• Journal of Animal Environmental Science
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• v.18 no.2
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• pp.91-94
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• 2012

This study was conducted to develop an algorithm for determination of abnormal body temperature in piglets through skin and core temperature database at normal condition. 5 piglets (mean BW : 46 kg) were employed for the experiment. They were adapted in the individual metabolism cage set at $22.5{\pm}2.0^{\circ}C$ of room temperature for 2 weeks before the measurement of body temperature. Ear, neck, head and subcutaneous neck temperature (as core temperature) of piglets were measured for every 1 minute during 30 consecutive days through 1mm k-type thermocouple wire and NI-devices (National Instruments Corporation, Austin, Texas, USA). Body temperature data were accumulated and integrated into the 1 day unit. Change of daily mean skin and core body temperatures in piglets were lowest at around 06:00, highest at around 14:00 and gradually decreased until the day after 06:00. Each skin temperatures were varied with the measuring site and largely depended on the room temperature changes. Established database of skin and core body temperature in piglets through this study can be applied to develop an algorithm for monitoring and determining the abnormal condition of animal by using radio frequency identification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12B
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• pp.1444-1451
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• 2009

This paper first proposes diverse C determining models in the Q algorithm which is proposed in the EPCglobal C1 Gen 2 standard and then compares and analyzes its performance. EPCglobal C1 Gen 2 standard proposes the slot-count (Q) selection algorithm for multiple tag identification environment, but there is no such definition for the C value which modifies the Q value depending on collision or no reply. During the tag anti-collision process, the Q algorithm adds C to the Q when there is a collision and reduces the Q by C when there is no reply. The modified Q value updates new slot-counts for tags which determines the tag identification speed, so the C value is an important factor. However, many researches only intend to increase the tag identification speed by proposing a new method or modifying the Q algorithm without any research about the C value. This paper suggests diverse C models which satisfies the EPCglobal C1 Gen 2 and analyzes their performance in the multi tag identification environment. The result of this paper can be used as an index for future researches on EPCglobal C1 Gen 2 C models and multiple tag identification performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.277-280
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• 2016

Currently, systems for finding missing children are composed of using communication between a QR code and RFID chip, as the use of a smartphone. However, the current systems for finding missing children have limitations in that children can only be found if there are people in the surrounding area; there is an economic burden on parents required to purchase a smartphone for their children; along with difficulties in finding the missing children without the assistance of those in the surrounding area in critical situations such as a kidnapping, due to the limited duration of the battery life. In order to solve such problems, approaches need to be made from two perspectives: having someone in the surrounding area; and absence of anyone in the surrounding area. This thesis is centered on the development of a IoT (Internet of Things) system for finding missing children that combines two methods, namely, the method of finding missing children without a guardian in the surrounding area -within the limited space in which AP is installed by using a beacon and open source hardware being highlighted as the IoT technology - and the method of finding missing children with the smartphone application in which each individual becomes the Access Point (AP). The Main purpose is to provide accurate information of missing children's location for the 2situations and it is found that the accuracy of smartphones APP is 97.7% and security device AP is 91.1%.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.869-875
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• 2009

Safety is a big issue in the construction sites. For safe and secure management, tracking locations of construction resources such as labors, materials, machineries, vehicles and so on is important. The materials, machineries and vehicles could be controlled by computer, whereas the movement of labors does not have fixed pattern. So, the location and movement of labors need to be monitored continuously for safety. In general, Global Positioning System(GPS) is an opt solution to obtain the location information in outside environments. But it cannot be used for indoor locations as it requires a clear Line-Of-Sight(LOS) to satellites Therefore, indoor location monitoring system could be a convenient alternative for environments such as tunnel and indoor building construction sites. This paper presents a case study to investigate feasibility of Wi-Fi based indoor location monitoring system in construction site. The system is developed by using fingerprint map of gathering Received Signal Strength Indication(RSSI) from each Access Point(AP). The signal information is gathered by Radio Frequency Identification (RFID) tags, which are attached on a helmet of labors to track their locations, and is sent to server computer. Experiments were conducted in a shield tunnel construction site at Guangzhou, China. This study consists of three phases as follows: First, we have a tracking test in entrance area of tunnel construction site. This experiment was performed to find the effective geometry of APs installation. The geometry of APs installation was changed for finding effective locations, and the experiment was performed using one and more tags. Second, APs were separated into two groups, and they were connected with LAN cable in tunnel construction site. The purpose of this experiment was to check the validity of group separating strategy. One group was installed around the entrance and the other one was installed inside the tunnel. Finally, we installed the system inner area of tunnel, boring machine area, and checked the performance with varying conditions (the presence of obstacles such as train, worker, and so on). Accuracy of this study was calculated from the data, which was collected at some known points. Experimental results showed that WiFi-based indoor location system has a level of accuracy of a few meters in tunnel construction site. From the results, it is inferred that the location tracking system can track the approximate location of labors in the construction site. It is able to alert the labors when they are closer to dangerous zones like poisonous region or cave-in..

