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检索条件"主题词=software algorithms"

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Design of Visualization Simulation software for Collaborative Formation Control of Mobile Robot Cluster

Design of Visualization Simulation Software for Collaborativ...

引用

Artificial Intelligence, Robotics, and Communication (ICAIRC), IEEE International Conference on

作者： Haiming Liu Jiaxiang Luo Mei Zhang An Chen School of Automation Science and Engineering South China University of Technology Guangzhou China

ISBN: (数字)9798331531225

ISBN: (纸本)9798331531232

Simulation tools are important auxiliary tools for scientific research. Design method of a practical and convenient simulation software for visual simulation of collaborative formation control for mobile robot cluster was discussed in this paper. The simulation software was designed in two main parts: human-computer interaction and visualization display of algorithm simulation. The software was implemented based on Qt development platform and some key methods of design and implementation involved were detailed. The simulation results of this software under different formation control algorithms are shown to demonstrate its practicality and flexibility in applications.

关键词： Human computer interaction Visualization Design methodology software algorithms Clustering algorithms Collaboration software Formation control Hardware Mobile robots

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Improving Fairness in Machine Learning software via Counterfactual Fairness Thinking

Improving Fairness in Machine Learning Software via Counterf...

引用

International Conference on software Engineering - Companion, ICSE, Companion

作者： Zhipeng Yin Zichong Wang Wenbin Zhang Florida International University Miami Florida USA

ISBN: (数字)9798400705021

ISBN: (纸本)9798350351781

Machine Learning (ML) software is increasingly influencing decisions that impact individuals' lives. However, some of these decisions show discrimination and thus introduce algorithmic biases against certain social subgroups defined by sensitive attributes (e.g., gender or race). This has elevated software fairness bugs to an increasingly significant concern for software engineering (SE). However, most existing bias mitigation works enhance software fairness, a non-functional software property, at the cost of software performance. To this end, we proposed a novel framework, namely Group Equality Counterfactual Fairness (GECF), which aims to miti-gate sensitive attribute bias and labeling bias using counterfactual fairness while reducing the resulting performance loss based on ensemble learning. Experimental results on 6 real-world datasets show the superiority of our proposed framework from different aspects.

关键词： Machine learning algorithms Costs software algorithms Computer bugs software performance Labeling Ensemble learning

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Security Vulnerability Detection Method of Open-source software Based on Graph Attention Network

Security Vulnerability Detection Method of Open-source Softw...

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Artificial Intelligence, Computer Technology and Control Engineering (ACTCE), International Seminar on

作者： Qinghao Li Zhida Guo Deru Guo Ran Hu Hanlin Du Mingqian Xiao Huizhou Power Supply Corporation of Guangdong Power Grid Co Ltd. China Huizhou China

ISBN: (数字)9798331521714

ISBN: (纸本)9798331521721

With the popularity of open source software, software security problems have become increasingly prominent. Traditional vulnerability detection methods are no longer able to cope with today’s complex virus vulnerabilities, and the detection results often have certain limitations. Therefore, an open source software security vulnerability detection method based on graph attention network is proposed. Firstly, the graph attention network model is constructed, and the source code detection is used to identify and detect the graph attention vulnerability. In order to verify the performance of the graph attention network model in the proposed method, the paper compares the proposed model with Drebin algorithm. The results show that the graph attention network model can effectively detect the number of security vulnerabilities in open source software, and its maximum error value is 4. Compared with Drebin algorithm, the security vulnerability detection method has higher accuracy and efficiency.

关键词： Seminars Accuracy Control engineering Source coding software algorithms Neural networks Security Data mining Open source software Viruses (medical)

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Characterizing software Architectural Metrics for Continuous Compliance in the Automotive Domain

Characterizing Software Architectural Metrics for Continuous...

引用

Working IEEE/IFIP Conference on software Architecture

作者： Domenico Amalfitano Marco De Luca Anna Rita Fasolino Patrizio Pelliccione Tiziano Santilli DIETI University of Naples Federico II Naples Italy Gran Sasso Science Institute (GSSI) L'Aquila Italy

ISBN: (数字)9798350359169

ISBN: (纸本)9798350359176

The software of critical systems, such as automotive, is increasingly required to change and evolve after production. In the automotive domain, this is a consequence of self-driving and connected cars, which continuously collect data from the field that is then exploited to produce safer and more advanced and reliable versions of the used algorithms or AI modules. Consequently, there exists a need for techniques and tools to facilitate incremental and Continuous Compliance with safety and security standards. This paper focuses on software architectural metrics that can be used for Continuous Compliance in the automotive domain. Our initial stride involved a literature review to find metrics capable of assessing software architectures. Subsequently, in collaboration with architecture, safety, and security experts in the automotive domain, we proposed a framework defining the characteristics these metrics must possess for continuous evaluation of software architectural compliance. The framework was used to characterize 48 metrics gathered from the literature review and to associate them with a score expressing their suitability to be used in software architecture Continuous Compliance processes.

