• 농촌계획
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• 제10권4호
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• pp.19-28
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• 2004

In order to revitalize rural areas fundamentally through multifunctional utilization of their resources, it should be necessary to prepare the rational development plan to the areal characteristics and conditions, and the first priority of its planning works should be given to spatial planning. The space syntax method, a powerful objective and quantitative analysis tool on the relationship between social and spatial characteristics, was introduced in this study. Five Comprehensive Rural Clustered Villages Development Areas in the Jeonnam-province were selected as case study areas, of which total area's and included villages' spatial variables were measured and analyzed. Rural villages analyzed in this study have the spatial structure badly systematized and much complicated, which results from low integration and deep spatial depth of them. And, by virtue of relatively many axial lines, there should be few differences between villages in terms of local integration, connectivity and control, while being significant difference in terms of global integration showing the whole areal characteristics. Intelligibility, the correlation coefficient between connectivity(local variable) and integration(global one) is low, which means that the spatial structure of the study areas is difficult for visitors to understand the area or village well. Spatial configuration analysis results in the case study areas showed that each development area has a unique spatial structure and is differentiated in terms of not only local spatial variables but also global spatial variables. Therefore, global and local characteristics should be considered in spatial analysis of development areas.

• 사회복지연구
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• 제42권3호
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• pp.207-231
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• 2011

이 연구는 기초지방정부의 사회복지비 지출수준과 이에 영향을 미치는 요인들을 정부 간 관계의 맥락에서 파악하였다. Beck and Kats가 제안한 PCSE(Panel corrected Standard Error) 모형을 이용하여 2003년부터 2008년까지 230개 기초지방정부의 사회복지비 지출수준에 결정요인을 분석하였다. 분석결과를 정리하면 다음과 같다. 첫째, 상위정부로부터의 재정이전이 기초지방정부의 사회복지비 지출확대에 영향을 미치는 것을 확인하였다. 둘째, 기초지방정부와 광역정부, 중앙정부와의 정치적 관계를 나타내는 정당구조가 사회복지비 지출을 결정하는데 영향을 미치는 것으로 나타났다. 셋째, 기초지방정부들 간에 복지확대 경쟁이 존재하고 있음을 파악하였다. 이와 같은 분석결과는 우리나라와 같이 중앙집권적 성격이 강한 지방자치제 하에서는 지역사회 내에 존재하는 요인들뿐만 아니라 정부 간 관계적 요인들이 지역복지 발전에 중요한 영향을 미치고 있음을 시사한다.

• 전기전자학회논문지
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• 제25권4호
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• pp.778-781
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• 2021

본 논문에서는 SPICE를 사용한 16단 3D NAND Flash memory compact modeling을 제안한다. 동일한 structure와 simulation 조건에서 Down Coupling Phenomenon(DCP)과 Natural Local Self Boosting(NLSB)에 대한 channel potential을 Technology Computer Aided Design(TCAD) tool Atlas(Silvaco^TM)와 SPICE로 simulation하고 분석했다. 그 결과 두 현상에 대한 TCAD와 SPICE의 channel potential이 매우 유사한 것을 확인할 수 있었다. SPICE는 netlist를 통해 소자 structure를 직관적으로 확인할 수 있다. 또한, simulation 시간이 TCAD에 비해 짧게 소요된다. 그러므로 SPICE를 이용하여 3D NAND Flash memory의 효율적인 연구를 기대할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.825-836
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• 2016

In this paper, a speed-up technique for the non-local means (NLM) image denoising method based on local binary descriptor (LBD) is proposed. In the NLM, most of the computation time is spent on searching for non-local similar patches in the search window. The local binary descriptor which represents the structure of patch as binary strings is employed to speed up the search process in the NLM. The descriptor allows for a fast and accurate preselection of non-local similar patches by bitwise operations. Using this approach, a tradeoff between time-saving and noise removal can be obtained. Simulations exhibit that despite being principally constructed for speed, the proposed algorithm outperforms in terms of denoising quality as well. Furthermore, a parallel implementation on GPU brings NLM-LBD to real-time image denoising.

