• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.1-10
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• 2013

RFID(Radio Frequency Identification) system is non-contact identification technology. A basic RFID system consists of a reader, and a set of tags. RFID tags can be divided into active and passive tags. Active tags with power source allows their own operation execution and passive tags are small and low-cost. So passive tags are more suitable for distribution industry than active tags. A reader processes the information receiving from tags. RFID system achieves a fast identification of multiple tags using radio frequency. RFID systems has been applied into a variety of fields such as distribution, logistics, transportation, inventory management, access control, finance and etc. To encourage the introduction of RFID systems, several problems (price, size, power consumption, security) should be resolved. In this paper, we proposed an algorithm to significantly alleviate the collision problem caused by simultaneous responses of multiple tags. In the RFID systems, in anti-collision schemes, there are three methods: probabilistic, deterministic, and hybrid. In this paper, we introduce ALOHA-based protocol as a probabilistic method, and Tree-based protocol as a deterministic one. In Aloha-based protocols, time is divided into multiple slots. Tags randomly select their own IDs and transmit it. But Aloha-based protocol cannot guarantee that all tags are identified because they are probabilistic methods. In contrast, Tree-based protocols guarantee that a reader identifies all tags within the transmission range of the reader. In Tree-based protocols, a reader sends a query, and tags respond it with their own IDs. When a reader sends a query and two or more tags respond, a collision occurs. Then the reader makes and sends a new query. Frequent collisions make the identification performance degrade. Therefore, to identify tags quickly, it is necessary to reduce collisions efficiently. Each RFID tag has an ID of 96bit EPC(Electronic Product Code). The tags in a company or manufacturer have similar tag IDs with the same prefix. Unnecessary collisions occur while identifying multiple tags using Query Tree protocol. It results in growth of query-responses and idle time, which the identification time significantly increases. To solve this problem, Collision Tree protocol and M-ary Query Tree protocol have been proposed. However, in Collision Tree protocol and Query Tree protocol, only one bit is identified during one query-response. And, when similar tag IDs exist, M-ary Query Tree Protocol generates unnecessary query-responses. In this paper, we propose Adaptive M-ary Query Tree protocol that improves the identification performance using m-bit recognition, collision information of tag IDs, and prediction technique. We compare our proposed scheme with other Tree-based protocols under the same conditions. We show that our proposed scheme outperforms others in terms of identification time and identification efficiency.

• Cartoon and Animation Studies
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• s.41
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• pp.455-486
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• 2015

The 3D printing technology, which started from the patent registration in 1986, was a technology that did not attract attention other than from some companies, due to the lack of awareness at the time. However, today, as expiring patents are appearing after the passage of 20 years, the price of 3D printers have decreased to the level of allowing purchase by individuals and the technology is attracting attention from industries, in addition to the general public, such as by naturally accepting 3D and to share 3D data, based on the generalization of online information exchange and improvement of computer performance. The production capability of 3D printers, which is based on digital data enabling digital transmission and revision and supplementation or production manufacturing not requiring molding, may provide a groundbreaking change to the process of manufacturing, and may attain the same effect in the character merchandise sector. Using a 3D printer is becoming a necessity in various figure merchandise productions which are in the forefront of the kidult culture that is recently gaining attention, and when predicting the demand by the industrial sites related to such character merchandise and when considering the more inexpensive price due to the expiration of patents and sharing of technology, expanding opportunities and sectors of employment and cultivating manpower that are able to engage in further creative work seems as a must, by introducing education courses cultivating manpower that can utilize 3D printers at the education field. However, there are limits in the information that can be obtained when seeking to introduce 3D printers in school education. Because the press or information media only mentions general information, such as the growth of the industrial size or prosperous future value of 3D printers, the research level of the academic world also remains at the level of organizing contents in an introductory level, such as by analyzing data on industrial size, analyzing the applicable scope in the industry, or introducing the printing technology. Such lack of information gives rise to problems at the education site. There would be no choice but to incur temporal and opportunity expenses, since the technology would only be able to be used after going through trials and errors, by first introducing the technology without examining the actual information, such as through comparing the strengths and weaknesses. In particular, if an expensive equipment introduced does not suit the features of school education, the loss costs would be significant. This research targeted general users without a technology-related basis, instead of specialists. By comparing the strengths and weaknesses and analyzing the problems and matters requiring notice upon use, pursuant to the representative technologies, instead of merely introducing the 3D printer technology as had been done previously, this research sought to explain the types of features that a 3D printer should have, in particular, when required in education relating to the development of figure merchandise as an optional cultural contents at cartoon-related departments, and sought to provide information that can be of practical help when seeking to provide education using 3D printers in the future. In the main body, the technologies were explained by making a classification based on a new perspective, such as the buttress method, types of materials, two-dimensional printing method, and three-dimensional printing method. The reason for selecting such different classification method was to easily allow mutual comparison of the practical problems upon use. In conclusion, the most suitable 3D printer was selected as the printer in the FDM method, which is comparatively cheap and requires low repair and maintenance cost and low materials expenses, although rather insufficient in the quality of outputs, and a recommendation was made, in addition, to select an entity that is supportive in providing technical support.

