• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.1
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• pp.1-14
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• 2008

Eight comprehensive oceanographic cruises on a squared $30{\times}30\;km$ area have been made to investigate the short and long-term impacts on the water qualities due to the sand mining operations at Exclusive Economic Zone (EEZ) in the central Yellow Sea from 2004 to 2007. The area was categorized to 'Sand Mining Zone', 'Potentially Affected Zone', and 'Reference Zone'. The investigation covered suspended solids, nutrients (nitrate, nitrite, ammonium, phosphate), and chlorophyll-a in seawater and several parameters such as water temperature, salinity, pH, and ORP. Additionally, several intensive water collections were made to trace the suspended solids and other parameters along the turbid water by sand mining activities. The comprehensive investigation showed that suspended solids, nitrate, chlorophyll-a and ORP be sensitively responding parameters of seawater by sand mining operations. The intensive collection of seawater near the sand mining operation revealed that each parameter show different distribution pattern: suspended solids showed an oval-shaped distribution of the north-south direction of 8 km wide and the east-west direction of 5 km wide at the surface and bottom layers. On the other hand, phosphate showed so narrow distribution not to traceable. Also ammonium showed a limited distribution, but its boundary was connected to the high nitrate and chlorophyll-a concentrations with high N/P ratios. From the last 4 years of the comprehensive and intensive investigations, we found that suspended solids, ammonium, nitrate, chlorophyll-a, and ORP revealed the sensitive parameters of water quality for tracing the sand mining operations in seawater. Especially suspended solids and ORP would be useful tracers for monitoring the water qualities of remote area like EEZ in Yellow Sea.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.586-594
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• 2004

Because web documents become creation and disappearance rapidly, users require the recommend system that offers users to browse the web document conveniently and correctly. One largely untapped source of knowledge about large data collections is contained in the cumulative experiences of individuals finding useful information in the collection. Recommendation systems attempt to extract such useful information by capturing and mining one or more measures of the usefulness of the data. The existing Information Filtering system has the shortcoming that it must have user's profile. And Collaborative Filtering system has the shortcoming that users have to rate each web document first and in high-quantity, low-quality environments, users may cover only a tiny percentage of documents available. And dynamic recommendation system using the user browsing pattern also provides users with unrelated web documents. This paper classifies these web documents using the similarity between the web documents under the web document type and extracts the user browsing sequential pattern DB using the users' session information based on the web server log file. When user approaches the web document, the proposed Dynamic recommendation system recommends Top N-associated web documents set that has high similarity between current web document and other web documents and recommends set that has sequential specificity using the extracted informations and users' session information.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.35-54
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• 2009

The recent economic crisis not only reduces the profit of department stores but also incurs the significance losses caused by the increasing late-payment rate of credit cards. Under this pressure, the scope of credit prediction needs to be broadened from the simple prediction of whether this customer has a good credit or not to the accurate prediction of how much profit can be gained from this customer. This study classifies the delinquent customers of credit card in a Korean department store into homogeneous clusters. Using this information, this study analyzes the repayment patterns for each cluster and develops the credit prediction system to manage the delinquent customers. The model presented by this study uses Kohonen network, which is one of artificial neural networks of data mining technique, to cluster the credit delinquent customers into clusters. Cox proportional hazard model is also used, which is one of survival analysis used in medical statistics, to analyze the repayment patterns of the delinquent customers in each cluster. The presented model estimates the repayment period of delinquent customers for each cluster and introduces the influencing variables on the repayment pattern prediction. Although there are some differences among clusters, the variables about the purchasing frequency in a month and the average number of installment repayment are the most predictive variables for the repayment pattern. The accuracy of the presented system leaches 97.5%.

• Economic and Environmental Geology
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• v.9 no.3
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• pp.143-156
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• 1976

The Cretaceous metal ore deposits in the Gyeongsang basin of Gyeongsangbuk-do are characterized by the formation of metallogenic provinces which show zonal distribution pattern around Yeonil province where pneumatolytic type is dominated and hydrothermal type are distributed in the order of decreasing temperature type outward. Some Cretaceous granitic rocks include zoned alkali feldspars which reflect rapid variation of $H_2O$ during emplacement and crystallization of the water-saturated granitic magma. The ore deposits are considered to be originated from upward transportation of ore solution from the excess of water exhausted from uprising magma, which seems to be intimately related to the fact that the majority of the ore deposits in Daegu area are cummulated around the granites including zoned alkali feldspars. In order to collect geochemical data necessary for geochemical exploration in the study area, certain trace elements were chosen as pathfinders from monzonite and soil in the vicinity of Dalsung Tungsten Mine by studying the dispersion patterns of trace elements: Ba and Sr show trends to decrease toward ore deposit while Cu, Pb, and Mo increase. Around mining area there are distributed apparently Equisetum arvense Linne and Mentha sachinensis Kudo which may be used as index plants. In the viewpoint of geologic structure, the trends of the ore veins in contact aureole around the Palgongsan granite body correspond with the pre- and syn- plutonism joint pattern in hornfels in the area.

• Korean Journal of Computational Design and Engineering
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• v.18 no.4
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• pp.250-257
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• 2013

This paper introduces a failure analysis procedure that underpins real-time fault prognosis. In the previous study, we developed a systematic eventization procedure which makes it possible to reduce the original data size into a manageable one in the form of event logs and eventually to extract failure patterns efficiently from the reduced data. Failure patterns are then extracted in the form of event sequences by sequence-mining algorithms, (e.g. FP-Tree algorithm). Extracted patterns are stored in a failure pattern library, and eventually, we use the stored failure pattern information to predict potential failures. The two practical case studies (marine diesel engine and SIRIUS-II car engine) provide empirical support for the performance of the proposed failure analysis procedure. This procedure can be easily extended for wide application fields of failure analysis such as vehicle and machine diagnostics. Furthermore, it can be applied to human health monitoring & prognosis, so that human body signals could be efficiently analyzed.

