• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.621-625
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• 2010

This paper presents a hand motion tracking method for hand gesture interface using a camera in mobile devices such as a smart phone and PDA. When a camera moves according to the hand gesture of the user, global optical flows are generated. Therefore, robust hand movement estimation is possible by considering dominant optical flow based on histogram analysis of the motion direction. A continuous hand gesture is segmented into unit gestures by motion state estimation using motion phase, which is determined by velocity and acceleration of the estimated hand motion. Feature vectors are extracted during movement states and hand gestures are recognized at the end state of each gesture. Support vector machine (SVM), k-nearest neighborhood classifier, and normal Bayes classifier are used for classification. SVM shows 82% recognition rate for 14 hand gestures.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1074-1088
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• 2016

Successful Visual Story Telling(VST) of desire is a crucial key for the success of animation because desire is the leading power of story development of animation. An analysis of the desire of VST using the top 5 successful American feature film animations is carried out. Totally, 147 desire shots are extracted by using the proposed Objective Selection of Desire Shots(OSDS) method based on the theory of Makee's conflict and desire pursuing modeling, Maslow's 20 desire types, Greimas's actant model, and the 17 narrative process classification. In addition to them, the 5 Beat(5B) model of a scene is proposed. Five image specialists have evaluated VST of the selected 147 desire shots. For each shot, the desire type among the 20 desires and the strength are obtained. Among them, the top 3 desires(affiliation, achievement, and nurturance) appearing 51.8% are analyzed. The composition elements of shots affecting the desire type and the strength have found. These can be used for better VST of preproduction and production of animation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1272-1277
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• 2010

Target detection and tracking wireless sensor network must have various signal processing ability. Wireless sensor nodes need to light weight signal processing algorithm because of energy constraints and communication bandwidth constraints. General signal processing algorithm of wireless sensor node consists of de-noising, received signal strength computation, feature extraction and signal compression. Wireless sensor network life-time and performance of target detection and classification depend on sensor node signal processing. In this paper, we propose energy efficient signal processing algorithm using wavelet transform. The proposed method estimates exact target position.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.391-398
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• 2017

In this paper, we compared the performance of "Network Intrusion Detection System based on attack feature selection using fuzzy control language"[1] and "Intelligent Intrusion Detection System Model for attack classification using RNN"[2]. In this paper, we compare the intrusion detection performance of two techniques using KDD CUP 99 dataset. The KDD 99 dataset contains data sets for training and test data sets that can detect existing intrusions through training. There are also data that can test whether training data and the types of intrusions that are not present in the test data can be detected. We compared two papers showing good intrusion detection performance in training and test data. In the comparative paper, there is a lack of performance to detect intrusions that exist but have no existing intrusion detection capability. Among the attack types, DoS, Probe, and R2L have high detection rate using fuzzy and U2L has a high detection rate using RNN.

• Tuberculosis and Respiratory Diseases
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• v.69 no.5
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• pp.354-360
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• 2010

Background: Primary non-Hodgkin's lymphoma of the lung is a rare entity. It is represented commonly as marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue (MALT) type. Although there have been a few reviews of this lymphoma, clinical features, radiologic findings, management and prognosis have not been well defined. Methods: We reviewed the medical records of 24 patients with primary pulmonary lymphoma between January 1995 and September 2008; all diagnoses had been confirmed based on pathology. Results: The median follow-up time was 42.3 months (range, 0.1~131.2 months). Five (20.8%) patients were asymptomatic, 17 (70.8%) patients had pulmonary symptoms, and the remaining 2 (8.3%) patients presented with constitutional symptoms. There were 16 (66.7%) patients with MALT lymphoma, 4 (16.7%) patients with diffuse large B-cell lymphoma and 4 (16.7%) patients with lymphoma that had not received a WHO classification. Radiologic findings of primary pulmonary lymphoma were diverse and multiple nodule or consolidation was the most common finding regardless of pathologic lymphoma type. PET scan was carried out in 13 (54.2%) patients and all lesions showed notable FDG uptake. MALT lymphoma showed a trend of better prognosis (3-year survival, 78.8% vs. 70.0%; 5-year survival, 78.8% vs. 52.5%; p=0.310) than non-MALT lymphoma. Conclusion: Primary non-Hodgkin's lymphoma of the lung occurs with nonspecific clinical features and radiologic findings. MALT lymphoma is the most common pathologic type of primary pulmonary lymphoma. This entity of lymphoma appears to have a good prognosis and in this study, there was a trend of better outcome than non-MALT lymphoma.

