• Structural Engineering and Mechanics
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• v.37 no.1
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• pp.17-37
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• 2011

This paper presents a new Internet-based computational framework for the realistic simulation of multi-scale response of structural systems. Two levels of parallel processing are involved in this frame work: multiple local distributed computing environments connected by the Internet to form a cluster-to-cluster distributed computing environment. To utilize such a computing environment for a realistic simulation, the simulation task of a structural system has been separated into a simulation of a simplified global model in association with several detailed component models using various scales. These related multi-scale simulation tasks are distributed amongst clusters and connected to form a multi-level hierarchy. The Internet is used to coordinate geographically distributed simulation tasks. This paper also presents the development of a software framework that can support the multi-level hierarchical simulation approach, in a cluster-to-cluster distributed computing environment. The architectural design of the program also allows the integration of several multi-scale models to be clients and servers under a single platform. Such integration can combine geographically distributed computing resources to produce realistic simulations of structural systems.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.95-105
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• 2008

In this paper, we propose the DAMMC(Distributed Authentication Model using Multi-level Cluster) for wireless sensor networks. The proposed model is that one cluster header in m-layer has a role of CA(Certificate Authority) but it just authenticates sensor nodes in lower layer for providing an efficient authentication without authenticating overhead among clusters. In here, the m-layer for authentication can be properly predefined by user in consideration of various network environments. And also, the DAMMC uses certificates based on the threshold cryptography scheme for more reliable configuration of WSN. Experimental results show that the cost of generation and reconfiguration certification are decreased but the security performance are increased compared to the existing method.

• Journal of the Korean Geographical Society
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• v.44 no.5
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• pp.634-646
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• 2009

This paper critically examines cluster dynamics and development in a multi-scalar approach, criticizing both the argument overemphasizing local networks and endogenous development for regional development and the contention highlighting global networks and the role of global players. We argue that state policies, exogenous and direct, play a significant part in cluster dynamics and development especially in the case of Korea where the state government's strong policies have led to rapid industrialization. We analyze multi-scalar factors, especially the government policies at a national level, in the development paths of the three cases including Ulsan automobile cluster, Daedeok research cluster, and Dongdaemun fashion cluster.

• ETRI Journal
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• v.43 no.3
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• pp.524-537
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• 2021

High-performance Linpack (HPL) is among the most popular benchmarks for evaluating the capabilities of computing systems and has been used as a standard to compare the performance of computing systems since the early 1980s. In the initial system-design stage, it is critical to estimate the capabilities of a system quickly and accurately. However, the original HPL mathematical model based on a single core and single communication layer yields varying accuracy for modern processors and accelerators comprising large numbers of cores. To reduce the performance-estimation gap between the HPL model and an actual system, we propose a mathematical model for multi-communication layered HPL. The effectiveness of the proposed model is evaluated by applying it to a GPU cluster and well-known systems. The results reveal performance differences of 1.1% on a single GPU. The GPU cluster and well-known large system show 5.5% and 4.1% differences on average, respectively. Compared to the original HPL model, the proposed multi-communication layered HPL model provides performance estimates within a few seconds and a smaller error range from the processor/accelerator level to the large system level.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.561-578
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• 2010

This study proposes a multi-level damage localization strategy to achieve an effective damage detection system for civil infrastructure systems based on wireless sensors. The proposed system is designed for use of distributed computation in a wireless sensor network (WSN). Modal identification is achieved using the frequency-domain decomposition (FDD) method and the peak-picking technique. The ASH (angle-between-string-and-horizon) and AS (axial strain) flexibility-based methods are employed for identifying and localizing damage. Fundamentally, the multi-level damage localization strategy does not activate all of the sensor nodes in the network at once. Instead, relatively few sensors are used to perform coarse-grained damage localization; if damage is detected, only those sensors in the potentially damaged regions are incrementally added to the network to perform finer-grained damage localization. In this way, many nodes are able to remain asleep for part or all of the multi-level interrogations, and thus the total energy cost is reduced considerably. In addition, a novel distributed computing strategy is also proposed to reduce the energy consumed in a sensor node, which distributes modal identification and damage detection tasks across a WSN and only allows small amount of useful intermediate results to be transmitted wirelessly. Computations are first performed on each leaf node independently, and the aggregated information is transmitted to one cluster head in each cluster. A second stage of computations are performed on each cluster head, and the identified operational deflection shapes and natural frequencies are transmitted to the base station of the WSN. The damage indicators are extracted at the base station. The proposed strategy yields a WSN-based SHM system which can effectively and automatically identify and localize damage, and is efficient in energy usage. The proposed strategy is validated using two illustrative numerical simulations and experimental validation is performed using a cantilevered beam.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.20-27
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• 2006

