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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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Enhancing Emotional and Performance Data Collection for Agile software Engineers: A Continuous Strategy Implementation 12

Enhancing Emotional and Performance Data Collection for Agil...

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12th international conference in software engineering Research and Innovation, CONISOFT 2024

作者： Salido, Martin G. Borrego, Gilberto Rodriguez, Luis-Felipe Instituto Tecnológico de Sonora Departamento de computación y diseño Mexico

ISBN: (纸本)9798331532116

Agile software Development (ASD) has become the industry standard, facilitating rapid delivery of high-quality software by prioritizing flexible, iterative processes and the interactions of agile software engineers over rigid procedures. Hence, the performance assessment of agile software engineers should consider their emotions. In this study, we aim to take the first steps toward implementing a strategy for collecting affective and performance data using biometric devices and project tracking tools through a mixed-methods study. First, we analyzed interviews on emotions and performance metrics among local agile software engineers. Second, we conducted a quantitative analysis using emotional data tools and a project tracking tool (Jira) with software engineering students on a local company project. Results indicated (i) the most experienced emotions of agile software engineers, (ii) the most used metrics to assess their performance, (iii) the discrepancy between self-assessments and biometric measurements, and (iv) the relationship between stress, emotions, and task progression in projects. Future research should aim to enhance emotional data collection strategies to reduce complexity and improve response rates, providing better insights into the emotions-performance dynamic in agile environments. © 2024 IEEE.

关键词： software quality

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A FLEXIBLE FRAMEWORK FOR ROBOTIC POST-PROCESSING OF 3D PRINTED COMPONENTS

A FLEXIBLE FRAMEWORK FOR ROBOTIC POST-PROCESSING OF 3D PRINT...

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ASME international Design engineering Technical conferences / 43rd Annual Computers and Information in engineering conference (IDETC-CIE) / 19th IEEE/ASME international conference on Mechatronic and Embedded Systems and Applications (MESA)

作者： Bajrami, Albin Palpacelli, Matteo C. Univ Politecn Marche DIISM Dept I-601341 Ancona Italy

ISBN: (纸本)9780791887356

three-dimensional (3D) printing has revolutionized the production of mechanical components by enabling the creation of objects of complex geometry, but at the same time it has introduced new issues related to post-processing operations. Similarly, robotics has seen an evolution with the emergence of collaborative robots, which can support the operator in human-centric applications. this work aims to bring these two technologies together by presenting a flexible framework for processing raw products obtained through 3D printing technology with the support of collaborative robotics. this framework lays the foundation for the subsequent development of a human-robot cooperation protocol with the aim of simplifying post-processing and particularly finishing operations of metal-printed 3D objects. In this paper, an initial integrated solution is proposed that can address the post-processing needs of objects from 3D printing, providing guidance on the software and hardware tools to be used and the process to be followed to achieve a quality product in compliance with the relevant standards. Verifications in a simulation environment and through algorithms based on the kinematics and statics of a Fanuc collaborative robot implemented in a numerical environment allow verification of the feasibility of several operations. the result is a comprehensive framework that starts from the feasibility study and reaches the completion of the 3D printed component through finishing and post-processing operations.

关键词： Manufacturing Robotics Computer-Aided engineering Process Planning

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Historical Ink: Semantic Shift Detection for 19th Century Spanish 5

Historical Ink: Semantic Shift Detection for 19th Century Sp...

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5th international Workshop on Computational Approaches to Historical Language Change, LChange 2024 - co-located with ACL 2024

作者： Montes, Tony Manrique-Gómez, Laura Manrique, Rubén Systems and Computing Engineering Department Universidad de los Andes Colombia History and Geography Department Universidad de los Andes D.C. Bogotá Colombia

ISBN: (纸本)9798891761384

this paper explores the evolution of word meanings in 19th-century Spanish texts, with an emphasis on Latin American Spanish, using computational linguistics techniques. It addresses the Semantic Shift Detection (SSD) task, which is crucial for understanding linguistic evolution, particularly in historical contexts. the study focuses on analyzing a set of Spanish target words. To achieve this, a 19th-century Spanish corpus is constructed, and a customizable pipeline for SSD tasks is developed. this pipeline helps find the senses of a word and measure their semantic change between two corpora using fine-tuned BERT-like models with old Spanish texts for both Latin American and general Spanish cases. the results provide valuable insights into the cultural and societal shifts reflected in language changes over time. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Remote Teaching of Electrical engineering Laboratory Course in the Context of COVID-19 7

Remote Teaching of Electrical Engineering Laboratory Course ...

