Depression is a common mental health *** current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary measures for ...
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Depression is a common mental health *** current depression detection methods,specialized physicians often engage in conversations and physiological examinations based on standardized scales as auxiliary measures for depression ***-biological markers-typically classified as verbal or non-verbal and deemed crucial evaluation criteria for depression-have not been effectively *** physicians usually require extensive training and experience to capture changes in these *** in deep learning technology have provided technical support for capturing non-biological *** researchers have proposed automatic depression estimation(ADE)systems based on sounds and videos to assist physicians in capturing these features and conducting depression *** article summarizes commonly used public datasets and recent research on audio-and video-based ADE based on three perspectives:Datasets,deficiencies in existing research,and future development directions.
Deep learning (DL) models are popular across various domains due to their remarkable performance and efficiency. However, their effectiveness relies heavily on large amounts of labeled data, which are often time-consu...
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Hand sign recognition is a vital technology in the human-computer interaction, enabling individuals to communicate with machines naturally and effectively. An innovative approach for real-time hand sign identification...
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Time-Sensitive Networking enhances Ethernet-based In-Vehicle Networks (IVNs) with real-time capabilities. Different traffic shaping algorithms have been proposed for time-critical communication, of which the Asynchron...
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ISBN:
(数字)9798331524371
ISBN:
(纸本)9798331524388
Time-Sensitive Networking enhances Ethernet-based In-Vehicle Networks (IVNs) with real-time capabilities. Different traffic shaping algorithms have been proposed for time-critical communication, of which the Asynchronous Traffic Shaper (ATS) is an upcoming candidate. However, recent research has shown that ATS can introduce unbounded latencies when shaping traffic from non-FIFO systems. This impacts the applicability of ATS in IVNs, as these networks often use redundancy mechanisms, i.e. Frame Replication and Elimination for Reliability (FRER), that can cause non-FIFO behavior. In this paper, we approach the problem of accumulated delays from ATS by analyzing the scenarios that generate latency and by devising placement and configuration methods for ATS schedulers to prevent this behavior. We evaluate our approach in a simulation environment and show how it prevents conditions of unbounded delays. In an IVN simulation case study, we demonstrate the occurrence of unbounded latencies in a realistic scenario and validate the effectiveness of our solutions in avoiding them.
Air pollution is one of the most common problems that the world is facing today. In fact, there are numerous causes of air pollution, including the large number of industries and automobiles that emit carbon dioxide (...
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This research aims to break communication barriers for the deaf and hard-of-hearing by pioneering a real-time, dynamic sign language translator. Unlike existing apps, it uses a CNN to translate simultaneously between ...
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The rapid advancement of smart home technologies necessitates efficient human activity recognition (HAR) systems while ensuring user privacy. This research presents a novel architecture that integrates deep learning a...
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We present GauKGT5, a sequence-to-sequence model proposed for knowledge graph completion (KGC). Our research extends the KGT5 model, a recent sequence-to-sequence link prediction (LP) model. GauKGT5 takes advantage of...
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Though the Butterfly Bptimization Algorithm(BOA)has already proved its effectiveness as a robust optimization algorithm,it has certain ***,a new variant of BOA,namely mLBOA,is proposed here to improve its *** proposed...
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Though the Butterfly Bptimization Algorithm(BOA)has already proved its effectiveness as a robust optimization algorithm,it has certain ***,a new variant of BOA,namely mLBOA,is proposed here to improve its *** proposed algorithm employs a self-adaptive parameter setting,Lagrange interpolation formula,and a new local search strategy embedded with Levy flight search to enhance its searching ability to make a better trade-off between exploration and ***,the fragrance generation scheme of BOA is modified,which leads for exploring the domain effectively for better *** evaluate the performance,it has been applied to solve the IEEE CEC 2017 benchmark *** results have been compared to that of six state-of-the-art algorithms and five BOA ***,various statistical tests,such as the Friedman rank test,Wilcoxon rank test,convergence analysis,and complexity analysis,have been conducted to justify the rank,significance,and complexity of the proposed ***,the mLBOA has been applied to solve three real-world engineering design *** all the analyses,it has been found that the proposed mLBOA is a competitive algorithm compared to other popular state-of-the-art algorithms and BOA variants.
This paper proposes a modified version of the Dwarf Mongoose Optimization Algorithm (IDMO) for constrained engineering design problems. This optimization technique modifies the base algorithm (DMO) in three simple but...
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This paper proposes a modified version of the Dwarf Mongoose Optimization Algorithm (IDMO) for constrained engineering design problems. This optimization technique modifies the base algorithm (DMO) in three simple but effective ways. First, the alpha selection in IDMO differs from the DMO, where evaluating the probability value of each fitness is just a computational overhead and contributes nothing to the quality of the alpha or other group members. The fittest dwarf mongoose is selected as the alpha, and a new operator ω is introduced, which controls the alpha movement, thereby enhancing the exploration ability and exploitability of the IDMO. Second, the scout group movements are modified by randomization to introduce diversity in the search process and explore unvisited areas. Finally, the babysitter's exchange criterium is modified such that once the criterium is met, the babysitters that are exchanged interact with the dwarf mongoose exchanging them to gain information about food sources and sleeping mounds, which could result in better-fitted mongooses instead of initializing them afresh as done in DMO, then the counter is reset to zero. The proposed IDMO was used to solve the classical and CEC 2020 benchmark functions and 12 continuous/discrete engineering optimization problems. The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms.
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