• Genomics & Informatics
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• v.3 no.1
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• pp.15-23
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• 2005

Background MicroRNAs (miRNAs) are a class of noncoding RNAs found in various organisms such as plants and mammals. However, most of the mRNAs regulated by miRNAs are unknown. Furthermore, miRNA targets in genomes cannot be identified by standard sequence comparison since their complementarity to the target sequence is imperfect in general. In this paper, we propose a kernel-based method for the efficient prediction of miRNA targets. To help in distinguishing the false positives from potentially valid targets, we elucidate the features common in experimentally confirmed targets. Results The performance of our prediction method was evaluated by five-fold cross-validation. Our method showed 0.64 and 0.98 in sensitivity and in specificity, respectively. Also, the proposed method reduced the number of false positives by half compared with TargetScan. We investigated the effect of feature sets on the classification of miRNA targets. Finally, we predicted miRNA targets for several miRNAs in the Caenorhabditis elegans (C. elegans) 3' untranslated region (3' UTR) database. Condusions The targets predicted by the suggested method will help in validating more miRNA targets and ultimately in revealing the role of small RNAs in the regulation of genomes. Our algorithm for miRNA target site detection will be able to be improved by additional experimental­knowledge. Also, the increase of the number of confirmed targets is expected to reveal general structural features that can be used to improve their detection.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.4
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• pp.145-154
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• 2008

In this paper, we propose the pet robot control system using hand gesture recognition in image sequences acquired from a camera affixed to the pet robot. The proposed system consists of 4 steps; hand detection, feature extraction, gesture recognition and robot control. The hand region is first detected from the input images using the skin color model in HSI color space and connected component analysis. Next, the hand shape and motion features from the image sequences are extracted. Then we consider the hand shape for classification of meaning gestures. Thereafter the hand gesture is recognized by using HMMs (hidden markov models) which have the input as the quantized symbol sequence by the hand motion. Finally the pet robot is controlled by a order corresponding to the recognized hand gesture. We defined four commands of sit down, stand up, lie flat and shake hands for control of pet robot. And we show that user is able to control of pet robot through proposed system in the experiment.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.88-100
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• 1998

In this paper, an algorithm for a real-time automatic fingerprint identification system is proposed. The fingerprint feature volume is extracted by considering distinct and local characteristics(such as intensity and image quality difference etc.) in fingerprint images, which makes the algorithm properly adaptive to various image acquisitionj methods. Also the matching technique is designed to be invariant on rotation, scaling and translation (RST) changes while being capable of real-time processing. And the classification of fingerprints is performed based on the ridge flow and the relations among singular points such as cores and deltas. The developed fingerprint identification algorithm has been applied to various sets of fingerprint images such as one from NIST(National Institute of Standards and Technology, USA), a pressed fingerprint database constructed according to Korean population distributions in sex, ages and jobs, and a set of rolled-than-scanned fingerprint images. The overall performance of the algorithm has been analyzed and evaluated to the false rejection ratio of 0.07% while holding the false acceptance ratio of 0%.

• Journal of architectural history
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• v.21 no.1
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• pp.99-118
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• 2012

This study aims to classify the architectural formation of the Stylobate of and Staircase types of Post-Lintel Construction in Backje style and Silla style and also to figure out their specific elements by periods and transformation characteristics. The scope of this study was restricted to architectural remains between the Three Kingdom period and the Goryeo period. To progress the investigation, the study classified remains in a similar type by period and type, and then and analyzed its character based on formation method and specific factors of subsidiary materials. As a result, its type can be classified as Backje type(I), Silla type(II) and Mixed type(III). Regionally, it is found that Woongjin, Sabi and surroundings in the capital of Backje, Gyeongju and main towns in the capital of Silla, and Gaeseong and main towns in the capital of Goryeo. In particular, type III has the characteristics of type I and II simultaneously, which has one or two layers Jangdaeseok stone between the foundation stone of stylobate and plate stone, and tends to be decorative when Taengjuseok stone is installed. For types of staircase, it could be classified as 6~7C Backje type(I), 7~9C Silla type(II) and 9C Mixed type(III) according to the formation method of Somaetdol (banister of stone stair). And from the 9th century on, decorated Somaetdol stone type(IV) of 1/4 circle shape began to appear. The common feature of stylobate of post-lintel and staircase is that it became simplified, abbreviated and decorative. It seems to be intended to secure simplicity of construction or structural stability.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.154-161
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• 2008

In this paper, a novel method is proposed using color and pattern information for recognizing some emotions included in a fertile. Here we use 10 Kobayashi emotion to represent emotions. - { romantic, clear, natural, casual, elegant chic, dynamic, classic, dandy, modem } The proposed system is composed of feature extraction and classification. To transform the subjective emotions as physical visual features, we extract representative colors and Patterns from textile. Here, the representative color prototypes are extracted by color quantization method, and patterns exacted by wavelet transform followed by statistical analysis. These exacted features are given as input to the neural network (NN)-based classifiers, which decides whether or not a textile had the corresponding emotion. When assessing the effectiveness of the proposed system with 389 textiles collected from various application domains such as interior, fashion, and artificial ones. The results showed that the proposed method has the precision of 100% and the recall of 99%, thereby it can be used in various textile industries.