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检索条件"主题词=software algorithms"

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COmmitSHield: Tracking Vulnerability Introduction and Fix in Version Control Systems

COmmitSHield: Tracking Vulnerability Introduction and Fix in...

引用

International Conference on software Engineering - Companion, ICSE, Companion

作者： Zhaonan Wu Yanjie Zhao Chen Wei Zirui Wan Yue Liu Haoyu Wang Huazhong University of Science and Technology Wuhan China MYbank Ant Group Hangzhou China Monash University Melbourne Australia

ISBN: (数字)9798331536831

ISBN: (纸本)9798331536848

Version control systems are commonly used to manage open-source software, in which each commit may introduce new vulnerabilities or fix existing ones. Researchers have developed various tools for detecting vulnerabilities in code commits, but their performance is limited by factors such as neglecting descriptive data and challenges in accurately identifying vulnerability introductions. To overcome these limitations, we propose CommitShield, which combines the code analysis capabilities of static analysis tools with the natural language and code understanding capabilities of large language models (LLMs) to enhance the accuracy of vulnerability introduction and fix detection by generating precise descriptions and obtaining rich patch contexts. We evaluate CommitShield using the newly constructed vulnerability fix dataset, CommitVulFix, and a cleaned vulnerability introduction dataset. Experimental results indicate that CommitShield improves recall by 74%-77% over state-of-the-art methods in the vulnerability fix detection task, and its F1-score improves by 15%-27% in the vulnerability introduction detection task.

关键词： Codes Accuracy Large language models software algorithms Natural languages Static analysis Control systems History Open source software software engineering

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Multi-Scale Spatial and Channel Context Boosting Networks for Portrait Segmentation

Multi-Scale Spatial and Channel Context Boosting Networks fo...

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

作者： Yingyue Xu Zhanjiang Yuan Guangdong Polytechnic of Science and Technology Zhuhai China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

Portrait segmentation is a highly pervasive but challenging task. Existing portrait segmentation models usually deploy auxiliary knowledge for high precision, e.g., face, pose, boundary, etc. However, it requires additional inputs or extra annotations. This paper proposes a solid context boosting model, namely CSSNet, that makes the most of contexts from convolutional neural networks (CNNs) to achieve state-of-the-art performance without the supervision of auxiliary knowledge. Firstly, the CSSNet yields a top-down pathway formed by the global prior and a succession of scale-specific fusing blocks. The global prior from pyramid pooling guides the general localization of portraits on top of the CNN backbone, while the fusing blocks progressively boost and incorporate CNN contexts from coarse to fine scales for fine-grained details. Secondly, the scale-specific fusing blocks thoroughly boost contexts with three modules, including the channel boosting module to enrich feature representations by simple linear operations, the spatial boosting module to enhance feature quality with various spatial statistics via spatial pyramid pooling, and the scale boosting module to integrate multi-scale CNN contexts. The CSSNet facilitates end-to-end segmentation and executes at 57.21 FPS on 300×400 images. Moreover, we summarize existing portrait segmentation datasets and propose to deploy two evaluation metrics for experimental analysis. Evaluation over four public datasets shows that the CSSNet achieves state-of-the-art performance without auxiliary supervision in model training.

关键词： Training Measurement Image segmentation Solid modeling software algorithms Network security Boosting Solids Convolutional neural networks software engineering

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A Novel Transmission System Fault Identification Method Based on K-Nearest Neighbour Algorithm

A Novel Transmission System Fault Identification Method Base...

引用

IEEE Asia Power and Energy Engineering Conference (APEEC)

作者： Cheng Li Qiangren Zheng Muchen Liu State Grid Yanbian Power Supply Company Yanbian China Northeast Electric Power University Jilin China

ISBN: (数字)9798331517540

ISBN: (纸本)9798331517557

With the large-scale grid integration of wind turbines, the “double high” characteristics of the system emerge, and the existing power system fault identification methods are difficult to meet the needs of safe and stable operation of modern power grids. A power system fault identification method based on K-nearest neighbour (KNN) algorithm and stand-alone energy function is proposed to address this problem. Firstly, the stand-alone energy function based on short-circuit current is derived and its feasibility as a criterion for fault type identification is analysed. Secondly, considering the variation characteristics of wind turbine output energy, the partition boundary voltage values are used to initially screen the fault areas, and then a fault identification strategy for power systems containing new energy units is proposed by combining the KNN algorithm. Finally, experimental validation is carried out on a ten-unit system containing wind farms using Power System Analysis software Package(PSASP) software. The simulation results show that the method proposed in this paper has strong applicability and stability, and can maintain high fault type identification accuracy under different working conditions.

