• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.6-10
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• 2007

Classification of hyperspectral images is challenging. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. In other words in order to obtain statistically reliable classification results, the number of necessary training samples increases exponentially as the number of spectral bands increases. However, in many situations, acquisition of the large number of training samples for these high-dimensional datasets may not be so easy. This problem can be overcome by using multiple classifiers. In this paper we compared the effectiveness of two approaches for creating multiple classifiers, feature selection and feature extraction. The methods are based on generating multiple feature subsets by running feature selection or feature extraction algorithm several times, each time for discrimination of one of the classes from the rest. A maximum likelihood classifier is applied on each of the obtained feature subsets and finally a combination scheme was used to combine the outputs of individual classifiers. Experimental results show the effectiveness of feature extraction algorithm for generating multiple classifiers.

• 한국컴퓨터산업학회논문지
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• 제7권5호
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• pp.473-480
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• 2006

본 논문에서는 여러 개의 출력단을 갖는 논리회로에서 공통식을 찾는 방법을 제안하였다. 각각의 출력단위로 2개의 큐브로 구성된 몫을 찾고, 이 몫들 간의 쌍을 이용해서 부울 공통식을 찾는 방법을 보였다. 실험 결과로 2개의 큐브만을 이용한 공통식 산출만으로 전체 논리회로의 크기를 줄이는 데 효과가 있음을 SIS1.2 결과와 비교하여 보였다.

• 한국실내디자인학회논문집
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• 제17권5호
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• pp.99-106
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• 2008

Based on extraction items derived from previous related studies on viewing experiences in art museums, this study is conducted to investigate extraction factors that affect viewing satisfactions and to suggest a guideline for an effective viewing environment by clarifying a hierarchy among the extraction factors. For this study, a survey was given to museum visitors, and statistical analyses were conducted on data obtained from the survey. The results of this study are summarized as follows; 1. From an analysis of extraction items that affect overall viewing satisfaction, space and art works were found to be relatively satisfactory. 2. From correlation analyses of extraction items, a degree of concentration on art works was found to most 'affect the viewing satisfactions of art museums. 3. From factor analyses, extraction items were reduced to 11 extraction factors, and a simple extraction structure affecting the viewing satisfactions in art museums. 4. From multiple regression analyses, a extraction factors were derived, and a relative hierarchy among the factors was found.

• 한국전자통신학회논문지
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• 제8권8호
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• pp.1201-1206
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• 2013

영상에서 얼굴 및 얼굴 특징을 추출하기 위한 기법으로 active appearance model(AAM)이 있다. 본 논문에서는 두 개의 AAM을 이용하여 얼굴 특징을 추출하는 multiple active appearance model(MAAM) 기법을 제안한다. 두 개의 AAM은 학습 데이터에 대한 파라미터를 조절하여 상반되는 장단점을 가지도록 생성하고, 서로의 단점을 보완할 수 있도록 한다. 제안된 방법의 성능을 평가하기 위해 100장의 영상에 대해서 얼굴 특징추출 실험을 하였다. 실험 결과 기존의 AAM 하나만을 사용하는 기법에 비해 적은 횟수의 피팅만으로도 정확도 높은 결과를 얻을 수 있었다.

• 한국멀티미디어학회논문지
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• 제7권4호
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• pp.467-473
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• 2004

비디오내에서의 자막은 비디오 내용을 전달하는 중요한 역할을 수행한다. 기존의 자막 영 역 추출방법들은 잡음에 민감하여 배경에서 자막 영역의 추출이 어려웠다. 본 논문에서는 다중 프레임 병합과 영역 최소 사각형을 이용하여 스포츠 비디오에서 자막 영역을 추출하는 방법을 제안한다. 전처리과정으로서 명암 대비 스트래칭과 Othu Method를 이용하여 적응적 임계치를 추출할 수 있다. 다중 프레임 병합에 의하여 자막 프레임 구간을 추출하고, 자막 영역은 미디언 필터링, 형태학적 불림, 영역 레이블링, 후보 문자영역 필터링, 영역 최소 사각형 검출에 의하여 효율적으로 추출된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권1호
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• pp.123-144
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• 2014

