• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.177-197
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• 2001

This paper is aimed at proposing a data mining-driven analysis to manage the customer defection rate in the bank. After 1997 IMF crisis, Korean banks were suffering from hard-pressed restructuring. At the heart of such restructuring effects, there was the need to manage the customer more effectively than ever. So far, many banks in Korea used to a poor management of customers without any highly-skillful techniques. In line with this argument, we propose several data mining techniques to determine more effective technique far managing customer deflection. We applied three data mining techniques such as logit model, neural network, and C5.0. Experiment data were collected from personal deposit account data of a specific bank in Korea. After experiments, we found that C5.0 showed more robust performance compared to other two techniques. On the basis of those experiment results, we proposed customer defection management policy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1527-1537
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• 2016

As increasing of smartphone penetration over the world, various mobile payment services have been emerged and fraud transactions have drastically increased. Although many financial companies have deployed security solutions to detect fraud transactions in on/off-line environment, mobile payment services still lack fraud detection solutions and researches. The mobile payment is mainly comprised of micro-payments and payment environment is different from other payments, so mobile-specialized fraud detection is needed. In this paper, we propose a FDS (Fraud Detection System) based on data mining for mobile payment services. The method of this paper is applied to the real data provided by a PG (Payment Gateway) company in Korea. The proposed FDS consists of two phases; (1) the first phase is focused on classifying transactions at high speed (2) the second is designed to detect abnormal transactions with high accuracy. We could detect 13 transactions per second with 93% accuracy rate.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.205-215
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• 2024

Manually mapping fractures in construction stone mines is challenging, time-consuming, and hazardous. In this method, there is no physical access to all points. In contrast, digital image processing offers a safe, cost-effective, and fast alternative, with the capability to map all joints. In this study, two methods of detecting the trace of discontinuities using image processing in construction stone mines are presented. To achieve this, we employ two modified Hough transform algorithms and the degree of neighborhood technique. Initially, we introduced a method for selecting the best edge detector and smoothing algorithms. Subsequently, the Canny detector and median smoother were identified as the most efficient tools. To trace discontinuities using the mentioned methods, common preprocessing steps were initially applied to the image. Following this, each of the two algorithms followed a distinct approach. The Hough transform algorithm was first applied to the image, and the traces were represented through line drawings. Subsequently, the Hough transform results were refined using fuzzy clustering and reduced clustering algorithms, along with a novel algorithm known as the farthest points' algorithm. Additionally, we developed another algorithm, the degree of neighborhood, tailored for detecting discontinuity traces in construction stones. After completing the common preprocessing steps, the thinning operation was performed on the target image, and the degree of neighborhood for lineament pixels was determined. Subsequently, short lines were removed, and the discontinuities were determined based on the degree of neighborhood. In the final step, we connected lines that were previously separated using the method to be described. The comparison of results demonstrates that image processing is a suitable tool for identifying rock mass discontinuity traces. Finally, a comparison of two images from different construction stone mines presented at the end of this study reveals that in images with fewer traces of discontinuities and a softer texture, both algorithms effectively detect the discontinuity traces.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.19-33
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• 2009

With the continuously increasing volume of e-commerce transactions, it is now popular to buy some products and to evaluate them on the World Wide Web. The product reviews are very useful to customers because they can make better decisions based on the indirect experiences obtainable through the reviews. Product Reviews are results expressing customer's sentiments and thus are divided into positive reviews and negative ones. However, as the number of reviews in on-line shopping increases, it is inefficient or sometimes impossible for users to read all the relevant review documents. In this paper, we present a sentiment analysis algorithm for automatically classifying subjective opinions of customer's reviews using opinion mining technology. The proposed algorithm is to focus on product reviews of on-line shopping, and provides summarized results from large product review data by determining whether they are positive or negative. Additionally, this paper introduces an automatic review analysis system implemented based on the proposed algorithm, and also present the experiment results for verifying the efficiency of the algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.529-538
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• 2013

Coastline is the most dynamic part of seascape since its shape is affected by various factors. Coastal zone is an area with immense geological, geomorphological and ecological interest. Monitoring coastal change is very important for safe navigation, coastal resource management. This paper shows a result of monitoring coastal morphological changes using Remote Sensing and GIS. Study was carried out to obtain intensity of erosion, deposition and sand bar movement in the Red River Delta. Satellite images of ALOS/AVNIR-2 and Landsat were used for the monitoring of coastal morphological changes over the period of 1975 to 2009. Band rationing and threshold technique was used for the coastline extraction. Tidal levels at the time of image acquisition varied from -0.89m to 2.87m. Therefore, coastline from another image at a different tidal level in the same year was considered to get the corrected coastline by interpolation technique. A series of points were generated along the coastal line from 1975 image and were established as reference points to see the change in later periods. The changes were measured in Euclidean distances from these reference points. Positive values represented deposition to the sea and negative values are erosion. The result showed that the Red river delta area expanded to the sea 3500m in Red river mouth, and 2873m in Thai Binh river mouth from 1975 to 2009. The erosion process occurred continuously from 1975 up to now with the average magnitude 23.77m/year from 1975 to 1989 and 7.85m/year from 2001 to 2009 in Giao Thuy area. From 1975 to 2009, total 1095.2ha of settlement area was eroded by sea. On the other hand, land expanded to the sea in 4786.24ha of mangrove and 1673.98ha of aquaculture.

