• 대한임베디드공학회논문지
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• 제16권5호
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• pp.179-186
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• 2021

For stereo matching based on deep learning, the design of network structure is crucial to the calculation of matching cost, and the time-consuming problem of convolutional neural network in image processing also needs to be solved urgently. In this paper, a method of stereo matching using sparse loss volume in parallax dimension is proposed. A sparse 3D loss volume is constructed by using a wide step length translation of the right view feature map, which reduces the video memory and computing resources required by the 3D convolution module by several times. In order to improve the accuracy of the algorithm, the nonlinear up-sampling of the matching loss in the parallax dimension is carried out by using the method of multi-category output, and the training model is combined with two kinds of loss functions. Compared with the benchmark algorithm, the proposed algorithm not only improves the accuracy but also shortens the running time by about 30%.

• 인터넷정보학회논문지
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• 제12권2호
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• pp.113-122
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• 2011

최근, 온라인상에서 사용자간 관계형성 및 커뮤니케이션을 지원하는 Social Network Service(SNS)들이 주목을 받고 있다. SNS에서 형성되는 사용자 정보와 그들의 활동에 대한 정보는 사용자에 대한 특징적인 정보로서 추천과 같은 외부서비스에서 재사용될 수 있는 유용한 정보로 여겨진다. 기존의 사용자 기본 프로파일 정보를 통한 분석이나, 친밀도 및 유사도를 도출하기 위한 단편적인 분석 방법은 가공된 정보의 활용에 있어 한계점을 지닌다. 본 논문에서는 사용자의 SNS활동들로 부터 사용자간 상호영향을 도출하고 다차원 상호관계(Multi-dimension interaction)를 표현 할 수 있는 통합 된 프로파일 모델을 정의하고 이를 도출하기 위한 시스템을 제안한다. 제안된 시스템은 대표적인 SNS인 트위터(Twitter.com)부터 사용자 정보를 수집하여 정보의 재가공을 수행한다. 본 논문의 실험에서는 가공된 정보를 통해 얻을 수 있는, 기존 방식에서는 드러나지 않던 사용자간의 새로운 관계들에 대해 설명한다. 가공된 정보는 특정 사용자의 통합 프로파일로서 컨텐츠 아이템 추천과 같은 외부서비스에서 활용가능 할 것으로 기대된다.

• East Asian mathematical journal
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• 제28권1호
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• pp.101-107
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• 2012

For each dimension exceeds 1, determining the number of multi-dimensional partitions of a positive integer is an open question in combinatorial number theory. For n ${\leq}$ 14 and d ${\geq}$ 1 we derive a formula for the function ${\wp}_d(n)$ where ${\wp}_d(n)$ denotes the number of partitions of n arranged on a d-dimensional space. We also give an another definition of the d-dimensional partitions using the union of finite number of divisor sets of integers.

• 대한수학회보
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• 제58권3호
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• pp.559-572
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• 2021

It is well known that every invariant harmonic function on the unit ball of the multi-dimensional complex space has the volume version of the invariant mean value property. In 1993 Ahern, Flores and Rudin first observed that the validity of the converse depends on the dimension of the underlying complex space. Later Lie and Shi obtained the analogues on the unit ball of multi-dimensional real space. In this paper we obtain the half-space analogues of the results of Liu and Shi.

• 한국디지털건축인테리어학회논문집
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• 제11권2호
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• pp.61-70
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• 2011

This study aims to establish the concept about a new approaching method dor remodeling in the planning step. also, this study sets up the way how to approach in a dimensional way by classifying the conceptual composition of the target housing as a method. The dimensional definition is as below. The one dimensional approach: the spot. the two dimensional approach: the line, the three dimensional approach: the apatial mass, the four dimensional approach: space + time, the n dimensional (multi-dimensional) approach: the space + time + emotion. The research findings are as follows : For the purpose of remodeling, the old housing should be viewed in the three dimensional shape and space. It is defined as multi-dimensional module method to design the shape and space of the target housing in a multi-dimensional point, considering the three dimensional space composition, the emotion of the user, the housing itself. and the time of the user.

• 경영과학
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• 제24권2호
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• pp.57-72
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• 2007

Many Applications of scientific research have coupled with functional data signal clustering techniques to discover novel characteristics that can be used for the diagnoses of several issues. In this article we present an interpretable multi-scale cluster hierarchy framework for clustering functional data using its multi-aspect frequency information. The suggested method focuses on how to effectively select transformed features/variables in unsupervised manner so that finally reduce the data dimension and achieve the multi-purposed clustering. Specially, we apply our suggested method to mutual fund returns and make superior-performing funds group based on different aspects such as global patterns, seasonal variations, levels of noise, and their combinations. To promise our method producing a quality cluster hierarchy, we give some empirical results under the simulation study and a set of real life data. This research will contribute to financial market analysis and flexibly fit to other research fields with clustering purposes.

