• Journal of Communications and Networks
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• v.12 no.5
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• pp.433-441
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• 2010

Multihop transmission is a promising technique that helps in achieving broader coverage (excellent network connectivity) and preventing the impairment of wireless channels. This paper proposes a cluster-based multihop wireless network that makes use of the advantages of multihop relaying, i.e., path loss gain, and partial relay selection in each hop, i.e., spatial diversity. In this partial relay selection, the node with the maximum instantaneous channel gain will serve as the sender for the next hop. With the proposed protocol, the transmit power and spectral efficiency can be improved over those in the case of direct transmission and conventional multihop transmission. Moreover, at a high signal-to-noise ratio (SNR), the performance of the system with at least two nodes in each cluster is dependent only on the last hop and not on any of the intermediate hops. For a practically feasible decode-and-forward relay strategy, a compact expression for the probability density function of the end-to-end SNR at the destination is derived. This expression is then used to derive closed-form expressions for the outage probability, average symbol error rate, and average bit error rate for M-ary square quadrature amplitude modulation as well as to determine the spectral efficiency of the system. In addition, the probability of SNR gain over direct transmission is investigated for different environments. The mathematical analysis is verified by various simulation results for demonstrating the accuracy of the theoretical approach.

• Journal of The Korean Astronomical Society
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• v.37 no.5
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• pp.349-353
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• 2004

Magnetic fields are an important ingredient of galaxy clusters and are indirectly observed on cluster scales as radio haloes and radio relics. One promising method to shed light on the properties of cluster wide magnetic fields is the analysis of Faraday rotation maps of extended extragalactic radio sources. We developed a Fourier analysis for such Faraday rotation maps in order to determine the magnetic power spectra of cluster fields. In an advanced step, here we apply a Bayesian maximum likelihood method to the RM map of the north lobe of Hydra A on the basis of our Fourier analysis and derive the power spectrum of the cluster magnetic field. For Hydra A, we measure a spectral index of -5/3 over at least one order of magnitude implying Kolmogorov type turbulence. We find a dominant scale of about 3 kpc on which the magnetic power is concentrated, since the magnetic autocorrelation length is ${\lambda}_B = 3 {\pm} 0.5\;kpc$. Furthermore, we investigate the influences of the assumption about the sampling volume (described by a window function) on the magnetic power spectrum. The central magnetic field strength was determined to be ${\~}7{\pm}2{\mu}G$ for the most likely geometries.

• Journal of the Korean Magnetic Resonance Society
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• v.28 no.2
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• pp.6-9
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• 2024

HscA is a Hsp70-type chaperone protein that plays an essential role to mediate the iron-sulfur (Fe-S) cluster biogenesis mechanism in Escherichia coli. Like other Hsp70 chaperones, HscA is composed of two domains: the nucleotide binding domain (NBD), which can hydrolyze ATP and use its chemical energy to facilitate the Fe-S cluster transfer process, and the substrate binding domain (SBD), which directly interacts with the substrate, IscU, the scaffold protein of an Fe-S cluster. In the present work, we prepared the isolated SBD construct of HscA (HscA(SBD)) and conducted the solution-state nuclear magnetic resonance (NMR) experiments to have its backbone chemical shift assignment information. Due to low spectral quality of HscA(SBD), we obtained all the NMR data from the sample containing the peptide LPPVKIHC, the HscA-interaction motif of IscU, from which the chemical shift assignment could be done successfully. We expect that this information provides an important basis to execute detailed structural characterization of HscA and appreciate its interaction with IscU.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1409-1411
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• 2003

The application of simulated KOMPSAT-2 imagery to monitor graveyards is to be developed. Positions calculated from image were compared with those obtained from Geographic Positioning System. With 24 checkpoints, the position of graveyards showed within 5-meter range. Unsupervised classification, supervised classification, and objected-orientation classification algorithms were used to extract the graveyard. Unsupervised classification with masking processes based on National topographic data gives the best result. The graveyards were categorized with four types in field studies while the two types of graveyards were shown in descriptive statistics. Cluster Analysis and discriminant analysis showed the consistency with two types of tombs. It was hard to get a specific spectral signature of graveyards, as they are covered with grasses at different levels and shaded from the surrounding trees. The slopes and aspects of location of graveyards did not make any difference in the spectral signatures. This study gives the basic spectral characteristics for further development of objected-oriented classification algorithms and plausibility of KOMPSAT-2 images for management of mountainous areas in the aspect of position accuracy and classification accuracy.

• Wind and Structures
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• v.39 no.1
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• pp.1-14
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• 2024

Widespread damages from extreme winds have attracted lots of attentions of the resilience assessment of power distribution systems. With many related environmental parameters as well as numerous power infrastructure components, such as poles and wires, the increased challenge of power asset management before, during and after extreme events have to be addressed to prevent possible cascading failures in the power distribution system. Many extreme winds from weather events, such as hurricanes, generate widespread damages in multiple areas such as the economy, social security, and infrastructure management. The livelihoods of residents in the impaired areas are devastated largely due to the paucity of vital utilities, such as electricity. To address the challenge of power grid asset management, power system clustering is needed to partition a complex power system into several stable clusters to prevent the cascading failure from happening. Traditionally, system clustering uses the Binary Decision Diagram (BDD) to derive the clustering result, which is time-consuming and inefficient. Meanwhile, the previous studies considering the weather hazards did not include any detailed weather-related meteorologic parameters which is not appropriate as the heterogeneity of the parameters could largely affect the system performance. Therefore, a fragility-based network hierarchical spectral clustering method is proposed. In the present paper, the fragility curve and surfaces for a power distribution subsystem are obtained first. The fragility of the subsystem under typical failure mechanisms is calculated as a function of wind speed and pole characteristic dimension (diameter or span length). Secondly, the proposed fragility-based hierarchical spectral clustering method (F-HSC) integrates the physics-based fragility analysis into Hierarchical Spectral Clustering (HSC) technique from graph theory to achieve the clustering result for the power distribution system under extreme weather events. From the results of vulnerability analysis, it could be seen that the system performance after clustering is better than before clustering. With the F-HSC method, the impact of the extreme weather events could be considered with topology to cluster different power distribution systems to prevent the system from experiencing power blackouts.

