• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.1 s.307
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• pp.53-66
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• 2006

This paper proposes the combined image retrieval system that gives the same relevance as exhaustive search method while its performance can be considerably improved. This system is combined with two different retrieval methods and each gives the same results that full exhaustive search method does. Both of them are two-stage method. One uses condensation of feature vectors, and the other uses binary-tree clustering. These two methods extract the candidate images that always include correct answers at the first stage, and then filter out the incorrect images at the second stage. Inasmuch as these methods use equal algorithm, they can get the same result as full exhaustive search. The first method condenses the dimension of feature vectors, and it uses these condensed feature vectors to compute similarity of query and images in database. It can be found that there is an optimal condensation ratio which minimizes the overall retrieval time. The optimal ratio is applied to first stage of this method. Binary-tree clustering method, searching with recursive 2-means clustering, classifies each cluster dynamically with the same radius. For preserving relevance, its range of query has to be compensated at first stage. After candidate clusters were selected, final results are retrieved by computing similarities again at second stage. The proposed method is combined with above two methods. Because they are not dependent on each other, combined retrieval system can make a remarkable progress in performance.

• Journal of the Korean GEO-environmental Society
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• v.10 no.5
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• pp.19-26
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• 2009

Rammed Aggregate Pier (RAP) method is intermediate foundation between deep and shallow foundation, and it has been built in world wide. RAP represents a relatively new method that has grown steadily over 19 years since Geopier of USA developed this revolutionary method in 1989. The investigation and research in domestic is not accomplished. In this paper, the examined details of different spacing of piles, bearing capacities, respectively, conclude with recommendations on how RAP can be used in future needs. This documentation further provides comparisons of the laboratory test results which were obtained from changing the spacing of piles, namely installed rammed aggregate pier. Laboratory model test was administered in a sand box. Strain control test was conducted to determine the bearing capacities of the piers; 20 mm, 30 mm and 40 mm RAP in diameter using drilling equipment to make holes were installed in sand at initial relative densities of 40%. By comparing different spacing of piles, in this experiment, piles are spaced structually span, form a ring shape, narrowing the distance of each other, to the center. the result shows that as diameter of pier is bigger in diameter, bearing capacity also dramatically increased due to raised stiffness. Also, as the space between each piers was closed, the settlement rate of soil was decreased significantly. From the test results, as the space between each piles were getting closer, it allows greater chances to have more resistance to deformation, and shows more improved stability of structures. After from the verification work which is continuous leads the accumulation of the site measuring data which is various, and bearing capacity and the settlement is a plan where the research will be advanced for optimum installed RAP.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.646-653
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• 2016

Outbound market is a rapidly growing global industry, and has evolved into a 11 trillion won trade. A lot of recommender systems, which are based on collaborative and content filtering, target the existing purchase log or rely on studies based on similarity of products. These researches are not highly efficient as data was not obtained in advance, and acquiring the overwhelming amount of data has been relatively slow. The characteristics of an outbound product are that it should be purchased at least twice in a year, and its pricing should be in the higher category. Since the repetitive purchase of a product is rare for the outbound market, the old recommender system which profiles the existing customers is lacking, and has some limitations. Therefore, due to the scarcity of data, we suggest an improved customer-profiling method using web usage mining, algorithm of association rule, and rule-based algorithm, for faster recommender system of outbound product.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.545-550
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• 2013

In pattern recognition field, data classification is an essential process for extracting meaningful information from data. Adaptive boosting algorithm, known as AdaBoost algorithm, is a kind of improved boosting algorithm for applying to real data analysis. It consists of weak classifiers, such as random guessing or random forest, which performance is slightly more than 50% and weights for combining the classifiers. And a strong classifier is created with the weak classifiers and the weights. In this paper, a research is performed using AdaBoost algorithm for detecting chaff echo which has similar characteristics to precipitation echo and interrupts weather forecasting. The entire process for implementing chaff echo classifier starts spatial and temporal clustering based on similarity with weather radar data. With them, learning data set is prepared that separated chaff echo and non-chaff echo, and the AdaBoost classifier is generated as a result. For verifying the classifier, actual chaff echo appearance case is applied, and it is confirmed that the classifier can distinguish chaff echo efficiently.

• Tuberculosis and Respiratory Diseases
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• v.43 no.6
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• pp.1008-1018
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• 1996

Primary mediastinal nonseminomatous germ cell tumor is extremely rare. Apart from rarity and large size, mediastinal germ cell tumors show striking similarity to testicular tumors in age, incidence, and tumor type. The symptoms associated with these tumors are related mainly to size, invasion of neighboring structures, and distant metastases. Tissue diagnosis is obtained by biopsy of the primary lesion or by biopsy of metastatic sites. Tumors often present with advanced bulky disease, which are unresectable. So these tumors require an aggressive multidisciplinary approach to management. Optimal management includes aggressive surgical debulking and early use of cisplatin-bleomycin-based combination chemotherapy. Serial biomarker measurements permit early recognition of recwrence and improved timing of surgical intervention. The prognosis for mediastinal germ cell tumors is poor, not only because they are far advanced at the time of diagnosis but also because some of the tumors-such as embryonal carcinomas, choriocarcinomas, and endodermal sinus tumors-are very aggressive. In these cases, we present three young male patients with large mass on anterior mediastinum. Tissue diagnosis was obtained by primary lesion biopsy. All patients received surgical debulking and combination chemotherapy and experienced a brief response and eventually had relapses. We report these cases with a review of literatures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1777-1787
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• 2017

