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5th High Performance Computing and Cluster Technologies Conference, HPCCT 2021

作者： Martin, Mogamat Yaaseen Winberg, Simon Lucas Gaffar, Mohammed Yunus Abdul Macleod, David Department of Electrical Engineering University of Cape Town South Africa Advanced Computer Engineering Lab Centre for High Performance Computing South Africa

ISBN: (纸本)9781450390132

The problem of space debris represents a major topic of concern in astronomy as the threat of space junk continues to grow, and the accuracy of its tracking is greatly restricted by the insufficiency and limitations of current surveillance sensors. This article presents the development of an open-source, high-performance, signal-level radar simulator to assist in modelling the detection and tracking of space debris from terrestrial radar stations, including multistatic installations where the transmitter and receiver may be separated by many kilometers. This tool is expected to aid astronomers and researchers in space situational awareness, supporting the modelling of radar interactions in this context and simulation-based exploration of radar designs for space surveillance. It makes use of an accelerated orbit propagation technique with measured two-line element datasets being used to define space debris objects. The software has been named the Space Object Astrodynamics and Radar Simulator - or SOARS - and both the transmitted and received signals generated by the application have been shown to agree with theoretical expectations. Additionally, SOARS is presently undergoing continued development, extension and optimization for heterogeneous computing platforms, enabling the use of the NVIDIA® Compute Unified Device Architecture (CUDA) interface. Results have demonstrated promising speed-ups in simulation runtimes when using the CUDA version of the application over the original sequential version, even on lower-end graphics processors. It is anticipated that the developed application will be used for the design and testing of radar sensors for space situational awareness applications, as well as for use in research, teaching and training environments. © 2021 ACM.

关键词： Application programs

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ChromaSense-Empowering Health, Empowering You

ChromaSense-Empowering Health, Empowering You

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2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023

作者： Durbha, Ravi Koomson, Valencia Tufts University Advanced Integrated Circuits & Systems Lab Department of Electrical & Computer Engineering MedfordMA United States

ISBN: (纸本)9798350300260

Wearable devices have transformed from novelties into indispensable companions for millions, finding applications in health and wellness, empowering individuals to proactively manage their well-being. Among these, pulse oximeters play a vital role in detecting health issues like hypoxemia. Yet, traditional oximeters struggle with accuracy in individuals with darker skin tones and lack multi-vital sign monitoring using Photoplethysmogram (PPG) signals. Addressing these challenges, we introduce ChromaSense, a Skintone Compensated Pulse Oximeter (SCPO) equipped with advanced sensors and intelligent algorithms. It aims to provide precise oxygen saturation readings for all skin tones, ensuring equitable access to quality healthcare. By addressing pulse oximetry disparities, ChromaSense seeks to enhance patient outcomes, promote inclusivity in healthcare, revolutionize medical diagnostics and treatment, and drive a patient-centered healthcare transformation. © 2023 IEEE.

关键词： Accessible healthcare Business Canvas model Chronic health patient-centric diagnosis Photoplethysmogram Pulse Oximeter Purpose Launchpad radar Tele-medicine Value Preposition

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Roller chain-like robot for steel bridge inspection 9

Roller chain-like robot for steel bridge inspection

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9th International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII 2019

作者： Nguyen, Son Thanh La, Hung Manh Advanced Robotics and Automation Lab Department of Computer Science and Engineering University of Nevada RenoNV89557 United States

This paper presents a novel design of steel bridge/structure inspection robot. Compared to most existing robots designed to work on particular surface contour of steel structures such as flat or curving, the proposed roller chain-like robot can implement and transfer smoothly on many kind of steel surfaces. The developed robot can be applied to inspection tasks for steel bridges with complicated structures. The robot is able to carry cameras, sensors for visual and specialized examination. Rigorous analysis of robot kinematics, adhesion force and turn-over failure has been conducted to demonstrate the stability of the proposed design. Mechanical and magnetic force analysis together with turn-over failure investigation can serve as an useful framework for designing various steel climbing robots in the future. Experimental results and field deployments prove the adhesion, climbing, inspection capability of the developed robot. Copyright © SHMII 2019. All rights reserved.

