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检索条件"任意字段=Knowledge-Based Software Engineering Conference"

共 17413 条记录，以下是101-110 订阅

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Active Learning Methodology for Advanced Agile software engineering and DevOps Practices

Active Learning Methodology for Advanced Agile Software Engi...

引用

IEEE World engineering Education conference (EDUNINE)

作者： Juan Ignacio Irabedra Martin Solari Universidad ORT Uruguay Montevideo Uruguay

ISBN: (数字)9798331542788

ISBN: (纸本)9798331542795

Creation of digital products and services requires today high-performance interdisciplinary teams that respond quickly to customer needs. This context presents a great challenge for software engineering education, where it seeks to give students an active learning environment of professionally relevant and technologically updated skills. This report presents a classroom experience with a focus on active learning pedagogical strategies for advanced agile software engineering and DevOps practices. The instructional design of the course was based on two main pedagogical methodologies: Team-based Learning and Project-based Learning. The course was developed on digital platforms that support both the pedagogical approach and software engineering teamwork and software quality practices. Evaluation was carried out from both teacher's and student's perspectives, using quantitative and qualitative analysis. Lessons learned from the experience are presented to enable adoption of these active learning methodologies in other software engineering courses.

关键词： knowledge engineering DevOps Active learning Agile software development software quality Teamwork Maintenance Online services engineering education software engineering

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Axiomatic software Architecture

Axiomatic Software Architecture

引用

IEEE International conference on software Architecture Workshops (ICSAW)

作者： Aydin Homay Mario de Sousa Chair of Industrial Communications Technische Universität Dresden Dresden Germany Faculty of Engineering University of Porto Porto Portugal

ISBN: (数字)9798331533366

ISBN: (纸本)9798331533373

In his March 2009 resume, David L. Parnas noted that the phrase “software engineering” was coined to urge software designers to adopt the knowledge and discipline of engineers in other domains, allowing them to rely on well-developed problem-solving skills, analytical methods, mathematics, and scientific knowledge instead of relying exclusively on intuition and natural ability. We attempt to work towards that goal by reintroducing axiomatic design into software engineering, addressing major concerns and critiques highlighted by previous research in the field. The axiomatic design offers a scientific approach to improve design activities based on rational and logical thought processes and tools. The ultimate goal of axiomatic design is to encourage solution-neutral thinking to identify problems and requirements, fostering human designer's creativity, reducing random search process, and minimizing random trial-and-error to determine the best design among those proposed.

关键词： knowledge engineering Design engineering software design software architecture Computer architecture software systems Search problems Mathematics Problem-solving Creativity

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Minimizing Inconsistency in Pairwise Comparison Matrices Using Genetic Algorithm 59

Minimizing Inconsistency in Pairwise Comparison Matrices Usi...

引用

59th Annual conference on Information Sciences and Systems, CISS 2025

作者： Sayadi, Atiyeh Shajari, Baran Janicki, Ryszard McMaster University Department of Computing and Software Hamilton Canada

ISBN: (纸本)9798331513269

This paper introduces a novel approach to reduce inconsistencies in pairwise comparison matrices using a genetic algorithm inspired by the process of natural selection. The method applies a distance-based inconsistency index as the fitness function within an evolutionary process. Through experiments, we show that our genetic algorithm greatly reduces inconsistencies over generations. Smaller matrices quickly become consistent in just a few generations, showing the method's effectiveness and efficiency for different scenarios and use cases. Larger matrices, however, require more generations to reach the acceptable consistency level. The algorithm works well for different matrix sizes, adapting effectively to various challenging situations. © 2025 IEEE.

关键词： Genetic algorithms

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Leveraging knowledge Graphs for Personalized Internship Recommendations: A Case Study on software engineering Courses

Leveraging Knowledge Graphs for Personalized Internship Reco...

引用

Cybernetics and Innovations (ICCI), International conference on

作者： Supitsara Seetaworn Phuree Phenhiran Perapard Ngokpol Montira Innoy Sorayuth Ingboon Tharathon Utasri Akkharawoot Takhom Faculty of Engineering Thammasat School of Engineering Pathum Thani Thailand

ISBN: (数字)9798331533267

ISBN: (纸本)9798331533274

Internships play a vital role in bridging academic learning with industry requirements. This paper presents a knowledge graph-based framework for generating personalized internship recommendations by integrating course syllabi, student competencies, and job descriptions. The approach leverages structured knowledge representation and graph traversal to dynamically match students' academic progress with relevant opportunities. Additionally, Large Language Models (LLMs) are employed for entity extraction to enhance recommendation accuracy. A case study involving software engineering subjects within a Programme of Innovative engineering demonstrates the framework's ability to provide tailored internship suggestions and identify skill gaps. The results indicate that knowledge graphs offer a scalable and adaptable solution for aligning academic curricula with evolving industry needs.

