• Journal of People, Plants, and Environment
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• v.24 no.2
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• pp.179-194
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• 2021

Background and objective: Plant-based biofilter system has become a promising candidate for improving indoor air quality due to its eco-friendly and sustainable nature. However, it remains controversial whether indoor air purification using a biofilter is effective. Methods: This study used the one-group pre- and post-test design to analyze the effects of the operation of the plant-based biofilter system on indoor air quality, students' perception of indoor air quality, health effects, and subjective and objective attentiveness. Results: Results of this study show that the application of the plant-based biofilter system changed the air environment in the classroom. The operation of the plant-based biofilter system significantly decreased PM_2.5 and PM₁₀ and slightly increased temperature and humidity. Satisfaction with air quality and subjective attentiveness were significantly improved but objective attentiveness and health effects were not improved. Conclusion: Further studies need to be conducted for improving indoor air quality of schools and evaluating the health effects and attention of occupants to present the objective performance of the plant-based biofilter system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.80-96
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• 2022

Nowadays, artificial intelligence promotes the rapid development of skin cancer detection technology, and the federated skin cancer detection model (FSDM) and dual generative adversarial network model (DGANM) solves the fragmentation and privacy of data to a certain extent. To overcome the problem that the many-objective evolutionary algorithm (MaOEA) cannot guarantee the convergence and diversity of the population when solving the above models, a many-objective evolutionary algorithm based on integrated strategy (MaOEA-IS) is proposed. First, the idea of federated learning is introduced into population mutation, the new parents are generated through sub-populations employs different mating selection operators. Then, the distance between each solution to the ideal point (SID) and the Achievement Scalarizing Function (ASF) value of each solution are considered comprehensively for environment selection, meanwhile, the elimination mechanism is used to carry out the select offspring operation. Eventually, the FSDM and DGANM are solved through MaOEA-IS. The experimental results show that the MaOEA-IS has better convergence and diversity, and it has superior performance in solving the FSDM and DGANM. The proposed MaOEA-IS provides more reasonable solutions scheme for many scholars of skin cancer detection and promotes the progress of intelligent medicine.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1238-1259
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• 2024

Previous studies on joint optimization of computation offloading and service caching policies in Mobile Edge Computing (MEC) have often neglected the impact of dependency-aware subtasks, edge server resource constraints, and multiple users on policy formulation. To remedy this deficiency, this paper proposes a many-objective joint optimization dependency-aware task offloading and service caching model (MaJDTOSC). MaJDTOSC considers the impact of dependencies between subtasks on the joint optimization problem of task offloading and service caching in multi-user, resource-constrained MEC scenarios, and takes the task completion time, energy consumption, subtask hit rate, load variability, and storage resource utilization as optimization objectives. Meanwhile, in order to better solve MaJDTOSC, a many-objective evolutionary algorithm TSMSNSGAIII based on a three-stage mating selection strategy is proposed. Simulation results show that TSMSNSGAIII exhibits an excellent and stable performance in solving MaJDTOSC with different number of users setting and can converge faster. Therefore, it is believed that TSMSNSGAIII can provide appropriate sub-task offloading and service caching strategies in multi-user and resource-constrained MEC scenarios, which can greatly improve the system offloading efficiency and enhance the user experience.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.608-611
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• 2003

Performance assessment was introduced to improvement of self-directed learning and method of assessment for differenced learning as the seventh educational curriculum is enforced. Performance assessment is overcoming limitation about problem solving ability and higher thinking abilities assessment that is problem of a written examination and get into the spotlight by way for quality of class and school normalization. But performance assessment has problems about possibilities of assessment fault by appraisal, fairness, reliability, and validity of grading, ambiguity of grading standard, difficulty about objectivity security etc. This study proposes fuzzy performance assessment system to solve problem of the conventional performance assessment. This paper presented an objective and reliable performance assessment method through fuzzy reasoning, design fuzzy membership function and define fuzzy rule analyzing factor that influence in each sacred ground of performance assessment to account principle subject. Also, performance assessment item divides by formation estimation and subject estimation and designed membership function in proposed performance assessment method. Performance assessment result that is worked through fuzzy performance assessment system can pare down burden about appraisal's fault and provide fair and reliable assessment result through grading that have correct standard and consistency to students.

