Article
Psychology, Multidisciplinary
Hod Orkibi
Summary: This article discusses the concept of creative adaptability and its measurement, correlates, and outcomes in stressful situations. The results show that the association between creative adaptability and well-being is mediated by creative self-efficacy, and CA may mitigate the impact of individuals' concern about the COVID-19 pandemic.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Economics
Junjie Wang, Feixiong Liao, Jianjun Wu, Huijun Sun, Weiping Wang, Ziyou Gao
Summary: This study proposes an application-oriented framework for measuring the dynamic functional resilience of a transport network responding to disruptions. The framework incorporates three complementary capacity-related dimensions and suggests a measurement model. The results indicate that the measurement model can capture network dynamics and predict the influence of capacity expansions on network resilience.
Article
Ethics
Ibo van de Poel
Summary: The translation mentions the lack of attention in the value sensitive design literature regarding how values may change during the adoption and use of a sociotechnical system, as well as proposing a value change taxonomy and technical features to address value change.
ETHICS AND INFORMATION TECHNOLOGY
(2021)
Article
Automation & Control Systems
Xiaolei Yu, Zhibin Zhao, Xingwu Zhang, Qiyang Zhang, Yilong Liu, Chuang Sun, Xuefeng Chen
Summary: Existing fault diagnosis methods assume consistent label sets for training and test data, which is not applicable for real applications. This article proposes open set fault diagnosis (OSFD) to address this problem, where the test label set includes a portion of the training label set and unknown classes. The article further divides OSFD into shared-domain and cross-domain cases, and proposes different solutions for each case.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Xinjiani Long, Haitao Li, Yuefeng Du, Enrong Mao, Jianjian Tai
Summary: Difficulties exist in building a general model for mechanical product design due to the diversity of product types and complexity of domain knowledge required. Furthermore, challenges arise in automating, intelligentializing, and accelerating the design process based on experiential knowledge and expert decision-making. A knowledge-based automated design system was developed to address these challenges, improving the efficiency and intelligence of mechanical product design.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Biochemistry & Molecular Biology
Timo Hellwig, Shahal Abbo, Amir Sherman, Ron Ophir
Summary: Genetic diversity of Pisum fulvum was found to be low to medium, distributed between well diverged populations, with a surprising selfing rate lower than expected at 56%. There was a strong genetic bottleneck during the last glacial period, and only limited patterns of isolation by distance and environment explained 13%-18% of the genetic variation.
Article
Computer Science, Information Systems
Sejong Oh
Summary: This paper proposes a new method for measuring feature importance and interaction. For the classification model, cases with correct predictions are grouped based on their characteristics, while for the regression model, cases are grouped based on the change in prediction error. The proposed method supports understanding of feature importance and interaction, and decomposes feature importance into feature power and feature interactions.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Interdisciplinary Applications
Arjomandi Rad Mohammad, Kent Salomonsson, Mirza Cenanovic, Henrik Balague, Dag Raudberget, Roland Stolt
Summary: The design process of many high-level technical products is iterative and simulation-driven. Regression models can be useful tools, but building them from CAD parameters faces challenges. By extracting hidden features from CAD, dimensionality can be reduced and prediction accuracy improved, enabling real-time prediction capability in the early development stage.
COMPUTERS IN INDUSTRY
(2022)
Article
Computer Science, Artificial Intelligence
Xiao-Yu Zhang, Changsheng Li, Haichao Shi, Xiaobin Zhu, Peng Li, Jing Dong
Summary: This article proposes a novel adaptability decomposing encoder-decoder network to transfer reliable knowledge between trimmed and untrimmed videos for action recognition and localization. By decomposing the original features into domain-adaptable and domain-specific ones, trim- untrimmed knowledge transfer can be safely confined within a more coherent subspace.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Aerospace
Lanchuan Zhang, Weiyu Zhu, Huafei Du, Mingyun Lv
Summary: This study significantly increases the efficiency of high altitude airships in receiving solar energy through an optimized design methodology, which can save the weight of the PV array. In addition, the effects of different factors on airship endurance performance were analyzed, and a higher adaptability ratio was achieved through multi-objective optimization.
