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检索条件"任意字段=19th International Conference on Software Engineering and Knowledge Engineering"

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knowledge graphs for digital twins of structural dynamic systems 31

Knowledge graphs for digital twins of structural dynamic sys...

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31st international conference on Noise and Vibration engineering, ISMA 2024 and 10th international conference on Uncertainty in Structural Dynamics, USD 2024

作者： Shen, X. Devaraja, P. Wagg, D. Bonney, M.S. The Alan Turing Institute LondonNW1 2DB United Kingdom University of Sheffield Department of Mechanical Engineering SheffieldS1 3JD United Kingdom Department of Aerospace Engineering University of Swansea SwanseaSA1 8EN United Kingdom

ISBN: (纸本)9789082893175

In this paper we consider how ontological knowledge graphs (KGs) can be used to move towards a reasoning functionality for digital twins of structural dynamic systems. the KG is used to integrate geometric and material properties, that determine the dynamic behaviours of the structure. A three-storey, small-scale building is used as a use case to create a prototype digital twin, in the context of modal testing. the concept is based on combining geometric information from computer-aided design (CAD) models, finite element analysis (FEA), data recorded from modal tests and Bayesian uncertainty quantification. the required functionality of the digital twin is to provide integration of "heterogeneous" data sources, to create an overall knowledge model of the structural dynamics that are validated by the modal test data. the KG was built using the Neo4j interface. the CAD and FEA were carried out in the open-source software Blender and FEniCSx, respectively. the resulting digital twin can provide user information, as required, via a web-based user interface. © 2024 Proceedings of ISMA 2024 - international conference on Noise and Vibration engineering and USD 2024 - international conference on Uncertainty in Structural Dynamics. All rights reserved.

关键词： knowledge graph

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Generative engineering and Design - A Comparison of Different Approaches to Utilize Artificial Intelligence in CAD software Tools 19th

Generative Engineering and Design - A Comparison of Differen...

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19th IFIP WG 5.1 international conference on Product Lifecycle Management (PLM)

作者： Gerhard, Detlef Koring, Timo Neges, Matthias Ruhr Univ Bochum Inst Prod & Serv Engn Digital Engn Chair Univ Str 150 D-44801 Bochum Germany

ISBN: (纸本)9783031251818;9783031251825

there are new CAD software tools emerging that will likely pave the way to next generation engineering design. they are labelled Generative engineering, Generative Design, Algorithm Based Design, Simulation Based Design or similar. those new tools have in common that they make intensive use of Artificial Intelligence methods and extensive computing power. the focus of these algorithm-driven approaches to developing products and finding solutions is not the explicit creation of geometry but rather the definition of constraints, boundary conditions, rules and procedures that allow the computation of feasible solutions including the implicit generation of geometric models. One major idea is to initially open up wide solution spaces that are goal-oriented based on given requirements and provide engineers with all relevant information to perform trade-off studies and create new and innovative solutions instead of perpetuating existing solutions. the newtools are often associated with topology optimization and generative manufacturing, but the concepts go far beyond and lead to a complete workflow in the creation of products. the paper systematically analyses different software tools and shows that Generative Design and engineering is interpreted and implemented differently by various software vendors, all pursuing different goals. In addition to the potentials, the paper mainly shows the current limitations of the implemented approaches in the different CAD tools. the focus is not only on the design phase, but also on how the tools take into account different aspects such as the automation of the entire development process, cost evaluation and manufacturing processes.

关键词： Generative design Generative engineering Topology optimization Artificial intelligence

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A method for adding domain knowledge to semi-supervised fault detection using signal processing gradients 31

A method for adding domain knowledge to semi-supervised faul...

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31st international conference on Noise and Vibration engineering, ISMA 2024 and 10th international conference on Uncertainty in Structural Dynamics, USD 2024

作者： Marx, D. Kunte, D. Cornelis, B. Gryllias, K. KU Leuven Department of Mechanical Engineering Celestijnenlaan 300 HeverleeB-3001 Belgium Flanders Make@KU Leuven Belgium Siemens Digital Industries Software NV Interleuvenlaan 68 Leuven Belgium Leuven.AI - KU Leuven Institute for AI Belgium

ISBN: (纸本)9789082893175

Fault detection methods for mechanical systems have diverse applications, such as detecting rotating machinery faults and identifying undesirable vehicle cabin acoustics. Supervised models are effective for this task, but rely on scarce training data from faulty conditions. As an alternative, semi-supervised methods trained on readily available reference data can be used, but these methods disregard fault detection domain knowledge from signal processing methods. In this paper it is proposed to enhance semi-supervised fault detection methods by leveraging signal processing gradients. the proposed method is based on a subspace detector, utilizing the singular value decomposition of signal processing gradients from reference conditions. Tests on three datasets show that the proposed method can outperform semi-supervised and signal processing baselines, especially in scenarios where imperfect signal processing assumptions were made. the results show future potential for using differentiable signal processing methods in semi-supervised fault detection. © 2024 Proceedings of ISMA 2024 - international conference on Noise and Vibration engineering and USD 2024 - international conference on Uncertainty in Structural Dynamics. All rights reserved.