Federated authentication (FA) is a multi-domain authentication and authorization infrastructure that enables users to access nationwide R&D resources with their home-organizational accounts. An FA-enabled user is redirected to his/her home organization, after selecting the home from an identity-provider (IdP) discovery service, to log in. The discovery service allows a user to search his/her home from all FA-enabled organizations. Users get troubles to find their home as federation size increases. Therefore, a discovery service has to provide an intuitive way to make a fast IdP selection. In this paper, we propose a discovery system which leverages geographical information. The proposed system calculates geographical proximity and text similarity between a user and organizations, which determines the order of organizations shown on the system. We also introduce a server redundancy and a status monitoring method for non-stop service provision and improved federation management. Finally, we deployed the proposed system in a real service environment and verified the feasibility of the system.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.193-200
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• 2014

Due to the advent of ubiquitous computing environment, it is becoming a part of our common life style. And tremendous information is cumulated rapidly. In these trends, it is becoming a very important technology to find out exact information in a large data to present users. Collaborative filtering is the method based on other users' preferences, can not only reflect exact attributes of user but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, we propose clustering method by user's features based on SOM for predicting purchase pattern in u-Commerce. it is necessary for us to make the cluster with similarity by user's features to be able to reflect attributes of the customer information in order to find the items with same propensity in the cluster rapidly. The proposed makes the task of clustering to apply the variable of featured vector for the user's information and RFM factors based on purchase history data. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.70-77
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• 2008

This paper proposes a new text candidate region detection method that uses genetic algorithm based on information of the segmented regions. In image segmentation, a classification of the pixels at each color channel and a reclassification of the region-unit for reducing inhomogeneous clusters are performed. EWFCM(Entropy-based Weighted C-Means) algorithm to classify the pixels at each color channel is an improved FCM algorithm added with spatial information, and therefore it removes the meaningless regions like noise. A region-based reclassification based on a similarity between each segmented region of the most inhomogeneous cluster and the other clusters reduces the inhomogeneous clusters more efficiently than pixel- and cluster-based reclassifications. And detecting text candidate regions is performed by genetic algorithm based on energy and variance of the directional edge components, the number, and a size of the segmented regions. The region information-based detection method can singles out semantic text candidate regions more accurately than pixel-based detection method and the detection results will be more useful in recognizing the text regions hereafter. Experiments showed the results of the segmentation and the detection. And it confirmed that the proposed method was superior to the existing methods.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.287-296
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• 2003

There has been much research focused on collaborative filtering technique in Recommender System. However, these studies have shown the First-Rater Problem and the Sparsity Problem. The main purpose of this Paper is to solve these Problems. In this Paper, we suggest the user's predicting preference method using Bayesian estimated value and the associative user clustering for the recalculation of preference. In addition to this method, to complement a shortcoming, which doesn't regard the attribution of item, we use Representative Attribute-Neighborhood method that is used for the prediction when we find the similar neighborhood through extracting the representative attribution, which most affect the preference. We improved the efficiency by using the associative user's clustering analysis in order to calculate the preference of specific item within the cluster item vector to the collaborative filtering algorithm. Besides, for the problem of the Sparsity and First-Rater, through using Association Rule Hypergraph Partitioning algorithm associative users are clustered according to the genre. New users are classified into one of these genres by Naive Bayes classifier. In addition, in order to get the similarity value between users belonged to the classified genre and new users, and this paper allows the different estimated value to item which user evaluated through Naive Bayes learning. As applying the preference granted the estimated value to Pearson correlation coefficient, it can make the higher accuracy because the errors that cause the missing value come less. We evaluate our method on a large collaborative filtering database of user rating and it significantly outperforms previous proposed method.

• Korean Journal of Microbiology
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• v.54 no.4
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• pp.428-435
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• 2018

In this study, we isolated and identified bacteria from freshwater and soil collected from Osang reservoir, to screen antimicrobial bacteria against various pathogenic bacteria. 38 strains were isolated and assigned to the class Proteobacteria (22 strains), Actinobacteria (7 strains), Bacteroidets (6 strains), and Firmicutes (3 strains) based on 16S rRNA gene sequence analysis. Among them, strain OS17 showed a good growth inhibition against 5 methicillin-resistant Staphylococcus aureus subsp. aureus strains and Bacillus cereus, Bacillus subtilis, Filobasidium neoformans. As a result of the 16S rRNA gene sequence analysis, strain OS17 show the high similarity with Burkholderia ambifaria $AMMD^T$, B. diffusa $AM747629^T$, B. tettitorii $LK023503^T$ 99.8%, 99.7%, 99.6%, respectively. We investigated cell growth and antimicrobial activity according to commercial culture medium, temperature, pH for culture optimization of strain OS17. Optimal conditions for growth and antimicrobial activity in strain OS17 were found to be: YPD medium, $35^{\circ}C$ and pH 6.5. When the strain was cultured in LB, NB, TSB, R2A media at $20^{\circ}C$ and $25^{\circ}C$, the antimicrobial activity did not show. Culture filtrate of strain OS17 showed antimicrobial activity against 5 MRSA strains, Bacillus cereus, Bacillus subtilis, and Filobasidium neoformans with inhibition zones from 2 to 8 mm. Optimal reaction time was 48 h in YPD medium, 100 rpm and 0.3 vvm in 2 L-scale fed-batch fermentation process for antimicrobial activity. Culture optimization of strain OS17 can be improved on antimicrobial activity. Therefore, the antimicrobial activity of Burkholderia sp. OS17 had potential as antibiotics for pathogens including MRSA.