• 제목/요약/키워드: Low level feature

검색결과 273건 처리시간 0.03초

2차측 결합 인덕터를 이용한 ZVZCS Three Level DC/DC 컨버터에 관한 연구 (A Study on the Zero-Voltage and Zero-Current-Switching Three Level DC/DC Converter using Secondary Coupled Inductor)

  • 배진용;김용;백수현;김필수;이은영
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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    • pp.200-204
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    • 2001
  • A ZVZCS(Zero Voltage and Zero Current Switching) Three Level DC/DC Converter is presented to secondary auxiliary circuit. The new converter presented in this paper used a phase shift control with a flying capacitor in the primary side to achieve ZVS for the outer switch. A secondary auxiliary circuit, which consists of one small capacitor two small diode and one coupled inductor is added in the secondary to provides ZVZCS conditions to primary switches, ZVS for outer switches and ZCS for inner switches. Many advantages including simple circuit topology high efficiency, and low cost make the new converter attractive for high power applications. The principle of operation, feature and design considerations are illustrated and verified through the experiment with a 1kW 50kHz IGBT based experimental circuit.

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Pattern Recognition of Meteorological fields Using Self-Organizing Map (SOM)

  • Nishiyama Koji;Endo Shinichi;Jinno Kenji
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2005년도 학술발표회 논문집
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    • pp.9-18
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    • 2005
  • In order to systematically and visually understand well-known but qualitative and rotatively complicated relationships between synoptic fields in the BAIU season and heavy rainfall events in Japan, these synoptic fields were classified using the Self-Organizing Map (SOM) algorithm. This algorithm can convert complex nonlinear features into simple two-dimensional relationships, and was followed by the application of the clustering techniques of the U-matrix and the K-means. It was assumed that the meteorological field patterns be simply expressed by the spatial distribution of wind components at the 850 hPa level and Precipitable Water (PW) in the southwestern area including Kyushu in Japan. Consequently, the synoptic fields could be divided into eight kinds of patterns (clusters). One of the clusters has the notable spatial feature represented by high PW accompanied by strong wind components known as Low-Level Jet (LLJ). The features of this cluster indicate a typical meteorological field pattern that frequently causes disastrous heavy rainfall in Kyushu in the rainy season. From these results, the SOM technique may be an effective tool for the classification of complicated non-linear synoptic fields.

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다중해상도 개념을 이용한 기계 부품의 유사성 비교 (Similarity Comparison of Mechanical Parts)

  • 홍태식;이건우;김성찬
    • 한국CDE학회논문집
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    • 제11권4호
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    • pp.315-325
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    • 2006
  • It is very often necessary to search for similar parts during designing a new product because its parts are often easily designed by modifying existing similar parts. In this way, the design time and cost can be reduced. Thus it would be nice to have an efficient similarity comparison algorithm that can be used anytime in the design process. There have been many approaches to compare shape similarity between two solids. In this paper, two parts represented in B-Rep is compared in two steps: one for overall appearances and the other for detail features. In the first step, geometric information is used in low level of detail for easy and fast pre-classification by the overall appearance. In the second step, feature information is used to compare the detail shape in high level of detail to find more similar design. To realize the idea above, a multi resolution algorithm is proposed so that a given solid is described by an overall appearance in a low resolution and by detail features in high resolution. Using this multi-resolution representation, parts can be compared based on the overall appearance first so that the number of parts to be compared in high resolution is reduced, and then detail features are investigated to retrieve the most similar part. In this way, computational time can be reduced by the fast classification in the first step while reliability can be preserved by detail comparison in the second step.

Dual Vector Control Strategy for a Three-Stage Hybrid Cascaded Multilevel Inverter

  • Kadir, Mohamad N. Abdul;Mekhilef, Saad;Ping, Hew Wooi
    • Journal of Power Electronics
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    • 제10권2호
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    • pp.155-164
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    • 2010
  • This paper presents a voltage control algorithm for a hybrid multilevel inverter based on a staged-perception of the inverter voltage vector diagram. The algorithm is applied to control a three-stage eighteen-level hybrid inverter, which has been designed with a maximum number of symmetrical levels. The inverter has a two-level main stage built using a conventional six-switch inverter and medium- and low- voltage three-level stages constructed using cascaded H-bridge cells. The distinctive feature of the proposed algorithm is its ability to avoid the undesirable high switching frequency for high- and medium- voltage stages despite the fact that the inverter's dc sources voltages are selected to maximize the number of levels by state redundancy elimination. The high- and medium- voltage stages switching algorithms have been developed to assure fundamental switching frequency operation of the high voltage stage and not more than few times this frequency for the medium voltage stage. The low voltage stage is controlled using a SVPWM to achieve the reference voltage vector exactly and to set the order of the dominant harmonics. The inverter has been constructed and the control algorithm has been implemented. Test results show that the proposed algorithm achieves the desired features and all of the major hypotheses have been verified.

