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检索条件"主题词=software algorithms"

共 12410 条记录，以下是221-230 订阅

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Continuous Evaluation: Using CI Techniques for Experimentation at Scale

Continuous Evaluation: Using CI Techniques for Experimentati...

引用

IEEE International Conference on software Testing Verification and Validation Workshop, ICSTW

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Many-Objective Neuroevolution for Testing Games

Many-Objective Neuroevolution for Testing Games

引用

International Conference on software Testing, Verification, and Validation, ICST

作者： Patric Feldmeier Katrin Schmelz Gordon Fraser University of Passau Germany

ISBN: (数字)9798331508142

ISBN: (纸本)9798331508159

Games are designed to challenge human players, but this also makes it challenging to generate software tests for computer games automatically. Neural networks have therefore been proposed to serve as dynamic test cases trained to reach statements in the underlying code, similar to how static test cases consisting of event sequences would do in traditional software. The Neatest approach combines search-based software testing principles with neuroevolution to generate such dynamic test cases. However, it may take long or even be impossible to evolve a network that can cover individual program statements, and since Neatest is a single-objective algorithm, it will have to be sequentially invoked for a potentially large number of coverage goals. In this paper, we therefore propose to treat the neuroevolution of dynamic test cases as a many-objective search problem. By targeting all coverage goals at the same time, easy goals are covered quickly, and the search can focus on more challenging ones. We extend the state-of-the-art many-objective test generation algorithms MIO and MOSA as well as the state-of-the-art many-objective neuroevolution algorithm NEWS/D to generate dynamic test cases. Experiments on 20 Scratch games show that targeting several objectives simultaneously increases Neatest's average branch coverage from 75.88% to 81.33% while reducing the search time by 93.28%.

关键词： software testing Costs Heuristic algorithms software algorithms Neural networks Games Search problems Generators software Test pattern generators

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Taming Uncertainty in Critical Scenario Generation for Testing Automated Driving Systems

Taming Uncertainty in Critical Scenario Generation for Testi...

引用

International Conference on software Testing, Verification, and Validation, ICST

作者： Selma Grosse Adam Molin Dejan Ničković Alessio Gambi Cristinel Mateis DENSO AUTOMOTIVE Deutschland GmbH Germany AIT Austrian Institute of Technology GmbH Austria

ISBN: (数字)9798331508142

ISBN: (纸本)9798331508159

Scenario-based testing in simulation has become a cornerstone of industrial practice for systematically assessing autonomous driving systems across diverse and relevant situations. Generating critical scenarios is central to this methodology, yet it remains challenging due to the inherent uncertainties resulting from scenario parameterization. While parameterization is essential for modeling unpredictable factors, like weather, an excess of parameters hampers testing effectiveness. To address these challenges, this paper introduces a methodology that guides testers in selecting scenario parameters and managing the associated uncertainties. Our approach integrates specification-driven and optimization-based test generation with sensitivity analysis, enabling testers to assess the impact of scenario parameters on scenario criticality. We implemented our approach using well-established industry technologies and evaluated it in a highway case study on three reference search-based scenario generation methods with varying degrees of exploitativeness. Results from our evaluation suggest that reducing the parameter-induced uncertainty can improve the ability of some testing methods to identify critical scenarios while maintaining the diversity of input parameter values.

关键词： Road transportation Measurement software testing Uncertainty Sensitivity analysis software algorithms Test pattern generators Scenario generation Autonomous vehicles Testing

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Non-Unit Protection Scheme Assessment of Stand-Alone PV Generating System

Non-Unit Protection Scheme Assessment of Stand-Alone PV Gene...

引用

Sustainable Energy Technologies and Computational Intelligence (SETCOM), International Conference on

作者： Saswat Mishra Gyan Ranjan Biswal Papia Ray VSSUT Burla Odisha India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

Due to recent energy policies and increased rate of global warming, to curtail the impact of greenhouse gas emissions, a source like solar plays an important role in power generation but it is affected by irradiance, temperature (which changes due to changing atmospheric conditions) and load. As PV array has a unique point depending on both temperature and irradiation, where the generation of power, is maximum, an optimum algorithm is necessary to implement. To get optimal power under all possible conditions, the maximum power point (MPP) must be accurately tracked. In this proposed work, the performance of Perturb & Observe (P&O) algorithm is analyzed. Depending on local geographical location, the simulation parameters of proposed model are taken. Here, different types of protection schemes incorporated with relay system are provided in the power system network. The primary aim of these schemes is to detect faults in the network and to isolate the faulted part from the remaining healthy system. The protective relays continuously monitor the power system and operate when any quantities deviate from their normal levels. In this work, the impedance type relay is considered for the test model for detection of faults and the protection of the system. The results of proposed system are analyzed and verified using MATLAB/Simulink software. It is found that the proposed scheme works effectively under all adverse situations like fault, irradiance etc.

关键词： Temperature sensors Radiation effects Temperature dependence software algorithms Protective relaying Mathematical models Impedance Power system protection Power generation Photovoltaic systems Converters Climate change

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Development and Design of Online Management Platform for Talent Cultivation Based on Artificial Intelligence

Development and Design of Online Management Platform for Tal...

