• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.411-426
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• 2009

Most of the metaheuristics are made by imitating the action of the animals. In this paper, we proposed Mine Algorithm. The Mine Algorithm is a metaheuristic that imitates the action of the human being. Speaking of search, the field in which the know-how and the heuristics of the human being are melted best is the mining industry. In the Mine Algorithm we formalize the action pattern of the human being by focusing the mine business. The Mine Algorithm uses various searching techniques fluently and shows equally good performance for broad problems. That is, it has good generality. We show the improved generality of the Mine Algorithm by the comparing experiments with the conventional metaheuristics.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.107-120
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• 2003

In Web Based Instruction, as evaluation of learning process means individual student's learning activity, it demands data on learning time, pattern, participation, environment in a specific learning contents. The purpose of this paper is to reflect analysis results of individual student's learning status in achievement evaluation using the most suitable web log mining to settle evaluation problem of learning process, an issue in web based instruction. The contents and results of this study are as following. First, conformity item for learning status analysis is determined and web log data preprocessing is executed. Second, on the basis of web log data, I construct student's database and analyze learning status using data mining techniques.

• Journal of Digital Contents Society
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• v.19 no.3
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• pp.471-477
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• 2018

As time changes, users change their interest. In this paper, we propose a method to provide suitable service for users by dynamically weighting service interests in the context of age, timing, and seasonal changes in ubiquitous environment. Based on the service history data presented to users according to the age or season, we also offer useful services by continuously adding the most recent service rules to reflect the changing of service interest. To do this, a set of services is considered as a transaction and each service is considered as an item in a transaction. And also we represent the association of services in a graph and extract frequent service items that refer to the latest information services for users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.978-985
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• 2003

The implementation of abnormal behavior detection IDS is more difficult than the implementation of misuse behavior detection IDS because usage patterns are various. Therefore, most of commercial IDS is misuse behavior detection IDS. However, misuse behavior detection IDS cannot detect system intrusion in case of modified intrusion patterns occurs. In this paper, we apply data mining so as to detect intrusion with only audit data related in intrusion among many audit data. The agent in the distributed IDS can collect log data as well as monitoring target system. False positive should be minimized in order to make detection accuracy high, that is, core of intrusion detection system. So We apply data mining algorithm for prediction of modified intrusion pattern in the level of audit data learning.

• Journal of Information Technology Application
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• v.3 no.2
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• pp.1-24
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• 2001

This purpose of this study is to drive important criteria for improving customer relationship of R institute using data mining techniques. The focus of this research is to consider patterns and interactions of research variables from research management database of R institute, and to classify the outside organizations and the inside organizations for research contract organizations, and to decide the directions of customer relationship management through analyzing the research type and research cost of research topics. In order to drive criteria variables through pattern analysis of the research database, decision tree algorithm is employed. The results show that determinant variables of 17 input variables are research period, overhead cost, R ＆ D cost as variables to classify the outside and inside contract organization.

• Geomechanics and Engineering
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• v.20 no.1
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• pp.55-66
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• 2020

The damage or failure of coal rock is accompanied by energy accumulation, dissipation and release. It is crucial to study the energy evolution characteristics of coal rock for rock mechanics and mining engineering applications. In this paper, coal specimens sourced from the Xinhe mine located in the Jining mining area of China were initially subjected to uniaxial compression, and the micro-parameters of the two-dimensional particle flow code (PFC^2D) model were calibrated according to the experimental test results. Then, the PFC^2D model was used to subject the specimens to substantial uniaxial compression, and the energy evolution laws of coal specimens with various schemes were presented. Finally, the elastic energy storage ratio m was investigated for coal rock, which described the energy conversion in coal specimens with various arrangements of preformed holes. The arrangement of the preformed holes significantly influenced the characteristics of the crack initiation stress and energy in the prepeak stage, whereas the characteristics of the cumulative crack number, failure pattern and elastic strain energy during the loading process were similar. Additionally, the arrangement of the preformed holes altered the proportion of elastic strain energy U_e in the total energy in the prepeak stage, and the probability of rock bursts can be qualitatively predicted.

• Computers and Concrete
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• v.22 no.5
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• pp.469-479
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• 2018

The Brazilian tensile strength of concrete samples is a key parameter in fracture mechanics since it may significantly change the quality of concrete materials and their mechanical behaviors. It is well known that porosity is one of the most often used physical indices to predict concrete mechanical properties. In the present work the influence of porosity shape on concrete tensile strength characteristics is studied, using a bonded particle model. Firstly numerical model was calibrated by Brazilian experimental results and uniaxial test out puts. Secondly, Brazilian models consisting various pore shapes were simulated and numerically tested at a constant speed of 0.016 mm/s. The results show that pore shape has important effects on the failure pattern. It is shown that the pore shape may play an important role in the cracks initiation and propagation during the loading process which in turn influence on the tensile strength of the concrete samples. It has also been shown that the pore size mainly affects the ratio of uniaxial compressive strength to that of the tensile one in the simulated material samples.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.16 no.2
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• pp.33-46
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• 2012

Purpose : Nowadays excrement-related disease that repeats constipation and diarrhea is on the increase due to the change of dietary and lack of exercise, etc. We analyzed Bangyakhappyeon in order to find out the materia medica which is used for the excrement patterns. Methods : The database used in present thesisis consist of disease pattern, nature of medicinals and materia medica from Bangyakhappyeon was constructed. We analyzed the nature of medicinals of excrement patterns(or symptom) by frequency analysis and network analysis, and also searched main materia medica of excrement patterns(or symptom) by frequency analysis and rule mining. Results : We analyzed the nature of medicinals of excrement patterns(or symptom) in Bangyakhappyeon. And we researched the high frequency materia medica, high specificity materia medica and high frequent paired-drugs as main materia medica of excrement patterns(or symptom). Conclusion : This study found the information about frequency relationship between excrement patterns(or symptoms) and materia medica.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.316-321
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• 2008

Advanced computer network technology enables computers to be connected in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, which makes it vulnerable to previously unidentified attack patterns and variations in attack and increases false negatives. Intrusion detection and analysis technologies are thus required. This paper investigates the asymmetric costs of false errors to enhance the performances the detection systems. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors, this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of anomaly traffic detection is enhanced by considering the costs of false errors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.479-482
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• 2001

IDS has been studied mainly in the field of the detection decision and collecting of audit data. The detection decision should decide whether successive behaviors are intrusions or not, the collecting of audit data needs ability that collects precisely data for intrusion decision. Artificial methods such as rule based system and neural network are recently introduced in order to solve this problem. However, these methods have simple host structures and defects that can't detect transformed intrusion patterns. So, we propose the method using data mining that can retrieve and estimate the patterns and retrieval of user's behavior in the distributed different hosts.