Refine
Year of publication
- 2023 (181) (remove)
Document Type
- Article (63)
- Conference Proceeding (47)
- Report (18)
- Part of a Book (13)
- Bachelor Thesis (9)
- Master's Thesis (7)
- Doctoral Thesis (6)
- Book (5)
- Working Paper (4)
- Journal (Complete Issue of a Journal) (3)
Language
- English (99)
- German (81)
- Multiple languages (1)
Keywords
- 1D-CNN (1)
- 3D Extended Object Tracking (1)
- 3D shape tracking (1)
- 3D urban planning (1)
- 3D-Druck (1)
- 5-10-40-Bedingung (1)
- ASEAN (1)
- Abwärmenutzung (1)
- Accelerometer (2)
- Accelerometer calibration (1)
- Accelerometer sensor (1)
- Accelerometers (1)
- Adapted business models design for sustainability (aDBMfS) (1)
- Adaption (1)
- Adolescent idiopathic scoliosis (1)
- Adoption (1)
- Agile administration (1)
- Allegation (1)
- Anticipation (1)
- Apnea detection (1)
- Arbeitsmarkt (1)
- Architektur (1)
- Artificial intelligence (1)
- Artificial intelligence models (1)
- Autoethnography (1)
- Automatic sleep assessment (1)
- Automobiles (1)
- Autonomous vessels (1)
- BCG signal (1)
- BIPV (1)
- BISOL (1)
- Backstepping control (1)
- Ballistocardiography (2)
- Bayesian parameter estimation (1)
- Berechnung (1)
- Berechnungsverfahren (1)
- Bernstein polynomial (1)
- Bi-LSTM Model (1)
- Bildgeneratoren (1)
- Body Position (1)
- Boids Flocking Algorithm (1)
- Branch&Bound (1)
- Buchenfurnierschichtholz (1)
- Building with earth (2)
- Bullock carts (1)
- Business Idea Quality (1)
- CDE (1)
- CEFR (1)
- COBIT Components (1)
- Capital project performance (1)
- Cardiac activity (1)
- Cardiorespiratory parameters (2)
- Carroll, Archie B. (1)
- Case Study (1)
- Case studies (1)
- Challenges (1)
- Channel estimation (1)
- China (1)
- Circular economy (2)
- Citizen Development (1)
- Classification (1)
- Climate action (1)
- Climate change (3)
- Climate communication (1)
- Climate policies and strategies (1)
- Climate resilience (1)
- Co-Specialization (1)
- Co-specialization (1)
- Code-based cryptography (1)
- Collaboration (1)
- Colonial history (1)
- Combinations (1)
- Common Data Environment (1)
- Common goods (1)
- Component (1)
- Comprehensive quality management (1)
- Compressed earth (2)
- Computer Science Applications (1)
- Conflict (1)
- Construction industry (1)
- Contactless measurement (2)
- Contactless technologies (1)
- Control (1)
- Cooperatives (1)
- Coronal alignment (1)
- Coronal balance (1)
- Corporate Entrepreneurship (2)
- Corporate Venturing (1)
- Corporate entrepreneurship (2)
- Corporate misconduct (1)
- Corporate venturing (1)
- Cost-benefit analysis (1)
- Covid-19 (1)
- Creative Coding (1)
- Customer Journey (1)
- Customer integration (1)
- DGNB Version 2023 (1)
- DIN 4149 (1)
- DIN EN 1998-1 (1)
- Dance (1)
- Data (1)
- Data analytics (1)
- Data cooperatives (1)
- Data governance (1)
- Data sharing and exchange (1)
- Data sovereignty (2)
- Data stewardship (1)
- Data-driven learning (1)
- Decarbonisation (1)
- Decarbonization (1)
- Deep Learning (1)
- Deep learning (3)
- Demolition wastes (2)
- Design-Science Research (2)
- Development (1)
- Developmental state (1)
- Dienstleistungsmanagement (1)
- Digital Health (1)
- Digital Services (1)
- Digital commons (1)
- Digital platforms (1)
- Digital transformation (2)
- Digitalisierung (4)
- Digitalization (1)
- Digizalization (1)
- Distributional regression (1)
- Diversity (1)
- Downsampling (1)
- Driver Assistance Systems (1)
- Driving simulator (1)
- Dynamic Capabilities (1)
- EG-Richtlinie 2009/65/EC Artikel 52(2) (1)
- EPQR (1)
- EPQR-S (1)
- EU-Taxonomie (1)
- EW/TTS (1)
- Economic Sustainability (1)
- Edward Soja (1)
- Effizienzsteigerung (1)
- Einzelhandel (3)
- Elastic domes (1)
- Electrical and Electronic Engineering (1)
- Electrocardiographic signals (1)
- Electronic early warning (1)
- Elliptic Cylinder (1)
- Energieeffizientes Bauen (1)
- Energy transition (1)
- Entrepreneurial Ecosystems (2)
- Entrepreneurial motivation (1)
- Entrepreneurship Education (1)
- Entrepreneurship Support (1)
- Entwerfen (1)
