• Korean Journal of Construction Engineering and Management
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• v.5 no.6 s.22
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• pp.90-100
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• 2004

The importance of information management has been emphasized in Korean construction industry, Both public and private have invested to establish and operate construction CALS, construction management (CM), computer integrated construction(CIC), and earned value management system(EVMS). A standard construction information classification system is essential to operate the systems mentioned above. Therefore, Korean government released Integrated Construction Information Classification System(ICICS) in 2001. However, the ICICS is not widely used in construction due to: 1) difficulty of changing existing system, 2) insufficient publicity of the ICICS, and 3) no legal binding force. Especially, participants in construction do not recognize applicability of the ICICS. This research surveyed the degree of recognition and utilization of the ICICS. This survey includes both customized classification systems used by companies and the ICICS and investigates the degree of utilization and drawbacks. The results show some construction companies use their own classification systems and the others use the ICICS prepared by the government. Furthermore, the degree of recognition is in sufficient. The degree of use in design management, specifications, cost and schedule management is very limited. The publicity and education are critical to induce the utilization of the ICICS. The necessity of revision was recommended based on pilot project study that is performed to measure the degree of application of ICICS on the projects. Therefore, this research proposes the measurement model for information application and analyzes the degree of utilization of the ICICS in different phases of construction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.3
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• pp.194-202
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• 2003

To convert printed images into electronic ones automatically, it requires region analysis of document images and character recognition. In these, regional analysis segments document image into detailed regions and classifies thee regions into the types of text, picture, table and so on. But it is difficult to classify the text and the picture exactly, because the size, density and complexity of pixel distribution of some of these are similar. Thu, misclassification in region analysis is the main reason that makes automatic conversion difficult. In this paper, we propose region analysis method that segments document image into text and picture regions. The proposed method solves the referred problems using one dimensional median filter based method in text and picture classification. And the misclassification problems of boldface texts and picture regions like graphs or tables, caused by using median filtering, are solved by using of skin peeling filter and maximal text length. The performance, therefore, is better than previous methods containing commercial softwares.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.360-365
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• 2014

There are many types of advanced devices for weather prediction process such as weather radar, satellite, radiosonde, and other weather observation devices. Among them, the weather radar is an essential device for weather forecasting because the radar has many advantages like wide observation area, high spatial and time resolution, and so on. In order to analyze the weather radar observation result, we should know the inside structure and data. Some non-precipitation echoes exist inside of the observed radar data. And these echoes affect decreased accuracy of weather forecasting. Therefore, this paper suggests a method that could remove line-shaped non-precipitation echo from raw radar data. The line-shaped echoes are distinguished from the raw radar data and extracted their own features. These extracted data pairs are used as learning data for naive bayesian classifier. After the learning process, the constructed naive bayesian classifier is applied to real case that includes not only line-shaped echo but also other precipitation echoes. From the experiments, we confirm that the conclusion that suggested naive bayesian classifier could distinguish line-shaped echo effectively.

• Childhood Kidney Diseases
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• v.16 no.1
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• pp.21-31
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• 2012

Focal segmental glomerulosclerosis (FSGS) is the name of the primary glomerular disease as well as the terminology to describe the secondary phenomena of any other glomerular diseases. It is characterized by sclerosis, hyalinosis, foam cell infiltration, vacuolar change of podocytes, and halo formation in the glomerulus. Throughout the interstitium, lymphocytes infiltration, tubular atrophy and vascular changes are accompanied. Occasionally, IgM and/or C3 depositions are noted in the sclerotic areas. Electron microscopically, diffuse effacement of foot processes are seen in non-sclerotic area like minimal change disease. Podocyte injury patterns including vacuolar changes are frequently examined. Recently, Columbia group has suggested morphologic classification of FSGS and they demonstrated very good prognosis of tip lesion and poor prognosis of both collapsing and cellular types. However, the pathogenetic classification has been suggested by others; hyperfilteration, podocyte injury, genetic lesions etc. Further studies are necessary to understand and treat this disease.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.7-12
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• 2014

It has good features for social networking with friends SNS is maintained. However, various enterprises, individuals invading the inconvenience spammers have exposure to a number of users to tweet spam. The study was conducted in the existing research on these spam tweets. However, the results showed a more accurate classification and detection is difficult because of the lack of precision and different causes. In this paper, we describe how to classify the characteristics of spammers, classification criteria. Also has a link rate and difference between followers and following, these features were present classification criteria for spammers account. This experiment was performed according to the criteria. Randomized trial of spam and non-spam accounts were selected and account type was conducted according to the criteria 68% of the link ratio of spam accounts. Followers / Following ratio was 27581.5. Non-spam accounts was 6.12%. Followers / Following ratio was 1.26.