引用

Digital Analysis and Processing, Intelligent Computation (DAPIC), International Conference on

作者： Chao Jiang Mao Li Chengdu Aircraft Industrial (Group) Coporation Ltd. Chengdu Sichuan China

ISBN: (数字)9798331536169

ISBN: (纸本)9798331536176

With the development of information technology, especially the rapid progress of artificial intelligence (AI) technology, the traditional education model is facing a transformation. This paper analyzes the challenges of the current education model, and combines the latest progress of AI technology to build a comprehensive platform that integrates the functions of course management, learning progress tracking, intelligent recommendation and data analysis. The platform adopts micro-service architecture to improve the maintainability, expansibility and deployment flexibility of the system. The functional modules include user management, course management, learning management, intelligent recommendation and data analysis, aiming at deeply analyzing students' behaviors through AI algorithm, providing teaching feedback for teachers and personalized learning suggestions for students, thus improving teaching and learning effects. In terms of key technologies and algorithms, the platform integrates natural language processing (NLP), machine learning, deep learning and knowledge mapping to improve the level of intelligence. Algorithm selection includes collaborative filtering algorithm for personalized recommendation, K-means clustering algorithm for learning behavior analysis, and decision tree algorithm for teaching effect evaluation. The development environment involves highperformance hardware and software configuration, including cloud server, Linux system, Python language, database technology, etc., as well as version control and deployment using tools such as Git and Docker. In the testing and debugging stage, the stability, performance and security of the platform are ensured through unit testing, integration testing, performance testing, user acceptance testing and security testing. The research in this paper provides an efficient and intelligent online management platform for the education field to meet the challenge of educational modernization.

关键词： Machine learning algorithms Data analysis Education software algorithms Clustering algorithms Learning (artificial intelligence) Natural language processing Stability analysis Security Testing

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Uncovering the Challenges: A Study of Corner Cases in Bug-Inducing Commits

Uncovering the Challenges: A Study of Corner Cases in Bug-In...

引用

IEEE International Conference on software Analysis, Evolution and Reengineering (SANER)

作者： Atakan Şerifoğlu Eray Tüzün Computer Science Bilkent University Ankara Turkey

ISBN: (数字)9798331535100

ISBN: (纸本)9798331535117

In software development, accurately identifying bug-inducing commits (BICs) is crucial for maintaining code integrity and ensuring the reliability of software systems. The complexities involved in pinpointing the exact commits responsible for bugs necessitate a thorough investigation of the underlying issues and limitations of existing tools and algorithms. This study investigates and identifies corner cases in BIC identification, clarifying definitions and examining issues with existing algorithms and tools. By analyzing these cases, we aim to reveal challenges faced by current methods and propose insights for future improvements. We evaluated the SZZ algorithm and two large language models, GPT-40 and Llama 3.1, using a curated repository of corner-case bugs with detailed reports. This setup allowed us to assess the strengths and weaknesses of both traditional algorithms and LLMs. The SZZ algorithm achieved a recall of 0.8 and a precision of 0.36, resulting in an F1 score of 0.5 for corner cases and a recall of 1 and a precision of 0.5 for non-corner cases with an F1 score of 0.67. In comparison, the LLMs showed varied performance: for corner cases, Llama had an MRR of 0.7, while GPT scored 0.5. For non-corner cases, both models performed better, with an MRR of 0.875. Corner cases in BIC identification expose limitations in current methods, emphasizing the need for improved approaches to accurately handle these challenges.

关键词： Location awareness Codes Large language models software algorithms Computer bugs Debugging software systems software reliability Complexity theory software development management

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Clustering Technique Based on ARSH-FATI for Data Transmission in WSN-IoT Healthcare System

Clustering Technique Based on ARSH-FATI for Data Transmissio...

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Multi-Agent Systems for Collaborative Intelligence (ICMSCI), International Conference on

作者： P. Vinoth Kumar R. Jayanthi S. Sivaranjani S. Pradeep Department of Electronics and Communication Engineering Nandha College of Technology Erode Tamilnadu India Department of Electronics and Communication Engineering M.Kumarasamy College of Engineering Karur Tamilnadu India Department of Electronics Engineering K.S.Rangasamy College of Technology Tiruchengode Namakkal India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

This research study investigates the use of the Internet of Things in the health sector in terms of minimizing hospital visit costs, optimizing human resources, and enhancing the quality of healthcare. It tackles a crucial challenge in IoT-based e-health applications: the energy efficiency of battery-powered sensors. As the number of IoT sensors being used for the transmission of medical data is growing, concerns have been raised regarding the sustainability of sensor networks, which is highly dependent on battery life. A new technique, namely ARSH-FATI-based group selection, is proposed to extend the network lifespan. The ARSH-FATI algorithm combines global and local search strategies to maximize network longevity and balance performance parameters. In the CH selection process, the algorithm considers workload, residual energy, and communication distance parameters. Simulations with Python software show that the proposed ARSH-F ATI algorithm obtained a Packet Delivery Ratio (PDR) of 86%, which is almost a little lower value than that of the existing Particle Swarm Optimization (PSO) algorithm, which showed a PDR of 88% for a network of 400 sensor nodes. The outcomes of the proposed algorithm are promising and may provide a viable solution to improve the energy efficiency and lifespan of IoT networks in healthcare applications.

