• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.105-121
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• 2005

To realize a ubiquitous logistics management system using the smart object of Electronic Product Code(EPC) enabled RFID tag, the design and management of RFID Information Service is very important. RFID Information Service searches, transfers and responds to the other's PML request, but Physical Markup Language (PML) data management between trading system elements has issues of standardization of PML data description and processing, and problems of data traffic and communication time overload because of the innate distributed characteristics. As a complementary study, this research analyzes the usage patterns and data types of PML. On that analysis we provide a design of the distributed RFID Information Service architecture of PML data management that is using DB middleware. Standalone and Integrated type of RFID IS were proposed.

• The Journal of Information Systems
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• v.19 no.1
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• pp.79-96
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• 2010

The organizations in the competitive business environment are under pressure of handling internal management processes as well as external supply chain issues. In addition, the paradigm of supply chain management (SCM) has been shifted from static to dynamic problems. For the efficient SCM, organizations should be a RTE (Real Time Enterprises) that views entire supply chains as a single entity. In this paper, the agent system that makes RTE and dynamic supply chains possible is developed. Then, the developed agent system is verified in the TAC SCM(Trading Agent Competition Supply Chain Management) experimental environment and a dashboard is also developed for monitoring management activities of supply chains. The contributions of this paper are as followings. First, unlike the previous agent systems, the suggested agent system in this paper provides autonomy and scalability using SOA. Second, this suggested model for dynamic environment can be applied for the development of software supporting a SCM.

• Journal of Digital Contents Society
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• v.15 no.1
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• pp.121-128
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• 2014

SSE-CMM for security engineering, engineering, assurance, risk is divided into three elements of the process maturity assessment model and the level of information security presented. Maturity measurement of privacy, vulnerability diagnosis and risk analysis methodologies is used in practical field for present a comprehensive conclusion. The common cyber services are internet banking, mobile banking, telephone banking and the like. Transaction structure, a kind of cyber-banking system, information security maturity of the existing measurement methodologies for research purposes, vulnerability diagnosis and risk analysis methodologies to be used in practical field present a comprehensive conclusion. To ensure safety and convenience for the user, convenient to deal with cyber environment is the key to the activation of cyber trading. Particularly by measuring the maturity of cyber banking system to ensure the safety of the practice field much effects are expected as a result.

• Journal of Navigation and Port Research
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• v.29 no.6 s.102
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• pp.567-572
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• 2005

Trade between nations has been globalized since establishing the WTO(World Trade Organization). By lowering trading barriers under the WTO's system, trade in goods has been gradually increased It requires global logistic system that transports goods in between nations. To save cost of product, cargo of product is containerized and container ships to carry container cargo is going to be bigger: In the market, there are many vendors to provide artificial intelligent modules to operate container terminal. In order to integrate automated container terminal system easily and successfully, this thesis proposes high-level XML/ JMS( eXtensive Markup Language/Java Message Service) communication model and multi-agent based system architecture to share knowledges, solve problems, and active objectives by cooperating between autonomous and intelligent agents that are developed by 3rd party companies in the market. This thesis analyzed current situation of advanced automated container terminal with case studies on implemented systems and difficulties to develop automated container terminal system, reviewed technologies of intelligent agent, communication and automation that unmaned automated container terminal is required.

• International Journal of Human Ecology
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• v.11 no.1
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• pp.109-119
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• 2010

Modernization of cities and housing in Malaysia is a reflection of the history of the establishment of colonial trading ports for worldwide maritime trade and exchange. In cosmopolitan cities, new housing typology appeared from the influence of various ethnic immigrants and with the fusion of traditional Malay housing characteristics. This study is to focus on classifying the housing typologies of Malaysia which were formed through the modernization process of cities. The typologies of modern housing in Malaysia can be classified into two categories. The first category is the 'transformation of traditional housing'. The representative typology of this group is the ubiquitous shophouse. The shophouse was originally brought in by the Chinese immigrants from the south coast of China and transformed into the Malaysian urbanscape. The other typology is a detached-house known as the bungalo, which was the housing style combining the Malay traditional timber house and European palazzo. The second category is the 'modern urban housing typology'. Modern urbanization after the independence from the British in 1957 required the maximum utilization of land. To accommodate new social and economic needs, the new typologies were developed in the form of medium-density terrace houses (row houses) and high-density apartment. In the suburban areas, the British terrace house was adopted and developed into unique Malaysian terrace house and semi-detached house based on the British system of land sub division. In premium area of the city, luxurious housing type in the form of high-end condominium is one of the popular housing for upper middle-class and high-class society.