• Smart Media Journal
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• v.9 no.3
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• pp.46-51
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• 2020

Pine wilt disease is one of the reasons that results in huge damage on pine trees in east Asia including Korea, Japan, and China, and early finding and removing the diseased trees is an efficient way to prevent the forest from wide spreading. This paper proposes a searching method of the damaged pine trees from wilt disease in ortho-images corrected from RGB images, which are captured by unmanned aviation vehicles. The proposed method constructs patch-based classifier using ResNet18 backbone network, classifies the RGB ortho-image patches, and make the results as a heat map. The heat map can be used to find the distribution of diseased pine trees, to show the trend of spreading disease, and to extract the RGB distribution of the diseased areas in the image. The classifier in the work shows 94.7% of accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.3
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• pp.317-327
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• 2016

The extraction of significant feature points from a video is directly associated with the suggested method's function. In particular, the occlusion regions in trees or people, or feature points extracted from the background and not from objects such as the sky or mountains are insignificant and can become the cause of undermined matching or recognition function. This paper classifies the feature points required for building recognition by using multi-frames in order to improve the recognition function(algorithm). First, through SIFT(scale invariant feature transform), the primary feature points are extracted and the mismatching feature points are removed. To categorize the feature points in occlusion regions, RANSAC(random sample consensus) is applied. Since the classified feature points were acquired through the matching method, for one feature point there are multiple descriptors and therefore a process that compiles all of them is also suggested. Experiments have verified that the suggested method is competent in its algorithm.

• Resources Recycling
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• v.27 no.2
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• pp.11-23
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• 2018

The need for remanufacturing automotive parts is required due to the depletion of resources, rising raw material prices and strengthening environmental regulations. For remanufacturing, stable supply and demand of core must be accompanied. At present, remanufacturing companies collect cores through various routes, but the recovery rate of cores from the End-of-Life Vehicles is low. If we can systematically collect cores from hundreds of thousands of ELVs that were generated each year, the recovery rate of the core for remanufacturing will be further improved. Therefore, in this paper, we tried to establish a classification system for the ELV as a method for collecting the cores from the ELV. First, we selected the elements affecting the classification and determined the scope for the evaluation. The final rating classification is established by calculating the weights among the influence elements. Finally, through the case study, the dismantling grade of the actual ELV was evaluated to derive the second grade.

• Journal of Korean Society of Transportation
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• v.19 no.1
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• pp.7-16
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• 2001

The Principle objective of this paper is to introduce a systematic approach to identifying similar container ports in Asia. For this, it analyses data on port facilities, port facility availability, port service level total container throughput, and economic index, by using Multidimentional Scaling (MDS) method. Based on the analysis it identifies five groupings of similar container ports in Asia within which Port comparison can be justifiably made, evaluates a present position of five groupings on the basis of factors used to compare container ports in Asia ; and finally proposes policy implications for operation efficiency of Pusan container port in comparison with Kaohsiung Port. The major implication is that both the Kaosuing and the Pusan port have to strengthen port facility to attract more traffic, and particularly, Pusan Port has to reinforce the number of berth, total length of berth. and yard areas.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5150-5155
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• 2011

Alzheimer's disease (AD) and vascular dementia (VD) are the most common dementia. In this paper, we proposed a region selection for classification of AD, VD and normal (NOR) based on micro-Raman spectra from platelet. The preprocessing step is a smoothing followed by background elimination to the original spectra. Then we applied the minmax method for normalization. After the inspection of the preprocessed spectra, we found that 725-777, 1504-1592 and 1632-1700 $cm^{-1}$ regions are the most discriminative features in AD, VD and NOR spectra. We applied the feature transformation using PCA (principal component analysis) and NMF (nonnegative matrix factorization). The classification result of MAP(maximum a posteriori probability) involving 327 spectra transformed features using proposed local region showed about 92.8 % true classification average rate.