关键词： Fault diagnosis Power transmission lines Simulation Short-circuit currents software algorithms Power system stability Nearest neighbor methods software Wind turbines Thermal stability

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Underwater AUV Path Planning Algorithm Based on GWHASSA

Underwater AUV Path Planning Algorithm Based on GWHASSA

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Computers, Information Processing and Advanced Education (CIPAE), 2020 International Conference on

作者： Zhaoyang Wen Changsong Yao Jiajun Song National University of Defense Technology Changsha China

ISBN: (数字)9798331527662

ISBN: (纸本)9798331527679

In this paper, we introduce the application of an Adaptive Sparrow Search Algorithm Based on Mixed Gray Wolf Hierarchy (GWHASSA) in underwater AUV path planning. Given the complex marine environment, this paper lists some problems of traditional path planning methods, then, the sparrow search algorithm as a new intelligent optimization technology is introduced. It has the advantages of simple parameters and fast search speed. Path planning problem for solving underwater robots, the article proposes an underwater AUV path planning method based on a hybrid grey wolf hierarchical structure adaptive sparrow search algorithm (GWHASSA). This method takes into account complex marine environments and influencing factors such as ocean currents, and the velocity synthesis method and the fitness function of integrating ocean currents were introduced to evaluate the state of particles and perform path planning. At the same time, strategies such as dynamic inertia weights and adaptive proportional changes were introduced to improve global search capability and optimize position updates. The article used simulation software for a computer simulation environment, and performance tests were conducted on different testing functions. The results indicate that this method has a shorter path length compared to other classical and heuristic algorithms.

关键词： Heuristic algorithms Oceans software algorithms Education Information processing Search problems Path planning software Optimization Testing

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An Automatic Ship Cabin Filling Algorithm Applied in Loading Instruments

An Automatic Ship Cabin Filling Algorithm Applied in Loading...

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

作者： Zhongzheng Sun Qiang Sun School of Electronic Information Shanghai dianji university shanghai china

ISBN: (数字)9798331506582

ISBN: (纸本)9798331506599

To address the shortcomings of marine loading instruments in cargo loading visualization, particularly the issues of distortion and low efficiency caused by traditional filling algorithms when handling complex nested ship cabin graphics, this paper proposes an automatic ship cabin filling algorithm for use in loading instruments. The algorithm is based on vector principles and the minimum bounding rectangle (MBR) positioning method. It first identifies and stores the contour data of the target cabin area. Next, it locates and detects the cabin contour using the MBR of the ship cabin. Then, the algorithm determines the line direction based on the filling rules and calculates the number of lines needed for filling. Finally, an optimized Bresenham algorithm is employed to achieve high-precision line filling, which improves the accuracy and efficiency of the graphical display. The implementation results show that the proposed algorithm can effectively detect cabin contour information within ship cabin graphics and fill the cabin space according to the specified direction and percentage. It also enables real-time image filling and display within the loading instrument.

关键词： Graphics Instruments Loading software algorithms Data visualization Aerospace electronics Filling Real-time systems Vectors Marine vehicles

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Correctness of Flow Migration for Service Function Chains

Correctness of Flow Migration for Service Function Chains

引用

IEEE Symposium on Network Operations and Management

作者： Ranjan Patowary Gautam Barua Radhika Sukapuram Central Institute of Technology Kokrajhar India Indian Institute of Information Technology Guwahati India

ISBN: (数字)9798350327939

ISBN: (纸本)9798350327946

Network Functions (NFs) are responsible for ensuring security in the network, optimizing data traffic and balancing network load. NFs are chained to form Service Function Chains (SFCs). Flows may need to be migrated from a subset of NF instances (belonging to an SFC instance) to another for scaling out, scaling in, load balancing or software upgrades. When flows are migrated from an NF instance to another, states need to be migrated for the destination NF to function correctly. For the first time, we propose the correctness criteria for migration of a flow from an SFC instance to another. Existing algorithms for flow migration across NF instances require buffering packets. The amount of buffering required is not easily predictable, buffering is vulnerable to overflow attacks and do not tolerate packet bursts well. We propose an algorithm that does not require buffering or loss of packets, but causes reordering, for flow migration across SFC instances. The reordering that it causes is well managed by recent implementations of TCP, as is borne out by our experiments. Our simulations demonstrate that when a flow is migrated from an SFC instance with 2, 4, 6 and 8 NFs, the worst difference in the mean goodputs of cases with and without flow migration is only 3.6% and the best difference is 0.1%. Moreover, the implementations of NFs that are resistant to packet reordering strengthen our case.

关键词： Resistance Service function chaining software algorithms Prediction algorithms Load management software Noise measurement

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Fault Diagnosis of Integrated Core Processor in Avionics System Based on CNN-Transformer

Fault Diagnosis of Integrated Core Processor in Avionics Sys...

引用

Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), International Conference on

作者： Xinbo Zhao Lu Jiao Avionics department Chengdu Aircraft Design and Research Institute Chengdu China

ISBN: (数字)9798331529192

ISBN: (纸本)9798331529208

The structure and function of Integrated Core Processor (ICP) of the avionics system are relatively complex, while traditional fault diagnosis methods perform low accuracy and low efficiency. To address these issues, this paper proposes an enhanced CNN-Transformer algorithm for fault diagnosis of the integrated core processor. Initially, CNN model is employed to extract spatial features, reduce computational complexity, and preserve essential data. Subsequently, Transformer model utilizes self-attention calculations to capture relationships and characteristics within the input sequence. Finally, a fully connected neural network is applied to classify the faults. The method was validated using multiple datasets recorded by the Fiber Channel bus, achieving a diagnostic accuracy of 96.88%, outperforming other comparative approaches.