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Impact of COVID-19 on the Factors Influencing on-Time software Project Delivery: An Empirical Study 18

Impact of COVID-19 on the Factors Influencing on-Time Softwa...

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18th international conference on Evaluation of Novel Approaches to software engineering (ENASE)

作者： Islam, Mahmudul Khan, Farhan Hasan, Mehedi Sadia, Farzana Hasan, Mahady Independent Univ Dept Comp Sci & Engn Dhaka Bangladesh

ISBN: (纸本)9789897586477

the objective of this research paper is to investigate the impact of COVID-19 on the factors influencing on-time software project delivery in different software Development Life Cycle (SDLC) models such as Agile, Incremental, Waterfall, and Prototype models. Also to identify the change of crucial factors with respect to different demographic information that influences on-time software project delivery. this study has been conducted using a quantitative approach. We surveyed software Developers, Project Managers, software Architect, QA Engineer and other roles using a Google form. Python has been used for data analysis purposes. We received 72 responses from 11 different software companies of Bangladesh, based on that we find that Attentional Focus, Team Stability, Communication, Team Maturity, and User Involvement are the most important factors for on-time software project delivery in different SDLC models during COVID-19. On the contrary, before COVID-19 Team Capabilities, Infrastructure, Team Commitment, Team Stability and Team Maturity are found as the most crucial factors. Team Maturity and Team Stability are found as common important factors for both before and during the COVID-19 scenario. We also identified the change in the impact level of factors with respect to demographic information such as experience, company size, and different SDLC models used by participants. Attentional focus is the most important factor for experienced developers while for freshers all factors are almost equally important. this study finds that there is a significant change among factors for on-time software project delivery before and during the COVID-19

关键词： Empirical Study COVID-19 Factors on-Time software Delivery SDLC Models

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Presentation of a New Decoder Based on Quantum Cellular Automata Technology Along with an Analysis of Energy Consumption 14

Presentation of a New Decoder Based on Quantum Cellular Auto...

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14th international conference on Information and knowledge Technology, IKT 2023

作者： Sadeghi, Mostafa Asadinia, Sanaz Hamidkhani, Mehdi Zavareh, Faezeh Memarzadeh Islamic Azad University Zavareh Branch Department of Computer Engineering Zavareh Iran Islamic Azad University Esfahan Branch Department of Computer Engineering Esfahan Iran Islamic Azad University Esfahan Branch Department of Electrical Engineering Esfahan Iran Pardaz Afarinane Kavir Company Zavareh Iran

ISBN: (纸本)9798350349412

Quantum Cellular Automata, a proposed nanotechnology for circuit implementation, stands out due to its high computational power and high operational frequency, along with the simplicity of designing logical circuits. this paper proposes a new decoder circuit, simulated using QCADesigner and analyzed for energy consumption using QCApro software © 2023 IEEE.

关键词： Energy utilization

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15th international conference on knowledge Discovery and Information Retrieval, KDIR 2023 as part of IC3K 2023 - Proceedings of the 15th international Joint conference on knowledge Discovery, knowledge engineering and knowledge Management

15th International Conference on Knowledge Discovery and Inf...

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15th international conference on knowledge Discovery and Information Retrieval, KDIR 2023 as part of the 15th international Joint conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2023

ISBN: (纸本)9789897586712

the proceedings contain 51 papers. the topics discussed include: identifying similar top-k household electricity consumption patterns;detecting greenwashing in the environmental, social, and governance domains using natural language processing;speech detection of real-time MRI vocal tract data;a flexible approach for retrieving geometrically similar finite element models using point cloud autoencoders;fine-tuning and aligning question answering models for complex information extraction tasks;closeness centrality detection in homogeneous multilayer networks;subject classification of software repository;recommendation system for product test failures using BERT;and an explainable knowledge graph-based news recommendation system.

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Multivocal Literature Review on Non-Technical Debt in software Development: An Exploratory Study 18

Multivocal Literature Review on Non-Technical Debt in Softwa...

