• Journal of the Korean Home Economics Association
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• v.48 no.1
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• pp.83-96
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• 2010

This study was conducted to derive useful predictive variations for the qualitative supply of homes to provide information to real estate venture businesses and other business owners in neighborhood amenities and significant basic information to housing suppliers and policy makers. For this purpose, a number of apartment dwellers in Seoul were surveyed to examine their housing satisfaction, difference in housing satisfaction according to variables, and any relevant correlations. In detail, 500 apartment dwellers in Seoul were surveyed from September 1, 2009 to September 20, 2009 to gather resources that were processed through SPSS 14.0 to find percentage of frequency, mean, standard deviations, t-test, ANOVA, and Duncan Multiple Ranger's Test. The following were the findings of this study: First, housing satisfaction of apartment dwellers in Seoul was above average with the highest satisfaction with neighborhood environment. Second, satisfaction with amenities was significantly affected by dweller-related variables. Gangnam dwellers were more satisfied with housing environment and community environment than Gangbuk dwellers. By age, people in 20s and 30s showed high satisfaction with housing environment. Satisfaction with community environment was high among 20s, 30s and 40s. Satisfaction with management conditions was high among 20s. Also, satisfaction was high when housing period was between 1 and 10 years. By size, dwellers in 40py or larger homes showed high satisfaction with housing environment and management conditions. Dwellers in 30py and 40py or larger homes were satisfied with community environment. By ownership, dwellers with ownership of their homes showed high satisfaction. Third, there was a significant difference in satisfaction with neighborhood and social environments according to dweller-related variables. By region, dwellers of Gangnam area showed high satisfaction with neighborhood environment. By age, people in 20s, 30s and 40s showed high satisfaction with neighborhood environment. Also, satisfaction with neighborhood environment was high when housing period was around 10 years. By size, dwellers in 30py and 40py or larger homes were satisfied with neighborhood and social environments. Fourth, there was a close correlation between satisfaction with housing environment and satisfaction with community environment, and between satisfaction with community environment and satisfaction with management conditions. Thus, most dwellers that were satisfied with one variable of housing environment showed high satisfaction with other variables.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.3
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• pp.99-114
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• 2024

Recently, the concept of neighborhood unit plan has been receiving attention due to expectations of balanced development and sustainable development through resolving regional gaps and reflecting regional characteristics. Accessibility to essential living facilities that can support daily life is considered an important factor in neighborhood unit plan. Therefore, this study analyzed accessibility from facilities based on the living facilities and access range set in the neighborhood unit plan, and analyzed spatial accessibility inequality in connection with the neighborhood unit plan and spatial clustering. As a result of analyzing accessibility in Busan Metropolitan City, various accessibility ranges were found depending on the facility. In addition, as a result of analyzing in connection with spatial clustering, regional inequality was found, such as hotspot areas in Gangdong, old downtown, Dongrae, and Haeundae, and coldspot areas in Gangseo and Gijang, and spatial inequality was found in which hotspots and coldspots exist simultaneously within the same neighborhood unit. Considering these spatial characteristics, detailed planning and policy establishment are necessary for facilities lacking in small-size neighborhood units, and the results of the analysis are expected to be meaningful in realizing the urban policy of balanced development that has been recently promoted.

• Management Science and Financial Engineering
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• v.15 no.1
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• pp.81-96
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• 2009

Data mining, specially clustering is one of exciting research areas for ant based algorithms. Ant clustering algorithm, however, has many difficulties for resolving practical situations in clustering. We propose a new grid-based ant colony algorithm for clustering of data. The previous ant based clustering algorithms usually tried to find the clusters during picking up or dropping down process of the items of ants using some stigmergy information. In our ant clustering algorithm we try to make the ants reflect neighborhood information within the storage nests. We use two ant classes, search ants and labor ants. In the initial step of the proposed algorithm, the search ants try to guide the characteristics of the storage nests. Then the labor ants try to classify the items using the guide in-formation that has set by the search ants and the stigmergy information that has set by other labor ants. In this procedure the clustering decision of ants is quickly guided and keeping out of from the stagnated process. We experimented and compared our algorithm with other known algorithms for the known and statistically-made data. From these experiments we prove that the suggested ant mining algorithm found the clusters quickly and effectively comparing with a known ant clustering algorithm.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.87-92
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• 2022

In this study, we aimed to illustrate that the thresholding method gives different results when tested on the original and the refined histograms. We use the global thresholding method, the well-known image segmentation method for separating objects and background from the image, and the refined histogram is created by the neighborhood distinction metric. If the original histogram of an image has some large bins which occupy the most density of whole intensity distribution, it is a problem for global methods such as segmentation and contrast enhancement. We refined the histogram to overcome the big bin problem in which sub-bins are created from big bins based on distinction metric. We suggest the refined histogram for preprocessing of thresholding in order to reduce the big bin problem. In the test, we use Otsu and median-based thresholding techniques and experimental results prove that their results on the refined histograms are more effective compared with the original ones.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.8 no.3
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• pp.105-112
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• 1983