AEROSPACE SCIENCE AND TECHNOLOGY
(2021)
Review
Environmental Sciences
Nurul Izzati Othmani, Syahidah Amni Mohamed, Nor Hamizah Abdul Hamid, Noorliyana Ramlee, Lee Bak Yeo, Mohd Yazid Mohd Yunos
Summary: Bio-inspired research in sustainable building design has the potential to inspire new ecological morals, address challenges, and create a healthy environment. By adopting biomimicry approaches and principles, building designs can become more ecologically sustainable, benefiting both humans and other living organisms, while safeguarding biodiversity.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Biology
Gautam Reddy, Michael M. Desai
Summary: Recent research shows that consistent patterns of fitness increase in microbial evolution experiments are mainly driven by diminishing-returns and increasing-costs epistasis. Although the origin of this global epistasis remains unknown, it is found to emerge as a consequence of widespread microscopic epistasis. The specific quantitative relationship between the magnitude of global epistasis and the stochastic effects of microscopic epistasis predicts a universal form of fitness effects distribution when epistasis is prevalent.
Article
Computer Science, Information Systems
Xinying Pang, Yitian Xu
Summary: Multi-task lasso (MTL) is an effective algorithm for multi-task problems, but it is time-consuming for high-dimensional problems. To accelerate the training process, an improved safe feature elimination rule called IEDPP is proposed based on the row sparsity of the optimal solution.
INFORMATION SCIENCES
(2023)
Article
Psychology, Multidisciplinary
Danqi Wang, Xiping Liu
Summary: This article explores the effectiveness of Life Design Counseling (LDC) for high school students in the subject selection. The Career Adapt-Abilities Scale-China Form was used to evaluate the outcomes of LDC before and after intervention. The Innovative Moments Coding System (IMCS) and Future Career Autobiography (FCA) were used to evaluate the process of LDC. The results showed a significant change in career adaptability through LDC, and a significant narrative movement or change during the process was observed. Implications for future research and practice were discussed.
FRONTIERS IN PSYCHOLOGY
(2023)
Article
Energy & Fuels
Yongwang Zhang, Wanjiang Wang, Zhe Wang, Meng Gao, Litong Zhu, Junkang Song
Summary: This article discusses how to improve the quality of buildings and promote low energy consumption, green, ecological, and sustainable building development by developing green buildings and using renewable energy such as solar energy in light of global warming, environmental degradation, and energy resource shortage issues.
Review
Computer Science, Artificial Intelligence
Wei Gao, Shuangshuang Ge
Summary: This study provides a comprehensive review of slope stability research based on artificial intelligence methods, focusing on slope stability computation and evaluation. The review covers studies using quasi-physical intelligence methods, simulated evolutionary methods, swarm intelligence methods, hybrid intelligence methods, artificial neural network methods, vector machine methods, and other intelligence methods. The merits, demerits, and state-of-the-art research advancement of these studies are analyzed, and possible research directions for slope stability investigation based on artificial intelligence methods are suggested.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Khuong Le Nguyen, Hoa Thi Trinh, Saeed Banihashemi, Thong M. Pham
Summary: This study investigated the influence of input parameters on the shear strength of RC squat walls and found that ensemble learning models, particularly XGBoost, can effectively predict the shear strength. The axial load had a greater influence than reinforcement ratio, and longitudinal reinforcement had a more significant impact compared to horizontal and vertical reinforcement. The performance of XGBoost model outperforms traditional design models and reducing input features still yields reliable predictions.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Bo Hu, Huiyan Zhang, Xiaoyi Wang, Li Wang, Jiping Xu, Qian Sun, Zhiyao Zhao, Lei Zhang
Summary: A deep hierarchical echo state network (DHESN) is proposed to address the limitations of shallow coupled structures. By using transfer entropy, candidate variables with strong causal relationships are selected and a hierarchical reservoir structure is established to improve prediction accuracy. Simulation results demonstrate that DHESN performs well in predicting algal bloom.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Limin Wang, Lingling Li, Qilong Li, Kuo Li
Summary: This paper discusses the urgency of learning complex multivariate probability distributions due to the increase in data variability and quantity. It introduces a highly scalable classifier called TAN, which utilizes maximum weighted spanning tree (MWST) for graphical modeling. The paper theoretically proves the feasibility of extending one-dependence MWST to model high-dependence relationships and proposes a heuristic search strategy to improve the fitness of the extended topology to data. Experimental results demonstrate that this algorithm achieves a good bias-variance tradeoff and competitive classification performance compared to other high-dependence or ensemble learning algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhejing Hu, Gong Chen, Yan Liu, Xiao Ma, Nianhong Guan, Xiaoying Wang
