Article
Computer Science, Information Systems
Qinli Zhang, Yiying Chen, Gangqiang Zhang, Zhaowen Li, Lijun Chen, Ching-Feng Wen
Summary: The paper discusses the handling of categorical data in machine learning, introducing fuzzy information structures and new uncertainty measurements for considering the equality of attribute values. Numerical experiments and statistical tests were conducted to evaluate the performance of the proposed measurements, showing that they outperform traditional measurements based on I-structures. Furthermore, attribute reduction algorithms based on the new measurements were presented and tested in clustering analysis, showing effective performance in reducing attributes.
INFORMATION SCIENCES
(2021)
Article
Green & Sustainable Science & Technology
Dejiang Luo, Jie Huang, Hao Wu, Long Cheng, Zhilei Huo
Summary: Due to the growing demand for minerals and metals, the green mining industry has gained significant support. China has taken specific actions and made green mining a crucial part of establishing an eco-society. This study used 16 common indicators divided into four categories and employed the analytic hierarchy process and entropy weight method to reflect the relationship between indicators at different levels.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Construction & Building Technology
Yue Pan, Limao Zhang
Summary: This paper introduces a closed-loop digital twin framework integrating BIM, IoT, and data mining for smart construction project management. By capturing real-time data, modeling, and analysis, the digital twin can simulate task execution and worker cooperation to predict and optimize physical construction operations.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Geriatrics & Gerontology
Qing Zheng, Christianna S. Williams, Evan T. Shulman, Alan J. White
Summary: This study used auditable staffing data to examine the relationship between staff turnover and nursing home quality. The results showed that higher turnover rates were consistently associated with lower quality of care. The study suggests that measures should be taken to retain staff in order to improve the quality of care for nursing home residents.
JOURNAL OF THE AMERICAN GERIATRICS SOCIETY
(2022)
Article
Computer Science, Information Systems
Hao Zhang, Shenghong Ren, Xiang Li, Hanif Baharin, Abdullah Alghamdi, O. A. Alghamdi
Summary: The traditional MIS with BFD has limitations in terms of data summarization, query times, and complexity in analysis. The proposed MIS-BFD-DMM architecture, which includes a Data Mart and data mining, allows for the extraction of useful information and decision-making based on non-financial/financial info held by businesses. The test and analysis in this paper showed that the arranged star schema in DM is faster than ERD and SVM is the best algorithm based on the confusion matrix parameters.
INFORMATION PROCESSING & MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Yan Song, Damei Luo, Ningxin Xie, Zhaowen Li
Summary: This paper focuses on studying uncertainty measurement for an incomplete set-valued information system (ISVIS) and its application to attribute reduction. The similarity degree between information values is presented, along with the tolerance relation and rough approximations based on it. Furthermore, tools for measuring uncertainty in ISVIS are proposed and analyzed statistically. Information granulation and information entropy are applied to attribute reduction, and the effectiveness under different incomplete rates is analyzed and verified.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2022)
Article
Computer Science, Artificial Intelligence
Bruno Sotto-Mayor, Meir Kalech
Summary: Defect prediction is a technique used to optimize software testing by predicting potential defects in components. This study focused on using bad code smells as features in cross-project defect prediction and found that they significantly improved predictive performance.
Article
Computer Science, Information Systems
Jia Luo, Junping Xu, Obaid Aldosari, Sara A. Althubiti, Wejdan Deebani
Summary: With the growth of electronic bank data, traditional database and human analyst are unable to handle the large-scale data. This study developed an efficient Electronic Bank MIS based DW and Mining Processing system to provide accurate decision support.
INFORMATION PROCESSING & MANAGEMENT
(2022)
Editorial Material
Multidisciplinary Sciences
Michael Eisenstein
Summary: Data sharing can help preserve important scientific work, but it requires researchers to ensure that the resources can be easily located and reused.
Article
Computer Science, Artificial Intelligence
Linda Erlenhov, Francisco Gomes de Oliveira Neto, Philipp Leitner
Summary: This paper presents an empirical study on bot activity, using both quantitative and qualitative analysis. The study highlights the differences in definitions of bot activity in open-source software and identifies tools that comply with the characteristics of Devbots. The analysis also reveals that most projects experiment with multiple bots before making a decision on adoption or switching. Factors such as generated noise and required adaptation in development practices are found to drive discussions about the adoption or removal of Devbots.
PEERJ COMPUTER SCIENCE
(2022)
Article
Automation & Control Systems
Yang Li, Jiachen Yang, Zhuo Zhang, Jiabao Wen, Prabhat Kumar
Summary: This article proposes a normalized double entropy (NDE) method to assess image data quality, and the experimental results demonstrate its stability and effectiveness. Comparisons driven by selected good and bad data show that even with 70% of the dataset, the accuracy can be maintained. This is of great significance for improving efficiency and cybersecurity in healthcare systems.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Wlodzimierz Wysocki, Ireneusz Miciula, Marcin Mastalerz
Summary: This article discusses the challenges of managing software development processes and introduces a concept for classifying different types of project tasks. By utilizing statistics and iterative aggregation, the analysis becomes more accurate, allowing for better planning and faster completion of software development projects.
Article
Computer Science, Information Systems
Lukasz Reszka, Janusz Sosnowski, Bartosz Dobrzynski
Summary: This paper discusses the utilization and analysis of software repository data. By exploring the contents of repositories, detailed information about the software project development process can be obtained, which can be used to assess its efficiency and identify shortcomings.