Multi-level thresholding is a method that is widely used in image segmentation. However most of the existing methods are not suited to be directly used in applicable fields and moreover expanded until a step of image segmentation. This paper proposes region-based multi-level thresholding as an image segmentation method. At first we classify pixels of each color channel to two clusters by using EWFCM(Entropy-based Weighted Fuzzy C-Means) algorithm that is an improved FCM algorithm with spatial information between pixels. To obtain better segmentation results, a reduction of clusters is then performed by a region-based reclassification step based on a similarity between regions existing in a cluster and the other clusters. The clusters are created using the classification information of pixels according to color channel. We finally perform a region merging by Bayesian algorithm based on Kullback-Leibler distance between a region and the neighboring regions as a post-processing method as many regions still exist in image. Experiments show that region-based multi-level thresholding is superior to cluster-, pixel-based multi-level thresholding, and the existing mettled. And much better segmentation results are obtained by the post-processing method.

• Journal of Korea Technology Innovation Society
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• v.6 no.2
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• pp.175-190
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• 2003

This paper deals with the methods for selecting the key research areas, which fit for the large, multi-disciplinary, and long-term programs by making use of Technology Cluster Analysis. This method is applied to mano-technology field at the level of national R&D program. 56 nano-technologies are analyzed and grouped into three main clusters based on the survey data from 180 experts. Three main clusters are \circled1 naro-materials related cluster, \circled2 naro-device related cluster, and \circled3 naro-bio related cluster. These three clusters are coincided with the focused areas of nano-technology in Korea. Each cluster is analyzed in view of its competence position.

• ETRI Journal
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• v.29 no.5
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• pp.700-702
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• 2007

We present a relevance feedback approach based on multi-class support vector machine (SVM) learning and cluster-merging which can significantly improve the retrieval performance in region-based image retrieval. Semantically relevant images may exhibit various visual characteristics and may be scattered in several classes in the feature space due to the semantic gap between low-level features and high-level semantics in the user's mind. To find the semantic classes through relevance feedback, the proposed method reduces the burden of completely re-clustering the classes at iterations and classifies multiple classes. Experimental results show that the proposed method is more effective and efficient than the two-class SVM and multi-class relevance feedback methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3B
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• pp.123-134
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• 2008

In this paper, a routing algorithm for wireless sensor networks is proposed to improve the efficiency of energy consumption in sensor nodes. Each sensor node has the value called ‘Flooding Level’ obtained through the initial flooding from a sink node instead of sending beacon messages in multi-hop sensor field. This value can be used for guaranteeing the sensor nodes to connect with a sink node and determining the roles of cluster-head and cluster-gateway node efficiently and simply during the clustering. If different algorithms are added to our protocol, it will work better in the side of energyefficiency. This algorithm is evaluated through analysis and extensive simulations.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.635-642
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• 2003

The radical development of recent network technology provides the basic foundation which can establish a high speed and cheap cluster system. It is a general trend that conventional cluster systems are built as the system over a fixed level based on stabilized and high speed local networks. A multi-distributed web cluster group is a web cluster model which can obtain high performance, high efficiency and high availability through mutual cooperative works between effective job division and system nodes through parallel performance of a given work and shared memory of SC-Server with low price and low speed system nodes on networks. For this, multi-distributed web cluster group builds a sub-cluster group bound with single imaginary networks of multiple system nodes and uses the web distributed shared memory of system nodes for the effective data transmission within sub-cluster groups. Since the presented model uses a load balancing and parallel computing method of large-scale work required from users, it can maximize the processing efficiency.