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TCRing: A Novel Single-Channel Deadlock-Free Concentrated on-Chip Network 24

TCRing: A Novel Single-Channel Deadlock-Free Concentrated on...

引用

24th IEEE International Conference on High Performance computing and Communications, 8th IEEE International Conference on Data Science and Systems, 20th IEEE International Conference on Smart City and 8th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Zhenjiang, Guo Huandong, Wang Longbing, Zhang Junhua, Xiao Institute of Computing Technology University of Chinese Academy of Sciences Beijing China Loongson Technology Co. Ltd. Beijing China

ISBN: (纸本)9798350319934

On-chip network designed for modular System-on-Chip(SoC) has recent became a research hotspot, especially when methodology is employed rather than programmer experience. Most of the existing research relies on a specific topology, or modification to the subnet inside a module. In this paper, we propose TCRing, a novel concentrated network-on-chip. TCRing is a bi-directional ring with only three routers, but has the ability to mount one or more nodes on each router. Despite the fact that TCRing has only one channel, there is no deadlock problem. In addition, TCRing's simple architecture is friendly to physical layout. However, the low-complexity design does not compromise the flexibility and scalability of TCRing. An irregular modular SoC based on TCRing is given as an example in this paper. Based on the Booksim2.0 simulator, TCRing has 33% lower latency and 50% higher throughput than traditional concentrated rings in uniform traffic patterns. Besides, TCRing consistently maintains low latency in neighbor and randperm traffic at any injection rates. TCRing is capable of dispersing congestion traffic by enabling adaptive routing. Excitingly, irregular TCRing performs better than regular topology, indicated that it is capable of dealing with complex application scenarios. Design Compiler results show that TCRing saves 30% area and 20% power consumption. © 2022 IEEE.

关键词： Topology

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Edge Detection in Dark Industrial Environments 9

Edge Detection in Dark Industrial Environments

引用

9th International Conference on Computer and Communications, ICCC 2023

作者： Jing, Dongdong Li, Beibei Wang, Shiyu Lin, Jinrong Jiao, Yu University of Chinese Academy of Sciences Shenyang Institute of Computing Technology Shenyang China University of Chinese Academy of Sciences Beijing China Shenyang Casnc Technology Co. Ltd. Shenyang China

ISBN: (纸本)9798350317251

To solve the problem that current edge detectors cannot accurately detect the edges of artifacts under low-light conditions, we propose an edge detection network-EDD that adapts to scale changes and low-light environments. First, we utilize a feature pyramid to divide the features of the input image into 4 stages of different resolutions. Second, we introduce a scale enhancement module to obtain feature information at different scales. In addition, in order to solve the challenge of inconspicuous edge details in low-light environments, we design a high frequency enhancement module. We conduct experimental verification on the BSDS500 dataset and our own artifact dataset MPBD, and the results show that EDD has a significant edge detection effect in low-light environments. Compared with other methods, EDD can capture the edge of the workpiece more accurately, and provides an effective solution to the edge detection problem in dark conditions. © 2023 IEEE.

关键词： Edge detection

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Enhancing Electric Vehicle Energy Conservation through ML Algorithms

Enhancing Electric Vehicle Energy Conservation through ML Al...

引用

2024 IEEE International BIT Conference, BITCON 2024

作者： Manda, Jolly Viji, D. SRM Institute of Science and Technology Department of Computing Technologies Kattankulathur Chennai India

ISBN: (纸本)9798331518394

A novel approach has been considered for energy consumption and how it can be optimized for industries utilizing microgrids powered by renewable energy sources (RES). The targeted industry includes a microgrid, an integrated system with photovoltaic cells (PV), electric vehicles (EV), charging stations, and additional renewable energy generation methods. The main goal of the application created is to provide predictive analysis on energy generation, consumption, and availability by utilizing historical and real-time inputs. The system will be providing the EV users with automatic notifications regarding the optimal period to charge the EV. By constant monitoring of the EV user battery levels, timely alerts can be delivered to users on charging their vehicle. In addition, the system also facilitates bidirectional energy flow (BEF), a process that includes vehicle-to-grid (V2G) and grid-to-vehicle (G2V) between EVs and microgrids, allowing EVs to return energy back to the grid during low-generation periods of renewable energy. This approach will contribute to maintaining grid stability, reducing load consumption costs, and enhancing energy resilience within the industry. Overall, this system represents a significant contribution to sustainable energy management by ensuring efficient utilization of renewable energy resources and improving industrial energy autonomy. © 2024 IEEE.

关键词： Electric vehicles

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DTC Implementation on SRM using Mid-Point Converter: Simulation and Experimental Validation 23

DTC Implementation on SRM using Mid-Point Converter: Simulat...

