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检索条件"任意字段=5th Israel Conference on Computer Systems and Software Engineering"

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AccMILP: An Approach for Accelerating Neural Network Verification Based on Neuron Importance 28th

AccMILP: An Approach for Accelerating Neural Network Verific...

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28th International conference on engineering of Complex computer systems (ICECCS)

作者： Zheng, Fei Xu, Qingguo Lei, Zhou Miao, Huaikou Shanghai Univ Sch Comp Engn & Sci Shanghai Peoples R China Shanghai Key Lab Comp Software Evaluating & Testi Shanghai Peoples R China

ISBN: (纸本)9783031664557;9783031664564

Deep Neural Networks (DNNs) have found successful applications in various non-safety-critical domains. However, given the inherent lack of interpretability in DNNs, ensuring their prediction accuracy through robustness verification becomes imperative before deploying them in safety-critical applications. Neural Network Verification (NNV) approaches can broadly be categorized into exact and approximate solutions. Exact solutions are complete but time-consuming, making them unsuitable for large network architectures. In contrast, approximate solutions, aided by abstraction techniques, can handle larger networks, although they may be incomplete. this paper introduces AccMILP, an approach that leverages abstraction to transform NNV problems into Mixed Integer Linear Programming (MILP) problems. AccMILP considers the impact of individual neurons on target labels in DNNs and combines various relaxation methods to reduce the size of NNV models while ensuring verification accuracy. the experimental results indicate that AccMILP can reduce the size of the verification model by approximately 30% and decrease the solution time by at least 80% while maintaining performance equal to or greater than 60% of MIPVerify. In other words, AccMILP is well-suited for the verification of large-scale DNNs.

关键词： Neural network Formal verification Mixed integer linear programming Neuron importance

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LS-DYNA-Based Car Frontal Fascia Simulation During Collision 14th

LS-DYNA-Based Car Frontal Fascia Simulation During Collision

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14th EAI International conference on Broadband Communications, Networks, and systems, BROADNETS 2024

作者： Prasanna, Jalapudi Laxmi Kumar, Kandukuri Vasantha Dhanraj, Burragalla Madduri, Uday Kumar Department of Mechanical Engineering JNTUH University College of Engineering Jagtial505501 India Department of Mechanical Engineering Vardhaman College of Engineering Hyderabad501218 India

ISBN: (纸本)9783031811708

the bumper beam assembly of an automobile is crucial for absorbing impact energy and shielding occupants from front and rear collisions. Crash testing is a type of destructive testing that is typically used to verify that cars or related components meet safe design requirements for crashworthiness including crash compatibility. Utilizing computer software to simulate car wrecks has become a vital strategy for cutting expenses and development times for automobiles. this article examines the frontal fascia of cars in a simulated crash test. the simulation of a car collision test is reported in this paper. this work seeks to verify the findings of simulating a frontal impact collision of an automobile. In order to lessen the forces encountered during the crash, it is also intended to change some of the materials that make up the parts. To assess the vehicle's collision characteristics, computer models were utilized. this particular model was a version of the Chevrolet C1500 pickup truck. the simulation is conducted using LS-DYNA software. the automobile sector uses it extensively to analyze car design. It foretells a car's actions in an accident with accuracy. the simulation's results were then verified by contrasting them with the outcomes of an identical test conducted by the NCAC (National Crash Analysis Center). © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Crashworthiness

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Overview of Current Challenges in Multi-architecture software engineering and a Vision for the Future 12th

Overview of Current Challenges in Multi-architecture Softwar...

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12th International conference on Big Data Analytics, BDA 2024

作者： Sowiński, Piotr Lacalle, Ignacio Vaño, Rafael Palau, Carlos E. Ganzha, Maria Paprzycki, Marcin Faculty of Mathematics and Information Science Warsaw University of Technology ul. Koszykowa 75 Warsaw00-662 Poland Systems Research Institute Polish Academy of Sciences ul. Newelska 6 Warsaw01-447 Poland Communications Department Universitat Politècnica de València Valencia46022 Spain