• Journal of Distribution Science
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• v.8 no.3
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• pp.37-47
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• 2010

CRM refers to the operating activities that always maintain and promote good relationship with customers to ultimately maximize the company's profits by understanding the value of customers to meet their demands, establishing a strategy which may maximize the Life Time Value and successfully operating the business by integrating the customer management processes. In our country, many big businesses are introducing CRM initiatively to use it in marketing strategy however, most medium and small sized companies do not understand CRM clearly or they feel difficult to introduce it due to huge investment needed. This study is intended to present CRM promotion strategy and activities plan fit for the medium and small sized companies by analyzing the success factors of the leading companies those have already executed CRM by surveying the precedents to make the distributors out of the industries have close relation with consumers to overcome their weakness in scale and strengthen their competitiveness in such a rapidly changing and fiercely competing market. There are 5 stages to build CRM such as the recognition of the needs of CRM establishment, the establishment of CRM integrated database, the establishment of customer analysis and marketing strategy through data mining, the practical use of customer analysis through data mining and the implementation of response analysis and close loop process. Through the case study of leading companies, CRM is needed in types of businesses where the companies constantly contact their customers. To meet their needs, they assertively analyze their customer information. Through this, they develop their own CRM programs personalized for their customers to provide high quality service products. For customers helping them make profits, the VIP marketing strategy is conducted to keep the customers from breaking their relationships with the companies. Through continuous management, CRM should be executed. In other words, through customer segmentation, the profitability for the customers should be maximized. The maximization of the profitability for the customers is the key to CRM. These are the success factors of the CRM of the distributors in Korea. Firstly, the top management's will power for CS management is needed. Secondly, the culture across the company should be made to respect the customers. Thirdly, specialized customer management and CRM workers should be trained. Fourthly, CRM behaviors should be developed for the whole staff members. Fifthly, CRM should be carried out through systematic cooperation between related departments. To make use of the case study for CRM, the company should understand the customer and establish customer management programs to set the optimal CRM strategy and continuously pursue it according to a long-term plan. For this, according to collected information and customer data, customers should be segmented and the responsive customer system should be designed according to the differentiated strategy according to the class of the customers. In terms of the future CRM, integrated CRM is essential where the customer information gathers together in one place. As the degree of customers' expectation increases a lot, the effective way to meet the customers' expectation should be pursued. As the IT technology improved rapidly, RFID (Radio Frequency Identification) appears. On a real-time basis, information about products and customers is obtained massively in a very short time. A strategy for successful CRM promotion should be improving the organizations in charge of contacting customers, re-planning the customer management processes and establishing the integrated system with the marketing strategy to keep good relation with the customers according to a long-term plan and a proper method suitable to the market conditions and run a company-wide program. In addition, a CRM program should be continuously improved and complemented to meet the company's characteristics. Especially, a strategy for successful CRM for the medium and small sized distributors should be as follows. First, they should change their existing recognition in CRM and keep in-depth care for the customers. Second, they should benchmark the techniques of CRM from the leading companies and find out success points to use. Third, they should seek some methods best suited for their particular conditions by achieving the ideas combining their own strong points with marketing. Fourth, a CRM model should be developed that will promote relationship with individual customers just like the precedents of small sized businesses in Switzerland through small but noticeable events.

• The Journal of Industrial Distribution & Business
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• v.2 no.2
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• pp.15-24
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• 2011