This paper discribes technique of the recursive restoration for the images degraded by linear space invariant blur and additive white Gaussian noise. The image is characterized statistically by tis mean and correlation function. An exponential autocorrelation function has been used to model neighborhood model. The vector model was used because of analytical simplicitly and capability to implement brightness correlation function. Base on the vector model, a two-dimensional discrete stochastic a 12 point neighborhood model for represeting images was developme and used the technique of moving window processing to restore blurred and noisy images without dimensionality increesing, It has been shown a 12 point neighborhood model was found to be more adequate than a 8 point pixel model to obtain optimum pixel estimated. If the image is highly correlated, it is necessary to use a large number of points in the neighborhood in order to have improvements in restoring image. It is believed that these result could be applied to a wide range of image processing problem. Because image processing thchniques normally required a 2-D linear filtering.

• Spatial Information Research
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• v.21 no.6
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• pp.81-89
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• 2013

Recently, several studies conducted for other countries show that housing price has very close relationship with personal or neighborhood level obesity. Also these studies suggest the use of housing price as a new SES(Socio-Economic Status) variable for health related studies. In this study, whether this relationship can be found in regions of the Seoul Metropolitan Area is investigated. The results of this study show that, as in the cases of other countries, the regions with SES represented by higher housing prices show lower obesity levels. Further, the results show that the differences in regional housing prices well explain the variations of regional obesity levels as other traditional SES variables do. This finding indicates that housing price which is objectively, continuously, and spatially measured in Korea can be used as a new SES indicator for health research in Korea.

• Journal of IKEEE
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• v.27 no.3
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• pp.251-257
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• 2023

In this paper, we propose a dual-structured self-attention method that improves the lack of regional features of the vision transformer's self-attention. Vision Transformers, which are more computationally efficient than convolutional neural networks in object classification, object segmentation, and video image recognition, lack the ability to extract regional features relatively. To solve this problem, many studies are conducted based on Windows or Shift Windows, but these methods weaken the advantages of self-attention-based transformers by increasing computational complexity using multiple levels of encoders. This paper proposes a dual-structure self-attention using self-attention and neighborhood network to improve locality inductive bias compared to the existing method. The neighborhood network for extracting local context information provides a much simpler computational complexity than the window structure. CIFAR-10 and CIFAR-100 were used to compare the performance of the proposed dual-structure self-attention transformer and the existing transformer, and the experiment showed improvements of 0.63% and 1.57% in Top-1 accuracy, respectively.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.27-35
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• 2009

Integer programming is a very effective technique for searching optimal solution of combinatorial optimization problems. However, its applicability is limited to linear models. In this paper, I propose an effective method for solving a nonlinear optimization problem by integrating the powerful search performance of integer programming and the flexibility of neighborhood search algorithms. In the first phase, integer programming is executed with subproblem which can be represented as a linear form from the given problem. In the second phase, a neighborhood search algorithm is executed with the whole problem by taking the result of the first phase as the initial solution. Through the experimental results using a nonlinear maximal covering problem, I confirmed that such a simple integration method can produce far better solutions than a neighborhood search algorithm alone. It is estimated that the success is primarily due to the powerful performance of integer programming.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.21-26
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• 2016

This study examined the effects of the online community, such as chatting, book-cafe on the neighborhood relationship. Through a case study of 'The Sharp' apartment area, the characters of neighborhood relationship between user and non-user were compared. The factors affecting the community relationships were analyzed by regression analysis. According to the results, the residents using the online community shared their emotions, thoughts and information with their neighbors so that the level of neighborhood relationship was higher. To reprove the neighborhood relationship being cut off the online community should be handled as an important factor in the planning of apartments. This study as a basic research is expected to contribute to policing against crimes and accidents in apartments.

• Land and Housing Review
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• v.13 no.2
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• pp.81-90
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• 2022

This study is based on social needs for green healing spaces assumed to enhance mental health in a city. This study proposes development directions through the analysis of modern social recognition factors for neighborhood gardens. As a research method, web information data was collected using Textom among big data tools. Text Mining was conducted to extract elements and analyze their relationship through keyword analysis, network analysis, and cluster analysis. As a result, first, the healing space and the healing environment were creating an eco-friendly healthy environment in a space close to the neighborhood within the city. Second, neighborhood gardens included projects and activities that involved government, local administration, and citizens by linking facilities as well as living culture and urban environments. These gardens have been reinforced through green welfare and service programs. In conclusion, friendly gardens in the neighborhood for the purpose of public interest, which are beneficial to mental health, are green infrastructures as a healing environment that can produce positive effects.