• International journal of advanced smart convergence
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• v.13 no.2
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• pp.16-24
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• 2024

With an increase in the relevance of next-generation integrated networking environments, the need to effectively utilize advanced networking techniques also increases. Specifically, integrating Software-Defined Networking (SDN) with Multi-access Edge Computing (MEC) is critical for enhancing network flexibility and addressing challenges such as security vulnerabilities and complex network management. SDN enhances operational flexibility by separating the control and data planes, introducing management complexities. This paper proposes a reinforcement learning-based network path optimization strategy within SDN environments to maximize performance, minimize latency, and optimize resource usage in MEC settings. The proposed Enhanced Proximal Policy Optimization (PPO)-based scheme effectively selects optimal routing paths in dynamic conditions, reducing average delay times to about 60 ms and lowering energy consumption. As the proposed method outperforms conventional schemes, it poses significant practical applications.

• Smart Media Journal
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• v.12 no.11
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• pp.113-124
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• 2023

With the advent of 5G and B5G (Beyond 5G) networks, network virtualization technology that can overcome the limitations of existing networks is attracting attention. The purpose of network virtualization is to provide solutions for efficient network resource utilization and various services. Existing heuristic-based VNE (Virtual Network Embedding) techniques have been studied, but the flexibility is limited. Therefore, in this paper, we propose a GNN-based network slicing classification scheme to meet various service requirements and a RL-based VNE scheme for optimal resource allocation. The proposed method performs optimal VNE using an Actor-Critic network. Finally, to evaluate the performance of the proposed technique, we compare it with Node Rank, MCST-VNE, and GCN-VNE techniques. Through performance analysis, it was shown that the GNN and RL-based VNE techniques are better than the existing techniques in terms of acceptance rate and resource efficiency.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.169-177
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• 2024

Industrial Wireless Sensor Network (IWSN) is a key feature of Industrial IoT that enables industrial automation through process monitoring and control by connecting industrial equipment such as sensors, robots, and machines wirelessly, and must support the strict requirements of modern industrial environments such as real-time, reliability, and energy efficiency. To achieve these goals, IWSN uses reliable communication methods such as multipath routing, fixed redundant resource allocation, and non-contention-based scheduling. However, the issue of wasting redundant resources that are not utilized for communication degrades not only the efficiency of limited radio resources but also the energy efficiency. In this paper, we propose a scheme that utilizes reinforcement learning in communication scheduling to periodically identify unused wireless resources and reallocate them to save energy consumption of the entire industrial network. The experimental performance evaluation shows that the proposed approach achieves about 30% improvement of resource efficiency in scheduling compared to the existing method while supporting high reliability. In addition, the energy efficiency and latency are improbed by more than 21% and 38%, respectively, by reducing unnecessary communication.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.145-151
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• 2024

Road sign support systems are not usually well managed because bridges and pavement have budget and maintenance priority while the sign boards and sign supports are considered as miscellaneous items. The authors of this paper suggested the implementation of simplified machine learning algorithms for asset risk management in highway sign support systems. By harnessing historical and real-time data, machine learning models can forecast potential vulnerabilities, enabling early intervention and proactive maintenance protocols. The raw data were collected from the Connecticut Department of Transportation (CTDOT) asset management database that includes asset ages, repair history, installation and repair costs, and other administrative information. While there are many advanced and complicated structural deterioration prediction models, a simple deterioration curve is assumed, and prediction model has been developed using machine learning algorithm to determine the risk assessment and prediction. The integration of simplified machine learning in asset risk management for highway sign support systems not only enables predictive maintenance but also optimizes resource allocation. This approach ensures that decision-makers are not inundated with excessive detailed information, making it particularly practical for industry application.

• The Journal of Korean Association of Computer Education
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• v.20 no.1
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• pp.87-97
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• 2017

Recently, much research has been done on the turnover and retirement intentions of the organization members as many companies recognize the negative impact of the human resource outflow on the organization. However, most of the studies are conducted in the form of questionnaires, and there is still a lack of studies on the turnover and retirement intentions based on the work life data. In this study, we analyzed the factors affecting the retirement of employees based on the work life profile, and created a retirement prediction model using the machine learning method. As a result, we could identify various factors that were not covered in previous researches. In addition, we have established a basis for research that can provide a solution for the problem of human resource outflow by generating a good performance retirement prediction model.

