• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.103-109
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• 2010

Total performance is improved by minimizing the channel interference between links in wireless mesh networks (WMNs). The paper refines on the CB-CA [1] to be suitable for multi-radio multi-channel (MRMC) WMNs. The CB-CA is the cluster-based channel assignment algorithm for one radio three channel WMN based on IEEE 802.11b/g. The CB-CA does not perform the channel scanning and the channel switching between the cluster heads (CHs) and the edge gateway nodes (EGs). However, the use of co-channel for links between CHs and EGs brings the problem of channel interference among many nodes. We propose and evaluate an improved CB-CA algorithm to solve this problem in MRMC WMNs. The proposed algorithm discriminates between transmission channel and receive channel and assigns channels to each interface randomly and advertises this information to neighbor clusters in order to be assigned no-interference channel between clusters. Therefore, the proposed algorithm can minimize the interference between clusters and also improve QoS, since it can use multiple interfaces and multiple channels.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.583-586
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• 1999

In this paper, the wavelet transform is performed in the input 256$\times$256 color image and decomposes a image into low-pass and high-pass components. Since the high-pass band contains the components of three directions, edges are detected by combining three parts. After finding the position of face using the histogram of the edge component, a face region in low-pass band is cut off. Since RGB color image is sensitively affected by luminances, the image of low pass component is normalized, and a facial region is detected using face color informations. As the wavelet transform decomposes the detected face region into three layer, the dimension of input image is reduced. In this paper, we use the 3000 images of 10 persons, and KL transform is applied in order to classify face vectors effectively. FCM(Fuzzy C-Means) algorithm classifies face vectors with similar features into the same cluster. In this case, the number of cluster is equal to that of person, and the mean vector of each cluster is used as a codebook. We verify the system performance of the proposed algorithm by the experiments. The recognition rates of learning images and testing image is computed using correlation coefficient and Euclidean distance.

• Bulletin of the Korean Chemical Society
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• v.25 no.5
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• pp.673-675
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• 2004

The tetranuclear copper(II) cluster compound $[Cu_4OCl_6(C_{14}H_{12}N_2)_4]$ has been synthesized by hydrothermal reaction and studied by X-ray diffraction. The four copper(II) atoms locate four capsheaves of a tetrahedral skeletal structure and a oxygen atom as interstitial atom occupies the center position of the same tetrahedron, and each edge of the Cu-Cu tetrahedron is bridged by one ${\mu}_2$-Cl anion. The copper atom possesses slightly distorted trigonal bipyramidal geometry with three ${\mu}_2$-Cl atoms in equatorial position and the interstitial O atom and one N atom from 3-benzyl-benzimidazole ligand occupying axial position. The Cu-Cu distances are in the range of 3.0986-3.1162 ${\AA}$. The EPR spectrum suggested that the copper(II) ground state $d_{x2-y2}$ and the coordination geometry was trigonal bipyramidal.

• Bulletin of the Korean Chemical Society
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• v.22 no.2
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• pp.154-158
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• 2001

The steps for the generation of very thin GaN films on ultrathin AlN/6H-SiC surface by alternating a pulsative supply (APS) of trimethyl gallium and NH3 gases have been examined by ASED-MO calculations. We postulate that the gallium cul ster was formed with the evaporation of CH4 gases via the decomposition of trimethyl gallium (TMG), dimethyl gallium (DMG), and monomethyl galluim (MMG). During the injection of NH3 gas into the reactor, the atomic hydrogens were produced from the thermal decomposition of NH3 molecule. These hydrogen gases activated the Ga-C bond cleavage. An energetically stable GaN nucleation site was formed via nitrogen incorporation into the layer of gallium cluster. The nitrogen atoms produced from the thermal degradation of NH3 were expected to incorporate into the edge of the gallium cluster since the galliums bind weakly to each other (0.19 eV). The structure was stabilized by 2.08 eV, as an adsorbed N atom incorporated into a tetrahedral site of the Ga cluster. This suggests that the adhesion of the initial layer can be reinforced by the incorporation of nitrogen atom through the formation of large grain boundary GaN crystals at the early stage of GaN film growth.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.53-63
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• 2022

