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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Munir, Achmad Muhammad, Rivaldi Aulia Nurmantris, Dwi Andi Maulana, Muhammad Farhan Institut Teknologi Bandung Radio Telecommunication and Microwave Laboratory School of Electrical Engineering and Informatics Bandung Indonesia Uin Sunan Gunung Djati Bandung Faculty of Science and Technology Department of Electrical Engineering Bandung Indonesia Itb Radio Telecommunication and Microwave Laboratory School of Electrical Engineering and Informatics Bandung Indonesia Telkom University School of Applied Sciences Bandung Indonesia

ISBN: (纸本)9798350317558

The development of a slot array antenna based on Substrate Integrated waveguide (SIW) has been carried out. The antenna, consisting of 4 rectangular slots, is designed to operate at a frequency of 2.4 GHz. The design process includes SIW and slot array structure design, microstrip to SIW transition structure design, and microstripline structure design. The final design results were then fabricated on an FR4 Epoxy substrate with a substrate thickness of 1.6 mm for measurements. From the measurement results, it was found that the antenna resonates at a frequency of 2.385 GHz with a bandwidth of 1.67%. The measurement results, in general, also agree with the simulation results. The manufactured antenna is suitable for use in WLAN applications. © 2024 IEEE.

关键词： slotted array antenna substrate integrated waveguide (SIW) wavegudie Wireless Local Area Networks (WLAN) communications

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Deep Learning Approaches for Stress Detection: A Survey

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IEEE Transactions on Affective Computing 2025年第2期16卷 499-517页

作者： Kyrou, Maria Kompatsiaris, Ioannis Petrantonakis, Panagiotis C. Aristotle University of Thessaloniki Artificial Intelligence and Information Analysis Laboratory Deptartment of Informatics Thessaloniki54124 Greece Centre for Research and Technology - Hellas Information Technologies Institute Thessaloniki57001 Greece Aristotle University of Thessaloniki Deptartment of Electrical and Computer Engineering Thessaloniki54124 Greece

Stress has a severe impact on individuals irrespective of age, sex, work, or background. The reliable development of stress detection techniques enhances the social, educational, physical, economic, and professional quality of life, preventing chronic stress and proposing alleviation strategies. Research studies examine psychological, cognitive, behavioral, and physiological reactions to identify stress adequately. Deep Learning (DL) has received significant attention in recent years as it deals with high-dimensional, heterogeneous data and automatically learns representative features. This paper presents a survey on stress detection with recent DL approaches, leveraging data from all possible sources (physiological, speech, facial expressions, gestures, and social media content). The methodological outlines, the best results, and the main contributions of each study are discussed. We also describe publicly available datasets used by several of the presented works. Finally, we emphasize various open issues within the field of research and highlight key directions for future work. © 2010-2012 IEEE.

关键词： Social psychology

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A Novel Approach to Remote Detection in Medical Radar Applications Using Flexible Transmit Array Lenses

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IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology 2024年第1期8卷 36-50页

作者： Asyari, Rifa Atul Izza Lee, Kuan-Yuan Arif, Rezki El Horng, Tzyy-Sheng Jason Teichmann, Daniel University of Southern Denmark Sdu Health Informatics and Technology The Maersk Mc-Kinney Moller Institute Odense5230 Denmark National Sun Yat-Sen University Department of Electrical Engineering Kaohsiung804 Taiwan Institut Teknologi Sepuluh Nopember Department of Biomedical Engineering Surabaya60111 Indonesia

This study introduces a novel method employing adaptable transmitarray lenses for medical radar systems, enhancing the direction of electromagnetic beams in the far-field. The newly developed antenna array exhibited marked improvements in gain, bandwidth, return loss, and isolation within specific frequency ranges during testing. Comprehensive evaluations, including various focal lengths and bending scenarios, underscored the superior performance of this adaptable lens over prior techniques. Its exceptional precision and sensitivity render it an ideal tool for real-time remote health monitoring systems, particularly in pulse detection. The research findings consistently aligned the heart rates detected by this innovative method with standard reference rates, reaffirming its reliability and accuracy. This consistency highlights the potential of the transmitarray lenses as a valuable advancement in medical radar systems. The study not only validates the effectiveness and reliability of the lenses but also lays a solid foundation for further research and development in this field. The insights garnered are expected to significantly bolster the progression of radar technologies in healthcare, leading to more accurate, efficient, and non-invasive health monitoring solutions, thereby enhancing patient care and outcomes. © 2016 IEEE.

