• 한국전산유체공학회:학술대회논문집
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• 2001.05a
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• pp.161-169
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• 2001

At the end of 1999, the TeraCluster Project in the KISTI Supercomputing Center was initiated to explore the possibility of PC clusters as a scientific computing platform to replace the Cray T3E system in KISTI by 2002. Since actual performance of a computing system varies significantly for different architectures, representative in-house codes from major application fields were executed to evaluate the actual performance of systems with different combination of CPU, network and network topology. As an example of practical CFD(Computational Fluid Dynamics) simulations, the flow past the Onera-M6 wing and the flow past a infinite wing were simulated on a clusters of Linux and several other hardware environments.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.331-336
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• 2013

The purpose of this study is to visualize the characteristics of ER fluids as preceding step of developing 3 port ER valves. As the strength of the electric field increases, more clusters in flow are made and these clusters are thought to be the reasons of the load flow rate being increased and the outlet flow rate being decreased. The ER Valves and load and outlet flow rate check method are considered to be applied to the fluid power control system. Using the manufactured pressure control valve, a one-link manipulator with FHA in robot system is driven. As a result, it is experimentally confirmed that the pressure control valve using ER fluids is applicable to use in driving actuator. If it applies characteristics of the ER fluids, it will be able to apply in the control system for the ER Valve which occurs from industrial controller(PLC).

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.164-169
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• 2008

The increasing late-payment rate of credit card customers caused by a recent economic downturn are incurring not only reduced profit of department stores but also significant loss. Under this pressure, the objective of credit forecasting is extended from presumption of good or bad customers to contribution to revenue growth. As a method of managing defaults of department store credit card, this study classifies credit delinquents into some clusters, analyzes repaying patterns of customers in each cluster, and develops credit forecasting system to manage delinquents of department store credit card using data of Korean D department store's delinquents. The model presented by this study uses Kohonen network, a kind of artificial neural network of data mining techniques to cluster credit delinquents into groups. Logistic regression model is also used to predict repayment rate of customers of each cluster per period. The accuracy of presented system for the whole clusters is 92.3%.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.464-469
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• 2001

CRM(Customer Relationship Management : CRM) is an advanced marketing supporting system which analyze customers\` transaction data and classify or target customer groups to effectively increase market share and profit. Many engines were developed to implements the function and those for classification and clustering are considered core ones. In this study, an improved clustering method based on SOM(Self-Organizing Maps : SOM) is proposed. The proposed clustering method finds the optimal number of clusters so that the effectiveness of clustering is increased. It considers all the data types existing in CRM data warehouses. In particular, and adaptive algorithm where the concepts of degeneration and fusion are applied to find optimal number of clusters. The feasibility and efficiency of the proposed method are demonstrated through simulation with simplified data of customers.

• The Plant Pathology Journal
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• v.34 no.1
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• pp.11-22
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• 2018

Type VI secretion system (T6SS) has been discovered in a variety of gram-negative bacteria as a versatile weapon to stimulate the killing of eukaryotic cells or prokaryotic competitors. Type VI secretion effectors (T6SEs) are well known as key virulence factors for important pathogenic bacteria. In many Burkholderia species, T6SS has evolved as the most complicated secretion pathway with distinguished types to translocate diverse T6SEs, suggesting their essential roles in this genus. Here we attempted to detect and characterize T6SSs and potential T6SEs in target genomes of plant-associated and environmental Burkholderia species based on computational analyses. In total, 66 potential functional T6SS clusters were found in 30 target Burkholderia bacterial genomes, of which 33% possess three or four clusters. The core proteins in each cluster were specified and phylogenetic trees of three components (i.e., TssC, TssD, TssL) were constructed to elucidate the relationship among the identified T6SS clusters. Next, we identified 322 potential T6SEs in the target genomes based on homology searches and explored the important domains conserved in effector candidates. In addition, using the screening approach based on the profile hidden Markov model (pHMM) of T6SEs that possess markers for type VI effectors (MIX motif) (MIX T6SEs), 57 revealed proteins that were not included in training datasets were recognized as novel MIX T6SE candidates from the Burkholderia species. This approach could be useful to identify potential T6SEs from other bacterial genomes.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.4
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• pp.1-10
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• 2022

