• Journal of Korea Game Society
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• v.18 no.1
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• pp.115-124
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• 2018

Various kinds of tile-based ultra-high resolution display devices have been developed by, for example, constructing display walls using many commodity LCD displays. To represent 3D applications like computer games on these devices, one has to develop 3D applications or develop particular APIs only for representing on these devices. If one can develop a distributed rendering system using legacy 3D APIs such as OpenGL and Direct3D by extending a remote rendering system, commercial computer games can be represented on such display devices without modifying their source codes. The purpose of the paper is to propose a new Dired3D-based distribute rendering system by extending a Direct3D-based remote rendering system and to show its feasibility technically by appling it to a sample Direct3D application and performing a few experimentations.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.459-470
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• 2003

It is required to research on high-dimensional index structures for efficiently retrieving high-dimensional data because an attribute vector in data warehousing and a feature vector in multimedia database have a characteristic of high-dimensional data. For this, many high-dimensional index structures have been proposed, but they have so called ‘dimensional curse’ problem that retrieval performance is extremely decreased as the dimensionality is increased. To solve the problem, the cell-based filtering (CBF) scheme has been proposed. But the CBF scheme show a linear decreasing on performance as the dimensionality. To cope with the problem, it is necessary to make use of parallel processing techniques. In this paper, we propose a parallel CBF scheme which uses a horizontally-partitioned technique as declustering. In order to maximize the retrieval performance of the proposed parallel CBF scheme, we construct our parallel CBF scheme under a SN (Shared Nothing) cluster architecture. In addition, we present a data insertion algorithm, a rage query processing one, and a k-NN query processing one which are suitable for the SN cluster architecture. Finally, we show that our parallel CBF scheme achieves better retrieval performance in proportion to the number of servers in the SN cluster architecture, compared with the conventional CBF scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2493-2499
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• 2011

With growth of nano-bio industry, it is of significant importance to develop an automated system to exploit cell behaviors, including migration, mitosis, apoptosis, shape deformation of individual cells and their interactions among cells in the process of cell growth. In this paper, we proposed preprocessing techniques, a classification method which classifies clusters (overlapping multiple cells) from cells and an automated method which counts the number of cells and clusters in order to analyze 2D or 3D deformations of the cells in the real-time images from microscope in the cell culture. We conducted the 3T3 cell images taken from each thirty-minute interval. It showed the average 99.8% accuracy automatically for separating cells and clusters.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.2
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• pp.108-113
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• 2003

Research results have demonstrated that conventional client-server databases have scalability problem in the presence of many concurrent clients. The multi-tier architecture that exploits similarities in clients' object access behavior partitions clients into logical clusters according to their object request pattern. As a result, object requests that are served inside the clusters, server load and request response time can be optimized. Management of clustering by utilizing clients' access pattern-based is an important component for the system's goal. Off-line methods optimizes the quality of the global clustering, the necessary cost and clustering schedule needs to be considered and planned carefully in respect of stable system's performance. In this paper, we propose methods that detect changes in access behavior and optimize system configuration in real time. Finally this paper demonstrates the effectiveness of on-line change detection and results of experimental investigation concerning reconfiguration.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.3
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• pp.343-361
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• 2013

We proposed and evaluated a tag semantic analysis method in which original tags are expanded and the semantic relations between original or expanded tags are used to extract key sentences from lecture speech transcripts. To do that, we first investigated how useful Flickr tag clusters and WordNet synonyms are for expanding tags and for detecting the semantic relations between tags. Then, to evaluate our proposed method, we compared it with a latent semantic analysis (LSA) method. As a result, we found that Flick tag clusters are more effective than WordNet synonyms and that the F measure mean (0.27) of the tag semantic analysis method is higher than that of LSA method (0.22).

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.41-47
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• 2008

Cluster based fuzzy model tree has certain drawbacks to decrease performance of testinB data when over-fitting of training data exists. To reduce the sensitivity of performance due to over-fitting problem, we proposed a modified cluster based fuzzy model tree with node information. To construct model tree, cluster centers are calculated by fuzzy clustering method using all input and output attributes in advance. And then, linear models are constructed at internal nodes with fuzzy membership values between centers and input attributes. In the prediction step, membership values are calculated by using fuzzy distance between input attributes and all centers that passing the nodes from root to leaf nodes. Finally, data prediction is performed by the weighted average method with the linear models and fuzzy membership values. To show the effectiveness of the proposed method, we have applied our method to various dataset. Under various experiments, our proposed method shows better performance than conventional cluster based fuzzy model tree.

• Journal of KIISE
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• v.42 no.3
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• pp.307-319
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• 2015

Current ontology studies use the Hadoop distributed storage framework to perform map-reduce algorithm-based reasoning for scalable ontologies. In this paper, however, we propose a novel approach for scalable Web Ontology Language (OWL) Horst Lite ontology reasoning, based on distributed cluster memories. Rule-based reasoning, which is frequently used for scalable ontologies, iteratively executes triple-format ontology rules, until the inferred data no longer exists. Therefore, when the scalable ontology reasoning is performed on computer hard drives, the ontology reasoner suffers from performance limitations. In order to overcome this drawback, we propose an approach that loads the ontologies into distributed cluster memories, using Spark (a memory-based distributed computing framework), which executes the ontology reasoning. In order to implement an appropriate OWL Horst Lite ontology reasoning system on Spark, our method divides the scalable ontologies into blocks, loads each block into the cluster nodes, and subsequently handles the data in the distributed memories. We used the Lehigh University Benchmark, which is used to evaluate ontology inference and search speed, to experimentally evaluate the methods suggested in this paper, which we applied to LUBM8000 (1.1 billion triples, 155 gigabytes). When compared with WebPIE, a representative mapreduce algorithm-based scalable ontology reasoner, the proposed approach showed a throughput improvement of 320% (62k/s) over WebPIE (19k/s).