关键词： Bandwidth

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Web-based Rice Pest and Diseases Detection Using Hybrid Fuzzy and K-Nearest Neighbor Methods

Web-based Rice Pest and Diseases Detection Using Hybrid Fuzz...

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6th International Conference on informatics and Computational Sciences, ICICoS 2022

作者： Anamisa, Devie Rosa Satoto, Budi Dwi Yusuf, Muhammad Sophan, Moch. Kautsar Alamsyah, Nurwahyu Muntasa, Arif University of Trunojoyo Madura Informatics Engineering Department Bangkalan Indonesia National Taiwan University of Science and Technology Informatics Engineering Department Taipei Taiwan

ISBN: (数字)9781665460996

ISBN: (纸本)9781665460996

Rice is a food crop that produces rice which is very useful for human life. And this is one of the main food commodities in Indonesia. Therefore, the Government must pay attention to the agricultural sector as a forum for providing food needs for the Indonesian population, which is increasing every year. East Java Province is one of the regions that produces the highest rice harvest in Indonesia. However, in recent years, rice production in East Java has not been able to meet the population's food demand properly. This is due to disease and pest attacks on rice plants and a lack of knowledge so that rice farmers experience crop failure. Therefore, rice production at the farm level can be increased through web-based technological innovations in early detection of diseases and pests. This research used the hybrid Fuzzy and K-Nearest Neighbor (K-NN) method to detect diseases and problems in rice plants. The fuzzy logic is used to find the membership value of the disease detection class and the K-NN method is used to find the closest distance between the evaluated data and its k closest neighbors in the training data. The results of trials conducted on 200 case data with 13 diseases and pests and 32 symptoms resulted in an accuracy of 98.74% with 160 training data and 40 test data, and the value of k=4. © 2022 IEEE.

关键词： Crops

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Assessing Security and Performance: Varying Ring Oscillator Counts in Configurable Inversion Unit-based PUF

Assessing Security and Performance: Varying Ring Oscillator ...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Husam Kareem Dmitriy Dunaev Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9798350387568

ISBN: (纸本)9798350387575

The concept of Physical Unclonable Function (PUF) has recently garnered attention in both industrial and academic fields as a promising hardware primitive for enhancing the security of electronic systems and devices. PUFs leverage inherent manufacturing inconsistencies to generate a distinct key for every device. PUFs utilize the inherent manufacturing variations to generate a distinct key for each device despite using identical input values across all devices. A range of PUF types have been developed, such as optical, electronic, and magnetic variations. However, the Ring Oscillator (RO) PUF stands out particularly due to its simple implementation and impressive performance. Due to the limited combinations of the RO-PUF input-output bits, or as it is called in the field of PUFs, challenge-response pairs (CRPs), researchers have developed the configurable ring oscillator (CRO) PUF, which produces a larger set of CRPs by utilizing a configurable inversion unit (CIU) instead of the standard inverter in the traditional design. Most of the recent research primarily focuses on increasing the size of the CRPs and enhancing security features. Yet, there is a lack of emphasis on investigating how the count of ROs affects the performance of the CRO-PUF. This paper uses several performance metrics to investigate the impact of altering the ring oscillator count on the CRO-PUF.

关键词： Ring oscillators Performance evaluation Embedded computing Physical unclonable function Reliability engineering Hardware Inverters

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Continuous Prompt for Chemical Language Model Aided Anticancer Synergistic Drug Combination Prediction

Continuous Prompt for Chemical Language Model Aided Anticanc...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Geng, Guannan Zhao, Lingling Wang, Chunyu Liu, Xiaoyan Wang, Junjie The First Affiliated Hospital of Harbin Medical University Department of Endocrinology Harbin China Harbin Institute of Technology Faculty of Computing Harbin China Nanjing Medical University School of Biomedical Engineering and Informatics Department of Medical Informatics Nanjing China

