004 Datenverarbeitung; Informatik
Refine
Has Fulltext
- yes (127)
Is part of the Bibliography
- yes (127)
Year of publication
Document Type
- Journal article (127) (remove)
Keywords
- virtual reality (15)
- machine learning (5)
- augmented reality (4)
- human-computer interaction (4)
- crowdsensing (3)
- database (3)
- deep learning (3)
- immersion (3)
- mHealth (3)
- neural networks (3)
- resistance (3)
- Deep learning (2)
- IoT (2)
- Quadrocopter (2)
- Quadrotor (2)
- XR (2)
- artificial intelligence (2)
- automation (2)
- design (2)
- education (2)
- endoscopy (2)
- engineering (2)
- exposure (2)
- framework (2)
- fully convolutional neural networks (2)
- gastroenterology (2)
- genetics (2)
- historical document analysis (2)
- immersive technologies (2)
- metabolic modeling (2)
- natural variation (2)
- navigation (2)
- ontology (2)
- perception (2)
- prediction (2)
- scalability (2)
- segmentation (2)
- self-aware computing (2)
- smart speaker (2)
- spatial presence (2)
- tinnitus (2)
- virtual agent (2)
- virtual environments (2)
- 26S RDNA Data (1)
- 3D collation (1)
- 3D fluoroscopy (1)
- 3D viewer (1)
- 3D-reconstruction methods (1)
- 3DTK toolkit (1)
- 4D-GIS (1)
- ACKR4 (1)
- AI (1)
- AKT (1)
- AVA (1)
- Analysis (1)
- Aufwandsanalyse (1)
- Automatisierte Prüfungskorrektur (1)
- Autonomous UAV (1)
- BPM (1)
- BPMN (1)
- Barcodes (1)
- Biology (1)
- Boolean function (1)
- Boolean tree (1)
- Brüder Grimm Privatbibliothek (1)
- CD4+T cells (1)
- CD8+T cells (1)
- CD95 (1)
- CETCH cycle (1)
- CLIP (1)
- CO2-sequestration (1)
- COVID-19 (1)
- Caenorhabditis elegans (1)
- Charged aerosol detector (CAD) (1)
- Colonial volvocales chlorophyta (1)
- Computer software (1)
- Convolutional Neural Network (1)
- Cost Analysis (1)
- DNA (1)
- DNA storage (1)
- Dasycladales chlorophyta (1)
- EEG (1)
- EEG frequency band analysis (1)
- EEG preprocessing (1)
- EEG processing (1)
- EPM (1)
- Educational Measurement (I2.399) (1)
- Entscheidungsfindung (1)
- Erkennung handschriftlicher Artefakte (1)
- Ethik (1)
- FLIMbee (1)
- Fatty acids (1)
- Forces (1)
- GNSS/INS integrated navigation (1)
- Gradient boosted trees (GBT) (1)
- Grimm brothers personal library (1)
- HGPS (1)
- HHblits (1)
- HMD (Head-Mounted Display) (1)
- HTTP adaptive video streaming (1)
- High-performance liquid chromatography (HPLC) (1)
- Hittitology (1)
- I-tasser (1)
- ICEP (1)
- IGFBP2 (1)
- III secretion (1)
- INS/LIDAR integrated navigation (1)
- IT security (1)
- Image Aesthetic Assessment (1)
- ImageJ (1)
- Informatik (1)
- Intelligent Virtual Agents (1)
- InteractionSuitcase (1)
- Internet of Things (1)
- IoT-driven processes (1)
- IronChip Evaluation Package (1)
- Jacobian matrix (1)
- Java 3D (1)
- Kerneldensity estimation (1)
- Klima (1)
- Künstliche Intelligenz (1)
- LC-MS/MS (1)
- Land plants (1)
- Lifetime spectroscopy (1)
- LoRaWAN (1)
- MDR (1)
- Measurement (1)
- Microarray (1)
- Modell (1)
- Molecular systematics (1)
- Multiple-Choice Examination (1)
- Multiple-Choice Prüfungen (1)
- Mycoplasma (1)
- NP-hardness (1)
- Neuromuscular junctions (1)
- Neuronales Netz (1)
- Nuclear RDNA (1)
- Optical Flow (1)
- Poisson surface reconstruction (1)
- Positron annihilation spectroscopy (1)
- Profile distances (1)
- Programmierbare logische Anordnung (1)
- Quantitative structure-property relationship modeling (QSPR) (1)
- RBCL Gene-sequences (1)
- RGB-D (1)
- RNA sequencing (1)
- Robotics (1)
- SARS-CoV-2 (1)
- SMLM (1)
- SNP (1)
- Secondary structure (1)
- Self-Evaluation Programs (I2.399.780) (1)
- Septins (1)
- Simulation (1)
- Software product lines (1)
- Structure-from-Motion (1)
- Synapses (1)
- Synaptic vesicles (1)
- Terramechanics (1)
- Time resolved measurements (1)
- Torque (1)
- V-antigen (1)
- Variability (1)
- Vesicles (1)
- Visualisierung (1)
- WH2 domain (1)
- WNT (1)
- WebGL (1)
- WhatsApp (1)
- Wheel (1)
- XR-artificial intelligence combination (1)
- XR-artificial intelligence continuum (1)
- Yersinia enterocolitica (1)
- Yolk protein (1)
- YouTube (1)
- Zebrafish (1)
- acrophobia (1)
- actin nucleation (1)
- adaptation (1)
- adaptation models (1)
- adult learning (1)
- advertising effectiveness (1)
- aerodynamics (1)
- agents (1)
- aging (1)
- alignment (1)
- anamnesis tool (1)
- aneurysm (1)
- annotation (1)
- anomaly detection (1)
- anomaly prediction (1)
- ant-colony optimization (1)
- anthropomorphism (1)
- anxiety (1)
- apixaban (1)
- application design (1)
- approximation algorithm (1)
- arabidopsis thaliana (1)
- arabidpsis thaliana (1)
- architectural design (1)