- Erdbebennorm (1)
- Evaluation (1)
- Expert Interviews (1)
- Expert systems (1)
- Experteninterviews (1)
- Extended object tracking (2)
- Extension estimation (1)
- Extent estimation (1)
- FSR Sensors (1)
- FSR sensors (1)
- Female Entrepreneurship (2)
- Female entrepreneurship (1)
- Financial sustainability (1)
- Forcesensitive resistor sensors (1)
- Formatting (1)
- Fourier-Chebyshev double series (1)
- Freistellungssemesterbericht (15)
- Funds (1)
- GIS (1)
- GRC (2)
- Gaussian processes (1)
- Gebäudedesign (1)
- Geldpolitik (1)
- Gender (1)
- Generalized concatenated codes (1)
- Generalized multistream spatial modulation (1)
- Generation Z (3)
- Geotechnik im Hochbau (1)
- German Industry (1)
- Geschäftsmodelle (1)
- Goals (1)
- Governance (1)
- Grasshopper (1)
- Gravity-based in-field calibration (1)
- Green bridge (1)
- Greening campus (1)
- Grey box modeling (1)
- Hardware and Architecture (1)
- Hardware prototyping (1)
- Health monitoring (4)
- Health monitoring systems (1)
- Heart rate (2)
- Heart rate estimation (1)
- Heart rate variability (HRV) (1)
- Higher education (2)
- Human activity recognition (1)
- Human-Computer Interaction (1)
- IT Cost Management (1)
- IT Governance (1)
- IT-Compliance (2)
- IT-Governance (1)
- India (1)
- Indonesian language (1)
- Indonesisches Nationalmuseum (1)
- Industrial heating process (1)
- Inertial measurement unit (IMU) (1)
- Information Exchange (1)
- Information Security Management (1)
- Infrastructure (2)
- Innovationen (1)
- Insert tech ventures (1)
- Integrative approach (1)
- Intelligent Swarming (1)
- Interoperability (1)
- Interwar period (1)
- Investitionsgüter-Service (1)
- Investitionsgüterindustrie (2)
- Investitionsgüterservice (1)
- Investor reaction (1)
- J-Peak (1)
- Japan (1)
- KI (1)
- KI-Kunst (1)
- KMU (1)
- Kapitalanlagegesetzbuch (KAGB) § 206 (1)
- Kleinwasserkraft (1)
- Kleinwindkraftanlage (1)
- Klimaresiliente Stadtentwicklung (1)
- Klimasimulationen (1)
- Knowledge Centered Service (1)
- Knowledge Transfer (1)
- Knowledge management (1)
- Korpuslinguistik (1)
- Kraft-Wärme-Kopplung (1)
- Krise (1)
- Kunst (1)
- Künstliche Intelligenz (2)
- Land value capture (1)
- Lane Association (1)
- Lazgi (1)
- Lehm (1)
- LiDAR (1)
- Lidar (1)
- Lineare Portfoliooptimierung (1)
- Literature Review (1)
- Literature review (1)
- Long-term care (1)
- Low-Code Development Plattformen (1)
- Low-Voltage (1)
- Low-carbon construction (2)
- Low-complexity detection (1)
- Low-cost IMU calibration (1)
- MCDA (1)
- MPC (1)
- Machine Learning Algorithms (1)
- Machine learning (3)
- Management Routines (1)
- Maori tourism (1)
- Maori values (1)
- Marketingrecht (1)
- Markov chain Monte Carlo (MCMC) (1)
- Mashine learning (1)
- McEliece cryptosystem (1)
- Mechatronic systems (1)
- Micro-electro-mechanical systems (MEMSs) (1)
- Minea Design (1)
- Mitigation (1)
- Model predictive control (1)
- Modellfabrik (1)
- Moderner Lehmbau (1)
- Multiple units (1)
- Multiposition calibration (1)
- Multistage detection (1)
- Multivariate rational function (1)
- Museumstourismus (1)
- NA 2021-07 (1)
- Neural network (2)
- Neural networks (1)
- Nichtwohngebäude (1)
- Non-volatile NAND flash (1)
- Nonlinear least squares problem (1)
- Nonlinear system identification (1)
- Nonlinear systems (1)
- Normalizing Flows (1)
- ODH framework (1)
- Objective and subjective sleep measurement (1)
- Observability (1)
- Obstructive sleep apnea (1)
- One Health (1)
- Online travel reviews (1)
- Open data (1)
- Open digital federation platform (1)
- PHP (1)
- PSQ (1)
- Packaging (1)
- Personality trait (1)
- Personenstromsimulation (1)
- Physiological signals (1)
- Polysomnography system (PSG) (1)
- Portable monitor (1)
- Portfolio Management (1)
- Portfolio Optimierung (1)
- Post-growth economy (1)
- Post-quantum public-key cryptography (1)
- Principles of Blockchain Technology (1)
- Probabilistic Load Forecasting (1)
- Probabilistic Regression (1)
- Probability of Exploitation (1)
- Productivity (1)
- Public engagement (1)
