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检索条件"任意字段=Proceedings of the 9th Knowledge-Based Software Engineering Conference"

共 20280 条记录，以下是201-210 订阅

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8th Workshop on software Architecture Erosion and Architectural Consistency, SAEroCon 2021, 1st International Workshop on software Architecture and Machine Learning, SAML 2021, 4th International Workshop on Context-aware, Autonomous and Smart Architecture, CASA 2021, 5th Workshop on Formal Approaches for Advanced Computing Systems, FAACS 2021, 2nd International Workshop on Model-Driven engineering for software Architecture, MDE4SA 2021 and 1st International Workshop on Mining software Repositories for software Architecture, MSR4SA 2021 which complemented 15th European conference on software Architecture, ECSA 2021

8th Workshop on Software Architecture Erosion and Architectu...

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8th Workshop on software Architecture Erosion and Architectural Consistency, SAEroCon 2021, 1st International Workshop on software Architecture and Machine Learning, SAML 2021, 4th International Workshop on Context-aware, Autonomous and Smart Architecture, CASA 2021, 5th Workshop on Formal Approaches for Advanced Computing Systems, FAACS 2021, 2nd International Workshop on Model-Driven engineering for software Architecture, MDE4SA 2021 and 1st International Workshop on Mining software Repositories for software Architecture, MSR4SA 2021 which complemented 15th European conference on software Architecture, ECSA 2021

ISBN: (纸本)9783031151156

the proceedings contain 15 papers presendted at a virtual meeting. the special focus in this conference is on software Architecture Erosion and Architectural Consistency. the topics include: Interactive Elicitation of Resilience Scenarios based on Hazard Analysis Techniques;Towards an Extensible Approach for Generative Microservice Development and Deployment Using LEMMA;applying knowledge-Driven Architecture Composition with Gabble;architectural Optimization for Confidentiality Under Structural Uncertainty;foundations and Research Agenda for Simulation of Smart Ecosystems Architectures;Blended Graphical and Textual Modelling of UML-RT State-Machines: An Industrial Experience;toward Awareness Creation of Common Challenges Women are Facing in Academia: A Study from a German Perspective;mapping Source Code to Modular Architectures Using Keywords;hierarchical Code-to-Architecture Mapping;Building the MSR Tool Kaiaulu: Design Principles and Experiences;self-adaptive Machine Learning Systems: Research Challenges and Opportunities;behavioral Maps: Identifying Architectural Smells in Self-adaptive Systems at Runtime;an Architectural Approach for Enabling and Developing Cooperative Behaviour in Diverse Autonomous Robots.

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REFSQ-JP 2023 - Joint proceedings of REFSQ-2023 Workshops, Doctoral Symposium, Posters and Tools Track and Journal Early Feedback, co-located with the 28th International conference on Requirements engineering: Foundation for software Quality, REFSQ 2023

REFSQ-JP 2023 - Joint Proceedings of REFSQ-2023 Workshops, D...

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Joint of REFSQ-2023 Workshops, Doctoral Symposium, Posters and Tools Track and Journal Early Feedback, REFSQ-JP 2023

the proceedings contain 23 papers. the topics discussed include: rule-based NLP vs ChatGPT in ambiguity detection, a preliminary study;from US to domain models: recommending relationships between entities;let’s stop building at the feet of giants: recovering unavailable requirements quality artifacts;comparing general purpose pre-trained word and sentence embeddings for requirements classification;understanding developers privacy concerns through reddit thread analysis;chatbots4mobile: feature-oriented knowledge base generation using natural language;towards an agent-oriented approach for requirements engineering in the digital era;modeling and analysis of emotion-oriented goal models: virtual clinics case study;and vision paper: the sustainability awareness framework (SusAF) as a de-facto standard?.

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Study on Testing System of CAE software for Ship Structural Analysis 24

Study on Testing System of CAE Software for Ship Structural ...

