• Journal of the Semiconductor & Display Technology
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• v.8 no.3
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• pp.39-44
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• 2009

Local Binary Pattern (LBP) is becoming a popular tool for various machine vision applications such as face recognition, classification and background subtraction. In this paper, we propose a new extension of LBP, called the Diagonal LBP (DLBP), to handle the image-based gender classification problem arise in interactive display systems. Instead of comparing neighbor pixels with the center pixel, DLBP generates codes by comparing a neighbor pixel with the diagonal pixel (the neighbor pixel in the opposite side). It can reduce by half the code length of LBP and consequently, can improve the computation complexity. The Support Vector Machine is utilized as the gender classifier, and the texture profile based on DLBP is adopted as the feature vector. Experimental results revealed that our approach based on the diagonal LPB is very efficient and can be utilized in various real-time pattern classification applications.

• Journal of the Korean Society of Physical Medicine
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• v.14 no.3
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• pp.55-62
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• 2019

PURPOSE: Text-mining has been shown to be useful for understanding the clinical characteristics and patients' concerns regarding a specific disease. Low back pain (LBP) is the most common disease in modern society and has a wide variety of causes and symptoms. On the other hand, it is difficult to understand the clinical characteristics and the needs as well as demands of patients with LBP because of the various clinical characteristics. This study examined online texts on LBP to determine of text-mining can help better understand general characteristics of LBP and its specific elements. METHODS: Online data from www.spine-health.com were used for text-mining. Keyword frequency analysis was performed first on the complete text of postings (full-text analysis). Only the sentences containing the highest frequency word, pain, were selected. Next, texts including the sentences were used to re-analyze the keyword frequency (pain-text analysis). RESULTS: Keyword frequency analysis showed that pain is of utmost concern. Full-text analysis was dominated by structural, pathological, and therapeutic words, whereas pain-text analysis was related mainly to the location and quality of the pain. CONCLUSION: The present study indicated that text-mining for a specific element (keyword) of a particular disease could enhance the understanding of the specific aspect of the disease. This suggests that a consideration of the text source is required when interpreting the results. Clinically, the present results suggest that clinicians pay more attention to the pain a patient is experiencing, and provide information based on medical knowledge.

• Journal of Internet of Things and Convergence
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• v.2 no.4
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• pp.15-20
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• 2016

This paper describes the construction of knowledge data retrieval management system based on medical image CT. The developed system is aimed to improve the efficiency of the hospital by reading the medical images using the intelligent retrieval technology and diagnosing the patient 's disease name. In this study, the medical image DICOM file of PACS is read, the image is processed, and feature values are extracted and stored in the database. We have implemented a system that retrieves similarity by comparing new CT images required for medical treatment with the feature values of other CTs stored in the database. After converting 100 CT dicom provided for academic research into JPEG files, Code Book Library was constructed using SIFT, CS-LBP and K-Mean Clustering algorithms. Through the database optimization, the similarity of the new CT image to the existing data is searched and the result is confirmed, so that it can be utilized for the diagnosis and diagnosis of the patient.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.423-431
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• 2016

In general LPR(License Plate Recognition) in outdoor image is not so simple differently from in the image captured from manmade environment, because of geometric shape distortion and large illumination changes. this paper proposes three techniques for LPR in outdoor images captured from CCTV. At first, a serially connected multi-stage Adaboost LP detector is proposed, in which different complementary features are used. In the proposed detector the performance is increased by the Haar-like Adaboost LP detector consecutively connected to the MB-LBP based one in serial manner. In addition the technique is proposed that makes image processing easy by the prior determination of LP type, after correction of geometric distortion of LP image. The technique is more efficient than the processing the whole LP image without knowledge of LP type in that we can take the appropriate color to gray conversion, accurate location for separation of text/numeric character sub-images, and proper parameter selection for image processing. In the proposed technique we use DBN(Deep Belief Network) to achieve a robust character recognition against stroke loss and geometric distortion like slant due to the incomplete image processing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.536-543
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• 2015

This study describes on the level of back pain knowledge from a survey that conducted from November 1, 2013 to January 31, 2014 for 82 cement factory workers at C region in Chung-Buk. The survey results showed that 56.1% of workers experienced back pain. Also the number of back pain of workers increased when workers who subjected more stresses from their works, had been growth in urban area and have not satisfied their given works. The survey also show that workers who subjected back pain once, usually they stopped smoking and reduced drinking, and they willing to take education for back pain-reducing. The worker's level of back pain knowledge was relatively low scores as 56.29 points in the 100-point conversion score, specially back pain associated with the posture were the lowest point of 50 points. Knowledge of back pain, a positive correlation was observed. Finally workers experienced back pain and education of back pain had higher willing to receive the education in the future. However, workers were not obtained the knowledge information on back pain indicated lower scores.

• Journal of the Ergonomics Society of Korea
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• v.29 no.3
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• pp.347-356
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• 2010

The purpose of this study is to analyze the spine stability by comparing muscle activation in various scaffold working conditions. The independent working conditions were designed by two levels of working height, existence and absence of safety handrail, and the two levels of expertise. The corresponding activities of the agonist and antagonist muscles of spine were simultaneously recorded by using EMG. As results, novice worker showed increased muscle activity while doing the task on the 2nd floor, absence of handrail. And expert showed the increase of co-contraction while working on the 2nd floor without handrail. Such co-contraction was found to increase the spine stability when the working condition become risky. On the other hand, the co-contraction was prolonged, the spine muscle fatique and disc pressure could be increased, which would increase the risk of musculo-skeletal disorder. The results of co-contraction in this study indicates that the motor control system responds to maintain the stability of the spine particularly when workers cognitively recognize the danger of falling or imbalance. This study also quantitatively accounted for the biomechanical cause of LBP among workers who has to prevent themselves from falling. Therefore, if can be said that safe environment preventing falling can also prevent workers from MSDs as well. Such knowledge can be applied to design ergonomic workplace environment as well as movable scaffold.