- Quadratische Portfoliooptimierung (1)
- Quality management (1)
- Quality of life (1)
- Radolfzeller Aach (1)
- Radsatz-Torsionsmoment (1)
- Rammed earth (2)
- Random matrices (2)
- Range enclosure (1)
- Read reference adjustment (1)
- Reconstruction (1)
- Recycled materials (2)
- Refactoring (1)
- Reference model (1)
- Regelung (1)
- Remediation Strategies (1)
- Remote sensing (1)
- Research (1)
- Resilience (1)
- Respiration rate (1)
- Revised eysenck personality questionnaire (1)
- Rezension (1)
- Road Infrastructure Projects (1)
- Road transport (1)
- Rotordynamics (1)
- Runtime Reduction (1)
- SIRM (1)
- SME (2)
- SQLi (1)
- Scheinselbständigkeit (1)
- Schlafstadien (1)
- Scoring Systems (1)
- Segmentation (1)
- Selbsterregte Schwingung (1)
- Self Service (1)
- Sensitivity matrix (1)
- Sensor data (1)
- Sensor fusion (1)
- Sensors (1)
- Sensors fusion (1)
- Service Management (1)
- Service business model (1)
- Servicemanagement (1)
- Seychelles (1)
- Shape Tracking (1)
- Shape classification (1)
- Signal processing (2)
- Sleep Apnea (1)
- Sleep apnea (1)
- Sleep diary (1)
- Sleep efficiency (3)
- Sleep measurements (1)
- Sleep medicine (1)
- Sleep monitoring (3)
- Sleep monitoring systems (1)
- Sleep scoring (1)
- Sleep stages (1)
- Sleep study (4)
- Small and medium-sized enterprises (2)
- Smart Services (1)
- Smart services (1)
- Smart-home (1)
- Smartwatch (1)
- Social innovations (1)
- Social life cycle assessment integration into PLM System (1)
- Social life cycle sustainability assessment (SLSA) (1)
- Solar drying (1)
- Solaraktive Gebäudehülle (1)
- Solararchitektur (1)
- Southeast Asia (1)
- Spillover (1)
- Spinal deformity (1)
- Stadtgeschichte (1)
- Stadtplanung (1)
- Stampflehmherstellung (1)
- Startups (1)
- Static code analysis (1)
- Stationary Retail (1)
- Statistical data analysis (1)
- Stochastische Programmierung (1)
- Storage (1)
- Strategic Renewal (1)
- Strategic approaches (1)
- Stress (2)
- Style (1)
- Styling (1)
- Städtebau (2)
- Subjective sleep assessment (3)
- Sufficiency (1)
- Support Units (1)
- Surgical planning (1)
- Surrogate Modell (1)
- Survey systems (1)
- Sustainability (1)
- Sustainable construction (2)
- Sustainable development (1)
- Sustainable infrastructure (1)
- System dynamics modelling (1)
- Systematic Literature Review (1)
- Systemdenken (1)
- Systemisches Denken (1)
- Target Discrimination (1)
- Teaching (1)
- Teaching material (1)
- Text mining (1)
- Thirdspace (1)
- Tomato powder (1)
- Total quality management (1)
- Tourism (1)
- Tourismus (1)
- Track and triage system (1)
- Trajectory tracking (1)
- Transformation models (1)
- TripAdvisor (1)
- Türkei (1)
- Umrechnungsfaktor (1)
- Uncertainty (1)
- Unobtrusive measurement (1)
- Urban adaptation to global climate change (1)
- Uzbekistan (1)
- Value networks (1)
- Value-networks (1)
- Venture creation business model (1)
- Virtual measurement model (1)
- Vital signals (1)
- Vulnerability Pattern (1)
- Vulnerability Prioritization (1)
- Wasserkraft (1)
- Wavelet signal processing (1)
- Wearable device (1)
- Wearables (1)
- Web security (1)
- Website-Marketing (1)
- Wirkungszusammenhänge (1)
- Wirtschaftspolitik (1)
- Wissensmanagement (4)
- Wärmepumpe (1)
- X-ray (1)
- XSS (1)
- eHealth (1)
- zirkuläre und automatisierte Bauweisen (1)
Institute
- Fakultät Architektur und Gestaltung (5)
- Fakultät Bauingenieurwesen (23)
- Fakultät Elektrotechnik und Informationstechnik (3)
- Fakultät Informatik (7)
- Fakultät Maschinenbau (6)
- Fakultät Wirtschafts-, Kultur- und Rechtswissenschaften (17)
- Institut für Angewandte Forschung - IAF (31)
- Institut für Naturwissenschaften und Mathematik - INM (1)
- Institut für Optische Systeme - IOS (4)
- Institut für Strategische Innovation und Technologiemanagement - IST (12)
Background
This is a systematic review protocol to identify automated features, applied technologies, and algorithms in the electronic early warning/track and triage system (EW/TTS) developed to predict clinical deterioration (CD).
