Article
Computer Science, Interdisciplinary Applications
Armand Huet, Romain Pinquie, Philippe Veron, Antoine Mallet, Frederic Segonds
Summary: The integration of design rules and CAD software can be achieved through a knowledge graph that structures design rules in a computable format, facilitating the development of the data model and the definition of design context concept. Capturing design context in near real time and running reasoning operations on the knowledge graph can extend traditional CAD capabilities.
COMPUTERS IN INDUSTRY
(2021)
Article
Computer Science, Artificial Intelligence
Armand Huet, Frederic Segonds, Romain Pinquie, Philippe Veron, Jerome Guegan, Antoine Mallet
Summary: Design rules are important for exchanging information between designers and experts. Despite advancements in Knowledge-Based Engineering and Knowledge Management, unstructured design rules documents are still commonly used in the manufacturing industry. The Context-Aware Cognitive Design Assistant (CACDA) helps to recommend design rules, verify design solutions, and automate design routines, ultimately improving the quality of CAD models in the design process.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Ru Wang, Anand Balu Nellippallil, Guoxin Wang, Yan Yan, Janet K. Allen, Farrokh Mistree
Summary: Process knowledge is crucial for the digitalization and intelligentization of the manufacturing industry. The management of complexity and uncertainty in model-based engineered systems is critical to achieving rational, comprehensive, and robust decisions. The proposed decision-centric design process representation scheme aims to support the management of complexity and uncertainty in decision-making processes.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Green & Sustainable Science & Technology
Delio I. Castaneda, Camilo A. Ramirez
Summary: The study found that cultural values are related to knowledge sharing behavior, with uncertainty avoidance, individualism-collectivism, and paternalism being correlated with knowledge sharing, while power distance and masculinity-femininity are not correlated with knowledge sharing.
Review
Computer Science, Information Systems
Luke Bartlett, Muhammad Ashad Kabir, Jun Han
Summary: This study investigates the integration of BPM, virtualization, and work design to enhance organizational performance and productivity. The findings suggest that integrating virtualization and work design in BPM systems improves flexibility, scalability, and user experience. The study also identifies gaps in the current literature and opportunities for further research.
Article
Computer Science, Artificial Intelligence
Yongjun Ji, Zuhua Jiang, Xinyu Li, Yongwen Huang, Fuhua Wang
Summary: In collaborative product design, engineers' knowledge needs are disrupted by complex multitask context information. Traditional knowledge recommendation methods often lack relevance and accuracy. To address this, a multitask context-aware approach for DLK recommendation is proposed, which effectively meets engineers' knowledge needs in different tasks and ensures accuracy.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Computer Science, Artificial Intelligence
Xinyu Li, Chun-Hsien Chen, Pai Zheng, Zuhua Jiang, Linke Wang
Summary: This paper proposes a context-aware diversity-oriented knowledge recommendation approach, addressing three diversity concerns through semantic-based content analysis, context definition and awareness, and user profile modeling, to assist stakeholders in accomplishing engineering solution design in a smarter manner.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Information Science & Library Science
Adnan Alghail, Liu Yao, Mohammed Abbas, Yahia Baashar
Summary: Integrating knowledge process capabilities into project management enables institutions to perform critical tasks and value chain activities, enhancing project management maturity level. However, if one capability does not positively impact project management maturity, it affects the maturity level of the entire project.
