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Emerging Trends in Electrical, Control, and Telecommunication engineering (ETECTE), International Conference on

作者： Ghulam Abbas Arshad Ali Muhammad Zubair Zohaib Mushtaq Umar Farooq Irfan A. Khan Department of Electrical Engineering The University of Lahore Lahore Pakistan Faculty of Computer and Information Systems Islamic University of Madinah Madinah Saudi Arabia College of Engineering and Technology University of Doha for Science and Technology Doha Qatar Department of Electrical Electronics and Computer Systems University of Sargodha Sargodha Pakistan Intelligent Systems Lab & Automation Facility (ISLAF) IEECE University of the Punjab Lahore Pakistan Clean and Resilient Energy Systems (CARES) Lab Texas A&M University Galveston TX USA

ISBN: (数字)9798331504861

ISBN: (纸本)9798331504878

To assess the wind power potential of a specific wind site, a suitable distribution function that best suits the wind data needs to be known. In this study, we employ four probability density functions (PDFs), namely Weibull, Rayleigh, Log-Normal, and Gamma, on wind speed data obtained from two coastal cities in Pakistan, Gwadar and Karachi, to check which one is the best suited. Cities along the coastline of Pakistan offer greater wind speeds and, thus, greater wind power potential. The maximum likelihood technique is used to estimate the parameters of the density distributions. Three statistical measures-Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R 2 )-are used to assess the goodness of fit for every distribution. These measures give a complete picture of every distribution's correctness in terms of reflecting the recorded wind speed patterns. Numerical results reveal that the Weibull distribution fits well with the wind speeds of the two coastal cities compared to the other three probability distributions, providing insightful analysis for the evaluation of wind resources and possible local energy generation. The MATLAB environment is used to compare the distributions and validate the effectiveness of the proposed methodology.

关键词： Wind energy generation Electric potential Wind energy Wind speed Urban areas Sea measurements Wind power generation Probability density function Probability distribution Weibull distribution

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Distributed Event-Triggered Bandit Convex Optimization With Time-Varying Constraints

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IEEE Transactions on Control of Network Systems 2025年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Ministry of Education Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China Southeast University School of Automation Nanjing210096 China University of Groningen Engineering and Technology Institute Groningen Faculty of Science and Engineering GroningenAG 9747 Netherlands KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm10044 Sweden KTH Royal Institute of Technology Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms solving this problem require that each agent broadcasts its decision to its neighbors at each iteration. However, communication resources are often limited. To better utilize communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. © 2014 IEEE.

关键词： Optimization algorithms

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Exploiting the Intrinsic Neighborhood Semantic Structure for Domain Adaptation in EEG-based Emotion Recognition

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IEEE Transactions on Affective Computing 2025年

作者： Yang, Yi Wang, Ze Song, Yu Jia, Ziyu Wang, Boyu Jung, Tzyy-Ping Wan, Feng Macau University of Science and Technology Macao Centre for Mathematical Sciences Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications Faculty of Innovation Engineering 999078 China Tianjin University of Technology School of Electrical Engineering and Automation Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin300384 China Chinese Academy of Sciences Beijing Key Laboratory of Brainnetome and Brain-Computer Interface and Brainnetome Center Institute of Automation Beijing100045 China Western University Department of Computer Science Brain Mind Institute LondonONN6A 3K7 Canada University of California at San Diego Swartz Center for Computational Neuroscience Institute for Neural Computation La Jolla CA92093 United States University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology China University of Macau Centre for Cognitive and Brain Sciences Centre for Artificial Intelligence and Robotics Institute of Collaborative Innovation 999078 China