Methodology
This study will be conducted using PubMed, Scopus, and Web of Science databases to evaluate the features of EW/TTS in terms of their automated features, technologies, and algorithms. To this end, we will include any English articles reporting an EW/TTS without time limitation. Retrieved records will be independently screened by two authors and relevant data will be extracted from studies and abstracted for further analysis. The included articles will be evaluated independently using the JBI critical appraisal checklist by two researchers.
Discussion
This study is an effort to address the available automated features in the electronic version of the EW/TTS to shed light on the applied technologies, automated level of systems, and utilized algorithms in order to smooth the road toward the fully automated EW/TTS as one of the potential solutions of prevention CD and its adverse consequences.
Recognizing Human Activity of Daily Living Using a Flexible Wearable for 3D Spine Pose Tracking
(2023)
The World Health Organization recognizes physical activity as an influencing domain on quality of life. Monitoring, evaluating, and supervising it by wearable devices can contribute to the early detection and progress assessment of diseases such as Alzheimer’s, rehabilitation, and exercises in telehealth, as well as abrupt events such as a fall. In this work, we use a non-invasive and non-intrusive flexible wearable device for 3D spine pose measurement to monitor and classify physical activity. We develop a comprehensive protocol that consists of 10 indoor, 4 outdoor, and 8 transition states activities in three categories of static, dynamic, and transition in order to evaluate the applicability of the flexible wearable device in human activity recognition. We implement and compare the performance of three neural networks: long short-term memory (LSTM), convolutional neural network (CNN), and a hybrid model (CNN-LSTM). For ground truth, we use an accelerometer and strips data. LSTM reached an overall classification accuracy of 98% for all activities. The CNN model with accelerometer data delivered better performance in lying down (100%), static (standing = 82%, sitting = 75%), and dynamic (walking = 100%, running = 100%) positions. Data fusion improved the outputs in standing (92%) and sitting (94%), while LSTM with the strips data yielded a better performance in bending-related activities (bending forward = 49%, bending backward = 88%, bending right = 92%, and bending left = 100%), the combination of data fusion and principle components analysis further strengthened the output (bending forward = 100%, bending backward = 89%, bending right = 100%, and bending left = 100%). Moreover, the LSTM model detected the first transition state that is similar to fall with the accuracy of 84%. The results show that the wearable device can be used in a daily routine for activity monitoring, recognition, and exercise supervision, but still needs further improvement for fall detection.
Cardiovascular diseases (CVD) are leading contributors to global mortality, necessitating advanced methods for vital sign monitoring. Heart Rate Variability (HRV) and Respiratory Rate, key indicators of cardiovascular health, are traditionally monitored via Electrocardiogram (ECG). However, ECG's obtrusiveness limits its practicality, prompting the exploration of Ballistocardiography (BCG) as a non-invasive alternative. BCG records the mechanical activity of the body with each heartbeat, offering a contactless method for HRV monitoring. Despite its benefits, BCG signals are susceptible to external interference and present a challenge in accurately detecting J-Peaks. This research uses advanced signal processing and deep learning techniques to overcome these limitations. Our approach integrates accelerometers for long-term BCG data collection during sleep, applying Discrete Wavelet Transforms (DWT) and Ensemble Empirical Mode Decomposition (EEMD) for feature extraction. The Bi-LSTM model, leveraging these features, enhances heartbeat detection, offering improved reliability over traditional methods. The study's findings indicate that the combined use of DWT, EEMD, and Bi-LSTM for J-Peak detection in BCG signals is effective, with potential applications in unobtrusive long-term cardiovascular monitoring. Our results suggest that this methodology could contribute to HRV monitoring, particularly in home settings, enhancing patient comfort and compliance.
