• Journal of IKEEE
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• v.14 no.3
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• pp.224-231
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• 2010

Automatic detection of objects in images has been one of core challenges in the areas such as computer vision and pattern analysis. Especially, with the recent deployment of personal mobile devices such as smart phone, such technology is required to be transported to them. Usually, these smart phone users are equipped with devices such as camera, GPS, and gyroscope and provide various services through user-friendly interface. However, the smart phones fail to give excellent performance due to limited system resources. In this paper, we propose a new scheme to improve object recognition performance based on pre-computation and simple local features. In the pre-processing, we first find several representative parts from similar type objects and classify them. In addition, we extract features from each classified part and train them using regression functions. For a given query image, we first find candidate representative parts and compare them with trained information to recognize objects. Through experiments, we have shown that our proposed scheme can achieve resonable performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.99-104
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• 2011

In this paper the approach of neural network was proposed which detects a variety of defects in the molded parts. In an attempt to improve the response of the system, It is designed to minimize the use of memory via LookUp table in software. The goal of these methods was to extract the features of samples in learning of neural networks, overcoming the algorithms of defects detection and classification. Through the learning of 500 sample patterns of molded parts, defects of 3% molded parts was detected and classified as the incorrect diameter parts. We expect that proposed approach is an effective alternative to save test time and cost for defect detection of a fine pattern within the molded parts.

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.1927-1935
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• 2016

This paper propose a framework for human body parts in RGB-D image. We conduct tasks of obtaining person area, finding candidate areas and local detection in order to detect hand, foot and head which have features of long accumulative geodesic distance. A person area is obtained with background subtraction and noise removal by using depth image which is robust to illumination change. Finding candidate areas performs construction of graph model which allows us to measure accumulative geodesic distance for the candidates. Instead of raw depth map, our approach constructs graph model with segmented regions by quadtree structure to improve searching time for the candidates. Local detection uses HOG based SVM for each parts, and head is detected for the first time. To minimize false detections for hand and foot parts, the candidates are classified with upper or lower body using the head position and properties of geodesic distance. Then, detect hand and foot with the local detectors. We evaluate our algorithm with datasets collected Kinect v2 sensor, and our approach shows good performance for head, hand and foot detection.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.17 no.3
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• pp.102-106
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• 2004

Obective : This study was designed to investigated clinical features and frequent parts of chronic paranasal sinusitis Method : The ratio of male and female, the distribution of symptoms, the frequent parts of paranasal sinusitis on PNS images were investigated in 26 patients who visited Department of otorhinolaryngology Semyung university Oriental medical hostipal during from march, 2004 to october, 2004. Results: 1. The ratio of male and female was 1:1.5 and the teens were high rate of age group 2. The results reveal1he most common symptoms as follows ; nasal stuffiness(28.1$\%$), rhinorrhea26.5$\%$), laryngopharyngial disorder(14$\%$). 3. The frequent parts of paranasal sinusitis on PNS images were ethmodial sinus, maxillary sinus, fronal sinus in good order. 4. 87.5$\%$ of patients show effective result in medical treatment Conclusion: We suggest that this results form the foundation of objectification of medical treatment of paranasal sinusitis

• Transactions of Materials Processing
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• v.9 no.5
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• pp.512-525
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• 2000

Designers are frequently faced with multiple quality issues in injection molded parts. These issues are usually In conflict with each other, and thus tradeoff needs to be made to reach a final compromised solutions. The objective of this study is to develop an automated injection molding design methodology, whereby part defects such as warpage and weld line are optimized. The features of the proposed methodology are as follows: first, Utility Function approach is applied to transform the original multiple objective problem into single objective problem. Second is an implementation of a direct search-based Injection molding optimization procedure with automated consideration of process variation. The Space Reduction Method based on Taguchi's DOE(Design Of Experiment) is used as a general optimization tool in this study. The computational experimental verification of the methodology was partially carried out for a can model of Cavallero Plastics Incorporation, U. S. A. Applied to production, this study will be of immense value to companies in reducing the product development time and enhancing the product quality.

• Nuclear Engineering and Technology
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• v.50 no.7
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• pp.1160-1167
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• 2018

Detectability of the loose parts (LPs) in steam generator (SG) was studied with eddy current testing technique such as X-probe, bobbin and rotating coils ($MRPC^{(R)}$) as a function of LP size and spacing between LP and tube or between LP and support structures. SG mockup simulating SG tube and support structures with LP was fabricated. The X-probe showed slightly better detectability than $MRPC^{(R)}$ for LP of ferrous (F-LP) material and vice versa for LP of nonferrous (NF-LP) material. In terms of feasibility, inspection rate and other predictable features of the SG tubing inspections, X-probe can be used reliably for monitoring the LPs and the flaws formed by LPs on SG tubes.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.90-99
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• 1992

In this paper, we propose a neural network model for speech recognition. The model consists of feature extraction parts and recognition parts. The interconnection model based on ${\Delta}^2$G operator was used for frequency analysis. Two features, global feature and local feature, were extracted from this model. Recognition parts consist of global grouping stage and local grouping stage. When the input pattern was coded by slope method, the recognition rate of speakers, A and B, was 100%. When the test was performed with the data of 9 speakers, the recognition rate of 91.4% was obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1856-1869
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• 2015

This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.

• The Journal of Internal Korean Medicine
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• v.21 no.5
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• pp.889-895
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• 2000

I experienced a case of a patient with clinical features of cerebellar dysfunction in the intracranial hemorrhage which encroached the basis of lower pontine and all parts of pontine tegmentum. So I report this case with bibliographical inquiry. In addition, I applied the treatment of Oriental medicine to sequelae of intracranial hemorrhage like disorders of eye movement, central dizziness, cerebellar tremor and ataxias but the effect did not meet my expectation. I anticipate more clinical studies and reports on this hereafter.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.1
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• pp.99-112
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• 1994

This paper describe the development of a systematic method of slicing solid parts based on a data structure called Sliced Profile Data Structure(SPDS). SPDS is an augmented polygon data structure that allows multiple layers of sliced profiles to be connected together. The method consists of five steps: (1) Selection of slicing directions, (2) Determination of slicing levels, (3) Creation of sliced profiles, (4) Connection of sliced profiles, and (5) Refinement. The presented method is aimed at enhancing the applicability of CSG for manufacturing by overcoming the problem of non-uniqueness and global nature. The SPDS-based method of feature extraction is suitable for recognizing broad scope of features with detailed information. The method is also suitable for identifying the global relationships among features and is capable of incorporating the context dependency of feature extraction.