• International Journal of High-Rise Buildings
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• v.8 no.2
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• pp.125-136
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• 2019

This paper offers new ways to learn about popular places in the city. Using locational data from Social Media platforms platforms, including Twitter, Facebook, and Instagram, along with participatory field visits and combining insights from architecture and urban design literature, this study reveals popular socio-spatial clusters in the City of Chicago. Locational data of photographs were visualized by using Geographic Information Systems and helped in producing heat maps that showed the spatial distribution of posted photographs. Geo-intensity of photographs illustrated areas that are most popularly visited in the city. The study's results indicate that the city's skyscrapers along open spaces are major elements of image formation. Findings also elucidate that Social Media plays an important role in promoting places; and thereby, sustaining a greater interest and stream of visitors. Consequently, planners should tap into public's digital engagement in city places to improve tourism and economy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2737-2753
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• 2013

In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.4
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• pp.206-216
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• 2010

Wireless sensor networks (WSNs) are used to collect various data in environment monitoring applications. A spatial clustering may reduce energy consumption of data collection by partitioning the WSN into a set of spatial clusters with similar sensing data. For each cluster, only a few sensor nodes (samplers) report their sensing data to a base station (BS). The BS may predict the missed data of non-samplers using the spatial correlations between sensor nodes. ASAP is a representative data collection algorithm using the spatial clustering. It periodically reconstructs the entire network into new clusters to accommodate to the change of spatial correlations, which results in high message overhead. In this paper, we propose a new data collection algorithm, name EPDC (Energy-efficient Periodic Data Collection). Unlike ASAP, EPDC identifies a specific cluster consisting of many dissimilar sensor nodes. Then it reconstructs only the cluster into subclusters each of which includes strongly correlated sensor nodes. EPDC also tries to reduce the message overhead by incorporating a judicious probabilistic model transfer method. We evaluate the performance of EPDC and ASAP using a simulation model. The experiment results show that the performance improvement of EPDC is up to 84% compared to ASAP.

• International Journal of High-Rise Buildings
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• v.6 no.2
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• pp.149-163
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• 2017

With the intensification of urban development in Chinese cities, mixed land use in urban centers extends vertically into 3-D and expands its scale from a single building to commercial clusters. The multi-level pedestrian system in city centers also changed its role from one of traffic isolation to spatial integration, where transit nodes, street sidewalks, squares, building entrances, atriums, and corridors are interconnected, both horizontally and vertically, into a whole spatial system, within which pedestrian flows are guided and shopping facilities are arranged. This paper uses spatial configuration analysis of space syntax to examine the impacts of spatial patterns on movement distribution and the business performance of tenant mix in the multi-level commercial system of the Nanshan Commercial Cultural District in Shenzhen, China. The key objective is to better understand the interactions between the socio-economic variables and spatial design parameters of a shopping complex. The research findings point to the importance of multiplicity between syntactic variables and other spatial variables in influencing the pedestrian flows, business performance and tenant mix in highly complex commercial systems. Particularly noteworthy is the relationship between spatial accessibility measures and the location of escalators, and the ways in which individual commercial buildings are embedded into the overall spatial system. The study suggests that this may lead to the preliminary identification of the spatial qualities of effective vertical extensions of mixed land use in a high-density urban settings.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.45.1-45.1
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• 2015

Galaxy clusters have provided important information to understand the evolution of the universe, since the number density and mass of clusters are tightly related to the cosmological parameters. In addition, galaxy clusters are an excellent laboratory to investigate the galaxy evolution in dense environments. However, finding galaxy clusters at high redshift ($z{\geq}1$) still remains as a main subject in astronomy due to their rareness and difficulty in identifying such objects from optical imaging data alone. Here, we report a spectroscopic follow-up observation of distant galaxy cluster candidates identified by a deep optical-NIR dataset of Infrared Medium-deep Survey. Through the galaxy spectra taken with the IMACS instrument on the Magellan telescope, we confirm at least 3 massive clusters at z~0.92. Interestingly, the maximum spatial separation between these clusters is ~8Mpc, which implies that this system is a new supercluster in the distant universe. We also discuss properties of galaxies in these clusters based on multi-wavelength photometric data.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.59.2-59.2
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• 2018

Recent studies of galaxy clusters have shown that the galaxy clusters in dense environment tend to have lower star formation rate in local universe with z < 1. However, this correlation is not significant in galaxy clusters with z > 1. The study of galaxy clusters around z=1 can yield insight into cosmological galaxy evolution. Nevertheless, the identification of galaxy clusters beyond the scope of immediate local universe requires wide field data in optical and near-infrared bands. By incorporating data from Canada-France-Hawaii Telescope Legacy Survey(CFHTLS) and Infrared Medium-Deep Survey(IMS), the photometric redshifts of galaxies in CFHTLS W2 field were calculated. Using spatial distribution and photometric redshifts, the galaxies in the field were divided into redshift bins. The image of each redshift bin was analyzed by measuring the number density within proper distance of 1Mpc. By comparing high density regions in consecutive redshift bins, we identified the cluster candidates and mapped the large-scale structure within the CFHTLS W2 field.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.40.1-40.1
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• 2019