关键词： Measurement software architecture Bibliographies software algorithms Production software Safety

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Optimizing Judicial Efficiency- A software Solution for Case Listing with Customized Case Flow Management

Optimizing Judicial Efficiency- A Software Solution for Case...

引用

International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Sangeetha V Ishwariya Pani Jay Jariwala Anirudha Dargar Rishu H Rai Srestha Agarwala Department of CSE Ramaiah Institute of Technology Bangalore India

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505479

The most significant disadvantage of the administration of justice in India today is delay. The Indian judiciary has always struggled with delays and pending cases. Over the past five decades, India's judiciary proposed several solutions to address delays and pending cases. In the legal domain, a dynamic balance between automation and people is required. And also due to the increased complexity and volume of legal cases, there is a critical demand for improving efficiency, accuracy, and responsiveness in the judicial process. Artificial Intelligent(AI) is used to automate the process in the legal environment to make system operations more agile. The proposed framework will optimize the case organization and prioritize the development of user-friendly software integrated with Natural Language Processing(NLP) algorithms. The main objective is to develop a web application with differentiated case flow management. Implement AI algorithms for precise case categorization, fostering a seamless user experience, and ensuring adaptability across diverse legal environments. The result of the proposed system improves case management processes with enhanced user experience, and more effective decision-making through prioritized case listings. Also support a transparent judicial system, ultimately supporting societal well-being by fostering a more responsive legal environment.

关键词： Accuracy Law Systems operation software algorithms Transforms software User experience Delays Reliability Predictive analytics

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Design and Implementation of French Teaching Assistant software Based on Machine Translation Algorithm

Design and Implementation of French Teaching Assistant Softw...

引用

Telecommunications and Power Electronics (TELEPE), International Conference on

作者： Yuzi Cui Xi'an Fanyi University Xi'an Shaanxi China

ISBN: (数字)9798350369212

ISBN: (纸本)9798350380002

This article aims to design and implement a French teaching assistant software based on machine translation (MT) algorithm, so as to improve the learning efficiency and learning experience of French learners. In order to achieve this goal, this article deeply studies the theoretical basis of MT technology, and analyzes the functional requirements, performance requirements, user interface and interaction design of the software in detail. In the process of software design, hierarchical architecture and modular design are adopted to ensure the stability and expansibility of the software. The implementation of MT module is based on the deep learning framework, and it is trained through a large number of bilingual corpora to improve the accuracy and fluency of translation. The experimental results show that the proposed model achieves a high BLEU score of 0.95 on the test set, which shows that its translation output is close to that of human translation. Furthermore, the algorithm has a fast response speed and remains stable even when concurrent requests increase; Moreover, there is no obvious performance degradation when the software is used concurrently by multiple users. This study not only provides an efficient learning tool for French learners, but also provides a new idea for the application of MT technology in the teaching field.

关键词： Degradation Accuracy Education software algorithms User interfaces software Stability analysis Real-time systems Machine translation Thermal stability

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Security in IoT Networks. Simulation, capture, and traffic analysis using Contiki Cooja software and RPL protocols for anomaly detection

Security in IoT Networks. Simulation, capture, and traffic a...

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Inteligencia Ambiental, Ingeniería de software y Salud Electrónica y Móvil (AmITIC), V Congreso Internacional en

作者： Parra Calderón Sergio Samuel Gutiérrez Portela Fernando Diaz Triana Oscar Augusto Semillero de investigación INNOVASIC Universidad Cooperativa de Colombia Grupo de Investigación AQUA Universidad Cooperativa de Colombia

ISBN: (数字)9798350364538

ISBN: (纸本)9798350364545

The study addresses the challenge of securing Internet of Things (IoT) networks by integrating simulation, capture, and analysis of network traffic. Currently, the security of these networks is compromised due to the lack of robust protocols and rigorous standards. The project utilizes Contiki Cooja and the RPL protocol, known for its security limitations, along with machine learning models for anomaly detection. A development framework is proposed that includes simulation scenarios with benign and malicious traffic, involving fifteen normal nodes and one vulnerable node. Attack modules such as Hello Flood, Rank Decrease, and Version Number Modification are implemented to recreate threat scenarios. Simulated traffic undergoes preprocessing to facilitate analysis and is evaluated using machine learning algorithms such as KNN, Random Forest, and Artificial Neural Networks to measure their effectiveness and performance in anomaly detection. The use of Cooja allows efficient simulation of complex network systems without requiring excessive computational resources, enabling the development of experiments in controlled and repeatable environments, thus significantly reducing costs associated with physical network deployment tests. Based on the results obtained, it was demonstrated that the algorithm with the highest accuracy in detecting attacks is Random Forest, achieving 97% detection for Hello Flood attack, 78% for Rank Decrease, and 95% for Version Number Modification. The attack with the lowest detection probability is Rank Decrease due to its behavior in the IoT network. It is important to conduct further simulations with a variety of attacks and IoT network protocols to optimally train the algorithms.

