• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2121-2128
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• 2015

In this paper presents a method of extracting reliable and regions of interest (ROI) in barcode for the purpose of factory automation. backgrounds are separated based on directional components and the characteristics of detected patterns. post-processing is performed on candidate images with analysis of problems caused by blur, rotation and areas of high similarity. In addition, the resizing factor is used to achieve faster calculations through image resizing. The input images contained multiple product or barcode for application to diverse automation environments; a high extraction success rate is accomplished despite the maximum shooting distance of 80 cm. Simulations involving images with various shooting distances gave an ROI detection rate of 100% and a post-processing success rate of 99.3%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.79-86
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• 2009

This study proposed a method of detecting the facial area by calculating Euclidian distances among skin color elements and extracting the characteristics of the face. The proposed algorithm is composed of light calibration and face detection. The light calibration process performs calibration for the change of light. The face detection process extracts the area of skin color by calculating Euclidian distances to the input images using as characteristic vectors color and chroma in 20 skin color sample images. From the extracted facial area candidate, the eyes were detected in space C of color model CMY, and the mouth was detected in space Q of color model YIQ. From the extracted facial area candidate, the facial area was detected based on the knowledge of an ordinary face. When an experiment was conducted with 40 color images of face as input images, the method showed a face detection rate of 100%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.487-492
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• 2018

Recently, various applications for image processing have been ported to the mobile environment due to the expansion of the image shooting on the mobile device. However, in the case of extracting the image foreground, which is one of the most important functions of image synthesis, is difficult since it needs complex calculation. In this paper, we propose an video synthesis technique that can divide images captured by mobile devices into foreground / background and combine them in real time on target images. Considering the characteristics of mobile shooting, our system can extract automatically foreground of input video that contains weak motion when shooting. Using SIMD and GPGPU-based acceleration algorithms, SD-quality images can be processed on mobile in real time.

• Journal of KIISE:Databases
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• v.36 no.3
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• pp.169-179
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• 2009

Communication log data consist of communication events such as sending and receiving e-mail or instance message and visiting web sites, etc. Many countries including USA and EU enforce the retention of these data on the communication service providers for the purpose of investigating or detecting criminals through the Internet. Because size of the retained data is very large, the efficient method for extracting valuable information from the data is needed for Law Enforcement Authorities to use the retained data. This paper defines the Interactive Communication Sequence Patterns(ICSPs) that is the important information when each communication event in communication log data consists of sender, receiver, and timestamp of this event. We also define a Mining(FDICSP) problem to discover such patterns and propose a method called Fast Discovering Interactive Communication Sequence Pattern(FDICSP) to solve this problem. FDICSP focuses on the characteristics of ICS to reduce the search space when it finds longer sequences by using shorter sequences. Thus, FDICSP can find Interactive Communication Sequence Patterns efficiently.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.521-526
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• 2016

As on-line informal text data have massive in its volume and have unstructured characteristics in nature, there are limitations in applying traditional relational data model technologies for data storage and data analysis jobs. Moreover, using dynamically generating massive social data, social user's real-time reaction analysis tasks is hard to accomplish. In the paper, to capture easily the semantics of massive and informal on-line documents with unsupervised learning mechanism, we design and implement automatic topic extraction systems according to the mass of the words that consists a document. The input data set to the proposed system are generated first, using N-gram algorithm to build multiple words to capture the meaning of the sentences precisely, and Hadoop and Spark (In-memory distributed computing framework) are adopted to run topic model. In the experiment phases, TB level input data are processed for data preprocessing and proposed topic extraction steps are applied. We conclude that the proposed system shows good performance in extracting meaningful topics in time as the intermediate results come from main memories directly instead of an HDD reading.

• Korean Journal of Acupuncture
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• v.37 no.3
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• pp.203-208
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• 2020

Objectives : Since there are complex associations between diseases/symptoms and acupoints, one-to-one correspondence may not be the proper approach. Pattern identification has been being used as a clinical framework to make treatment decisions by extracting and synthesizing clinical data including patients' signs and symptoms. In this article, we propose two different models explaining the relationships between diseases and acupoints based on the branch treatment [Zhibiaofa] and the root treatment [Zhibenfa]. Methods : We explained the relationships between diseases/symptoms and acupoints from the example data from our previous study on traditional acupuncture point selection patterns for pain control. Diseases include low back pain, migraine, irritable bowel syndrome, osteoarthritis, ankle sprain, carpal tunnel syndrome, and dysmenorrhea, and acupoints included LI4, BL23, BL25, SP6, BL60, TE5, and CV4. Results : The relationships between diseases/symptoms and acupoints can be explained directly based on the branch treatment, and also can be explained indirectly through pattern identification based on the root treatment. Pattern identifications included both meridian-based pattern identification based on the spatial information of diseases and visceral organ-based pattern identification based on the characteristics of diseases. Conclusions : In the East Asian traditional medicine, Korean medicine doctors choose the most appropriate acupoints based either on the diseases/symptoms (i.e., branch treatment) or on the results of pattern identifications (i.e., root treatment). It is necessary to understand the two different approaches to choose specific acupoints for the targeted diseases.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.3
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• pp.75-82
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• 2010

The static strengths of the existing RC beams were experimentally investigated in this paper to understand the strength characteristics of existing structural members and to get appropriate data in strengthening RC members in the remodelling construction. Ten RC beams were prepared by cutting and extracting directly from the demolition site of apartment housings and tested in order to evaluate the flexural and shear strengths of existing RC beams by their geometric condition. From the test results, it was found that most of the specimens had a sufficient structural capacity except for some special case, for example, specimens with severe cracks or concrete losses caused by improper casting. Therefore, the severely deteriorated members originated from bad concrete casting or careless construction process should be repaired and strengthened in remodelling construction.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.119-124
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• 2007

The few observed data related snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. Remote sensing technology is very effective to observe a wide area. Although many researchers have used remote sensing for snow observation, there were a few discussions on the characteristics of spatial and temporal variation. Snow cover maps were derived from NOAA AVHRR images for the winter seasons from 1997 to 2006. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation stations. Model parameters (Snow Cover Area: SCA, snow depth, Snow cover Depletion Curve: SDC) building for 5 major watersheds in South Korea. Especially SDC is important parameter of snowmelt model.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• Journal of Fisheries and Marine Sciences Education
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• v.16 no.2
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• pp.181-186
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• 2004

The current situation of heating and cooling system of the classrooms of our country is rather poor compared not only to those of the developed nation's classrooms but also in case of other buildings such as financial institutions, office compounds. In winter, especially students have been in hatred state with respect to their health due to the fact that the heater is operated by petroleum. Korea has been heavily dependent on foreign nations for the very fact of importing energy in the form of oil or natural gas. So it is important to conserve energy and the picture with respect to energy remains similar till today as it was in long past periods. The purpose of this study is to contribute actively in energy economy and facilitate towards a healthy school life of students and other institutions proving a system of extracting energy from river water and then converting it into heat which can stand as an effective alternate of expensive oil or gas. Installing oil-stove based heating system at classrooms of school could get considerable attentation in several respects. The proposed heat energy could be collected unlimitedly both in time and in amount. The stable and uninterrupted heat energy from river water, optimally utilizing the typical-regional and geographical characteristics has the potential to be long-lasting in duration, cheap in energy economy and beneficial to health as well.