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LSGraph: A Locality-centric High-performance Streaming Graph Engine 24

LSGraph: A Locality-centric High-performance Streaming Graph...

引用

19th European Conference on Computer systems, EuroSys 2024

作者： Qi, Hao Wu, Yiyang He, Ligang Zhang, Yu Luo, Kang Cai, Minzhi Jin, Hai Zhang, Zhan Zhao, Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computer Science University of Warwick United Kingdom Zhejiang Lab China

ISBN: (纸本)9798400704376

Streaming graph has been broadly employed across various application domains. It involves updating edges to the graph and then performing analytics on the updated graph. However, existing solutions either suffer from poor data locality and high computation complexity for streaming graph analytics, or need high overhead to search and move graph data to ensure ordered neighbors during streaming graph update. This paper presents a novel locality-centric streaming graph engine, called LSGraph, to enable efficient both graph analytics and graph update. The main novelty of this engine is a differentiated hierarchical indexed streaming graph representation approach to achieve efficient data search and movement for graph update and also maintain data locality and ordered neighbors for efficient graph analytics simultaneously. Besides, a locality-aware streaming graph data update mechanism is also proposed to efficiently regulate the distance of data movement, minimizing the overhead of memory access during graph update. We have implemented LSGraph and conducted a systematic evaluation on both real-world and synthetic datasets. Compared with three cutting-edge streaming graph engines, i.e., Terrace, Aspen, and PaC-tree, LSGraph achieves 2.98×-81.08×, 1.46×-12.56×, and 1.26×-10.31× speedups during graph update, while obtaining 1.02×-4.28×, 1.58×-3.55×, and 1.20×-2.72× speedups during graph analytics, respectively. © 2024 Owner/Author.

关键词： Engines

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Review of Animal Remote Managing and Monitoring system 5

Review of Animal Remote Managing and Monitoring System

引用

5th Artificial Intelligence and Cloud Computing Conference, AICCC 2022

作者： Ojo, John Io Tu, Chunling Owolawi, Pius A Du, Shengzhi Plessis, Deon Du Department of Computer System Engineering Tshwane University of Technology Pretoria South Africa

ISBN: (纸本)9781450398749

Livestock is an integral part of everyday life contributing to the social, cultural, and economic sectors. Livestock farming faces challenges in animal remote management and monitoring, due to cost constraints and product quality requirements. The latest development of smart techniques, especially the Internet of Things (IoT) and cloud devices/services provide significant potential for efficient and secure farm management. This paper presents a review of smart farm management and monitoring systems for livestock based on IoT techniques, including the monitoring of animal behavior, weather condition, environment, and more. The review provides a comprehensive understanding of the sensing techniques, data analysis, communication, hardware, and software used in existing smart livestock solutions. © 2022 ACM.

关键词： Drones

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Preliminary Bilateral Upper Limb Rehabilitation system Based on sEMG and Muscle Tone 20

Preliminary Bilateral Upper Limb Rehabilitation System Based...

引用

20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Wang, Hanze Guo, Shuxiang Li, He Bu, Dongdong Key Laboratory of Convergence Biomedical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology Beijing Institute of Technology Beijing100081 China Southern University of Science and Technology The Department of Electronic and Electrical Engineering Guangdong Shenzhen518055 China

ISBN: (纸本)9798350320831

In recent years, with the increasing number of stroke patients, master-slave telerehabilitation has become one of the research hotspots in the field of rehabilitation. However, when estimating the angle of the main end, the angle estimation model is difficult to be widely applicable due to the different muscle tension of the physiotherapist itself. During remote rehabilitation training, it is difficult for physical therapists to obtain the damage of the affected limb, so it is difficult to arrange appropriate training intensity and training volume, which affects the effect of remote rehabilitation to a certain extent. To address these issues, this paper proposes a novel master-slave rehabilitation system. The therapist obtains his own muscle tension level a priori through FSR402, and jointly estimates the movement angle through the (Surface Electromyography) sEMG signal collected by MYO, so as to control the slave end. While following the rehabilitation training, the patient at the slave end reflects real-time muscle force of the affected limb and the true feeling of the movement to the master end through the muscle tension measurement arm cuff and the relevant buttons on the PC end. The overall system realizes data transmission through (User Datagram Protocol) UDP, so as to realize more secure and personalized master-slave control. The experiment proves that the new master-slave rehabilitation system is real and feasible. © 2023 IEEE.

