• Title/Summary/Keyword: cluster method

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Efficient Load Balancing Scheme using Resource Information in Web Server System (웹 서버 시스템에서의 자원 정보를 이용한 효율적인 부하분산 기법)

  • Chang Tae-Mu;Myung Won-Shig;Han Jun-Tak
    • The KIPS Transactions:PartA
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    • v.12A no.2 s.92
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    • pp.151-160
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    • 2005
  • The exponential growth of Web users requires the web serves with high expandability and reliability. It leads to the excessive transmission traffic and system overload problems. To solve these problems, cluster systems are widely studied. In conventional cluster systems, when the request size is large owing to such types as multimedia and CGI, the particular server load and response time tend to increase even if the overall loads are distributed evenly. In this paper, a cluster system is proposed where each Web server in the system has different contents and loads are distributed efficiently using the Web server resource information such as CPU, memory and disk utilization. Web servers having different contents are mutually connected and managed with a network file system to maintain information consistency required to support resource information updates, deletions, and additions. Load unbalance among contents group owing to distribution of contents can be alleviated by reassignment of Web servers. Using a simulation method, we showed that our method shows up to $50\%$ about average throughput and processing time improvement comparing to systems using each LC method and RR method.

Extraction of Intestinal Obstruction in X-Ray Images Using PCM (PCM 클러스터링을 이용한 X-Ray 영상에서 장폐색 추출)

  • Kim, Kwang Baek;Woo, Young Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.12
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    • pp.1618-1624
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    • 2020
  • Intestinal obstruction diagnosis method based on X-ray can affect objective diagnosis because it includes subjective factors of the examiner. Therefore, in this paper, a detection method of Intestinal Obstruction from X-Ray image using Hough transform and PCM is proposed. The proposed method uses Hough transform to detect straight lines from the extracted ROI of the intestinal obstruction X-Ray image and bowel obstruction is extracted by using air fluid level's morphological characteristic detected by the straight lines. Then, ROI is quantized by applying PCM clustering algorithm to the extracted ROI. From the quantized ROI, cluster group that includes bowel obstruction's characteristic is selected and small bowel regions are extracted by using object search from the selected cluster group. The proposed method of using PCM is applied to 30 X-Ray images of intestinal obstruction patients and setting the initial cluster number of PCM to 4 showed excellent performance in detection and the TPR was 81.47%.

A Content-Aware toad Balancing Technique Based on Histogram Transformation in a Cluster Web Server (클러스터 웹 서버 상에서 히스토그램 변환을 이용한 내용 기반 부하 분산 기법)

  • Hong Gi Ho;Kwon Chun Ja;Choi Hwang Kyu
    • Journal of Internet Computing and Services
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    • v.6 no.2
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    • pp.69-84
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    • 2005
  • As the Internet users are increasing rapidly, a cluster web server system is attracted by many researchers and Internet service providers. The cluster web server has been developed to efficiently support a larger number of users as well as to provide high scalable and available system. In order to provide the high performance in the cluster web server, efficient load distribution is important, and recently many content-aware request distribution techniques have been proposed. In this paper, we propose a new content-aware load balancing technique that can evenly distribute the workload to each node in the cluster web server. The proposed technique is based on the hash histogram transformation, in which each URL entry of the web log file is hashed, and the access frequency and file size are accumulated as a histogram. Each user request is assigned into a node by mapping of (hashed value-server node) in the histogram transformation. In the proposed technique, the histogram is updated periodically and then the even distribution of user requests can be maintained continuously. In addition to the load balancing, our technique can exploit the cache effect to improve the performance. The simulation results show that the performance of our technique is quite better than that of the traditional round-robin method and we can improve the performance more than $10\%$ compared with the existing workload-aware load balancing(WARD) method.