关键词： Industries Technological innovation Accuracy Large language models knowledge graphs Cybernetics software engineering

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A Lithium-Ion Battery Cathode Material Literature Entity Recognition Method based on Deep Learning 4th

A Lithium-Ion Battery Cathode Material Literature Entity Rec...

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4th International conference on Data and Information in Online Environments

作者： Yin, Ziyu Lei, Gang Xiao, Jianmao Qiu, Xinji Zhang, Qian Chang, Lei Chen, Haohui Wu, Musheng Zhao, Xushan Jiangxi Normal Univ Sch Software Nanchang 330022 Jiangxi Peoples R China Jiangxi Normal Univ Dept Phys Nanchang 330022 Jiangxi Peoples R China Contemporary Amperex Technol Co Ltd Innovat Lab Ningde 352100 Fujian Peoples R China Jiangxi Prov Engn Res Ctr Blockchain Data Secur & Nanchang 330022 Jiangxi Peoples R China

ISBN: (纸本)9783031807121;9783031807138

With the continuous deepening of research on lithium-ion battery materials, the number of literature in related fields has shown explosive growth, posing a challenge to researchers in terms of literature reading and information screening. Named entity recognition technology can automatically mark the pre-defined entity content in the literature, helping researchers to quickly locate the key information of the articles, and improve the reading rate of the literature. In this paper, the classification system of lithium-ion battery materials literature is constructed through the combination of automation and manual analysis, and the named entity recognition operation is conducted. We adopt the named entity recognition model based on BiLSTM-CRF, combined with Bert word embedding technology, to automatically identify and extract entities in the literature, and develope an automatic document annotation tool. Our work provides strong support for researchers to quickly understand the literature content and key information, and lays a foundation for subsequent relationship extraction and the construction of a knowledge graph.

关键词： Lithium-ion Battery Materials Information Extraction Classification System Named Entity Identification

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Machine Learning-assisted Test Records Analysis during the Real-Time Validation of Automotive software Systems based on HIL Simulation 58

Machine Learning-assisted Test Records Analysis during the R...

引用

58th Hawaii International conference on System Sciences, HICSS 2025

作者： Abboush, Mohammad Knieke, Christoph Rausch, Andreas Technische Universität Clausthal Institute for Software and Systems Engineering Germany

ISBN: (纸本)9780998133188

In the automotive industry, according to ISO 26262, comprehensive testing is conducted to ensure software systems quality over various phases of the V-model. However, at the system integration and testing phase, a significant amount of time series data is analyzed manually based on expert knowledge to identify the nature of the failure occurring, which is a costly process in terms of time, effort, and difficulty. This study proposes a novel Machine Learning (ML)-assisted failure analysis approach for the real-time validation of automotive software systems (ASSs). Specifically, based on a representative critical faults dataset, intelligent data-driven ML-based Fault Detection and Diagnosis (FDD) models are developed, including LSTM and Denoising Autoencoder (DAE) + k-means techniques for known and unknown sensor-related faults, respectively. The novelty of these models lies in their ability to identify single and simultaneous faults in noisy conditions. To assess the efficacy of the developed model, a dataset from a virtual test drive platform with a high-fidelity entire vehicle model was employed. The evaluation outcomes illustrate the superiority of the proposed model for known faults classification in comparison to other state-of-the-art methods, with an average F1-score of 91.85%. Furthermore, the integration of DAE with k-means exhibited a high clustering performance against noise with a low MSE and DB, i.e., 0.044 and 0.68, respectively. Consequently, the proposed approach facilitates the real-time validation of the ASSs in an efficient manner enhancing the safety and reliability. © 2025 IEEE Computer Society. All rights reserved.

关键词： software testing

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An Ontology-based Framework for Automated Dataset Validation

An Ontology-Based Framework for Automated Dataset Validation

引用

2025 2nd International conference on Algorithms, software engineering and Network Security (ASENS)

作者： Yong Cai Xi Wang School of Computer Engineering and Science Shanghai University Shanghai China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

With the rapid development of artificial intelligence, the importance of data quality has become increasingly prominent. The existing data quality assessment methods, such as accuracy, completeness, consistency, effectiveness, timeliness, uniqueness, intelligibility assessment and data quality indicators, lack user perspective and may not accurately reflect the applicability and practicability of the data in practical application, resulting in the evaluation results not matching with the specific needs and expectations of users. In this paper, we propose OmniSense, a framework of data quality assessment based on domain model and knowledge inference. Using domain model as a bridge, the link between the original data set and the user's needs is established, and the automatic data quality assessment from the user's perspective is realized. This approach enables the developer to estimate the support of the dataset for the implementation of the function before starting training, thereby reducing the cost of retraining due to the inapplicability of the dataset.

