Article
Mathematics
Alin Opreana, Simona Vinerean, Diana Marieta Mihaiu, Liliana Barbu, Radu-Alexandru Serban
Summary: In recent years, research on bank-related decision analysis has become important due to factors influencing the operating environment of banks. This study aims to develop a model that links bank performance to the operating context determined by country risk. The multi-analytic methodology proposed in this study combines fuzzy analytic network process (fuzzy-ANP) with principal component analysis (PCA) to overcome limitations of existing mathematical methods and decision-making approaches. The study demonstrates the significance of country risk in bank performance and offers contributions in terms of methodology and business and economic analysis.
Article
Automation & Control Systems
Yang Tao, Hongbo Shi, Bing Song, Shuai Tan
Summary: In this article, a distributed adaptive principal component regression algorithm is proposed for the online indicator monitoring of large-scale dynamic process. The algorithm constructs distributed data subblocks according to the process operation units and uses an adaptive resampling method to extract process local and global information simultaneously. The effectiveness of the proposed method is demonstrated through a numerical example and the Tennessee Eastman process.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Social Sciences, Interdisciplinary
Matheus Pereira Liborio, Oseias da Silva Martinuci, Alexei Manso Correa Machado, Renata de Mello Lyrio, Patricia Bernardes
Summary: Composite Indicators are one-dimensional measurements that simplify the interpretation of multidimensional phenomena and aid in the formulation of public policies. The literature on composite indicators is diverse and abundant, aimed at reducing uncertainties in the process of normalization, weighting, and aggregation. While there is already a large body of literature to guide researchers in constructing reliable composite indicators, there are still open questions regarding representing multidimensional phenomena in time-space analysis.
SOCIAL INDICATORS RESEARCH
(2022)
Article
Automation & Control Systems
Atefeh Daemi, Bhushan Gopaluni, Biao Huang
Summary: In this article, we propose a novel transfer learning approach, called domain adversarial probabilistic principal component analysis (DAPPCA), to monitor processes with data from multiple distributions. DAPPCA automatically learns feature representations that are relevant across different operational modes and improves fault detection accuracy by transferring knowledge from previously known modes.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Madjid Tavana, Mehdi Soltanifar, Francisco J. Santos-Arteaga, Hamid Sharafi
Summary: Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA) are decision science methods used in business, science, and engineering. AHP is used for prioritizing alternatives, while DEA estimates production frontiers. This study proposes hybrid MADM-DEA models that combine the strengths of AHP with DEA to address the weaknesses of conventional DEA methods and improve discrimination power. The effectiveness of the proposed models is demonstrated through numerical examples and a real-world problem, showing high correlation with benchmark models and consensus rankings.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Chemistry, Analytical
Hemant K. Upadhyay, Sapna Juneja, Ghulam Muhammad, Ali Nauman, Nancy Awadallah Awad
Summary: This study aims to evaluate ergonomics-based IoT related healthcare issues using the analytic hierarchy process, with consensus solutions potentially crucial for increasing human efficiency.
Article
Operations Research & Management Science
Jiancheng Tu, Zhibin Wu
Summary: This study investigates the causes and solutions to rank reversals in the analytic hierarchy process (AHP). It confirms that intransitive preference and prioritization methods cause rank reversals in single pairwise comparison matrices. An optimization model is proposed to obtain the priority vector with minimal rank violations and logarithmic square errors. The study also analyzes the applicability and shortcomings of existing revised AHP models in distributive AHP, ideal AHP, and multiplicative AHP, identifying inconsistency, prioritization methods, and aggregation rules as the respective causes of rank reversals. Finally, a modification suggestion is generated for intransitive collective pairwise comparison matrices using an optimization model based on minimizing the number of reversed preferences and the amount of change in preferences.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Hideaki Ishibashi, Shotaro Akaho
Summary: This letter proposes an extension of principal component analysis for gaussian process (GP) posteriors, denoted by GP-PCA. It introduces a low-dimensional space estimation for GP posteriors, which can be used for metalearning to enhance the performance of target tasks. The study addresses the challenge of defining a structure for a set of GPs with infinite-dimensional parameters by reducing the infinite dimensionality to finite-dimensional case using information geometrical framework. Additionally, an approximation method based on variational inference is proposed and the effectiveness of GP-PCA as meta-learning is demonstrated through experiments.
