• Journal of information and communication convergence engineering
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• v.2 no.2
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• pp.106-109
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• 2004

This study designs a load balancer via direct routing that share a virtual service on a single IP address in the Linux system and suggests an efficient load balancing method to improve transmission speed in the web server cluster environment. It will increase performance and scalability with fast packet transfer and removing bottleneck problem by using TCP Splicing and Content-Aware Distributor method. This method is expected to be the noticeable technology that provides an important interface, which make application services for e-commerce effectively be applied to high-speed network infrastructure. At this time, it is required to study further on the optimum balancing method in the web server cluster environment so as to apply the hybrid (optimum load balancing method by software and hardware) method and improve the reuse of security cession based on high-speed TCP connections.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.35-41
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• 2018

In this paper, we propose a swarm-based possibilistic c-means(PCM) algorithm in order to overcome the problems of PCM, which are sensitiveness of clustering performance due to initial cluster center's values and producing coincident or close clusters. To settle the former problem of PCM, we adopt a swam-based global optimization method which can be provided the optimal initial cluster centers. Furthermore, to settle the latter problem of PCM, we design an adaptive thresholding model based on the optimized cluster centers that yields preliminary clustered and un-clustered dataset. The preliminary clustered dataset plays a role of preventing coincident or close clusters and the un-clustered dataset is lastly clustered by PCM. From the experiment, the proposed method obtains a better performance than other PCM algorithms on a simulated magnetic resonance(MR) brain image dataset which is corrupted by various noises and bias-fields.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.157-163
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• 2023

Recently, as businesses and data types become more complex and diverse, efficient data analysis using machine learning is required. However, since communication in the cloud environment is greatly affected by network latency, data analysis is not smooth if information delay occurs. In this paper, SPT (Safe Proper Time) was applied to the cluster-based machine learning data analysis agent proposed in previous studies to solve this delay problem. SPT is a method of remotely and directly accessing memory to a cluster that processes data between layers, effectively improving data transfer speed and ensuring timeliness and reliability of data transfer.

• Journal of IKEEE
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• v.27 no.4
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• pp.679-682
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• 2023

In wireless sensor networks, communication failure between sensor nodes causes continuous connection attempts, which results in a large power loss. In this paper, an appropriate distance between the CH(Cluster Head) node and the communicating sensor nodes is limited so that a group of clusters of appropriate size is formed on a two-dimensional plane. To equalize the cluster size, sensor nodes in the shortest distance communicate with each other to form member nodes, and clusters are formed by gathering nearby nodes. Based on the proposed cluster uniformity algorithm, the improvement rate of cluster uniformity is shown by simulation results. The proposed method can improve the cluster uniformity of the network by about 30%.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.221-233
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• 2008

In general, we use a Parallel processing computer manufactured specially for the purpose of parallel processing to do high performance computings. But we can depoly and use a PC cluster composed of several common PCs instead of the very expensive parallel processing computer. A common way to get a PC cluster is to adopt the star topology network connected by a switch hub. But in this paper, we grope efficient implementations of hypercube networks based on TCP/IP to connect 8 PCs directly for more useful parallel processing environment, and make evaluations on functionality and efficiency of them using ping, netperf, MPICH. The two proposed methods of implementation are IP configuration based on link and IP configuration based on node. The results of comparison between them show that there is not obvious difference in performance but the latter is more efficient in simplicity of routing table. For verification of functionality, we compare the parallel processing results of an application in them with the same in a star network based PC cluster. These results also show that the proposed hypercube networks support a perfect parallel processing environment respectively.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.4
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• pp.192-200
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• 2002

