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检索条件"主题词=software algorithms"

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A Lightweight AES Algorithm Optimization for NoC Communication

A Lightweight AES Algorithm Optimization for NoC Communicati...

引用

Computer Applications and Information Technology (ISCAIT), International Symposium on

作者： Chenhao Liu Lin Gu China Electronics Technology Group Corporation 58th Research Wuxi China

ISBN: (数字)9798331542856

ISBN: (纸本)9798331542863

In response to the contradiction between high throughput and low hardware overhead faced by data encryption in Network on Chip (NoC) communication, this paper proposes a lightweight AES implementation method based on chaos initial permutation (IP) matrix and look up table optimization based on composite field $\mathrm{GF}\left(2^{4}\right)^{2}$. By introducing the Logistic-Tent composite chaotic system to generate a nonlinear initial permutation matrix, replacing the SubBytes operation, randomness of the diffusion layer is effectively improved; Composite filed $\mathrm{GF}\left(2^{4}\right)^{2}$ compress the storage size of the look up table to 12.5% of the original structure (from 4KB to 0.25KB). The average encryption time is optimized by 26.6% compared with SIMON, and only increase 4.5% average execution time of base NoC in Gem5 simulator. NIST tests are also used to evaluate the effectiveness of proposed algorithm. All results have shown that this method significantly improves the adaptability of AES in NoC.

关键词： Chaotic communication software algorithms NIST Throughput Hardware software Encryption Table lookup SIMO Optimization

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Traffic Signal Timing Optimization at Urban Intersections Based on Differential Evolution Algorithm

Traffic Signal Timing Optimization at Urban Intersections Ba...

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2025 2nd International Conference on algorithms, software Engineering and Network Security (ASENS)

作者： Haigang Kang Zhenwei Huang Chuanghui Yang Kaichun Zheng Shengtong Mai Zhanjiang Yuan Jianhua Hu Xiangfei Feng Wei Nie Guangdong Polytechnic of Science and Technology Zhuhai China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

With the acceleration of urbanization in China, urban road construction has gradually lagged behind, unable to meet the increasing transportation demand. To alleviate the problem of over-saturation at intersections, this paper proposes an optimization model for intersection signal timing based on the average vehicle delay cost, average vehicle stops, and overall traffic throughput as optimization objectives. A multi-objective nonlinear function model is established for intersection signal timing, and the Differential Evolution (DE) algorithm is employed for initialization, mutation, crossover, and selection operations to iteratively optimize each individual, aiming to find the optimal signal timing strategy. The results show that the DE algorithm, by optimizing green light durations, phase combinations, and flow balancing, reduces average delays to 27.16~35.67 seconds, average stops to 0.70, and improves intersection throughput, effectively alleviating traffic congestion at intersections.

关键词： Costs Roads Optimization models software algorithms Urban areas Transportation Throughput Delays Optimization Traffic congestion

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Resource Scheduling of High-Performance Computing Clusters based on the Combination of Ant Colony Algorithm and Active Caching Strategy

Resource Scheduling of High-Performance Computing Clusters b...

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Cloud Computing, Big Data Applications and software Engineering (CBASE), International Conference on

作者： Xuemei Bai Jingbo Zhou Zhijun Wang School of Electronic Information Engineering Changchun University of Science and Technology Changchun China School of Coumputer Science and Technology Changchun Normal University Changchun China

ISBN: (数字)9798331506582

ISBN: (纸本)9798331506599

In recent years, the HPC cluster has developed rapidly and has become an important tool to solve large-scale and complex computing problems. However, in a cluster environment, how to efficiently schedule HPC cluster resources has become a problem worthy of attention. Based on this, this paper proposes a scheduling strategy that integrates the ant colony algorithm and active cache to minimize resource scheduling time and maximize resource utilization. Simulation results show that compared with the ant colony algorithm, the new strategy proposed in this paper can improve the efficiency of resource scheduling, significantly reduce the scheduling time, greatly improve the resource utilization rate, and significantly reduce the job loss rate.

关键词： Greedy algorithms Schedules Processor scheduling Simulation High performance computing software algorithms Clustering algorithms Scheduling Resource management software engineering

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Mining More Inter-Cluster Association Information to Improve Ensemble Clustering

Mining More Inter-Cluster Association Information to Improve...

