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IEEE Open Journal of Instrumentation and Measurement 2025年 4卷

作者： Kameli, Sayed Mohammad Abuelrub, Abdelaziz AlShaikh Saleh, Mohammad Refaat, Shady S. Ghrayeb, Ali Abu-Rub, Haitham Olesz, Marek Texas A&M University at Qatar Electrical and Computer Engineering Department Doha Qatar Texas A&M University Department of Electrical and Computer Engineering College StationTX77843 United States University of Hertfordshire School of Physics Engineering and Computer Science Department of Engineering HatfieldAL10 9EU United Kingdom Hamad Bin Khalifa University Qatar Foundation Electrical and Computer Engineering Program in College of Science and Engineering Doha Qatar Gdańsk University of Technology Department of Electrical Power Engineering Gdańsk80-233 Poland

Partial discharge (PD) is a widespread phenomenon instigated in power transformer (PT) insulation systems. PDs are triggered by voids that vary in size and position within the PT insulation. The electrical characteristics of those damaging, PD-causing cavities must be well understood, to accelerate the development of advanced PD detection techniques. Thus, the impact of varying the radius and position of spherical air voids on the characteristics of PDs in PTs is examined using a 3-D finite element analysis (FEA) model designed in COMSOL Multiphysics. The spherical voids are positioned between two windings of a 512 kV, three-phase (3φ ) PT. The peak electric field (EF) and aggregate energy in the FEA model are used in conjunction with laboratory measurements of the apparent discharge magnitude, for detailed analysis of Polyethylene Terephthalate Glycol (PET-G)-based cylindrical voids with different heights. Simulations demonstrate that the inception of PD activity in the PT model occurs for spherical voids with a radius exceeding 1 mm. Furthermore, the most severe PDs occur within the press-board insulation, adjacent to the uppermost part of the innermost windings. Experiments demonstrate that a significant increase in PD activity was observed for PET-G-based cylindrical voids with heights exceeding 1 mm. © 2022 IEEE.

关键词： Partial discharges

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engineering dimensionality of collective dipole-dipole interactions using a nanophotonic environment

Engineering dimensionality of collective dipole-dipole inter...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Boddeti, Ashwin K. Wang, Yi Juarez, Xitlali Boltasseva, Alexandra Alaeian, Hadiseh Odom, Teri W. Jacob, Zubin Elmore Family School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Chemistry Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States

ISBN: (纸本)9781957171258

We experimentally demonstrate reduced dimensionality in a interacting ensemble of emitters. The well-known stretched exponential decay dynamics, (Equation presented) with β = 0.5 in 3D geometries, is strikingly modified in a nanophotonic environment that supports long-range interaction to β ~ 0.3. © Optica Publishing Group 2023.

关键词： Nanophotonics

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Automated rice counting using canny edge detection technique

Automated rice counting using canny edge detection technique

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8th IET Smart Cities Symposium (SCS 2024)

作者： Rahul Goraksha Durgesh Nandan Department of Robotics & Automation Engineering Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune India School of Computer Science & Artificial Intelligence S R University Warangal Telangana 506371 India

ISBN: (数字)9781837243105

In many Asian countries, rice is a staple food of critical importance to local and global markets where rice quality matters. Rice quality has traditionally been appraised by human inspectors, but this approach is labor intensive, time-consuming and subjective. Such samples comprise whole kernels, broken kernels, damaged grains, paddy, stones and other impurities hence their sorting into grades according to the quality required. In this study a machine learning approach as well as image processing techniques for classification and segmentation of rice grain samples based on color texture features are proposed. Automated counting of rice is essential in farming processes such as estimation of yields, management of stores and transport planning. Manual counting is tasking, slow and likely to have errors. Machine vision technology provides an alternative that can be relied upon for automated rice counting systems. This paper gives details on methodology using machine vision for automating rice counting on the field. To identify and count rice grains in images Gaussian blur; thresholding; canny edge detection; contour extraction; are some examples of the image processing methods applied here. High accuracy rate was achieved when tested against a dataset containing several images of rice grains.

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Incentive Mechanism Design for Distributed Ensemble Learning

arXiv

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arXiv 2023年

作者： Huang, Chao Han, Pengchao Huang, Jianwei The Department of Computer Science the University of California Davis United States The School of Science and Engineering The Chinese University of Hong Kong Shenzhen China The School of Science and Engineering The Chinese University of Hong Kong Shenzhen China The Shenzhen Institute of Artificial Intelligence and Robotics for Society China

Distributed ensemble learning (DEL) involves training multiple models at distributed learners, and then combining their predictions to improve performance. Existing related studies focus on DEL algorithm design and optimization but ignore the important issue of incentives, without which self-interested learners may be unwilling to participate in DEL. We aim to fill this gap by presenting a first study on the incentive mechanism design for DEL. Our proposed mechanism specifies both the amount of training data and reward for learners with heterogeneous computation and communication costs. One design challenge is to have an accurate understanding regarding how learners’ diversity (in terms of training data) affects the ensemble accuracy. To this end, we decompose the ensemble accuracy into a diversity-precision tradeoff to guide the mechanism design. Another challenge is that the mechanism design involves solving a mixed-integer program with a large search space. To this end, we propose an alternating algorithm that iteratively updates each learner’s training data size and reward. We prove that under mild conditions, the algorithm converges. Numerical results using MNIST dataset show an interesting result: our proposed mechanism may prefer a lower level of learner diversity to achieve a higher ensemble accuracy. Copyright © 2023, The Authors. All rights reserved.