ISBN: (纸本)9783031861925

the landscape of computing technologies is changing rapidly, straining existing software engineering practices and tools. the growing need to produce and maintain increasingly complex multi-architecture applications makes it crucial to effectively accelerate and automate software engineering processes. At the same time, artificial intelligence (AI) tools are expected to work hand-in-hand with human developers. therefore, it becomes critical to model the software accurately, so that the AI and humans can share a common understanding of the problem. In this contribution, firstly, an in-depth overview of these interconnected challenges faced by modern software engineering is presented. Secondly, to tackle them, a novel architecture based on the emerging WebAssembly technology and the latest advancements in neuro-symbolic AI, autonomy, and knowledge graphs is proposed. the presented system architecture is based on the concept of dynamic, knowledge graph-based WebAssembly Twins, which model the software throughout all stages of its lifecycle. the resulting systems are to possess advanced autonomous capabilities, with full transparency and controllability by the end user. the concept takes a leap beyond the current software engineering approaches, addressing some of the most urgent issues in the field. Finally, the efforts towards realizing the proposed approach, as well as future research directions, are summarized. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Knowledge graph

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Enhancing Performance of Machine Learning Models in Healthcare: An Analytical Framework for Assessing and Improving Data Quality 5th

Enhancing Performance of Machine Learning Models in Healthca...

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5th International conference on Advances in Information Communication Technology and Computing, AICTC 2024

作者： Al-Hgaish, Areen Atan, Rodziah Yaakob, Razali Osman, Mohd Hafeez Department of Software Engineering and Information Systems Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang44330 Malaysia Department of Computer Science Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang44330 Malaysia

ISBN: (纸本)9789819761050

the utilization of Data-Driven Machine Learning (DDML) models in the healthcare sector poses unique challenges due to the crucial nature of clinical decision-making and its impact on patient outcomes. A primary concern in this domain is the data quality that forms the basis for these models, which is essential for their effectiveness. While numerous studies are dedicated to leveraging Machine Learning (ML) to enhance patient care, a substantial gap exists in understanding and evaluating the quality of training data before training ML models. this issue is exacerbated by the lack of well-defined standards to ensure that data characteristics align with the specific goals of ML in healthcare. To address this, our study introduces a conceptual three-dimensional framework focusing on data accuracy, completeness, and consistency aimed at assessing and improving the quality of training data. this framework is designed to enhance the performance, predictability, and interpretability of healthcare-specific ML models and reduce biases, thus bridging current research gaps and laying the groundwork for future developments in ML-driven healthcare systems. this paper presents the initial step for our proposed Data Quality Framework (DQF), which addresses the three dimensions mentioned above. It discusses its potential implications and applications in healthcare data, and its main goal is to provide a comprehensive overview of the proposed DQF, illustrating its significance in advancing healthcare data quality and ultimately improving patient outcomes. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data accuracy

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Two-Dimensional Multi-Deep CNNs for Accurate and Robust software Defect Detection: A Performance-Driven Approach 5

Two-Dimensional Multi-Deep CNNs for Accurate and Robust Soft...

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5th International conference on Emerging systems and Intelligent Computing, ESIC 2025

作者： Veeramachaneni, Vinod Mallick, Pradeep Kumar Rout, Subhashree Pareek, Piyush Kumar Colorado Technical University Department of Information Technology United States Kiit Deemed to be University School of Computer Engineering India Nalanda Institute of Technology Department of Computer Science and Engineering Odisha Bhubaneswar India Nitte Meenakshi Institute of Technology Yelahanka Karnataka Bengaluru560064 India

ISBN: (纸本)9798331522100

software systems are growing in size and complexity. these properties make software defect prevention challenging. thus, automatically predicting software module defects can help engineers conserve resources. Several ways have been presented to discover and fix these issues cheaply. However, these solutions may need a performance bump. this paper introduces the Multi-Deep Convolutional Neural Network to improve binary and multi-class software classification. Instead of one-dimensional CNNs, the proposed model captures n-gram characteristics inside and between datasets using a two-dimensional multi-scale convolutional technique. Advanced crow search optimisation algorithm (ACSOA) is used to optimally select model parameters. Besides Apache Active MQ, the study employed Eclipse data sets to evaluate the recommended deep learning method. F1-score, recall, accuracy, and precision were utilized to validate the model. the results show that the suggested strategy finds software vulnerabilities better and more reliably than current models. © 2025 IEEE.