Measuring cardiorespiratory parameters in sleep, using non-contact sensors and the Ballistocardiography technique has received much attention due to the low-cost, unobtrusive, and non-invasive method. Designing a user-friendly, simple-to-use, and easy-to-deployment preserving less errorprone remains open and challenging due to the complex morphology of the signal. In this work, using four forcesensitive resistor sensors, we conducted a study by designing four distributions of sensors, in order to simplify the complexity of the system by identifying the region of interest for heartbeat and respiration measurement. The sensors are deployed under the mattress and attached to the bed frame without any interference with the subjects. The four distributions are combined in two linear horizontal, one linear vertical, and one square, covering the influencing region in cardiorespiratory activities. We recruited 4 subjects and acquired data in four regular sleeping positions, each for a duration of 80 seconds. The signal processing was performed using discrete wavelet transform bior 3.9 and smooth level of 4 as well as bandpass filtering. The results indicate that we have achieved the mean absolute error of 2.35 and 4.34 for respiration and heartbeat, respectively. The results recommend the efficiency of a triangleshaped structure of three sensors for measuring heartbeat and respiration parameters in all four regular sleeping positions.
Sleep is a multi-dimensional influencing factor on physical health, cognitive function, emotional well-being, mental health, daily performance, and productivity. The barriers such as time-consuming, invasiveness, and expense have caused a gradual shift in sleep monitoring from traditional and standard in-lab approach, e. g., polysomnography (PSG) to unobtrusive and noninvasive in-home sleep monitoring, yet further improvement is required. Despite an increasing interest in fiberoptic-based methods for cardiorespiratory estimation, the traditional mechanical-based sensors consist of force-sensitive resistors (FSR), lead zirconate titanate piezoelectric (PZT), and accelerometers yet serve as the dominant approach. The part of popularity lies in reducing the system’s complexity, expense, easy maintenance, and user-friendliness. However, care must be taken regarding the performance of such sensors with respect to accuracy and calibration.
Contemporary empirical applications frequently require flexible regression models for complex response types and large tabular or non-tabular, including image or text, data. Classical regression models either break down under the computational load of processing such data or require additional manual feature extraction to make these problems tractable. Here, we present deeptrafo, a package for fitting flexible regression models for conditional distributions using a tensorflow backend with numerous additional processors, such as neural networks, penalties, and smoothing splines. Package deeptrafo implements deep conditional transformation models (DCTMs) for binary, ordinal, count, survival, continuous, and time series responses, potentially with uninformative censoring. Unlike other available methods, DCTMs do not assume a parametric family of distributions for the response. Further, the data analyst may trade off interpretability and flexibility by supplying custom neural network architectures and smoothers for each term in an intuitive formula interface. We demonstrate how to set up, fit, and work with DCTMs for several response types. We further showcase how to construct ensembles of these models, evaluate models using inbuilt cross-validation, and use other convenience functions for DCTMs in several applications. Lastly, we discuss DCTMs in light of other approaches to regression with non-tabular data.
Die Kleinwasserkraft stand zuletzt zunehmend in der öffentlichen Kritik wegen des ökologischen Einflusses und der verhältnismäßigen geringen Stromerzeugung. Der vorliegende Beitrag beschreibt die Einschätzung von KWK-Betreibern zum Potenzial einer Effizienzsteigerung ihrer bestehenden Anlagen durch eine intelligente Informationsvernetzung innerhalb des Flusslaufes der Radolfzeller Aach im Süden Baden-Württembergs, um somit die Stromerzeugung der einzelnen Anlagen zu erhöhen.
Short-Term Density Forecasting of Low-Voltage Load using Bernstein-Polynomial Normalizing Flows
(2023)
The transition to a fully renewable energy grid requires better forecasting of demand at the low-voltage level to increase efficiency and ensure reliable control. However, high fluctuations and increasing electrification cause huge forecast variability, not reflected in traditional point estimates. Probabilistic load forecasts take uncertainties into account and thus allow more informed decision-making for the planning and operation of low-carbon energy systems. We propose an approach for flexible conditional density forecasting of short-term load based on Bernstein polynomial normalizing flows, where a neural network controls the parameters of the flow. In an empirical study with 3639 smart meter customers, our density predictions for 24h-ahead load forecasting compare favorably against Gaussian and Gaussian mixture densities. Furthermore, they outperform a non-parametric approach based on the pinball loss, especially in low-data scenarios.