• Spatial Information Research
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• v.10 no.2
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• pp.215-232
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• 2002

Variables representing neighborhood quality should be included in hedonic price models to control lfor the influences of negative or positive externalities from the quality of neighborhood on urban housing prices. This study proposes a GIS-based method to effectively measure the neighborhood quality variable when data on the neighborhood quality are aggregated by census sub area. This study also tests the superiority of the proposed neighborhood quality variable created by intensive use of GIS operations to a neighborhood variable not based on GIS operations in explaining the housing price variations by using Seoul＇s apartment sales data. The results from this study show that the neighborhood quality variable based on GIS-based operations shows better performance in explaining the urban housing price variations in Seoul＇s housing market. The implication from the results is that the potentials of GIS-based spatial operations in creating neighborhood quality variables should be well acknowledged by the researchers in the area of urban housing market study and GIS-based spatial operations should be more actively applied to generate better neighborhood quality variables for hedonic price models.

• MALSORI
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• no.67
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• pp.79-102
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• 2008

In this paper, we investigate the relation between Bayes factor and likelihood ratio test (LRT) approaches and apply the neighborhood information of Bayes factor to building an alternate hypothesis model of the LRT system. To consider the neighborhood approaches, we contemplate a distance measure between models and algorithms to be applied. We also evaluate several methods to improve performance of utterance verification using neighborhood information. Among these methods, the system which adopts anti-models built by collecting mixtures of neighborhood models obtains maximum error rate reduction of 17% compared to the baseline, linear and weighted combination of neighborhood models.

• Industrial Engineering and Management Systems
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• v.8 no.1
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• pp.22-28
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• 2009

We consider facility layout problems, where mn facility units are assigned into mn cells. These cells are arranged into a rectangular pattern with m rows and n columns. In order to solve this cell type facility layout problem, many approximation algorithms with improved local search methods were studied because it was quite difficult to find exact optimum of such problem in case of large size problem. In this paper, new algorithms based on Simulated Annealing (SA) method with two neighborhood generation methods are proposed. The new neighborhood generation method adopts the exchanging operation of facility units in accordance with adjacent preference. For evaluating the performance of the neighborhood generation method, three algorithms, previous SA algorithm with random 2-opt neighborhood generation method, the SA-based algorithm with the new neighborhood generation method (SA1) and the SA-based algorithm with probabilistic selection of random 2-opt and the new neighborhood generation method (SA2), are developed and compared by experiment of solving same example problem. In case of numeric examples with problem type 1 (the optimum layout is given), SA1 algorithm could find excellent layout than other algorithms. However, in case of problem type 2 (random-prepared and optimum-unknown problem), SA2 was excellent more than other algorithms.

• Journal of the Korean housing association
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• v.28 no.1
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• pp.9-17
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• 2017

This study investigates and analyzes (1) the status of neighborhood commercial facilities, (2) the location of neighborhood commercial facilities and (3) the users' viewpoint of them for the purpose of establishing the revitalizing factors of neighborhood commercial facilities within permanent rental housing complexes. This study attempts to determine the factors that revitalize neighborhood commercial facilities through quantitative factor analysis based on the analysis of the basic status and purpose of neighborhood commercial facilities using the basic status of permanent rental housing complexes and the quantitative data on neighborhood commercial facilities within these complexes. A survey investigating the residents' perception of neighborhood commercial facilities was conducted to analyze the qualitative aspects neighborhood commercial facilities within permanent rental housing complexes. The factors affecting the revitalization of neighborhood commercial facilities were analyzed by quantifying the actual problems perceived by the users and the elements of their use patterns. From these analysis results, it was found that the factors are not independent from one another, but organically affect one another. It is expected that more meaningful data will be obtained if future studies conduct correlation analysis and weighted value analysis on each factor based on the findings of the present study.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.6
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• pp.13-21
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• 2016

Feature selection is the one of important issue in the field of data mining and machine learning. It is the technique to find a subset of features which provides the best classification performance, from the source data. We propose a feature subset selection method using the neighborhood rough set model based on information granularity. To demonstrate the effectiveness of proposed method, it was applied to select the useful features associated with breast tumor diagnosis of 298 shape features extracted from 5,252 breast ultrasound images, which include 2,745 benign and 2,507 malignant cases. Experimental results showed that 19 diagnostic features were strong predictors of breast cancer diagnosis and then average classification accuracy was 97.6%.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.6
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• pp.963-971
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• 1990

This paper proposes a memory intensive VLSI architecture for the realization of real-time 3x3 neighborhood processor based on the distributed arithmetic. The proposed architecture is characterized by a bit serial and multi-kernel parallel processing which exploits the pixel kernel parallelism and concurrency. The chip implements 8 neighborhood processing elements in parallel with efficirnt input and output modules which operate concurrently. Besides the a4chitectural design of a neighborhood processor, the design methodology using module generator concept has been considered and MOGOT(MOdule Generator Oriented VLSI design Tool) has been constructed based on the workstation. Based on these design environments MOGOT, it has been shown that the main part of the suggested architecture can be designed efficiently using 2\ulcorner double metal CMOS technology. It includes design of input delay and data conversion module, look-up table for inner product operation, carry save accumulator, output data converter and delay module, and control module.