关键词： Search engines

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Analysis of Key Parameters in software Defined Network for Optimizing the Performance 5

Analysis of Key Parameters in Software Defined Network for O...

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5th International conference on Emerging systems and Intelligent Computing, ESIC 2025

作者： Chandra, Pushpendra Kumar Sharma, Suraj Ray, Niranjan Kumar Negi, Satish Kumar Guru Ghasidas Vishwavidyalaya Dept. of Cse Bilaspur India Kiit Deemed to be University School of Computer Engineering Odisha Bhubaneswar India

ISBN: (纸本)9798331522100

SDN is a novel approach to networking by decoupling the control and data planes and allowing for centralized management and dynamic configuration. the paper looks into the core performance parameters critical to SDN functionality, focusing on their role in ensuring efficient, scalable, and reliable network operations. Additionally, it highlights optimization strategies and tools that address the challenges posed by these parameters. this research study aims to provide the desired broad perspective in development of innovative solutions to improve SDN performance in meeting the requirements of modern and emerging networking environments. © 2025 IEEE.

关键词： performance parameters software-Defined Networking (SDN)

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Design of Flexure Robotic Hand for Teleoperation 6th

Design of Flexure Robotic Hand for Teleoperation

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6th Joint International conference on Multibody System Dynamics and 10th Asian conference on Multibody systems, IMSD-ACMD 2020

作者： Zubair, Mohammad Bhandari, Shubham Chatterjee, Indranath Department of Mechanical Engineering Adamas University Kolkata India Software Development Engineer-I HashedIn by Deloitte Bengaluru India Department of Computer Science Manchester Metropolitan University Manchester United Kingdom

ISBN: (纸本)9789819775248

Robots are getting deployed at home and in industries, becoming an integral part of our daily lives. Sophisticated mechanisms are required to make the joints of the robots compact and simple. In this paper, we have developed a flexure joint for the fingers of the robotic hand. the flexure joint is arranged in series to make a three-DOF underactuated finger. Five fingers are arranged to make a robotic hand. Castigliano’s theorem is used to develop the deformation related to the applied loads, using the equation the flexure mechanism was designed. Pseudo-rigid model is developed to determine the stiffness of the flexure mechanism. A virtual model of the flexure mechanism is developed in a CAD environment. Finite Element (FE) simulation is conducted to the different loading conditions to evaluate the performance of the flexure mechanism. It was seen that the flexure mechanism is flexible about the rotational axis and stiff about the other axes. the stiffness model developed using the pseudo-rigid model has a good correlation with the FE simulation model. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Robotic arms

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Research on the Security Assessment Method for Mimetic Multivariate systems Based on Multi-Granularity Features

Research on the Security Assessment Method for Mimetic Multi...

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Consumer Electronics and computer engineering (ICCECE), 2021 IEEE International conference on

作者： Junwei Wang Qinglei Zhou Liming Zhang Shiliang Yu School of Cyber Science and Engineering Zhengzhou University Zhengzhou China Songshan Laboratory Zhengzhou China School of Computer Science and Artificial Intelligence Zhengzhou University Zhengzhou China

ISBN: (数字)9798331533113

ISBN: (纸本)9798331533120

Aiming at the current status quo that the security assessment of mimetic multivariate systems generally adopts a single level of assessment, which is unable to establish a security link between its internal software diversity and the overall security of mimetic multivariate systems, this paper proposes an assessment mechanism that combines two assessment methods, namely, software diversity metrics under multi-granularity characterization and risk assessment of vulnerability attacking system modeling. the experimental part of the dataset uses the GNU core toolset (coreutils 8.32), and the validity of this assessment method is verified by designing a security assessment algorithm that weights and scores the heterogeneity of the multi-granularity software diversity technique, and then by modeling an attack on the mimetic multi-variant system experiment. the experimental results show that the security assessment algorithm can effectively assess the anti-attack ability and security of the mimetic multivariate system under the multi-granularity feature, which has certain reference value for the future research on the security assessment method of the mimetic multivariate system.