• Journal of the Korean Society of Food Science and Nutrition
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• v.32 no.1
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• pp.96-101
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• 2003

This study was done to analyze the contents of minerals, to compare the measured values of calcium and the labeled values in food labeling and to analyze the ratio of calcium to other minerals in 43 calcium-fortified Food products sold in markets in Seoul, Korea. Content of minerals such as Ca, P, Mg, Na, K, Fe, Cu, Zn was measured by atomic absorption or colorimetric method after dry-ashing or wet-ashing. The measured values of calcium were ranged 65.5~343.9% of the labeled values in 43 calcium-fortified products. In 21 calcium-fortified food products, the measured calcium values were ranged 120～160% of the labeled values, and in three drinks those were less than 80% of the labeled, which is not acceptable to the food regulation. The ratios of Ca:P were 2.63$\pm$1.99 (mean$\pm$SD) in grain Products, 1.79$\pm$0.39 in Ramyuns, 2.80$\pm$0.53 in retort pouch food products and 8.35$\pm$12.87 in drinks. The Ca:Fe ratios were 126.33$\pm$44.36 in grain products, 130.65$\pm$34.67 in Ramyuns, 120.31$\pm$71.15 in retort pouch food products and 700.25$\pm$553.70 in drinks. The ratios of Ca:Mg were 11.86$\pm$5.40 in grain products, 9.29$\pm$1.34 in Ramyuns, 9.09$\pm$2.09 in retort pouch food products and 32.50$\pm$41.35 in drinks. The P:Mg ratios were 4.11$\pm$1.54 in grain products, 4.17$\pm$0.67 in Ramyuns, 2.58$\pm$0.45 in retort pouch food Products and 2.59$\pm$2.50 in drinks. These results suggest calcium contents and the ratio of calcium contents to other minerals in calcium-fortified food products should be strictly controlled.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.8
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• pp.1083-1093
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• 2007

The purpose of this study was to investigate the difference between students' beverage preference and dietitians' perception in elementary school lunch program. This study was conducted in three phases: (1) questionnaire development and survey administration to elementary school students (2) survey administration to dietitians who were in charge of the elementary school food service, and (3) comparison of beverage preferences between elementary school students and dietitians. In phase I, 703 elementary school students in Seoul were surveyed from July 11 to July 19. In Phase II, 100 school food service dietitians in Seoul participated by mail survey from September 15 to October 30, 2006. Based on the results, elementary school students tended to show a neutral milk preference (mean=3.04), whereas dietitians perceived that elementary school students had lower milk preference (mean=2.67). Also dietitians perceived higher yogurt preference (mean=4.27) than the real elementary school students' preference (mean=4.02). T-test results showed the gender difference on milk and yogurt preference. Male students had higher milk preference (t=4.912, p<0.001) and yogurt preference (t=3.621, p<0.001) than female students. Elementary school students showed high fruit juice preference (mean=4.34); however, dietitians perceived lower fruit juice preference of students (mean=3.92). There was no gender difference on fruit juice preference. Though elementary school students had higher fruit juice preference, the frequency of fruit juice served in school lunch was quite low. Over half of the dietitians reported that they served fruit juice less than once a semester. The results of this study indicated the existence of distinctive difference between students' fruit juice preference and school lunch menu offerings.

• Journal of the East Asian Society of Dietary Life
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• v.22 no.6
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• pp.744-757
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• 2012

This study was designed to obtain basic data for the globalization of Korean food and the expansion of food exports through contract foodservices. A survey of dietary habits and attitudes toward school foodservices was given to students in three American international schools served by a domestic contract foodservice management company located in Seoul and Gyeonggi area. The results showed an average of three meals taken daily 3.39 times for male students and 2.95 times for female students and the time required for a meal was about 24~26 minutes. The average breakfast frequency was 5.10 times(4.59 times for male students and 5.35 times for female students) and many students reported skipping breakfast due to a lack of time. The average weekly frequency of dining out was 1.78 times(2.15 times for male students and 1.60 times for female students). In all schools, irrespective of gender and grade, students responded that a desire for snacking was 'why they want to have cookies', and snacking hours were frequently listed as 'between noon and evening'. Many also responded that an unbalanced diet is the reason some snacks are 'not to their taste'. Overall, students were highly satisfied with the foodservice menu, although there was a significant difference in what was considered proper food temperature, proper food seasoning, suitable amounts of food, and freshness of food. Male and female students were specifically highly satisfied with the 'freshness of food materials' and 'variety of menu' respectively. Overall, all students were highly satisfied with the foodservice, including the 'cleanliness of tables and trays'.