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proceedings of the 7th International conference on Information Technologies and Electrical engineering

作者： Yifan Jiang Jun Ding Jianhai Jin Yu Lin Taihu Laboratory of Deepsea Technological Science Wuxi Jiangsu China China Ship Scientific Research Center Wuxi Jiangsu China The Fifth Electronics Research Institute of MIIT Guangzhou Guangdong China

ISBN: (纸本)9798400707087

CAE software for ship structural analysis includes not only the traditional structure finite element simulation analysis, but also the ship specific performance simulation analysis, involving complex mathematics, mechanics knowledge and ship industry expert knowledge, with a wide range of coverage and easy errors. the existing traditional software testing technology and industrial software testing system are not targeted, the content is not rich and specific enough, and they can't fully meet the testing needs of CAE software for ship structural analysis. In order to solve the problem, based on the existing research on the testing technology and testing system of CAE software for ship structural analysis, a quality assessment testing system including functionality, performance, interface, usability, reliability, compatibility and autonomous controllability is proposed. At the same time, testing techniques such as testing process, method and tools are introduced. It provides an effective support for the quality test of CAE software for ship structural analysis, and has been well applied in the independently developed SAM software test.

关键词： CAE software

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An iterative test case sampling method to identify critical limits of ADAS/ADS in simulation

An iterative test case sampling method to identify critical ...

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14th International Munich Chassis Symposium, IMCS 2023

作者： Markofsky, Moritz Schramm, Dieter Porsche Engineering Services GmbH Bietigheim-Bissingen Germany Universität Duisburg-Essen Duisburg Germany

ISBN: (纸本)9783662703472

How to prove safety of an Advanced Driver Assistance System (ADAS) or Automated Driving System (ADS)? Statistical validation in road traffic as used for simple ADAS quickly reaches the limits of feasibility for complex ADAS and ADS featuring SAE level 3 or higher. Scenario-based testing both in real prototype vehicles and in simulation offers an approach to tackle this challenge. In this process, the events in road traffic are described by logical scenarios based on parameters. this space defined by scenario parameters has to be explored in simulation, while the simulation itself is validated by comparison with real test drives. However, even in virtual driving tests that can be processed automatically the number of possible combinations of scenario parameters quickly gets too large when trying to test the entire parameter space. this paper presents a test case sampling method that iteratively explores the boundary between critical and non-critical test cases in the space of scenario parameters. New test cases are created near the suspected boundary, increasing the density of test cases in this region of the parameter space. this allows to characterize the parameter space with significantly fewer test cases to be simulated. the knowledge about critical limits of the system under test can be used for comparison of different software and hardware, continuous integration approaches as well as statements about the occurrence probability of critical behavior in road traffic. In this paper, the test case sampling method is explained and exemplarily evaluated for virtual validation of an Adaptive Cruise Control model in a target-cut-in scenario. © the Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature 2025.

关键词： Advanced driver assistance systems

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Research on Obstacle Avoidance Trajectory for Robots based on RRT Algorithm

Research on Obstacle Avoidance Trajectory for Robots Based o...

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Robotics, Control and Automation (ICRCA), International conference on

作者： Jiaran Wang Pengfei Sun Rao Yao Dazhong Wang School of Mechanical and Automotive Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

Aerospace engine blade remanufacturing technology requires intelligent adaptive techniques for support. Due to the complexity of the operating environment and the demand for intelligence, in order to maximize machining efficiency, avoid collisions, and adapt to different blade shapes and sizes, as well as to enhance production flexibility, research emphasis should be placed on path planning. through robotic path planning, it is possible to effectively optimize the machining path, reduce the movement time of the robot during the machining process, improve machining efficiency, and reduce the machining cycle. this paper first introduces the traditional rapidly exploring random tree (RRT) algorithm and the RRT* algorithm, and proposes an improved RRT* algorithm to address the shortcomings of these two algorithms. It first introduces the improved RRT* algorithm and proposes three improvement strategies. then, it conducts simulations in two-dimensional space and validates its effectiveness in two map environments. Finally, the paper models a robotic arm on the MATLAB software platform, simulates the path smoothing planning of the robotic arm, thereby verifying the feasibility and superiority of the algorithm.

关键词： Smoothing methods Shape Blades software algorithms Machining Manipulators software Trajectory MATLAB Collision avoidance

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Research on Document Layout Detection and Description Method for Retrieval-Augmented Generation of Large Language Model

Research on Document Layout Detection and Description Method...