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.11
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• pp.369-382
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.736-738
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• 2001

웹을 사용하는 사용자들의 급속도로 증가하는 서비스 요청을 신속하고 저렴한 비용으로 처리하기 위한 대응책으로, LAN 환경의 웹 서버 클러스터 구조가 각광을 받고 있다. 높은 가용성 및 확장성을 보장하는 웹 서비스를 제공하기 위해 많은 부하의 서비스 요구를 여러 서버에게 효과적으로 나누어 처리할 수 있어야 하며, 따라서 서비스 요청 패킷을 고르게 분배할 수 있는 합리적인 스케줄링 기법을 필요로 한다. ONE-IP 스케줄링 기법은 이더넷의 브로드케스트 메시지에 의해 스케줄링이 분산되도록 하는 전략을 사용함으로써, 클러스터에 유입되는 패킷의 집중화로 인해 발생할 수 있는 병목 현상(bottleneck)과 치명적인 오류(Single-point of Failure) 문제를 효과적으로 해결하였다. 그러나, 서비스를 요청하는 패킷의 발신지 주소만을 이용하는 단순한 패킷 스케줄링을 사용하기 때문에 클러스터를 구성하는 서버들 간의 부하 불균형을 가중시키며, 결과적으로 클러스터의 효율성을 저하시키는 문제점을 가지고 있다. 본 논문에서는 이러한 문제점을 해결하기 위하여 RR ONE-IP 기법을 제안하였다. 제안한 기법은 서버에 할당되는 부하간에 불균형이 발생하는 문제점을 해결하기 위해 TCP 연결 단위의 스케줄링 전략을 사용하였으며, 서버의 부하 정보를 이용하지 않는 RR 스케줄링 기법을 도입함으로써, ONE-IP 기법의 장점을 그대로 유지하면서 보다 나은 부하의 균등한 분배로 시스템의 처리 능력을 향상시키도록 하였다. 또한, 실험을 수행한 결과 제안한 기법이 기존의 기법에 비해 평균 3.84%의 시스템의 성능 향상을 보였으며, 과부하 발생율에서는 평균 23.5%의 감소를 가져왔음을 보였다.우 단어 인식률이 43.21%인 반면 표제어간 음운변화 현상을 반영한 1-Best 사전의 경우 48.99%, Multi 사전의 경우 50.19%로 인식률이 5~6%정도 향상되었음을 볼 수 있었고, 수작업에 의한 표준발음사전의 단어 인식률 45.90% 보다도 약 3~4% 좋은 성능을 보였다.으로서 hemicellulose구조가 polyuronic acid의 형태인 것으로 사료된다. 추출획분의 구성단당은 여러 곡물연구의 보고와 유사하게 glucose, arabinose, xylose 함량이 대체로 높게 나타났다. 점미가 수가용성분에서 goucose대비 용출함량이 고르게 나타나는 경향을 보였고 흑미는 알칼리가용분에서 glucose가 상당량(0.68%) 포함되고 있음을 보여주었고 arabinose(0.68%), xylose(0.05%)도 다른 종류에 비해서 다량 함유한 것으로 나타났다. 흑미는 총식이섬유 함량이 높고 pectic substances, hemicellulose, uronic acid 함량이 높아서 콜레스테롤 저하 등의 효과가 기대되며 고섬유식품으로서 조리 특성 연구가 필요한 것으로 사료된다.리하였다. 얻어진 소견(所見)은 다음과 같았다. 1. 모년령(母年齡), 임신회수(姙娠回數), 임신기간(姙娠其間), 출산시체중등(出産時體重等)의 제요인(諸要因)은 주산기사망(周産基死亡)에 대(對)하여 통계적(統計的)으로 유의(有意)한 영향을 미치고 있어 $25{\sim}29$세(歲)의 연령군에서, 2번째 임신과 2번째의 출산에서 그리고 만삭의 임신 기간에, 출산시체중(出産時體重) $3.50{\sim}3.99kg$사이의 아이에서 그 주산기사망률(周産基死亡率)

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.1-6
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• 2019

Multicast is an efficient method for real-time transmission in many multimedia applications. It is important to recover lost packets and to manage multicast groups according to the network status in order to improve the reliability of multicast transmissions. In this paper, we propose a method that can efficiently recover lost packets in a large multicast group. In the proposed method, we create a recovery cluster (RC) using a multicast domain (MD) for recovery of lost packets. In the conventional methods, clusters send a request message for lost packets to the senders in order to recover the packets lost from many multicast applications. This increases packet delay time and overhead because of the feedback messages and retransmitted packets. In the proposed method, we improve these problems using the RC, which consists of many MDs (which have overlay multicast senders), and many cluster heads (CHs). We divide the message into blocks, and divide each block into many segments for packet recovery using the CHs. When packet loss occurs, all CHs share the segment information and recover the lost segments at the same time. Simulation results show that the proposed method could improve the packet recovery ratio by about 50% compared to the conventional methods.