In the paper, we propose a TSCH-based scheduling scheme for IEEE 802.15.4e, which is able to perform the scheduling of its own network by avoiding collision from interference network cluster (INC). Firstly, we model a bipartite graph structure for presenting the slot-frame (channel-slot assignment) of TSCH. Then, based on the bipartite graph edge weight, we utilize the Hungarian assignment algorithm to implement a scheduling scheme. We have employed two features (maximization and minimization) of the Hungarian-based assignment algorithm, which can perform the assignment in terms of minimizing the throughput of INC and maximizing the throughput of own network. Further, in this work, we called the scheme "dual-stage Hungarian-based assignment algorithm". Furthermore, we also propose deep learning (DL) based deep neural network (DNN)scheme, where the data were generated by the dual-stage Hungarian-based assignment algorithm. The performance of the DNN scheme is evaluated by simulations. The simulation results prove that the proposed DNN scheme providessimilar performance to the dual-stage Hungarian-based assignment algorithm while providing a low execution time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1700-1721
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• 2017

The problem of blocking artifacts is very common in block-based image and video compression, especially at very low bit rates. In this paper, we propose a post-processing method for JPEG-coded image deblocking via sparse representation and adaptive residual threshold. This method includes three steps. First, we obtain the dictionary by online dictionary learning and the compressed images. The dictionary is then modified by the histogram of oriented gradient (HOG) feature descriptor and K-means cluster. Second, an adaptive residual threshold for orthogonal matching pursuit (OMP) is proposed and used for sparse coding by combining blind image blocking assessment. At last, to take advantage of human visual system (HVS), the edge regions of the obtained deblocked image can be further modified by the edge regions of the compressed image. The experimental results show that our proposed method can keep the image more texture and edge information while reducing the image blocking artifacts.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.265-280
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• 2001

Estimation of the edge of a distribution has many important applications. It is related to classification, cluster analysis, neural network, and statistical image recovering. The problem also arises in measuring production efficiency in economic systems. Three most promising nonparametric estimators in the existing literature are introduced. Their statistical properties are provided, some of which are new. Themes of future study are also discussed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.317-318
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• 2022

본 논문에서는 클러스터 기반 엣지 모델에서 자원을 효율적으로 사용할 수 있는 지능형 엣지 자원 할당 정책 모델을 제안한다. 최근 쿠버네틱스 기반 클러스터 엣지 시스템 개발 연구 다양한 방향에서 진행 중이다. 따라서, 본 논문에서는 클러스터-엣지 모델 구조를 소개하고 이 모델에서 컴퓨팅 자원을 가진 워커에 컴퓨팅 오프로딩 서비스를 효율적으로 사용할 수 있는 최적의 지능형 클러스터-엣지 컴퓨팅 자원 정책을 생성하는 구조 및 알고리즘을 제안한다.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.189-194
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• 2012

In this paper, we propose a query expansion method based on word graphs using pseudo-relevant and pseudo non-relevant documents to achieve performance improvement in information retrieval. The initially retrieved documents are classified into a core cluster when a document includes core query terms extracted by query term combinations and the degree of query term proximity. Otherwise, documents are classified into a non-core cluster. The documents that belong to a core query cluster can be seen as pseudo-relevant documents, and the documents that belong to a non-core cluster can be seen as pseudo non-relevant documents. Each cluster is represented as a graph which has nodes and edges. Each node represents a term and each edge represents proximity between the term and a query term. The term weight is calculated by subtracting the term weight in the non-core cluster graph from the term weight in the core cluster graph. It means that a term with a high weight in a non-core cluster graph should not be considered as an expanded term. Expansion terms are selected according to the term weights. Experimental results on TREC WT10g test collection show that the proposed method achieves 9.4% improvement over the language model in mean average precision.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.49.2-49.2
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• 2015

Galaxy cluster is the most important laboratoriy to study the effect of environment on galaxies, one of key questions in astronomy. In the local universe, it is well known that red, passive galaxies are concentrated in the cluster core. However, it is still controversial whether the star formation-density relation at the low redshift is retained in the distant universe. Many surveys have tried to find galaxy clusters at various epochs. However the optical dataset has limitations in finding galaxy clusters at z > 1, since the bulk of stellar emission of z > 1 galaxies is redshifted into the near-IR regime. We used the multi-wavelength data from the UKIDSS DXS (J and K bands), the SWIRE (4 IRAC bands), and the PAN-STARRS (g, r, i, z, y bands) and IMS (J band; Im et al. 2015, in preparation) in the European Large Area ISO Survey North1 (ELAIS-N1) field to search for high redshift galaxy clusters and study the properties of member galaxies. Using the multi-wavelength data, we investigated overdensities of galaxies at 0.2 < z < 1.6 based on the photometric redshift information. We found several superclusters where cluster candidates are concentrated within scales of few tens of Mpc at z ~ 0.9. Interestingly, some of the supercluster candidates consist of galaxy clusters which are dominated by blue galaxies. We will present high redshift galaxy cluster and supercluster candidates in ELAIS-N1 field and galaxy properties in different environments including dense clusters and fields.