• Journal of Korean Library and Information Science Society
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• v.32 no.4
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• pp.331-360
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• 2001

School Libraries are facilities which support teachers and students in their teaching and learning activities and help to fulfil the school curriculum. Recently the Ministry of Education & Human Resources and Development is emphasizing ‘self learning’and it means that the problem solving ability of students can be improved through resource based learning & self learning. The resource based learning is closely connected with school libraries. School libraries are basic organization among all kind of libraries in all parts of th country and they can not develop without the systematic support of the government. The school libraries are just nominal because education in schools is centered on entrance examination and the government is indifferent to them. Therefore, it is urgent to constitute the related regulations and systems to rescue school libraries. The present school libraries laws should be revised toward the direction of effectiveness and it is possible to revise them after School Library Promotion Acts are constituted in public. All kinds of system and organization can develop only when they attach great importance to people Even though we constitute good laws and have good systems, they can not develop without the support of administrative organizations. They can develop when the administrative organizations have the strong will to develop them and are affectionately interested with them. The development of school libraries are under the control of strong interest and will of the people who are in charge of the systems and apply the related regulations.

• The Journal of Information Systems
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• v.30 no.3
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• pp.93-112
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• 2021

Purpose Recently, many organizations are actively adopting enterprise architecture (EA) as a methodology to manage IT assets and build IT-based business system. This study intended to empirically examine how the role of EA operating unit and utilization capability of organizational members impact on system performance at the post-adoption stage. A balanced score card (BSC) is being used as a framework for a company's key performance indicator (KPI). Design/methodology/approach This study tried to investigate the causal relationship between the four perspectives of the balanced scorecard as an influencing factor of the introduction of the Enterprise Resource Planning (ERP) on the financial value. In particular, the mediating effect between the customer's point of view and the business process point of view was investigated between the learning growth point of view and the financial point of view, and the interaction effect (regulating effect) of strategic linkage in the system introduction process was investigated. Findings The results of the study were first, that the organizational learning and growth perspective had a positive effect on the customer perspective, business process, and financial perspective. In addition, the customer perspective and the process perspective also had a positive influence on the financial perspective. Second, between the learning growth and financial perspectives, the customer perspective and the process perspective showed a partial mediating effect. Third, as for strategic linkage, the interaction effect between the customer perspective, the learning growth perspective, and the process perspective and the financial perspective was not significant. The results of this study are expected to provide a framework for performance evaluation to organizations that have introduced ERP systems.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.205-211
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• 2024

Effective warehouse management requires advanced resource planning to optimize profits and space. Robots offer a promising solution, but their effectiveness relies on embedded artificial intelligence. Multi-agent reinforcement learning (MARL) enhances robot intelligence in these environments. This study explores various MARL algorithms using the Multi-Robot Warehouse Environment (RWARE) to determine their suitability for warehouse resource planning. Our findings show that cooperative MARL is essential for effective warehouse management. IA2C outperforms MAA2C and VDA2C on smaller maps, while VDA2C excels on larger maps. IA2C's decentralized approach, focusing on cooperation over collaboration, allows for higher reward collection in smaller environments. However, as map size increases, reward collection decreases due to the need for extensive exploration. This study highlights the importance of selecting the appropriate MARL algorithm based on the specific warehouse environment's requirements and scale.

• International Journal of Contents
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• v.10 no.3
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• pp.26-34
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• 2014

Mobile learning is a practical learning method for busy adult learners because the mobility of digital devices can overcome the drawbacks of e-learning. However, research is strongly lacking in the theoretical exploration of mobile learning effects and functions and its empirical research. Moreover, the research of learning characteristics and learners' requirements must be considered before applying and disseminating mobile learning into the educational field. To address this shortcoming, this study conducted an online survey with 1,542 officers of the Ministry of Health and Welfare Affairs (MHWA) regarding learner recognition to mobile learning. The analysis of learners' attitudes toward mobile learning, based on age and position, indicated that subordinate workers appeared to place more value on mobile learning. Many participants preferred mobile learning because of its mobility and the effectiveness of anywhere and anytime. However, some participants continue to misunderstand mobile learning and its necessity. Therefore, consideration of learning effectiveness, the form of the content, and learner-centered learning must be reviewed in advance. This study could lead to practical implications of mobile learning.

• Research in Mathematical Education
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• v.19 no.1
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• pp.81-88
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• 2015

This study used a posttest control group design and to find out differences between students' self-regulated learning strategies in traditional and non-traditional classroom. To this end, 131 first year university students within the experimental and control groups took part in the study. While ICT-based approach was used as the main medium of instruction in the experimental group, in the control group the paper-based traditional method was used. A survey adapted from Davaanyam [Davaanyam, T. (2013). The structural relationships among Mongolian students' attitudes toward mathematics, motivational beliefs, self-regulated learning strategies, and mathematics achievement. Ph. D. Dissertation. Jeonju, Jeonbuk, Korea: Chonbuk National Unversity.] was used to gather the data. The results of the study indicated a significant difference between the control and experimental groups in regard with their self-regulated learning. That is to say, the experimental group taught through ICT tools acquired higher levels of self-regulation as compared with the control group instructed through the traditional teaching method.