Due to the inherent non-stationarity and individual differences present in electroencephalogram (EEG) signals, developing a generalizable model that performs well on new subjects is challenging in EEG-based emotion recognition. Most existing domain adaptation (DA) methods typically mitigate these discrepancies by aligning the marginal distributions of domain feature representations. However, when there is a significant difference in the class-conditional distribution between domain features and labels, the domain-invariant features learned by aligning marginal distributions may have limited discriminative ability for unlabeled target instances or even prove counterproductive. To address this issue, we propose a Neighborhood Semantic Aware Learning-based Dynamic Graph Attention Convolution (NSAL-DGAT) approach that learns target semantic information by considering the inter-domain semantic topological structure, thereby improving classifier adaptation for target instances. Specifically, the proposed NSAL framework is designed to capitalize on the insight that after domain feature alignment, some target samples and their neighboring source samples exhibit similar semantics. By leveraging the neighborhood topological structure, we extract and incorporate semantic target features to train a more transferable classifier. Besides, we implement an entropy weighting mechanism to emphasize representative target semantic information, encouraging target instances to prioritize high-confidence individuals within the source neighborhood. We have conducted extensive experiments on the public SEED dataset and our collected the Hearing-Impaired EEG Dataset (HIED). The experimental results underscore the efficacy of our proposed NSAL-DGAT approach, showcasing state-of-the-art accuracy in subject-dependent as well as subject-independent scenarios. The source code is available at https://***/YYingDL/NSAL-DGAT. © 2010-2012 IEEE.

关键词： Speech analysis

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Influence of electric field orientation on the effect of ocular current stimulation using full field electroretinogram

Influence of electric field orientation on the effect of ocu...

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作者： Blum, Maren-Christina Leydolph, Lilly Klee, Sascha Institute of Biomedical Engineering and Informatics Faculty of Computer Sciences and Automation Technische Universität Ilmenau Ilmenau Germany Department of General Health Studies Division Biostatistics and Data Science Karl Landsteiner University of Health Sciences Krems an der Donau Austria

Ocular current stimulation (CS) exhibits potential for the treatment of neurodegenerative ocular diseases. For a full field electroretinogram (ffERG) we found no CS effect on the characteristic waves (a-wave, b'-wave, and b-wave). To investigate whether the orientation of the generated electric field has an influence on the CS effect, this study repeated the previous ffERG study with changing one CS electrode position and compared the results of both studies. In the first study 15 (8 m, 27.5 ± 4.5 years) and in the second study 17 (7 m, 22.0 ± 1.9 years) healthy volunteers were stimulated with an anodal, cathodal, and sham direct CS of 800 μA for 5 min in three sessions (randomized, different days). For both studies, a cut-sized ring rubber electrode was placed around the eye. A square rubber electrode was placed for the first study at the ipsilateral temple and for the second study at the visual cortex. Before (ERG 1) and during (ERG 2) the CS, the ffERG was measured. For both studies, the difference between the ERG 1 and ERG 2 measurement (CS effect) for the three characteristic waves was analyzed and compared between the studies. For statistical analysis, the Mann-Whitney U test with Bonferroni correction was applied (α = 0.05). The comparison of the data distribution showed only slight differences between the studies. The Mann-Whitney U test found no significant difference of the CS effect between the studies for all amplitudes and CS groups (p ≥ 0.0055). In the mean, the latency differences were smaller than the time resolution, therefore no statements for latency effects were possible. It can be concluded that the retinal cells generating the ffERG are not affected by ocular CS in either electrode montages tested. © 2021 by Walter de Gruyter Berlin/Boston.

关键词： Rubber

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Technical light-field setup for 3D imaging of the human nerve head validated with an eye model

Technical light-field setup for 3D imaging of the human nerv...

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作者： Schramm, Stefan Dietzel, Alexander Blum, Maren-Christina Link, Dietmar Klee, Sascha Institute of Biomedical Engineering and Informatics Faculty of Computer Sciences and Automation Technische Universität Ilmenau Ilmenau Germany Department of General Health Studies Division Biostatistics and Data Science Karl Landsteiner University of Health Sciences Krems an der Donau Austria

With the new technology of 3D light field (LF) imaging, fundus photography can be expanded to provide depth information. This increases the diagnostic possibilities and additionally improves image quality by digitally refocusing. To provide depth information in the human optic nerve head such as in glaucoma diagnostics, a mydriatic fundus camera was upgraded with an LF imager. The aim of the study presented here was the validation of the technical setup and resulting depth estimations with an appropriate eye model. The technical setup consisted of a mydriatic fundus camera (FF450, Carl Zeiss Meditec AG, Jena, Germany) and an LF imager (R12, Raytrix GmbH, Kiel, Germany). The field of view was set to 30°. The eye model (24.65 mm total length) consisted of a two-lens optical system and interchangeable fundus models with papilla excavations from 0.2 to 1 mm in steps of 0.2 mm. They were coated with red acrylic lacquer and vessels were drawn with a thin brush. 15 images were taken for each papilla depth illuminated with green light (wavelength 520 nm ± 20 nm). Papilla depth was measured from the papilla ground to the surrounding flat region. All 15 measurements for each papilla depth were averaged and compared to the printed depth. It was possible to perform 3D fundus imaging in an eye model by means of a novel LF-based optical setup. All LF images could be digitally refocused subsequently. Depth estimation in the eye model was successfully performed over a 30° field of view. The measured virtual depth and the printed model papilla depth is linear correlated. The presented LF setup allowed high-quality 3D one-shot imaging and depth estimation of the optic nerve head in an eye model. © 2021 by Walter de Gruyter Berlin/Boston.