- arithmetic calculations (1)
- artificial intelligence education (1)
- artificial intelligence literacy (1)
- augmentation (1)
- autonomous (1)
- autonomous UAV (1)
- availability (1)
- avatar embodiment (1)
- avatars (1)
- background knowledge (1)
- baseline detection (1)
- behavior (1)
- behavior change (1)
- behavior perception (1)
- bibliometric analysis (1)
- binary decision diagram (1)
- binary tanglegram (1)
- biofuel (1)
- biohybrid systems (1)
- bioinformatics (1)
- biological development (1)
- biomanufacturing (1)
- biosignals (1)
- brain (1)
- caenorhabditis elegans (1)
- camera orientation (1)
- carbon (1)
- carboxylation (1)
- cardiac magnetic resonance (1)
- caspase-3 (1)
- cell membranes (1)
- cerebral ischemia (1)
- certifying algorithm (1)
- chain cover (1)
- channel management (1)
- cisplatin (1)
- classification (1)
- climate (1)
- cloud-native (1)
- co-authorships (1)
- co-inventorships (1)
- coherence (1)
- collaboration (1)
- collision (1)
- colony-stimulating factor (1)
- combination therapy (1)
- communication models (1)
- communication networks (1)
- community detection (1)
- comparative sequence analysis (1)
- complex traits (1)
- compressed sensing (1)
- computational (1)
- computers as social actors (1)
- condition prediction (1)
- congruence (1)
- connector (1)
- content-based image retrieval (1)
- continuous-time SLAM (1)
- conversational agent (1)
- conversational agents (1)
- convex bipartite graph (1)
- convolutional neural network (1)
- corticotropin-releasing hormone (1)
- cost-sensitive learning (1)
- crossing minimization (1)
- crosstalk (1)
- crowdsourced measurements (1)
- cultural and media studies (1)
- culturally aware (1)
- cuneiform (1)
- cyber-physical systems (1)
- cybersickness (1)
- cytokine profiling (1)
- dSTORM (1)
- data stream processing (1)
- data warehouse (1)
- decision support system (1)
- decision-making (1)
- deep metric learning (1)
- deformation-based method (1)
- design cycle (1)
- detection time simulation (1)
- diagnostic accuracy (1)
- differentiation (1)
- digital twin (1)
- dimensions of proximity (1)
- direct oral anticoagulants (1)
- direct thrombin inhibitor (1)
- disease (1)
- disruption project (1)
- distributed control (1)
- drug (1)
- drug-minded protein (1)
- dynamic programming (1)
- eHealth (1)
- eco-metabolomics (1)
- ecological momentary assessment (1)
- educational tool (1)
- electroencephalography (1)
- electrolytes (1)
- electronic health records (1)
- elementary mode analysis (1)
- elementary modes (1)
- elevated plus-maze (1)
- embedding techniques (1)
- emotions (1)
- empathy (1)
- encryption (1)
- endurance (1)
- environmental sound (1)
- enzyme (1)
- event detection (1)
- event-related potentials-ERP (1)
- evolution (1)
- exercise intensity (1)
- experience (1)
- experimental evaluation (1)
- expertise framing (Min5-Max 8) (1)
- expression (1)
- expression signature (1)
- extended reality (XR) (1)
- factor XA inhibitor (1)
- failure prediction (1)
- fault detection (1)
- feature matching (1)
- few-shot learning (1)
- fixed-parameter tractability (1)
- flies (1)
- fluoroscopy (1)
- food quality (1)
- force dynamics (1)
- foreign language learning and teaching (1)
- formation flight (1)
- fruit temperature (1)
- functional analysis (1)
- future energy grid exploration (1)
- games (1)
- gamification (1)
- gamma (1)
- generative systems (1)
- genes (1)
- genetic algorithm (1)
- genetic regulatory network (1)
- geospatial data (1)
- graph algorithm (1)
- green systems biology (1)
- group-based communication (1)
- handwriting (1)
- handwritten artefact recognition (1)
- hepatotoxicity (1)
- hierarchy (1)
- histidine kinase (1)
- historical images (1)
- homology modeling (1)
- hospital data (1)
- human body weight (1)
- human computer interaction (HCI) (1)
- human-artificial intelligence interaction (1)
- human-artificial intelligence interface (1)
- human-centered design (1)
- human-centered, human-robot (1)
- humantechnology interaction (1)
- human–computer interaction (1)
- hypotonic (1)
- hypotonic solutions (1)
- illusion of self-motion (1)
- image classification (1)
- image processing (1)
- image schemas (1)
- imbalanced regression (1)
- immersive advertising (1)
- immersive classroom (1)
- immersive classroom management (1)
- immunity (1)
- implicit association test (1)
- in situ analysis (1)
- induced matching (1)
- informal education (1)
- information extraction (1)
- information systems and information technology (1)
- inhibitor (1)