The Potential Impact of Service Quality Uncertainty and Retail Pricing Strategies on Consumer Purchase Intention

  • Nguyen, Dieu Hoa;Jeong, Euihyeon;Chung, Jaekwon
    • 유통과학연구
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    • 제16권12호
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    • pp.13-21
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    • 2018
  • Purpose - Because it is not possible to assess the quality of service products before experiencing them, one feature of a service product is quality uncertainty; hence consumers may react sensitively to pricing. It is necessary to investigate how different pricing strategies affect consumer purchase intention depending on the level of service quality uncertainty. Research design, data, and methodology - The authors have investigated the potential impact of the level of service quality uncertainty, price discount rate and presentation method on consumer purchase intention. A play was selected as an experimental stimulus, and Vietnamese consumers were surveyed to verify the hypotheses. Results - When uncertainty regarding service quality is low, consumer purchase intention is higher when the price discount rate is high or when the price is low. When uncertainty regarding service quality is high, if the normal price, discount rate, and discounted price are presented simultaneously, consumer purchase intention is higher when the price discount rate is low, but when only the discounted price is presented, purchase intention is higher when the price discount rate is high. Conclusions - The results of this study can provide valuable practical implications for pricing for service products with quality uncertainty.

달 영구음영지역에서 로버 탐사를 위한 저조도 영상강화 및 영상 특징점 추출 성능 실험 (Experiment on Low Light Image Enhancement and Feature Extraction Methods for Rover Exploration in Lunar Permanently Shadowed Region)

  • 박재민;홍성철;신휴성
    • 대한토목학회논문집
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    • 제42권5호
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    • pp.741-749
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    • 2022
  • 달 영구음영지역에 얼음 형태의 물이 발견되면서 주요 우주국들은 로버 중심의 현장 탐사를 준비 중이다. 달 영구음영지역은 극지역 크레이터의 중심부로 태양광이 직접 도달하지 않지만, 크레이터 벽면으로부터 반사되는 태양광으로 인해 일정 수준의 저조도 환경이 유지되는 것으로 예상된다. 본 연구에서는 달 영구음영지역의 조도와 지형환경을 모사한 실내 테스트베드를 구축하여 모의 지형영상을 촬영하였다. 모의 영상을 대상으로 저조도 영상강화 기법(CLAHE, Dehaze, RetinexNet, GLADNet)을 적용하여 밝기값과 색상복원 효과를 분석하였고, 특징점 추출 및 정합 기법(SIFT, SURF, ORB, AKAZE)의 성능 향상을 분석하였다. 실험 결과 GLADNet과 Dehaze 영상 순으로 저조도 환경에 강인한 시인성 개선 효과를 보여주었다. 반면 특징점 검출 및 정합 기법은 Dehaze와 GLADNet 영상 순으로 성능이 향상됨을 확인하였고, 특히 ORB와 AKAZE의 성능이 크게 개선되었다. 달 탐사에서 로버 탑재 카메라는 3차원 지형정보구축과 지질학적 조사에 활용된다. 따라서 GLADNet은 토양 성분과 암석 종류 판별에 유용하고, Dehaze는 로버의 주행과 함께 3차원 지형정보 구축에 적합할 것으로 판단된다.

다중 특징을 지원하는 학습 기반의 saliency map에 관한 연구 (Estimate Saliency map based on Multi Feature Assistance of Learning Algorithm)

  • 한현호;이강성;박영수;이상훈
    • 한국융합학회논문지
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    • 제8권6호
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    • pp.29-36
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    • 2017
  • 본 논문에서는 인간의 시각인지 형태와 유사한 결과를 갖는 Saliency map의 정확성과 신뢰성을 향상시키기 위해 학습한 다중 특징을 기반으로 개선된 saliency map 방법을 제안한다. 기존의 Saliency map 생성에서 색상 기반의 돌출 영역 추정 시 발생하는 역 선택이나 부분손실 등의 부정확한 결과가 나오는 것을 보완하기 위해 제안하는 방법은 학습 기반의 다중 특징 데이터를 생성하였다. 원 영상에서의 색상 패턴과 특이성을 갖는 영역의 구별과정을 거쳐 영상에서 고려될 특성들을 분석하고, LAB 색 공간 기반의 색상 분석을 이용한 유사 돌출 영역 정의와 특이성 영역의 조합으로 학습 데이터를 구성한다. 구성된 학습 데이터와 주파수, 색상, 초점정보 등의 low level feature로 구한 돌출 정보를 결합한 뒤 최종 saliency map을 구하기 위해 재구성 과정을 거쳐 부정확한 saliency 영역을 최소화하도록 하였다. 실험을 위해 Ground truth 이미지를 각 실험 결과와 비교하여 precision-recall 및 F-Measure 값을 구한 결과 기존 알고리즘에 비해 7%, 29%의 향상된 결과를 나타내었다.

