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检索条件"主题词=Software algorithms"

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Computer-Simulated Performance Comparison of T-type and Π-type Network based Microwave Angular Displacement Sensors

Computer-Simulated Performance Comparison of T-type and Π-t...

引用

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

作者： Hongxu Zhu Zhongming Yang Computer Engineering Technical College (Artificial Intelligence College) Guangdong Polytechnic of Science and Technology Zhuhai China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

In this paper, the T-type and Π-type network based microwave angular displacement sensors are compared and analyzed. By incorporating neural networks, one can optimize the design parameters of microwave sensors, enhance the evaluation of critical sensor performance indicators, including frequency response, linearity, sensitivity, bandwidth, and stability.

关键词： Sensitivity Neural networks software algorithms Linearity Bandwidth Network security Microwave sensors Stability analysis Sensors software engineering

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An Automatic Intrinsic and Extrinsic Calibration Method for Multi-Camera Systems Without a Common Field of View Under Weak Observation Conditions Based on Total-Station-Assisted Point Localization

An Automatic Intrinsic and Extrinsic Calibration Method for ...

引用

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

作者： Wenfeng Bai Haitao Luo Xiankang Yu Mingjie Chen Wenjun Chen Yihe Yin Biao Hu Xiaolin Liu Guangzhou Metro Design&Research Institute Co. Ltd. Guangzhou China Institute of Intelligent Optical Measurement and Detection Shenzhen University Shenzhen China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

To address the calibration challenges of multi-camera measurement systems without a common field of view under weak observation conditions, this paper proposes an automatic intrinsic and extrinsic calibration method based on total-station-assisted point localization. First, illuminated marker points are deployed on-site, while cameras and a total station are set up in appropriate positions. The cameras capture images of the illuminated markers and quickly compute the spot center coordinates using the grayscale centroid method, while the total station acquires the 3D world coordinates of the markers. Finally, the intrinsic and extrinsic parameter matrices of the cameras is solved within the RANSAC algorithm framework, enabling automatic calibration of multi-camera systems without a common field of view. A field experiment was conducted in a subway tunnel under weak observation conditions. The average reprojection error of the calibrated camera parameters was 0.65 pixels. The experimental results demonstrate that the proposed total station and camera joint point localization-based calibration method achieves high-precision camera calibration and holds promising potential for engineering applications.

关键词： Location awareness Three-dimensional displays software algorithms Network security Gray-scale Cameras Calibration Public transportation software engineering

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Leveraging Fine-Tuned LightGBM for Advanced AI-Driven Android Malware Detection

Leveraging Fine-Tuned LightGBM for Advanced AI-Driven Androi...

引用

Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), International Conference on

作者： Rajasekar Kanniappan V. Jamuna Anna University Chennai Tamil Nadu India Department of Electrical and Electronics Engineering Jerusalem College of Engineering Chennai Tamil Nadu India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

Increasing instances of cyber threats, specifically malware, require faster creation of proper detection systems that utilize higher learning algorithms. This paper examines the effectiveness of an AI-malware detection technique whereby a LightGBM model finetuned on the CICAndMal2017 dataset is employed. As it will be shown, the CICAndMal2017 dataset is suitable to evaluate the proposed algorithms for detecting malware since this dataset offers sample of different types of malware and benign software. After carefully extracting the features, and selecting the best parameters that allow for the highest potential LightGBM achieved 97.56% accuracy. The results show that the model achieves low false positive rates while accurately identifying the presence or absence of malware in an application. This research helps to advance the cybersecurity field as a whole by presenting a fast, highly efficient, and accurate solution for real-time malware detection with the use of machine learning methods as a proof of concept for eradicating modern cyber threats.

关键词： Accuracy Machine learning algorithms Scalability software algorithms Machine learning Feature extraction Malware Real-time systems Telecommunication computing Computer security

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The Experience of Creating Information Measuring and Control Systems in Metallurgy

The Experience of Creating Information Measuring and Control...