- intelligent transportation systems (1)
- intelligent vehicles (1)
- intelligent virtual agents (1)
- intelligent voice assistant (1)
- intention-behavior-gap (1)
- inter-coder reliability (1)
- interaction (1)
- intercultural learning and teaching (1)
- interdisciplinary education (1)
- intermediate host (1)
- internal transcribed spacer 2 (1)
- internet traffic (1)
- interpolation (1)
- intervention design (1)
- intervention evaluation (1)
- intraoperative imaging (1)
- invasive vascular interventions (1)
- iowa gambling task (1)
- isotonic (1)
- key-insight extraction (1)
- kinect (1)
- language-image pre-training (1)
- layout recognition (1)
- learning environments (1)
- life-span regulation (1)
- lifetime spectroscopy (1)
- light-gated proteins (1)
- local energy system (1)
- logistics (1)
- long-term analysis (1)
- lymphotoxicity (1)
- malaria (1)
- map projections (1)
- mapping (1)
- markers (1)
- mathematical model (1)
- measurement (1)
- measurements (1)
- media analysis (1)
- media equation (1)
- medical analytics (1)
- medical device regulation (1)
- medical device software (1)
- medical records (1)
- medieval manuscripts (1)
- meditation (1)
- membrane proteins (1)
- memory immune responses (1)
- metabolic flux (1)
- metabolism (1)
- metabolomics (1)
- metastasis (1)
- methylene blue (1)
- mice (1)
- microbes (1)
- mindfulness (1)
- misconceptions (1)
- mixed reality (1)
- mixed-cultural (1)
- mixed-cultural settings (1)
- mobile application (1)
- mobile instant messaging (1)
- mobile messaging application (1)
- mobile networks (1)
- mobile streaming (1)
- model following (1)
- model output statistics (1)
- model-based diagnosis (1)
- modules (1)
- molecular systematics (1)
- mouse (1)
- multimodal fusion (1)
- multimodal interface (1)
- multiple myeloma (1)
- multirotors (1)
- multiscale encoder (1)
- mutation (1)
- nano-satellite (1)
- nanocellulose (1)
- natural interfaces (1)
- natural language processing (1)
- networks (1)
- neume notation (1)
- neural architecture (1)
- noise measurement (1)
- non-native accent (1)
- nonhuman-primates (1)
- nonverbal behavior (1)
- object detection (1)
- octree (1)
- omics (1)
- optical music recognition (1)
- organogenesis (1)
- origin (1)
- oxidative stress (1)
- painful (1)
- pangolin (1)
- passage of time (1)
- passive haptic feedback (1)
- pathway (1)
- performance (1)
- performance analysis (1)
- performance liquid chromatography (1)
- performance prediction (1)
- permeability (1)
- pestis infection (1)
- photorespiration (1)
- phylogenetic tree (1)
- phylogeny (1)
- place-illusion (1)
- plausibility (1)
- plausibility-illusion (1)
- pneumonic plague (1)
- point cloud (1)
- point cloud compression (1)
- point-to-plane measure (1)
- point-to-point measure (1)
- pollution (1)
- positioning (1)
- precision horticulture (1)
- precision training (1)
- presence (1)
- private chat groups (1)
- procedural fusion methods (1)
- processing pipeline (1)
- progeria (1)
- promoter (1)
- prompt engineering (1)
- protein (1)
- protein chip (1)
- protein-interaction networks (1)
- pseudomas-syringae (1)
- psychophyisology (1)
- public speaking (1)
- pulse simulation (1)
- quadcopter (1)
- quadcopters (1)
- quality assurance (1)
- quality evaluation (1)
- quality of experience (1)
- quality of experience prediction (1)
- quantification (1)
- radiology (1)
- ransomware (1)
- real world evidence (1)
- real-world application (1)
- realism (1)
- receptor (1)
- recombinant protein rVE (1)
- recombination (1)
- recommender system (1)
- regelbasierte Nachbearbeitung (1)
- research methods (1)
- response regulator (1)
- ribosomal RNA (1)
- rich vehicle routing problem (1)
- richtersius coronifer (1)
- robustness (1)
- rotors (1)
- rule based post processing (1)
- sample weighting (1)
- satisfiability problems (1)
- scalable quadcopter (1)
- scheduling (1)
- science, technology and society (1)
- secondary structure (1)
- secure group communication (1)
- self-adaptive (1)
- self-adaptive systems (1)
- self-aware computing systems (1)
- self-managing systems (1)
- semantic fusion (1)
- sensitivity analysis (1)
- sensor (1)
- sensor fusion (1)
- sensor networks (1)
- sentinel (1)
- sequence alignment (1)
- serious games (1)
- serum (1)
- sesnsors (1)
- set (1)
- shootin-1 (1)
- signal processing (1)
- simulation (1)
- simulation system (1)
- single-electron transistors (1)
- sketching (1)
- smart meter data utilization (1)
- social VR (1)
- social interaction (1)
- social relationship (1)
- social robot (1)
- social robotics (1)