The performance of a PC cluster system is limited by the use of traditional communication protocols, such as TCP/IP because these protocols are accompanied with significant software overheads. To overcome the problem, systems based on user-level interface for message passing without intervention of kernel have been developed. The VIA(Virtual Interface Architecture) is one of the representative user-level interfaces which provide low latency and high bandwidth. In this paper, a VIA system is implemented on an SCI(Scalable Coherent Interface) network based PC cluster. The system provides both message-passing and shared-memory programming environments and shows the maximum bandwidth of 84MB/s and the latency of $8{\mu}s$. The system also shows better performance in comparison with other comparable computer systems in carrying out parallel benchmark programs.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.712-714
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• 2005

Real-time 3D visualization of large datasets imposes a distributed architecture of the rendering system and dedicated hardware for image composition. Previous work on this domain has relied on prohibitively expensive cluster systems with hardware composition done by complicated schemes. In this paper we propose a low-cost hardware compositor fur a high performance visualization cluster. We show the system's design and the results obtained using Simulink [1] for our image composition scheme.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.139-142
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• 2010

클러스터 기반의 무선 센서 네트워크는 데이터를 병합하여 전송함으로써 에너지를 효율적으로 사용할 수 있다. 하지만 데이터를 병합하는 클러스터 헤드에 집중된 부하로 인해 센서노드 간 에너지 불균형이 발생하게 된다. 에너지가 고갈되어 가는 센서노드는 클러스터 헤드 선출기간에 필요한 메시지 전송에 따른 에너지 소모가 부담이 된다. 본 논문에서는 센서노드의 에너지가 고갈되어 갈 때 클러스터 선출에 발생하는 에너지 소모를 감소시키기 위해 클러스터 헤드 스케줄링 기법(Cluster Head Scheduling Scheme:CHSS)을 제안한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.271-272
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• 2021

본 논문에서는 Gazebo 시뮬레이터 기반 UAV 군집 시뮬레이션 구현 및 비행 고도 계층화를 구현한 결과를 보인다. Gazebo 시뮬레이션과 Autopilot Program인 Pixhawk4 SITL(Software In The Loop)을 이용하여 UAV를 시뮬레이터에 생성한 뒤 사전에 정의된 Mission에 대한 정보에 따라 비행이 되도록 구현하였다. 또한, Gazebo 시뮬레이터의 Box Object를 이용하여 UAV의 비행 고도를 시각적으로 계층화하여 표현하였다.

• Journal of the Korean Society of Clothing and Textiles
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• v.10 no.3
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• pp.37-48
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• 1986

The purpose of this study was to analyze 'the natural groupings' of subjects in order to classify highly similar somatotype for clothing construction. The sample for the study was drawn randomly out of senior high school boys in Seoul urban area. The sample size was 425 boys between age 16 and 18. Cluster analysis was more concerned with finding the hierarchical structure of subjects by three dimensional distance of stature. bust girth and sleeve length. The groups forming a partition can be subdivided into 5 and 6 sets by the hierarchical tree of the given subjects. Ward's Minimum Variance Method was applied after extraction of distance matrix by the Standardized Euclidean Distance. All of the above data was analyzed by the computer installed at Korea Advanced Institute of Science and Technology. The major findings, take for instance, of 16 age group can be summarized as follows. The results of cluster analysis of this study: 1. Cluster 1 (32 persons means $18.29\%$ of the total) is characterized with smaller bust girth than that of cluster 5, but stature and sleeve length of the cluster 1 are the largest group. 2. Cluster 2 (18 Persons means $10.29\%$ of the total) is characterized with the group of the smallest stature and sleeve length, but bust girth larger than that of cluster 3. 3. Cluster 3(35persons means $20\%$ of the total) is classified with the smallest group of all the stature, bust girth and sleeve length. 4. Cluster 4(60 persons means $34.29\%$ of the total) is grouped with the same value of sleeve length with the mean value of 16 age group, but the stature and bust girth is smaller than the mean value of this age group. 5. Cluster 5(30 persons means $17.14\%$ of the total) is characterized with smaller stature than that of cluster 1, and with larger bust girth than that of cluster 1, but with the same value of the sleeve length with the mean value of the 16 age group.