• Economic and Environmental Geology
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• v.30 no.1
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• pp.25-33
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• 1997

The purpose of this study is to examine the feasibility of using stable isotopes as a hydrologic tracer, and to elucidate the groundwater circulation system and the source of S component dissolved in thermal water of the Chonju Jukrim thermal spring district based on the O, H and S isotopic variabilities of environmental materials including bedrock, rainwater, surface water, shallow subsurface water and thermal spring water. The ${\delta}^{18}O$ and ${\delta}D$ of subsurface waters and surface water show highly restricted range and plotted on the same meteoric water line as a ${\delta}D=8{\delta}^{18}O+19$ line, and derivate from the mean annual isotopic composition of the rain water but are analogous to those of rain waters precipitated during winter season, indicating that ground waters are originated from the meteoric water and are strongly affected by the seasonal variation of air mass. Thermal spring waters are more depleted in ${\delta}^{18}O$ and ${\delta}D$ than those of shallow ground water and surface water. It can be explained by the difference of recharge area. The hydrochemical properties of subsurface waters and surface water devide into two groups: $Ca(HCO_3)_2$ type including shallow subsurface water and surface water, and $Na(HCO_3)$ type of thermal spring waters. The ${\delta}^{34}S$ values of thermal spring water show very high positive and quitely distinct from those of shallow subsurface water and surface water that are similar to those of bed rocks, indicating that sulfate dissolved in thermal spring water has not only a terrigenic origin, but also originates partially from the foreign source containing very heavy ${\delta}^{34}S$ component such as an ancient sea water. However, the presence of $H_2S$ can not be ignore the affact of the isotopic fractionation to explaine the heavy ${\delta}^{34}S$ of thermal spring water. Overall, the Oxygen and Hydrogen stable isotopes can identify the source and the circulation system of the natural waters and the S-isotopes can provide a crucial clue on tracing the dissolved material transports in the circulation system of the natural water.

• Structural Engineering and Mechanics
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• v.66 no.4
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• pp.453-463
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• 2018

Three points bending flexural test was modelled numerically to study the crack propagation in the pre-cracked beams. The pre-existing double internal cracks inside the beam models were considered to investigate the crack propagation and coalescence paths within the modelled samples. Notch configuration effects on the failure stress were considered too. This numerical analysis shown that the propagation of wing cracks emanating from the tips of the pre-existing internal cracks caused the final breaking of beams specimens. It was also shown that when two notches were overlapped, they both mobilized in the failure process and the failure stress was decreased when the notches were located in centre line. However, the failure stress was increased by increasing the bridge area angle. Finally, it was shown that in all cases, there were good agreements between the discrete element method results and, the other numerical and experimental results. In this research, it is tried to improve the understanding of the crack propagation and crack coalescence phenomena in brittle materials which is of paramount importance in the stability analyses of rock and concrete structures, such as the underground openings, rock slopes and tunnel construction.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.594-597
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• 2004

The ground subsidence that occurred in an abandoned coal mining area, Gaeun, Korea, was observed by using 25 JERS-1 SAR interferograms from November 1992 to October 1998. We estimated the subsidence on a subset of image pixels corresponding to point-wise permanent scatters (PSs) by exploiting a long temporal series of interferometric phases. The results were compared it with a distribution map of in situ examined crack level. PSs were identified by means of amplitude dispersion index and coherence of the interferograms. The measured subsidence rate represented the average velocity in a period of image acquisition and excluded complex nonlinear displacements such as an abrupt collapse. The mean line-of-sight velocity in the study area is 0.19cm/yr and an r.m.s. error is 0.18cm/yr. The center of the abandoned Gaeun coal mine (0.49cm/yr) and the area near to the Gaeun station (1.66cm/yr) were observed as most rapidly subsiding areas.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1171-1171
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• 2001

Quantitative analysis is an important requirement in exploration, mining and processing of minerals. There is an increasing need for the use of quantitative mineralogical data to assist with bore hole logging, deposit delineation, grade control, feed to processing plants and monitoring of solid process residues. Quantitative analysis using X-Ray Powder Diffraction (XRD) requires fine grinding and the addition of a reference material, or the application of Rietveld analysis to XRD patterns to provide accurate analysis of the suite of minerals present. Whilst accurate quantitative data can be obtained in this manner, the method is time consuming and limited to the laboratory. Mid infrared when combined with multivariant analysis has also been used for quantitative analysis. However, factors such as the absorption coefficients and refractive index of the minerals requires special sample preparation and dilution in a dispersive medium, such as KBr to minimize distortion of spectral features. In contrast, the lower intensity of the overtones and combinations of the fundamental vibrations in the near infrared allow direct measurement of virtually any solid without special sample preparation or dilution. Thus Near Infrared Spectroscopy (NIR) has found application for quantitative on-line/in line analysis and control in a range of processing applications which include, moisture control in clay and textile processing, fermentation processes, wheat analysis, gasoline analysis and chemicals and polymers. It is developing rapidly in the mineral exploration industry and has been underpinned by the development of portable NIR spectrometers and spectral libraries of a wide range of minerals. For example, iron ores have been identified and characterized in terms of the individual mineral components using field spectrometers. Data acquisition time of NIR field instruments is of the order of seconds and sample preparation is minimal. Consequently these types of spectrometers have great potential for in-line or on-line application in the minerals industry. To demonstrate the applicability of NIR field spectroscopy for quantitative analysis of minerals, a specific example on the quantification of lateritic bauxites will be presented. It has been shown that the application of Partial Least Squares regression analysis (PLS) to the NIR spectra can be used to quantify chemistry and mineralogy in a range of lateritic bauxites. Important, issues such as sampling, precision, repeatability, and replication which influence the results will be discussed.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.