- social role (1)
- socially interactive agents (1)
- spire (1)
- stability (1)
- stable state (1)
- statistical validity (1)
- statistics and numerical data (1)
- stereotypes (1)
- stream processing (1)
- stroke (1)
- student simulation (1)
- stylus (1)
- sun exposure (1)
- sunburn (1)
- superoxide-dismutase (1)
- supervised learning (1)
- surface model (1)
- survey (1)
- survival (1)
- switching navigation (1)
- synthetic biology (1)
- synthetic pathways (1)
- system architecture design (1)
- systematic literature review (1)
- systematic review (1)
- table extraction (1)
- table understanding (1)
- taxonomy (1)
- teacher education (1)
- technology-supported learning (1)
- temperature (1)
- text line detection (1)
- text supervision (1)
- theory (1)
- therapeutic application (1)
- thermal camera (1)
- thermal point cloud (1)
- time calibration (1)
- time perception (1)
- time series (1)
- tolerance (1)
- tonicity (1)
- tools (1)
- trait anxiety (1)
- transcription (1)
- transformations (1)
- transformer (1)
- translational neuroscience (1)
- transmission (1)
- transport microenvironments (1)
- transportation (1)
- trust (1)
- trustworthiness (1)
- unmanned aerial vehicle (1)
- unmanned aerial vehicles (1)
- usability evaluation (1)
- use cases (1)
- user experience (1)
- user interaction (1)
- user interfaces (1)
- user study (1)
- vaccine (1)
- validation (1)
- vection (1)
- vehicle dynamics (1)
- vehicular navigation (1)
- verbal behaviour (1)
- virtual agent interaction (1)
- virtual audience (1)
- virtual humans (1)
- virtual reality training (1)
- virtual stimuli (1)
- virtual tunnel (1)
- virtual-reality-continuum (1)
- visual analytics (1)
- vitellogenin (1)
- voice assistant (1)
- voice-based artificial intelligence (1)
- water stress (1)
- waypoint parameter (1)
- wearable (1)
Institute
- Institut für Informatik (78)
- Theodor-Boveri-Institut für Biowissenschaften (27)
- Institut Mensch - Computer - Medien (15)
- Institut für Klinische Epidemiologie und Biometrie (7)
- Center for Computational and Theoretical Biology (4)
- Medizinische Klinik und Poliklinik II (3)
- Institut für Funktionsmaterialien und Biofabrikation (2)
- Institut für Pharmazie und Lebensmittelchemie (2)
- Institut für Psychologie (2)
- Deutsches Zentrum für Herzinsuffizienz (DZHI) (1)
Sonstige beteiligte Institutionen
Effects of Acrophobic Fear and Trait Anxiety on Human Behavior in a Virtual Elevated Plus-Maze
(2021)
The Elevated Plus-Maze (EPM) is a well-established apparatus to measure anxiety in rodents, i.e., animals exhibiting an increased relative time spent in the closed vs. the open arms are considered anxious. To examine whether such anxiety-modulated behaviors are conserved in humans, we re-translated this paradigm to a human setting using virtual reality in a Cave Automatic Virtual Environment (CAVE) system. In two studies, we examined whether the EPM exploration behavior of humans is modulated by their trait anxiety and also assessed the individuals’ levels of acrophobia (fear of height), claustrophobia (fear of confined spaces), sensation seeking, and the reported anxiety when on the maze. First, we constructed an exact virtual copy of the animal EPM adjusted to human proportions. In analogy to animal EPM studies, participants (N = 30) freely explored the EPM for 5 min. In the second study (N = 61), we redesigned the EPM to make it more human-adapted and to differentiate influences of trait anxiety and acrophobia by introducing various floor textures and lower walls of closed arms to the height of standard handrails. In the first experiment, hierarchical regression analyses of exploration behavior revealed the expected association between open arm avoidance and Trait Anxiety, an even stronger association with acrophobic fear. In the second study, results revealed that acrophobia was associated with avoidance of open arms with mesh-floor texture, whereas for trait anxiety, claustrophobia, and sensation seeking, no effect was detected. Also, subjects’ fear rating was moderated by all psychometrics but trait anxiety. In sum, both studies consistently indicate that humans show no general open arm avoidance analogous to rodents and that human EPM behavior is modulated strongest by acrophobic fear, whereas trait anxiety plays a subordinate role. Thus, we conclude that the criteria for cross-species validity are met insufficiently in this case. Despite the exploratory nature, our studies provide in-depth insights into human exploration behavior on the virtual EPM.