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Robotics, Control and Automation (ICRCA), International conference on

作者： Simiao Xiong Caixiao Ouyang Wuhan Britain-China School Wuhan China Wuhan Vocational College of Software and Engineering Wuhan China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

Improve the accuracy of Retrieval-Augmented Generation (RAG) for Large Language Model (LLM), this paper proposes a document layout detection and description network model (Doc-LDNet) for RAG. Doc-LDNet can accomplish two tasks: one is to conduct document layout detection which can accurately identifying the positions and boundaries of different regions in the document, such as text blocks and tables. the other is to describe the images within the document by converting the image content into textual descriptions. Applying Doc-LDNet as a document parsing tool in RAG can effectively enrich the results of document parsing. the experimental results show that applying the Doc-LDNet in RAG can effectively improve the accuracy of LLM in professional domain knowledge question-answering.

关键词： Accuracy Automation Large language models Layout Semantics Retrieval augmented generation Robots

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6th International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2022, 4th International Workshop on Machine Learning and knowledge Graphs, MLKgraphs 2022, 2nd International Workshop on Time Ordered Data, ProTime2022, 2nd International Workshop on AI System engineering: Math, Modelling and software, AISys2022, 1st International Workshop on Distributed Ledgers and Related Technologies, DLRT2022 and 1st International Workshop on Applied Research, Technology Transfer and knowledge Exchange in software and Data Science, ARTE2022 held at 33rd International conference on Database and Expert Systems Applications, DEXA 2022

6th International Workshop on Cyber-Security and Functional ...

引用

6th International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2022, 4th International Workshop on Machine Learning and knowledge Graphs, MLKgraphs 2022, 2nd International Workshop on Time Ordered Data, ProTime2022, 2nd International Workshop on AI System engineering: Math, Modelling and software, AISys2022, 1st International Workshop on Distributed Ledgers and Related Technologies, DLRT2022 and 1st International Workshop on Applied Research, Technology Transfer and knowledge Exchange in software and Data Science, ARTE2022 held at 33rd International conference on Database and Expert Systems Applications, DEXA 2022

ISBN: (纸本)9783031143427

the proceedings contain 40 papers. the special focus in this conference is on Database and Expert Systems Applications. the topics include: Synthetic Data in Automatic Number Plate Recognition;An Untold Tale of Scientific Collaboration: SCCH and AC 2 T;on the Creation and Maintenance of a Documentation Generator in an Applied Research Context;towards the Digitalization of Additive Manufacturing;Twenty Years of Successful Translational Research: A Case Study of three COMET Centers;data Integration, Management, and Quality: From Basic Research to Industrial Application;building a YouTube Channel for Science Communication;introduction of Visual Regression Testing in Collaboration Between Industry and Academia;vibration Analysis for Rotatory Elements Wear Detection in Paper Mill Machine;applying Time-Inhomogeneous Markov Chains to Math Performance Rating;introducing Data Science Techniques into a Company Producing Electrical Appliances;a Technology Transfer Portal to Promote Industry-Academia Collaboration in South-Tyrol;fast and Automatic Object Registration for Human-Robot Collaboration in Industrial Manufacturing;sending Spies as Insurance Against Bitcoin Pool Mining Block Withholding Attacks;risks in DeFi-Lending Protocols - An Exploratory Categorization and Analysis of Interest Rate Differences;battling the Bullwhip Effect with Cryptography;Reporting of Cross-Border Transactions for Tax Purposes via DLT;securing File System Integrity and Version History Via Directory Merkle Trees and Blockchains;taxation of Blockchain Staking Rewards: Propositions based on a Comparative Legal Analysis;comparison Framework for Blockchain Interoperability Implementations;A Comparative Analysis of Anomaly Detection Methods for Predictive Maintenance in SME;towards Strategies for Secure Data Transfer of IoT Devices with Limited Resources;application of Validation Obligations to Security Concerns;mode Switching for Secure Edge Devices;a Lifecycle Framework for Semantic Web Machine Learn

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Workshops on AI4EA, F-IDE, CoSim-CPS, CIFMA 2022, Collocated with the 20th International conference on software engineering and Formal Methods, SEFM 2022

Workshops on AI4EA, F-IDE, CoSim-CPS, CIFMA 2022, Collocated...