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software Engineering and Computer Science (CSECS), International Conference on

作者： Ruihan Li Fusheng Yu School of Mathematical Sciences Beijing Normal University Beijing People's Republic of China

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Ensemble clustering has gained increasing attention for its critical role in data analysis. Recent studies emphasize the importance of mining inter-cluster relationships instead of relying solely on pairwise similarities. However, existing methods often fail to fully exploit the global structure of inter-cluster association graphs, limiting their effectiveness. To address this, we propose a Deep Walk-based method to mine and utilize inter-cluster association information more effectively. By learning embeddings of cluster nodes, the approach captures multi-scale and global inter-cluster relationships, which are then incorporated into the co-association matrix to enhance clustering performance. Furthermore, we introduce an adaptive linkage selection strategy for hierarchical clustering as the consensus function. Unlike existing methods with fixed linkage modes, our approach leverages the inter-cluster association graph to adaptively select the most suitable linkage strategy, improving adaptability across diverse datasets. Experimental results on multiple datasets demonstrate that the proposed algorithm achieves superior performance and robustness, validating its effectiveness in ensemble clustering.

关键词： Couplings Limiting Heuristic algorithms Scalability software algorithms Clustering algorithms Data structures Robustness Data mining software engineering

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Medical Insurance Fraud Risk Monitoring and Identification Model Based on Feature Selection and Machine Learning

Medical Insurance Fraud Risk Monitoring and Identification M...

引用

Cloud Computing, Big Data Applications and software Engineering (CBASE), International Conference on

作者： Junwei Feng Mingze Li Yiming Feng Yiran Xin Yuhang Zhao Yongxin Jiang Yixiao Zhang Fayuan Li Northwestern Polytechnical University Xi'an China

ISBN: (数字)9798331506582

ISBN: (纸本)9798331506599

Medical insurance fraud has the characteristic of concealment and is challenging to detect promptly through manual investigation. Therefore, a dataset was collected for medical insurance monitoring and a model was designed for automatically detecting medical insurance fraud based on big data technology. This article first visualizes the dataset, removes abnormal samples, and explores the distribution and feature correlation of the dataset. Afterward, the dataset was divided into a training set and a testing set, and the training set was used to train ten machine learning algorithms. The four baseline algorithms were selected with the best performance: XGBoost, LightGBM, CatBoost, and Random Forest. A feature selection algorithm has been designed based on the concept of greed, which selects three of the most essential features from 80 features while still ensuring high accuracy. Finally, the baseline model was trained using the three selected features, and grid search was used for parameter tuning. After model fusion, an accuracy of 92.3% was achieved on the test set.

关键词： Training Machine learning algorithms Accuracy software algorithms Insurance Feature extraction Data models Fraud Tuning Monitoring

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Power Control in Dual Active Clamp DC-DC Converter with Non-Isolated DC-DC Converter for MPPT (INC Method) with Varying Temperatures for Photovoltaic Applications

Power Control in Dual Active Clamp DC-DC Converter with Non-...

引用

International Conference on Devices, Circuits and Systems (ICDCS)

作者： Manish K S. Jaanaa Rubavathy S. Gomathi Saveetha School of Engineering SIMATS Saveetha University Chennai

ISBN: (数字)9798350350470

ISBN: (纸本)9798350350487

This work aims to manage power in a dual active clamp (DAC)DC-DC converter at different temperatures using the Inc Method, which is an MPPT algorithm. The implementation and investigation of the voltage are examined by comparing a (DAC) DC-DC converter with a non-isolated(NI) step-up DC-DC converter. One way to control the converter's power and thus the temperature is with maximum power point tracking (MPPT). After utilising the GPower software to determine the sample size, it was found that each algorithm has 7 samples, and a grand total of 14 sample tests were conducted (G Power 0.8). There are two separate T-tests run on the two sets of data. It is deemed statistically significant when the corresponding P value for a difference is lower than 0.039 (p<0.05). Comparing the power-regulated DAC DC Converter (120.00) to the NI Converter (48.00), the former performed better in terms of the mean bar value of the input and output voltage.

关键词： Maximum power point trackers Photovoltaic systems Power system management software algorithms DC-DC power converters software Temperature control

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Boolean Algorithm Empirical Results for a PV Dual-Axes Tracking-Type System

Boolean Algorithm Empirical Results for a PV Dual-Axes Track...

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IEEE Asia Power and Energy Engineering Conference (APEEC)

作者： Motlatsi Cletus Lehloka Department of Electrical Engineering University of South Africa Roodepoort South Africa

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

Renewable energy sources, such as solar photovoltaic (PV) systems are becoming more popular globally due to their profuse availability and eco-friendly nature. Given that the sun moves daily, an effective solar PV system setup is not straightforward. Harvesting of solar energy from a PV module efficiently is affected not only by varying environmental conditions, but also by the installation angles, load profile, latitude of the location of interest and energy management system. PV module energy conversion can further be increased by using solar tracking technologies. The purpose of this study was to develop an effective algorithm for automatic solar tracking system using Boolean algorithm in order to optimize the output power from a dual-axes tracking-type system. A fixed-type PV module installed at tilt angles of 16° served as the baseline to the dual-axes tracking type system. The Boolean algorithm was developed in a National Instruments (NI) LabVIEW user interface software. The direct-tracking system power showed 32 % improvement over the fixed-system power. The study only focused on the summer season in the Highveld of South Africa prompting that further study needs to be conducted for the other seasons to establish if the results will still hold.

