• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.4
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• pp.187-200
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• 2012

Korean government imposed a free education policy called "Nuri-Curriculum program" available for children under age of 5 ever since march 2012 due to consolidation of national responsibility. The policy presents providing of cost-free and high-quality education/childcare services to people. Nuri program services will expand to applied age of 3-5 children from march 2013. however, because to gain successful outcomes from the program requires well-trained professional educator, it is necessary to standardize education infrastructure in order to improve employees' professionality. Therefore study suggests followings: fisrt, establishment of desirable role-model. second, unification of the training process. third, unifications of administration system and qualification standard. fourth, readjust curriculums to focus on basic knowledge of human life. fifth, clarify the duty of educator and systematize curriculums. sixth, consolidate base criteria.

• Journal of the Economic Geographical Society of Korea
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• v.4 no.2
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• pp.79-96
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• 2001

This paper introduces a new type of industrial cluster developed at the CBD of Seoul. Conventionally, clusters are said to be consisted of hi-tech, often If activities, manufacturing industries or artisan craft industries with increasing vertical integration and performance usually supported by venture capitals and favorable business infrastructure, not to mention governments', be it central or local, incentive plans. The study area, Cheonggyechon region has long been a traditional CBD frame of Seoul, Korea, being troubled by deterioration, traffic jams, and environmental degradation as most inner cities experience. Recently. this region has transformed to the most dynamic and productive area not by IT industries but by apparel and fashion activities. The study of the developmental trajectory and key characteristics for this kind of industrial cluster can give us insight both for the transition of inner city and for the cluster theory. This Paper firstly briefly Profiles the growth of the Cheonggyechon region over the past decade. It then shows the current spatial and business structure of the new industrial cluster, focusing on the fact that transactions costs are reduced, the creation and flow of information improves. and the local institutions are prone to be most responsive to the new cluster's specialized needs. The third section presents the key components of the customized production-distribution-shopping cluster development process, emphasizing the localized networking. social capital, spontaneous institutionalization of associational economic climate, and cultural economy based on place-specific inertia. The paper concludes with some comments about the prospects and perils of the new industrial cluster of Seoul.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.153-173
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• 2013

The ontology has been gaining increasing interests by recent arise of the semantic web and related technologies. The focus is mostly on inference query processing that requires high-level techniques for storage and searching ontologies efficiently, and it has been actively studied in the area of semantic-based searching. W3C's recommendation is to use RDFS and OWL for representing ontologies. However memory-based editors, inference engines, and triple storages all store ontology as a simple set of triplets. Naturally the performance is limited, especially when a large-scale ontology needs to be processed. A variety of researches on proposing algorithms for efficient inference query processing has been conducted, and many of them are based on using proven relational database technology. However, none of them had been successful in obtaining the complete set of inference results which reflects the five characteristics of the ontology properties. In this paper, we propose a new index structure called hyper cube index to efficiently process inference queries. Our approach is based on an intuition that an index can speed up the query processing when extensive inferencing is required.

• The KIPS Transactions:PartD
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• v.17D no.2
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• pp.157-166
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• 2010

More recently, RFID (Radio Frequency Identification) systems have begun to find greater use in various industrial fields. The use of RFID system in these application domains has been promoted by efforts to develop the RFID tags which are low in cost, small in size, and high in performance. The RFID applications enable the real-time capture and update of RFID tag information, while simultaneously allowing business process change through real-time alerting and alarms. These be developed to monitor person or objects with RFID tags in a place and to provide visibility and traceability of the seamless flows of RFID tags. In this time, the RFID readers should be placed in diverse locations, the RFID flows between these readers can be tested based on various scenarios. However, due to the high cost of RFID readers, it may be difficult to prepare the similar environment equipped with RFID read/write devices. In this paper, we propose a simulator to allow RFID application testing without installing physical devices. It can model the RFID deployment environment, place various RFID readers and sensors on this model, and move the RFID tags through the business processes. This simulator can improve the software development productivity by accurately testing RFID middleware and applications. In addition, when data security cannot be ensured by any fault, it can decide where the problem is occurred between RFID hardware and middleware.

• Journal of Service Research and Studies
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• v.10 no.2
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• pp.17-29
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• 2020

This study was performed to derive a modern service management model reflecting the philosophy of the new business administration. Service management as the modern business administration should be faithful to the spirit of modernity. In addition, service management must be faithful to the essence of service in service economy era. And since modern management is to manage organizations those are the central organizations of human society, it must be managed according to the common principles of the world. Management that satisfies these three management philosophy conditions is defined as modern service management. In this study, we analyzed that the existing service management framework does not meet these standards of modern management and derived an improved modern service management model. The modern service management model must be a management model that reflects the essence of intangible goods called service, it must be a management framework that reflects the modern spirit, and it must be a management model that reflects the common principles of the world required by the central organization of the modern economic society. Therefore, this study analyzed the modern spirit in addition to the service essence and the common principle of the world analyzed in the previous study, and presented a modern service management model with these three requirements. Also, examples of modern service management were presented. This study is a conceptual model, and analytical research is needed to demonstrate that this management model can consistently produce excellent management performance by strengthening empirical studies in the future.