Modern enterprises should concentrate their efforts on continuous improvements in focusing their development in the core areas of business and to reduce their expenses and to enhance the quality of service for customers. The enterprises should focus on their core business while outsourcing the non-core areas of business to external specialists for the purpose of reducing cost. In South Korea, the enterprises are becoming increasingly interested in outsourcing their logistics function, especially in using IT technologies to the 3PL. The underlying reason for this trend is because the logistics costs of Korean businesses are much higher than that of other advanced countries. This higher logistic costs weakens the price competitiveness of Korean companies in the overseas export markets and even dampening the balance of international trade. Domestically, the higher logistics costs have the effect of raising prices in the local markets and thus affecting the local economy. Therefore a solution is urgently needed to save the logistics costs for the Korean companies in the interest of increasing national competitiveness. Outsourcing to the 3PL is becoming an attraction solution to this problem. Thanks to the increasing supply of professional logistics companies, many of the enterprises are switching to the Third Party Logistics. Nevertheless the enterprises do not yet utilize the integrated third-party logistics services on a full scale. This study analyzes present conditions and problems of the domestic third-party logistics market and suggests directions for future development. To solve the problems in the domestic third-party logistics market, four actions are recommended. First there should be new supporting policies in the laws and regulations and a system for small and medium sized companies to grow. Solutions to structural problems such as abnormal multilevel merchandising, illegal operation of private cars, and freight dumping should be implemented concurrently. Furthermore, standards for new companies entry into the market should be enhanced to allow only the competitive distribution companies to enter the market. Second, development of variety of educational programs is needed through establishing human-resource development system and specialized formal educational institution focused on this market. Third, the third party distribution companies, which seek long-term relationships with the owners of goods, should endeavor to strengthen their communications capability. Fourth, adoption of high-tech distribution system and the advent of U-Logistics, making use of RFID is urgent. This study has the limitation of objectivity because it does not include various comparative case studies about companies relating to the Third Party Logistics and domestic franchise companies. However, this study is significant to the extent that it analyzes the general present conditions and the problems of domestic Third Party Logistics and suggests recommendations for revitalization of Third Party Logistics. For future studies, analyzing the successful cases of international third party logistics companies' empirical data and studying the application into domestic franchise companies would improve the objectivity of the results. This would assist the domestic third party logistics companies not only to perform excellent domestic logistics function but also to enter into the global market for international logistics.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.195-211
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• 2010

An exhibition is defined as market events for specific duration to present exhibitors' main product range to either business or private visitors, and it also plays a key role as effective marketing channels. Especially, as the effect of the opinions of the visitors after the exhibition impacts directly on sales or the image of companies, exhibition organizers must consider various needs of visitors. To meet needs of visitors, ubiquitous technologies have been applied in some exhibitions. However, despite of the development of the ubiquitous technologies, their services cannot always reflect visitors' preferences as they only generate information when visitors request. As a result, they have reached their limit to meet needs of visitors, which consequently might lead them to loss of marketing opportunity. Recommendation systems can be the right type to overcome these limitations. They can recommend the booths to coincide with visitors' preferences, so that they help visitors who are in difficulty for choices in exhibition environment. One of the most successful and widely used technologies for building recommender systems is called Collaborative Filtering. Traditional recommender systems, however, only use neighbors' evaluations or behaviors for a personalized prediction. Therefore, they can not reflect visitors' dynamic preference, and also lack of accuracy in exhibition environment. Although there is much useful information to infer visitors' preference in ubiquitous environment (e.g., visitors' current location, booth visit path, and so on), they use only limited information for recommendation. In this study, we propose a booth recommendation methodology using Sequential Association Rule which considers the sequence of visiting. Recent studies of Sequential Association Rule use the constraints to improve the performance. However, since traditional Sequential Association Rule considers the whole rules to recommendation, they have a scalability problem when they are adapted to a large exhibition scale. To solve this problem, our methodology composes the confidence database before recommendation process. To compose the confidence database, we first search preceding rules which have the frequency above threshold. Next, we compute the confidences of each preceding rules to each booth which is not contained in preceding rules. Therefore, the confidence database has two kinds of information which are preceding rules and their confidence to each booth. In recommendation process, we just generate preceding rules of the target visitors based on the records of the visits, and recommend booths according to the confidence database. Throughout these steps, we expect reduction of time spent on recommendation process. To evaluate proposed methodology, we use real booth visit records which are collected by RFID technology in IT exhibition. Booth visit records also contain the visit sequence of each visitor. We compare the performance of proposed methodology with traditional Collaborative Filtering system. As a result, our proposed methodology generally shows higher performance than traditional Collaborative Filtering. We can also see some features of it in experimental results. First, it shows the highest performance at one booth recommendation. It detects preceding rules with some portions of visitors. Therefore, if there is a visitor who moved with very a different pattern compared to the whole visitors, it cannot give a correct recommendation for him/her even though we increase the number of recommendation. Trained by the whole visitors, it cannot correctly give recommendation to visitors who have a unique path. Second, the performance of general recommendation systems increase as time expands. However, our methodology shows higher performance with limited information like one or two time periods. Therefore, not only can it recommend even if there is not much information of the target visitors' booth visit records, but also it uses only small amount of information in recommendation process. We expect that it can give real?time recommendations in exhibition environment. Overall, our methodology shows higher performance ability than traditional Collaborative Filtering systems, we expect it could be applied in booth recommendation system to satisfy visitors in exhibition environment.