• Structural Engineering and Mechanics
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• v.29 no.4
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• pp.433-453
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• 2008

The equation of motion of a one way (vertical) spanning strip wall, as an assembly of two rigid bodies, is presented. Only one degree of freedom is needed to completely describe the wall response as the bodies are assumed to be perfectly rectangular and are allowed to rock but not to slide horizontally. Furthermore, no arching action occurs since vertical motion of the upper body is not restrained. Consequently, the equation of motion is nonlinear, with non constant coefficients and a Coriolis acceleration term. Phenomena associated with overburden to self weight ratio, motion triggering, impulsive energy dissipation, amplitude dependency of damping and period of vibration, and scale effect are discussed, contributing to a more complete understanding of experimental observations and to an estimation of system parameters based on the wall characteristics, such as intermediate hinge height and energy damping, necessary to perform nonlinear time history analyses. A comparison to a simple standing, or parapet, wall is developed in order to better highlight the characteristics of this assembly.

• Journal of the Korea Safety Management & Science
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• v.5 no.3
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• pp.107-119
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• 2003

Expectation and interest about e-CRM are rising for more efficient customer management in on-line including electronic commerce. The decision-making tree can be used usefully as the data mining technology for e-CRM. In this paper, the representative decision making techniques, CART, C4.5, CHAID analyzed the differences in personalization point of view with actuality customer data through an experiment. With these analysis data, it is proposed a new decision-making tree system that has big advantage in personalization techniques. Through new system, it can get following advantage. First, it can form superior model more qualitatively in personalization by adding individual's weight value. Second it can supply information personalized more to customer. Third, it can have high position about customer's loyalty than other site of similar types of business. Fourth, it can reduce expense that cost marketing and decision-making. Fifth, it becomes possible that know that customer through smooth communication with customer who use personalized service wants and make from goods or service's quality to more worth thing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.104-109
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• 2006

We can offer suitable information to users analyzing the pattern of users. An association rule is one of data mining techniques which can discover the pattern. We use an association rule which considers the web page visiting time and we should the pattern analyse of users. The offered method puts the weights in Web page visiting time of the user and produces an association rule. Weight is web page visiting time unit divide to total of web page visiting time. We offer rather meaningful result the association rule by Apriori algorithm. This method that proposes in the paper offers rather meaningful result Apriori algorithm

• Geomechanics and Engineering
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• v.17 no.6
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• pp.527-534
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• 2019

There have been developed a number of methods to assess the abrasivity of rock materials with the increased use of mechanized rock excavation. These methods range from determination of abrasive and hard mineral content using petrographic thin section analysis to weight loss or development of wear flat on a specified cutting tool. The Cerchar abrasivity index (CAI) test has been widely accepted for the assessment of rock abrasiveness. This test has been considered to provide a reliable indication of rock abrasiveness for isotropic rocks. However, a great amount of rocks in nature are anisotropic. Hence, viability assessment of Cerchar abrasivity test for the anisotropic rocks is investigated in this research. The relationship between CAI value and quartz content for the isotropic rocks is well known in literature. However, a correlation between EQ, F-Schimazek value, Rock Abrasivity Index (RAI) and CAI of anisotropic rocks such as phyllite was done first time in literature with this research. The results obtained with this research show F-Schimazek values and RAI values should be considered when determination of the abrasivity of anisotropic rocks instead of just using Cerchar scratch test.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1084-1087
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• 2013

텍스트마이닝은(Text mining) 바이오분야에서 사용되는 도구 중 하나이다. 본 논문에서는 전립선암(Prostate cancer)과 관련된 질병 유전자(Disease gene)를 찾기 위해 텍스트마이닝을 이용하여 유전자 네트워크(Gene-network)를 구축하였다. 추가적으로 구글(Google) 검색을 통해 네트워크 내의 유전자 노드(Node)들 사이의 간선(Edge)에 새로운 가중치(Weight)를 추가하고 네트워크를 재구성하였다. 구축된 네트워크에서 노드와 노드 사이의 가중치를 기반으로 전립선암과 관련된 질병 유전자를 추출하였다. 본 논문의 방법은 성공적으로 네트워크를 구축하고 질병 유전자를 찾았으며, 구글 데이터를 사용하지 않고 네트워크를 구축하는 경우보다 더 높은 정확성을 입증했다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.6
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• pp.677-682
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• 2014

In the present study, a decision tree and artificial neural network were used to determine critical design parameters for lithium ion batteries and compare their performances. First, a design method that used a decision tree-artificial neural network model was used to determine the major design factors among early pole plate design factors that showed nonlinearity. Then, the artificial neural network was used to implement a weighted value analysis of the importance of the design factors and their effect on the current density. The second method involved the use of an artificial neural network model to construct artificial networks without separate determinations of the major early design factors to analyze the connections and weighted values related to the current density.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.209-217
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• 2016

Recently, the outdoor activities were increased in accordance with economic growth and improved quality of life. In addition, weather and outdoor activities are closely related. Currently, Outdoor Activities decisions are determined by the Korea Meteorological Administrator's forecasts and subjective experience. Therefore, we need the analysis method that can provide a basis for the decision on outdoor activities based on meteorological information. In this paper, we propose an algorithm that can analyze meteorological information to support decision-making outdoor activities. And the algorithm is based on the data mining. In addition, we have constructed a baseball game schedule with automatic weather system's observation data in the training data. We verified the improved performance of the proposed algorithm.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.51-58
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• 2018

As the amount of users and data of NS explosively increased, research based on SNS Big data became active. In social mining, Latent Dirichlet Allocation(LDA), which is a typical topic model technique, is used to identify the similarity of each text from non-classified large-volume SNS text big data and to extract trends therefrom. However, LDA has the limitation that it is difficult to deduce a high-level topic due to the semantic sparsity of non-frequent word occurrence in the short sentence data. The BTM study improved the limitations of this LDA through a combination of two words. However, BTM also has a limitation that it is impossible to calculate the weight considering the relation with each subject because it is influenced more by the high frequency word among the combined words. In this paper, we propose a technique to improve the accuracy of existing BTM by reflecting semantic relation between words.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.970-977
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• 2020

The collaborative filtering recommendation technique has been the most widely used since the beginning of e-commerce companies introducing the recommendation system. As the online purchase of products or contents became an ordinary thing, however, recommendation simply applying purchasers' ratings led to the problem of low accuracy in recommendation. To improve the accuracy of recommendation, in this paper suggests the method of collaborative filtering that analyses product reviews and uses them as a weighted value. The proposed method refines product reviews with text mining to extract features and conducts sentiment analysis to draw a sentiment score. In order to recommend better items to user, sentiment weight is used to calculate the predicted values. The experiment results show that higher accuracy can be gained in the proposed method than the traditional collaborative filtering.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.343-349
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• 2022

We intend to use topic modeling to identify radiation-themed papers published from 1989 to 2022 and analyze the relevance and weight between topics. This study analyzed topics derived from national subjects for 717 papers published until recently in 2022 to contribute to the revitalization of research in the field of radiation. Through text mining, overall research trends on the subject distribution of the study were analyzed, and five topics were derived through topic modeling. First, among the papers to be analyzed, a total of 1,675 words were frequency-analyzed through the preprocessing process of key words in a total of 717 papers centered on keywords. Second, as a result of analyzing topics based on the association of constituent words for five topics, it was found that studies focused on minimizing dose in the range that does not degrade image quality in the fields of radiation, image, CT clinical. In addition, it was found that various studies were mainly conducted in the MRI, and the study of ultrasound in various areas of disease analysis was actively attempted.