• Computers and Concrete
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• v.19 no.1
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• pp.99-110
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• 2017

In this paper, the effect of normal load on the failure mechanism of echelon joint has been studied using PFC2D. In the first step, calibration of PFC was undertaken with respect to the data obtained from experimental laboratory tests. Then, six different models consisting various echelon joint were prepared and tested under two low and high normal loads. Furthermore, validation of the simulated models were cross checked with the results of direct shear tests performed on non-persistent jointed physical models. The simulations demonstrated that failure patterns were mostly influenced by normal loading, while the shear strength was linked to failure mechanism. When ligament angle is less than $90^{\circ}$, the stable crack growth length is increased by increasing the normal loading. In this condition, fish eyes failure pattern occur in rock bridge. With higher ligament angles, the rock bridge was broken under high normal loading. Applying higher normal loading increases the number of fracture sets while dilation angle and mean orientations of fracture sets with respect to ligament direction will be decreased.

• Structural Engineering and Mechanics
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• v.68 no.4
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• pp.497-505
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• 2018

Three points bending flexural test was modeled numerically to study the crack propagation in the pre-cracked beams. The pre-existing edge cracks in the beam models were considered to investigate the crack propagation and coalescence paths within the modeled samples. The effects of particle size on the single edge-notched round bar in bending test were considered too. The results show that Failure pattern is constant by increasing the ball diameter. Tensile cracks are dominant mode of failure. These crack initiates from notch tip, propagate parallel to loading axis and coalescence with upper model boundary. Number of cracks increase by decreasing the ball diameter. Also, tensile fracture toughness was decreased with increasing the particle size. In the present study, the influences of particles sizes on the cracks propagations and coalescences in the brittle materials such as rocks and concretes are numerically analyzed by using a three dimensional particle flow code (PFC3D). These analyses improve the understanding of the stability of rocks and concretes structures such as rock slopes, tunnel constructions and underground openings.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.147-158
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• 2009

Recently, the data model in stream data environment has massive, continuous, and infinity properties. However the stream data processing like query process or data analysis is conducted using a limited capacity of disk or memory. In these environment, the traditional frequent pattern discovery on transaction database can be performed because it is difficult to manage the information continuously whether a continuous stream data is the frequent item or not. In this paper, we propose the method which we are able to predict the frequent items using the regression model on continuous stream data environment. We can use as a prediction model on indefinite items by constructing the regression model on stream data. We will show that the proposed method is able to be efficiently used on stream data environment through a variety of experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.349-352
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• 2000

As a lot of people have used electronic commerce, many shopping malls have appeared on the Interne and the shopping information in them has been enormous. So, the need for a system to recommend product to customers is on the increase so as to reduce time and efforts for shopping. In this paper, we suppose a Product Recommender System which is constructed by applying data mining techniques to web for files and analyzing customer's action pattern, customer's profile and product purchase data. This system offers convenience that customers can get their desired information easily, by sending e-mail or mail and recommending web pages when they visit a shopping mall.

• Proceedings of the KSRS Conference
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• v.2
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• pp.706-709
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• 2006

Cancer is one of the major causes of death; however, the survival rate can be increased if discovered at an early stage for timely treatment. According to the statistics of the World Health Organization of 2002, breast cancer was the most prevalent cancer for all cancers occurring in women worldwide, and it account for 16.8% of entire cancers inflicting Korean women today. In order to classify the type of breast cancer whether it is benign or malignant, this study was conducted with the use of the discriminant analysis and the decision tree of data mining with the breast cancer data disclosed on the web. The discriminant analysis is a statistical method to seek certain discriminant criteria and discriminant function to separate the population groups on the basis of observation values obtained from two or more population groups, and use the values obtained to allow the existing observation value to the population group thereto. The decision tree analyzes the record of data collected in the part to show it with the pattern existing in between them, namely, the combination of attribute for the characteristics of each class and make the classification model tree. Through this type of analysis, it may obtain the systematic information on the factors that cause the breast cancer in advance and prevent the risk of recurrence after the surgery.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.249-255
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• 2014

Recently, creation and sharing of information make progress actively through the SNS(Social Network Service) such as twitter, facebook and so on. It is necessary to extract the knowledge from aggregated information and data mining is one of the knowledge based approach. Especially, emotion analysis is a recent subdiscipline of text classification, which is concerned with massive collective intelligence from an opinion, policy, propensity and sentiment. In this paper, We propose the emotion prediction method, which extracts the significant key words and related key words from SNS paragraph, then predicts the emotion using these extracted emotion features.