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18th international conference on Evaluation of Novel Approaches to software engineering (ENASE)

作者： Saeeda, Hina Ahmad, Muhammad Ovais Gustavsson, Tomas Karlstad Univ Dept Comp Sci Karlstad Sweden Karlstad Univ Karlstad Business Sch Karlstad Sweden

ISBN: (纸本)9789897586477

Earlier research has focused on technical debt (TD). While numerous issues connected to non-technical aspects of software development (SD) that are equally worthy of "debt" status are neglected. Simultaneously, these types of debts regularly develop significant challenges to be addressed, demonstrating that the debt metaphor may be used to reason about elements other than technical ones. It motivates us to create the new umbrella term "Non-Technical Debt" (NTD) to investigate people, processes, culture, social, and organizational concerns under its cover. All types of debt are similar in some ways, and they are often caused by making risky decisions. therefore, ignoring any one dimension of debt can have severe consequences on the successful completion of SD projects. this study investigates recent literature on the current state of knowledge about NTD, its causes, and mitigation strategies. By using a thematic analysis approach, we found five NTD types (i.e., people, process, culture, social, and organizational). We further identified their accumulation causes and discussed remedies for mitigation.

关键词： Technical Debt Non-Technical Debt Process Debt Social Debt People Debt Organizational Debt software Development Multivocal Literature Review Systematic Review

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software Defect Prediction via Positional Hierarchical Attention Network 35

Software Defect Prediction via Positional Hierarchical Atten...

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35th international conference on software engineering and knowledge engineering, SEKE 2023

作者： Yi, Xinyan Xu, Hao Lu, Lu Zou, Quanyi Yang, Zhanyu School of Computer Science and Engineering South China University of Technology Guangzhou China School of Journalism and Communication South China University of Technology Guangzhou China Pazhou Laboratory Guangzhou China

software Defect Prediction (SDP) aims to identify defect-prone modules in advance to ensure software quality. In SDP research based on deep learning, the mainstream approach is to extract deep semantic features from an Abstract Syntax Tree (AST). theoretically, the AST as a bi-dimensional structure encloses information at the node level, fragment level, and entire tree level. However, most existing research serializes the whole AST without considering the expression at different granularities. To address this limitation, we introduce a positional hierarchical attention network (PHAN) that acquires semantic features by simultaneously considering contexts between nodes and paths. Specifically, our model incorporates attention mechanisms to capture information of varying importance at separate hierarchies, and relative position representations to distinguish the contributions of different paths. Experimental results demonstrate that PHAN significantly outperforms existing baseline methods. © 2023 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Defects

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ACIA: A Methodology for identification of Architectural Design Patterns that support Continuous Integration based on Continuous Assessment 19

ACIA: A Methodology for identification of Architectural Desi...

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19th IEEE international conference on software Architecture (ICSA)

作者： Helwani, Fahd Jahic, Jasmin Tutoolio GmbH Bonn Germany Univ Cambridge Cambridge England

ISBN: (纸本)9781665494939

Architectural patterns are solutions to common problems in software design. these usually tackle one or more customer requirements (business, functional, or quality requirements). As continuous deployment becomes more important for satisfying customer's experience in software projects, there is a greater need in supporting continuous integration as its prerequisite. the nature of architectural design patterns is that some are more suitable for continuous integration then others. However, the existing approaches do not prescribe how to tailor architectural design considering integration challenges. To identify patterns suitable for continuous integration, we present a methodology for identification of architectural design patterns that support continuous integration based on continuous assessment. Our methodology, based on Aglie, enables DevOps engineers to assess their integration experience considering design changes, implementation changes, and creation of new version deliverables. the methodology complements common DevOps activities and introduces templates for communicating feedback from DevOps engineers to architects. Architects handle the communicated feedback as requirements and optimise their design accordingly. In this way, the design decisions take shape of solution patterns that, besides other existing requirements, satisfy requirements necessary to facilitate continuous integration.

关键词： Continuous engineering Continuous Integration Patterns Anti-patterns Architecture Agile DevOps

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Plug-and-Play software Architecture for Coordinating Multiple Industrial Robots and Sensors from Multiple Vendors 19

Plug-and-Play Software Architecture for Coordinating Multipl...

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19th IEEE international conference on Automation Science and engineering, CASE 2023

作者： He, Honglu Aksoy, Burak Saunders, Glenn Wason, John Wen, John T. Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute United States Manufacturing Innovations Center Rensselaer Polytechnic Institute United States Wason Technology Llc United States

ISBN: (纸本)9798350320695

Integrating robots from multiple vendors into an automation ecosystem is a challenge that hinders the deployment of industrial automation. the COVID-19 pandemic has added urgency to the need for automation to maintain productivity while observing physical distancing. To address this challenge, we propose a plug-and-play software architecture using Robot Raconteur (RR). Our approach allows quick and seamless integration of disparate sensors and robots into a production system, enabling complex tasks to be performed efficiently. this technology has the potential to transform the robotics revolution in the industry. In this paper, we present a case study that demonstrates the effectiveness of our plug-and-play software architecture. the demonstration includes a plug-and-play smart teachpendant and a mock production line that performs pick-and-place tasks. Using Robot Raconteur enables ready integration of robots from multiple vendors, leading to improved productivity and cost savings. © 2023 IEEE.

关键词： software architecture

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