Die Erkennung handschriftlicher Artefakte wie Unterstreichungen in Buchdrucken ermöglicht Rückschlüsse auf das Rezeptionsverhalten und die Provenienzgeschichte und wird auch für eine OCR benötigt. Dabei soll zwischen handschriftlichen Unterstreichungen und waagerechten Linien im Druck (z. B. Trennlinien usw.) unterschieden werden, da letztere nicht ausgezeichnet werden sollen. Im Beitrag wird ein Ansatz basierend auf einem auf Unterstreichungen trainierten Neuronalen Netz gemäß der U-Net Architektur vorgestellt, dessen Ergebnisse in einem zweiten Schritt mit heuristischen Regeln nachbearbeitet werden. Die Evaluationen zeigen, dass Unterstreichungen sehr gut erkannt werden, wenn bei der Binarisierung der Scans nicht zu viele Pixel der Unterstreichung wegen geringem Kontrast verloren gehen. Zukünftig sollen die Worte oberhalb der Unterstreichung mit OCR transkribiert werden und auch andere Artefakte wie handschriftliche Notizen in alten Drucken erkannt werden.
Synthetically designed alternative photorespiratory pathways increase the biomass of tobacco and rice plants. Likewise, some in planta–tested synthetic carbon-concentrating cycles (CCCs) hold promise to increase plant biomass while diminishing atmospheric carbon dioxide burden. Taking these individual contributions into account, we hypothesize that the integration of bypasses and CCCs will further increase plant productivity. To test this in silico, we reconstructed a metabolic model by integrating photorespiration and photosynthesis with the synthetically designed alternative pathway 3 (AP3) enzymes and transporters. We calculated fluxes of the native plant system and those of AP3 combined with the inhibition of the glycolate/glycerate transporter by using the YANAsquare package. The activity values corresponding to each enzyme in photosynthesis, photorespiration, and for synthetically designed alternative pathways were estimated. Next, we modeled the effect of the crotonyl-CoA/ethylmalonyl-CoA/hydroxybutyryl-CoA cycle (CETCH), which is a set of natural and synthetically designed enzymes that fix CO₂ manifold more than the native Calvin–Benson–Bassham (CBB) cycle. We compared estimated fluxes across various pathways in the native model and under an introduced CETCH cycle. Moreover, we combined CETCH and AP3-w/plgg1RNAi, and calculated the fluxes. We anticipate higher carbon dioxide–harvesting potential in plants with an AP3 bypass and CETCH–AP3 combination. We discuss the in vivo implementation of these strategies for the improvement of C3 plants and in natural high carbon harvesters.
The successful development and classroom integration of Virtual (VR) and Augmented Reality (AR) learning environments requires competencies and content knowledge with respect to media didactics and the respective technologies. The paper discusses a pedagogical concept specifically aiming at the interdisciplinary education of pre-service teachers in collaboration with human-computer interaction students. The students’ overarching goal is the interdisciplinary realization and integration of VR/AR learning environments in teaching and learning concepts. To assist this approach, we developed a specific tutorial guiding the developmental process. We evaluate and validate the effectiveness of the overall pedagogical concept by analyzing the change in attitudes regarding 1) the use of VR/AR for educational purposes and in competencies and content knowledge regarding 2) media didactics and 3) technology. Our results indicate a significant improvement in the knowledge of media didactics and technology. We further report on four STEM learning environments that have been developed during the seminar.
To enable a sustainable supply of chemicals, novel biotechnological solutions are required that replace the reliance on fossil resources. One potential solution is to utilize tailored biosynthetic modules for the metabolic conversion of CO2 or organic waste to chemicals and fuel by microorganisms. Currently, it is challenging to commercialize biotechnological processes for renewable chemical biomanufacturing because of a lack of highly active and specific biocatalysts. As experimental methods to engineer biocatalysts are time- and cost-intensive, it is important to establish efficient and reliable computational tools that can speed up the identification or optimization of selective, highly active, and stable enzyme variants for utilization in the biotechnological industry. Here, we review and suggest combinations of effective state-of-the-art software and online tools available for computational enzyme engineering pipelines to optimize metabolic pathways for the biosynthesis of renewable chemicals. Using examples relevant for biotechnology, we explain the underlying principles of enzyme engineering and design and illuminate future directions for automated optimization of biocatalysts for the assembly of synthetic metabolic pathways.
