Article
Engineering, Industrial
Jessica Morton, Aleksandra Zheleva, Bram B. Van Acker, Wouter Durnez, Pieter Vanneste, Charlotte Larmuseau, Jonas De Bruyne, Annelies Raes, Frederik Cornillie, Jelle Saldien, Lieven De Marez, Klaas Bombeke
Summary: Industrial settings will undergo extensive production automation with advancements in robotics and artificial intelligence. Assembly workers will need to adapt to new, more complex procedures, potentially increasing cognitive workload. The study suggests that lower individual alpha frequency (IAF) could be a promising marker for distinguishing between different levels of cognitive load and overload.
APPLIED ERGONOMICS
(2022)
Article
Computer Science, Hardware & Architecture
K. Lalitha Devi, S. Valli
Summary: The study utilizes a genetic algorithm for dynamic resource scheduling management, focusing on predicting the number of virtual machines and their CPU and memory requirements for task scheduling in the cloud as well as cost-optimized resource scheduling strategy. Tasks are clustered using the K-means algorithm and scheduled on VMs based on workload prediction results, ultimately validating the effectiveness of the algorithms.
JOURNAL OF SUPERCOMPUTING
(2021)
Article
Mathematics, Applied
Tao Feng, Chenbo Liu
Summary: Understanding the dynamics of social insect colonies is crucial in fields such as developmental biology, behavioral ecology, and sociology. In this study, we developed deterministic and stochastic models to investigate how internal and external factors drive collective foraging behavior. The theoretical analysis showed that the models exhibited global stability and a unique stationary distribution. Interestingly, these properties were independent of additional conditions. The main contribution of this work is the development of a new mathematical framework to study the impact of internal and external factors on social insect colony dynamics.
APPLIED MATHEMATICS LETTERS
(2023)
Article
Computer Science, Information Systems
Xiao Ma, Ao Zhou, Shan Zhang, Qing Li, Alex X. Liu, Shangguang Wang
Summary: The cloud-assisted mobile edge computing system is an important architecture for processing computation-intensive and delay-sensitive mobile applications efficiently. The paper proposes a Water-filling Based Dynamic Task Scheduling algorithm to solve the dynamic task scheduling problem, aiming at minimizing average task response time within the resource budget limit.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Engineering, Industrial
Xueke Wang, Steven A. Lavender, Carolyn M. Sommerich, Michael F. Rayo
Summary: Higher cognitive mental workload during office computer tasks may increase the risk of MSDs among office workers. The study found that increased mental effort was associated with changes in participants' biomechanical responses, particularly when the chair's backrest was not used.
Article
Psychology, Applied
Le Zhou, Mo Wang, Zhen Zhang
Summary: This article discusses how to handle intensive longitudinal data using the dynamic structural equation modeling method under the multilevel modeling framework, as well as the challenges and solutions that may arise when analyzing ILD.
ORGANIZATIONAL RESEARCH METHODS
(2021)
Article
Management
Shaobo Wei, Xiayu Chen, Ronald E. E. Rice
Summary: This study explores how group technology workarounds affect group performance, individual technology workarounds, and individual performance. The study finds that group technology workarounds have different effects on short- and long-term group performance. While they have a significantly positive impact on short-term group performance, this effect diminishes over time. System failure and competition intensity strengthen the positive effect of group technology workarounds on short-term performance, while system failure and task nonroutineness lessen the negative effect of group technology workarounds on long-term performance. The study also confirms the multilevel nature of technology workarounds, showing that group technology workarounds can influence individual technology workarounds and individual performance.
