• Journal of Information Processing Systems
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• 제13권2호
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• pp.321-339
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• 2017

In this work, we are interested in the extraction of areas of interest from satellite images by introducing a MO-TRIBES/OC-SVM approach. The One-Class Support Vector Machine (OC-SVM) is based on the estimation of a support that includes training data. It identifies areas of interest without including other classes from the scene. We propose generating optimal training data using the Multi-Objective TRIBES (MO-TRIBES) to improve the performances of the OC-SVM. The MO-TRIBES is a parameter-free optimization technique that manages the search space in tribes composed of agents. It makes different behavioral and structural adaptations to minimize the false positive and false negative rates of the OC-SVM. We have applied our proposed approach for the extraction of earthquakes and urban areas. The experimental results and comparisons with different state-of-the-art classifiers confirm the efficiency and the robustness of the proposed approach.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1657-1662
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• 2017

Facial expression recognition systems using video devices have emerged as an important component of natural human-machine interfaces which contribute to various practical applications such as security systems, behavioral science and clinical practices. In this work, we present a new method to analyze, represent and recognize human facial expressions using a sequence of facial images. Under our proposed facial expression recognition framework, the overall procedure includes: accurate face detection to remove background and noise effects from the raw image sequences and align each image using vertex mask generation. Furthermore, these features are reduced by principal component analysis. Finally, these augmented features are trained and tested using Hidden Markov Model (HMM). The experimental evaluation demonstrated the proposed approach over two public datasets such as Cohn-Kanade and AT&T datasets of facial expression videos that achieved expression recognition results as 96.75% and 96.92%. Besides, the recognition results show the superiority of the proposed approach over the state of the art methods.

• Advances in nano research
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• 제5권1호
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• pp.49-59
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• 2017

Till now nanotechnology based anti-parasite pharmaceutical dosage forms development and application is being vastly developed worldwide. The field of nanotechnology involves an array of different areas of expertise with the application of innovative products in Medicine, Engineering, and to a less extent to Veterinary Medicine. In our conclusion, enriched experimental analysis is required, to announce the state of the art outputs to remove negative problems. Animals or human may benefit from nanotechnological products respectively, like vaccines, target recombinant peptides, or novel pharmaceutical alternatives. As a result, it would be desirable to give some energy for thought to drive nanomedical scientific introductions. To create more safe medium to animals and or humans. In this review all aspects of nanoparticles applications in parasitology will be carefully discussed depending on particle charge and size as well as kind of nanoparticles. Perspectives and prospective of nanoparticles in human parasitology will be predicted as well.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2003년도 추계종합학술대회 논문집
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• pp.493-496
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• 2003

애니메이션은 종합영상예술이다. 배경음악과 그림이 미지의 동조(Sync)는 매우 중요하다. 본 작품은 일반적인 애니메이션 작품처럼 그림의 스토리를 생각하며 배경음악을 선정하지 않고, 먼저 배경음악을 감상한 후 그 음악에서 느끼는 작가의 감정(feeling)을 추상적인 이미지 애니메이션으로 제작한 실험 작품이다. 대학에서 수많은 실험적 애니메이션 작품을 연구하고 제작해 봄으로서 창의적인 애니메이션제작과 우리나라 애니메이션 산업을 발전시키는데 일조 할 수 있을 것이다.

• Clinical and Experimental Reproductive Medicine
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• 제32권4호
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• pp.353-359
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• 2005

Heterotopic pregnancy is named when an extrauterine (ectopic) pregnancy coexists with an intrauterine pregnancy simultaneously by many causes such as PID (pelvic inflammatory disease), endometriosis, IUD (intrauterine device), previous pelvic surgery and others. This is very rare in general population, with a range of occurrence estimated between 1:7963 and 1:30000. But recently the incidence has increased as the uses of ARTs (assisted reproductive technologies) including ovulation induction, IVF-ET (in-vitro fertilization and embryo transfer) and GIFT (gamete intrafallopian transfer) increase. Because this has high maternal morbidity, mortality and fetal loss, early diagnosis and proper management is very important. We report a case of heterotopic pregnancy following IVF-ET with a brief review.