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Workshops on AI4EA, F-IDE, CoSim-CPS, CIFMA 2022, Collocated with the 20th International conference on software engineering and Formal Methods, SEFM 2022

ISBN: (纸本)9783031262357

the proceedings contain 31 papers. the special focus in this conference is on AI4EA, F-IDE, CoSim-CPS, CIFMA. the topics include: Debugging Support in Atelier B;varCorC: Developing Object-Oriented software Product Lines Using Correctness-by-Construction;a Case Study in Formal Analysis of System Requirements;the TLA Debugger;Developing the UML-B Modelling Tools;validity in (Co-) Simulation;Using INTO-CPS Tools in the Development of a Digital Twin for the F1TENth Race Car;Do-it-Yourself FMU Generation;a Conceptual Framework for Production Process Parameter Optimization with Modular Hybrid Simulations;a Co-simulation-based System Using Vico for Marine Operation;paving the Way for Reinforcement Learning in Smart Grid Co-simulations;coCoSim: A Tool for Co-simulation of Mobile Cooperative Robots;high-Fidelity Modeling & Co-simulation with HyFlow;robot Nudgers. What About Transparency?;robot as Embodied Agent? A Phenomenological Critique;markov Blankets for Sustainability;executive Function and Intelligent Goal-Directed Behavior: Perspectives from Psychology, Neurology, and Computer Science;A BRDL-based Framework for Motivators and Emotions;a Depth-Bounded Semantics for Becoming Informed;Forecasting Algae Growth in Photo-Bioreactors Using Attention LSTMs;knowledge-of-Own-Factivity, the Definition of Surprise, and a Solution to the Surprise Examination Paradox;using Justified True Beliefs to Explore Formal Ignorance;evaluating Zero-Cost Active Learning for Object Detection;Fast Simulation Response by a Simulation based Machine Learning (SMiLe) Approach;condition Monitoring of a Mechanical Pulsatile Heart Support System via Support-Vector Machine;siamese Basis Function Networks for Data-Efficient Defect Classification in Technical Domains;quality Monitoring Procedure in Additive Material Extrusion Using Machine Learning;A Formal IDE for Railways: Research Challenges;preface.

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Hydrodynamic modeling of OWC and U-OWC wave energy converters using the SPH method 6th

Hydrodynamic modeling of OWC and U-OWC wave energy converter...

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6th International conference on Renewable Energies Offshore, RENEW 2024

作者： Mina, B. Martínez-Estévez, I. Gómez-Gesteira, M. Tagliafierro, B. Altomare, C. Malara, G. Arena, F. University School for Advanced Studies IUSS Pavia Pavia Italy Environmental Physics Laboratory CIM-UVIGO Universidade de Vigo Ourense Spain Maritime Engineering laboratory Universitat Politècnica de Catalunya – BarcelonaTech Barcelona Spain School of Natural and Built Environment Queen’s University Belfast Belfast United Kingdom Natural Ocean Engineering Laboratory NOEL Università "Mediterranea" di Reggio Calabria Italy

ISBN: (纸本)9781032905570

Oscillating Water Column devices (OWC) have been the object of many numerical studies, especially mesh-based ones. the peculiarity of these devices is their Power Take-off system, which often involves another phase (air) and requires special effort to be modeled properly. this work proposes a Smoothed-Particle Hydrodynamics (SPH) investigation of OWCs in their standard conception and in a slightly modified version, equipped with a U-shaped duct at the seafront (U-OWC). the novelty of this study is the modeling of a singlephase pneumatic model within an SPH framework (meshless), based on the DualSPHysics software. Hydrodynamic investigation and comparison is presented. © 2025 the Author(s).

关键词： Wave energy conversion

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Towards an Approach for Extracting UML Class Diagrams Using Advanced Language Models 9th

Towards an Approach for Extracting UML Class Diagrams Using ...

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9th International conference on Smart City Applications, SCA 2024

作者： Zakaria, Babaalla Bouziane, El Mahi Jakimi, Abdeslam Oualla, Nohamed Saadane, Rachid GL-ISI Team Faculty of Sciences and Technology Errachidia UMI-Meknes Meknes Morocco Electrical Engineering Department Hassania School of Public Works Casablanca Morocco

ISBN: (纸本)9783031886522

Modern software engineering faces complex challenges, particularly in accurately and efficiently modeling systems from textual specifications. UML class diagrams are essential tools for representing the static structure of a software system, but creating them manually can be laborious and error-prone. the emergence of deep learning techniques, more specifically Large Language Models (LLMs) opens new perspectives for automatically extracting these UML diagrams from textual descriptions. this article explores the use of deep learning, particularly large language models, to automate this extraction process. We review existing approaches, including linguistic and statistical methods, and propose a new method based on deep learning models to improve accuracy and flexibility compared to current extraction tools. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Class diagram Deep learning LLMs MDA approach NLP UML

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