• Tuberculosis and Respiratory Diseases
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• v.49 no.5
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• pp.624-632
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• 2000

Background : Home ventilation can decrease hospital-acquired infection, increase physical activity, improve nutritional status, enhance quality of life, and reduce medical costs. The number of patient using home ventilators has been increasing, particularly in Europe and United States. Although the number of patients with home ventilation has been increasing in Korea, the current status of these patients is not well known. This study was undertaken to obtain basic information upon these patients in addition to evaluating any problems related to patients' home care in our country. Methods : A register of 92 patients with home ventilators in Seoul and Kyunggi Province were obtained from commercial ventilator supply companies. The patients were contacted by phone and 29 of them accepted our visit. Information concerning education about home care before discharge, equipment cost, and problems related to home care were documented. The mode and preset variables of the home ventilator were checked; tidal volume (TV), peak airway pressure, and oxygen saturation were measured. Results : There were 26 males (90%) and their mean age was 48.0 (${\pm}20.1$) years. The underlying diseases were : 21 neuromuscular disorders, 2 spinal cord injuries, 6 chronic lung diseases. Among the caregivers, spouses (n=14) predominated. Education for home care before discharge was performed primarily by intensive care unit nurses and the education for ventilator management by commercial companies. Twenty-five of the 29 patients had tracheostomies. Volume targeted type (VTT ; n=20, 69%) was more frequently used than the pressure targeted type (PTT). Twenty-three of the 29 patients purchased a ventilator privately, which cost 7,450,000 (${\pm}$3,290,000) won for a PTT, and 14,280.000 (${\pm}$3,130,000) won for a VTT. Total cost for the equipment was 11,430,000 (${\pm}$634,000) won. The average cost required for home care per month was 1,120,000 (${\pm}$1,360, 000) won. Conclusion : The commonest underlying disease of the patients was neuromuscular disease. The VTT ventilator was primarily used with tracheostomy. Patients and their families considered the financial difficulties associated with purchasing and maintaining equipment for home care an urgent problem. Some patients were aided by a visiting nurse, however most patients were neglected and left without professional medical supervision.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Nutrition and Health
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• v.47 no.3
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• pp.214-220
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• 2014

Purpose: The purpose of this study was to assess hygiene status of meals for poorly-fed children through microbiological quality. Methods: Meals were provided by two social enterprises, one franchise, and one convenience store. There were a total of six meal samples; two samples (social enterprise meal 1; SEM 1, social enterprise meal 2; SEM 2) from two social enterprises, respectively, two samples (franchise meal 1; FM 1, franchise meal 2; FM 2) from one franchise, and two samples (convenience store meal 1; CSM 1, convenience store meal 2; CSM 2) from one convenience store. Microbiological analysis and assessment were performed by Korean food standards codex (KFSC). Results: General bacteria and E. coli in SEM 1 were detected, but the levels were not over KFSC, and Coliform less than $9.2{\times}10$ CFU/g was also detected in seasoned bean sprouts of SEM 1. General bacteria was detected at $1.6{\times}10^6$ CFU/g in cabbage kimchi of SEM 2. Coliform was detected in cabbage kimchi, squid cutlet, stir-fried pork, and fried chicken of FM1 and 2, but the levels were not over KFSC. In addition, S. aureus was detected in cabbage kimchi and seasoned dried white radish of FM 1 and 2 ($9.8{\times}10^2$ CFU/g, $9.4{\times}10^3$ CFU/g respectively), thus was over KFSC. B. cereus was detected in stir-fried pork and fried chicken ($1.2{\times}10^3$ CFU/g, $1.5{\times}10^3$ CFU/g respectively) of FM 1 and 2, thus was over KFSC. Finally, S. aureus was detected in stir-fried dried squid, seasoned spicy chicken, and stir-fried kimchi of CSM 1 and 2, and was over KFSC too ($9.5{\times}10^4$ CFU/g, $2.4{\times}10^2$ CFU/g, $1.3{\times}10^3$ CFU/g respectively). Conclusion: Results of this study suggest that systemic management of hygiene is necessary to safely providing meals to poorly-fed children.

• Journal of Sericultural and Entomological Science
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• v.50 no.2
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• pp.101-108
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• 2012

This study was conducted to confirm the mass production of male pupae and sex-limited larval marking variety as a host for synnemata production of Isaria tenupes in RDA(Rural Development Administration). Silkworm pupation, infection rate and synnemate formation of I.tenuipes were examined. Among the silkworm varieties tested, male Hansaengjam showed the highest pupation rate at 98.7%. I. tenuipes infection rate of larvae of newly-exuviated 5th instar silkworm was 83.7 ~ 90.4% in the spring rearing season and 91.7 ~ 96.6% in the autumn rearing season. Synnemata production of I. tenuipes was execellent in female Yangwonjam with an incidence rate of 99.5% followed by male Yangwonjam(99.5%) and Baegokjam(99.4%) in the spring and autumn rearing season. Synnemata living weight ranged from 0.93 ~ 1.25 g in the spring rearing season. The female Hansaengjam had the heaviest synnemata weight(1.25 g). Synnemata dry weight ranged from 0.27 ~ 0.35 g in the spring rearing season. The female Yangwonjam had the heaviest synnemata weight(0.35 g).