JOURNAL OF KNOWLEDGE MANAGEMENT
(2022)
Article
Computer Science, Interdisciplinary Applications
Iman Morshedzadeh, Amos H. C. Ng, Manfred Jeusfeld, Jan Oscarsson
Summary: Virtual engineering requires maintenance in a PLM system to manage the increasing rate and diversity of models being created. This research proposes an extension to PLM systems by designing a new information model to effectively manage historical information related to virtual models and engineering activities.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2022)
Article
Environmental Sciences
Dirk J. Roux, Peter Novellie, Izak P. J. Smit, Joop de Kraker, Samantha Mc Culloch-Jones, Luthando E. Dziba, Stefanie Freitag, Danie J. Pienaar
Summary: Adaptive management is a systematic approach that combines learning with implementation to facilitate continuous improvement in natural resource management. Learning from experience and adapting subsequent policies, strategies, and actions is appealing, but obstacles such as lack of documented lessons and insufficient attention to the social aspects of learning hinder its application.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Information Science & Library Science
Anna Zeuge, Cindy Schaefer, Andreas Weigel, Andreas Eckhardt, Bjoern Niehaves
Summary: Process Virtualization Theory (PVT) proposes requirements and relationships to explain the virtualization of knowledge work processes. However, crisis-driven digital transformation has shown that almost all knowledge work processes can be unexpectedly and immediately virtualized in remote work settings. This study explores how information technology (IT) can fulfill the requirements of virtualized knowledge work processes in a crisis-driven digital transformation through interviews and finds that the characteristics of PVT support the fulfillment of requirements, with two additional characteristics positively contributing to the fulfillment.
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT
(2023)
Article
Chemistry, Physical
Ahmad Naquash, Amjad Riaz, Muhammad Abdul Qyyum, Gwangsik Kim, Moonyong Lee
Summary: This study presents a simple yet efficient approach, known as knowledge-based optimization (KBO), to selecting an optimal mixed refrigerant (MR) composition and studying the effect of each refrigerant on the performance of the H2 liquefaction process. The KBO approach guides in selecting the lower and upper limit of each refrigerant based on their impact inside heat exchangers. This study is of great importance for developing an energy-efficient and cost-effective initial design for the H2 liquefaction process.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Article
Information Science & Library Science
Shuyang Li, Jorge Tiago Martins, Ana Cristina Vasconcelos, Guochao Peng
Summary: This study presents a new framework that explores the interaction between knowledge domains and knowledge sharing skills in construction projects. The research fills the gaps in understanding the nature of knowledge domains that need to be shared in project contexts and the key skills contributing to knowledge sharing.
JOURNAL OF KNOWLEDGE MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Yongjun Ji, Zuhua Jiang, Xinyu Li, Yongwen Huang, Jianfeng Liu
Summary: The paper proposes a hypernetwork-based context-aware DLK proactive feedback approach to predict possible design quality problems in the design process. By constructing a hypernetwork-based DLK representation model and utilizing a context-aware collaborative reason strategy, this approach provides designers with DLK and helps reduce the reoccurrence of previous quality problems in DFM.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Social Sciences, Interdisciplinary
Ushaque Ahmed, Rabia Aslam, Najmonnisa Khan, Muhammad Mujtaba Asad
Summary: This study aimed to investigate EFL teachers' knowledge management practices. The findings showed that teachers create, share, and utilize knowledge through various activities and media, but rarely use technological devices for knowledge management. The study suggests that teachers should receive regular training in knowledge management.
Article
Computer Science, Cybernetics
Danilo P. Freitas, Marcos R. S. Borges, Paulo Victor R. de Carvalho
BEHAVIOUR & INFORMATION TECHNOLOGY
(2020)
Review
Chemistry, Analytical
Ramon Chaves, Daniel Schneider, Antonio Correia, Claudia L. R. Motta, Marcos R. S. Borges
Article
Environmental Sciences
M. Iturriza, L. Labaka, M. Ormazabal, M. Borges
Article
Computer Science, Information Systems
Bruna Diirr, Marcos Roberto da Silva Borges
Summary: Handling irregular phenomena can be complex for teams involved. Planning for recommended procedures may result in multiple decision alternatives, making it challenging. In addition, expectations may not align with observed phenomena, requiring creative actions and decision-making. An approach for on-the-fly adaptation of plans was evaluated and found feasible in dealing with unforeseen situations while handling irregular phenomena in complex environments, specifically in the emergency management domain.
