• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.461-474
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• 2020

Korea launched Geostationary Environmental Monitoring Satellite (GEMS), a UV/visible spectrometer that measure pollution gases on 18 February 2020. Because satellite retrieval is an ill-posed inverse solving process, the validation with ground-based measurements or other satellite measurements is essential to obtain reliable products. For this purpose, satellite-based OMI and OMPS total column ozone (TCO), and ground-based Pandora TCO in Busan and Seoul were selected for future GEMS validation. First of all, the goal of this study is to validate the ground ozone data using characteristics that satellite data provide coherent ozone measurements on a global basis, although satellite data have a larger error than the ground-based measurements. In the cross validation between Pandora and OMI TCO, we have found abnormal deviation in ozone time series from Pandora #29 observed in Seoul. This shows that it is possible to perform inverse validation of ground data using satellite data. Then OMPS TCO was compared with verified Pandora TCO. Both data shows a correlation coefficient of 0.97, an RMSE of less than 2 DU and the OMPS-Pandora relative mean difference of >4%. The result also shows the OMPS-Pandora relative mean difference with SZA, TCO, cross-track position and season have insignificant dependence on those variables.In addition, we showed that appropriate thresholds depending on the spatial resolution of each satellite sensor are required to eliminate the impact of the cloud on Pandora TCO.

• Journal of Soil and Groundwater Environment
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• v.13 no.5
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• pp.20-32
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• 2008

Runoff characteristics of the Oedocheon in Jeju island were investigated using the long-term stream stage monitoring data. At the Cheonah valley in the upstream area and Oedocheon downstream, annual runoff occurred 21 and 12 times, respectively, and their average runoff periods were 21 days and 12 days, respectively. Stream stage response time to rainfall was 4 hours, and storm-water transfer from the upstream, Cheonah valley, to the Oedocheon downstream took about 2 hours. The stream discharge measurements had been carried out from Feb. 2004 to Jul. 2005, and showed that normal discharge of the Oedocheon was 0.39 $m^3$/sec in average. Stage-discharge curves were developed to estimate base flow (normal discharge) and (direct) surface runoff. The base flow separations by a numerical filtering technique illustrated that annual surface runoff and base flow accounted respectively for 31.8${\sim}$36.5%, 63.5${\sim}$68.2% of the total stream discharge.

• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.182-191
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• 2015

The Korean government introduced an automated speed enforcement system (ASES), which uses traffic enforcement cameras, to counteract safety issues that are caused by speeding. As the information of the traffic enforcement camera locations is provided to the drivers via navigation systems and mobile applications in a timely manner, drivers can avoid enforcement by momentarily diminishing their speeds only near the camera locations. To prevent drivers' evasional behavior and improve the effectiveness of ASES, section control, which enforces speeding vehicles by measuring their average travel speeds over a stretch of road and checking against the speed limit, has been recently implemented. In this study, Section Speed Enforcement Zone and Comparison Zone are compared in terms of traffic stream characteristics under free flow conditions. To this end, loop detector data were obtained from the three study sites and analyzed. The study results demonstrated that drivers maintain their speeds below the speed limit over the enforcement section with a lower variance of speeds.

• The Journal of Engineering Geology
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• v.27 no.3
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• pp.217-231
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• 2017

The subsidence of ground in urban area can be caused by the occurrence of the cavity and the change in ground volumetric water content. The objective of this study is the detection of abnormal area of ground in urban area where the cavity or the change in ground volumetric water content is occurred by the ground penetrating radar signal. GPR survey is carried out on the test bed with a circular buried object. From the GPR survey, the signals filtered by the bandpass filtering are measured, and the methods consisting of gain function, time zero, background removal, deconvolution and display gain are applied to the filtered signals. As a result of application of the signal processing methods, the polarity of signal corresponds with the relation of electrical impedance of the cavity and the ground in test bed. In addition, the relative permittivity calculated by GPR signal is compared with that of predicted by volumetric water content of the test bed. The relative permittivities obtained from two different methods show similar values. Therefore, the abnormal area where the change in ground volumetric water content is occurred can be detected from the results of the GPR survey in case the depth of underground utilities is known. Signal processing methods and estimation of relative permittivity performed in this study may be effectively used to detect the abnormal area of ground in urban area.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.3
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• pp.249-255
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• 2017

The finger vein recognition technology is a method to acquire a finger vein image by illuminating infrared light to the finger and to authenticate a person through processes such as feature extraction and matching. In order to recognize a finger vein, a 2D mask-based two-dimensional convolution method can be used to detect a finger edge but it takes too much computation time when it is applied to a low cost micro-processor or micro-controller. To solve this problem and improve the recognition rate, this study proposed an extraction method for the region of interest based on virtual core points and moving average filtering based on the threshold and absolute value of difference between pixels without using 2D convolution and 2D masks. To evaluate the performance of the proposed method, 600 finger vein images were used to compare the edge extraction speed and accuracy of ROI extraction between the proposed method and existing methods. The comparison result showed that a processing speed of the proposed method was at least twice faster than those of the existing methods and the accuracy of ROI extraction was 6% higher than those of the existing methods. From the results, the proposed method is expected to have high processing speed and high recognition rate when it is applied to inexpensive microprocessors.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.60-70
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• 2011