引用

International Russian Smart Industry Conference (SmartIndustryCon)

作者： Dokov Dmitriy Novikov Anatoly Efimov Aleksey Coherent LLC Ryazan Russian Federation Department of Electronic Computing Machines Ryazan State Radio Engineering University named after V.F. Utkin Ryazan Russian Federation

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

The article discusses two tasks of information systems for monitoring the parameters of technological processes in metalworking creating. In the first task, the width and sickle shape of metal sheets are estimated based on information received from laser rangefinders. The task is solved automatically when the flow of metal sheets moves along the roller. The second task is to determine with high accuracy the coordinates of the edge edges of the bent metal sheet in the production of pipes of various diameters. Both tasks are solved automatically using laser rangefinders (profilometers) and original mathematical software. Solving these tasks allows automated quality control of rolled metal products performing and reducing the time spent on the final product. Using of laser profilometers as primary information sources makes it possible to ensure the accuracy required for technological processes. The design of the algorithms assumes low computational complexity, ensuring compliance with time constraints.

关键词： Industries Shape Welding Lasers software algorithms Metals software Metallurgy Monitoring Information systems

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Testing of Asymmetric Cryptographic Authentication Protocols for Vehicle Communication

Testing of Asymmetric Cryptographic Authentication Protocols...

引用

International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Alžbeta Kanáliková Emília Bubeníková Peter Peniak Department of Control and Information systems University of Zilina Zilina Slovakia

ISBN: (数字)9798350379365

ISBN: (纸本)9798350379372

Many vehicles move in automobile traffic, and their increase is higher than the necessary traffic on roads. For this reason, situations arise when these roads in cities, and towns, but also outside them, are often crowded, which results in collisions or traffic accidents. For this reason, it is also appropriate to implement mutual communication in vehicles through appropriately selected network protocols. At the same time, vehicle communication is also related to their mutual authentication, which can be implemented through cryptographic algorithms, or complex cryptographic protocols (based on multiple algorithms). In this article, we discuss methods of cryptographic vehicle authentication using digital signatures. The main goal is to test selected cryptographic protocols suitable for authentication and suitable software libraries. The testing was carried out on various devices. The result is their mutual comparison and evaluation.

关键词： software libraries software algorithms Urban areas Authentication Road safety Cryptography Automobiles Digital signatures Testing Cryptographic protocols

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Verification of the Denning-Sacco Protocol Based on APTC

Verification of the Denning-Sacco Protocol Based on APTC

引用

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

作者： Yuqi Liu Yong Wang School of Computer Science Beijing University of Technology Beijing China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

With the rapid development of information technology, network communication security has become one of the core issues in ensuring information security. As a typical representative in the field of key exchange, the security analysis and verification of the Denning - Sacco protocol have always been a hot topic in cryptography. The protocol was initially designed to address security issues in key exchange, but it has exposed some security vulnerabilities in practical applications, such as being susceptible to replay attacks and man - in - the - middle attacks. Therefore, in response to these known vulnerabilities, this study will conduct a detailed modeling and analysis of the protocol using true concurrent process algebra to verify its security and ensure that the protocol can resist various types of attacks.

关键词： Analytical models Protocols Algebra software algorithms Information security Resists Network security Solids Security Information technology

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Guiding Grokking: How Curriculum Learning Shapes Algorithmic Understanding in Neural Networks

Guiding Grokking: How Curriculum Learning Shapes Algorithmic...

引用

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

作者： Haotian Chen Zihao Wang College of Computer Science-College of Software Inner Mongolia University Hohhot China

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Understanding how neural networks suddenly achieve strong generalization after extended training (grokking) remains a fundamental challenge in deep learning. While this phenomenon has been observed in algorithmic tasks, the factors influencing its emergence remain poorly understood. We investigate whether curriculum learning—gradually increasing task complexity—can facilitate and accelerate grokking. Through systematic experiments on modular arithmetic tasks with varying prime moduli, we compare four curriculum strategies (linear, exponential, step-wise, and gradual progression) against a baseline. Our results reveal that only modular addition benefits significantly from curriculum learning, achieving 81.1% validation accuracy with gradual progression compared to 65.7% and 57.2% for linear and exponential curricula respectively. In contrast, operations like modular division and permutation show minimal improvement, with validation accuracies below 20% across all curricula. The gradual curriculum maintains smoother training loss transitions and higher training stability, particularly for addition, while step-wise progression shows the worst performance with validation accuracy drop- ping to 34.4% for addition. These findings suggest curriculum learning is most effective for operations with simpler underlying structures, while complex operations remain challenging regardless of curriculum design. This work provides practical insights into curriculum strategies for algorithmic learning tasks and highlights fundamental limitations of current approaches.

关键词： Training Deep learning Computer science Accuracy Systematics Shape software algorithms Neural networks Complexity theory software engineering

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Advanced Darknet Traffic Detection through Minority-Class Augmentation and Multi-Model Fusion

Advanced Darknet Traffic Detection through Minority-Class Au...