关键词： Muscle

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A joint sparse Bayesian learning for wideband DOA estimation

A joint sparse Bayesian learning for wideband DOA estimation

引用

2024 Conference on Spectral technology and Applications, CSTA 2024

作者： Zhao, Yonghong Liu, Jisong Wang, Junlong Dong, Shuxin Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Department of Automation and Information Engineering Xi'an University of Technology Shaanxi Xi'an710048 China

ISBN: (纸本)9781510683082

Wideband direction of arrival (DOA) estimation using sensor array is a noteworthy problem frequently occurring in many applications involving radar, sonar, and communication. We present a wideband DOA method based on a sparse Bayesian learning of multiple sub-bands jointly with the redundant dictionary matrix at the reference frequency. Explicitly enforcing the focusing operation and the singular value decomposition (SVD) to sensor measurements is motivated by a desire to decrease the computational complexity and storage capacity. A joint sparse Bayesian learning framework is proposed to deal with multiple sub-bands under one segment to obtain the DOA information. Moreover, the proposed method can be directly extended to multiple segments. Comparing to other wideband DOA estimation methods, the proposed method has the advantages of increased resolution, higher accuracy, and correlation of the sources, as well as not requiring the initial angles for the focusing matrix. Simulations are provided to show the effectiveness and improved performance of the proposed method. © 2024 SPIE.

关键词： Direction of arrival

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Enhancing Network Intrusion Detection Using Effective Stacking of Ensemble Classifiers With Multi-Pronged Feature Selection Technique 2

Enhancing Network Intrusion Detection Using Effective Stacki...

引用

2nd International Conference on Emerging Trends in Electrical, Control, and Telecommunication engineering, ETECTE 2023

作者： Rahman, Saifur Mursal, Salim Nasar Faraj Latif, Muhammad Armghan Mushtaq, Zohaib Irfan, Muhammad Waqar, Ali Najran University College of Engineering Department of Electrical Engineering Najran Saudi Arabia Cleveland State University Department of Computer and Information System United States University of Sargodha College of Engineering and Technology Department of Electrical Engineering Sargodha Pakistan North China electric power University Beijing China

ISBN: (纸本)9798350305654

Information security depends on Network Intrusion Detection (NID), which properly identifies network threats. This work explores simulating a NID system by stacking ensemble classifiers with various feature selection methods. We used the NSL-KDD dataset for the investigation. The binary classification performance integrates all assaults into one class and treats another target variable as usual. Random Forest (RF), Bagging Classifier (BC), and Extra Tree Ensemble (ETE) using Logistics Regression (LR) as a meta estimator. Chi2-square (Chi2) and Recursive Feature Elimination (RFE) are also used for feature selection. The experimental findings suggest that the proposed technique is ideal for developing a classification model with high accuracy and outperforms standard machine learning classification methods. The Chi 2 attribute selection strategy with modest characteristics has the greatest accuracy of 99.84 %. A careful comparison with prior research shows that our technique produces state-of-the-art performance with reduced computing costs. © 2023 IEEE.

关键词： Feature Selection

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Investigations on Improving Wide Angular Beam Scanning of Conformal X-Band Array Antennas by Tunable Metasurfaces

Investigations on Improving Wide Angular Beam Scanning of Co...

引用

2024 IEEE International Symposium on Phased Array systems and technology, ARRAY 2024

作者： Badawy, Taher Bertuch, Thomas Weinmann, Frank Knott, Peter Antennas and Frontend Fraunhofer FHR Wachtberg Germany IHF-Institute of High Frequency Technology RWTH Aachen University Department of Radar System Engineering Aachen Germany

ISBN: (纸本)9798350392142

This paper presents an investigation on improving the radiation characteristics of a conformal X-band array antenna by means of a low profile dual-polarized tunable metasurface structure. The considered configuration consists of several tunable metasurface planar circuit boards arranged in a faceted manner and excited by a conformal antenna array. The electromagnetic transmission properties of the tunable meta-surface structure are controlled by applying DC bias voltages to the varactor diodes integrated into the metasurface's unit-cell structure. The transmission phase response of this tunable metasurface can be tuned in a range up to 170° for both polarizations. Experimental investigations are performed on a demonstrator consisting of a faceted planar tunable metasurface configuration integrated with a conformal antenna array. The tunable metasurface performs phase compensation (like a lens) and beam steering. The measurement results demonstrate that the tunable metasurface slightly improves the beam scanning capabilities of the conformal antenna array in the horizontal plane for both polarizations at 10 GHz. © 2024 IEEE.

关键词： Antenna phased arrays

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Research on Immersion Evaporative Cooling Under Different Pressure Conditions in High Power Density Motor 27

Research on Immersion Evaporative Cooling Under Different Pr...