Article
Computer Science, Information Systems
Xing Zong, Guiyu Li, Shang Zheng, Haitao Zou, Hualong Yu, Shang Gao
Summary: Heterogeneous Cross-Project Defect Prediction (HCPDP) aims to learn a prediction model from a heterogeneous source project and apply it to a target project. This paper introduces optimal transport (OT) theory to establish the relationship between source and target data distributions and proposes two prediction algorithms based on OT theory. Experimental results demonstrate the effectiveness of the proposed methods in helping developers identify defects in the early phase of software development.
Article
Computer Science, Software Engineering
Maleknaz Nayebi, Guenther Ruhe, Thomas Zimmermann
Summary: The study introduces an analytical approach called the Gandhi-Washington Method (GWM) to investigate the impact of recurring events in software projects. By mining treatment-outcome constructs from data, the method analyzes the influence of events sequences. The applicability of this method is demonstrated in empirical studies on file editing, code ownership, and release cycle time sequences.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2021)
Article
Computer Science, Information Systems
Ming Zheng, Tong Li, Rui Zhu, Yahui Tang, Mingjing Tang, Leilei Lin, Zifei Ma
INFORMATION SCIENCES
(2020)
Article
Engineering, Electrical & Electronic
Jishu Wang, Rui Zhu, Tong Li, Fengsen Gao, Qiang Wang, Qiang Xiao
Summary: The study proposes a blockchain architecture for an electronic toll collection system, incorporating a vehicle behavior management mechanism based on credit value and an evidence chain framework. Additionally, a data protection method is designed to encrypt transaction data for data security during transactions.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Review
Computer Science, Software Engineering
Ruiyin Li, Peng Liang, Mohamed Soliman, Paris Avgeriou
Summary: This research systematically investigates the reasons, consequences, and ways of detecting and handling Architecture Erosion (AEr). It finds that AEr not only leads to architectural violations and structural issues, but also affects software quality and evolution. Non-technical reasons for AEr should receive equal attention as technical reasons, and a range of approaches and tools have been proposed to detect and tackle AEr. Empirical studies are needed to understand the practices of addressing AEr in industrial settings.
JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS
(2022)
Article
Chemistry, Multidisciplinary
Jing Chen, Tong Li, Rui Zhu
Summary: This paper presents a block-network-based malicious node detection mechanism, which utilizes blockchain technology and malicious node identification algorithm to ensure smooth communication between vehicles and improve network transmission performance in the Internet of Vehicles.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Civil
Jishu Wang, Chao Zhu, Chen Miao, Rui Zhu, Xuan Zhang, Yahui Tang, Hexiang Huang, Chen Gao
Summary: This paper introduces a blockchain-enabled parking reservation framework to address the issues of low efficiency and malicious reservations in traditional parking lots. By designing a reputation mechanism and dynamically adjusting the block size, it effectively reduces malicious nodes and improves the performance balance of the blockchain.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Software Engineering
Rui Zhu, Hang Liu, Xiaolong Xu, Leilei Lin, Yeting Chen, Wenxin Li
Summary: In this study, a neural network-based method with an attention mechanism is proposed for automatic business process model generation from RPA process descriptions. By analyzing natural language text documents and using unsupervised automation to generate tree-like business process graphs, the method improves learning efficiency and optimizes business processes.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Information Systems
Kunpeng Du, Xuan Zhang, Chen Gao, Rui Zhu, Qiong Nong, Xianyu Yang, Chunlin Yin
Summary: Paraphrase Identification is a crucial task in NLP that aims to determine the semantic consistency between sentence pairs. This paper proposes a Graph-based Interaction Matching model (GIMM) that utilizes graph convolutional networks to effectively integrate the interactive information between sentences. Experimental results demonstrate the excellent performance of the proposed model.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Ruiyin Li, Mohamed Soliman, Peng Liang, Paris Avgeriou
Summary: This study investigates the erosion symptoms discussed in code reviews, their trends, and the actions taken by developers in the OpenStack community. The findings show that code review is an effective way to reduce erosion symptoms, and analyzing the trend of erosion symptoms can provide insights into the erosion status of software systems and help avoid potential risks.
IEEE 19TH INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE (ICSA 2022)
(2022)
Proceedings Paper
Computer Science, Software Engineering
Ruiyin Li, Peng Liang, Mohamed Soliman, Paris Avgeriou
Summary: As software systems evolve, their architecture can deviate from the changes in requirements, the environment, and the implementation, causing architecture erosion and impacting system maintenance and evolution. Developers usually identify architecture erosion through symptoms and find that it is caused not only by technical factors but also by non-technical factors.
2021 IEEE/ACM 29TH INTERNATIONAL CONFERENCE ON PROGRAM COMPREHENSION (ICPC 2021)
(2021)
Article
Computer Science, Software Engineering
Yahui Tang, Tong Li, Rui Zhu, Fei Du, Jishu Wang, Zifei Ma
Summary: The paper proposes a component-based hierarchical software behavior model discovery method that can discover hierarchical nested call structures during software runtime, improving the fitness of the model. By partitioning the discovery model into several parts, it aims to improve the comprehensibility of the model and reflect the interaction behavior within and between components.
SCIENTIFIC PROGRAMMING
(2021)
Proceedings Paper
Computer Science, Software Engineering
Ruiyin Li, Peng Liang, Chen Yang, Georgios Digkas, Alexander Chatzigeorgiou, Zhuang Xiong
2019 26TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC)
(2019)
Article
Computer Science, Information Systems
Rui Zhu, Yichao Dai, Tong Li, Zifei Ma, Ming Zhen, Yahui Tang, Jiayi Yuan, Yue Huang
Article
Computer Science, Information Systems
Ming Zheng, Tong Li, Rui Zhu, Jing Chen, Zifei Ma, Mingjing Tang, Zhongqiang Cui, Zhan Wang