关键词： Protocols software algorithms Telecommunication traffic software Security Internet of Things Floods Anomaly detection Random forests Standards

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Systematic Literature Review of software Estimation in Global software Development

Systematic Literature Review of Software Estimation in Globa...

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Information Technology and Computing (ICITCOM), International Conference on

作者： Arifia Kasastra Ridi Ferdiana Syukron Abu Ishaq Alfarozi Department of Electrical and Information Engineering Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798350379839

ISBN: (纸本)9798350379846

software development is always characterized by certain parameters. In the context of Global software Development (GSD), one of the key challenges for software developers is predicting the development effort of a software system based on developer details, size, complexity, and other measures. When development teams are spread apart, it presents a number of challenges. Communication and coordination become more complex, leading to hidden costs associated with managing software development across different locations. Hence, the software estimation models used for co-located software development are not suitable for estimation in GSD. software estimation in GSD has become a crucial area of research. This paper presents the findings of a systematic literature review on software estimation in the context of GSD, with the aim of providing researchers and practitioners with a comprehensive understanding of the current state of the art in this area. Over the last decade, only a handful of researchers have devoted their attention to estimating efforts in GSD. The results show that estimation methods in GSD have not been widely explored. The COCOMO-II method is the most widely adapted method for GSD, and Time Zone is the most agreed Cost Driver for GSD.

关键词： Costs Accuracy Computational modeling software algorithms Estimation software systems software software measurement Standards software development management

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Runtime Embedded software Malfunction Detection Based on Profile Generation of Current-Level Pattern Matcher

Runtime Embedded Software Malfunction Detection Based on Pro...

引用

International Conference on Electronics, Information and Communications (ICEIC)

作者： Sanghoon Lee Daejin Park Software Disaster Research Center Kyungpook National University Daegu Korea School of Electronics Engineering Kyungpook National University Daegu Korea

ISBN: (数字)9798331510756

ISBN: (纸本)9798331510763

As the demand for high-performance embedded systems grows, the complexity of embedded software increases, potentially leading to software errors and system malfunctions. In this paper, we propose a system to monitor malfunctions caused by software errors by extracting the normal operating current patterns of a target embedded system (TES) in actual operation and comparing them with the real time current TES data. By using a monitoring embedded system (MES), the normal operating current patterns can be automatically generated, making it easy to promptly detect malfunctions in the exposed TES. When the MES detects a malfunction, it applies algorithms to efficiently recover the malfunctioning TES. The proposed system employs two algorithms when a malfunction in the TES is detected. First, upon detecting a malfunction, the MES resets TES to restore it to normal operation. If the malfunction persists after the reset, the MES controls the TES to completely halt operation. Second, if a malfunction is detected, it stabilizes the abnormal current state to the normal current state through a proportional integral derivation (PID) control. The TES typically consumes about 75 to 95 mA of current during normal operation. The MES applies a specific error detection rate of 20 %, considering any consumption above 114 mA a malfunction and using the algorithms to control it. The system has been verified to reset TES upon detecting a malfunction and to stabilize the operational current through PID control during abnormal current states.

关键词： Embedded systems PI control Runtime software algorithms Real-time systems PD control Protection Monitoring Pattern matching Embedded software

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Development and Application of an Intelligent Clash Check and Handling System Based on PDMS Plant Design software

Development and Application of an Intelligent Clash Check an...

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Artificial Intelligence and Digital Technology (ICAIDT), International Conference on

作者： Qian Hao Shaoyi Dong Shandong Electric Power Engineering Consulting Institute Corp. LTD Jinan China

ISBN: (数字)9798350386905

ISBN: (纸本)9798350386912

This paper proposes an intelligent clash check and handling system tailored for the 3D design software PDMS in the power industry, aiming to enhance its clash check capabilities. The system comprises multiple modules, including clash check configuration, scheduled and real-time clash checks, data storage, data retrieval, and processing modules. It allows users to set clash check times and objects based on design progress, perform clash checks automatically or manually, and store the results. Additionally, it utilizes algorithms to avoid redundant processing of clash data. Designers can retrieve and view clash data, formulate handling plans, and input the results, providing support for data traceability and design review. The application of this system will improve the functional integrity of the PDMS software in terms of clash check, providing an efficient tool for digital design in the power industry.

关键词： Three-dimensional displays Reviews software algorithms Memory software Power industry Real-time systems

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