Image Retrieval Method Based on IPDSH and SRIP

  • Zhang, Xu;Guo, Baolong;Yan, Yunyi;Sun, Wei;Yi, Meng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권5호
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    • pp.1676-1689
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    • 2014
  • At present, the Content-Based Image Retrieval (CBIR) system has become a hot research topic in the computer vision field. In the CBIR system, the accurate extractions of low-level features can reduce the gaps between high-level semantics and improve retrieval precision. This paper puts forward a new retrieval method aiming at the problems of high computational complexities and low precision of global feature extraction algorithms. The establishment of the new retrieval method is on the basis of the SIFT and Harris (APISH) algorithm, and the salient region of interest points (SRIP) algorithm to satisfy users' interests in the specific targets of images. In the first place, by using the IPDSH and SRIP algorithms, we tested stable interest points and found salient regions. The interest points in the salient region were named as salient interest points. Secondary, we extracted the pseudo-Zernike moments of the salient interest points' neighborhood as the feature vectors. Finally, we calculated the similarities between query and database images. Finally, We conducted this experiment based on the Caltech-101 database. By studying the experiment, the results have shown that this new retrieval method can decrease the interference of unstable interest points in the regions of non-interests and improve the ratios of accuracy and recall.

Instance segmentation with pyramid integrated context for aerial objects

  • Juan Wang;Liquan Guo;Minghu Wu;Guanhai Chen;Zishan Liu;Yonggang Ye;Zetao Zhang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권3호
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    • pp.701-720
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    • 2023
  • Aerial objects are more challenging to segment than normal objects, which are usually smaller and have less textural detail. In the process of segmentation, target objects are easily omitted and misdetected, which is problematic. To alleviate these issues, we propose local aggregation feature pyramid networks (LAFPNs) and pyramid integrated context modules (PICMs) for aerial object segmentation. First, using an LAFPN, while strengthening the deep features, the extent to which low-level features interfere with high-level features is reduced, and numerous dense and small aerial targets are prevented from being mistakenly detected as a whole. Second, the PICM uses global information to guide local features, which enhances the network's comprehensive understanding of an entire image and reduces the missed detection of small aerial objects due to insufficient texture information. We evaluate our network with the MS COCO dataset using three categories: airplanes, birds, and kites. Compared with Mask R-CNN, our network achieves performance improvements of 1.7%, 4.9%, and 7.7% in terms of the AP metrics for the three categories. Without pretraining or any postprocessing, the segmentation performance of our network for aerial objects is superior to that of several recent methods based on classic algorithms.

적응적 상관도를 이용한 주성분 변수 선정에 관한 연구 (A Study on Selecting Principle Component Variables Using Adaptive Correlation)

  • 고명숙
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제10권3호
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    • pp.79-84
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    • 2021
  • 고차원의 데이터를 처리하기 위해서는 데이터의 성질을 유지하면서 특징을 잘 반영할 수 있는 특징 추출 방법이 필요하다. 주성분분석 방법은 고차원 데이터에 포함된 정보를 저차원의 데이터로 변환하여 원래 데이터의 변수 수보다 적은 수의 변수로 고차원 데이터를 표현 할 수 있는 방법으로서 데이터의 특징 추출을 위한 대표적인 방법이다. 본 연구에서는 데이터가 고차원인 경우 데이터 특징 추출을 위한 주성분 분석에 있어서 주성분 변수 선정 시 적응적 상관도를 기반으로 한 주성분 분석 방법을 제안한다. 제안하는 방법은 입력 데이터간의 상관 관계를 기반으로 상관도를 적응적으로 반영하여 데이터의 주성분을 분석함으로써 다른 여러 변수에 중복적으로 상관도가 높은 변수와 주성분을 유도하는데 연관성이 적은 변수를 주성분 변수 후보 대상에서 제외시키고자 한다. 고유벡터 계수 값에 의한 주성분 위계를 분석하고 위계가 낮은 주성분이 변수로 선정이 되는 것을 막고 또한 상관 분석을 통하여 데이터의 중복 발생이 데이터 편향을 유도하는 것을 최소화하 하고자 한다. 이를 통하여 주성분 변수 선정 시 데이터 편향성의 영향을 줄임으로써 실제 데이터의 특징을 잘 나타내는 주성분 변수를 선정하는 방법을 제안하고자 한다.