Summary: Anxiety is a prevalent issue and music therapy has been found effective in reducing anxiety. To meet the diverse needs of individuals, a novel model called the spatio-temporal therapeutic music transfer model (StTMTM) is proposed.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Nur Ezlin Zamri, Mohd. Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, Siti Syatirah Sidik, Alyaa Alway, Nurul Atiqah Romli, Yueling Guo, Siti Zulaikha Mohd Jamaludin
Summary: In this study, a hybrid logic mining model was proposed by combining the logic mining approach with the Modified Niche Genetic Algorithm. This model improves the generalizability and storage capacity of the retrieved induced logic. Various modifications were made to address other issues. Experimental results demonstrate that the proposed model outperforms baseline methods in terms of accuracy, precision, specificity, and correlation coefficient.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys
Summary: The paper addresses the problem of efficiently optimizing machine learning solutions by reducing the configuration space of ML pipelines and leveraging historical performance. The experiments conducted show that opportunistic/systematic meta-knowledge can improve ML outcomes, and configuration-space culling is optimal when balanced. The utility and impact of meta-knowledge depend on various factors and are crucial for generating informative meta-knowledge bases.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
G. Sophia Jasmine, Rajasekaran Stanislaus, N. Manoj Kumar, Thangamuthu Logeswaran
Summary: In the context of a rapidly expanding electric vehicle market, this research investigates the ideal locations for EV charging stations and capacitors in power grids to enhance voltage stability and reduce power losses. A hybrid approach combining the Fire Hawk Optimizer and Spiking Neural Network is proposed, which shows promising results in improving system performance. The optimization approach has the potential to enhance the stability and efficiency of electric grids.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhijiang Wu, Guofeng Ma
Summary: This study proposes a natural language processing-based framework for requirement retrieval and document association, which can help to mine and retrieve documents related to project managers' requirements. The framework analyzes the ontology relevance and emotional preference of requirements. The results show that the framework performs well in terms of iterations and threshold, and there is a significant matching between the retrieved documents and the requirements, which has significant managerial implications for construction safety management.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Yung-Kuan Chan, Chuen-Horng Lin, Yuan-Rong Ben, Ching-Lin Wang, Shu-Chun Yang, Meng-Hsiun Tsai, Shyr-Shen Yu
Summary: This study proposes a novel method for dog identification using nose-print recognition, which can be applied to controlling stray dogs, locating lost pets, and pet insurance verification. The method achieves high recognition accuracy through two-stage segmentation and feature extraction using a genetic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Shaohua Song, Elena Tappia, Guang Song, Xianliang Shi, T. C. E. Cheng
Summary: This study aims to optimize supplier selection and demand allocation decisions for omni-channel retailers in order to achieve supply chain resilience. It proposes a two-phase approach that takes into account various factors such as supplier evaluation and demand allocation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jinyan Hu, Yanping Jiang
Summary: This paper examines the allocation problem of shared parking spaces considering parking unpunctuality and no-shows. It proposes an effective approach using sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm to solve the problem. The numerical experiments demonstrate the significance of supply-demand balance for the operation and user satisfaction of the shared parking system.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Soroor Motie, Bijan Raahemi
Summary: Financial fraud is a persistent problem in the finance industry, but Graph Neural Networks (GNNs) have emerged as a powerful tool for detecting fraudulent activities. This systematic review provides a comprehensive overview of the current state-of-the-art technologies in using GNNs for financial fraud detection, identifies gaps and limitations in existing research, and suggests potential directions for future research.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Enhao Ning, Changshuo Wang, Huang Zhang, Xin Ning, Prayag Tiwari
Summary: This review provides a detailed overview of occluded person re-identification methods and conducts a systematic analysis and comparison of existing deep learning-based approaches. It offers important theoretical and practical references for future research in the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jiajun Ma, Songyu Hu, Jianzhong Fu, Gui Chen
Summary: The article presents a novel visual hierarchical attention detector for multi-scale defect location and classification, utilizing texture, semantic, and instance features of defects through a hierarchical attention mechanism, achieving multi-scale defect detection in bearing images with complex backgrounds.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)