• Journal of Computing Science and Engineering
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• 제11권4호
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• pp.130-141
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• 2017

Feature selection is one of the most challenging problems of pattern recognition and data mining. In this paper, a feature selection algorithm based on an improved version of binary differential evolution is proposed. The method simultaneously optimizes two feature selection criteria, namely, set approximation accuracy of rough set theory and relational algebra based derived score, in order to select the most relevant feature subset from an entire feature set. Superiority of the proposed method over other state-of-the-art methods is confirmed by experimental results, which is conducted over seven publicly available benchmark datasets of different characteristics such as a low number of objects with a high number of features, and a high number of objects with a low number of features.

• Journal of Multimedia Information System
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• 제2권1호
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• pp.171-178
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• 2015

This article describes 3 dimensional (3D) face recognition system using histogram of oriented gradients (HOG) based on face curvature. The surface curvatures in the face contain the most important personal feature information. In this paper, 3D face images are recognized by the face components: cheek, eyes, mouth, and nose. For the proposed approach, the first step uses the face curvatures which present the facial features for 3D face images, after normalization using the singular value decomposition (SVD). Fisherface method is then applied to each component curvature face. The reason for adapting the Fisherface method maintains the surface attribute for the face curvature, even though it can generate reduced image dimension. And histogram of oriented gradients (HOG) descriptor is one of the state-of-art methods which have been shown to significantly outperform the existing feature set for several objects detection and recognition. In the last step, the linear discriminant analysis is explained for each component. The experimental results showed that the proposed approach leads to higher detection accuracy rate than other methods.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2012년도 제45회 KOSCO SYMPOSIUM 초록집
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• pp.89-91
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• 2012

The numerical simulation for detonation failure of ammonium nitrate (AN) based non-ideal explosives is carried out with an accurate and state-of-the-art Eulerian method. Detonation failure is readily observed in the rate stick experiments utilizing the AN mixture explosives and the inert confinements of varying thicknesses. The composition of non-ideal explosives and thickness of the confinements influence the characteristics of detonation failure. Calculated results are compared against the experimental data of both unconfined and confined rate stick problems and provide a reliable guideline to establish a fine-tuned chemical kinetic model for detonation failure.

• Journal of Power Electronics
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• 제14권6호
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• pp.1189-1196
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• 2014

A modular multilevel-clamped composited multilevel converter ($M-MC^2$) is proposed. $M-MC^2$ enables topology reconfiguration, power device reuse, and composited clamping. An advanced five-level converter ($5L-M-MC^2$) is derived from the concept of $M-MC^2$. $5L-M-MC^2$ integrates dual three-level T-type modules and one three-level neutral point clamped module. This converter can also integrate dual three-level T-type modules and one passive diode module by utilizing the device reuse scheme. The operation principle and SPWM modulation are discussed to highlight converter performance. The proposed $M-MC^2$ is comprehensively compared with state-of-the-art five-level converters. Finally, simulations and experimental results are presented to validate the effectiveness of the main contributions of this study.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2018년도 제30회 한글 및 한국어 정보처리 학술대회
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• pp.504-509
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• 2018

Neural machine translation (NMT) has recently achieved the state-of-the-art performance. However, it is reported failing in the word sense disambiguation (WSD) for several popular language pairs. In this paper, we explore the extent to which NMT systems are able to disambiguate the Korean homographs. Homographs, words with different meanings but the same written form, cause the word choice problems for NMT systems. Consistent with the popular language pairs, we discover that NMT systems fail to translate Korean homographs correctly. We provide a Korean word sense disambiguation tool-UTagger to use for improvement of NMT's translation quality. We conducted translation experiments using Korean-English and Korean-Vietnamese language pairs. The experimental results show that UTagger can significantly improve the translation quality of NMT in terms of the BLEU, TER, and DLRATIO evaluation metrics.