ISBN: (纸本)9798350324457

Identifying synergistic drug combinations is paramount significance in addressing complex diseases while reducing the risks of toxicities and other adverse effects. Although a plethora of computational methods have been proposed in this domain, most of them are underpinned only by physicochemical or biological features. Recently, Chemical Language Models (CLMs) are shown to be capable of learning better representations that hold utility across diverse tasks, from molecular property prediction, de novo drug design, drug-target interaction, and more. In this study, we proposed CLMSyn, a continuous prompt for CLM aided synergistic drug combinations prediction. Unlike existing works employ CLMs for downstream tasks, we adopt the prompt learning to fine-tune CLM, that is, only train small-scale prompt while keeping CLM fixed. Furthermore, we harness the the multi-head attention mechanism to fuse the learned vector from the CLM, chemical descriptors and gene expression of cell line. A comprehensive array of experiments conducted on a benchmark dataset, encompassing four distinct synergy types, substantiates the superior performance of CLMSyn when contrasted against existing state-of-the-art methods. These empirical findings provide compelling evidence attesting to the efficacy of CLMSyn as a potent instrumentality in expediting the identification of pioneering combination therapies. © 2023 IEEE.

关键词： Chemical Language Model Drug Combination Multi-head Attention Prompt Learning

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A Blockchain-Assisted Distributed Edge Intelligence for Privacy-Preserving Vehicular Networks

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Computers, Materials & Continua 2023年第9期76卷 2959-2978页

作者： Muhammad Firdaus Harashta Tatimma Larasati Kyung-Hyune Rhee Department of Artificial Intelligence Convergence Pukyong National UniversityBusan48513Korea School of Electrical Engineering and Informatics Institut Teknologi BandungBandung40132Indonesia College of Information Technology and Convergence Division of Computer Engineering and AIPukyong National UniversityBusan48513Korea

The enormous volume of heterogeneous data fromvarious smart device-based applications has growingly increased a deeply interlaced cyber-physical *** order to deliver smart cloud services that require low latency with strong computational processing capabilities,the Edge Intelligence System(EIS)idea is now being employed,which takes advantage of Artificial Intelligence(AI)and Edge Computing technology(ECT).Thus,EIS presents a potential approach to enforcing future Intelligent Transportation Systems(ITS),particularly within a context of a Vehicular Network(VNets).However,the current EIS framework meets some issues and is conceivably vulnerable tomultiple adversarial attacks because the central aggregator server handles the entire ***,this paper introduces the concept of distributed edge intelligence,combining the advantages of Federated Learning(FL),Differential Privacy(DP),and blockchain to address the issues raised *** performing decentralized data management and storing transactions in immutable distributed ledger networks,the blockchain-assisted FL method improves user privacy and boosts traffic prediction ***,DP is utilized in defending the user’s private data from various threats and is given the authority to bolster the confidentiality of data-sharing *** model has been deployed in two strategies:First,DP-based FL to strengthen user privacy by masking the intermediate data during model ***,blockchain-based FL to effectively construct secure and decentralized traffic management in vehicular *** simulation results demonstrated that our framework yields several benefits for VNets privacy protection by forming a distributed EIS with privacy budget(ε)of 4.03,1.18,and 0.522,achieving model accuracy of 95.8%,93.78%,and 89.31%,respectively.

关键词： Edge intelligence federated learning differential privacy blockchain vehicular networks

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Determining the Global Response Characteristics of General Rotor/Stator Rubbing Systems with Hydrodynamic Forces

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Journal of engineering Science and technology Review 2023年第2期16卷 37-48页

作者： Cai, Huayi Wang, Shunzeng Li, Tao School of Electrical and Information Engineering The University of Sydney SydneyNSW2006 Australia School of Intelligent Manufacturing Nanyang Institute of Technology Nanyang473006 China Department of Informatics University of Zurich Zurich8050 Switzerland

