• 농촌계획
• /
• 제23권3호
• /
• pp.21-36
• /
• 2017

Climate change is intensifying storms and floods around the world. Where nature has been destroyed by development, communities are at risk from these intensified climate patterns. This study was to suggest a methodology for estimating flood vulnerability using Potential Flood Damage(PFD) concept and classify city/county about Potential Flood Damage(PFD) using various typology techniques. To evaluate the PFD at a spatial resolutions of city/county units, the 20 representative evaluation indexing factors were carefully selected for the three categories such as damage target(FDT), damage potential(FDP) and prevention ability(FPA). The three flood vulnerability indices of FDT, FDP and FPA were applied for the 167 cities and counties in Korea for the pattern classification of potential flood damage. Potential Flood Damage(PFD) was classified by using grouping analysis, decision tree analysis, and cluster analysis, and characteristics of each type were analyzed. It is expected that the suggested PFD can be utilized as the useful flood vulnerability index for more rational and practical risk management plans against flood damage.

• 전기학회논문지
• /
• 제58권2호
• /
• pp.342-348
• /
• 2009

This paper introduces a novel denoising algorithm for the partial-discharge(PD) signals from power apparatuses. The developed algorithm includes three kinds of specific denoising sub-algorithms. The first sub-algorithm uses the fuzzy logic which classifies the noise types in the magnitude versus phase PD pattern. This sub-algorithm is especially effective in the rejection of the noise with high and constant magnitude. The second one is the method simply removing the pulses in the phase sections below the threshold count in the count versus phase pattern. This method is effective in removing the occasional high level noise pulses. The last denoising sub-algorithm uses the grouping characteristics of PD pulses in the 3D plot of the magnitude versus phase versus cycle. This special technique can remove the periodical noise pulses with varying magnitudes, which are very difficult to be removed by other denoising methods. Each of the sub-algorithm has different characteristic and shows different quality of the noise rejection. On that account, a parameter which numerically expresses the noise possessing degree of signal, is defined and evaluated. Using the parameter and above three sub-algorithms, an adaptive complex noise rejection algorithm for the on-line PD diagnosis system is developed. Proposed algorithm shows good performances in the various real PD signals measured from the power apparatuses in the Korean plants.

• 한국음향학회지
• /
• 제20권2호
• /
• pp.44-51
• /
• 2001

본 연구에서는 능동소나와 관련된 시스템에 적용가능한 잠수함 수중표적의 표적강도 및 신호형태를 예측하는 반사신호 합성모델을 제안한다. 이는 입사각에 따라 외부헐로 하이라이트의 위치가 변하는 UTAHID (Underwater TArget by Highlight Distribution) 모델을 기초로 하여 잠수함 내부의 복잡한 형상에 의한 반사점들을 산란자운에 의한 구룹화된 하이라이트군으로 변형을 가하여 반사신호를 합성한다. 제안된 모델은 입사신호의 펄스길이 변화에 따른 표적강도 변화특성 및 합성신호 파형, 시간분산손실, 신장효과 등에 대해 분석하였으며, 이는 능동소나, 음향대항, 감시 시스템과 같이 반사신호 합성에 관련된 여러가지 실시스템에 적용이 가능하다.

• Plant Resources
• /
• 제3권3호
• /
• pp.211-218
• /
• 2000

Intraspecific genetic relationship of 19 variation types of the Yam (Dioscorea alata) classified by their external morphological characteristics such as leaf and tuber shape were assessed by DNA using random and specific primer. Twenty two out of 113 primers (100 random[10-mer] primers, two 15 mer [M13 core sequence, and (GGAT)$_4$ sequence]) had been used in PCR-amplification. Only 12 primers, however, were success in DNA amplification in all of the analyzed plants, resulting in 93 randomly and specifically amplified DNA fragments. The analyzed taxa showed very high polymorphisms(69 bands, 71.0 %), allowing individual taxon to be identified based on DNA fingerprinting. Monomorphic bands among total amplified DNA bands of each primer was low under the 50%. Similarity indices between accessions were computed from PCR(polymerase chain reaction) data, and genetic relationships among intraspecific variations were closely related at the levels ranging from 0.66 to 0.90. These DNA data were not matched well with those of morphological characters since they were divided into two major groups at the similarity coefficient value of 0.70. Therefore, Grouping of species into variation types by mainly morphological charactistics was suggested unreasonable.