关键词： Robots

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Resource allocation in UAV assisted air ground intelligent inspection system

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Cognitive Robotics 2022年 2卷 1-12页

作者： Zhang, Zhuoya Xu, Fei Qin, Zengshi Xie, Yue School of ordnance science and technology Xi'an Technological University Xi'An China Engineering Laboratory The State and Provincial Joint Engineering Lab. of Advanced Network Monitoring and Control Xi'An China School of Computer Science and Engineering Xi'an Technological University Xi'An China

With the progress of power grid technology and intelligent technology, intelligent inspection robot (IR) came into being and are expected to become the main force of substation inspection in the future. Among them, mobile edge computing provides a promising architecture to meet the explosive growth of communication and computing needs of inspection robot. Inspection robot can transmit the collected High Definition (HD) video to adjacent edge servers for data processing and state research and judgment. However, the communication constraints of long-distance transmission, high reliability and low delay pose challenges to task offloading optimization. Therefore, this paper introduced Unmanned Aerial Vehicle (UAV) and established UAV assisted mobile edge computing system. UAV assisted and mobile edge computing are combined to form edge computing nodes. In this way, it provided communication and computing services to the IR for fast data processing. Specifically, in order to optimize the system energy consumption, a resource allocation strategy based on genetic algorithm is proposed. By optimizing the offloading decision and computing resource allocation of the IRs, the computing task of the IRs are offloaded to an energy-efficient UAV. The experimental results show that the resource allocation strategy based on genetic algorithm can effectively reduce the energy consumption and cost of UAVs and IRs, and effectively realize the reasonable allocation of resources. The results verify the effectiveness and reliability of the algorithm in the real scene. © 2021

关键词： Resource allocation

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A flexible capacitive photoreceptor for the biomimetic retina

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Light(Science & Applications) 2022年第1期11卷 38-49页

作者： Mani Teja Vijjapu Mohammed E.Fouda Agamyrat Agambayev Chun Hong Kang Chun-Ho Lin Boon S.Ooi Jr-Hau He Ahmed M.Eltawil Khaled N.Salama Sensors lab Advanced Membranes and Porous Materials CenterComputerElectrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Communication and Computing Systems Lab ComputerElectrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Department of Electrical Engineering and Computer Science University of California-IrvineIrvineCA 92612USA Department of Electrical Computer and Energy EngineeringArizona State UniversityTempeAZUSA Computer Electrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Department of Materials Science and Engineering City University of Hong KongHong Kong SARChina

Neuromorphic vision sensors have been extremely beneficial in developing energy-efficient intelligent systems for robotics and privacy-preserving security *** is a dire need for devices to mimic the retina's photoreceptors that encode the light illumination into a sequence of spikes to develop such ***,we develop a hybrid perovskite-based flexible photoreceptor whose capacitance changes proportionally to the light intensity mimicking the retina's rod cells,paving the way for developing an efficient artificial retina *** proposed device constitutes a hybrid nanocomposite of perovskites(methyl-ammonium lead bromide)and the ferroelectric terpolymer(polyvinylidene fluoride trifluoroethylene-chlorofluoroethylene).A metal-insulator-metal type capacitor with the prepared composite exhibits the unique and photosensitive capacitive behavior at various light intensities in the visible light *** proposed photoreceptor mimics the spectral sensitivity curve of human photopic *** hybrid nanocomposite is stable in ambient air for 129 weeks,with no observable degradation of the composite due to the encapsulation of hybrid perovskites in the hydrophobic *** functionality of the proposed photoreceptor to recognize handwritten digits(MNIST)dataset using an unsupervised trained spiking neural network with 72.05%recognition accuracy is *** demonstration proves the potential of the proposed sensor for neuromorphic vision applications.

