• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.31-37
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• 2011

Recently, MANET(Mobile Ad-hoc Network) is developing increasingly in the wireless network. MANET has weakness because phases change frequently and MANET doesn't have middle management system. Every node which consists of MANET has to perform data forwarding, but traceback is not reliable if these nodes do malicious action owing to attack. It also is not easy to find location of attacker when it is attacked as moving of nodes. In this paper, we propose a hierarchical-based traceback method that reduce waste of memory and can manage path information efficiently. In order to manage trace path information and reduce using resource in the cluster head after network is formed to cluster, method which recomposes the path efficiently is proposed. Proposed method in this paper can reduce path trace failure rate remarkably due to moving of nodes. It can also reduce the cost for traceback and time it takes to collect information.

• Journal of the Korea Safety Management & Science
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• v.14 no.1
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• pp.75-85
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• 2012

In this study, the representative hand shapes for the adult Koreans were analyzed by factor analysis and cluster analyses. The analyses were conducted on the anthropometric data of 58 hand dimensions from 325 subjects having nonhomogeneous demographics. Maximum hand circumference, first phalanx length of index finger, and ratio between the two measures were the independent variables for the cluster analyses. The results of the study showed that Korean hand shapes can be divided into 2 clusters irrespective of their size for each of the male and female group. There were slight differences in component ratio of hand shapes with respect to the occupation and the age, but their differences were not statistically significant. The representative Korean hand shapes and their anthrpometric dimensions could be used to design and establish proper sizing system for various hand operating devices.

• Management & Information Systems Review
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• v.33 no.2
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• pp.171-188
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• 2014

Previous researches on technological innovation of SMEs have several limitations such as lack of study for industrial cluster system and entrepreneurship in SMEs, and ignoring role of RandD capability. So, this study suggested empirically a new model to SMEs. Major results are as follows. Firstly, system of industry and production had a significant and positive effect on entrepreneurship. Secondly, entrepreneurship had a significant and positive effect on technological innovation. Thirdly, system of science and technology had positive and significant effects on RandD capability and technological innovation. Fourthly, RandD capability had a positive and significant effect on technological innovation. Fifthly, business support system was not significantly related to entrepreneurship, RandD capability and technological innovation. Research results revealed that industrial cluster system(system of industry and production, system of science and technology), entrepreneurship and RandD capability were important for improvement of technological innovation performance in SMEs.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.892-898
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• 2007

This study aims to implement an efficient process management system for small and medium sized(local) construction companies and a performance management system for the Korean construction industry. The process management system by Lean Construction is Web 2.0 platform-based and creates clusters with numerous general contractors and sub-contractors, which will enable mutually organic process management. Plus, this system will enable them to compare project performance management by analyzing it during or after a project by collecting and accumulating lots of data occurring in pursuit of a project. These performance management cases will be of help in process planning during similar upcoming projects. This study is expected to somewhat reduce the burden of implementing a complicated process management protocol and system that Korean small and medium sized (local) construction companies experience with their web-based process management, and is supposed to realize accurate performance management with highly reliable data which are significantly accumulated within the database.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.161-174
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• 2007

In this paper, we propose a high performance database cluster system called HyperDB to process OLAP queries efficiently. HyperDB is a virtual database system running on top of internet-connected PCs; the PCs are used for their own purpose at ordinary times, but they are able to participate in the database cluster system at non-office hours. We propose fully logical replication technique and optimal parallel intra-query routing technique for extensibility and performance. Experiment for TPC-R benchmark shows significant performance upgrade compared with conventional approaches.

