• Journal of the Korean Geographical Society
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• v.30 no.1
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• pp.68-92
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• 1995

Recentry the structure of the retail trade have been chanaed with its environmantal changes. Some studies may be necessary on the changing process of environment and fundamental structure analyses of the retail trade. This study analyzes the location of retail trades, inhabitants' behavior in retail tredes and their desirable utilization scheme of them in Kwangju-si. Some study methods, contents and coming-out results are as follows: 1. Retail trades can be classified into independent stores, chain-stores (supermarket, voluntary chain and frenchiise system and convenience store), department stores, cooperative associations, traditional, markets mail-order marketing, automatic vending and others by service levels, selling-items, prices, managements, methods of retailing and store or nonstore type. 2. In Kwangju, the environment of retail trades is related to the consumers of population structure: chanes in consumers pattern, trends toward agings and nuclear family, increase of leisur: time and female advances to society. Rapid structural shift in retail trade has also been occurred due to these social changes. Traditionl and premodern markets until 1970s altere to supermarkets or department stores in 1980s, and various types, large enterprises and foreign capitals came into being in 1990s. 3. The locational characteristics of retail trades are resulted from the spatial analysis of the total population distribution, and from the calculation of segregation index in the light of potential demand. The densely-populated areas occurs in newly-built apartment housing complex which is distributed with a ring-shaped pattern around the old urban core. The numbers and rates of the aged over sixty in Kwangsan-gu and the circumference area of Mt.Moodeung, are larger and higher where rural elements are remarkable. A relation between population distribution and retail trade are analysed by the index of population per shop. The index of the population number per shop is lower in urban center, as a whole, being more convenient for consumers. In newly-formed apartment complex areas, on the other, the index more than 1,000 per shop, meeting not the demands for consumers. Because both the younger and the aged are numerous in these areas, the retail trade pattern pertinent to both are needed. Urban fringes including Kwangsan-gu and the vicinity of Mt.Moodeung have some problems owing to the most of population number per shop (more than 1, 500) and the most extensive as well. 4. The regional characteristic of retail trade is analyzed through the location quotient of shops by locational patterns and centerality index. Chungkum-dong is the highest-order central place in CBD. It is the core of retail trades, which has higher-ordered specialty store including three big department stores, supermarkets and large stores. Taegum-dong, Chungsu-dong, Taeui-dong, and Numun-dong that are neiahbored to Chungkum-dong fall on the second group. They have a central commercial section where large chain stores, specialty shopping streets, narrow-line retailing shops (furniture, amusement service, and gallary), supermarkets and daily markets are located. The third group is formed on the axis of state roads linking to Naju-kun, Changseong-kun, Tamyang-kun, Hwasun-kun and forme-Songjeong-eup. It is related to newly, rising apartment housing complex along a trunk road, and characterized by markets and specialty stores. The fourth group has neibourhood-shopping centers including older residential area and Songjeong-eup area with independent stores and supermarkets as main retailing functions. The last group contains inner residential area and outer part of a city including Songjeong-eup. Outer part of miscellaneous shops being occasionally found is rural rather than urban (Fig. 7). 5. The residents' behaviors using retail trade are analyzed by factors of goods and facilities. Department stores are very high level in preference for higher-order shopping-goods such as clothes for full dress in view of both diversity and quality of goods(28.9%). But they have severe traffic congestions, and high competitions for market ranges caused by their sma . 64.0% of respondents make combined purpose trips together with banking and shopping. 6. For more efficiency of retail-trading, it is necessary to induce spatial distribution policy with regard to opportunity frequency of goods selection by central place, frontier regions and age groups. Also we must consider to analyze competition among different types of retail trade and analyze the consumption behaviors of working females and younger-aged groups, in aspects of time and space. Service improvement and the rationalization of management should be accomplished in such as cooperative location (situation) must be under consideration in relations to other functions such as finance, leisure & sports, and culture centers. Various service systems such as installment, credit card and peremium ticket, new used by enterprises, must also be carried service improvement. The rationalization and professionalization in for the commercial goods are bsically requested.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.47-67
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• 2017

Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector's intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. 'Simultaneous' implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.