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RRSEB: A Reliable Routing Scheme For Energy-Balancing Using A Self-Adaptive Method In Wireless Sensor Networks

  • Shamsan Saleh, Ahmed M.;Ali, Borhanuddin Mohd.;Mohamad, Hafizal;Rasid, Mohd Fadlee A.;Ismail, Alyani
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.7
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    • pp.1585-1609
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    • 2013
  • Over recent years, enormous amounts of research in wireless sensor networks (WSNs) have been conducted, due to its multifarious applications such as in environmental monitoring, object tracking, disaster management, manufacturing, monitoring and control. In some of WSN applications dependent the energy-efficient and link reliability are demanded. Hence, this paper presents a routing protocol that considers these two criteria. We propose a new mechanism called Reliable Routing Scheme for Energy-Balanced (RRSEB) to reduce the packets dropped during the data communications. It is based on Swarm Intelligence (SI) using the Ant Colony Optimization (ACO) method. The RRSEB is a self-adaptive method to ensure the high routing reliability in WSNs, if the failures occur due to the movement of the sensor nodes or sensor node's energy depletion. This is done by introducing a new method to create alternative paths together with the data routing obtained during the path discovery stage. The goal of this operation is to update and offer new routing information in order to construct the multiple paths resulting in an increased reliability of the sensor network. From the simulation, we have seen that the proposed method shows better results in terms of packet delivery ratio and energy efficiency.

Image Scale Prediction Using Key-point Clusters on Multi-scale Image Space (다중 스케일 영상 공간에서 특징점 클러스터를 이용한 영상스케일 예측)

  • Ryu, kwon-Yeal
    • Journal of the Institute of Convergence Signal Processing
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    • v.19 no.1
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    • pp.1-6
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    • 2018
  • In this paper, we propose the method to eliminate repetitive processes for key-point detection on multi-scale image space. The proposed method detects key-points from the original image, and select a good key-points using the cluster filters, and create the key-point clusters. And it select reference objects by using direction angles of the key-point clusters, predict the scale of the original image by using the distributed distance ratio. It transform the scale of the reference image, and apply the detection of key-points to the transformed reference image. In the results of the experiment, the proposed method can be found to improve the key-points detection time by 75 % and 71 % compared to SIFT method and scaled ORB method using the multi-scale images.

Data Direction Aware Clustering Method in Sensor Networks (데이터 전송방향을 고려한 센서네트워크 클러스터링 방법)

  • Jo, O-Hyoung;Kwon, Tae-Wook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.7B
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    • pp.721-727
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    • 2009
  • Wireless Sensor Networks(WSN) make use of low cost and energy constrained sensor nodes. Thus, reaching the successful execution of its tasks with low energy consumption is one of the most important issues. The limitation of existing hierarchical algorithms is that many times the data are transmitted to the opposite direction to the sink. In this paper, DDACM (Data Direction Aware Clustering Method) is proposed. In this method, the nearest node to the sink is elected as cluster head, and when its energy level reaches a threshold value, the cluster head is reelected. We also make a comparison with LEACH showing how this method can reduce the energy consumption minimizing the reverse direction data transmission.

The Introduction of Design Thinking to Science Education and Exploration of Its Characterizations as a Method for Group Creativity Education (집단 창의성 교육을 위한 방안으로서 과학 교육에 디자인적 사고의 도입과 속성 탐색)

  • Lee, Dohyun;Yoon, Jihyun;Kang, Seong-Joo
    • Journal of The Korean Association For Science Education
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    • v.34 no.2
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    • pp.93-105
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    • 2014
  • Group creativity has recently been heightened as a core competence in the 21st century. Therefore, there is a need for introduction of concepts on design thinking emphasizing the collaboration and empathy to science education as an effective method for fostering group creativity. Understanding design thinking for effective introduction should be preceded, so we explore the characterizations of design thinking through the generic model overlay method, focus group interview, and critical incident technique analysis. The results reveal 4 cluster units of competency and 15 core competencies. The collaboration cluster consists of 5 competencies and they are as follows: organization of the team, communication, self-control, persuasiveness, and initiative competency. The integrative thinking cluster consists of 3 competencies and they are as follows: analytical, strategic, and intuitive thinking competency. The human-centeredness cluster consists of 3 competencies and they are as follows: user-orientation, relationship building, and interpersonal understanding competency. The multidisciplinary cluster consists of 4 competencies and they are as follows: achievement orientation, information seeking, curiosity, and flexibility competency. Findings are expected to provide the basic data for developing programs and establishing strategies in order to foster group creativity as well as introducing design thinking to science education effectively.

