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NC-ALG: Graph-based Active Learning under Noisy Crowd 40

NC-ALG: Graph-Based Active Learning under Noisy Crowd

引用

40th IEEE International conference on Data engineering, ICDE 2024

作者： Zhang, Wentao Wang, Yexin You, Zhenbang Li, Yang Cao, Gang Yang, Zhi Cui, Bin Center for Machine Learning Research Peking University China Key Lab of High Confidence Software Technologies Peking University China Institute of Advanced Algorithms Research Shanghai China Institute of Computational Social Science Peking University Qingdao China National Engineering Labratory for Big Data Analytics and Applications China TEG Tencent Inc. Department of Data Platform China Beijing Academy of Artificial Intelligence China

ISBN: (纸本)9798350317152

Graph Neural Networks (GNNs) have achieved great success in various data mining tasks but they heavily rely on a large number of annotated nodes, requiring considerable human efforts. Despite the effectiveness of existing GNN-based Active Learning (AL) methods, they assume that the annotated labels are always correct, which is contradictory to the error-prone labeling process in a practical crowdsourcing environment. Besides, due to this impractical assumption, existing works only focus on optimizing the node selection in AL but neglect optimizing the labeling process. Therefore, we present NC-ALG, the first GNN-based AL framework that optimizes both the node selection and node labeling process under a noisy crowd. For node selection, NC-ALG introduces a new measurement to model influence reliability and an effective influence maximization objective to select nodes. For node labeling, NC-ALG significantly reduces the labeling cost by considering the model-predicted labels and the labels of mirror nodes. To the best of our knowledge, this is the first attempt to consider GNN-based AL under the practical noisy crowd. Empirical studies on public datasets demonstrate that NC-ALG significantly outperforms existing methods in terms labeling efficiency. Notably, it only takes NC-ALG one-third of the labeling budget that the competitive baseline GRAIN needs to achieve an accuracy of 70.7 % on PubMed. © 2024 IEEE.

关键词： Crowdsourcing

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Home Interior Design Suggestion System using Deep Learning 15

Home Interior Design Suggestion System using Deep Learning

引用

15th International conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Shonali Romeshika, H.D. Dasanayaka, Dilshan Deeghayu Alwis, D.C. Herath, Hashini Wijendra, Dinuka Dassanayake, Thamali Sri Lanka Institute of Information Technology Department of Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350370249

This research investigates the transformative potential of deep learning in revolutionizing home interior design through the development of a web application with three core functionalities: object replacement within an existing interior design image, object removal from the interior design image, and text-to-image design generation based on user inputs. Leveraging deep learning models like ControlNet, DeepFill, and stable diffusion, as well as YOLOv8 for object detection and image classification (home interior/non-home interior), the proposed system is an innovative approach to democratizing design knowledge and expediting interior design procedures. This research advances interior design practices and shapes the future of personalized and effective home interior design solutions by offering effective design modifications and design suggestions. © 2024 IEEE.

关键词： Architectural design

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Theoretical Framework engineering Methodology of Cloud-based Open Cyber Infrastructure 2

Theoretical Framework Engineering Methodology of Cloud-Based...

引用

2nd IEEE International conference on Power, Electronics and Computer Applications, ICPECA 2022

作者： Zhang, Jian Yang, Tao Niu, Ziyue Zhang, Yaping Wang, Jiaqi Zhou, Kangning Beijing University of Technology School of Software Engineering Beijing China

ISBN: (纸本)9781665442763

To facilitate efforts to transform the domain-specific business vendor to be customer-centered, results-oriented, and market-based cyber-organization or e-organization, with the advances of Advanced Computing Technologies (ACT). In this paper we propose an engineering methodology and theoretical framework of constructing of an open, shared, collaborative multiple-tenant, multiple-organization domain-specific (SMEs enterprise, education, healthcare wellness, farming etc.) digital service ecosystem. The theoretical description of Cloud-based Open Cyber Infrastructure (COCI) model, as well as the software infrastructure for such a model, are developed to implement the knowledge-intensive cyber-service environment for the domain-specific business vendors. Our approach provides an ACT solution to transform the physical-vendors into cyber-vendors or e-vendors with the low-cost, high-availability, economical. At the same time, we put the forward the concept of knowledge-intensive Model as a Service (KMaaS) to meet the need of enhance the productivity and service pattern reshaping © 2022 IEEE.

关键词： Ecosystems

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Application of finite element analysis software ABAQUS in civil engineering course teaching 3

Application of finite element analysis software ABAQUS in ci...

