topographies and microstructures. For specimens with all variants of the morphologies, fatigue tests were performed in the Low Cycle Fatigue (LCF) and High Cycle Fatigue (HCF) regime to characterize the cyclic deformation behavior and fatigue life. Moreover, this study focused on the frequency-dependent self-heating of the specimens caused by cyclic plasticity in the HCF regime. The results show that both surface morphology and specimen temperature have a significant influence on the cyclic deformation behavior of HSD® 600 TWIP steel in the HCF regime.
Cyanobacteria of biological soil crusts (BSCs) represent an important part of circumpolar
and Alpine ecosystems, serve as indicators for ecological condition and climate
change, and function as ecosystem engineers by soil stabilization or carbon and nitrogen
input. The characterization of cyanobacteria from both polar regions remains
extremely important to understand geographic distribution patterns and community
compositions. This study is the first of its kind revealing the efficiency of combining
denaturing gradient gel electrophoresis (DGGE), light microscopy and culture-based
16S rRNA gene sequencing, applied to polar and Alpine cyanobacteria dominated
BSCs. This study aimed to show the living proportion of cyanobacteria as an extension
to previously published meta-transcriptome
data of the same study sites.
Molecular fingerprints showed a distinct clustering of cyanobacterial communities
with a close relationship between Arctic and Alpine populations, which differed from
those found in Antarctica. Species richness and diversity supported these results,
which were also confirmed by microscopic investigations of living cyanobacteria
from the BSCs. Isolate-based
sequencing corroborated these trends as cold biome
clades were assigned, which included a potentially new Arctic clade of Oculatella.
Thus, our results contribute to the debate regarding biogeography of cyanobacteria
of cold biomes.
Multiphase materials combine properties of several materials, which makes them interesting for high-performing components. This thesis considers a certain set of multiphase materials, namely silicon-carbide (SiC) particle-reinforced aluminium (Al) metal matrix composites and their modelling based on stochastic geometry models.
Stochastic modelling can be used for the generation of virtual material samples: Once we have fitted a model to the material statistics, we can obtain independent three-dimensional “samples” of the material under investigation without the need of any actual imaging. Additionally, by changing the model parameters, we can easily simulate a new material composition.
The materials under investigation have a rather complicated microstructure, as the system of SiC particles has many degrees of freedom: Size, shape, orientation and spatial distribution. Based on FIB-SEM images, that yield three-dimensional image data, we extract the SiC particle structure using methods of image analysis. Then we model the SiC particles by anisotropically rescaled cells of a random Laguerre tessellation that was fitted to the shapes of isotropically rescaled particles. We fit a log-normal distribution for the volume distribution of the SiC particles. Additionally, we propose models for the Al grain structure and the Aluminium-Copper (\({Al}_2{Cu}\)) precipitations occurring on the grain boundaries and on SiC-Al phase boundaries.
Finally, we show how we can estimate the parameters of the volume-distribution based on two-dimensional SEM images. This estimation is applied to two samples with different mean SiC particle diameters and to a random section through the model. The stereological estimations are within acceptable agreement with the parameters estimated from three-dimensional image data
as well as with the parameters of the model.
In recent years, enormous progress has been made in the field of Artificial Intelligence (AI). Especially the introduction of Deep Learning and end-to-end learning, the availability of large datasets and the necessary computational power in form of specialised hardware allowed researchers to build systems with previously unseen performance in areas such as computer vision, machine translation and machine gaming. In parallel, the Semantic Web and its Linked Data movement have published many interlinked RDF datasets, forming the world’s largest, decentralised and publicly available knowledge base.
Despite these scientific successes, all current systems are still narrow AI systems. Each of them is specialised to a specific task and cannot easily be adapted to all other human intelligence tasks, as would be necessary for Artificial General Intelligence (AGI). Furthermore, most of the currently developed systems are not able to learn by making use of freely available knowledge such as provided by the Semantic Web. Autonomous incorporation of new knowledge is however one of the pre-conditions for human-like problem solving.
This work provides a small step towards teaching machines such human-like reasoning on freely available knowledge from the Semantic Web. We investigate how human associations, one of the building blocks of our thinking, can be simulated with Linked Data. The two main results of these investigations are a ground truth dataset of semantic associations and a machine learning algorithm that is able to identify patterns for them in huge knowledge bases.
The ground truth dataset of semantic associations consists of DBpedia entities that are known to be strongly associated by humans. The dataset is published as RDF and can be used for future research.
The developed machine learning algorithm is an evolutionary algorithm that can learn SPARQL queries from a given SPARQL endpoint based on a given list of exemplary source-target entity pairs. The algorithm operates in an end-to-end learning fashion, extracting features in form of graph patterns without the need for human intervention. The learned patterns form a feature space adapted to the given list of examples and can be used to predict target candidates from the SPARQL endpoint for new source nodes. On our semantic association ground truth dataset, our evolutionary graph pattern learner reaches a Recall@10 of > 63 % and an MRR (& MAP) > 43 %, outperforming all baselines. With an achieved Recall@1 of > 34% it even reaches average human top response prediction performance. We also demonstrate how the graph pattern learner can be applied to other interesting areas without modification.