关键词： Photovoltaic systems Renewable energy sources Tracking Instruments software algorithms Solar energy User interfaces

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A New Integrated Instrument for Partial Discharge Monitoring and Diagnostics of Medium Voltage Cables

A New Integrated Instrument for Partial Discharge Monitoring...

引用

AEIT Annual Conference

作者： Manuel Sozzi Sergio Chiarello Giovanni Pirovano Johnny Borghetto Alfredo Contin Transmission & Distribution Tech Dept Ricerca sul Sistema Energetico Milan Italy Dept Enigineering & Architecture -DIA University of Trieste Trieste Italy

ISBN: (数字)9788887237627

ISBN: (纸本)9798350378498

The main features of a new integrated instrument designed for Partial Discharge (PD) monitoring and diagnostics of Medium Voltage (MV) cables, are summarized in this paper. The instrument is based on a multi-channel acquisition system that allows monitoring the PD activity in a given number of tested objects or couplers, after prefixed time-intervals by selecting individually the input channels using the “daisy-chain” technique. After acquisition, pulse-signals are first separated in classes according to their shape by means of the OPTICS clustering algorithm. Each class is successively organized in the so-called Phase Recorded PD (PRPD) patters and each sub-pattern is analyzed to distinguish noise (to be rejected) or PD. A fuzzy-logic inference engine is employed to identify the defect typology that support the discharge phenomenon. A short description of the integrated instrument is presented in this paper that include some analyzes acquisition and processing of PD occurring in a real MV cable. The integrated PD instrument has been designed to be utilized by a non-particularly skilled operator.

关键词： Partial discharges Statistical analysis Shape Instruments software algorithms Medium voltage Couplers software Monitoring Cables

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A Novel Approach to Depth Estimation and Disparity Map Generation in Stereoscopic Images Using Convolutional Neural Networks

A Novel Approach to Depth Estimation and Disparity Map Gener...

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Communication & Computing (WCONF), World Conference on

作者： Vipin Solanki Rahul Gupta Preeti Naval Department of Applied Science Sanskriti University Mathura Uttar Pradesh India Department of Management School of Mangement - PG JAIN (Deemed to be University) Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (数字)9798350395327

ISBN: (纸本)9798350395334

This paper provides a singular approach to depth estimation and disparity map technology in stereoscopic snap shots using convolutional neural networks (CNNs). Stereoscopic pictures are pairs brand new two or more photographs taken from barely extraordinary points in space., commonly utilized in 3-D film manufacturing. A good way to extract depth information from the 2 photographs., a stereo-disparity map can be generated by way of comparing the similarities among the two. The undertaking latest estimating the disparity map traditionally calls for tedious and computational heavy feature matching algorithms. This paper introduces a CNN-based disparity estimation technique that is both light-weight and quicker than traditional feature-matching algorithms. In particular., a completely-convolutional neural community (FCN) model is employed to regress the disparity map from an input stereoscopic photograph pair. To train this community., a large-scale artificial dataset is generated using simulation software program., presenting the essential ground fact. An extensive list state-of-the-art experiments and comparisons with approaches were conducted to evaluate its performance. Outcomes display that the proposed approach is capable of estimating displacement maps in stereo snap shots speedy and as it should be.

关键词： Navigation Stereo image processing software algorithms Estimation Optical imaging software Real-time systems Convolutional neural networks Optical films Tuning

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Development of a Vision-Based Search System for Unmanned Aerial Vehicles

Development of a Vision-Based Search System for Unmanned Aer...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Yongjie Zheng Guangyu Zhang Yuqing He Liying Yang Zhaoxiong Huang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

This paper presents the development of an autonomous unmanned aircraft system (UAS) that excelled in the Unmanned Platform Stereoscopic Cross-Domain Collaboration Challenge held in Yuxi, China, from August 1-15, 2022. The challenge was divided into four subtasks: (1)navigation and control, (2)recognition and localization, (3)online trajectory planning, and (4)task planning and scheduling, all of which were to be performed autonomously and safely by the robot. To meet these requirements, we designed and implemented a UAS with high autonomy and reliability, built on a hexacopter system, integrating sensors, an onboard computer, power batteries, and an electro-optical pod. We then developed the software algorithm and implemented the executable calculation code, integrated with the UAV hardware system. This paper outlines the main components and design process of the UAS and describes its application in a competition mission.

关键词： Trajectory planning Stereo image processing software algorithms Autonomous aerial vehicles Robot sensing systems software Sensor systems

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