引用

3rd International conference on Education, knowledge and Information Management, ICEKIM 2022

作者： Pan, Futing Wang, Ying Hu, Yuanchao Huang, Chunxiao Institutes Anhui Xinhua University Key Laboratory of Building Structure of Anhui Higher Education Hefei China Anhui Xinhua University Hefei China

ISBN: (纸本)9781665416665

Civil engineering is one of the disciplines with close combination of theory and practice. Theory teaching is the main form of imparting knowledge. Mechanics course is abstract and boring, and focuses on theory and formula derivation. The contents of professional courses such as steel structure and concrete structure need to be combined with experiment and theoretical analysis, and the experimental class hours of these courses are very few, so it is difficult for students to have an in-depth understanding of theoretical knowledge. ABAQUS is an engineering simulation software based on finite element method, which can solve various problems from linear analysis to complex nonlinear analysis. Applying ABAQUS finite element technology to the teaching of civil engineering courses helps to stimulate students' interest in learning and enhance students' ability to solve practical problems, so as to improve the teaching effect. © 2022 IEEE.

关键词： ABAQUS

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Investigation of Thermal Management and Control System of Lithium-Ion Battery based on Multiphysics Model 6

Investigation of Thermal Management and Control System of Li...

引用

6th IEEE International conference on knowledge Innovation and Invention, ICKII 2023

作者： Yu, Po-Yi Wang, Jung-Chang National Taiwan Ocean University Department of Marine Engineering Keelung Taiwan

ISBN: (纸本)9798350323535

Spontaneous thermal runaway has become a significant issue for thermal management and control systems during the operation of lithium-ion batteries recently. Therefore, we discussed the heat distribution of lithium-ion batteries under different high discharge rates. Firstly, the lithium-ion batteries were tested to obtain the properties of electrochemical and thermal behavior at different discharge rates. One-dimensional electrochemical coupling three-dimensional heat transfer models was established by using numerical simulation commercial software. The simulation results were compared with the experimental results to verify the feasibility of the model. Finally, the electrochemical characteristics were incorporated into the three-dimensional model, and the heat distribution profile generated by the batteries connected in series and parallel was simulated to figure out the critical temperature when the thermal runaway was triggered under different C-rates. © 2023 IEEE.

关键词： Lithium-ion batteries

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Data Literacy Framework for Thailand Government Officers 20

Data Literacy Framework for Thailand Government Officers

引用

20th International Joint conference on Computer Science and software engineering, JCSSE 2023

作者： Jirakitpaibool, Chaiwat Thammaboosadee, Sotarat Socharoentum, Monsak Mahidol University It Management Division Faculty of Engineering Nakhon Pathom Thailand Bangkok Thailand

ISBN: (纸本)9798350300505

Data has become a crucial element powering the fourth industrial revolution, making it more important than ever for employees at various organizations to be able to work with data. The value of data literacy is rapidly increasing across the globe. According to Forrester's research, by 2025, approximately 70% of employees are expected to work extensively with data, up from only 40% in 2018. Organizations that integrate data literacy into their workplace culture will have a competitive advantage in the increasingly complex global economy. Therefore, The Objective of this study is to develop a data literacy framework that covers all job positions for government officers in Thailand. This will be based on a gap analysis from international data literacy standards and national digital literacy standards to enhance the data skills of government officers. Additionally, required courses and related skills will be analyzed and synthesized from various frameworks with international standards on digital and data skills, and a gap analysis will also be performed to identify the most suitable data knowledge framework for government agencies. © 2023 IEEE.

关键词： Personnel

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Research progress of remote sensing in the field of ecological services: bibliometric analysis based on CiteSpace 5

Research progress of remote sensing in the field of ecologic...

引用

5th International conference on Geoscience and Remote Sensing Mapping, ICGRSM 2023

作者： Zhang, Kouqiang Gao, Lei School of Logistics and Management Engineering Yunnan University of Finance and Economics Kunming China Yunnan Institute of Green Science and Technology Kunming China

ISBN: (纸本)9781510672789

Remote sensing is a detection technology that has gained increasing prominence due to the global climate change and the degradation of ecosystems. In an effort to examine the current state of research and key areas of interest regarding remote sensing in the domain of ecological services, the core collection database of WOS papers was employed for retrieval. This involved querying papers published between 1994 and 2023 using specific keywords. Utilizing the literature analysis tools and Histcite provided by WOS, an analysis was conducted on the publication and citation trends among fundamental knowledge papers over different years, countries, journals, and academic disciplines. Subsequently, the CiteSpace software was utilized to identify research hotspots and create a knowledge map. The study's findings indicate that China holds a leading position in global remote sensing research related to ecological services. Moreover, there has been a notable increase in research activities concerning remote sensing in the ecological services field, accompanied by shifts in research focus. More and more studies are now directed towards addressing challenges posed by climate change, conserving biodiversity, establishing patterns for ecological security, and promoting ecological protection and restoration. These areas have emerged as prominent frontiers in this field. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Remote sensing

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Employers' Perspectives on Skills Falling Short, HEIs' Education System, and Graduates' Attributes

Employers' Perspectives on Skills Falling Short, HEIs' Educa...