关键词： Fault diagnosis Accuracy Machine learning algorithms software algorithms Optical fiber networks Aerospace electronics Feature extraction Transformers Data models Classification algorithms

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Improving Location Estimates of Distribution Faults With Imperfect Grid Edge Measurements

Improving Location Estimates of Distribution Faults With Imp...

引用

IEEE PES Transmission and Distribution Conference and Exposition

作者： Hamed Valizadeh Haghi Kyle Chang Michael Balestrieri John Battenschlag Data Science Operations SCE Irvine USA Grid Technology Innovation SCE Westminster USA

ISBN: (数字)9798350316377

ISBN: (纸本)9798350316384

This paper proposes a hybrid algorithm to improve location estimates of momentary and incipient faults in distribution operations. The proposed scheme is implemented and tested as a software program using actual field data collected at distribution substations and grid edge. The estimation is achieved by modeling the relationship graph between fault recorder waveforms at the substation and smart meter voltage exceptions that captures the spatial and temporal dependency. A windowed transformation of the waveforms is utilized to mine the temporal dependency for the location estimation and anomaly scoring. The performance of the proposed method is demonstrated on the failure of an underground residential distribution switch to a 50 kVA transformer. In the pilot testing, the estimated fault area of the affected structures proved to be 100% accurate whenever the spatiotemporal alignment was successful.

关键词： Substations software algorithms Estimation Switches Fault location Transformers Smart meters

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Development of Microcontroller-Based BLDC Motor Speed Controller for EV

Development of Microcontroller-Based BLDC Motor Speed Contro...

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Communication & Computing (WCONF), World Conference on

作者： Anup Kshirsagar Aabid C Mulla Sachin G Argade Akshata Band Ashutosh More H.S. Anantwar Dept. of Electrical Engg JSPM's Rajarshi Shahu College of Engg Pune India Dept. of Electrical Engg JSPM's Rajarshi Shahu College of Engineering Tathawade Pune Maharashtra India

ISBN: (数字)9798350395327

ISBN: (纸本)9798350395334

The Arduino UNO-based BLDC motor controller project demonstrates the successful integration of hardware and software components to achieve efficient motor control for electric vehicles. The project utilizes the Arduino UNO microcontroller and Hall effect sensors for feedback, enabling precise commutation and smooth motor operation. Through meticulous circuit design and programming, the controller effectively regulates the speed and direction of the BLDC motor. The inclusion of a potentiometer for real-time speed adjustment enhances user control. It is built to design and implement a Brushless DC (BLDC) motor controller using a microcontroller, to achieve precise speed control, efficient operation, and reliable performance in various applications such as electric vehicles, robotics, and industrial automation. Future work involves optimizing the code, exploring regenerative braking features, and adapting the controller for broader electric vehicle platforms. The project sets a foundation for further refining and expanding electric vehicle technology. Overall this study provides a comprehensive investigation into the design, implementation, and performance evaluation of a microcontroller-based Brushless DC (BLDC) motor controller. It highlights the significance of closed-loop control systems in enhancing motor efficiency and responsiveness, offering practical solutions for industries requiring advanced motor control capabilities.

关键词： Performance evaluation Motor drives Microcontrollers Heuristic algorithms Velocity control software algorithms Motors Electric vehicles software Sensors

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Tacit Knowledge-Based Expert Model for Decision Support in Injection Mould Design

Tacit Knowledge-Based Expert Model for Decision Support in I...

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International Conference on Information Technology Research (ICITR)

作者： K.H.J. Mangala R.K.P.S. Ranaweera H.K.G. Punchihewa Dept. of Mechanical Engineering University of Moratuwa Moratuwa Sri Lanka

ISBN: (数字)9798331511425

ISBN: (纸本)9798331511432

Injection moulding is the most popular technique used by Sri Lankan small and medium-scale enterprises for producing plastic parts in large quantities. Once a strong industry that catered to over 50% of local demand for dies and moulds are now barely meeting one-tenth of the demand due to import competition. Moreover, the local industry lacks access to state-of-the-art design tools owing to funding limitations and mainly relies on experience of long-standing mould design experts. The brain drain following country's economic downturn has now severely affected growth or even existence of this important industry. In this context, the paper introduces a unique strategy to digitally transform the tacit knowledge of mould design experts, and thereby establish a data-driven decision-making process for mould design. In order to manage both explicit and tacit knowledge in injection mould design, a framework was developed, and corresponding databases were established. The proposed expert model uses a predefined case bank and a case-based filtering algorithm to identify matching data sets for a given new design from explicit and tacit databases. Suitability of parameters of the new design is determined using a decision-making algorithm, where higher weightage is assigned to tacit knowledge-based on data availability. The expert model was validated using a case study, and results of the expert model were found to be significantly agreeable to the output of industry-standard mould design software. The findings indicate potential of the proposed tacit knowledge-based expert model to positively impact mould industry affected by low resources and help reach Industry 4.0.

关键词： Industries Databases Knowledge based systems Decision making software algorithms Transforms Data models Personnel software tools Standards

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