JOURNAL OF OPERATIONS MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Xing Jin, Zhihui Lai, Zhong Jin
Summary: The study introduces a novel double dynamic relationships graph convolutional network (DDRGCN) to estimate the strength of edges in facial graph and achieves superior performance in the field of facial expression recognition (FER). The proposed model has significantly fewer parameters and model size, outperforming existing methods in terms of accuracy, model size, and speed.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Environmental Sciences
Nancy Ivette De Las Casas, Jorge De La Riva-rodriguez, Aide Aracely Maldonado-Macias, David Saenz-Zamarron
Summary: This study aims to design and evaluate a Graphical User Interface (GUI) based on Dual N-Back tasks to induce mental workload in human-machine systems. Cognitive analysis techniques were used to identify human errors and improve user-system interaction. The study involved ten participants who completed the NASA-TLX questionnaire, which confirmed the effectiveness of inducing different levels of mental workload. The cognitive analysis also identified opportunities for GUI redesign.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2023)
Article
Psychology, Applied
Ruoxuan Li, Hongyun Liu, Zuowei Chen, Yunan Wang
Summary: Intrinsic motivation (IM) and controlled extrinsic motivation (EM) have been widely studied, but research on the dynamic relationship between employee motivation and the potential weekend effect is limited. This study used dynamic structural equation modeling (DSEM) to assess the daily dynamic and cyclic relationship between IM and controlled EM. Results showed a positive relationship between IM and controlled EM at the trait level, with low or moderate carryover from one workday to the next. An increase in controlled EM was associated with higher IM on the next workday, and weekly cycles revealed lower motivation on Monday. The autoregressive effects of IM and controlled EM were greater from Friday to Monday, and bidirectional cross-lagged effects were negative after considering weekends.
JOURNAL OF VOCATIONAL BEHAVIOR
(2023)
Article
Engineering, Civil
Jingzhou Zhu, Guochen Zhao, Longjun Xu, Shuang Li
Summary: This paper develops probabilistic seismic demand models for circular tunnels under transversal seismic load, considering uncertainties in ground motion, soil profile, tunnel depth, and lining size. It utilizes dynamic numerical analyses to construct more accurate probabilistic models, as quasi-static analyses may underestimate tunnel seismic responses. The constructed unbiased model facilitates the fragility analysis of tunnels. As a demonstration, the proposed probabilistic models are used to estimate the seismic fragility curves of a specific tunnel.
JOURNAL OF EARTHQUAKE ENGINEERING
(2023)
Article
Engineering, Biomedical
Kai Guan, Zhimin Zhang, Xiaoke Chai, Zhikang Tian, Tao Liu, Haijun Niu
Summary: Accurately evaluating the mental workload of operators is crucial in human-machine systems. This study applied a dynamic brain network analysis method to explore changes in mental workload across different tasks. The results showed that certain nodes and connectivity were sensitive to mental workload, and a SVM classifier achieved high accuracy in mental workload discrimination. The findings suggest that evaluating cross-task mental workload using dynamic functional connectivity metrics is feasible and important for understanding the neural mechanisms of different types of information.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Haotian Li, Jianxue Wang, Zeyuan Shen, Chenjia Gu, Qingtao Li, Qiangyu Ren
Summary: This paper proposes an optimal energy base planning method considering dynamic line rating (DLR) and integrated industry demand response (DR). The transmission capacity is estimated by establishing the relationship between renewable power generation and DLR calculation. The study explores the operational flexibility and maximum generation substitution capacity of the chemical industry. Numerical results demonstrate that considering DLR and industrial DR improves the economy of the energy base and facilitates renewable energy utilization.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Wen Wu, Nan Chen, Conghao Zhou, Mushu Li, Xuemin Shen, Weihua Zhuang, Xu Li
Summary: This paper investigates a dynamic RAN slicing framework for Internet of vehicles services, using a two-layer constrained RL algorithm called RAWS to solve the constrained RAN slicing problem by tackling resource allocation and workload distribution subproblems. Extensive trace-driven simulations show that RAWS effectively reduces system cost and meets QoS requirements with high probability compared to benchmarks.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2021)
Article
Automation & Control Systems
Yongping Zhang, Ying Cheng, Haitao Zheng, Fei Tao
Summary: This article proposes a personalized dynamic pricing based MS collaboration optimization method, which estimates the long-term and short-term preferences of enterprises and constructs a consumer utility model considering time decay and price changes to adapt to the dynamic collaboration process.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)