We report progress on identifying cosmic voids using cluster halos as the antipode. According to the standard scenario of structure formation, clusters are expected to form at peaks of the initial density field, whereas cosmic voids form at troughs. Then, a cluster would be a void if the sign of the initial density fluctuation of the universe were inverted. To study the relevance of anti-structures of clusters to cosmic voids, we use a pair of simulations whose initial density fields are sign inverted versions to each other. By examining the spatial distribution and environment of the particles in inverted simulation, which are the member particles of clusters in the other simulation, we discuss the characteristics of the antipode structures of clusters including their size, density, internal structure, and redshift evolution as well.

• Journal of the Korean Institute of Educational Facilities
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• v.24 no.4
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• pp.15-24
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• 2017

This paper aims to investigate in what extent subject-centered clusters are different from one another in terms of message system, which is composed of curriculum, pedagogy and evaluation. For this, Bernstein's pedagogic transmission code(i.e., classification and framing) and school typology(i.e., open-type or close-type) have been explored, and then applied into Shimin Junior School, Japan, in order to find out substantial characteristics between subject-centered clusters. In this case study, VGA(visibility graph analysis), as one of syntactical methodologies in space syntax theory, has been used to measure to what degree they are actually different. Throughout in-depth investigation of spatial configurations, it can be said that the square of clusters is strongly connected and integrated very well, so that it acts as an anchor place for school life within a cluster. However, it works in different ways according to message systems. In the subjects like Japanese and Science whose message system are characterized by strong classification and strong framing, integration values are relatively low, and this means that it is hard to expect cross-referencing activities through the subject squares. On the contrary, the subject of Social Studies defined by weak classification and weak framing shows the highest mean integration values, and this can be expected that there are inter-changeable learning activities in the square.

• Anatomy and Cell Biology
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• v.56 no.3
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• pp.382-393
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• 2023

Cell clusters are a histological hallmark feature of intervertebral disc degeneration. Clusters arise from cell proliferation, are associated with replicative senescence, and remain metabolically, but their precise role in various stages of disc degeneration remain obscure. The aim of this study was therefore to investigate small, medium, and large size cell-clusters. For this purpose, human disc samples were collected from 55 subjects, aged 37-72 years, 21 patients had disc herniation, 10 had degenerated non-herniated discs, and 9 had degenerative scoliosis with spinal curvature <45°. 15 non-degenerated control discs were from cadavers. Clusters and matrix changes were investigated with histology, immunohistochemistry, and Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Data obtained were analyzed with spearman rank correlation and ANOVA. Results revealed, small and medium-sized clusters were positive for cell proliferation markers Ki-67 and proliferating cell nuclear antigen (PCNA) in control and slightly degenerated human discs, while large cell clusters were typically more abundant in severely degenerated and herniated discs. Large clusters associated with matrix fissures, proteoglycan loss, matrix metalloproteinase-1 (MMP-1), and Caspase-3. Spatial association findings were reconfirmed with SDS-PAGE that showed presence to these target markers based on its molecular weight. Controls, slightly degenerated discs showed smaller clusters, less proteoglycan loss, MMP-1, and Caspase-3. In conclusion, cell clusters in the early stages of degeneration could be indicative of repair, however sustained loading increases large cell clusters especially around microscopic fissures that accelerates inflammatory catabolism and alters cellular metabolism, thus attempted repair process initiated by cell clusters fails and is aborted at least in part via apoptosis.

• Journal of the Korean association of regional geographers
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• v.16 no.5
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• pp.590-609
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• 2010

The purpose of the study is to propose and evaluate Exploratory Spatial Data Analysis(ESDA) methods for examining age-specific population migration characteristics. First, population migration pyramid which is a pyramid-shaped graph designed with in-migration, out-migration, and net migration by age (or age group), was developed as a tool exploring age-specific migration propensities and structures. Second, various spatial statistics techniques based on local indicators of spatial association(LISA) such as Local Moran''s $I_i$, Getis-Ord ${G_i}^*$, and AMOEBA were suggested as ways to detect spatial dusters of age-specific net migration rate. These ESDA techniques were applied to age-specific population migration of Daegu Metropolitan City. Application results demonstrated that suggested ESDA methods can effectively detect new information and patterns such as contribution of age-specific migration propensities to population changes in a given region, relationship among different age groups, hot and cold spot of age-specific net migration rate, and similarity between age-specific spatial clusters.