关键词： Measurement software algorithms systems modeling Diversity methods software Security Risk management computer security Consumer electronics

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Performance Evaluation of Multi-ONU Customers Access Network using Spectrum Slicing and Duplication Techniques 5

Performance Evaluation of Multi-ONU Customers Access Network...

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5th International conference on Emerging Electrical Energy, Electronics and Computing Technologies, ICE4CT 2024

作者： Rahman, Juwairiyyah Abdul Mugunthan, Sivaguru A.L. Hassan, Hasliza Abu Muslim, Norliana Ab-Rahman, Mohammad Syuhaimi Department of Electrical Engineering Faculty of Engineering and Life Sciences Universiti Selangor Selangor Bestari Jaya45600 Malaysia Department of Computer and Communication Technology Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Perak Kampar31900 Malaysia Department of Electrical Electronics and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Malaysia Electrical and Computer Engineering Program Faculty of Engineering Sohar University PC:311 Sohar Oman

this study aims to increase the number of access users by limiting the sample size to 30 users while ensuring that every Optical Network Unit (ONU) receives data from the Optical Line Terminal (OLT). the proposed solution allows for the determination of power requirements at each ONU based on bus-star topologies, facilitating an increase in user capacity. the power received by each ONU is a critical parameter that system designers must consider when planning the implementation of Fiber to the Home (FTth), as it impacts the output data in terms of Bit Error Rate (BER) and Signal Quality Factor (QF) for each user. Various parameters were evaluated to ensure that the enhanced network improves scalability while adhering to standard specifications. these parameters included the Q-factor, BER, eye diagram, user count, and received power. the study employed slicing and duplication techniques, utilizing Arrayed Waveguide Grating (AWG) for signal duplication and Wavelength Division Multiplexing for signal slicing. the simulations were conducted using a transmitter operating at a frequency of 1491 nm with a power output of 0 dBm, utilizing the latest version of OptiSystem 20 software. the results highlighted the system's capability to support a total of 73,728 users, meeting stringent performance criteria. Specifically, the system achieved a Q-factor greater than 6, indicating high signal quality, and a bit error rate (BER) lower than 1 × 10-9, ensuring reliable data transmission. For the sampled 30 users, the average Q factor was 8.1527, and the average BER was 5.3648 × 10^-11, with an output power level of -54.278 dBm. Despite an increase in users, the quality of the data supplied to clients remained unchanged. these outcomes underscore the robustness and efficiency of the design in delivering high-capacity, error-resilient optical communication. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Q factor measurement

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A Graph-Based Approach for software Functionality Classification on the Web 25th

A Graph-Based Approach for Software Functionality Classific...

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25th International conference on Web Information systems engineering, WISE 2024

作者： Jiang, Yinhao Bewong, Michael Mahboubi, Arash Halder, Sajal Islam, Rafiqul Islam, Md Zahidul Ip, Ryan H. L. Gauravaram, Praveen Xue, Jason Charles Sturt University Wagga WaggaNSW2678 Australia University of Wollongong WollongongNSW2522 Australia Cyber Security Cooperative Research Centre JoondalupWA6027 Australia Data61 The Commonwealth Scientific and Industrial Research Organisation SydneyNSW2000 Australia Auckland University of Technology Auckland1010 New Zealand Tata Consultancy Services BrisbaneQLD4000 Australia

ISBN: (纸本)9789819605750

In the context of rising cybersecurity threats within software supply chains, the precise classification of software package functionalities is essential for mitigating risks posed by the exploitation of third-party libraries in web-based systems. this paper introduces a novel approach employing a Heterogeneous Information Network (HIN) and the Metapath2Vec algorithm to elevate the security and reliability of software package classification within the NPM repository, which is crucial for web application development. Our methodology capitalises on intricate package dependencies and metadata to not only enhance classification accuracy but also effectively utilise the complex and dynamic relationships widespread in web ecosystems. Comparative analyses underscore that our framework outstrips conventional methods such as DeepWalk and Node2Vec, with substantial improvements in precision and recall across a majority of functionality classes assessed. this research significantly advances web information systems engineering by providing a robust framework for the dynamic analysis of relationships and functionalities in software packages, thereby strengthening the security resilience of web-based software ecosystems. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Application programs

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