Background: Since the replication crisis, standardization has become even more important in psychological science and neuroscience. As a result, many methods are being reconsidered, and researchers’ degrees of freedom in these methods are being discussed as a potential source of inconsistencies across studies.
New Method: With the aim of addressing these subjectivity issues, we have been working on a tutorial-like EEG (pre-)processing pipeline to achieve an automated method based on the semi-automated analysis proposed by Delorme and Makeig.
Results: Two scripts are presented and explained step-by-step to perform basic, informed ERP and frequency-domain analyses, including data export to statistical programs and visual representations of the data. The open-source software EEGlab in MATLAB is used as the data handling platform, but scripts based on code provided by Mike Cohen (2014) are also included.
Comparison with existing methods: This accompanying tutorial-like article explains and shows how the processing of our automated pipeline affects the data and addresses, especially beginners in EEG-analysis, as other (pre)-processing chains are mostly targeting rather informed users in specialized areas or only parts of a complete procedure. In this context, we compared our pipeline with a selection of existing approaches.
Conclusion: The need for standardization and replication is evident, yet it is equally important to control the plausibility of the suggested solution by data exploration. Here, we provide the community with a tool to enhance the understanding and capability of EEG-analysis. We aim to contribute to comprehensive and reliable analyses for neuro-scientific research.
Uplink vs. Downlink: Machine Learning-Based Quality Prediction for HTTP Adaptive Video Streaming
(2021)
Streaming video is responsible for the bulk of Internet traffic these days. For this reason, Internet providers and network operators try to make predictions and assessments about the streaming quality for an end user. Current monitoring solutions are based on a variety of different machine learning approaches. The challenge for providers and operators nowadays is that existing approaches require large amounts of data. In this work, the most relevant quality of experience metrics, i.e., the initial playback delay, the video streaming quality, video quality changes, and video rebuffering events, are examined using a voluminous data set of more than 13,000 YouTube video streaming runs that were collected with the native YouTube mobile app. Three Machine Learning models are developed and compared to estimate playback behavior based on uplink request information. The main focus has been on developing a lightweight approach using as few features and as little data as possible, while maintaining state-of-the-art performance.
Mapping and localization of mobile robots in an unknown environment are essential for most high-level operations like autonomous navigation or exploration. This paper presents a novel approach for combining estimated trajectories, namely curvefusion. The robot used in the experiments is equipped with a horizontally mounted 2D profiler, a constantly spinning 3D laser scanner and a GPS module. The proposed algorithm first combines trajectories from different sensors to optimize poses of the planar three degrees of freedom (DoF) trajectory, which is then fed into continuous-time simultaneous localization and mapping (SLAM) to further improve the trajectory. While state-of-the-art multi-sensor fusion methods mainly focus on probabilistic methods, our approach instead adopts a deformation-based method to optimize poses. To this end, a similarity metric for curved shapes is introduced into the robotics community to fuse the estimated trajectories. Additionally, a shape-based point correspondence estimation method is applied to the multi-sensor time calibration. Experiments show that the proposed fusion method can achieve relatively better accuracy, even if the error of the trajectory before fusion is large, which demonstrates that our method can still maintain a certain degree of accuracy in an environment where typical pose estimation methods have poor performance. In addition, the proposed time-calibration method also achieves high accuracy in estimating point correspondences.
Neural networks have to capture mathematical relationships in order to learn various tasks. They approximate these relations implicitly and therefore often do not generalize well. The recently proposed Neural Arithmetic Logic Unit (NALU) is a novel neural architecture which is able to explicitly represent the mathematical relationships by the units of the network to learn operations such as summation, subtraction or multiplication. Although NALUs have been shown to perform well on various downstream tasks, an in-depth analysis reveals practical shortcomings by design, such as the inability to multiply or divide negative input values or training stability issues for deeper networks. We address these issues and propose an improved model architecture. We evaluate our model empirically in various settings from learning basic arithmetic operations to more complex functions. Our experiments indicate that our model solves stability issues and outperforms the original NALU model in means of arithmetic precision and convergence.
The rating of perceived exertion (RPE) is a subjective load marker and may assist in individualizing training prescription, particularly by adjusting running intensity. Unfortunately, RPE has shortcomings (e.g., underreporting) and cannot be monitored continuously and automatically throughout a training sessions. In this pilot study, we aimed to predict two classes of RPE (≤15 “Somewhat hard to hard” on Borg’s 6–20 scale vs. RPE >15 in runners by analyzing data recorded by a commercially-available smartwatch with machine learning algorithms. Twelve trained and untrained runners performed long-continuous runs at a constant self-selected pace to volitional exhaustion. Untrained runners reported their RPE each kilometer, whereas trained runners reported every five kilometers. The kinetics of heart rate, step cadence, and running velocity were recorded continuously ( 1 Hz ) with a commercially-available smartwatch (Polar V800). We trained different machine learning algorithms to estimate the two classes of RPE based on the time series sensor data derived from the smartwatch. Predictions were analyzed in different settings: accuracy overall and per runner type; i.e., accuracy for trained and untrained runners independently. We achieved top accuracies of 84.8 % for the whole dataset, 81.8 % for the trained runners, and 86.1 % for the untrained runners. We predict two classes of RPE with high accuracy using machine learning and smartwatch data. This approach might aid in individualizing training prescriptions.