Hydrodynamic forces caused by fluid-rotor interaction in fluid-rotor-stator systems can directly influence the occurrence of rubbing fault between the rotor and the stator, thereby affecting the stability of the rotating machinery. Considering the rotor-stator dynamics, the dry friction, and the flexibility on the contact surfaces as well as the fluid-rotor interaction, a 4D fluid-rotor-stator rubbing system was established to determine the global response characteristics exhibited in the general rotor/stator rubbing system with hydrodynamic forces. Aided by the features of orbits and full spectra, three types of rubbing responses were identified through experimental observation. The critical rotating speed of no-rub motion was analytically derived and confirmed by numerical simulation. Then, the global response characteristics on the parameter plane of the friction coefficient and rotating speed were numerically obtained. Results show that the critical rotating speed of no-rub motion decreases from 0.716 to 0.589 because of the hydrodynamic forces, and the coexistence of the partial rub with other responses is evident. From the influences of the system parameters, the decrease of the rotor mass has the same effect as increasing the rotor stiffness to mitigate rubbing responses. On the other hand, the increase of the rotor radius has the same effect as decreasing the clearance to increase the amplitudes of the rubbing responses. This study provides deeper insights into the highly detailed response characteristics of the general fluid-rotor-stator rubbing system. © 2023 School of Science, IHU. All rights reserved.

关键词： Stators

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Disaster-Resilient Upgrade of Interdependent Networks 13

Disaster-Resilient Upgrade of Interdependent Networks

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13th International Workshop on Resilient Networks Design and Modeling, RNDM 2023

作者： Pašić, Alija Revisnyei, Peter Mogyorósi, Ferenc Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Telecommunications and Media Informatics BudapestH-1l11 Hungary ELKH-BME Information Systems Research Group BudapestH-1117 Hungary

ISBN: (纸本)9798350327359

Recent global emergencies have emphasized the importance of reliable communication networks. With increasing dependence on critical infrastructure, it is no longer sufficient to consider single-link or link-pair failures. Instead, networks must be designed to withstand disasters, considering their interdepen-dence with other infrastructures like the power grid. This paper investigates the problem of the disaster resilient upgrade of interdependent networks, focusing on enhancing network resilience during emergencies and ensuring a service-level agreement. In this paper, we analyze how the interdependency between the networks affects the disaster resilience and propose heuristic methods for network operators to improve resilience against disasters. Using simulations with real networks and earthquake data, we demonstrate that limiting the number of interdependent edges per node significantly affects resilience. Additionally, we show that selecting appropriate upgrade methods can reduce network upgrade costs by up to 25%. © 2023 IEEE.

关键词： Disasters

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A framework for object tracking in videos with complex backgrounds and obstructions

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Neural Computing and Applications 2025年 1-20页

作者： Chang, Tsui-Ping Chen, Tzer-Long Hsiao, Tsung-Chih Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan Department of Healthcare Administration and Medical Informatics Kaohsiung Medical University Gaoxiong807 Taiwan Department of Radio Television and Film Shih Hsin University Taipei11604 Taiwan

The research of object tracking in videos utilizes computer vision and machine learning techniques to identify and track objects in the consecutive image frames of videos. The popular algorithms used in the research are YOLO, DeepSORT, StrongSORT, and ByteTrack. YOLO has gained recognition for its hardware efficiency and impressive performance in object detection tasks. It efficiently detects objects in the consecutive image frames of videos. On the other hand, DeepSORT, StrongSORT, and ByteTrack leverage the prediction capabilities to estimate the positions of objects in the next image frames. These algorithms play a significant role to enhance the capabilities of object tracking systems. Recently, many researchers have proposed their methods to enhance the accuracy in object tracking tasks. However, the division of videos into the consecutive image frames for tracking objects can pose challenges, especially when the videos have complex backgrounds and many obstructions in the image frames. In fact, the complex backgrounds with many obstructions in image frames decrease the accuracy of tracking objects in applications. In this study, we present TraObs, a framework for object Tracking in complex backgrounds with Obstructions in the image frames of videos. In TraObs, two novel mechanisms CFM and M-controller are proposed for detectors and trackers to enhance the accuracy of object tracking performance. CFM addresses the tracked objects which are missing in some image frames of videos, while M-controller makes sure the tracked objects with the correct object ids in the system. Some experiments with four testing datasets and benchmark datasets are designed and used respectively to analyze the performance of TraObs. Furthermore, the HOTA and MOTA metrics are used to evaluate our proposed methods. The experimental results also prove the effectiveness of CFM and M-controller in our framework TraObs. © The Author(s), under exclusive licence to Springer-Verlag London Ltd.,

关键词： Image enhancement

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