• Journal of The Korean Astronomical Society
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• v.37 no.5
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• pp.583-587
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• 2004

With the aim to investigate the statistical properties and the connection between thermal and non-thermal properties of the ICM in galaxy clusters, we have developed a statistical magneto-turbulent model which describes, at the same time, the evolution of the thermal and non-thermal emission from galaxy clusters. In particular, starting from the cosmological evolution of clusters, we follow cluster. mergers, calculate the spectrum of the magnetosonic waves generated in the ICM during these mergers, the evolution of relativistic electrons and the resulting synchrotron and Inverse Compton spectra. We show that the broad band (radio and hard x-ray) non-thermal spectral properties of galaxy clusters can be well accounted for by our model for viable values of the parameters (here we adopt a EdS cosmology).

• Bulletin of the Korean Chemical Society
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• v.19 no.9
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• pp.923-926
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• 1998

Spectral diffusion following direct triplet excitation from the ground state in glassy Methylbenzophenone as a function of transition energy has been studied. The concentrations of donor and acceptor have been determined for different transition energies. The geometrical distribution was determined by a computer simulation. The cluster size increases gradually with concentration and cluster percolation is observed at 0.31 mole fraction for a three dimensional system. The average distance between a donor and an acceptor also has been determined for different concentrations. The energy transfer efficiency changes abruptly at a critical concentration of 0.054, corresponding to a critical distance of 9.8 Å. The γvalue was evaluated to be 1.17.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.47.1-47.1
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• 2013

We present structural parameters of galaxies in the Extended Viro Cluster Catalog (EVCC), new catalog of galaxies in the Viro cluster using homogeneous Sloan Digital Sky Survey (SDSS) Date Release 7 (DR7) data. The EVCC covers more extended region of the Viro cluster than of the Virgo Cluster Catalog (VCC) and presents updated morphologies of galaxies using multi-band images and spectral features. We obtain the surface brightness profiles of galaxies using ellipse task in IRAF. Based on the analysis of surface brightness profile we construct a catalog of various structural parameters of galaxies, i.e. central surface brightness, effective radius, sersic index, effective surface brightness, and mean effective surface brightness. Taking advantage of these structural parameters in various parameter spaces, we refine criteria of dividing giant elliptical and dwarf elliptical galaxies. In addition, we found that bulge dominated galaxies have larger sersic index and brighter central surface brightness than disk dominated galaxies. At fixed magnitude, dwarf elliptical galaxies dwarf lenticular galaxies, and dwarf irregular low surface brightness (LSB) galaxies show larger effective radii than giant elliptical galaxies, giant lenticular galaxies, and irregular high surface brightness (HSB) galaxies, respectively. Dwarf elliptical galaxies and dwarf irregular LSB galaxies occupy the similar structural parameter spaces. We suggest that giant elliptical galaxies and dwarf elliptical galaxies may have different origin.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.73-78
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• 2003

In this research, we implement Realtime Air Diffusion Prediction System which is a parallel Fortran model running on distributed-memory parallel computers. The system is designed for air diffusion simulations with four-dimensional data assimilation. For regional air quality forecasting a series of dynamic downscaling technique is adopted using the NCAR/Penn. State MM5 model which is an atmospheric model. The realtime initial data have been provided daily from the KMA (Korean Meteorological Administration) global spectral model output. It takes huge resources of computation to get 24 hour air quality forecast with this four step dynamic downscaling (27km, 9km, 3km, and lkm). Parallel implementation of the realtime system is imperative to achieve increased throughput since the realtime system have to be performed which correct timing behavior and the sequential code requires a large amount of CPU time for typical simulations. The parallel system uses MPI (Message Passing Interface), a standard library to support high-level routines for message passing. We validate the parallel model by comparing it with the sequential model. For realtime running, we implement a cluster computer which is a distributed-memory parallel computer that links high-performance PCs with high-speed interconnection networks. We use 32 2-CPU nodes and a Myrinet network for the cluster. Since cluster computers more cost effective than conventional distributed parallel computers, we can build a dedicated realtime computer. The system also includes web based Gill (Graphic User Interface) for convenient system management and performance monitoring so that end-users can restart the system easily when the system faults. Performance of the parallel model is analyzed by comparing its execution time with the sequential model, and by calculating communication overhead and load imbalance, which are common problems in parallel processing. Performance analysis is carried out on our cluster which has 32 2-CPU nodes.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.339-346
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• 2000

Medical image is analyzed to get an anatomical information for diagnostics. Segmentation must be preceded to recognize and determine the lesion more accurately. In this paper, we propose automatic segmentation algorithm for MR brain images using T1-weighted, T2-weighted and PD images complementarily. The proposed segmentation algorithm is first, extracts cerebrum images from 3 input images using cerebrum mask which is made from PD image. And next, find 3D clusters corresponded to cerebrum tissues using scale filtering and 3D clustering in 3D space which is consisted of T1, T2, and PD axis. Cerebrum images are segmented using FCM algorithm with its initial centroid as the 3D cluster's centroid. The proposed algorithm improved segmentation results using accurate cluster centroid as initial value of FCM algorithm and also can get better segmentation results using multi spectral analysis than single spectral analysis.