Conventional content management systems are independently developed for a specific field in general. Therefore usage of contents for the CMS will be limited to the corresponding CMS field. These characteristics might reveal a defect that CMS could not support effectively in exchange and sharing of information between CMSs. On the other hand, metadata standardization shows big differences in method and representation for the fields of CMS because all metadata standardizations are variously performed according to applications of them. There are lots differences that make interoperability between CMSs impossible. In this paper, we propose a novel metadata schema based on METS(metadata encoding and transmission standard) so that metadata standardization can be fulfilled in reality and solved the problem of duplicated contents created from different CMSs. This framework of integrated metadata proposed here can offer an interoperability between contents created by different CMSs, and discard duplicated contents. As a result of the proposed technology, we obtain 0.5% duplication rate from traditional 10.3%. In addition the filtering ability of duplicated contents shows from 92% to 96%, which proves the effectiveness and stability of the proposed technology.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.341-351
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• 2003

Digital image watermarking is the method that can protect the copyright of the image by embedding copyright information, which is called watermark. Watermarking must have robustness to intentional or unintentional data changing, called attack. The conventional watermarking schemes are robust to waveform attacks such as image compression, filtering etc. However, they are vulnerable to geometrical attacks such as rotation, scaling, translation, and cropping. Accordingly, this paper proposes new watermarking scheme that is robust to geometrical attacks by using invariant centroid. Invariant centroid is the gravity center of a central area in a gray scale image that remains unchanged even when the image is attacked by RST including cropping and proposed scheme uses invariant centroids of original and inverted image as the template. To make geometrically invariant domain, template and angle compensated Log -Polar Map(LPM) is used. Then Discrete Cosine Transform(DCT) is performed and the watermark is embedded into the DCT coefficients. Futhermore, to prevent a watermarked image from degrading due to interpolation during coordinate system conversion, only the image of the watermark signal is extracted and added to the original image. Experimental results show that the proposed scheme is especially robust to RST attacks including cropping.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.318-327
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• 2008

With the advance of information technologies and the spread of Internet use, the volume of usable information is increasing explosively. A content recommendation system provides the services of filtering out information that users do not want and recommending useful information. Existing recommendation systems analyze the records and patterns of Web connection and information demanded by users through data mining techniques and provide contents from the service provider's viewpoint. Because it is hard to express information on the users' side such as users' preference and lifestyle, only limited services can be provided. The semantic Web technology can define meaningful relations among data so that information can be collected, processed and applied according to purpose for all objects including images and documents. The present study proposes a content recommendation search system that can update and reflect personalized profiles dynamically in semantic Web environment. A personalized profile is composed of Collector that contains the characteristics of the profile, Aggregator that collects profile data from various collectors, and Resolver that interprets profile collectors specific to profile characteristic. The personalized module helps the content recommendation server make regular synchronization with the personalized profile. Choosing music as a recommended content, we conduct an experience on whether the personalized profile delivers the content to the content recommendation server according to a service scenario and the server provides a recommendation list reflecting the user's preference and lifestyle.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.183-200
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• 2009

Collaborative Filtering is one of the most used recommender systems. However, basically it cannot be used to recommend new products to customers because it finds products only based on the purchasing history of each customer. In order to cope with this shortcoming, many researchers have proposed the hybrid recommender system, which is a combination of collaborative filtering and content-based filtering. Content-based filtering recommends the products whose attributes are similar to those of the products that the target customers prefer. However, the hybrid method is used only for the limited categories of products such as music and movie, which are the products whose attributes are easily extracted. Therefore it is essential to find a more effective approach to recommend to customers new products in any category. In this study, we propose a new recommendation method which applies centrality concept widely used to analyze the relational and structural characteristics in social network analysis. The new products are recommended to the customers who are highly likely to buy the products, based on the analysis of the relationships among products by using centrality. The recommendation process consists of following four steps; purchase similarity analysis, product network construction, centrality analysis, and new product recommendation. In order to evaluate the performance of this proposed method, sales data from H department store, one of the well.known department stores in Korea, is used.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.151-166
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• 2020

A recommender system is a system that recommends products or services that best meet the preferences of each customer using statistical or machine learning techniques. Collaborative filtering (CF) is the most commonly used algorithm for implementing recommender systems. However, in most cases, it only uses purchase history or customer ratings, even though customers provide numerous other data that are available. E-commerce customers frequently use a search function to find the products in which they are interested among the vast array of products offered. Such search keyword data may be a very useful information source for modeling customer preferences. However, it is rarely used as a source of information for recommendation systems. In this paper, we propose a novel hybrid CF model based on the Doc2Vec algorithm using search keywords and purchase history data of online shopping mall customers. To validate the applicability of the proposed model, we empirically tested its performance using real-world online shopping mall data from Korea. As the number of recommended products increases, the recommendation performance of the proposed CF (or, hybrid CF based on the customer's search keywords) is improved. On the other hand, the performance of a conventional CF gradually decreased as the number of recommended products increased. As a result, we found that using search keyword data effectively represents customer preferences and might contribute to an improvement in conventional CF recommender systems.