NEURAL COMPUTATION
(2022)
Article
Computer Science, Artificial Intelligence
Dhanapal Durai Dominic Panneer Selvam, Sarit Maitra, P. Parthiban, Abdul Zubar Hameed
Summary: This paper developed an effective IT vendor selection model for the banking & financial services industries, identifying ten main criteria and 43 sub-criteria, as well as a vendor selection score model. Practical recommendations for BFSI were provided, with Silverlake identified as the most recommended vendor.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2021)
Article
Computer Science, Artificial Intelligence
Zhou-Jing Wang
Summary: This study develops a modeling method for triangular fuzzy multiplicative preference relations and proposes an index for measuring the consistency of TFMPRs, as well as two logarithmic least square models. A comparative analysis is conducted through a numerical example to clarify the effectiveness and advantages of the proposed method, and the practicality of the proposed triangular FAHP approach is demonstrated.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Biochemical Research Methods
Kuangnan Fang, Rui Ren, Qingzhao Zhang, Shuangge Ma
Summary: Dimension reduction techniques like PCA, PLS, and CCA are extensively used in the analysis of high-dimensional omics data. Integrative analysis, which outperforms meta-analysis and individual-data analysis, has been developed for multiple datasets with compatible designs. We developed the R package iSFun to facilitate integrative dimension reduction analysis, offering comprehensive analysis options under different models and penalties.
Article
Chemistry, Multidisciplinary
Italo Linhares Salomao, Placido Rogerio Pinheiro
Summary: This paper introduces a multicriteria method to assist in selecting the most suitable structural system for slabs based on project needs and objectives. The study used the Analytic Hierarchy Process (AHP) and information from bibliographic research, expert opinion, and machine learning to determine the priority of different slab types. The analysis showed that the conventional solid slab type was the top priority, followed by other options.
APPLIED SCIENCES-BASEL
(2023)
Article
Automation & Control Systems
Xiaofeng Chen, Yanting Fang, Junyi Chai, Zeshui Xu
Summary: This paper investigates the integration of intuitionistic fuzzy (IF) sets and Analytical Hierarchy Process (AHP) to maximize advantages. Quantitative differences between AHP weights and normalized defuzzified IF-AHP weights are illustrated, revealing qualitative and quantitative disparities between AHP and IF-AHP. The study identifies conditions and strategies for utilizing IF-AHP over AHP, with data experiments and case studies for validation.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2022)
Article
Computer Science, Information Systems
Zhou-Jing Wang
Summary: This paper analyzes deficiencies in recent fuzzy eigenvector methods and introduces two frameworks of additively normalized triangular fuzzy priorities (ANTFPs) to characterize equivalent fuzzy priority vectors. By establishing three eigenproblems with positive real matrices and developing an eigenvector based linear program, the study aims to obtain support interval based ANTFPs from fuzzy multiplicative preference relation matrices.
INFORMATION SCIENCES
(2021)
Article
Mathematics
Jih-Jeng Huang
Summary: The study combines AHP with WordNet to handle the correlation between criteria, deriving independent factor weights and comparing with traditional AHP method through an online shopping case study.
Article
Genetics & Heredity
Kiran Zahid, Jian-Hua Zhao, Neil A. Smith, Ulrike Schumann, Yuan-Yuan Fang, Elizabeth S. Dennis, Ren Zhang, Hui-Shan Guo, Ming-Bo Wang
Letter
Biochemistry & Molecular Biology
Tao Zhang, Yun Jin, Jian-Hua Zhao, Feng Gao, Bang-Jun Zhou, Yuan-Yuan Fang, Hui-Shan Guo
Article
Virology
Jian-Hua Zhao, Chen-Lei Hua, Yuan-Yuan Fang, Hui-Shan Guo
CURRENT OPINION IN VIROLOGY
(2016)
Article
Microbiology
Yuan-Yuan Fang, Jian-Hua Zhao, Shang-Wu Liu, Sheng Wang, Cheng-Guo Duan, Hui-Shan Guo
FRONTIERS IN MICROBIOLOGY
(2016)
Article
Virology
Jian-Hua Zhao, Xiao-Lan Liu, Yuan-Yuan Fang, Rong-Xiang Fang, Hui-Shan Guo
Article
Biochemistry & Molecular Biology
Zhong-Qi Chen, Jian-Hua Zhao, Qian Chen, Zhong-Hui Zhang, Jie Li, Zhong-Xin Guo, Qi Xie, Shou-Wei Ding, Hui-Shan Guo
Review
Virology
Yun Jin, Jian-Hua Zhao, Hui-Shan Guo
Summary: Molecular interactions between plants and viruses provide insights into host antiviral immunity and viral counter-defense mechanisms. Antiviral defense in plants is initiated by virus-derived small-interfering RNAs, while plant viruses have evolved viral suppressors of RNAi to counteract this defense. Recent research has shown that plant antiviral responses are regulated by endogenous small silencing RNAs, RNA decay, and autophagy, with some viral suppressors also targeting these defense responses to promote infection.
