• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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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%.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.113-122
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• 2011

Social Network Service(SNS) has become a hot trend as a web service which helps users construct social relationships in the web and enables online communication. The information about user activities and behaviors obtained from the SNSs is expected to be an useful knowledge source for other services such as recommendation services. Most of previous researches on SNS rely on analyzing overall network topology and surveying the activities in a one-dimensional aspect. This paper propose a system for measuring multi-dimensional interaction through the activities in a SNS. The proposed system delivers an unified profile (consisting of profile and multi-dimension interaction) model from user-activities in Twitter.com. At the experimental section, some meaningful perspectives on a set of the unified profiles are described.

• East Asian mathematical journal
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• v.28 no.1
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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.

• Bulletin of the Korean Mathematical Society
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• v.58 no.3
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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.

• Journal of The Korean Digital Architecture Interior Association
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• v.11 no.2
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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.

• Korean Management Science Review
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• v.24 no.2
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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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.1
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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.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.6
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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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• 2003.10a
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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.

• Journal of Broadcast Engineering
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• v.14 no.6
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• pp.733-741
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• 2009

The design rule of digital communication systems is the reliable data transmission with high spectral efficiency and minimum allowable power. This paper suggests the method that saves the average power by implementing a multi-dimensional constellation in case of multi-carrier communication system. By using multi-dimensional constellations we can relocate constellation points in the form of a sphere. If we simply convert the two-dimensional QAM modulation into multi-dimensional QAM, constellation points of 2 N dimensional cube form are made up. Relocating outermost constellation points of 2 N dimensional cube form into low energy constellation points, the constellation of the 2 N-dimensional sphere form is made up which decreases power consumption. In this paper, the multi-dimensional constellations of 2 N-dimensional sphere form are designed from 16-QAM to 2,048-QAM, and power reductions are obtained by comparing constellations of 2-dimensional QAMs and multi-dimensional constellations of 2 N-dimensional sphere form. The result shows that the average power consumption of higher dimensional constellations increases, because the more a dimension elevates, the more the relocatable constellation points increase. But, the increment of the average power savings decreases as the a dimension elevates. The transmission of the data by using multi-dimensional constellations of the sphere form is effective to save the average power consumption with little hardware complexity.