引用

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

作者： Zikang Liu School of Cyber Science and Technology Shandong University Qingdao China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

The Tor network is an anonymous communication technology that can protect user privacy and break through network censorship, but it can also be used by malicious actors and is a focus of network security research. Because its traffic is encrypted multiple times and is similar to ordinary traffic in some characteristics, traditional rule-based matching or anomaly detection methods are difficult to accurately distinguish, resulting in high false positive and false negative rates. To address this problem, this paper proposes an anonymous traffic detection method that combines data enhancement and ensemble learning. Logarithmic transformation, quantile truncation and normalization methods are used for data processing, and minority class samples are supplemented based on data enhancement strategies to alleviate the data imbalance problem, and its impact is evaluated through visualization. This paper constructs an ensemble learning framework based on LightGBM and RandomForest, and uses the Soft Voting strategy to fuse classifier prediction results, significantly improving detection accuracy and stability. Experiments on the CIC-Darknet2020 dataset show that the model can effectively improve the accuracy of anonymous traffic detection, has good stability, and plays a positive role in optimizing the performance of existing network traffic classification models.

关键词： Privacy Dark Web Accuracy Data enhancement software algorithms Telecommunication traffic Network security Stability analysis Ensemble learning software engineering

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A Novel Sky-Aware Dehazing Approach for Outdoor Autonomous Systems

A Novel Sky-Aware Dehazing Approach for Outdoor Autonomous S...

引用

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

作者： Xiaoyan Wu Dali Xu Fangfa Fu Bing Yang Hongyang Liu Kanglong Liu Xiyu Ding Chao Wu Na Niu School of Computer and Control Engineering Northeast Forestry University Harbin China School of Astronautics Harbin Institute of Technology Harbin China School of Computer Science Harbin University of Science and Technology Harbin China

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Clear outdoor images are essential for autonomous driving and accurate target detection, especially in haze. The majority of algorithms are unable to adequately address the issue of dehazing, resulting in a range of distortions, particularly in the sky area. This paper proposes an advanced dehazing algorithm for enhancing sky-area visuals (ESV). We segment the image into sky and non-sky areas, with atmospheric light levels being determined within the sky area. To enhance the recovery of the sky region, we suggest fine-tuning the sky's transmission to a predetermined constant value. Ultimately, the dehazed image is retrieved utilizing the atmospheric scattering model. Extensive experiments have shown that our proposed algorithm outperforms alternative methods, increasing PSNR by up to 1.3733%, 1.6360%, 2.4169%, 0.9512%, SSIM by up to 4.8995%, 0.6281%, 6.5335%, 8.7165%, enhancing the visuals of sky-area, compared to DCP, CAP, HC-CEP and AOD-Net.

关键词： Visualization Atmospheric modeling software algorithms Scattering Reinforcement learning Object detection Distortion Rendering (computer graphics) Robustness software engineering

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Vedic Mathematics Techniques - Real World Applications in Various Fields

Vedic Mathematics Techniques - Real World Applications in Va...

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Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), International Conference on

作者： Malini S Nivedha G Vijeta Iyer K. Meena Department of ECE Kumaraguru College of Technology Coimbatore India Department of Mathematics Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

Vedic mathematics is an ancient system of mathematical principles, rooted in Vedas which offers unique and efficient methods for solving complex problems. This paper aims to review and compare various research studies focusing on applications of Vedic mathematics techniques in contemporary fields. Through a detailed examination of literature, we explore its integration into education, computer science and various fields and how it improves computational speed and enhances mental calculation abilities. Moreover, in this paper we are going to investigate the importance of Vedic mathematics to optimize algorithm designs in software *** in modern-day problem-solving plays an vital role in reducing time factor. Ultimately, we discuss the broader implications of incorporating ancient mathematical methods into contemporary educational frameworks and technological innovations. The study delves into how Vedic techniques enhance computational efficiency, offering faster solutions to problems in arithmetic, algebra, and geometry. We explore the role of these methods in improving mental arithmetic skills, reducing time complexity in algorithmic problem-solving, and optimizing software development. The paper also discusses how Vedic Mathematics has found relevance in real-world applications, such as cryptography, signal processing, and machine learning, where speed and accuracy are paramount.

关键词： Technological innovation software algorithms Signal processing algorithms Machine learning Mathematics Hardware Problem-solving Cryptography Time complexity Arithmetic

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