• Journal of the Korean Society of Safety
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• v.34 no.5
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• pp.119-131
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• 2019

Among the themes for CSR(Corporate Social Responsibility), consumer issues include protecting the health and safety of consumers who purchase and use the products. In particular, ensuring product safety is a major theme of consumer issues for corporate social responsibility. Currently, the government implements the Electrical Appliances and Consumer Products Safety Control Act for product safety management and selects products that may harmful to consumers as safety control items, and manages the products by designating them as 4 types of safety certification, safety confirmation, supplier conformity verification, and safety standard compliance. In this paper, we propose management plans for the establishment of a more reasonable classification type of safety management target for 48 items of consumer products to be controlled by the act, and confirm the validity of the plan. First, we perform cluster analysis using data for CISS (Consumer Injury Surveillance System) to derive a new classification type of the safety management target. Next, we compare the results of the cluster analysis with the classification type of the act and the existing scenario classification method RAS (Risk Assessment by Scenario) and the causal network method RAMP (Risk Assessment Method based on Probability). Based on these results, we propose two new plans of safety management target classification and verify its validity.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.617-621
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• 2004

In recent, researchers in the field of Bioinformatics need to analyze thousands of genome sequences efficiently according to introduce of new analysis methods and technologies such as genome expression microchip. This rapid growth in the field of bio-engineering needs computing resources to analyze rapidly for genome sequences, but it does not introduce the computing resources due to an enormous investment expense. The core factor of this study is integrated environment based PC-Cluster system & high speed access rate up to 155Mbps, continuous collection system for bio-information at home and abroad. The results of the study are establishment & stabilization of information and communication infrastructure, establishment & stabilization of high performance computer network up to 155Mbps, development of PC-Cluster system with 32 nodes, a parallel BLAST on Cluster system, which can provides scalable speedup in terms of response time, and development of collection & search system for bio-information.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.159-171
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• 2005

It has been increased to use the SAN with increasing the size of storage device. In this paper, we design and implement a backup system to support the tape and disk based backup with devices and media in SAN cluster. Our backup system provides device and media management for efficiently managing a number of devices and media in SAN cluster. It also supports script management to process an additional tasks requested by clients and monitoring to control and manage tasks in execution. In addition, it supports reporting to offer backup and restore information to clients.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.73-78
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• 2003

In this research, we implement Realtime Air Diffusion Prediction System which is a parallel Fortran model running on distributed-memory parallel computers. The system is designed for air diffusion simulations with four-dimensional data assimilation. For regional air quality forecasting a series of dynamic downscaling technique is adopted using the NCAR/Penn. State MM5 model which is an atmospheric model. The realtime initial data have been provided daily from the KMA (Korean Meteorological Administration) global spectral model output. It takes huge resources of computation to get 24 hour air quality forecast with this four step dynamic downscaling (27km, 9km, 3km, and lkm). Parallel implementation of the realtime system is imperative to achieve increased throughput since the realtime system have to be performed which correct timing behavior and the sequential code requires a large amount of CPU time for typical simulations. The parallel system uses MPI (Message Passing Interface), a standard library to support high-level routines for message passing. We validate the parallel model by comparing it with the sequential model. For realtime running, we implement a cluster computer which is a distributed-memory parallel computer that links high-performance PCs with high-speed interconnection networks. We use 32 2-CPU nodes and a Myrinet network for the cluster. Since cluster computers more cost effective than conventional distributed parallel computers, we can build a dedicated realtime computer. The system also includes web based Gill (Graphic User Interface) for convenient system management and performance monitoring so that end-users can restart the system easily when the system faults. Performance of the parallel model is analyzed by comparing its execution time with the sequential model, and by calculating communication overhead and load imbalance, which are common problems in parallel processing. Performance analysis is carried out on our cluster which has 32 2-CPU nodes.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.400-409
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• 2003

Collaborative filtering (CF) recommendation is a knowledge sharing technology for distribution of opinions and facilitating contacts in network society between people with similar interests. The main concerns of the CF algorithm are about prediction accuracy, speed of response time, problem of data sparsity, and scalability. In general, the efforts of improving prediction algorithms and lessening response time are decoupled. We propose a three-step CF recommendation model which is composed of profiling, inferring, and predicting steps while considering prediction accuracy and computing speed simultaneously. This model combines a CF algorithm with two machine learning processes, SOM (Self-Organizing Map) and CBR (Case Based Reasoning) by changing an unsupervised clustering problem into a supervised user preference reasoning problem, which is a novel approach for the CF recommendation field. This paper demonstrates the utility of the CF recommendation based on SOM cluster-indexing CBR with validation against control algorithms through an open dataset of user preference.