• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.4
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• pp.353-366
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• 2021

Objectives: An appropriate level of cost support is being proposed to maximize the participation rate. In addition, as the amount of support is highly concentrated at the level of the limit under the current level of supports, the level of cost support is low when the actual level of cost of measuring the working environment exceeds the limit. This paper describes the adjustment of an appropriate cost support rate. Methods: First, this paper analyzes the current cost support status using data from the KOSHA. Second, an alternative for adjusting the cost support rate is presented in consideration of the incentive aspect. Third, we present simulation results for the average cost support rate, the impact of each alternative on finance, and more. Fourth, the most desirable adjustment method is presented after comparing and analyzing the results of various alternatives. Results: In this paper, we present a new scale model. This model is a mixture of flat-rate, fixed rate, and subside cap. It is expected that the new model will not only facilitate participation in businesses with low measurement costs, but also have the effect of controlling measurement costs for institutions that incur greater costs. It is also expected that setting a cap will have the effect of considering government finances and inducing excessively costly institutions to reduce costs. Thus, the new model is likely to be superior to others. If the fourth plan is applied to new businesses and the fifth plan is applied to sustainable businesses, the average cost support rates will be 87.68 percent and 65.18 percent, respectively, and the needed finances will be 2.5 billion won, 18.8 billion won, and 21.3 billion won in total. Conclusions: It seems most desirable to introduce a new model that combines flat-rate, fixed-rate, and subsidy cap systems and achieve an appropriate cost support rate through this model.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.197-205
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• 2014

This study set out to develop a logistics rationalization model to reduce logistics costs including return route costs by using open information systems that overcame the limitations of the old closed logistics systems by the corporations and applying the principle of freight car sharing among them. In recent years, information infrastructure that can be easily shared by many such as information networks, however, One of the causes of rising logistics costs is high empty transfer rates on return routes after goods are transported from the distribution center of each company to consumption sites, It is propose to promote logistic efficiency and innovation. The study especially identified a logistics rationalization plan by examining and analyzing the stages of transportation on the circulation route of a distribution system from the distribution center of a corporation to consumption sites and the empty transfer rates and their current state.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.975-982
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• 2004

In current P2P concept, pure P2P and Hybrid P2P structures are used commonly. Gnutella and Ktella are forms of pure P2P. and forms of Hybrid P2P are innumerable. File searching models exist in these models. These models provide group management for file sharing, searching and indexing. The general file sharing model is good at maintaining connectivity. However, it is defective in group management. Therefore, this study approaches hierarchical structure in file sharing models through routing technique and backup system. This system was designed so that the user was able to maintain group efficiency and connection reliability in large-scale network.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.1
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• pp.73-82
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• 2006

Supply chain management (SCM) has been regarded as one of the most critical issues in the current business environment. Moreover, supply chain partnerships between suppliers and buyers in SCM have had a significant impact on supply chain performance. In this paper, we conduct a quantitative analysis for supplier-buyer's profit sharing and pricing policies based on supply chain partnerships. For this purpose, we assume that a two echelon supply chain with a single supplier and a single buyer is given and the buyer faces deterministic demand which is not only a function of buyer's selling price, but also strictly decreasing, concave, and twice differentiable function. Then we will prove the following. Firstly, without supply chain partnerships, there exist supplier and buyer's selling prices per unit such that their total profits are maximized, under the assumption that buyer's order quantity is exactly equal to the demand buyer faced. Secondly, buyer's selling price per unit which maximizes supply chain's total profit with supply chain partnerships is lower than buyer's selling price per unit which maximizes buyer's total profit without supply chain partnerships. Thirdly, given supplier's selling price per unit. buyer's total profit without supply chain part nerships is greater than that with supply chain partnerships, whereas the opposite case happens for supplier's total profit. Finally, there exists supplier's selling price per unit which makes the maximum total profits for both supplier and buyer with supply chain partnerships greater than those obtained for any given supplier's selling price per unit without supply chain partnerships.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.1-8
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• 2023