• Korean Journal of Psychosomatic Medicine
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• v.4 no.2
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• pp.269-276
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• 1996

A theroretical study was made on the psychodynamism of somatoform disorder. Somatoform disorder is caused by a defense mechanism of somatization. Somatization is the tendency to react to stimuli(drives, defenses, and conflict between them) physically rather than psychically(Moore, 1990). Ford(1983) said it is a way of life, and Dunbar(1954) said it is the shift of psychic energy toward expression in somatic symptoms. As used by Max Shur(1955), somatization links symptom formation to the regression that may occur in response to acute and chronic conflict. In the neurotic individual psychic conflict often provokes regressive phenomena that may include somatic manifestations characteristic of an earlier developmental phase. Schur calls this resomatization. Pain is the most common example of a somatization reaction to conflict. The pain has an unconscious significance derived from childhood experiences. It is used to win love, to punish misdeeds, as well as a means to amend. Among all pains, chest pain has a special meaning. Generally speaking, 'I have pain in my chest' is about the same as 'I have pain in my mind'. The chest represent the mind, and the mind reminds us about the heart. So we have a high tendency to recognize mental pain as cardiac pain. Kellner(1990) said rage and hostility, especially repressed hostility, are important factors in somatization. In 'Psychoanalytic Observation on Cardiac Pain', psychoanalyst Bacon(1953) presented clinical cases of patients who complained of cardiac pain in a psychoanalytic session that spread from the left side of their chests down their left arms. The pain was from rage and fear which came after their desire to be loved was frustrated by the analyet. She said desires related to cardiac pain were dependency needs and aggressions. Empatic relationship and therapeutic alliances are indispensable to psychotherapy in somatoform disorder. The beginning of therapy is to discover a precipitating event from the time their symptoms have started and to help the patient understand a relation between the symptom and precipitating event. Its remedial process is to find and interpret a intrapsychic conflict shown through the symptoms of the patient. Three cases of somatoform disorder patients treated based on this therapeutic method were introduced. The firt patient, Mr. H, had been suffering from hysterical aphasia with repressed rage as ie psychodynamic cause. An interpretation related to the precipitating event was given by written communication, and he recovered from his aphasia after 3 days of the session. The second patient was a dentist in a cardiac neurosis with agitation and hypochondriasis, whose psychodynamism was caused by a fear that he might lose his father's love. His symptom was also interpreted in relation to the precipitating event. It showed the patient a child-within afraid of losing his father's love. His condition improved after getting a didactic interpretation which told him, to be master of himself, The third patient was a lady transferred from the deparment of internal medicine. She had a frequent and violent fit of chest pains, whose psychodynamic cause was separation anxiety and a rage due to the frustration of dependency needs. Her symptom vanished dramatically when she wore a holler EKG monitor and did not occur during monitoring. By this experience she found her symptom was a psychogenic one, and a therapeutic alliance was formed. later in reguar psychotherapy sessions, she was told the relaton between symptoms and precipitating events. Through this she understood that her separation anxiety was connected to the symptom and she became less terrifide when it occurred. Now she can travel abroad and take well part in social activities.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.203-207
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• 2010

Purpose: Hepatitis B is infection caused by Hepatitis B virus (HBV). Currently, there are several methods, Kits and equipments for conducting Hepatitis B test. Due to ununiformed methods, it would cause some differences. To manage these differences, it needs process evaluating function of test system and reagent using particular standard substance. The aim of this study is to investigate tendency of RIA method's reagent used in Asan Medical Center through comparing several other test reagents using national standard substance. Materials and Methods: The standard substance in National Institute of Food and Drug Safety Evaluation's biology medicine consists of 5 things, 4 antigens and 1 antibody. We tested reagents using A, B company's Kits according to each test method. All tests are measured repeatedly to obtain accurate results. Results: Test result of "HBs Ag Mixed titer Performance panel" is obtained match rate compared S/CO unit standard with RIA method and EIA 3 reagents, CIA 2 reagents is that company A's reagent is 94.4% (17/18), 83.3% (15/18), B is 88.9% (16/18), 77.8% (14/18). Test result of "HBs Ag Low titer Performance panel" is obtain that EIA 2 reagents is shown 7 posive results, CIA 3 reagents is 11, and RIA method's company A's reagent is 3, B is 2 of 13 in low panel. "HBV surface antigen 86.76 IU/vial" tested dilution. A is obtain positive results to 600 times(0.14 IU/mL), B is 300 times (0.29 IU/mL). Case of "HBV human immunoglobulin 95.45 IU/vial", A is shown positive result to 10,000 times (9.5 mIU/mL) and B is 4,000 times (24 mIU/mL). Test result of "HBs Ag Working Standards 0.02~11.52 IU/mL" is shown that Company A's kit concentration level was 0.38IU/mL, company B was 2.23 IU/mL and higher level of concentration was positive results. Conclusion: When comparing various test reagents and RIA method according to National Standard substances for Hepatitis B test, we recognized that there were no significant trends between reagents. For hepatitis B virus antigen-antibody titers even in parts of the test up to 600 times the antigen, antibodies to 10,000 times the maximum positive results could be obtained. Therefore, we confirmed that results from Asan Medical Center are performed smoothly by reagents and system for hepatitis B virus test.