关键词： Optical systems

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Young Driver Gaze (YDGaze): Dataset for driver gaze analysis

Young Driver Gaze (YDGaze): Dataset for driver gaze analysis

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Artificial Intelligence of Things (ICAIoT), International Conference on

作者： Süleyman Çeven Ahmet Albayrak Raif Bayır Dept. of Electronics and Automation Tech. Düzce Vocational School Düzce University Düzce Turkey Department of Computer Engineering Faculty of Engineering Düzce University Düzce Turkey Department of Mechatronics Engineering Faculty of Technology Karabük University Karabük Turkey

One of the most important factors in ensuring successful and safe driving in the road traffic network is the driver’s sense of sight. The driver can determine the environmental factors in the traffic with his gaze and can predict the next move after evaluating it with the current driving position. In this process, the focus of the driver’s gaze should be on the area to which the vehicle is heading. Driver eye movements and gaze analysis is a topic that has been intensively studied in recent years in “Intelligent Driver Assistance Systems”. In this study, a data set was prepared with a group of 40 participants between the ages of 18–28 in order to determine which points the driver looked at while driving. The dataset was created by having each participant look at the labeled areas on the vehicle in turn for one minute. Experimental studies lasted approximately 11 days. Approximately 350 hours of work was carried out to prepare the obtained data set.

关键词： Roads Environmental factors Safety Internet of Things Artificial intelligence Vehicles

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Development of CAN and OBD-II Supported Experimental Setup for Vehicle ECU Data Acquisition

Development of CAN and OBD-II Supported Experimental Setup f...

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Artificial Intelligence of Things (ICAIoT), International Conference on

Today, CAN Bus protocol is widely used in various technological fields such as industrial, medical or automotive. Data is provided from ECUs and diagnostic codes through the OBD-II system, which is a standard in vehicles. The aim of this study is to develop an experimental setup to analyze driver driving skills based on vehicle data obtained over CAN Bus protocol with an open-source software. In this study, an experimental setup with a PiCAN 2 module and an LCD touch screen compatible with Raspberry Pi 3 Model B+ has been developed. Thanks to the developed experimental setup, it is connected to the vehicle ECU via an OBD-II connector to obtain real-time ECU data of the vehicle. This article presents validation tests to determine the design and construction phases of the system and its functionality as a data logger. Python programming language CAN software library was used on the experimental setup.

关键词： Protocols Software libraries Data acquisition Touch sensitive screens Real-time systems Standards Open source software

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Relational Prompt-based Pre-trained Language Models for Social Event Detection

arXiv

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arXiv 2024年

作者： Pu, L.I. Xiaoyan, Y.U. Peng, Hao Xian, Yantuan Wang, Linqin Li, S.U.N. Zhang, Jingyun Philip, S.Y.U. Faculty of Information Engineering and Automation Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology Kunming650500 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China School of Cyber Science and Technology Beihang University No. 37 Xue Yuan Road Haidian District Beijing100191 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China Department of Computer Science University of Illinois at Chicago ChicagoIL60607 United States

Social Event Detection (SED) aims to identify significant events from social streams, and has a wide application ranging from public opinion analysis to risk management. In recent years, Graph Neural Network (GNN) based solutions have achieved state-of-the-art performance. However, GNN-based methods often struggle with missing and noisy edges between messages, affecting the quality of learned message embedding. Moreover, these methods statically initialize node embedding before training, which, in turn, limits the ability to learn from message texts and relations simultaneously. In this paper, we approach social event detection from a new perspective based on Pre-trained Language Models (PLMs), and present RPLM (Relational prompt-based Pre-trained Language Models for Social Event Detection). We first propose a new pairwise message modeling strategy to construct social messages into message pairs with multi-relational sequences. Secondly, a new multi-relational prompt-based pairwise message learning mechanism is proposed to learn more comprehensive message representation from message pairs with multi-relational prompts using PLMs. Thirdly, we design a new clustering constraint to optimize the encoding process by enhancing intra-cluster compactness and inter-cluster dispersion, making the message representation more distinguishable. We evaluate the RPLM on three real-world datasets, demonstrating that the RPLM model achieves state-of-the-art performance in offline, online, low-resource, and long-tail distribution scenarios for social event detection tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Risk assessment

