• Title/Summary/Keyword: Cluster Reduction

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A Location Registration Protocol for Distributed Call Processing Architecture in the ATM-based PCS (ATM기반의 PCS에서 분산 호 처리 구조를 위한 위치 등록 프로토콜)

  • Hong, Yong-Pyo;Park, Sun-Young;Lee, Jin
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.11
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    • pp.2812-2821
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    • 1997
  • In this paper, we presents performance analysis of a location registration protocol using cluster concept to minimize the number of location registrations caused by reduction of cell size and explosive increasement of wireless communication subscribers. We analyze the relationship between the size of cluster and the location registration rate, and finally we apply this analysis to the hexagonal cell structure for justification.

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Cooperative Content Caching and Distribution in Dense Networks

  • Kabir, Asif
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.11
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    • pp.5323-5343
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    • 2018
  • Mobile applications and social networks tend to enhance the need for high-quality content access. To address the rapid growing demand for data services in mobile networks, it is necessary to develop efficient content caching and distribution techniques, aiming at significantly reduction of redundant content transmission and thus improve content delivery efficiency. In this article, we develop optimal cooperative content cache and distribution policy, where a geographical cluster model is designed for content retrieval across the collaborative small cell base stations (SBSs) and replacement of cache framework. Furthermore, we divide the SBS storage space into two equal parts: the first is local, the other is global content cache. We propose an algorithm to minimize the content caching delay, transmission cost and backhaul bottleneck at the edge of networks. Simulation results indicates that the proposed neighbor SBSs cooperative caching scheme brings a substantial improvement regarding content availability and cache storage capacity at the edge of networks in comparison with the current conventional cache placement approaches.

An Energy Efficient Group-Based Cluster Key Management for Large Scale Sensor Networks (대규모 센서 네트워크에서 그룹을 기반으로 한 에너지 효율적인 클러스터키 관리 방안)

  • Kim, Jin-Su
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.11
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    • pp.5487-5495
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    • 2012
  • The important issue that applies security key are secure rekeying, processing time and cost reduction. Because of sensor node's limited energy, energy consumption for rekeying affects lifetime of network. Thus it is necessary a secure and efficient security key management method. In this paper, I propose an energy efficient group-based cluster key management (EEGCK) in the large scale sensor networks. EEGCK uses five security key for efficient key management and different polynomial degree using security fitness function of sector, cluster and group is applied for rekeying and security processing. Through both analysis and simulation, I also show that proposed EEGCK is better than previous security management method at point of network energy efficiency.

Cluster-based Image Retrieval Method Using RAGMD (RAGMD를 이용한 클러스터 기반의 영상 검색 기법)

  • Jung, Sung-Hwan;Lee, Woo-Sun
    • The KIPS Transactions:PartB
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    • v.9B no.1
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    • pp.113-118
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    • 2002
  • This paper presents a cluster-based image retrieval method. It retrieves images from a related cluster after classifying images into clusters using RAGMD, a clustering technique. When images are retrieved, first they are retrieved not from the whole image database one by one but from the similar cluster, a similar small image group with a query image. So it gives us retrieval-time reduction, keeping almost the same precision with the exhaustive retrieval. In the experiment using an image database consisting of about 2,400 real images, it shows that the proposed method is about 18 times faster than 7he exhaustive method with almost same precision and it can retrieve more similar images which belong to the same class with a query image.

A Unique Gene Expression Signature of 5-fluorouracil

  • Kim, Ja-Eun;Yoo, Chang-Hyuk;Park, Dong-Yoon;Lee, Han-Yong;Yoon, Jeong-Ho;Kim, Se-Nyun
    • Molecular & Cellular Toxicology
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    • v.1 no.4
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    • pp.248-255
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    • 2005
  • To understand the response of cancer cells to anticancer drugs at the gene expression level, we examined the gene expression changes in response to five anticancer drugs, 5-fluorouracil, cytarabine, cisplatin, paclitaxel, and cytochalasin D in NCI-H460 human lung cancer cells. Of the five drugs, 5-fluorouracil had the most distinctive gene expression signature. By clustering genes whose expression changed significantly, we identified three clusters with unique gene expression patterns. The first cluster reflected the up-regulation of gene expression by cisplatin, and included genes involved in cell death and DNA repair. The second cluster pointed to a general reduction of gene expression by most of the anticancer drugs tested. A number of genes in this cluster are involved in signal transduction that is important for communication between cells and reception of extracellular signals. The last cluster represented reduced gene expression in response to 5-fluorouracil, the genes involved being implicated in DNA metabolism, the cell cycle, and RNA processing. Since the gene expression signature of 5-fluorouracil was unique, we investigated it in more detail. Significance analysis of microarray data (SAM) identified 808 genes whose expression was significantly altered by 5-fluorouracil. Among the up-regulated genes, those affecting apoptosis were the most noteworthy. The down-regulated genes were mainly associated with transcription-and translation-related processes which are known targets of 5-fluorouracil. These results suggest that the gene expression signature of an anticancer drug is closely related to its physiological action and the response of caner cells.

