• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.8
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• pp.528-537
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• 2014

Wireless Sensor Network(WSN) is a network which consists of sensor nodes(SNs) in data collection area. It is hard for the SNs to replace battery. Thus energy and transfer efficiency is important because the energy is limited. In this paper, we propose energy-efficient data collection algorithm for wireless sensor networks by using mobile agent in distance-based cluster structure. For avoid collisions and guarantee low latency, make distance-based topology and build cluster by the topology. For performance comparison of the proposed algorithm, compare with existing mobile agent algorithm. When network constructed by 300 nodes, proposed algorithm has performance increase than existing algorithm(GCF, LCF, TBID) in network lifetime 194, 124.6, 1.46 times each and data merging energy efficiency 87.5%, 85%, 45% each.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.131-135
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• 2007

In this paper, The proposed algorithm consists of three steps. In the first step, TD(Transition Density) calculation has to be performed. a CLB-based CPLD low-power technology mapping algorithm considered a Trade-off is proposed. To perform low-power technology mapping for CPLDs, a given Boolean network has to be represented in a DAG. Total power consumption is obtained by calculating the switching activity of each node in a DAG. In the second step, the feasible clusters are generated by considering the following conditions: the number of inputs and outputs, the number of OR terms for CLB within a CPLD. The common node cluster merging method, the node separation method, and the node duplication method are used to produce the feasible clusters. In the final step, low-power technology mapping based on the CLBs packs the feasible clusters. The proposed algorithm is examined using SIS benchmarks. When the number of OR terms is five, the experiment results show that power consumption is reduced by 30.73% compared with TEMPLA, and by 17.11 % compared with PLA mapping.

• ETRI Journal
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• v.40 no.2
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• pp.227-236
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• 2018

Ultra-dense small cell networks (UD-SCNs) have been identified as a promising scheme for next-generation wireless networks capable of meeting the ever-increasing demand for higher transmission rates and better quality of service. However, UD-SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software-defined networking (SDN)-based hierarchical agglomerative clustering (SDN-HAC) framework, which leverages SDN to centrally control all sub-channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non-cooperative scenarios, respectively.

• Journal of The Korean Astronomical Society
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• v.49 no.3
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• pp.83-92
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• 2016

The Toothbrush radio relic associated with the merging cluster 1RXS J060303.3 is presumed to be produced by relativistic electrons accelerated at merger-driven shocks. Since the shock Mach number inferred from the observed radio spectral index, M_radio ≈ 2.8, is larger than that estimated from X-ray observations, M_X ≲ 1.5, we consider the re-acceleration model in which a weak shock of M_s ≈ 1.2 - 1.5 sweeps through the intracluster plasma with a preshock population of relativistic electrons. We find the models with a power-law momentum spectrum with the slope, s ≈ 4.6, and the cutoff Lorentz factor, γ_e,c ≈ 7-8×10⁴ can reproduce reasonably well the observed profiles of radio uxes and integrated radio spectrum of the head portion of the Toothbrush relic. This study confirms the strong connection between the ubiquitous presence of fossil relativistic plasma originated from AGNs and the shock-acceleration model of radio relics in the intracluster medium.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.7 s.262
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• pp.739-746
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• 2007

Recently, models in STL files are widely used in reverse engineering processes, CAD systems and analysis systems. However the models have poor geometric quality and include only triangles, so the models are not suitable for the finite element analysis. This paper presents a general method that generates finite element mesh from STL file models. Given triangular meshes, the method estimates triangles and makes clusters which consist of triangles. The clusters are merged by some geometric indices. After merging clusters, the method applies plane meshing algorithm, based on domain decomposition method, to each cluster and then the result plane mesh is projected into the original triangular set. Because the algorithm uses general methods to generate plane mesh, we can obtain both tri and quad meshes unlike previous researches. Some mechanical part models are used to show the validity of the proposed method.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.626-641
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• 2015

Conventional case-based reasoning (CBR) does not perform efficiently for high-volume datasets because of case retrieval time. To overcome this problem, previous research suggested clustering a case base into several small groups and retrieving neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performance than the conventional CBR. This paper proposes a new case-based reasoning method called the clustering-merging CBR (CM-CBR). The CM-CBR method dynamically indexes a search pool to retrieve neighbors considering the distance between a target case and the centroid of a corresponding cluster. This method is applied to three real-life medical datasets. Results show that the proposed CM-CBR method produces similar or better predictive performance than the conventional CBR and clustering-CBR methods in numerous cases with significantly less computational cost.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.428-431
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• 2004

A multi-stage hierarchical clustering technique, which is an unsupervised technique, has been proposed in this paper for classifying the hyperspectral data .. The multistage algorithm consists of two stages. The 'local' segmentor of the first stage performs region-growing segmentation by employing the hierarchical clustering procedure with the restriction that pixels in a cluster must be spatially contiguous. The 'global' segmentor of the second stage, which has not spatial constraints for merging, clusters the segments resulting from the previous stage, using a context-free similarity measure. This study applied the multistage hierarchical clustering method to the data generated by band reduction, band selection and data compression. The classification results were compared with them using full bands.

• Proceedings of the KSRS Conference
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• v.1
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• pp.188-190
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• 2006

A multistage hierarchical clustering technique, which is an unsupervised technique, was suggested in this paper for classifying large remotely-sensed imagery. The multistage algorithm consists of two stages. The local segmentor of the first stage performs regiongrowing segmentation by employing the hierarchical clustering procedure of CN-chain with the restriction that pixels in a cluster must be spatially contiguous. This stage uses a sliding window strategy with boundary blocking to alleviate a computational problem in computer memory for an enormous data. The global segmentor of the second stage has not spatial constraints for merging to classify the segments resulting from the previous stage. The experimental results show that the new approach proposed in this study efficiently performs the segmentation for the images of very large size and an extensive number of bands

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.1165-1168
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• 2003

In this paper, a CLB-based CPLD low-power technology mapping algorithm is proposed. To perform low power technology mapping for CPLD, a given Boolean network have to be represented to DAG. The proposed algorithm are consist of three step. In the first step, TD(Transition Density) calculation have to be performed. In the second step, the feasible clusters are generated by considering the following conditions: the number of output, the number of input and the number of OR-terms for CLB(Common Logic Block) within a CPLD. The common node cluster merging method, the node separation method, and the node duplication method are used to produce the feasible clusters. In the final step, low power technology mapping based on the CLBs is packing the feasible clusters into the several proper CLBs. Therefore the proposed algorithm is proved an efficient algorithm for a low power CPLD technology mapping.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.36.4-37
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• 2017

Although most of observed properties of giant radio relics detected in the outskirts of galaxy clusters could be explained by relativistic electrons accelerated at merger-driven shocks, a few significant puzzles remain. In some relics the shock Mach number inferred from X-ray observations is smaller than that estimated from radio spectral index. Such a discrepancy could be understood, if either the shock Mach number is nder-estimated in X-ray observation due to projection effects, or if pre-existing electrons with a flat spectrum are re-accelerated by a weak shock, retaining the flat spectral form. In this study, we explore these two scenarios by comparing the results of shock acceleration simulations with observed features of the so-called Toothbrush relic in the merging cluster 1RXS J060303.3. We find that both models could reproduce reasonably well the observed radio flux and spectral index profiles and the integrated radio spectrum. Either way, the broad transverse relic profile requires additional post shock electron acceleration by downstream turbulence.