引用

2024 International conference on TVET Excellence and Development, ICTeD 2024

作者： Saleh, Hasan Wahab, Nurul Asmida Abdul Fakulti Pengurusan Teknologi dan Teknousahawanan Melaka Malaysia

ISBN: (纸本)9798331516413

The objective of this study is to establish the relevance of employability skills that engineers lack, the educational system of higher education institutions, and the key characteristics of graduates from the perspective of Malaysian employers. There is an absence of information on the particular abilities needed by engineers in the workplace, the calibre of the nation's educational system, and the characteristics of graduates that make them employable. This study used a quantitative technique, with 140 questionnaires delivered to top managers at the organizational level at a Penang, Malaysia-based firm. The survey data was extracted using the Statistical Package for Social Sciences (SPSS) software version 29. Findings indicated employers agreed that engineers must be able to use and keep up with emerging technologies in engineering practice. The results suggest that Higher Education Institutions (HEIs) should update, improve, and deliver the skills with latest industry requirements to make fresh graduates more work-ready. Findings also revealed the important graduates' attributes to the industry are the ability to balance knowledge, skills, personality, and attitudes. It is suggested that this data analysis would be an important reference for engineers HEIs, and graduates to prepare themselves and take shared responsibility, especially in this challenging economic situation. © 2024 IEEE.

关键词： engineering education

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knowledge STRUCTURES OVER SIMULATION UNITS

KNOWLEDGE STRUCTURES OVER SIMULATION UNITS

引用

70th Annual Modeling and Simulation conference (ANNSIM)

作者： Kamburjan, Eduard Johnsen, Einar Broch Univ Oslo SIRIUS Ctr Gaustadalleen 23B N-0373 Oslo Norway

ISBN: (数字)9781713852889

ISBN: (纸本)9781713852889

Modern cyber-physical applications, such as those adopting the Digital Twin paradigm, typically connect simulators with data-rich components and domain knowledge, both often formalized as knowledge graphs. engineering such applications poses challenges to developers. This paper presents a language-based integration of knowledge graphs and simulators for object-oriented languages. We use Functional Mock-Up Objects (FMOs) as a programming layer to encapsulate simulators compliant with the FMI standard into OO structures and integrate FMOs into the class and type systems. We show how FMOs can be integrated into knowledge graphs by means of semantical lifting, and used to ensure structural properties of cyber-physical applications. We provide a prototype implementation of the proposed integration and discuss how it can be realized in other languages. Finally, the use of FMOs in practice is illustrated by two case studies.

关键词： Co-Simulation Object-Orientation software engineering knowledge Graphs

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An Empirical Study of Deep Transfer Learning-based Program Repair for Kotlin Projects 2022

An Empirical Study of Deep Transfer Learning-Based Program R...

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30th ACM Joint European software engineering conference / Symposium on the Foundations of software engineering (ESEC/FSE)

作者： Kim, Misoo Kim, Youngkyoung Jeong, Hohyeon Heo, Jinseok Kim, Sungoh Chung, Hyunhee Lee, Eunseok Sungkyunkwan Univ Inst Software Convergence Suwon South Korea Sungkyunkwan Univ Dept Elect & Comp Engn Suwon South Korea Samsung Elect SW Engn Grp Mobile Experience Suwon South Korea Sungkyunkwan Univ Coll Comp & Informat Suwon South Korea

ISBN: (纸本)9781450394130

Deep learning-based automated program repair (DL-APR) can automatically fix software bugs and has received significant attention in the industry because of its potential to significantly reduce software development and maintenance costs. The Samsung mobile experience (MX) team is currently switching from Java to Kotlin projects. This study reviews the application of DL-APR, which automatically fixes defects that arise during this switching process;however, the shortage of Kotlin defect-fixing datasets in Samsung MX team precludes us from fully utilizing the power of deep learning. Therefore, strategies are needed to effectively reuse the pretrained DL-APR model. This demand can be met using the Kotlin defect-fixing datasets constructed from industrial and open-source repositories, and transfer learning. This study aims to validate the performance of the pretrained DL-APR model in fixing defects in the Samsung Kotlin projects, then improve its performance by applying transfer learning. We show that transfer learning with open source and industrial Kotlin defect-fixing datasets can improve the defect-fixing performance of the existing DL-APR by 307%. Furthermore, we confirmed that the performance was improved by 532% compared with the baseline DL-APR model as a result of transferring the knowledge of an industrial (non-defect) bug-fixing dataset. We also discovered that the embedded vectors and overlapping code tokens of the code-change pairs are valuable features for selecting useful knowledge transfer instances by improving the performance of APR models by up to 696%. Our study demonstrates the possibility of applying transfer learning to practitioners who review the application of DL-APR to industrial software.

关键词： Empirical study Deep learning-based program repair Transfer learning Industrial Kotlin project SonarQube defects

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