引用

23rd National Power Systems Conference, NPSC 2024

作者： Sharma, Nishant Mishra, Himanshu School of Computing and Electrical Engineering Indian Institute of Technology HP Mandi India

ISBN: (纸本)9798331519568

Switched Reluctance Motors (SRMs) are known for their durable design, rendering them well-suited for demanding environments and high-speed operations. They offer advantages such as high torque density and fault tolerance, making them increasingly favored in electric vehicle propulsion systems and industrial automation. However, their inherent drawback of high torque ripple limits their applicability. This research endeavors to address this limitation by proposing a novel approach exploring the integration of Direct Torque Control (DTC) with a Mid-Point converter designed for 8/6 SRMs, aiming to enhance motor performance and reduction in torque ripple. The implementation of a mid-point converter, which employs fewer switches, helps reduce losses, while DTC is utilized to minimize torque ripple and acoustic noise. The DTC control strategy is initially simulated using MATLAB Simulink and subsequently experimentally validated with the TI28379D DSP controller. © 2024 IEEE.

关键词： MATLAB

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Biogas Fermentation Monitoring Research Based on Borderline-SMOTE Algorithm and Stacking Ensemble Learning 13

Biogas Fermentation Monitoring Research Based on Borderline-...

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13th International Conference of Information and Communication technology, ICTech 2024

作者： Xiu, Pengfei Fu, Lijun Sun, Yukun Wang, Hongliang Li, Xuerao Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Liaoning Province Human-Computer Interaction System Engineering Research Center Based on Digital Twin Shenyang China Shandong University Big Data Technology and Cognitive Intelligence Laboratory University of Chinese Academy of Sciences Shenyang China Shenyang Institute of Computing Technology Chinese Academy of Sciences Liaoning Province Human-Computer Interaction System Engineering Research Center Based on Digital Twin Shenyang China

ISBN: (纸本)9798350376258

Anaerobic fermentation is the most important link to gas production, this paper solves the current problem with the help of the current complete machine learning technology, combining perception and intelligent processing, intelligent processing of information, and derive a decision-making basis for its control or management [1]. Aiming at the current problems of the anaerobic fermentation process in biogas engineering, the system design was carried out, and the anaerobic fermentation process of biogas and its main influencing factors were investigated, and the monitoring parameters of the system were selected to be temperature, PH value, liquid level and redox potential [2]. Previous studies are mainly based on a single prediction model, which leads to poor generalization ability of the model. In this study, unbalanced samples are handled by Borderline-SMOTE algorithm. Based on the Stacking integrated learning approach, a common single prediction model is used to construct a combined prediction model. The accuracy, precision, recall, F1 score and area under the ROC curve are used to evaluate the advantages and disadvantages of the combined prediction model over the single prediction model. ©2024 IEEE.

关键词： Decision making

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Revisiting Temporal Inconsistency and Feature Extraction for Android Malware Detection

Revisiting Temporal Inconsistency and Feature Extraction for...

引用

Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Maryam Tanha Arunab Singh Gavin Knoke School of Computing and Academic Studies British Columbia Institute of Technology Burnaby Canada

ISBN: (数字)9798350371628

ISBN: (纸本)9798350371635

The growing popularity and ease of access have turned Android applications into prime targets for malicious attackers. Within the security research community, machine learning has become an essential instrument for conducting Android malware detection and analysis. However, there are potential threats to validity of existing studies, mainly resulting from their used datasets. One of the primary issues is temporal inconsistency (also called temporal bias) that is caused by incorrect time splits of training and testing sets or using imprecise indicators for release time of apps. This paper investigates the use of Google Play Store upload year of an app as a precise indicator of its release time to address temporal bias in machine learning-based Android malware detection. Using this approach is made possible by AndroZoo’s December 2023 data release. Through a three-layer filtering process, we demonstrate the unreliability of the commonly used dex_date as the release time of an app and propose a more accurate approach for creating temporally-consistent datasets based on an app’s upload year. Additionally, we have open-sourced our data and feature extraction process for Android malware analysis, supporting both server-side and on-device extraction, to enhance research reproducibility and facilitate community access.

关键词： Training Instruments Machine learning Feature extraction Malware Reproducibility of results Vectors

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A Distributed Data Integration Fault Tolerant Platform for Performance Optimization in Shooting Sports

A Distributed Data Integration Fault Tolerant Platform for P...