INTERNATIONAL JOURNAL OF DECISION SUPPORT SYSTEM TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Juan Francisco Carias, Marcos R. S. Borges, Leire Labaka, Saioa Arrizabalaga, Josune Hernantes
Article
Multidisciplinary Sciences
Juliana B. S. Franca, Marcos R. S. Borges
SN APPLIED SCIENCES
(2020)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Ramon Chaves, Daniel Schneider, Antonio Correia, Marcos R. S. Borges, Claudia Motta
PROCEEDINGS OF THE 2019 IEEE 23RD INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD)
(2019)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Angelica F. S. Dias, Juliana B. S. Franca, Adriana Vivacqua, Marcos Borges, Bruna Lima
PROCEEDINGS OF THE 2019 IEEE 23RD INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD)
(2019)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Maria Teresa A. Gouvea, Flavia Maria Santoro, Claudia Cappelli, Claudia L. R. Motta, Marcos R. S. Borges
PROCEEDINGS OF THE 2019 IEEE 23RD INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD)
(2019)
Proceedings Paper
Computer Science, Software Engineering
Cleidson R. B. de Souza, Laura S. Gaytan-Lugo, Claudia Lopez, Marcos R. S. Borges, Francisco J. Gutierrez, Cecilia Aragon
COMPANION OF THE 2018 ACM CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING (CSCW'18)
(2018)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Francila Weidt Neiva, Juliana B. S. Franca, Angelica F. S. Dias, Adriana S. Vivacqua, Marcus R. S. Borges
PROCEEDINGS OF THE 2018 IEEE 22ND INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN ((CSCWD))
(2018)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Angelica F. S. Dias, Juliana B. S. Franca, Francila Weidt Neiva, Marcos R. S. Borges, Adriana S. Vivacqua
PROCEEDINGS OF THE 2018 IEEE 22ND INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN ((CSCWD))
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
Francila Weidt Neiva, Juliana B. S. Franca, Angelica F. S. Dias, Marcos R. S. Borges
2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Juliana B. S. Franca, Francila W. Neiva, Angelica F. S. Dias, Marcos R. S. Borges
2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
(2017)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Francila Weidt Neiva, Marcos R. S. Borges
2017 IEEE 21ST INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD)
(2017)
Article
Computer Science, Information Systems
Xia Liang, Jie Guo, Peide Liu
Summary: This paper investigates a novel consensus model based on social networks to manage manipulative and overconfident behaviors in large-scale group decision-making. By proposing a novel clustering model and improved methods, the consensus reaching is effectively facilitated. The feedback mechanism and management approach are employed to handle decision makers' behaviors. Simulation experiments and comparative analysis demonstrate the effectiveness of the model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Xiang Li, Haiwang Guo, Xinyang Deng, Wen Jiang
Summary: This paper proposes a method based on class gradient networks for generating high-quality adversarial samples. By introducing a high-level class gradient matrix and combining classification loss and perturbation loss, the method demonstrates superiority in the transferability of adversarial samples on targeted attacks.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Lingyun Lu, Bang Wang, Zizhuo Zhang, Shenghao Liu
Summary: Many recommendation algorithms only rely on implicit feedbacks due to privacy concerns. However, the encoding of interaction types is often ignored. This paper proposes a relation-aware neural model that classifies implicit feedbacks by encoding edges, thereby enhancing recommendation performance.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Jaehong Yu, Hyungrok Do
Summary: This study discusses unsupervised anomaly detection using one-class classification, which determines whether a new instance belongs to the target class by constructing a decision boundary. The proposed method uses a proximity-based density description and a regularized reconstruction algorithm to overcome the limitations of existing one-class classification methods. Experimental results demonstrate the superior performance of the proposed algorithm.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Hui Tu, Shifei Ding, Xiao Xu, Haiwei Hou, Chao Li, Ling Ding
Summary: Border-Peeling algorithm is a density-based clustering algorithm, but its complexity and issues on unbalanced datasets restrict its application. This paper proposes a non-iterative border-peeling clustering algorithm, which improves the clustering performance by distinguishing and associating core points and border points.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Long Tang, Pan Zhao, Zhigeng Pan, Xingxing Duan, Panos M. Pardalos
Summary: In this work, a two-stage denoising framework (TSDF) is proposed for zero-shot learning (ZSL) to address the issue of noisy labels. The framework includes a tailored loss function to remove suspected noisy-label instances and a ramp-style loss function to reduce the negative impact of remaining noisy labels. In addition, a dynamic screening strategy (DSS) is developed to efficiently handle the nonconvexity of the ramp-style loss.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Raghunathan Krishankumar, Sundararajan Dhruva, Kattur S. Ravichandran, Samarjit Kar