• Journal of Nutrition and Health
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• v.41 no.5
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• pp.439-447
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• 2008

There is a limitation to estimate vitamin $B_{12}$ intake due to lack of data on vitamin $B_{12}$ content in many Korean foods. In this study, vitamin $B_{12}$ content was determined in some soybean or vegetable-fermented foods, edible seaweeds and other frequently consumed foods in Korea by microbioassay using Lactobacillus delbruecki ATCC 7830. The traditional type of Doenjang and Chungkookjang contained 1.85 ${\mu}g/100$ g and 0.69 ${\mu}g/100$ g of vitamin $B_{12}$, respectively, while the factory-type of Doenjang and Chungkookjang contained 0.04-0.86 ${\mu}g/100$ g and 0.06-0.15 ${\mu}g/100$ g. Vitamin $B_{12}$ was not detected in steamed soybeans and Tofu which is a not-fermented soybean product, indicating that vitamin $B_{12}$ in Doenjang and Chungkookjang might be produced during the fermentation process. The Korean-style soy sauce contained 0.04 ${\mu}g$ vitamin $B_{12}$/100 mL, but vitamin $B_{12}$ was not detected in Japanese-style soy sauce and white miso. Commercial Kimchi, a representative Korean vegetable- fermented food, made of Korean cabbage, Yeolmu, or Mustard leaves contained 0.013-0.03 ${\mu}g$ vitamin $B_{12}$/100 g, while Kimchi without red pepper and fermented fish sauce (White Kimchi) did not. Vitamin $B_{12}$ content was very high in some edible seaweeds such as laver (66.76 ${\mu}g/100$ g dry weight) and sea lettuce (84.74 ${\mu}g/100$ g dry weight), and it was 17.12 ${\mu}g/100$ g of dried small anchovy, 1.07 ${\mu}g/100$ g of whole egg, and 0.02 ${\mu}g/100$ g of coffee mix. From these results, it is assumed that Koreans take substantial amount of vitamin $B_{12}$ from plant-origin foods. And, with these data, we will be able to calculate dietary vitamin $B_{12}$ content more correctly than before. In conclusion, soybean-fermented foods, Kimchi, laver and sea lettuce are recommendable as good sources of vitamin $B_{12}$ for vegetarians or Korean elderly on grain and vegetable based diet.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Tuberculosis and Respiratory Diseases
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• v.46 no.5
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• pp.685-696
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• 1999

Background : Idiopathic pulmonary fibrosis (IPF) is a diffuse inflammatory and fibrosing process that occurs within the interstitium and alveolus of the lung with invariably poor prognosis. The major problem in management of IPF results from the variable rate of disease progression and the difficulties in predicting the response to therapy. The purpose of this retrospective study was to evaluate the short-term efficacy of steroid and immunosuppressive therapy for IPF and to identify the pre-treatment determinants of favorable response. Method : Twenty patients of IPF were included. Diagnosis of IPF was proven by thoracoscopic lung biopsy and they were presumed to have active progressive disease. The baseline evaluation in these patients included clinical history, pulmonary function test, bronchoalveolar lavage (BAL), and chest high resolution computed tomography (HRCT). Fourteen patients received oral prednisolone treatment with initial dose of 1mg/kg/day for 8 to 12 weeks and then tapering to low-dose prednisolone (0.25mg/kg/day). Six patients who previously had experienced significant side effects to steroid received 2mg/kg/day of oral cyclophosphamide with or without low-dose prednisolone. Follow-up evaluation was performed after 6 months of therapy. If patients met more than one of followings, they were considered to be responders : (1) improvement of more than one grade in dyspnea index, (2) improvement in FVC or TLC more than 10% or improvement in DLco more than 20% (3) decreased extent of disease in chest HRCT findings. Result : One patient died of extrapulmonary cause after 3 month of therapy, and another patient gave up any further medical therapy due to side effect of steroid. Eventually medical records of 18 patients were analyzed. Nine of 18 patients were classified into responders and the other nine patients into nonresponders. The histopathologic diagnosis of the responders were all nonspecific interstitial pneumonia (NSIP) and that of nonresponders were all usual interstitial pneumonia (UIP) (p<0.001). The other significant differences between the two groups were female predominance (p<0.01), smoking history (p<0.001), severe grade of dyspnea (p<0.05), lymphocytosis in BAL fluid ($23.8{\pm}16.3%$ vs $7.8{\pm}3.6%$, p<0.05), and less honeycombing in chest HRCT findings (0% vs $9.2{\pm}2.3%$, p<0.001). Conclusion : Our results suggest that patients with histopathologic diagnosis of NSIP or lymphocytosis in BAL fluid are more likely to respond to steroid or immunosuppressive therapy. Clinical results in large numbers of IPF patients will be required to identify the independent variables.

