Due to the various demands for lecturers, there is only a limited time to prepare lectures and lab courses. therefore, it is necessary to invest the time target-oriented for optimal student learning success. A theoret...
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ISBN:
(纸本)9781665489089
Due to the various demands for lecturers, there is only a limited time to prepare lectures and lab courses. therefore, it is necessary to invest the time target-oriented for optimal student learning success. A theoretic model is developed to structure course preparation work regarding scientific content, didactic preparation, and course presentation. Model parameters have to be chosen for each course depending on topic complexity, the lecturer's prior knowledge, and the already available preparation from the prior semesters. Withthese parameters, a course preparation model for a complete semester is developed. Analytic models for different optimization strategies are introduced according to the overall goal of the lecturer. Numerical optimization is done to find the appropriate course preparation times to reach an optimal course preparation for high student learning success. It is seen that due to the different optimization strategies, the preparation time results vary and no single truth is given. But this optimizationsystem gives hints on how to invest preparation
this paper explores and designs a simulation training system for substation relay protection based on virtual reality technology. the system utilizes 3D Max for three-dimensional modeling. the inverse distance weight ...
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Ultrasound has become an essential tool for airway management, providing non-invasive, real-time imaging that enhances the procedure efficacy. the main challenges of ultrasound include the specialized training needed ...
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ISBN:
(纸本)9798331530143
Ultrasound has become an essential tool for airway management, providing non-invasive, real-time imaging that enhances the procedure efficacy. the main challenges of ultrasound include the specialized training needed for interpretation and the high patient variability. this paper presents ULTRA-AIR (Ultrasound Landmark Tracking for Real-time Anatomical Airway Identification and Reliability Check), a deep learning system designed for real-time tracking of multiple neck anatomical landmarks to assist with ultrasound-guided airway management. Uncertainty estimation was also computed to quantify model confidence scores, providing safety measures for trustworthy AI in real-time. Utilizing the YOLOv9 architecture, ULTRA-AIR was fine-tuned using Leave-One-Out cross-validation on neck ultrasound data collected from six human subjects, total of 3,060 images and 11,142 annotated bounding boxes. the system achieved AUCs of 0.99, 0.95, 0.89, and 0.77 for the classes of strap muscle, thyroid gland, tracheal ring, and thyroid cartilage, respectively. Average F1 score was 0.83 and mAP50 was 0.84. High uncertainty scores helped to identify cases needing human intervention. ULTRA-AIR shows promise for safe, accurate, and rapid airway assessments at point of care.
Engineering systems heavily rely on mathematical modeling, significantly influencing bothsystem performance and the design of control systems. this paper thoroughly investigates the establishment of a third-order mat...
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Maintenance tasks represent a potential area for applying multi-purpose Autonomous Mobile Robots (AMRs). Intelligent control and coordination of such a system is challenging and optimization methods are feasible only ...
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ISBN:
(数字)9781728175683
ISBN:
(纸本)9781728175683
Maintenance tasks represent a potential area for applying multi-purpose Autonomous Mobile Robots (AMRs). Intelligent control and coordination of such a system is challenging and optimization methods are feasible only for small fleets. Decentralized control can provide flexibility and robustness, which are better applicable also for large fleets, though with less guaranteed performance. Our focus is on flexibility and robustness in task scheduling and task assignments and we use entropy as an indirect performance criterion for coordination, both at the system level (maximize entropy) and at the AMR level (minimize entropy). As a distributed coordination scheme, we use a modified contract negotiation protocol. We show preliminarily the feasibility of our approach with simulation results.
this paper presents a numerical optimization scheme of a surface permanent magnet synchronous generator (SPMSG) for achieving maximum efficiency. the generator and engine are linked and the optimal operating line is i...
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ISBN:
(纸本)9798350344455
this paper presents a numerical optimization scheme of a surface permanent magnet synchronous generator (SPMSG) for achieving maximum efficiency. the generator and engine are linked and the optimal operating line is identified. A genetic algorithm is combined with a mesh adaptive direct search to create an intelligent memetic algorithm used to find the maximum efficiency distribution of SPMSG compatible to the OOL. the proposed optimization scheme includes both electrical and mechanical losses. Efficiency accuracy is confirmed by the resultant efficiency map. A prototype based on an optimized model is experimentally validated and shown to be well-suited for an EGS of a PHEV.
the advancement of technology has brought about significant transformations in various domains, including home security systems. this study has developed a systemthat enhances the functionality and security of smart ...
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the proceedings contain 121 papers. the topics discussed include: design and development of policy enforcement for the privacy by design framework;using a correlation equation to ensure stability between personalizati...
ISBN:
(纸本)9798350319439
the proceedings contain 121 papers. the topics discussed include: design and development of policy enforcement for the privacy by design framework;using a correlation equation to ensure stability between personalization and security in composing web services;leveraging nucleotide dependencies for improved mRNA vaccine degradation prediction;using machine learning for earthquakes and quarry blasts discrimination;an overview of the image description systems in Arabic language;a data collection platform for network management;strategies for optimizing time series visual data exploration;DLA-ABIDS: deep learning approach for anomaly based intrusion detection system;graph-based indoor navigation system using BIM data and optimization algorithms;and traffic accident management system for intelligent and sustainable vehicle networking.
Cooperative topology of Participle Swarm optimization (PSO) heuristic (CPSO) is implemented for system identification over ad-hoc Networks. the main achievement is the development of PSO heuristic for system identific...
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the proceedings contain 33 papers. the special focus in this conference is on Information Processing and Management of Uncertainty in Knowledge-Based systems. the topics include: Graphical Causal Models with Disc...
ISBN:
(纸本)9783031739996
the proceedings contain 33 papers. the special focus in this conference is on Information Processing and Management of Uncertainty in Knowledge-Based systems. the topics include: Graphical Causal Models with Discretized Data and Background Information;enhancing the Intelligibility of Boolean Decision Trees with Concise and Reliable Probabilistic Explanations;towards an Interpretable Fuzzy Approach to Experimental Design;from Default to Analogical and Paralogical Reasoning. Logics of Pairs and their Multiple-Valued Extensions;lot Sizing Problem Under Lead-Time Uncertainty;forced Periodic Optimal Scheduling Policy for Graph Reinforcement Learning;similarity Relations Based Numerical Algorithm for Solving Maximin Problems;possibilistic Approach for Meta-analysis;Dual Resource Flexible Job Shop Scheduling Problems: the xBTF Algorithm;information Retrieval Using Fuzzy Fingerprints;Handling Veracity of SVM Predictions;interval Criterion-Based Evidential Set-Valued Classification;analysis of the φ-Index of Inclusion Restricted to a Set of Indexes;enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search;from Quantifying and Propagating Uncertainty to Quantifying and Propagating Both Uncertainty and Reliability: Practice-Motivated Approach to Measurement Planning and Data Processing;extending Idioms for Bayesian Network Construction with Qualitative Constraints;optimizing Causal Interventions in Hybrid Bayesian Networks: A Discretization, Knowledge Compilation, and Heuristic optimization Approach;visualization of Preference Matrices for Labeled Objects;assessing Causal Graph Uncertainty and Optimized Multivariate Discretization Strategy;exploring Word Embedding in modeling Risk Perception;similarity of Concepts in Weighted Knowledge Graphs;evidential Linear Regression for Soft Detrended Fluctuation Analysis;COPILS: COmParIson of Linguistic Summaries;groupoids in Categories of Fuzzy Topological Spaces with Continuous Fuzzy Relations;preface;On the Use of Mo
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