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7th IEEE World engineering Education conference (EDUNINE) - Reimaging engineering - Toward the Next Generation of engineering Education, Merging Technologies in a Connected World

作者： Galarza, Jose Condezo, David Saenz, Bartolome Natl Univ Cent Peru Dept Elect & Elect Eng Huancayo Peru

ISBN: (纸本)9798350320503

the outbreak of the COVID-19 pandemic has produced worldwide mandatory social immobilization. Peruvian universities decided to implement a 100% distance learning modality for the May-August 2020 academic semester. this research focused on the application of immediately available resources to reorganize and continue teaching laboratory courses in the context of the pandemic. We evaluate MATLAB/Simulink, scientific papers and technical papers in laboratory courses of our electrical engineering program. through classroom observation and interviews, the impact of the use of these resources in 6 laboratory courses has been evaluated. the use of software reduced the experiment time by more than 40% and doubled the number of cases evaluated. Technical articles and reports increasing student's knowledge through new analysis techniques and new measurements processes.

关键词： COVID-19 experiences remote teaching software technical resources and laboratory course

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knowledge-Assisted DRL for Energy Harvesting Based Multi-Access Wireless Communications 23

Knowledge-Assisted DRL for Energy Harvesting Based Multi-Acc...

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Luo, Sheng Zhang, Haodi Li, Qifan Wu, Kaishun College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China

ISBN: (纸本)9781665494571

this paper investigates the use of deep reinforcement learning (DRL) to maximize the long-term throughput of multi-access wireless communication systems. Specifically, we consider the scenario in which an access point (AP) without dedicated power supply harvests energy from the ambient environment and uses the harvested energy to deliver data packets to multiple users. We formulate the access control problem as a Markov Decision Process (MDP) with unknown system dynamics and apply the deep reinforcement learning (DRL) approach to solve this problem, i.e., the optimal access strategy is approximated by using a double deep Q-network (DDQN). As the considered system usually has large state and action spaces, some domain knowledge is embedded into the training process to improve the performance of DDQN. It is shown that with the help of domain knowledge, access control strategies which can achieve a higher system throughput can be found by the knowledge-embedded DDQN. Moreover, the performance of the access control policy obtained by using the knowledge-embedded DDQN is compared with that of several conventional transmission schemes. Experiment results show that the transmission policy obtained by using our proposed model can achieve better performance. © 2021 IEEE.

关键词： Access control Wireless communication Training System dynamics Smart cities Power supplies Process control

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Optimizing High-Dimensional Text Embeddings in Emotion Identification: A Sliding Window Approach 16

Optimizing High-Dimensional Text Embeddings in Emotion Ident...

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16th international conference on knowledge Discovery and Information Retrieval, KDIR 2024 as part of 16th international Joint conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2024

作者： Uymaz, Hande Aka Metin, Senem Kumova Izmir University of Economics Department of Software Engineering Izmir Turkey

ISBN: (纸本)9789897587160

Natural language processing (NLP) is an interdisciplinary field that enables machines to understand and generate human language. One of the crucial steps in several NLP tasks, such as emotion and sentiment analysis, text similarity, summarization, and classification, is transforming textual data sources into numerical form, a process called vectorization. this process can be grouped into traditional, semantic, and contextual vectorization methods. Despite their advantages, these high-dimensional vectors pose memory and computational challenges. To address these issues, we employed a sliding window technique to partition high-dimensional vectors, aiming not only to enhance computational efficiency but also to detect emotional information within specific vector dimensions. Our experiments utilized emotion lexicon words and emotionally labeled sentences in both English and Turkish. By systematically analyzing the vectors, we identified consistent patterns with emotional clues. Our findings suggest that focusing on specific sub-vectors rather than entire high-dimensional BERT vectors can capture emotional information effectively, without performance loss. With this approach, we examined an increase in pairwise cosine similarity scores within emotion categories when using only sub-vectors. the results highlight the potential of the use of sub-vector techniques, offering insights into the nuanced integration of emotions in language and the applicability of these methods across different languages. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Vectors

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INTEGRATION OF SIMULATION INTO PRODUCT DEVELOPMENT AT AUSTRIAN SECONDARY AND TERTIARY TECHNICAL EDUCATION 25

INTEGRATION OF SIMULATION INTO PRODUCT DEVELOPMENT AT AUSTRI...