关键词： Iterative methods

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Temporally Robust Multi-Agent STL Motion Planning in Continuous Time

arXiv

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arXiv 2023年

作者： Verhagen, Joris Lindemann, Lars Tumova, Jana The Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science Kth Royal Institute of Technology Stockholm Sweden The Thomas Lord Department of Computer Science University of Southern California Los AngelesCA United States

Signal Temporal Logic (STL) is a formal language over continuous-time signals (such as trajectories of a multiagent system) that allows for the specification of complex spatial and temporal system requirements (such as staying sufficiently close to each other within certain time intervals). To promote robustness in multi-agent motion planning with such complex requirements, we consider motion planning with the goal of maximizing the temporal robustness of their joint STL specification, i.e. maximizing the permissible time shifts of each agent's trajectory while still satisfying the STL specification. Previous methods presented temporally robust motion planning and control in a discrete-time Mixed Integer Linear programming (MILP) optimization scheme. In contrast, we parameterize the trajectory by continuous Bézier curves, where the curvature and the time-traversal of the trajectory are parameterized individually. We show an algorithm generating continuous-time temporally robust trajectories and prove soundness of our approach. Moreover, we empirically show that our parametrization realizes this with a considerable speed-up compared to state-of-the-art methods based on constant interval time discretization. Copyright © 2023, The Authors. All rights reserved.

关键词： Trajectories

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Text-Guided Graph Temporal Modeling for Few-Shot Video Classification

SSRN

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SSRN 2024年

作者： Fuqin, Deng Jiaming, Zhon Li, Nannan Lanhui, Fu Jiang, Bingchun Yi, Ningbo Feng, Qi He, Xin Lun, Lam Tin School of Intelligent Manufacturing the Wuyi University Jiangmen China School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology China School of Textile Materials and Engineering the Wuyi University Jiangmen China School of Applied Physics and Materials Science the Wuyi University Jiangmen China School of Mechanical and Electrical Engineering Guangdong University of Science and Technology Dongguan China Shenzhen Vatop Semicon Tech Co. Ltd. Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society School of Science and Engineering The Chinese University of Hong Kong Shenzhen China

Large-scale pre-trained models and graph neural networks have recently demonstrated remarkable success in few-shot video classification tasks. However, they generally suffer from two key limitations: i) the temporal relations between adjacent frames tends to be ambiguous due to the lack of explicit temporal modeling. ii) the absence of multi-modal semantic knowledge in query videos results in inaccurate prototypes construction and an inability to achieve multi-modal temporal alignment metrics. To address these issues, we develop a Text-guided Graph Temporal Modeling (TgGTM) method that consists of two crucial components: a text-guided feature refinement module and a learnable query text-token contrastive objective. Specifically, the former leverages the temporal masking layer to guide the model in learning temporal relationships between adjacent frames. Additionally, it utilizes multi-modal information to refine video prototypes for comprehensive few-shot video classification. The latter addresses the feature discrepancy between multi-modal support features and single-modal query features by aligning a learnable query text-token with corresponding base class text descriptions. Extensive experiments on three commonly used benchmarks demonstrate the effectiveness of our proposed method, which significantly outperforms existing state-of-the-art methods under various settings. A detailed ablation showcases the importance of learning temporal relationships between adjacent frames and obtaining query text-token. The source code and models will be publicly available at https://***/JiaMingZhong2621/TgGTM. © 2024, The Authors. All rights reserved.

关键词： Semantics

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Benchmarking Graph Representations and Graph Neural Networks for Multivariate Time Series Classification

arXiv

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arXiv 2025年

作者： Yang, Wennuo Wu, Shiling Zhou, Yuzhi Luo, Cheng He, Xilin Xie, Weicheng Shen, Linlin Song, Siyang Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University China Shenzhen Institute of Artificial Intelligence and Robotics for Society China Guangdong Provincial Key Laboratory of Intelligent Information Processing China HBUG Lab University of Exeter United Kingdom

Multivariate Time Series Classification (MTSC) enables the analysis if complex temporal data, and thus serves as a cornerstone in various real-world applications, ranging from healthcare to finance. Since the relationship among variables in MTS usually contain crucial cues, a large number of graph-based MTSC approaches have been proposed, as the graph topology and edges can explicitly represent relationships among variables (channels), where not only various MTS graph representation learning strategies but also different Graph Neural Networks (GNNs) have been explored. Despite such progresses, there is no comprehensive study that fairly benchmarks and investigates the performances of existing widely-used graph representation learning strategies/GNN classifiers in the application of different MTSC tasks. In this paper, we present the first benchmark which systematically investigates the effectiveness of the widely-used three node feature definition strategies, four edge feature learning strategies and five GNN architecture, resulting in 60 different variants for graph-based MTSC. These variants are developed and evaluated with a standardized data pipeline and training/validation/testing strategy on 26 widely-used suspensor MTSC datasets. Our experiments highlight that node features significantly influence MTSC performance, while the visualization of edge features illustrates why adaptive edge learning outperforms other edge feature learning methods. The code of the proposed benchmark is publicly available at https://***/CVI-yangwn/*** Codes 68T10 © 2025, CC BY.