In this article, we present approaches to interactive simulations of biohybrid systems. These simulations are comprised of two major computational components: (1) agent-based developmental models that retrace organismal growth and unfolding of technical scaffoldings and (2) interfaces to explore these models interactively. Simulations of biohybrid systems allow us to fast forward and experience their evolution over time based on our design decisions involving the choice, configuration and initial states of the deployed biological and robotic actors as well as their interplay with the environment. We briefly introduce the concept of swarm grammars, an agent-based extension of L-systems for retracing growth processes and structural artifacts. Next, we review an early augmented reality prototype for designing and projecting biohybrid system simulations into real space. In addition to models that retrace plant behaviors, we specify swarm grammar agents to braid structures in a self-organizing manner. Based on this model, both robotic and plant-driven braiding processes can be experienced and explored in virtual worlds. We present an according user interface for use in virtual reality. As we present interactive models concerning rather diverse description levels, we only ensured their principal capacity for interaction but did not consider efficiency analyzes beyond prototypic operation. We conclude this article with an outlook on future works on melding reality and virtuality to drive the design and deployment of biohybrid systems.
Two studies are reported that investigate how readily accessible and applicable ten force-dynamic categories are to novices in describing short episodes of human-technology interaction (Study 1) and that establish a measure of inter-coder reliability when re-classifying these episodes into force-dynamic categories (Study 2). The results of the first study show that people can easily and confidently relate their experiences with technology to the definitions of force-dynamic events (e.g. “The driver released the handbrake” as an example of restraint removal). The results of the second study show moderate agreement between four expert coders across all ten force-dynamic categories (Cohen’s kappa = .59) when re-classifying these episodes. Agreement values for single force-dynamic categories ranged between ‘fair’ and ‘almost perfect’, i.e. between kappa = .30 and .95. Agreement with the originally intended classifications of study 1 was higher than the pure inter-coder reliabilities. Single coders achieved an average kappa of .71, indicating substantial agreement. Using more than one coder increased kappas to almost perfect: up to .87 for four coders. A qualitative analysis of the predicted versus the observed number of category confusions revealed that about half of the category disagreement could be predicted from strong overlaps in the definitions of force-dynamic categories. From the quantitative and qualitative results, guidelines are derived to aid the better training of coders in order to increase inter-coder reliability.
Failure prediction is an important aspect of self-aware computing systems. Therefore, a multitude of different approaches has been proposed in the literature over the past few years. In this work, we propose a taxonomy for organizing works focusing on the prediction of Service Level Objective (SLO) failures. Our taxonomy classifies related work along the dimensions of the prediction target (e.g., anomaly detection, performance prediction, or failure prediction), the time horizon (e.g., detection or prediction, online or offline application), and the applied modeling type (e.g., time series forecasting, machine learning, or queueing theory). The classification is derived based on a systematic mapping of relevant papers in the area. Additionally, we give an overview of different techniques in each sub-group and address remaining challenges in order to guide future research.
In the present day, unmanned aerial vehicles become seemingly more popular every year, but, without regulation of the increasing number of these vehicles, the air space could become chaotic and uncontrollable. In this work, a framework is proposed to combine self-aware computing with multirotor formations to address this problem. The self-awareness is envisioned to improve the dynamic behavior of multirotors. The formation scheme that is implemented is called platooning, which arranges vehicles in a string behind the lead vehicle and is proposed to bring order into chaotic air space. Since multirotors define a general category of unmanned aerial vehicles, the focus of this thesis are quadcopters, platforms with four rotors. A modification for the LRA-M self-awareness loop is proposed and named Platooning Awareness. The implemented framework is able to offer two flight modes that enable waypoint following and the self-awareness module to find a path through scenarios, where obstacles are present on the way, onto a goal position. The evaluation of this work shows that the proposed framework is able to use self-awareness to learn about its environment, avoid obstacles, and can successfully move a platoon of drones through multiple scenarios.