• International Journal of Clinical Preventive Dentistry
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• v.14 no.4
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• pp.256-263
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• 2018

Objective: This study aimed to investigate the factors associated with masticatory performance, as measured with a chewing gum containing spherical resinous microparticles, and to evaluate the method by examining the relationship with self-reported masticatory status. Methods: The participants in this study comprised 903 industrial workers (mean age, $42.2{\pm}11.6years$). A questionnaire was administered to assess self-reported masticatory status. The masticatory performance score was calculated by counting the number of particles in the chewing gum. Clinical oral examinations were administered. Multiple linear regression analysis was conducted on the masticatory performance scores to examine the related factors. Analysis of covariance was conducted to investigate the association between the masticatory performance score and the self-reported masticatory status. Results: Significant predictors of the masticatory performance score were sex (p<0.001), age (p<0.001), decayed teeth (p=0.009), total-functional tooth units (p<0.001), periodontitis (p=0.003), and malocclusion (p=0.011). The relationship between the masticatory performance score and the self-reported masticatory status was attenuated after controlling for confounding factors. Conclusion: The masticatory performance increased with age and decreased as the oral health status worsened. Using this chewing gum method partly, but not comprehensively, reflects masticatory performance. Therefore, various masticatory performance-related indexes should be employed to measure masticatory performance accurately.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.159-177
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• 2024

Purpose - The purpose of this study is to reveal the effect of a High Performance Work System(HWPS) on research performance. In addition, this study examines the mediation effect of Innovation Commitment(IC) and the moderated mediation effect of Perceived Organizational Support(POS), and seeks to reveal the antecedents and boundary variables that affect research performance. Design/methodology/approach - The level of analysis is at the individual level. A survey was collected from researchers at government-funded research institutes in the Daejeon and Sejong areas. 265 questionnaires were used in the final statistical analysis. Confirmatory factor analysis was performed using the AMOS 21. Correlation analysis, regression analysis, and bootstrapping by Process Macro were performed using the SPSS 19. Findings - As a result of the study, HWPS has a positive effect on IC, and IC has a positive effect on research performance. Through this results, it was found that IC mediates the relationship between the HPWS and research performance. In addition, POS positively moderated the mediating effect of HPWS on research performance through IC. Research implications or Originality - First, IC can be increased through a HPWS. Second, the effect of the HWPS on individual research performance through IC provides implications that the HWPS can be effectively applied not only to general companies but also to research organizations. Third, the boundary effect of POS was revealed. Fourth, research performance was measured through objective quantitative indicators rather than subjective.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.147-157
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• 2006

In this paper we consider alternate m machine scheduling problem in which each job having at most two eligible machines should be assigned with the objective of makespan minimization. For this problem, we propose a $O(m2^m)$ time rounding algorithm with performance ratio at most 1.5. For a little general problem where each job can be processed at most three machines, we prove that there cannot exist a polynomial time algorithm with performance ratio less than 1.5.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.888-891
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• 1996

The objective of a mixed H$_{2}$/H$_{\infty}$ controller of active suspension system is to achieve not only the general performance improvement(H$_{2}$) but also the worst case disturbance rejection(H$_{\infty}$). In this paper, a mixed H$_{2}$/H$_{\infty}$ controller for an active suspension system, comparing the performance with that of an H$_{2}$ controller and of an H$_{\infty}$ controller.ler.EX> controller.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.148-151
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• 2009

We consider the problem of optimizing the performance of a system with resources shared by non-cooperative users. The worst-cast ratio between the cost of a Nash equilibrium and the optimal cost, called Price of Anarchy, is investigated. It measures the performance degradation due to the users' selfish behavior. As the objective function of the optimization problem, we are concerned in a load balancing measure, which is different from that used in the previous works. Also we consider the Stackelberg scheduling which can assign a fraction of the users to resources while the remaining users are free to act in a selfish manner.