Summary: Health 4.0 is gaining global attention for better healthcare through digital technologies. This study proposes a new decision-making framework for selecting viable blockchain service providers in the Internet of Medical Things (IoMT). The framework addresses the limitations in previous studies and demonstrates its applicability in the Indian healthcare sector. The results show the top ranking BSPs, the importance of various criteria, and the effectiveness of the developed model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Tao Tan, Hong Xie, Liang Feng
Summary: This paper proposes a heterogeneous update idea and designs HetUp Q-learning algorithm to enlarge the normalized gap by overestimating the Q-value corresponding to the optimal action and underestimating the Q-value corresponding to the other actions. To address the limitation, a softmax strategy is applied to estimate the optimal action, resulting in HetUpSoft Q-learning and HetUpSoft DQN. Extensive experimental results show significant improvements over SOTA baselines.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Guandong Xu
Summary: This paper proposes a dynamic transformer-based architecture called Dyformer for multivariate time series classification. Dyformer captures multi-scale features through hierarchical pooling and adaptive learning strategies, and improves model performance by introducing feature-map-wise attention mechanisms and a joint loss function.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Xiguang Li, Baolu Feng, Yunhe Sun, Ammar Hawbani, Saeed Hammod Alsamhi, Liang Zhao
Summary: This paper proposes an enhanced scatter search strategy, using opposition-based learning, to solve the problem of automated test case generation based on path coverage (ATCG-PC). The proposed ESSENT algorithm selects the path with the lowest path entropy among the uncovered paths as the target path and generates new test cases to cover the target path by modifying the dimensions of existing test cases. Experimental results show that the ESSENT algorithm outperforms other state-of-the-art algorithms, achieving maximum path coverage with fewer test cases.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Shirin Dabbaghi Varnosfaderani, Piotr Kasprzak, Aytaj Badirova, Ralph Krimmel, Christof Pohl, Ramin Yahyapour
Summary: Linking digital accounts belonging to the same user is crucial for security, user satisfaction, and next-generation service development. However, research on account linkage is mainly focused on social networks, and there is a lack of studies in other domains. To address this, we propose SmartSSO, a framework that automates the account linkage process by analyzing user routines and behavior during login processes. Our experiments on a large dataset show that SmartSSO achieves over 98% accuracy in hit-precision.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Renchao Wu, Jianjun He, Xin Li, Zuguo Chen
Summary: This paper proposes a memetic algorithm with fuzzy-based population control (MA-FPC) to solve the joint order batching and picker routing problem (JOBPRP). The algorithm incorporates batch exchange crossover and a two-level local improvement procedure. Experimental results show that MA-FPC outperforms existing algorithms in terms of solution quality.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Guoxiang Zhong, Fagui Liu, Jun Jiang, Bin Wang, C. L. Philip Chen
Summary: In this study, we propose the AMFormer framework to address the problem of mixed normal and anomaly samples in deep unsupervised time-series anomaly detection. By refining the one-class representation and introducing the masked operation mechanism and cost sensitive learning theory, our approach significantly improves anomaly detection performance.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Jin Zhou, Kang Zhou, Gexiang Zhang, Ferrante Neri, Wangyang Shen, Weiping Jin
Summary: In this paper, the authors focus on the issue of multi-objective optimisation problems with redundant variables and indefinite objective functions (MOPRVIF) in practical problem-solving. They propose a dual data-driven method for solving this problem, which consists of eliminating redundant variables, constructing objective functions, selecting evolution operators, and using a multi-objective evolutionary algorithm. The experiments conducted on two different problem domains demonstrate the effectiveness, practicality, and scalability of the proposed method.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Georgios Charizanos, Haydar Demirhan, Duygu Icen
Summary: This article proposes a new fuzzy logistic regression framework that addresses the problems of separation and imbalance while maintaining the interpretability of classical logistic regression. By fuzzifying binary variables and classifying subjects based on a fuzzy threshold, the framework demonstrates superior performance on imbalanced datasets.
INFORMATION SCIENCES
(2024)