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.463-474
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• 2009

To analyze multidimensional data conveniently and efficiently, OLAP (On-Line Analytical Processing) systems or e-business are widely using views in a horizontal form to represent measurement values over multiple dimensions. These views can be stored as materialized views derived from several sources in order to support accesses to the integrated data. The horizontal views can provide effective accesses to complex queries of OLAP or e-business. However, we have a problem of occurring maintenance of the horizontal views since data sources are distributed over remote sites. We need a method that propagates the changes of source tables to the corresponding horizontal views. In this paper, we address incremental maintenance of horizontal views that makes it possible to reflect the changes of source tables efficiently. We first propose an overall framework that processes queries over horizontal views transformed from source tables in a vertical form. Under the proposed framework, we propagate the change of vertical tables to the corresponding horizontal views. In order to execute this view maintenance process efficiently, we keep every change of vertical tables in a differential file and then modify the horizontal views with the differential file. Because the differential file is represented as a vertical form, its tuples should be converted to those in a horizontal form to apply them to the out-of-date horizontal view. With this mechanism, horizontal views can be efficiently refreshed with the changes in a differential file without accessing source tables. Experimental results show that the proposed method improves average performance by 1.2$\sim$5.0 times over the existing methods.

• Management & Information Systems Review
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• v.38 no.3
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• pp.137-150
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• 2019

As job market squeezes and more institutions have been requiring NCS(National Competency Standards) based recruitment, the importance of NCS has been growing. Among the 10 domains of NCS, the most relevant one with task processing and organizational performance filed is 'task processing capability group', which is becoming more important with the advent of the fourth industrial revolution era. The purpose of this study is to investigate the effect of college students' task processing capability group on their career outcome expectation and career preparation behavior. In this study, we set up a process model to comprehend the effect of college students' task processing capability group on career outcome expectation and career preparation behavior based on social cognitive career theory. Empirical analysis showed that task processing capability group(problem-solving capability, information capability, resource management capability, organizational capability) positively influenced college students' career outcome expectation and career preparation behavior for employment. However, the impact of technical capability on career outcome expectation and career preparation behavior was not explained. In order to strengthen the task processing capability group of college students, not only university-level efforts, but also college and faculty's efforts should be accompanied. Other academic and practical implications are discussed.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.29-48
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• 2019

Recently, product design innovation to improve user experience has been perceived as a core element of enterprise competitiveness due to the fierce market competition and decrease of the technological gap between companies, but there is insufficient services to support the product experience evaluation of small and medium-sized companies (SMCs). The aim of this study is to develop a web-based product user experience evaluation and certification system supporting product design practices for SMCs. For system interface design, we conducted systematic functional requirement elicitation methods such as user survey, workflow analysis, user task definition, and function definition. Then main functions, information structure, navigation method, and detailed graphic user interfaces were developed with consideration of user interactions and requirements. In particular, it provides the databases for evaluation efficiency to support the evaluation process above a certain level of performance and efficiency, and knowledge databases to utilize in the evaluation and product design improvement. With help of the developed service platform, It is expected that the service platform would enhance SMCs' product development capability with regard to the user experience evaluation by connecting the consulting firms with SMCs.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.93-106
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• 2021

Many recent studies on deep learning-based road crack detection have shown significantly more improved performances than previous works using algorithm-based conventional approaches. However, many deep learning-based studies are still focused on classifying the types of cracks. The classification of crack types is highly anticipated in that it can improve the crack detection process, which is currently relying on manual intervention. However, it is essential to calculate the severity of the cracks as well as identifying the type of cracks in actual pavement maintenance planning, but studies related to road crack detection have not progressed enough to automated calculation of the severity of cracks. In order to calculate the severity of the crack, the type of crack and the area of the crack in the image must be identified together. This study deals with a method of using Mobilenet-SSD that is deep learning-based object detection techniques to effectively automate the simultaneous detection of crack types and crack areas. To improve the accuracy of object-detection for road cracks, several experiments were conducted to combine the U-Net for automatic segmentation of input image and object-detection model, and the results were summarized. As a result, image masking with U-Net is able to maximize object-detection performance with 0.9315 mAP value. While referring the results of this study, it is expected that the automation of the crack detection functionality on pave management system can be further enhanced.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.