• Journal of Preventive Medicine and Public Health
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• v.38 no.3
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• pp.259-266
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• 2005

Recently much attention has been paid to the effect of neighborhood characteristics on the health of individuals, independent of individual demographic and/or socioeconomic characteristics. Although many empirical studies of a kind, mostly based on Western society, have appeared on various international journals, few studies have shown empirical evidence of neighborhood characteristics as an independent and significant risk factor of ill health in Korea. This paper discusses possible reasons that neighborhood seems to be neither significant nor substantial regarding its impact on the health of Koreans. Addressing the uniqueness of Korean society regarding the concept of neighborhood, attributes of neighborhoods, and methodological challenges, authors suggest that more sophisticated conceptual and methodological approach, specific to Korean society, should enable to reveal the effect of neighborhood characteristics on individual health in Korea.

• Korean Journal of Child Studies
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• v.37 no.1
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• pp.37-48
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• 2016

Objective: To prevent adolescent drinking and smoking, this study proposed a strategy based on the ecological perspective. Methods: The study applied multilevel moderated logistic regression analysis on nationally representative individual-level (2,046 9th grade adolescents) and neighborhood-level (92 geographic areas) data. Results: There was a positive association between risky neighborhood environments (e.g., rate of smoking, drinking, and presence of saloon/bars accommodation) and rates of adolescent drinking and smoking. Furthermore, the interplay between risky neighborhood environments and school adjustment pointed to a possible protective effect of a high level of school adjustment in predicting smoking and drinking among adolescents. Conclusion: Findings highlighted the importance of considering multiple neighborhood social contexts surrounding adolescents to understand their risky behavior. Furthermore, positive intervention strategies that focus on adolescents' positive development within the school domain may act to protect adolescents from harmful neighborhood environments.

• Proceedings of the IEEK Conference
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• 2000.11b
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• pp.59-62
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• 2000

As the density of memories increases, unwanted interference between cells and coupling noise between bit-lines are increased and testing high density memories for a high degree of fault coverage can require either a relatively large number of test vectors or a significant amount of additional test circuitry. From now on, conventional test algorithms have focused on faults between neighborhood cells, not neighborhood bit-lines. In this paper, a new algorithm for NPSFs, and neighborhood bit-line sensitive faults (NBLSFs) based on the NPSFs are proposed. Instead of the conventional five-cell and nine-cell physical neighborhood layouts to test memory cells, a three-cell layout which is minimum size for NBLSFs detection is used. To consider faults by maximum coupling noise by neighborhood bit-lines, we added refresh operation after write operation in the test procedure(i.e., write \longrightarrow refresh \longrightarrow read). Also, we present properties of the algorithm, such as its capability to detect stuck-at faults, transition faults, conventional pattern sensitive faults, and neighborhood bit-line sensitive faults.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.959-974
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• 2020

High efficiency video coding (HEVC) employs quadtree coding tree unit (CTU) structure to improve its coding efficiency, but at the same time, it also requires a very high computational complexity due to its exhaustive search processes for an optimal coding unit (CU) partition. With the aim of solving the problem, a fast CU size decision optimal algorithm based on neighborhood prediction is presented for HEVC in this paper. The contribution of this paper lies in the fact that we successfully use the partition information of neighborhood CUs in different depth to quickly determine the optimal partition mode for the current CU by neighborhood prediction technology, which can save much computational complexity for HEVC with negligible RD-rate (rate-distortion rate) performance loss. Specifically, in our scheme, we use the partition information of left, up, and left-up CUs to quickly predict the optimal partition mode for the current CU by neighborhood prediction technology, as a result, our proposed algorithm can effectively solve the problem above by reducing many unnecessary prediction and partition operations for HEVC. The simulation results show that our proposed fast CU size decision algorithm based on neighborhood prediction in this paper can reduce about 19.0% coding time, and only increase 0.102% BD-rate (Bjontegaard delta rate) compared with the standard reference software of HM16.1, thus improving the coding performance of HEVC.