In this paper, we propose a training method of a recommendation learning model that analyzes the battlefield situation and recommends a suitable hypothesis for the current situation. The proposed learning model uses the preference determined by comparing the two hypotheses as a label data to learn which hypothesis best analyzes the current battlefield situation. Our model is based on Siamese neural network architecture which uses the same weights on two different input vectors. The model takes two hypotheses as an input, and learns the priority between two hypotheses while sharing the same weights in the twin network. In addition, a score is given to each hypothesis through the proposed post-processing ranking algorithm, and hypotheses with a high score can be recommended to the commander in charge.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.3
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• pp.107-116
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• 2005

The paper addresses modeling and analysis of a grid-connected photovoltaic generation system (PV system). PSCAD/EMTDC, an industry standard simulation tool for studying the transient behavior of electric power system and apparatus, is used to conduct all aspects of model implementation and to carry out extensive simulation study. This paper is aimed at sharing with the PSCAD/EMTDC user community our user-defined model for PV system applications, which is not yet available as a standard model within PSCAD/EMTDC. An equivalent circuit model of a solar cell has been used for modeling solar array. A series of parameters required for array modeling have been estimated from general specification data of a solar module. A PWM voltage source inverter (VSI) and its current control scheme have been implemented. A maximum power point tracking (MPPT) technique is employed for drawing the maximum available energy from the PV array. Comprehensive simulation results are presented to examine PV array behaviors and PV system control performance in response to irradiation changes. In addition, dynamic responses of PV array and system to network fault conditions are simulated and analysed.

• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.75-101
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• 2007

The current technological revolution pushes forward the innovation in the library information systems. This study proposes functional requirements and an architectural reference model of Semantic Library, recognized as a prototype of next-generation library information systems, that is a seamless convergence of the library information systems and the Internet technologies. Semantic Library can realize semantic interoperability and integration based on ontology and metadata, and also renovate information services for users with openness, sharing, participation and collaboration. Semantic Library will be effectively implemented by means of service-oriented architecture and the logical structure of FRBR. In this study, a reference model of Semantic Library consisting of 6 horizontal layers and 3 vertical elements is presented as a next-generation model of library information systems.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.301-312
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• 2017

Quality evaluation and control represent increasingly important concerns for construction quality management. There is an evident need for a standard data model to be used as the basis for computer-aided quality management. This study focuses on how to realize evaluation of construction quality based on BIM and database technology. In this paper, the reinforced concrete main structure is taken as an example, and the BP neural network evaluation model is established by inquiring current construction quality acceptance specification and evaluation standard. Furthermore, IFC standard is extended to integrate quality evaluation information and realize the mapping of evaluation information in BIM model, contributing to the visualization and transfer sharing of evaluation information. Furthermore, the conceptual entity model is designed to build quality evaluation database, and this paper select MySQL workbench system to achieve the establishment of the database. This study is organized to realize the requirement of visualization and data integration on construction quality evaluation which makes it more effective, convenient, intuitive, easy to find quality problems and provide more comprehensive and reliable data for the quality management of construction enterprises and official construction administratiors.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.39-61
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• 2021

This study aims to examine the effect of the Mindfulness for YouTube users. Recently, video sharing platforms have grown rapidly with YouTube, and YouTube has grown rapidly despite the emergence of various video sharing platforms. Which YouTube represents these changes, provides an environment where anyone can make and distribute videos. And through these advantages, many viewers are coming in and more creators are making videos. The purpose of this study is to understand the influence factors of YouTube service in Korea and to clarify the causal relationship between the factors that affect the continued use intention through usefulness, confirmation, and satisfaction. For this reason, presented a research model that applied key variables of the Mindfulness theory, which emphasized that users should be aware of their emotions. In order to empirical verification the research model of this study, a questionnaire was conducted for university students and general office workers who had experience using YouTube. As a result, first decentered attention has been shown that has no positive effect on perceived usefulness and confirmation. Second, non-judgmental acceptance has benn shown that has a postitive effect on perceived usefulness and confirmation. Third, current self-perception has been shown that has no positive effect on perceived usefulness and confirmation. Fourth, concentration has been shown that has no positive effect on perceived usefulness and confirmation. And Mindfulness has been shown that has a positive effect on satisfaction and perceived usefulness. Through this, it is important to use YouTube to use what users feel is important, and it is important to determine whether the video is helpful to them when accepting content and make them expect the next video.