A vegetative filter strip (VFS) is one of the best management practices (BMPs) to reduce pollutant loads. This study aims to assess the effectiveness of VFS in dense upland field areas. The study areas are agricultural fields in the Maedae (MD), Gaa (GA), and Jaun (JU) watersheds, where severe sediment yields have occurred and the Korean government has designated them as non-point management regions. The agricultural fields were divided into three or four clusters for each watershed based on their slope, slope length, and area (e.g., MD1, MD2). To assess the sediment trapping (STE) and pesticide reduction efficiency (PRE) of VFS, the Vegetative Filter Strip Modeling System (VFSMOD) was applied with three different scenarios (SC) (SC1: VFS with rye vegetation; SC2: VFS with rye vegetation and a gentle slope in VFS range; and SC3: VFS with grass mixture). For SC1, there were relatively short slope lengths and small areas in the MD1 and GA3 clusters, and they showed higher pollutant reduction (STE>50%, PRE>25%). For SC2 and SC3, all clusters in GA and some clusters (MD1 and MD3) in MD show higher pollutant reduction (>25%), while the uplands in JU still show a lower pollutant (<25%). With correlation analysis between geographic characteristics and VFS effectiveness slope and slope length showed relative higher correlations with the pollutant efficiency than a area. The results of this study implied that slope and slope length should be considered to find suitable upland conditions for VFS installations.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.9
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• pp.416-424
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• 2007

The Bio-Inspired system is a computing model that emulates the objects in ecosystem which are evolving themselves and cooperate each other to perform some tasks. Since it could be used to solved the complex problems that have been very difficult to resolve with previous algorithms, there have been a lot of researches to develop an application based on the Bio-Inspired system. However, since this computing model requires the process of evolving and cooperating with a lot of objects and this process takes a lot of times, it has been very hard to develop an application based on this computing model. This paper presents a parallel simulator for a Bio-Inspired system that is designed and implemented with OMNeT++ on PC clusters, and proves its usefulness by showing its simulation performance for a couple of applications. In the proposed parallel simulator, the functions required in the ERS platform for evolving and cooperating between objects (called Ecogent) are mapped onto the functions of OMNeT++, and they are simulated on PC clusters simultaneously to reduce the total simulation time. The simulation results could be monitored with a GUI In realtime, and they are also recorded into DBMS for systematic analyses afterward. This paper shows the usefulness of the proposed system by analyzing its performances for simulating various applications based on Bio-Inspired system on PC clusters with 4 PCs.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.857-866
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• 2006

Performance of an image retrieval system is usually very low because of the semantic gap between the low level feature and the high level concept in a query image. Semantically relevant images may exhibit very different visual characteristics, and may be scattered in several clusters. In this paper, we propose a content based image rertrieval approach which combines region based image retrieval and a new relevance feedback method using adaptive clustering together. Our main goal is finding semantically related clusters to narrow down the semantic gap. Our method consists of region based clustering processes and cluster-merging process. All segmented regions of relevant images are organized into semantically related hierarchical clusters, and clusters are merged by finding the number of the latent clusters. This method, in the cluster-merging process, applies r: using v principal components instead of classical Hotelling's $T_v^2$ [1] to find the unknown number of clusters and resolve the singularity problem in high dimensions and demonstrate that there is little difference between the performance of $T^2$ and that of $T_v^2$. Experiments have demonstrated that the proposed approach is effective in improving the performance of an image retrieval system.

• Journal of the Korea Computer Graphics Society
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• v.16 no.4
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• pp.25-33
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• 2010

With the popularization of digital photography, people are now capturing and storing far more photos than ever before. However, the enormous number of photos often discourages the users to identify desired photos. In this paper, we present a novel method for fast and intuitive browsing through large collections of geo-referenced photographs. Given a set of photos, we construct a hierarchical structure of clusters such that each cluster includes a set of spatially adjacent photos and its sub-clusters divide the photo set disjointly. For each cluster, we pre-compute its convex hull and the corresponding polygon area. At run-time, this pre-computed data allows us to efficiently visualize only a fraction of the clusters that are inside the current view and have easily recognizable sizes with respect to the current zoom level. Each cluster is displayed as a single polygon representing its convex hull instead of every photo location included in the cluster. The users can quickly transfer from clusters to clusters by simply selecting any interesting clusters. Our system automatically pans and zooms the view until the currently selected cluster fits precisely into the view with a moderate size. Our user study demonstrates that these new visualization and interaction techniques can significantly improve the capability of navigating over large collections of geo-referenced photos.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.1
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• pp.133-158
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• 2011

In 2030s, as we enter in to the era of BT (Bio-Technology) market opening up, technologies in all areas such as IT, data analysis, IC and biochemistry are necessitated. New development in technology will be based on "Convergence", especially between IT and BT. In order to have synergy effects from the convergence, those related industries and universities should be physically inter-related in an appropriate location. Until 2009, 819 industrial clusters where many Korean industries and firms are concentrated have been constructed in Korea. They have had supports from various institutions and facilities. However, few systems designed to assist "intellectual property (IP) service" for technology convergence are found in Korea. Thus, by analyzing current problems and challenges of the Korean industrial clusters, this paper suggests a possible answer to maximize the synergy from technology convergence through organic cooperation among companies in industrial clusters. This paper finds that the Korean industrial clusters need to establish IP service supporting center while suggesting its function and concept on organization structure, and work flow, which help firms to develop IP strategies. In addition, the paper provides a direction for current IP system and policies implemented by the Korean government to be more effective to small-and-medium-sized companies located in the industrial clusters.