Semantic Fusion for Natural Multimodal Interfaces using Concurrent Augmented Transition Networks
(2018)
Semantic fusion is a central requirement of many multimodal interfaces. Procedural methods like finite-state transducers and augmented transition networks have proven to be beneficial to implement semantic fusion. They are compliant with rapid development cycles that are common for the development of user interfaces, in contrast to machine-learning approaches that require time-costly training and optimization. We identify seven fundamental requirements for the implementation of semantic fusion: Action derivation, continuous feedback, context-sensitivity, temporal relation support, access to the interaction context, as well as the support of chronologically unsorted and probabilistic input. A subsequent analysis reveals, however, that there is currently no solution for fulfilling the latter two requirements. As the main contribution of this article, we thus present the Concurrent Cursor concept to compensate these shortcomings. In addition, we showcase a reference implementation, the Concurrent Augmented Transition Network (cATN), that validates the concept’s feasibility in a series of proof of concept demonstrations as well as through a comparative benchmark. The cATN fulfills all identified requirements and fills the lack amongst previous solutions. It supports the rapid prototyping of multimodal interfaces by means of five concrete traits: Its declarative nature, the recursiveness of the underlying transition network, the network abstraction constructs of its description language, the utilized semantic queries, and an abstraction layer for lexical information. Our reference implementation was and is used in various student projects, theses, as well as master-level courses. It is openly available and showcases that non-experts can effectively implement multimodal interfaces, even for non-trivial applications in mixed and virtual reality.
This short letter proposes more consolidated explicit solutions for the forces and torques acting on typical rover wheels, that can be used as a method to determine their average mobility characteristics in planetary soils. The closed loop solutions stand in one of the verified methods, but at difference of the previous, observables are decoupled requiring a less amount of physical parameters to measure. As a result, we show that with knowledge of terrain properties, wheel driving performance rely in a single observable only. Because of their generality, the formulated equations established here can have further implications in autonomy and control of rovers or planetary soil characterization.
Lifetime techniques are applied to diverse fields of study including materials sciences, semiconductor physics, biology, molecular biophysics and photochemistry.
Here we present DDRS4PALS, a software for the acquisition and simulation of lifetime spectra using the DRS4 evaluation board (Paul Scherrer Institute, Switzerland) for time resolved measurements and digitization of detector output pulses. Artifact afflicted pulses can be corrected or rejected prior to the lifetime calculation to provide the generation of high-quality lifetime spectra, which are crucial for a profound analysis, i.e. the decomposition of the true information. Moreover, the pulses can be streamed on an (external) hard drive during the measurement and subsequently downloaded in the offline mode without being connected to the hardware. This allows the generation of various lifetime spectra at different configurations from one single measurement and, hence, a meaningful comparison in terms of analyzability and quality. Parallel processing and an integrated JavaScript based language provide convenient options to accelerate and automate time consuming processes such as lifetime spectra simulations.
Knowledge encoding in game mechanics: transfer-oriented knowledge learning in desktop-3D and VR
(2019)
Affine Transformations (ATs) are a complex and abstract learning content. Encoding the AT knowledge in Game Mechanics (GMs) achieves a repetitive knowledge application and audiovisual demonstration. Playing a serious game providing these GMs leads to motivating and effective knowledge learning. Using immersive Virtual Reality (VR) has the potential to even further increase the serious game’s learning outcome and learning quality. This paper compares the effectiveness and efficiency of desktop-3D and VR in respect to the achieved learning outcome. Also, the present study analyzes the effectiveness of an enhanced audiovisual knowledge encoding and the provision of a debriefing system. The results validate the effectiveness of the knowledge encoding in GMs to achieve knowledge learning. The study also indicates that VR is beneficial for the overall learning quality and that an enhanced audiovisual encoding has only a limited effect on the learning outcome.
The three-dimensional cuneiform script is one of the oldest known writing systems and a central object of research in Ancient Near Eastern Studies and Hittitology. An important step towards the understanding of the cuneiform script is the provision of opportunities and tools for joint analysis. This paper presents an approach that contributes to this challenge: a collaborative compatible web-based scientific exploration and analysis of 3D scanned cuneiform fragments. The WebGL -based concept incorporates methods for compressed web-based content delivery of large 3D datasets and high quality visualization. To maximize accessibility and to promote acceptance of 3D techniques in the field of Hittitology, the introduced concept is integrated into the Hethitologie-Portal Mainz, an established leading online research resource in the field of Hittitology, which until now exclusively included 2D content. The paper shows that increasing the availability of 3D scanned archaeological data through a web-based interface can provide significant scientific value while at the same time finding a trade-off between copyright induced restrictions and scientific usability.
The correct behavior of spacecraft components is the foundation of unhindered mission operation. However, no technical system is free of wear and degradation. A malfunction of one single component might significantly alter the behavior of the whole spacecraft and may even lead to a complete mission failure. Therefore, abnormal component behavior must be detected early in order to be able to perform counter measures. A dedicated fault detection system can be employed, as opposed to classical health monitoring, performed by human operators, to decrease the response time to a malfunction. In this paper, we present a generic model-based diagnosis system, which detects faults by analyzing the spacecraft’s housekeeping data. The observed behavior of the spacecraft components, given by the housekeeping data is compared to their expected behavior, obtained through simulation. Each discrepancy between the observed and the expected behavior of a component generates a so-called symptom. Given the symptoms, the diagnoses are derived by computing sets of components whose malfunction might cause the observed discrepancies. We demonstrate the applicability of the diagnosis system by using modified housekeeping data of the qualification model of an actual spacecraft and outline the advantages and drawbacks of our approach.