Wireless sensor networks are generally deployed for specific applications to accomplish certain objectives over a period of time. To fulfill these objectives, it is crucial that the sensor network continues to function for a long time, even if some of its nodes become faulty. Energy efficiency and fault tolerance are undoubtedly the most crucial requirements for the design of an information extraction protocol for any sensor network application. However, most existing software agent based information extraction protocols are incapable of satisfying these requirements because of static agent itineraries and large agent sizes. This paper proposes an Information Extraction protocol based on Multiple software Agents with Dynamic Itineraries (IEMADI), where multiple software agents are dispatched in parallel to perform tasks based on the query assigned to them. IEMADI decides the itinerary for an agent dynamically at each hop using local information. Through mathematical analysis and simulation, we compare the performance of IEMADI with a well known static itinerary based protocol with respect to energy consumption and response time. The results show that IEMADI provides better performance than the static itinerary based protocols.

• Mass Spectrometry Letters
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• 제5권3호
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• pp.79-83
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• 2014

Three different dutasteride extraction methods were compared and a method based on liquid-liquid extraction (LLE) using methyl tert-butyl ether and methylene chloride was proved to be more effective than others for the extraction of dutasteride and finasteride, the internal standard (IS), from rat plasma. Additionally, a method composed of the LLE extraction, liquid chromatography, and multiple reaction monitoring (MRM) to target dutasteride and IS was validated by assessing specificity, linearity ($r^2$ = 0.9993, 5 - 400 ng/mL), sensitivity (the limit of detection: 4.03 ng/mL; the limit of quantitation: 12.10 ng/mL), accuracy (intra-day: 89.4 - 105.9%; inter-day: 84.9 - 100.9%), precision (intra-day: 0.8 - 6.9%; inter-day: 2.9 - 15.9%), and recovery (84.7 - 107.8%). Since the validated method was successfully applied to a pharmacokinetic study of dutasteride, it can be useful for the pharmacokinetic evaluation of newly developed dutasteride formulations.

• Ocean Systems Engineering
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• 제2권2호
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• pp.137-145
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• 2012

Recent developments in underwater image recognition methods have received large attention by the ocean engineering researchers. In this paper, an improved bi-dimensional empirical mode decomposition (BEMD) approach is employed to decompose the given underwater image into intrinsic mode functions (IMFs) and residual. We developed a joint algorithm based on BEMD and Canny operator to extract multi-pixel edge features at multiple scales in IMFs sub-images. So the multiple pixel edge extraction is an advantage of our approach; the other contribution of this method is the realization of the bi-dimensional sifting process, which is realized utilizing regional-based operators to detect local extreme points and constructing radial basis function for curve surface interpolation. The performance of the multi-pixel edge extraction algorithm for processing underwater image is demonstrated in the contrast experiment with both the proposed method and the phase congruency edge detection.

• 융합신호처리학회논문지
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• 제12권3호
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• pp.176-180
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• 2011

Even though algorithms for watermark embedding and extraction step are important issue for digital watermarking, watermark selection and post-processing can give us an opportunity to improve our algorithms and achieve higher performance. For this reason, we summarized the possibilities of improvements for digital watermarking by referring to the watermark merging techniques rather than embedding and extraction algorithms in this paper. We chose Cox's function as main embedding and extraction algorithm, and multiple barcode watermarks as a watermark. Each bit of the multiple copies of barcode watermark was embedded into a gray-scale image with Cox's embedding function. After extracting the numbers of watermark, we applied the watermark merging techniques; including the simple merging, N-step iterated merging, recover merging and combination of iterated-recover merging. Main consequence of our paper was the fact of finding out how multiple barcode watermarks and merging techniques can give us opportunities to improve the performance of algorithm.

• 스마트미디어저널
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• 제7권4호
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• pp.79-89
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• 2018

In recent years, falls among elderly people have gained serious attention as a major cause of injuries. Falls often lead to fatal consequences due to lack of prompt response and rescue. Therefore, a more accurate fall detection system and an effective feature extraction technique are required to prevent and reduce the risk of such incidents. In this paper, we proposed an efficient feature extraction technique based on multiple sliding windows and validated it through a series of experiments using supervised learning algorithms. The experiments were conducted using the public datasets obtained from tri-axial accelerometers. The results depicted that extraction of the feature from adjacent sliding windows led to high accuracy in supervised machine learning-based fall detection. Also, the experiments conducted in this study suggested that the best accuracy can be achieved by keeping the window size as small as 2 seconds. With the kNN classifier and dataset from wearable sensors, the experiments achieved accuracy rates of 94%.