关键词： perovskite illumination preserving

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Vote and KNN outlier detection in Wireless Sensor Networks

Vote and KNN outlier detection in Wireless Sensor Networks

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2021 International Symposium on Networks, computers and Communications, ISNCC 2021

作者： Abid, Aymen Khediri, Salim El Moulahi, Tarek Cheour, Rym Kachouri, Abdennaceur Computer And Embedded Systems Lab National Engineering School Sfax Tunisia College Of Computer Department Of Infomration Technology Gabes Tunisia Advanced Fluid Dynamics Energetics And Evironment Lab National Engineering School Sfax Tunisia

ISBN: (纸本)9780738113166

The target of a Wireless Sensor Network (WSN) designer is to improve the robustness of the network while taking into account constraints such as verifying the detection of anomalies. Preventing anomalies can be assured by data analysis via outliers identification as it strongly affects decision-making in the case of smart-home, e-health and other high-risk applications. In this paper, we study some families of outliers and we propose to detect data anomalies using K Nearest Neighbours (KNN) and Voting techniques by a benchmark suitable to be a simulation for a smart-house. In order to evaluate the dependability, some performance metrics are analyzed such as data rate detection, precision, specificity and accuracy. Performance results are in the order of 100% detection rate with reduced false alarm and fast response time compared to some other existing ones. © 2021 IEEE.

关键词： Wireless sensor networks

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Potential Indicator for Continuous Emotion Arousal by Dynamic Neural Synchrony 4th

Potential Indicator for Continuous Emotion Arousal by Dyna...

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4th International Workshop on Human Brain and Artificial Intelligence, HBAI 2024

作者： Pan, Guandong Wu, Zhaobang Yang, Yaqian Wang, Xin Liu, Longzhao Zheng, Zhiming Tang, Shaoting School of Computer Science and Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Key Laboratory of Mathematics Informatics and Behavioral Semantics Beihang University Beijing100191 China Institute of Medical Artificial Intelligence Binzhou Medical University Yantai264003 China Zhongguancun Laboratory Beijing100094 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Beijing100191 China PengCheng Laboratory Shenzhen518055 China State Key Lab of Software Development Environment Beihang University Beijing100191 China

ISBN: (纸本)9789819640003

The need for automatic and high-quality emotion annotation is paramount in applications such as continuous emotion recognition and video highlight detection, yet achieving this through manual human annotations is challenging. Inspired by inter-subject correlation (ISC) utilized in neuroscience, this study introduces a novel Electroencephalography (EEG) based ISC methodology that leverages a single-electrode and feature-based dynamic approach. Our contributions are three folds: Firstly, we reidentify two potent emotion features suitable for classifying emotions-first-order difference (FD) an differential entropy (DE). Secondly, through the use of overall correlation analysis, we demonstrate the heterogeneous synchronized performance of electrodes. This performance aligns with neural emotion patterns established in prior studies, thus validating the effectiveness of our approach. Thirdly, by employing a sliding window correlation technique, we showcase the significant consistency of dynamic ISCs across various features or key electrodes in each analyzed film clip. Our findings indicate the method’s reliability in capturing consistent, dynamic shared neural synchrony among individuals, triggered by evocative film stimuli. This underscores the potential of our approach to serve as an indicator of continuous human emotion arousal. The implications of this research are significant for advancements in affective computing and the broader neuroscience field, suggesting a streamlined and effective tool for emotion analysis in real-world applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electroencephalography (EEG) Emotion Annotation Inter-subject Correlation

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DiaBD: A Diabetes Dataset for Enhanced Risk Analysis and Research in Bangladesh

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Data in Brief 2025年

作者： Tabia Tanzin Prama Md. Jobayer Rahman Marzia Zaman Farhana Sarker Khondaker A. Mamun Advanced Intelligent Multidisciplinary Systems (AIMS) Lab Institute of Research Innovation Incubation and Commercialization (IRIIC) United International University Dhaka 1212 Bangladesh CMED Health Ltd. Mohakhali DOHS Dhaka 1206 Bangladesh Department of Computer Science and Engineering Independent University Bangladesh (IUB) Dhaka 1229 Bangladesh Department of Computer Science and Engineering United International University (UIU) Dhaka 1212 Bangladesh