• Journal of Korea Foundry Society
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• v.8 no.4
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• pp.446-452
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• 1988

To obtain detailed information on the metastable and the equilibrium phases in rapidly solidified Al-(Fe,Ce) alloys, analysis of X-ray diffraction pattern has been carried out. It has been found that the metastable phase formed in Al-Fe alloys including up to 6wt%Fe is $Al_6Fe$ and the equilibrium phase is $Al_3Fe$. Any X-ray diffraction peak corresponding to the equilibrium phase $Al_{13}Fe_4$ has not been observed during aging. In Al-4wt%Fe alloy, which is ribbon shape with thickness less than $70\;{\mu}m$, aged at $400^{\circ}C$ for 1h after rapid solidification, unidentified phase has been found. In Al-4wt%Ce alloy, only X-ray diffraction peak corresponding to the equilibrium phase, $Al_4Ce$ has been observed. It has been found that the metastable phase Formed in Al-Fe-Ce alloys including up to 6wt% Fe and 4wt% Ce is $Al_6Fe$ and the equilibrium phases are $Al_3Fe$ and $Al_{10}CeFe_2$.

• Journal of Aerospace System Engineering
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• v.14 no.2
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• pp.50-56
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• 2020

In this study, we investigated whether long short-term memory (LSTM) can be used in the future to predict F10.7 index data; the F10.7 index is a space environment factor affecting atomic oxygen erosion. Based on this, we compared the prediction performances of LSTM, the Autoregressive integrated moving average (ARIMA) model (which is a traditional statistical prediction model), and the similar pattern searching method used for long-term prediction. The LSTM model yielded superior results compared to the other techniques in the prediction period starting from the max/min points, but presented inferior results in the prediction period including the inflection points. It was found that efficient learning was not achieved, owing to the lack of currently available learning data in the prediction period including the maximum points. To overcome this, we proposed a method to increase the size of the learning samples using the sunspot data and to upgrade the LSTM model.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.676-683
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• 2003

A laboratory experiment using artificial fracture rocks was used to understand the 3-dimensional dispersion of a tracer and the mixing process in a fractured network. In this experiment, 12cm polystyrene foam cubes with two electrodes for monitoring electric conductivity (EC) were used as artificial fractured rocks. Distilled water with 0.5mS/m was used as a tracer in water with 35mS/m and the difference of EC between the tracer and the water was monitored by a multipoint simultaneous measurement system of electrical resistance. The results showed that even if the fracture arrangement pattern was not straight in the direction of the flow, the tracer did not diffuse along individual fractures and an oval tracer plume, which was the distribution of tracer concentrations, tended to be form in the direction of the flow. The vertical cross section of the tracer distribution showed small diffusivity in the vertical direction. The calculated total tracer volume passing through each measurement point in the horizontal cross section showed while that the solute passed through measurement points near the direction of hydraulic gradient and in other directions, the passed tracer volumes were small. Using Peclet number as a criterion, it was found that the mass distribution at the fracture intersection was controlled in the stage of transition between the complete mixing model and the streamline routing model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.163-172
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• 2012

In this study, It is assumed that customers are both usage unit of spare parts and stores of displaying and selling the goods that are installation unit of having the spare parts. The demand pattern through the effective order of spare parts and issue list in installation unit is investigated based on the assumption. Current ASL (Authorized Stockage List) selection of the army has been conducted in the way of using the analysis result of real usage experiences on spare parts used during the Korea War. For this study, ASL selection criteria and procedures based on army regulations and field manuals are specified. Since the traditional method does not presents the association analysis on spare parts used for the current equipment operating and does not have the clear criterion and analysis system about the ASL selection, in order to solve these problems, it was carried out that the association rule is employed for analyzing relationship between the effective order and issue list of the spare parts in point of the spare parts between usage unit and occurring month about purchase spare parts based on the star-schema table. Finally the new ASL selection way using the analysis result is proposed.