引用

International Conference on Computer and Communications (ICCC)

作者： Ze Li Junda Wu Xulong Shu Yue Liu Shenyang Institute of Computing Technology University of Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

In today’ s fast-paced and highly competitive landscape, there is an ever-growing need to enhance the precision, agility, and overall performance of athletes, especially in sports that demand high levels of accuracy and coordination, such as shooting. With the rapid advancement of technology, the role of data analytics in athletic training has gained substantial attention, serving as a powerful tool to elevate athlete performance. This study aims to develop an integrated data platform to support a more precise and holistic approach to training for shooting athletes. By seamlessly combining various types of response and performance data - such as manual reaction times, shooting response times, eye-tracking data, video analyses, and biomechanical data-with a distributed Elasticsearch (ES) data synchronization system, the platform enables comprehensive data collection and analysis. This integration provides invaluable insights into the training status and individual differences of athletes, offering scientific, data-driven guidance for coaches. Furthermore, a robust distributed disaster recovery system is implemented by synchronizing two Elasticsearch clusters with a MySQL database. Although the primary and backup switch mechanisms are still under development, an automated script continuously monitors system health, allowing for rapid failover to backup clusters when necessary. This research opens new avenues in the application of data-driven platforms for athletic performance enhancement, providing a resilient infrastructure for continuous, uninterrupted data analytics, and setting a foundation for future enhancements in sports training methodologies.

关键词： Training Disasters Distributed databases Training data Data warehouses Real-time systems Synchronization Time factors Monitoring Sports

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A Novel Mobile Application for Personalized Hair Care Using Advanced Machine Learning Techniques

A Novel Mobile Application for Personalized Hair Care Using ...

引用

Advancements in computing (ICAC), International Conference on

作者： Anjali Kiriella Samadhi Rathnayake Thusithanjana Thilakarthna Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

Recent advancements in computer vision and machine learning have enabled personalized hair care, advancing beyond traditional methods by catering to individual hair types and health. This paper presents Glowllp, a mobile application that provides personalized hair care recommendations through three primary modules: image quality assessment, hair type detection, and health prediction. The image quality assessment module employs edge detection and SVM classifiers to filter blurry images, achieving over 95% accuracy. For hair type classification, a hybrid model of Mask R-CNN and Vision Transformers (ViTs) identifies hair types with 92% accuracy. The health assessment module predicts hair loss and other conditions using Random Forest and XGBoost models with an F1 score of 0.91, while K-means clustering further tailor's recommendations. By integrating these modules, Glow Up delivers a comprehensive, user-friendly solution that enhances hair care personalization.

关键词： Hair Image quality Support vector machines Computer vision Accuracy Image edge detection Predictive models Transformers Mobile applications Random forests

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Advancing Neural Network Performance with Probabilistic computing for ReLU Function

Advancing Neural Network Performance with Probabilistic Comp...

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International Conference on VLSI Design

作者： Amit Singh Amit Kumar Jangid B. Srinivasu School of Computing & Electrical Engineering (SCEE) Indian Institute of Technology Mandi Mandi India

ISBN: (数字)9798331522445

ISBN: (纸本)9798331522452

Probabilistic computing (using p-bits), based on stochastic computing, can operate in an invertible mode, enabling bidirectional operations. This functionality addresses significant challenges, improves neural network training, and opens new possibilities in neural networks. This article presents a framework and robust approach for designing p-circuits of logic circuits using p-bits to enhance probabilistic computing. This paper presents the design of a 2 × 1 multiplexer, a two-input non-imply logic gate (AB), and a ReLU activation function using the Hamiltonian method. Further, this paper presents two designs of ReLU, one using AND gate while the second design uses a non-imply logic gate. The non-imply gate based ReLU requires fewer number of p-bits. In particular, a 10-bit ReLU takes 20 p-bits, with ten inputs and ten outputs. Further, the proposed approach results the design with a lower graph density of 0.26 for the 5-bit proposed ReLU, whereas the best existing design has a graph density of 0.45. The proposed p-circuits were simulated, and results demonstrate the invertible nature of the p-circuits,

关键词： Multiplexing Training Embedded systems Logic circuits Neural networks Logic gates Very large scale integration Probabilistic logic Probabilistic computing

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Post-Quantum Single Sign-On Solution

Post-Quantum Single Sign-On Solution

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International Conference on Computer and Applications (ICCA)

作者： Meeran Hassan Ravindu Nimsara Rashmi Dharmawardhane Vishwa Basnagoda Kavinga Yapa Abeywardena Deemantha Siriwardana Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798350367560

ISBN: (纸本)9798350367577

Quantum computers pose a significant threat to widely used public-key cryptosystems, endangering current authentication and authorization systems. This paper presents a post-quantum Single Sign-On (SSO) solution that integrates Post-Quantum Cryptography (PQC) algorithms, specifically ML-DSA and ML-KEM, for authentication and authorization. The proposed system demonstrates a 90% improvement in token generation speed post-migration from traditional cryptosystems and a 331% increase in key-storage speed when storing PQC keys using a novel vector database mechanism. Additionally, an enhanced risk-based authentication model is developed, achieving a 98% accuracy in detecting risky logins, surpassing existing models. These contributions offer a comprehensive, efficient, and secure SSO system resistant to quantum attacks, addressing the limitations of current systems that do not fully integrate PQC algorithms or optimized key storage solutions.

关键词： Computers Authorization Resistance Quantum computing Accuracy Databases Authentication Benchmark testing Vectors Cryptography

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