• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.105-112
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• 2012

Face detection at a distance faces is very challenging since images are often degraded by blurring and noise as well as low resolution. This paper proposes an improved face detection method with AdaBoost filtering and sequential testing stages with color and shape information. The conventional AdaBoost filter detects face regions but often generates false alarms. The face detection method is improved by adopting sequential testing stages in order to remove false alarms. The testing stages comprise skin-color test and variable edge-mask filtering. The skin-color filtering is composed of two steps, which involve rectangular window regions and individual pixels to generate binary face clusters. The size of the variable edge-mask is determined by the ellipse which is estimated from the face cluster. The validation of the horizontal and vertical ratio of the mask is also investigated. In the experiments, the efficacy of the proposed algorithm is proved by images captured by a CCTV and a smart-phone

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.70.2-70.2
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• 2014

Galaxy clusters, the largest gravitationally bound systems, are an important means to place constraints on cosmological models. Moreover, they are excellent places to test galaxy evolution models in connection to the environments. To this day, massive clusters have been found unexpectedly(Kang & Im 2009, Durret et al. 2011, Tashikawa et al. 2012) and evolution of galaxies in cluster have been still controversial (Elbaz et al. 2007, Cooper et al. 2008, Tran et al. 2009). Finding galaxy cluster candidates in a wide, deep imaging survey data will enable us to solve the such issues of modern extragalactic astronomy. We have used multi-wavelength data from the UKIRT Infrared Deep Sky Survey Deep Extragalactic Survey (UKIDSS DXS/J and K bands), Spitzer Wise-area InfraRed Extragalactic survey (SWIRE/two mid-infrared bands), the Panoramic Survey Telescope and Rapid Response System (PAN-STARRS/ g, r, i, z, y bands) and Infrared Medium-deep Survey(IMS/J band). We report new candidates of galaxy clusters and properties of their member galaxies in one of the wide and deep survey fields ELAIS-N1, European Large Area ISO Survey North1, covering sky area of $8.75deg^2$.

• The Korean Journal of Ceramics
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• v.3 no.1
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• pp.5-12
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• 1997

Charged carbon clusters which are formed by the gas activation are suggested to be responsible for the formation of the metastable diamond film. The number of carbon atoms in the cluster that can reverse the stability between diamond and graphite by the capillary effect increases sensitively with increasing the surface energy ratio of graphite to diamond. The gas activation process produces charges such as electrons and ions, which are energetically the strong heterogeneous nucleation sites for the supersaturated carbon vapor, leading to the formation of the charged clusters. Once the carbon clusters are charged, the surface energy of diamond can be reduced by the electrical double layer while that of graphite cannot because diamond is dielectric and graphite is conducting. The unusual phenomena observed in the chemical vapor deposition diamond process can be successfully approached by the charged cluster model. These phenomena include the diamond deposition with the simultaneous graphite etching, which is known as the thermodynamic paradox and the preferential formation of diamond on the convex edge, which is against the well-established concept of the heterogeneous nucleation.

• Bulletin of the Korean Chemical Society
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• v.6 no.2
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• pp.68-73
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• 1985

Normal modes of solids HF, HCl and polyethylene having the exciting spectrometric phenomena have been evaluated by taking the lowest temperature phase of these species in the solid. The solids HF and HCl have the same space group as C$_{2}{\nu}$, and polyethylene has a space group with D$_{2h}$. The normal modes were obtained by the valence force field with modified force constants and a quantitative description of the normal mode is adjusted by the potential energy distribution (PED). From the PED, the most fittable force constants are also obtained. We have intended to calculate the normal modes by using the smallest size of the model and the simple computational process. To remove the edge effects being occurred in constructing the single cluster model, different from the boundary condition being generally used up to now, the idea of pseudolattice method being successfully applied to MO calculations of solid was extended to normal mode analysis in order to give the same environment for all moecules in a chosen cluster. By using the above valence force field and boundary condition, we obtain the assigned frequencies and compare those results with the results obtained by others.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.419-421
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.238-240
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Journal of Korean Society of Rural Planning
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• v.15 no.2
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• pp.19-26
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• 2009

The purpose of this study is to build Island biogeography in the basic concept of landscape ecology in South Korea by draw relationship between the species side of quantitative habitats and forest area surveyed in the national database based on investigation of the 2nd natural environment. In addition, try to present criterion of habitats character category after understanding habitats character of emergence area side of quality habitats based on the type of formatting. Species and forest area relationship analyzed using correlation analysis and simple regression analysis. Also habitat character limited composition ratio of neighboring land cover and analyzed using hierarchical cluster analysis to classify type of habitat. As a result, we found that forest area is correlated with number of species, forests which is bigger than 100ha are more important of increase in species' population. And according to land cover composition ratio, bird's classified types of forest inner species, forest edge species, forest outer species and mammal's classified types of forest inner species, forest general species, forest edge species. We suggest that study of species-forest area relationship and emergence habitat character be used as some management plans of species' conservation, protection and restoration.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.224-230
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• 2013

Lane boundary detection plays a key role in the driver assistance system. This study proposes a robust method for detecting lane boundary in severe environment. First, a horizontal line detects form the original image using improved Vertical Mean Distribution Method (iVMD) and the sub-region image which is under the horizontal line, is determined. Second, we extract the lane marking from the sub-region image using Canny edge detector. Finally, K-means clustering algorithm classifi left and right lane cluster under variant illumination, cracked road, complex lane marking and passing traffic. Experimental results show that the proposed method satisfie the real-time and efficient requirement of the intelligent transportation system.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.569-575
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• 2022

This is a research thesis on the development of a monitoring and diagnosis device that prevents the risk of an accident through monitoring and diagnosis of a modular Main Circuit Breaker (MCB) using Vacuum Interrupter (VI) for Korean high-speed rolling stock. In this paper, a comprehensive MCB monitoring and diagnosis was performed by converging vacuum level diagnosis of interrupter, operating coil monitoring of MCB and environmental temperature/humidity monitoring of modular box. In addition, to develop an algorithm that is expected to have a similar data processing before the actual field test of the MCB monitoring and diagnosis device in 2023, the cluster analysis and factor analysis were performed using the WEKA data mining technique on the big data of Korean railroad transformer, which was previously researched by Tae Hee Evolution with KORAIL.

• Korean Journal of Environmental Agriculture
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• v.28 no.4
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• pp.365-370
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• 2009

The aim of this study was to investigate the vegetation types of Minarimot, in Jeju Islands. The vegetation types were classified by the Z-M school method and cluster analysis. The vegetation in Minarimot was classified into 6 communities and 2 subcommunities: Persicaria thunbergii-Isachne globosa community (vegetation type: A), Scirpus tribangulatus-Eleocharis manillata var. cyclocarpa community (B) (Aneilema keisak subcommunity (B-1) and Caldesia parnassifolia-Potamogeton distinctus subcommunity (B-2)), Eleocharis kuroguwai community (C), Phragmites communis community (D), Scirpus tabernaemontani community(E) and Typha orientalis community (F). These communities were grouped into three main categories according to cluster analysis. The community (A) established at the edge of the wetland which has the driest condition was distinguished as Group I, while the community (B) emerged in the submerged zone was distinguished as Group III. The Group II was designated as the communities (C, D, E, F) between Group I and III, whose communities were occasionally submerged. The result of principal coordinate analysis (PCoA) appeared that the different vegetation established along the wetland were depending on water environment such as water depth and the period submerged.