• KIEAE Journal
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• v.17 no.3
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• pp.75-81
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• 2017

Purpose: The energy consumption of apartment units is affected by the lifestyle of the residents rather than system technology. In this study the numerical analysis of assumed energy consumption correlation factors with arbitrary value due to uncertainty. It is intended to be used as a simulation correction value which can be utilized as a predicted value of actual energy usage. The correction value of the simulation is set in the developed form of the existing process that derives the actual usage amount. The simulation results used in the existing evaluation system are used to maintain the useful value as the current system evaluation scale and predict the actual capacity. Method: The method of the study is to statistically analyze the data frames of all complexes capable of collecting the annual energy usage and to reconstruct the population by adding the variables that are expected to be correlated. Repeat the data frame configuration with variables that are assumed to be highly correlated with energy use levels. Determine whether there is correlation or not. The intensity of the external characteristics of the building equipment related to the energy consumption is presented as the quantitative value. Result: The correlation between electricity consumption and trading price since 2010 is analyzed as (Correlation coefficient 0.82). These results are higher than (Correlation coefficient 0.79), which is the correlation between residential area and trading price. This paper signifies the starting point of the methodology that broadens the field of view of verification of simulation feasibility limited to the prediction technique focused on the simulation tool and the element technology scope.The diversified phenomenon reproduction method develops the existing energy simulation method.It can be completed with a simulation methodology that can infer actual energy consumption.

• The Journal of Society for e-Business Studies
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• v.8 no.2
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• pp.63-76
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• 2003

The fundamental technology to the b2b e-commerce framework is Registry. Although Registries have developed, it is yet difficult to apply in actual e-business . That is, the e-business information was stored in physically and/or logically distributed and heterogeneous Registries. And Registry uses the keyword-based search to discovery the information stored. But, the keyword-based search technology can't provide the discovery the business information necessary for parties and trading partners. As spreading the understand of this problem, it requires the technologies for the integration of distributed and various Registries and the systematic definition and intelligent discovery of the e-business information. In this paper we propose the architecture of intelligent and integrated e-business registry system for solving these problems . This system composed of the Registry Integration Query Manager for integrating various registries and the Intelligent Registry Agent providing the systematic organization and discovery of e-business information.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.6
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• pp.112-122
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• 2009

Payment of Forest Landscape Service (PFLS) is based on the value of landscape conservation and is a positive forest policy inducing the owners of mountains to improve environmental service quality with economic incentives. The purpose of this study is to test the feasibility of PFLS and find out the elements related to PFLS such as associated statutes, target applications, eligible owner's requirements, and applicable environmental services. Research sites were selected in designated reserved forests by law and surveys were carried out with 28 professional forestry engineers and 10 owners of reserved forests located in Chungnam Province in November, 2008. As a result, the owners are willing to participate pilot-project of PFLS if they could have tax incentives. Preferred activities in their forestry are eco-tourism and carbon emission trading as PFLS business model. Although they expect low economic benefit from the PFLS, respondents answered introducing PFLS will give good opportunities for owners of a reserved forest to enhance willingness to manage their forestry properly for the landscape conservation. In this study, PFLS evaluation indicators and policy directions are established and recommends the strategies to cope with changing needs of forestry conservation by inducing the owners' active participation in the sustainable forest landscape management.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.5
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• pp.74-86
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• 2015

The purpose of this study was to deduce the landscape evaluation indices that can be applied from the preparation for the registration of major national farm/fishery heritages to post-management. For this purpose, the Delphi survey was performed on experts. From August to November in 2014, the primary open survey, secondary open survey, and tertiary closed survey were performed to gather opinions from 28 experts, 25 experts, and 29 experts, respectively. As a result, the landscape evaluation indices for farm/fishery heritage consisted of five areas of evaluation, ten items of evaluation, and 40 indices of evaluation. The areas of evaluation were rurality, authenticity, aesthetics, tourism potentials, and locality. Rurality was classified into rurality of farm/fishery towns and nostalgia. Authenticity was classified into objective authenticity and existential authenticity. Aesthetics was classified into attractiveness and harmony. Tourism potentials were classified into value of resources and value of usability. Locality was divided into physical originality and cultural identity. The study made the following findings: first, the general grounds of farm/fishery landscape evaluation cannot be applied when evaluating the quality of landscapes of farm/fishery heritage, as their value as a cultural heritage should be considered. Second, the new indices valued emotional factors in addition to the physical factors considered by the existing farm/fishery landscapes. The new indices involved a more expanded concept of landscapes as it also considers everyday or temporary activities, including the farm/fishery activities of local people or participation in festivals and experience programs. Third, farm/fishery heritage focuses on the lives of local people, as it involves both the synchronic and the diachronic perspectives to see what is currently visible and what is no longer visible. This brings into consideration not only the farms and the natural environments but also their relationships with the villages, especially the residential areas. Finally, the indices reflected both the farm/fishery heritage's value as cultural heritage and its value for tourism. They derived temporary and dynamic landscapes, including the trading activities of local specialty markets in relation to the production landscapes. However, further studies should be conducted as this study could not rate the relative importance of indices or compare the total scores of landscapes without the weight of each item.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.