引用

27th International Conference on Electrical Machines and systems, ICEMS 2024

作者： Liu, Yuqing Cao, Jiwei Chen, Bin Liu, Jiaxi Song, Yuchen Li, Liyi Harbin Institute of Technology Department of Electrical Engineering Harbin China Guangdong Provincial Key Laboratory of High-speed and Energy Conservation Motor System Zhuhai China

ISBN: (纸本)9784886864406

Temperature rise is one of the main factors affecting the safe operation of motors. In order to improve the thermal efficiency of the motor, this study explores the immersion evaporative cooling technology used in permanent magnet synchronous motors, focusing on the performance of the cooling system under different pressure environments. The influence of internal pressure of the device on the working time of the motor is analyzed. The operable time of the motor is predicted through multiple iterations. In addition, the cooling effectiveness of the motor was compared under unsealed, sealed (no pressure valve) and sealed (with pressure valve), using oil, water, and Novec7300 as heat exchange media, aiming to provide scientific basis and reference for the design and optimization of evaporative cooling systems for small and medium-sized motors. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Evaporative cooling systems

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A Resistance Change Detection Circuitry for Thread Based Resistive Sensors

A Resistance Change Detection Circuitry for Thread Based Res...

引用

2023 IEEE Applied Sensing Conference, APSCON 2023

作者： Samaddar, Narendranath Wani, Mohamad Idris Maharshi, Vikram Sonkusale, Sameer Malik, Shahid Indian Institute of Technology Centre for Sensors Instrumentation and Cyber Physical System Engineering Delhi New Delhi India Indian Institute of Technology Department of Electrical Engineering Delhi New Delhi India Tufts University Department of Electrical and Computer Engineering Boston Medford United States

ISBN: (纸本)9781665461634

Resistive pressure sensors such as strain gauge's have immense industrial applications due to low-cost and moderate to high sensitivity. Their applications have grown recently with the advancement in flexible resistive pressure sensors. However, the resistance of these sensors is highly affected by drift and offset resistance. Conventionally, voltage dividers and Wheatstone bridge-based circuits have been used for interfacing such sensors. However such interfacing circuits need calibration for offset resistance compensation. But the problem due to drift in resistance is still present. In this paper, a novel circuit is proposed to compensate for the offset and drift of these sensors. The proposed circuit detects the change in resistance using auto-zeroing feedback loop. The proposed circuit is tested with a fabricated thread-based pressure sensor for touch detection. Experimental results show that R variations as low as 10 Ω can be detected with a wide range of sensor resistance measurement. The error of measurement in sensor resistance is less than 1%. © 2023 IEEE.

关键词： Pressure sensors

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A Classification Method for ECG Signals Based on Convolutional Neural Network 20

A Classification Method for ECG Signals Based on Convolution...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Yang, Yuan Guo, Jin Lyu, Fengze Guo, Shuxiang Beijing Institute of Technology The Key Laboratory of Convergence Biomedical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology Beijing100081 China Southern University of Science and Technology The Department of Electronic and Electrical Engineering Guangdong Shenzhen518055 China

ISBN: (纸本)9798350320831

Cardiovascular disease is a chronic disease with high incidence, high disability and high mortality, which poses a great threat to the life and health of people all over the world. At present, the incidence and mortality of cardiovascular disease are increasing year by year worldwide, so the prevention and treatment of cardiovascular disease has become a top priority. In recent years, with the development of computer technology in the field of auxiliary diagnosis and treatment, the research on automatic classification of Electrocardiogram (ECG) signals has ushered in new opportunities. In this study, ECG signals are taken as the research object, to analyze the auxiliary diagnosis needs of users such as patients and pathologists. This study mainly uses ECG data from MIT-BIH database, combined with relevant preprocessing knowledge and deep learning classification model, to achieve ECG reading, denoising, segmentation, classification and so on. It can effectively improve the efficiency of diagnosis. It has certain reference value for assisting users to diagnose arrhythmia. © 2023 IEEE.

关键词： Convolutional neural networks

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Adaptive Confidence Threshold for ByteTrack in Multi-Object Tracking 12

Adaptive Confidence Threshold for ByteTrack in Multi-Object ...

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12th IEEE International Conference on Control, Automation and Information Sciences, ICCAIS 2023

作者： Ma, Linh Van Hussain, Muhammad Ishfaq Park, JongHyun Kim, Jeongbae Jeon, Moongu Gwangju Institute of Science and Technology School of Electrical Engineering and Computer Science Korea Republic of Pusan National University Department of Mechanical-IT Convergence System Engineering Busan Korea Republic of

ISBN: (纸本)9798350328783

We investigate the application of ByteTrack in the realm of multiple object tracking. ByteTrack, a simple tracking algorithm, enables the simultaneous tracking of multiple objects by strategically incorporating detections with a low confidence threshold. Conventionally, objects are initially associated with high confidence threshold detections. When the association between objects and detections becomes ambiguous, ByteTrack extends the association to lower confidence threshold detections. One notable drawback of the existing ByteTrack approach is its reliance on a fixed threshold to differentiate between high and low-confidence detections. In response to this limitation, we introduce a novel and adaptive approach. Our proposed method entails a dynamic adjustment of the confidence threshold, leveraging insights derived from overall detections. Through experimentation, we demonstrate the effectiveness of our adaptive confidence threshold technique while maintaining running time compared to ByteTrack. © 2023 IEEE.

关键词： Object detection

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