Diabetes is a chronic condition affecting millions worldwide and severely impacts health and quality of life. According to the International Diabetes Federation (IDF), over 463 million adults, which is 9.3% of the global population, live with diabetes. Diabetes ranks among the most prevalent chronic diseases and was the ninth-leading cause of mortality in 2019, with 4.2 million deaths reported. This article presents a dataset of 5,288 patient records from Bangladesh, addressing gaps in diabetes research and aiding in healthcare planning, risk analysis, and predictive modelling. The dataset comprises 14 attributes: age, gender, pulse rate, systolic and diastolic blood pressure, glucose levels, height, weight, body mass index (BMI), family history of diabetes and hypertension, cardiovascular disease (CVD), and stroke. A dependent attribute, Diabetic, indicates whether an individual has diabetes or not. The dataset ensures demographic diversity and precise measurements, supporting the study of diabetes and its related health issues. Features like CVD and stroke enable broader research on comorbidities. This dataset facilitates machine learning applications, risk assessment, and personalized healthcare strategies. Researchers can explore the links between diabetes, hypertension, CVD, and stroke, while healthcare providers and policymakers can leverage this to identify trends, allocate resources efficiently, and enhance public health strategies.

关键词： Diabetes Medical care Biometric Data Standardization Risk Factor Analysis Predictive Analysis

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Potential Indicator for Continuous Emotion Arousal by Dynamic Neural Synchrony

arXiv

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arXiv 2025年

作者： Pan, Guandong Wu, Zhaobang Yang, Yaqian Wang, Xin Liu, Longzhao Zheng, Zhiming Tang, Shaoting School of Computer Science and Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Key laboratory of Mathematics Informatics and Behavioral Semantics Beihang University Beijing100191 China Institute of Medical Artificial Intelligence Binzhou Medical University Yantai264003 China Zhongguancun Laboratory Beijing100094 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Beijing100191 China PengCheng Laboratory Shenzhen518055 China State Key Lab of Software Development Environment Beihang University Beijing100191 China

The need for automatic and high-quality emotion annotation is paramount in applications such as continuous emotion recognition and video highlight detection, yet achieving this through manual human annotations is challenging. Inspired by inter-subject correlation (ISC) utilized in neuroscience, this study introduces a novel Electroencephalography (EEG) based ISC methodology that leverages a single-electrode and feature-based dynamic approach. Our contributions are three folds: Firstly, we reidentify two potent emotion features suitable for classifying emotions—first-order difference (FD) an differential entropy (DE). Secondly, through the use of overall correlation analysis, we demonstrate the heterogeneous synchronized performance of electrodes. This performance aligns with neural emotion patterns established in prior studies, thus validating the effectiveness of our approach. Thirdly, by employing a sliding window correlation technique, we showcase the significant consistency of dynamic ISCs across various features or key electrodes in each analyzed film clip. Our findings indicate the method’s reliability in capturing consistent, dynamic shared neural synchrony among individuals, triggered by evocative film stimuli. This underscores the potential of our approach to serve as an indicator of continuous human emotion arousal. The implications of this research are significant for advancements in affective computing and the broader neuroscience field, suggesting a streamlined and effective tool for emotion analysis in real-world applications. © 2025, CC BY-NC-SA.

关键词： Neurons

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Integrated network interfaces for high-bandwidth TCP/IP

Integrated network interfaces for high-bandwidth TCP/IP

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作者： Binkert, Nathan L. Saidi, Ali G. Reinhardt, Steven K. Advanced Computer Architecture Lab. Department of Electrical Engineering and Computer Science University of Michigan Hewlett-Packard Labs. Reservoir Labs Inc.

ISBN: (纸本)1595934510

This paper proposes new network interface controller (NIC) designs that take advantage of integration with the host CPU to provide increased flexibility for operating system kernel-based performance *** believe that this approach is more likely to meet the needs of current and future high-bandwidth TCP/IP networking on end hosts than the current trend of putting more complexity in the NIC, while avoiding the need to modify applications and protocols. This paper presents two such NICs. The first, the simple integrated NIC (SINIC), is a minimally complex design that moves the responsibility for managing the network FIFOs from the NIC to the kernel. Despite this closer interaction between the kernel and the NIC, SINIC provides performance equivalent to a conventional DMA-based NIC without increasing CPU overhead. The second design, V-SINIC, adds virtual per-packet registers to SINIC, enabling parallel packet processing while maintaining a FIFO model. V-SINIC allows the kernel to decouple examining a packet's header from copying its payload to memory. We exploit this capability to implement a true zero-copy receive optimization in the Linux 2.6 kernel, providing bandwidth improvements of over 50% on unmodified sockets-based receive-intensive benchmarks. Copyright © 2006 ACM.

关键词： Interfaces (computer)

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