引用

25th international conference ON engineering AND PRODUCT DESIGN EDUCATION (E&PDE)

作者： Kroepfl, Patrick Probst, Andreas Landschuetzer, Christian Graz Univ Technol Graz Austria HTL Wels Wels Austria

ISBN: (纸本)9781912254194

Product development today is primarily driven by virtual methods and can therefore be assigned to virtual engineering. Various software systems are available on the market, on the one hand with embedded CAD systems and on the other hand with stand-alone systems. A major challenge in secondary and tertiary education is to combine virtual engineering methods with general engineering knowledge. this results in the quality issue of teaching how to use the software and teaching the generally applicable knowledge behind the software solutions - i.e., the methods must be taught. At Austrian HTL (secondary higher vocational schools), there is a strong focus on CAD during five years of education. In recent years, some aspects of virtual engineering have been taken up to prepare students well for working life. However, it is widely recognised that this needs to be strengthened. the paper will present the current state-of-the-art and show possible scenarios for improving the current state. At the Graz University of Technology (tertiary level), there is the situation that students have very different prior knowledge at the beginning of their studies (mainly mechanical engineering), as some of them come from HTL. An e-learning approach for CAD and CAE education was introduced in 2012 at TU Graz to counteract this and better adapt the teaching to the student's skills. As a result, a lot of experience and feedback have been gathered to improve the teaching approach continuously. the article shows this approach and outlines future perspectives.

关键词： Virtual engineering secondary education tertiary education CAE education FEA

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Transparent AI for Adaptive Fraud Detection 19

Transparent AI for Adaptive Fraud Detection

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19th international conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Agomuo, Okechukwu Clement Uzoma, Agomuo Kingsley Khan, Zohaib Otuomasirichi, Agomuo Ijeoma Muzamal, Junaid Hussain Department of Operations and Information Systems University of Utah Salt Lake City United States Center for Environmental Management and Green Energy University of Nigeria Enugu Nigeria Dept. of Software Engineering FAST NUCES Lahore Pakistan Department of Agricultural Economics University of Nigeria Enugu Nigeria Fast School of Computing Fast NUCES Lahore Pakistan

ISBN: (纸本)9798331507817

the rapid evolution of digital financial services has significantly increased the vulnerability of financial systems to fraudulent activities. Traditional machine learning models have offered substantial progress in detecting fraudulent transactions;however, they often lack adaptability and transparency, critical for dynamic financial environments and regulatory compliance. this paper introduces a novel approach that integrates Deep Reinforcement Learning (DRL) with Explainable Artificial Intelligence (XAI) to enhance fraud detection capabilities in cloud-based financial platforms. Our model, tested on the synthetic PaySim mobile money transaction dataset, leverages the adaptive nature of DRL to continuously learn and update its fraud detection strategies based on evolving transaction patterns. Concurrently, the integration of XAI provides clear, interpretable insights into the decision-making process, thus ensuring transparency and building trust. the proposed model demonstrates superior performance with an achieved accuracy of 99.5% and an F1-score of 99.0%, significantly outperforming traditional fraud detection systems. these results not only underscore the efficacy of our model in improving the accuracy of fraud detection but also highlight its capability in offering significant improvements in understanding the underlying reasons for each decision, thereby aiding compliance with financial regulations. the practical implications of this research highlight its potential to provide a robust, scalable, and transparent solution for real-time fraud detection, which is essential for safeguarding the integrity of modern financial systems. © 2025 IEEE.

关键词： Decentralized finance

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Dynamic Network Optimization with Deep Learning and Deployment of Intelligent Reflecting Surfaces 19

Dynamic Network Optimization with Deep Learning and Deployme...

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19th international conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Jang, Nayeon Bae, Jeonghoon Tianyu, Tao Byun, Gyurin Bui, Phuoc-Nguyen Lee, Tae-Jin Choo, Hyunseung Dept. of AI Systems Engineering Korea Republic of Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9798331507817

the proliferation of 5G technologies has presented challenges such as signal attenuation and high energy consumption. this study proposes a novel approach to enhance wireless networks by integrating Intelligent Reflecting Surfaces (IRS) and Artificial Intelligence (AI) to optimize signal propagation and predict the Received Signal Strength Indicator (RSSI). A new framework combines K-means clustering for IRS deployment with a Temporal Convolutional Network-Gated Recurrent Unit (TCN-GRU) model for signal prediction. Using data from 15,000 Wi-Fi access points in Herefordshire, UK, the results demonstrate significant improvements in signal strength, with the proposed model achieving a Mean Squared Error (MSE) of 37% lower than the existing models, indicating higher prediction accuracy. In addition to enhancing signal quality, the framework achieves throughput increases of 21.26% with single-group IRS and 64.91% with multi-group IRS. these results validate the proposed the potential of the framework to improve performance, making it suitable for next-generation wireless networks. © 2025 IEEE.

关键词： 5G mobile communication systems

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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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