• 한국기계가공학회지
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• 제20권1호
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• pp.110-115
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• 2021

A multi-band, compact, and complex vehicle roof antenna has become important in terms of car exterior design and multi-functions which include Radio, DAB/DMB, SXM, GNSS, Telematics, and V2X. In this paper, we propose a compact multi-band V2X pole-type roof antenna. Using impedance change characteristic, a single pole antenna which has multiband such as radio, DAB/DMB, telematics, and V2X band is proposed. With two patch antennas for GNSS and SXM, the dimension of a multiband roof antenna is 131x63x37mm only.

• 한국의류학회지
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• 제20권6호
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• pp.1016-1026
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• 1996

The purpose of this study was to extract protypes from features and concrete images of Lotus and Crane patterns. A qualitative and a quantitative methods were used. Qualitative informations were obtained from depth Interviews for pattern selection and feature extraction, and quantitative informations from a quail-experiment for pattern caregorization. The subjects were 20 female design students and non-design, students in Teajon. The results were summerized into a similarity metrix which was interpreted by the cluster analysis and the multi-dimensional scling(MDS). The patterns for the study were grouped into 8 clusters. Four dimensions were chosen for the MDS. The location of each pattern was visualized in a 2-dimesional spaces and the location of each cluster in a 3-dimensional spaces. The first dimension, "Lotus" vs "Crane" refired to pattern types, and the second dimension, "realistic" vs "transformable", the transformability. The third dimension, "simple" vs "complex", refired to the degree of simplification, and the forth dimension, "continuous" vs "discontinuous", continuity. The results of the Quantitative analysis could be summerized into 3-level prototype hiararchy In the first level, the patterns were devided clearly into two groups. Lotus and Crane by pattern types. In the second levelk, each group was devided into twosubgroups by continuity. In the third, each subgroup was divided into four subgroups by transformability and the degree of simplification. Four protypes, the final targets of the present study, were extracted from the third level. The are Stylized, Realistic, Decorative, Abstract types.d from the third level. The are Stylized, Realistic, Decorative, Abstract types.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.156-161
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• 2003

It is an interest problem to predict substance distributions in three-dimensional space. Recently, a research field as Geostatistics is advanced. It is a kind of inter- or extrapolation mathematically. Some useful means for the inter- and extrapolation are known, in which slide window method with neural networks is hopeful one. We propose multi-dimensional extrapolation using multi-layer neural networks and the slide-window method. The multi-dimensional extrapolation is not similar to one-dimension. It has plural algorithms. We researched line predictors and local-plain predictors I two-dimensional space. The both predictors are equivalent; however, in multi-dimensional extrapolation, it is very important to find the direction of predictions. Especially, since the slide window method requires information to predict the future in sampling data, if they are not ordered appropriately in the direction, the predictor cannot operate. We tested the extrapolation for typical two-dimensional functions, and found an excellent character of slide-window method based on local-plain. By using the method, we can extrapolate the function until twice-outer regions of the definitions.

• 방송공학회논문지
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• 제14권6호
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• pp.733-741
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• 2009

디지털 통신 시스템에서는 대역폭과 전력을 효율적으로 사용하면서 신뢰성 높은 데이터 전송을 요구한다. 본 논문에서는 다중 반송파 방식을 사용하는 시스템에서 반송파의 직교성을 이용하여 다차원 성상도를 구현하고 전력 소비가 큰 성상 포인트의 위치를 재배치하여 평균 소비 전력을 감소시킬 수 있는 기술을 제안한다. 기존의 2차원 QAM 변조 방식을 N개의 부반송파를 사용하여 다차원 QAM 형태로 단순하게 변환하면 2 N차원 큐브 형태의 성상 포인트가 구성되는데, 전력 소비가 많은 최외각 성상 포인트들을 효율적으로 재배치하면 전력 소비를 최소화할 수 있는 2 N차원 구 형태의 성상도를 구성할 수 있다. 이와 같은 방식으로 16-QAM부터 2,048-QAM까지의 2차원 성상도를 다차원으로 변환하여 구성하고 전산모의실험을 통해 얻을 수 있는 평균 소비 전력 이득 값을 비교 분석하였다. 차원을 높일수록 재배치 성상 포인트들이 증가하므로 평균 소비 전력 이득 값이 커지는 것을 알 수 있다. 하지만 차원 증가에 따른 이득의 증가비율은 로그 형태를 가지고 있기 때문에 QAM의 성상 포인트 개수에 따라 일정한 이득값에 수렴하게 되고 수렴 값을 바탕으로 적정 다차원 성상도를 유도할 수 있다. 본 논문에서 제안한 방법으로 데이터를 전송하는 것은 하드웨어 복잡도 증가가 거의 없이 소비 전력의 효율성을 높이는데 효과적이다.