关键词： Wireless sensor networks Energy consumption software algorithms Clustering algorithms software Energy efficiency Sensors Data communication Sustainable development Python

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Anaheim: Architecture and algorithms for Processing Fully Homomorphic Encryption in Memory

Anaheim: Architecture and Algorithms for Processing Fully Ho...

引用

IEEE Symposium on High-Performance Computer Architecture

作者： Jongmin Kim Sungmin Yun Hyesung Ji Wonseok Choi Sangpyo Kim Jung Ho Ahn Seoul National University

ISBN: (数字)9798331506476

ISBN: (纸本)9798331506483

Fully homomorphic encryption (FHE) is a promising solution for privacy-preserving cloud computing as it enables computations on sensitive data without any risk of data leakage. Despite the significant attention FHE has received, substantial computation and memory demands make it hardly practical for real-world applications. We propose a readily available and practical hardware solution to tackle this problem by using GPUs. GPUs have adequate computational and memory resources to handle complex operations in FHE, including number-theoretic transform (NTT), on which most prior work has deeply focused. However, through detailed analyses, we discover that the performance bottleneck on GPUs is primarily due to simpler element-wise operations, which are limited by off-chip memory (DRAM) bandwidth. Motivated by these observations, we develop Anaheim, a processing-in-memory (PIM) architecture for FHE. We develop optimized FHE execution flows and an end-toend software framework for using PIM with GPUs. Also, we design a versatile PIM unit that handles various modular integer arithmetic PIM instructions, along with an efficient data mapping and associated PIM execution algorithms that minimize data access overhead by leveraging the internal structure of DRAM. Our concerted efforts substantially enhance the performance and energy efficiency of various FHE workloads on GPUs.

关键词： software algorithms Layout Random access memory Computer architecture Bandwidth Transforms software Energy efficiency Hardware Homomorphic encryption

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DL-MD: Leveraging LSTM and GRU for Cutting-Edge Malware Detection

DL-MD: Leveraging LSTM and GRU for Cutting-Edge Malware Dete...

引用

Computing and Information Technology (ICCIT-1441), 2020 International Conference on

作者： Mohammed Ali Department of Computer Science King Khalid University Abha Saudi Arabia Center for Artificial Intelligence (CAI) King Khalid University Abha Saudi Arabi

ISBN: (数字)9798350353839

ISBN: (纸本)9798350353846

In the field of cyber-security, identifying and combating malware threats continues to pose a significant challenge. While traditional techniques like signature detection and behavioral analysis have shown success, they struggle to keep up with the evolving landscape of malware variations. Additionally, although traditional clustering algorithms have been beneficial, the increasing volume and complexity of malware threats have rendered these techniques less accurate and effective in malware detection. This paper introduces an innovative approach for detecting harmful software within executable files. Our approach diverges significantly from traditional malware detection systems, which typically rely on signatures. Instead, we employ Recurrent Neural Network (RNN) algorithms to differentiate between malicious and benign files. Our experiments demonstrate that our Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models, followed by traditional clustering algorithms, significantly and effectively aid in discerning between malicious and benign files. This approach benefits from the combination of advanced deep learning techniques and traditional clustering methods. Our experiments show that the GRU model slightly outperformed the LSTM model in terms of accuracy while both GRU and LSTM models perform much better than using only traditional clustering algorithms. The effectiveness of our approach was tested across three different datasets. This work also highlights the potential of deep learning techniques, especially RNN algorithms, in strengthening information security and cyber-security defenses in today's era.

关键词： Deep learning Accuracy Clustering methods software algorithms Clustering algorithms Information security Malware Reliability Information technology Long short term memory

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Enhancement of Improving Power Quality Using Solar PV Novel Shunt Active Power Filter and Advanced MPPT algorithms

Enhancement of Improving Power Quality Using Solar PV Novel ...

引用

Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), International Conference on

作者： Mohammed Zaid Khan Seema Agrawal Dept. of Electrical Engineering Rajasthan Technical University Kota India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

Power quality issues have become a significant concern in solar photovoltaic (PV) systems due to the intermittent nature of solar irradiance. In this study, a novel approach for optimizing power quality in PV systems using a Pulse Width Controlled Shunt Active Power Filter (PWC-SAP F) is proposed. The PWC-SAPF is equipped with a Perturbed and Observed Maximum Power Point Tracking (MPPT) algorithm to ensure efficient power extraction from the PV array. The effectiveness of the proposed system is demonstrated through simulation studies on PSIM software under various operating conditions. The results show that the PWC-SAPF with the Perturbed and Observed MPPT algorithm significantly improves the power quality by mitigating harmonics and reactive power fluctuations, thereby enhancing the overall performance of the PV system. Overall, the proposed approach offers a promising solution for optimizing power quality in solar PV systems.

关键词： Maximum power point trackers Solar irradiance Shunts (electrical) Reactive power Voltage source inverters Power quality software algorithms Pulse width modulation Active filters software

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