关键词： Training knowledge engineering Data integrity software algorithms Transforms Ontologies Network security Data models Kernel software engineering

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Integrating the Biological knowledge from Protein Databases Into Spatial RNA Sequencing Analyses 26th

Integrating the Biological Knowledge from Protein Database...

引用

26th International conference on Information Integration and Web Intelligence, iiWAS 2024

作者： Leśniewska, Anna Dziȩgielewski, Szymon Melnyk, Elena Okoniewski, Michal J. Wrembel, Robert Institute of Computing Sciences Poznan University of Technology Poznan Poland Department of Biosystems Science and Engineering ETH Zurich Basel Switzerland Scientific IT Services ETH Zurich Zurich Switzerland

ISBN: (纸本)9783031780929

Spatial transcriptomics has emerged in recent years as an advanced technique integrating modern microscopy and single-cell RNA sequencing (RNA-seq). The computational aspect of spatial transcriptomics analysis is actively evolving, with software packages like Squidpy at the forefront. A critical challenge in this field is achieving reliable image segmentation based on RNA expression levels within cells, necessitating robust sets of genomic signatures. In this paper, we present our approach to addressing this challenge through data integration and by leveraging proteome signatures from The Human Protein Atlas as a reference standard, applicable to transcriptomic profiles. Our heuristic-based segmentation method provides biological validation for unsupervised techniques and serves as a preliminary proof of concept. Additionally, it establishes a benchmark for the future application of artificial intelligence with the use of transcriptome foundation models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Biotic

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Variable Training of IT Engineers for software Development 27th

Variable Training of IT Engineers for Software Development

引用

27th International conference on Interactive Collaborative Learning-ICL

作者： Kirilova, Galia I. Khasanova, Gulnara F. Shorina, Tatyana V. Yimin, Chen Yangxingyue, Guo Kazan Volga Reg Fed Univ Kazan Russia Kazan Natl Res Technol Univ Kazan Russia Kazan State Power Engn Univ Kazan Russia

ISBN: (纸本)9783031856518;9783031856525

The paper is devoted to comparing the effectiveness of variable methods for training future IT specialists, based on identifying the initial level of proficiency in SQL and HTML programming languages. An experiment was conducted with the participation of second-year students of the Kazan State Energy University (N = 200). The experiment tested two options for completing tasks, combining experience in web programming and experience working with databases. Students were given the opportunity to begin doing their work in a known way, obtain a positive result sufficient for a positive self-assessment, and then develop their knowledge and experience in accordance with the requirements of the curriculum. The study demonstrated the effectiveness of conducting an entry survey to identify the initial level of programming languages proficiency. Changes made to the content and process of training future IT specialists based on data obtained from surveys made it possible to eliminate gaps in IT competencies.

关键词： Contents of IT specialists training SQL and HTML programming languages proximal development zone of students

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Complexity Handling in the software-Defined Vehicles: Documenting the Expert knowledge

Complexity Handling in the Software-Defined Vehicles: Docume...

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IEEE International conference on software Architecture Workshops (ICSAW)

作者： Xinxin Zhu Rose Sturm Christian Seiler Stefan Wagner Mercedes-Benz AG Böblingen Germany Mercedes-Benz AG Sindelfingen Germany Technical University of Munich Heilbronn Germany

ISBN: (数字)9798331533366

ISBN: (纸本)9798331533373

Technological advancements drive the development of new Electric/Electronic and software architectures, shifting the automotive industry to a software-defined paradigm. This change has significantly impacted product configuration, and is also expected to be crucial in maintenance and upgradability throughout the entire lifecycle. This position paper analyzes current complexities in product configuration and maintenance, emphasizing the expert knowledge on component dependency, based on functionalities and properties as well as legal and sales factors, is often applied indirectly, leading to insufficiencies. This paper proposes the idea of comprehensive documentation of relevant expert knowledge and direct utilization of this in product configuration, maintenance and upgrades. This approach aims to ensure efficient component deployment throughout the vehicle's lifecycle, preserving functional integrity with minimal errors and effort.

关键词： Industries knowledge engineering software architecture Law Documentation Transforms software Maintenance Complexity theory Automotive engineering

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