关键词： Graph neural networks

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Protein-Folding Inspired programmable Control System for Robot Swarms

Protein-Folding Inspired Programmable Control System for Rob...

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IEEE International Conference on robotics and Biomimetics

作者： Feng Zhang Yuping Gu Zebin Wang Shuai Yuan Yongliang Yang School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang Liaoning China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang Liaoning China School of Computer Science and Engineering Shenyang Jianzhu University Shenyang Liaoning China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

In swarm robotics, most of the control algorithms are inspired by the behaviors of animal swarms. The capability gap between robots and animals, however, hinders the reliability of these algorithms. Toward developing reliable algorithms of robot swarms, a promising solution is learning from the collective behaviors of low-intelligent natural swarms, such as cell collectives and molecular assemblies. Here, we proposed a programmable control system inspired by protein folding. Using our homemade RoboFold platform, we demonstrated a protein-folding inspired programmable control method for robot swarms. By programming and designing the sequence of a thread of protein-like robots, the developed system can mimic the formation of hierarchical structures in robot swarms as the three-level of protein structures. We quantitatively characterized the specific features of self-organized morphologies. The experimental results together demonstrated the feasibility of this method. To summarize, this work successfully translated the principles of protein-folding into programming methods to control the morphology of robot swarms. Considering that the protein folding problem is essentially a physicochemical problem, this system is not only beneficial for the control of swarm robots but also has the potential to develop into a tool for studying the protein folding problem.

关键词： Proteins Vibrations programmable control Animals Morphology Swarm robotics programming Control systems Robustness Robots

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Adopting Centroid and Bandwidth to Shape Security Line

Adopting Centroid and Bandwidth to Shape Security Line

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International Conference of computer science and Information Technology

作者： Heni Ispur Pratiwi Iman Herwidiana Kartowisastro Benfano Soewito Widodo Budiharto Doctorate Program School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Doctorate Program of Computer Science Bina Nusantara University Jakarta Indonesia Computer Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia Computer Science BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798350399080

The voice patterns of gender and age have been used as speaker's identity and implied into sectors such as smart cards, healthcare, banking, and other security access controls. However, age, illness, and ambient noise factors exist challenging issues of voice changes in speech recognition systems to be resolved. This paper presents experiment results of observing those issues, and its goal was obtaining the elements of voice features to secure the speaker's identity. Mel-frequency Cepstral Coefficient (MFCC) was used to conduct observations on spectral centroid and bandwidth, it has effectively performed capturing features of individual speech signal. The experiment was conducted with data split into three groups: under 13, range 13 to 19, and above 19 years old for both male and female. The results showed that both gender under 13 have centroid voices reached to 98%, age of 13 to 19 remain with centroid reached 98% of bandwidth for male and passing over 100% for female, then above 19 for both genders speak lower with centroid 50% of bandwidth, and male above age of 19 remains to keep centroid about 50% and female changes to 95%. MFCC fits to expose the speech spectrum for the purpose of an analysis frame on specific local spectral properties of voices, and the finding is to form a security line or an individual profiling adoption.

关键词： computer science Smart cards Shape Bandwidth Speech recognition Medical services Banking

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Twenty years of e-learning in health science: A bibliometric

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Procedia computer science 2023年 216卷 604-612页

作者： Fairuz Iqbal Maulana M. Aldiki Febriantono Dwi Risza Budi Raharja Khaeruddin Ridho Herasmara Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Indonesia Electrical Engineering Faculty of Science and Technology Raden Rahmat Islamic University Malang Indonesia

Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conventionally. Supposedly with the advancement of technology and the use of the internet everywhere, learning such as e-learning can be important, especially in the health sector. Until this research was conducted, only 514 academic documents about e-learning in health sciences were found for 20 years from 2001 to 2020, obtained in searching on the Scopus database. This study presents a comprehensive overview of studies related to E-learning in the Health sciences sector. This study uses bibliometric analysis and indexed digital methods to map scientific publications throughout the world. This research employs the Scopus database to gather information, as well as the Scopus online analysis tool and Vosviewer to show the bibliometric network. The method consists with five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. Among the most published and indexed articles by Scopus, papers published by researchers in the United States have the highest number of publications (80), followed by United Kingdom (63) and Australia with 45 academic publications. The processed data shows the pattern and trend of increasing the number of international publications in E-learning in Health sciences field, which Scopus index.

关键词： e-learning health science bibliometric vosviewer education

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