SDE-driven modeling of phenotypically heterogeneous tumors: The influence of cancer cell stemness
(2018)
We deduce cell population models describing the evolution of a tumor (possibly interacting with its
environment of healthy cells) with the aid of differential equations. Thereby, different subpopulations
of cancer cells allow accounting for the tumor heterogeneity. In our settings these include cancer
stem cells known to be less sensitive to treatment and differentiated cancer cells having a higher
sensitivity towards chemo- and radiotherapy. Our approach relies on stochastic differential equations
in order to account for randomness in the system, arising e.g., by the therapy-induced decreasing
number of clonogens, which renders a pure deterministic model arguable. The equations are deduced
relying on transition probabilities characterizing innovations of the two cancer cell subpopulations,
and similarly extended to also account for the evolution of normal tissue. Several therapy approaches
are introduced and compared by way of tumor control probability (TCP) and uncomplicated tumor
control probability (UTCP). A PDE approach allows to assess the evolution of tumor and normal
tissue with respect to time and to cell population densities which can vary continuously in a given set
of states. Analytical approximations of solutions to the obtained PDE system are provided as well.
Cutting-edge cancer therapy involves producing individualized medicine for many patients at the same time. Within this process, most steps can be completed for a certain number of patients simultaneously. Using these resources efficiently may significantly reduce waiting times for the patients and is therefore crucial for saving human lives. However, this involves solving a complex scheduling problem, which can mathematically be modeled as a proportionate flow shop of batching machines (PFB). In this thesis we investigate exact and approximate algorithms for tackling many variants of this problem. Related mathematical models have been studied before in the context of semiconductor manufacturing.
Collaboration aims to increase the efficiency of problem solving and decision making by bringing diverse areas of expertise together, i.e., teams of experts from various disciplines, all necessary to come up with acceptable concepts. This dissertation is concerned with the design of highly efficient computer-supported collaborative work involving active participation of user groups with diverse expertise. Three main contributions can be highlighted: (1) the definition and design of a framework facilitating collaborative decision making; (2) the deployment and evaluation of more natural and intuitive interaction and visualization techniques in order to support multiple decision makers in virtual reality environments; and (3) the integration of novel techniques into a single proof-of-concept system.
Decision making processes are time-consuming, typically involving several iterations of different options before a generally acceptable solution is obtained. Although, collaboration is an often-applied method, the execution of collaborative sessions is often inefficient, does not involve all participants, and decisions are often finalized with- out the agreement of all participants. An increasing number of computer-supported cooperative work systems (CSCW) facilitate collaborative work by providing shared viewpoints and tools to solve joint tasks. However, most of these software systems are designed from a feature-oriented perspective, rather than a human-centered perspective and without the consideration of user groups with diverse experience and joint goals instead of joint tasks. The aim of this dissertation is to bring insights to the following research question: How can computer-supported cooperative work be designed to be more efficient? This question opens up more specific questions like: How can collaborative work be designed to be more efficient? How can all participants be involved in the collaboration process? And how can interaction interfaces that support collaborative work be designed to be more efficient? As such, this dissertation makes contributions in:
1. Definition and design of a framework facilitating decision making and collaborative work. Based on examinations of collaborative work and decision making processes requirements of a collaboration framework are assorted and formulated. Following, an approach to define and rate software/frameworks is introduced. This approach is used to translate the assorted requirements into a software’s architecture design. Next, an approach to evaluate alternatives based on Multi Criteria Decision Making (MCDM) and Multi Attribute Utility Theory (MAUT) is presented. Two case studies demonstrate the usability of this approach for (1) benchmarking between systems and evaluates the value of the desired collaboration framework, and (2) ranking a set of alternatives resulting from a decision-making process incorporating the points of view of multiple stake- holders.
2. Deployment and evaluation of natural and intuitive interaction and visualization techniques in order to support multiple diverse decision makers. A user taxonomy of industrial corporations serves to create a petri network of users in order to identify dependencies and information flows between each other. An explicit characterization and design of task models was developed to define interfaces and further components of the collaboration framework. In order to involve and support user groups with diverse experiences, smart de- vices and virtual reality are used within the presented collaboration framework. Natural and intuitive interaction techniques as well as advanced visualizations of user centered views of the collaboratively processed data are developed in order to support and increase the efficiency of decision making processes. The smartwatch as one of the latest technologies of smart devices, offers new possibilities of interaction techniques. A multi-modal interaction interface is provided, realized with smartwatch and smartphone in full immersive environments, including touch-input, in-air gestures, and speech.
3. Integration of novel techniques into a single proof-of-concept system. Finally, all findings and designed components are combined into the new collaboration framework called IN2CO, for distributed or co-located participants to efficiently collaborate using diverse mobile devices. In a prototypical implementation, all described components are integrated and evaluated. Examples where next-generation network-enabled collaborative environments, connected by visual and mobile interaction devices, can have significant impact are: design and simulation of automobiles and aircrafts; urban planning and simulation of urban infrastructure; or the design of complex and large buildings, including efficiency- and cost-optimized manufacturing buildings as task in factory planning. To demonstrate the functionality and usability of the framework, case studies referring to factory planning are demonstrated. Considering that factory planning is a process that involves the interaction of multiple aspects as well as the participation of experts from different domains (i.e., mechanical engineering, electrical engineering, computer engineering, ergonomics, material science, and even more), this application is suitable to demonstrate the utilization and usability of the collaboration framework. The various software modules and the integrated system resulting from the research will all be subjected to evaluations. Thus, collaborative decision making for co-located and distributed participants is enhanced by the use of natural and intuitive multi-modal interaction interfaces and techniques.