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Development of the DSS sorting of sheet metal cutting residues 20

Development of the DSS sorting of sheet metal cutting residu...

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3rd International Scientific and Practical Conference, DEFIN 2020

作者： Sukonschikov, Alexey Ulitin, Anatoly Akhmetov, T.R. Faculty of Automation and Computer Engineering Vologda State University Lenin street 15 Vologda160000 Russia Kazan State Power Engineering University Kazan Russia

ISBN: (纸本)9781450375306

The article proposes the structure of the software package for managing material resources of sheet metal with elements of the DSS, and defines the features of interaction between the systems that make up the software package. The system is presented in the form of a set-theoretic description, based on which the tasks and connections of the modules are defined. © 2020 ACM.

关键词： Sheet metal

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Next-generation pediatric care:nanotechnology-based and AI-driven solutions for cardiovascular,respiratory,and gastrointestinal disorders

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World Journal of Pediatrics 2025年第1期21卷 8-28页

作者： Waldenice de Alencar Morais Lima Jackson G.de Souza Fátima García-Villén Julia Lira Loureiro Fernanda Nervo Raffin Marcelo A.C.Fernandes Eliana B.Souto Patricia Severino Raquel de M.Barbosa Laboratory of Galenic Pharmacy Department of PharmacyFederal University of Rio Grande Do NorteNatal 59012-570Brazil InovAI Lab nPITI/IMDFederal University of Rio Grande Do NorteNatalRN 59078-970Brazil Department of Pharmacy and Pharmaceutical Technology School of PharmacyUniversity of GranadaCampus of Cartuja18071 GranadaSpain Department of Computer Engineering and Automation Federal University of Rio Grande Do NorteNatalRN 59078-970Brazil Laboratory of Pharmaceutical Technology Faculty of PharmacyUniversity of PortoRua Jorge de Viterbo Ferreira2284050-313 PortoPortugal Industrial Biotechnology Program University of Tiradentes(UNIT)AracajuSergipe 49032-490Brazil Department of Pharmacy and Pharmaceutical Technology School of PharmacyUniversity of SevilleC/Professor García González241012 SevilleSpain

Background Global pediatric healthcare reveals significant morbidity and mortality rates linked to respiratory,cardiac,and gastrointestinal disorders in children and newborns,mostly due to the complexity of therapeutic management in pediatrics and neonatology,owing to the lack of suitable dosage forms for these patients,often rendering them“therapeutic orphans”.The development and application of pediatric drug formulations encounter numerous challenges,including physiological heterogeneity within age groups,limited profitability for the pharmaceutical industry,and ethical and clinical *** drugs are used unlicensed or off-label,posing a high risk of toxicity and reduced *** these circumstances,some regulatory changes are being performed,thus thrusting research innovation in this *** sources Up-to-date peer-reviewed journal articles,books,government and institutional reports,data repositories and databases were used as main data *** Among the main strategies proposed to address the current pediatric care situation,nanotechnology is specially promising for pediatric respiratory diseases since they offer a non-invasive,versatile,tunable,site-specific drug *** engineering is in the spotlight as strategy to address pediatric cardiac diseases,together with theragnostic *** integration of nanotechnology and theragnostic stands poised to refine and propel nanomedicine approaches,ushering in an era of innovative and personalized drug delivery for pediatric ***,the intersection of drug repurposing and artificial intelligence tools in pediatric healthcare holds great *** promises not only to enhance efficiency in drug development in general,but also in the pediatric field,hopefully boosting clinical trials for this *** Despite the long road ahead,the deepening of nanotechnology,the evolution of tissue engineering,and the combination of traditional techniques with artificia

关键词： Artificial intelligence Conventional therapy Nanotechnology Pediatrics Theragnostics

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