• Korean Journal of Organic Agriculture
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• v.8 no.3
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• pp.111-120
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• 2000

In this study, by-products of rice bran, rice hull, bean curd dregs and food waste were fermented with different ratios of 26, 26, 34 and 14% respectively and the experimental diets were prepared mixing it with various ratios of commercial diets (fermented feed commercial feed : A 80 : 20, B 70 : 30, C 60 : 40, D 50:50). In Experiment I, feed intake, nutrients digestibilities and nitrogen retention were investigated and body weight gain in Experiment 1. For chemical composition of experimental diets, crude protein contents were 13.73, 13.78, 14.45 and 15.14% in A, B, C and D respectively and the contents of crude fat and crude fiber were highest in A as 8.66 and 27.82% respectively. 2. Dry hurler intakes were significantly higher (P<0.05) in A(362.06g/d) and C(358.49g/d) than B and D. Intakes of crude protein and crude fat were not significantly different (P>0.05) among treatments however those of crude fiber and crude ash were significantly higher (P>0.05) in A(101.47g/d). 3. Dry matter digestibilities in the range of 53.38∼68.81% in all treatments have shown the highest value in C of 60% fermented feed plus 40% commercial diet but the lowest in A of 80% of fermented feed plus 20% commercial diet (P<0.05). 59.85% of digestibility of crude protein in A was also lowest among all treatments (p<0.05), 4. 8.47g/d of nitrogen intake in C was recorded highest (P<0.05) however the highest nitrogen retention was marked in B of 50% fermented feed plus 50% of commercial diet due mainly to lower excretion of nitrogen through feces. 5. The data of live weight gain in Experiment II has not been shown as a result since the proper daily gain of body weight was achieved only in D as 88.89g/d and the goats in other treatments have shown frequent diarrhea. However, neglecting the animals with diarrhea, higher amounts of concentrates in the diets (C and D) showed the tendency of higher weight gain. 6. In this study, feeding 60% fermented feed manufactured with domestic agricultural by-products of rice bran, rice hull, bean curd dregs and food waste to Korean native goats have shown satisfactory results of intake and digestibility and it indicates that utilization of domestic agricultural by-products in goats could be improved by the process of fermentation. However it's effects on body weight gain and nitrogen retention were below than expected. Different sources of feedstuff for fermentation may result in different performances of animals. However, to draw overall conclusion from this study, 50∼60% of fermented feed can be recommended in the case of mixing with concentrates.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.1-8
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• 2013

Data mining techniques are used to find important and meaningful information from huge databases, and pattern mining is one of the significant data mining techniques. Pattern mining is a method of discovering useful patterns from the huge databases. Frequent pattern mining which is one of the pattern mining extracts patterns having higher frequencies than a minimum support threshold from databases, and the patterns are called frequent patterns. Traditional frequent pattern mining is based on a single minimum support threshold for the whole database to perform mining frequent patterns. This single support model implicitly supposes that all of the items in the database have the same nature. In real world applications, however, each item in databases can have relative characteristics, and thus an appropriate pattern mining technique which reflects the characteristics is required. In the framework of frequent pattern mining, where the natures of items are not considered, it needs to set the single minimum support threshold to a too low value for mining patterns containing rare items. It leads to too many patterns including meaningless items though. In contrast, we cannot mine any pattern if a too high threshold is used. This dilemma is called the rare item problem. To solve this problem, the initial researches proposed approximate approaches which split data into several groups according to item frequencies or group related rare items. However, these methods cannot find all of the frequent patterns including rare frequent patterns due to being based on approximate techniques. Hence, pattern mining model with multiple minimum supports is proposed in order to solve the rare item problem. In the model, each item has a corresponding minimum support threshold, called MIS (Minimum Item Support), and it is calculated based on item frequencies in databases. The multiple minimum supports model finds all of the rare frequent patterns without generating meaningless patterns and losing significant patterns by applying the MIS. Meanwhile, candidate patterns are extracted during a process of mining frequent patterns, and the only single minimum support is compared with frequencies of the candidate patterns in the single minimum support model. Therefore, the characteristics of items consist of the candidate patterns are not reflected. In addition, the rare item problem occurs in the model. In order to address this issue in the multiple minimum supports model, the minimum MIS value among all of the values of items in a candidate pattern is used as a minimum support threshold with respect to the candidate pattern for considering its characteristics. For efficiently mining frequent patterns including rare frequent patterns by adopting the above concept, tree based algorithms of the multiple minimum supports model sort items in a tree according to MIS descending order in contrast to those of the single minimum support model, where the items are ordered in frequency descending order. In this paper, we study the characteristics of the frequent pattern mining based on multiple minimum supports and conduct performance evaluation with a general frequent pattern mining algorithm in terms of runtime, memory usage, and scalability. Experimental results show that the multiple minimum supports based algorithm outperforms the single minimum support based one and demands more memory usage for MIS information. Moreover, the compared algorithms have a good scalability in the results.