Structuralization Expected Outcome of Social Welfare Program Based on Community Network : Using Concept Mapping Method (지역사회네트워크를 기반으로 한 사회복지프로그램 기대성과 구조화 : 컨셉트 맵핑(concept mapping)을 활용하여)

  • Kwon, Sunae
    • The Journal of the Korea Contents Association
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    • v.14 no.5
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    • pp.107-116
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    • 2014
  • The purpose of this study is to verify the applicability of concept mapping in the process of planning social welfare program based on community network. Concept mapping is a kind of decision-making method that structuralized complex ideas and presented visually. Already, concept mapping is widely utilized in counseling, nursing and public health area to plan and evaluation their program and service. For recent, effectiveness of concept mapping has been reported. Concept mapping is a effective decision-making method that they recognize outcome gap between service provider and client, reach the outcome's consensus in counseling and nursing, medical area. In this study, we conceptualized 3rd year outcomes of Community Impact Project that was supported from Busan Chest using concept mapping. This CI project intervenes children and youth who lives in Buk-gu, Busan. Concept mapping has six stages-preparation, collecting ideas, structuring statements, representing statement, interpreting the results of the analysis, applying the results. We followed these steps. The participants were working at social welfare organizations, total 11 persons. We obtained 60 statements and analyzed using multidimensional scaling. we collected 5 clusters, cluster 1 'awareness and attitude change of children and youth', cluster 2 'social system change of children and youth', cluster 3 'friendly community formation', cluster 4 'community people change', cluster 5 'service provider change'. As a result, among total 5 clusters formed, 'awareness and attitude change of children and youth' came to the strongest outcomes. When concept mapping was applied to the program planning, the consensus of the opinion came easily in the decision-making process, and the participants were empowered. In addition, clear conceptualization on each element of the program planning was made.

A Study on Consumer Emotion for Social Robot Appearance Design: Focusing on Multidimensional Scaling (MDS) and Cluster Analysis (소셜 로봇 외형 디자인에 대한 소비자 감성에 관한 연구: 다차원 척도법 (MDS)과 군집분석을 중심으로)

  • Seong-Hun Yu;Ji-Chan Yun;Junsik Lee;Do-Hyung Park
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.397-412
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    • 2023
  • In order for social robots to take root in human life, it is important to consider the technical implementation of social robots and human psychology toward social robots. This study aimed to derive potential social robot clusters based on the emotions consumers feel about social robot appearance design, and to identify and compare important design characteristics and emotional differences of each cluster. In our study, we established a social robot emotion framework to measure and evaluate the emotions consumers feel about social robots, and evaluated the emotions of social robot designs based on the semantic differential method, an kansei engineering approach. We classified 30 social robots into 4 clusters by conducting a multidimensional scaling method and K-means cluster analysis based on the emotion evaluation results, confirmed the characteristics of design elements for each cluster, and conducted a comparative analysis on consumer emotions. We proposed a strategic direction for successful social robot design and development from a human-centered perspective based on the design characteristics and emotional differences derived for each cluster.

How to Measure the Agglomeration Effects of Industrial Cluster : A Case Study of the FOODPOLIS ( KOREA NATIONAL FOOD CLUSTER ) (산업클러스터 효과 추정 방법에 관한 연구 : 국가식품클러스터조성사업 사례를 중심으로)

  • Kim, Jung-Wook;Kim, Suk-Young;Yang, Seung-Min
    • Journal of the Economic Geographical Society of Korea
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    • v.15 no.1
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    • pp.42-62
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    • 2012
  • This paper suggests a genuine method to estimate the agglomeration effects of Industrial Cluster focusing on the FOODPOLIS (KOREA NATIONAL FOOD CLUSTER). In this study, we will focus on two issues related to the clustering effect. First, Clusters affect productivity, and a cluster allows companies to operate more productively in inputs; accessing technology, human resource, information, services, and needed institutions. Second, we assume that the effects of Industrial Cluster can be estimated from measurement on differency of an added value between large-scale enterprises and smaller ones. To demonstrate effectiveness of this approach, the estimated effect was compared with that from the related study (A Mini-Cluster). Industry Clusters have been considered as critical factors for regional competitiveness and economic revitalization. For this, the government and local government should find a way and strategy to provide useful contents that can attract the participation of firms and to secure strategic positioning and competition strategies.

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