• 전기학회논문지
• /
• 제61권8호
• /
• pp.1164-1171
• /
• 2012

Recently, machine olfactory systems as an artificial substitute of the human olfactory system are being studied actively because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. Even though dimensionality reduction is the very important part, in pattern analysis, We handled effectively the dimensionality reduction by grouping the sensors of which the measured patterns are similar each other, where genetic algorithms were used for combination optimization. To identify the gas type, we constructed the hierarchical rule base with two frames by using rough set theory. The first frame is to accept measurement characteristics of each sensor and the other one is to reflect the identification patterns of each group. Thus, the proposed methods was able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• 대한산업공학회지
• /
• 제29권4호
• /
• pp.259-270
• /
• 2003

In order to properly design warning sounds that are affectively suitable to computer users, warning sounds used in Windows operating system were analyzed in terms of their sound properties; frequency band, spectral characteristics and physical intensity. A total of 36 warning sounds (3*4*3) were generated and tested with respect to three experimental variables. Among 178 collected affective adjectives that are related to hearing and sounds, seven representative affective adjectives were abstracted by statistical grouping techniques. In the experiment, subjective preference tests were performed for the 36 warning sounds according to the seven affective factors. From the result, the affective factors were again grouped into three major factors and the 60dB boost-type warning sounds at the low frequency band were, in general, the most preferred. followed by the 70dB cut-type sounds at the middle frequency band. These warning sounds have a characteristic of boost power spectrum below 1000Hz frequency band and received good scores on simplicity, clarity and accurateness.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
• /
• 제1권3호
• /
• pp.151-160
• /
• 2012

본 논문에서는 IEC61400-25 국제표준기반 풍력 SCADA 시스템을 위한 데이터베이스 설계를 수행하였다. 국제표준의 도입과 풍력발전의 대형화, 단지화로 인하여 발생하는 방대한 양의 데이터를 처리하기 위하여 체계적 관리는 필수적이다. 복잡하고 다양한 기능의 풍력 데이터들의 특성을 파악하고 사용자의 사전 요구사항을 반영하여 데이터베이스를 설계함으로써 데이터 공간 낭비를 줄이고, 관리의 효율성을 향상시킬 수 있다. 결과적으로 구축, 유지비용과 노력을 줄일 수 있을 것으로 기대한다.

• Journal of Information Processing Systems
• /
• 제16권1호
• /
• pp.171-183
• /
• 2020

Capsule endoscopy is one of the increasingly demanded diagnostic methods among patients in recent years because of its ability to observe small intestine difficulties. It is often conducted for 12 to 14 hours, but significant frames constitute only 10% of whole frames. Thus, it has been designed to automatically acquire significant frames through deep learning. For example, studies to track the position of the capsule (stomach, small intestine, etc.) or to extract lesion-related information (polyps, etc.) have been conducted. However, although grouping or labeling the training images according to similar features can improve the performance of a learning model, various attributes (such as degree of wrinkles, presence of valves, etc.) are not considered in conventional approaches. Therefore, we propose a class-labeling method that can be used to design a learning model by constructing a knowledge model focused on main lesions defined in standard terminologies for capsule endoscopy (minimal standard terminology, capsule endoscopy structured terminology). This method enables the designing of a systematic learning model by labeling detailed classes through differentiation of similar characteristics.

• 한국컴퓨터정보학회논문지
• /
• 제26권10호
• /
• pp.185-198
• /
• 2021

인터넷 기술의 발달로 기존의 추천 알고리즘은 사용자나 항목의 심층적인 특성을 학습할 수 없기 때문에 본 논문은 이 문제를 해결하기 위해 AMITI(주의 메커니즘 및 개선된 TF-IDF)에 기반한 추천 알고리즘을 제안했다. CNN(Convolutional Neural Network)에 2중 주의 메커니즘을 도입함으로써 CNN의 특징 추출 능력이 향상되고, 항목 특징에 다른 선호도 가중치가 할당되며, 사용자 선호도와 더 일치하는 권고사항이 달성되었다. 대상 사용자에게 항목을 추천할 때 점수 데이터와 항목 유형 데이터를 TF-IDF와 결합하여 권장 결과의 그룹화를 완료하였다. 본 논문에서 진행한 MovieLens-1M 데이터 세트에 대한 실험 결과는, AMITI 알고리즘이 권장 사항의 정확도를 향상시키고 프레젠테이션 방법의 순서와 선택성을 향상시킨다는 것을 보여준다.

• 산업융합연구
• /
• 제7권1호
• /
• pp.45-61
• /
• 2009

This research is aimed at grouping for the extent to which the workers' job satisfaction influences productivity with a view to improving theirs, shedding light on the difference between the workers' concepts of job satisfaction and those of the executives of the matter in terms of the statistic characteristics of individuals and coming up with efficient measures to put the Korean tax accounting offices into smooth operation. The paper is suggesting a total of eight hypotheses, and the researcher tested those with the help of difference analyses and a regression analysis. The findings reveal that there was a difference in productivity in accordance with academic background, positions and total number years of work, etc. but tat there was no difference in gender. And superiors and pay among the factors of job satisfaction influenced productivity, whereas promotion and coworkers didn't. The worker subjects and the executive subjects turned out to differ in terms of pay levels, the welfare of the works, and the level of their ability to carry out their business in regard to the actual situation of tax accounting offices in Korea.