• Geomechanics and Engineering
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• v.13 no.4
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• pp.671-683
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• 2017

Groundwater control is a significant issue in most underground construction. An estimate of the inflow rate is required to size the pumping system, and treatment plant facilities for construction planning and cost assessment. An estimate of the excavation-induced drawdown of the initial groundwater level is required to evaluate potential environmental impacts. Analytical and empirical methods used in current engineering practice do not adequately account for the effect of the jointed-rock-mass anisotropy and heterogeneity. The impact of geostructural anisotropy of fractured rocks on tunnel inflows is addressed and the limitations of analytical solutions assuming isotropic hydraulic conductivity are discussed. In this paper the unexcavated Zagros tunnel route has been classified from groundwater flow point of view based on the combination of observed water inflow and numerical modeling results. Results show that, in this hard rock tunnel, flow usually concentrates in some areas, and much of the tunnel is dry. So the remaining unexcavated Zagros tunnel route has been categorized into three categories including high Risk, moderately risk and low risk. Results show that around 60 m of tunnel (3%) length can conduit the large amount of water into tunnel and categorized into high risk zone and about 45% of tunnel route has moderately risk. The reason is that, in this tunnel, most of the water flows in rock fractures and fractures typically occur in a clustered pattern rather than in a regular or random pattern.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.7-14
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• 2011

This paper discusses operational technique and effectiveness of Variable Speed Limits system that is implemented to control the traffic-flow on the Naebu Expressway. As the first step of the analysis, traffic data collected from vehicle detectors are corrected and smoothed. Applying a pattern analysis technique to the traffic data, the weekday traffic is classified into four different groups, and median of each group is calculated. Using three state variables, i.e., diverted traffic volume, average density and average speed, the conditions of roadway segments are determined. Computational outputs resulted from the application of the proposed model to the scenarios show that implementation of Variable Speed Limits system improved both safety and efficiency of the expressway. For the operational strategy, this paper also presents the change rate of the speed limit, and the effective duration of the speed limit according to the entering traffic volume.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.155-165
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• 2020

In this paper, we propose a smart thermostat temperature set-point control method based on machine learning and rule engine, which controls thermostat's temperature set-point so that it can achieve energy savings as much as possible without sacrifice of occupants' comfort while users' preference usage pattern is respected. First, the proposed method periodically mines data about how user likes for heating (winter)/cooling (summer) his or her home by learning his or her usage pattern of setting temperature set-point of the thermostat during the past several weeks. Then, from this learning, the proposed method establishes a weekly schedule about temperature setting. Next, by referring to thermal comfort chart by ASHRAE, it makes rules about how to adjust temperature set-points as much as low (winter) or high (summer) while the newly adjusted temperature set-point satisfies thermal comfort zone for predicted humidity. In order to make rules work on time or events, we adopt rule engine so that it can achieve energy savings properly without sacrifice of occupants' comfort. Through experiments, it is shown that the proposed smart thermostat temperature set-point control method can achieve better energy savings while keeping human comfort compared to other conventional thermostat.

• Smart Structures and Systems
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• v.22 no.4
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• pp.459-468
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• 2018

In this paper, the effect of non-persistent joints was determined on the behavior of concrete specimens subjected to biaxial loading through numerical modeling using particle flow code in two dimensions (PFC2D). Firstly, a numerical model was calibrated by uniaxial, Brazilian and triaxial experimental results to ensure the conformity of the simulated numerical model's response. Secondly, sixteen rectangular models with dimension of 100 mm by 100 mm were developed. Each model contains two non-persistent joints with lengths of 40 mm and 20 mm, respectively. The angularity of the larger joint changes from $30^{\circ}$ to $90^{\circ}$. In each configuration, the small joint angularity changes from $0^{\circ}$ to $90^{\circ}$ in $30^{\circ}$ increments. All of the models were under confining stress of 1 MPa. By using of the biaxial test configuration, the failure process was visually observed. Discrete element simulations demonstrated that macro shear fractures in models are because of microscopic tensile breakage of a large number of bonded discs. The failure pattern in Rock Bridge is mostly affected by joint overlapping whereas the biaxial strength is closely related to the failure pattern.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.10
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• pp.830-836
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• 2005

Application of microarray technologies which monitor simultaneously the expression pattern of thousands of individual genes in different biological systems results in a tremendous increase of the amount of available gene expression data and have provided new insights into gene expression during drug development, within disease processes, and across species. There is a great need of data mining methods allowing straightforward interpretation, visualization and analysis of the relevant information contained in gene expression profiles. Specially, classifying biological samples into known classes or phenotypes is an important practical application for microarray gene expression profiles. Gene expression profiles obtained from tissue samples of patients thus allowcancer classification. In this research, molecular classification of microarray gene expression data is applied for multi-class cancer using computational biology such gene selection, principal component analysis and fuzzy clustering. The proposed method was applied to microarray data from leukemia patients; specifically, it was used to interpret the gene expression pattern and analyze the leukemia subtype whose expression profiles correlated with four cases of acute leukemia gene expression. A basic understanding of the microarray data analysis is also introduced.