CURRENT OPINION IN VIROLOGY
(2021)
Article
Biochemistry & Molecular Biology
Tao Zhang, Jian-Hua Zhao, Yuan-Yuan Fang, Hui-Shan Guo, Yun Jin
Summary: HIGS has been successfully utilized to engineer host resistance to pests and pathogens, with this study demonstrating that it effectively triggers long-lasting trans-kingdom RNAi within plant vasculature interactions with soil-borne fungal pathogens.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Multidisciplinary Sciences
Chen Zhu, Jia-Hui Liu, Jian-Hua Zhao, Ting Liu, Yun-Ya Chen, Chun-Han Wang, Zhong-Hui Zhang, Hui-Shan Guo, Cheng-Guo Duan
Summary: A study has found that the fungal pathogen Verticillium dahliae counters cross-kingdom antifungal RNA interference (RNAi) by secreting a protein called VdSSR1. This protein suppresses the movement of small RNAs (sRNAs) between the host plant and the fungus, increasing the virulence of the fungus in plants.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Microbiology
Qingyan Liu, Yingchao Li, Huawei Wu, Bosen Zhang, Chuanhui Liu, Yi Gao, Huishan Guo, Jianhua Zhao
Summary: For successful colonization, fungal pathogens have evolved specialized infection structures. This study focused on Verticillium dahliae and its colonization process on eggplants. The formation of hyphopodium with penetration peg was found to be crucial for initial colonization, suggesting a similarity in the colonization processes on eggplant and cotton. The VdNoxB/VdPls1-dependent Ca2+ elevation activating VdCrz1 signaling was identified as a common genetic pathway to regulate infection-related development in V. dahliae.
Article
Multidisciplinary Sciences
Xue-Ming Wu, Bo-Sen Zhang, Yun-Long Zhao, Hua-Wei Wu, Feng Gao, Jie Zhang, Jian-Hua Zhao, Hui-Shan Guo
Summary: This study reveals a sophisticated pathogenic mechanism of VdUlpB-deSUMOylated enolase to facilitate fungal virulence by derepressing the expression of the effector VdSCP8.
NATURE COMMUNICATIONS
(2023)
Article
Biotechnology & Applied Microbiology
Jie Li, Bo-Sen Zhang, Hua-Wei Wu, Cheng-Lan Liu, Hui-Shan Guo, Jian-Hua Zhao
Summary: The study revealed that DCL3 protein is involved in systemic RNA silencing through its RNA binding activity, and it plays a role in noncell autonomous silencing and antiviral effect.
Article
Plant Sciences
Feng Gao, Bo-Sen Zhang, Jian-Hua Zhao, Jia-Feng Huang, Pei-Song Jia, Sheng Wang, Jie Zhang, Jian-Min Zhou, Hui-Shan Guo
Article
Plant Sciences
Tao Zhang, Yun-Long Zhao, Jian-Hua Zhao, Sheng Wang, Yun Jin, Zhong-Qi Chen, Yuan-Yuan Fang, Chen-Lei Hua, Shou-Wei Ding, Hui-Shan Guo
Article
Biochemical Research Methods
Yuan-Yuan Fang, Neil A. Smith, Jian-Hua Zhao, Joanne R. M. Lee, Hui-Shan Guo, Ming-Bo Wang
PLANT VIROLOGY PROTOCOLS: NEW APPROACHES TO DETECT VIRUSES AND HOST RESPONSES, 3RD EDITION
(2015)