Classification of Textural Descriptors for Establishing Texture Naming System(TNS) of Fabrics -Textural Descriptions of Women's Suits Fabrics for Fall/winter Seasons- (옷감의 질감 명명 체계 확립을 위한 질감 속성자 분류 -여성 슈트용 추동복지의 질감 속성을 중심으로-)

  • Han Eun-Gyeong;Kim Eun-Ae
    • Journal of the Korean Society of Clothing and Textiles
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    • v.30 no.5 s.153
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    • pp.699-710
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    • 2006
  • The objective of this study was to identify the texture-related components of woven fabrics and to develop a multidimensional perceptual structure map to represent the tactile textures. Eighty subjects in clothing and tektite industries were selected for multivariate data on each fabric of 30 using the questionnaire with 9 pointed semantic differential scales of 20 texture-related adjectives. Data were analyzed by factor analysis, hierarchical cluster analysis, and multidimensional scaling(MDS) using SPSS statistical package. The results showed that the five factors were selected and composed of density/warmth-coolness, stiffness, extensibility, drapeability, and surface/slipperiness. As a result of hierarchical cluster analysis, 30 fabrics were grouped by four clusters; each cluster was named with density/warmth-coolness, surface/slipperiness, stiffness, and extensibility, respectively. By MDS, three dimensions of tactile texture were obtained and a 3-dimensional perceptual structure map was suggested. The three dimensions were named as surface/slipperiness, extensibility, and stiffness. We proposed a positioning perceptual map of fabrics related to texture naming system(TNS). To classify the textural features of the woven fabrics, hierarchical cluster analysis containing all the data variations, even though it includes the errors, may be more desirable than texture-related multidimensional data analysis based on factor loading values in respect of the effective variables reduction without losing the critical variations.

Development and Application of Skin Age Prediction Model Based on Skin Measurement Data According to Age of 20's to 40's ages of Korean Women (한국 여성의 연령에 따른 피부 측정 데이터 기반 20대 ~ 40대 피부 나이 예측 모형 개발 및 적용)

  • Maeng, Jihye;Nam, Gaewon
    • Journal of the Society of Cosmetic Scientists of Korea
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    • v.48 no.1
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    • pp.25-32
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    • 2022
  • In this study, basic skin characteristics data were collected by measuring skin hydration, skin melanin, skin redness, and skin torsion elasticity from Korean women in from 20's to 40's ages, and then, age and correlation analysis were conducted. This was used to create a skin index, and cluster analysis was performed to classify the groups into 4 clusters, and the skin characteristics of each cluster were confirmed. Then, two prototypes were used for two weeks to confirm the improvement effect on skin moisture, skin redness, and skin dead mass reduction, and then analyzed which product was more effective in which cluster of subjects participated in the skin characteristics test. As a result of the study, the possibility of preparing for the customized cosmetics market was confirmed by applying the skin index and cluster analysis results to product efficacy evaluation.

Identification of Adaptive Traits Facilitating the Mechanized Harvesting of Adzuki Bean (Vigna angularis)

  • Xiaohan Wang;Yu-Mi Choi;Sukyeung Lee;Myoung-Jae Shin;Jung Yoon Yi;Kebede Taye Desta;Hyemyeong Yoon
    • Korean Journal of Plant Resources
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    • v.35 no.6
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    • pp.785-795
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    • 2022
  • Traditional germplasms are unsuitable for mechanized production, limiting adzuki bean production. The creation of cultivars that can be harvested by mechanized means is an urgent task for breeders. The bottom pod height (BPH), lodging resistance, and synchronous maturing of adzuki beans are critical factors for the reduction of losses due to mechanized harvesting. In this study, 14 traits of 806 adzuki bean accessions were analyzed. All growth stages and the yield, lodging score, and synchronous maturing correlated negatively with the BPH. These negative correlations reflect the increased difficulty of breeding to simultaneously satisfy the needs for no lodging, high synchronous maturing rates, BPHs > 10 cm, and high yield. We screened three germplasms with no lodging, high synchronous maturing rates, and BPHs > 10 cm that were used as mechanization-adapted breeding material for crossing with high-yield cultivars. Agronomic trait diversity in adzuki beans was also examined in this study. Principal component and cluster analyses were conducted for 806 germplasms resulting in three clusters with the yield and three growth stage traits serving as the main discriminating factors. Cluster 1 included high-yield germplasms with the number of pods per plant and the number of seeds per pod being the major discriminant factors. Cluster 2 included germplasms with long growth periods and large 100-seed weights while cluster 3 contained germplasms with high BPHs. In general, the characteristics that make mechanical harvesting feasible and those assessed in this study could be utilized to choose and enhance adzuki beans production.

The Design of Self-Organizing Map Using Pseudo Gaussian Function Network

  • Kim, Byung-Man;Cho, Hyung-Suck
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.42.6-42
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    • 2002
  • Kohonen's self organizing feature map (SOFM) converts arbitrary dimensional patterns into one or two dimensional arrays of nodes. Among the many competitive learning algorithms, SOFM proposed by Kohonen is considered to be powerful in the sense that it not only clusters the input pattern adaptively but also organize the output node topologically. SOFM is usually used for a preprocessor or cluster. It can perform dimensional reduction of input patterns and obtain a topology-preserving map that preserves neighborhood relations of the input patterns. The traditional SOFM algorithm[1] is a competitive learning neural network that maps inputs to discrete points that are called nodes on a lattice...

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Results of Discriminant Analysis with Respect to Cluster Analyses Under Dimensional Reduction

  • Chae, Seong-San
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.543-553
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    • 2002
  • Principal component analysis is applied to reduce p-dimensions into q-dimensions ( $q {\leq} p$). Any partition of a collection of data points with p and q variables generated by the application of six hierarchical clustering methods is re-classified by discriminant analysis. From the application of discriminant analysis through each hierarchical clustering method, correct classification ratios are obtained. The results illustrate which method is more reasonable in exploratory data analysis.