• 대한수학회지
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• 제36권2호
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• pp.431-445
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• 1999

A digraph T is called a local tournament if for every vertex x of T, the set of in-neighbors as well as the set of out-neighbors of in-neighbors of x induce tournaments. Let x and y be two vertices of a 3-connected and arc-3-cyclic local tournament T with y x. We investigate the structure of T such that T contains no (x,y)-path of length k for some k with 3 k V(T) -1. Our result generalized those of [2] and [5] for tournaments.

• 충청수학회지
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• 제22권1호
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• pp.73-80
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• 2009

This paper aims to study local and global structure of holomorphic flows on $\mathbb{C}^1$. At a singular point of a holomorphic flow, we locally sector the flow into parabolic or elliptic types. By the local structure of holomorphic flows, we classify all the possible types of topologies of $\omega$-limit sets.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1988년도 가을 학술발표회 논문집
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• pp.36-42
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• 1988

In this study, a formulation of the idealized plate element based upon the idealized structural unit method(ISUM) firstly proposed by Ueda et．al is made in an attempt to analyze the geometric nonlinear behaviour up to the buckling strength of thin-walled long structures like box-column structure including the coupling effect between local and global buckling. An application to the example box-column is also performed and it is found that the present method gives reliable results with consuming very short computing times and therefore is very useful for evaluation of the buckling strength of thin-walled long structures.

• 한국콘텐츠학회논문지
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• 제17권8호
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• pp.130-143
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• 2017

본 연구는 'B'지역노조라는 현대 일본의 '계급지향적' 노동운동을 검토하기 위해, 우선 그 이론적 틀을 모색하는 작업이다. 현재 일본에서 '계급지향적'인 노동운동은 주변에서 '잔여적인' 노동운동으로 설정되지만, 그럼에도 그 활동은 활발히 계속되고 있다. 이에 본 연구에서 그 '계급지향적' 노동운동을 분석하기 위한 이론적 틀을 살펴보았다. 먼저 윌리엄즈에 의한 개념의 변화를 검토하고, 마르크스주의의 계급 계급의식 개념과 '언어적 전회'의 새로운 주체 개념 등을 살펴보았다. 그리고 본 연구에서는 'B'지역노조의 사례에 맞게 '감정구조' 개념을 재해석하였다. 이와 같은 과정을 거쳐 본 연구에서는 'B'지역노조의 '집단적 노동자'와 '개인화된 노동자', '노동자'와 '비노동자'가 물질적 공간 혹은 비물질적 공간에서 집단화를 이룬다고 보았고, 그 '감정구조'는 '''계급지향성''을 둘러싼 모순과 절충'이라고 정리하였다. 그리고 마지막으로 본 연구에서는 그에 대한 '감정구조'의 모형을 제시했다.

• 전자공학회논문지C
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• 제35C권3호
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• pp.79-89
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• 1998

The Error Back-Propagation(EBP) algorithm is widely applied to train a multi-layer perceptron, which is a neural network model frequently used to solve complex problems such as pattern recognition, adaptive control, and global optimization. However, the EBP is basically a gradient descent method, which may get stuck in a local minimum, leading to failure in finding the globally optimal solution. Moreover, a multi-layer perceptron suffers from locking a systematic determination of the network structure appropriate for a given problem. It is usually the case to determine the number of hidden nodes by trial and error. In this paper, we propose a new algorithm to efficiently train a multi-layer perceptron. OUr algorithm uses stochastic perturbation in the weight space to effectively escape from local minima in multi-layer perceptron learning. Stochastic perturbation probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the EGP learning gets stuck to it. Addition of new hidden nodes also can be viewed asa special case of stochastic perturbation. Using stochastic perturbation we can solve the local minima problem and the network structure design in a unified way. The results of our experiments with several benchmark test problems including theparity problem, the two-spirals problem, andthe credit-screening data show that our algorithm is very efficient.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.914-927
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• 2017

Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model-local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.