• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1661-1678
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• 2016

Clustering is one of the key technologies in vehicular networks. Constructing and maintaining stable clusters is a challenging task in high mobility environments. DWCM (Distributed and Weighted Clustering based on Mobility Metrics) is proposed in this paper based on the d-hop dominating set of the network. Each vehicle is assigned a priority that describes the cluster relationship. The cluster structure is determined according to the d-hop dominating set, where the vehicles in the d-hop dominating set act as the cluster head nodes. In addition, cluster maintenance handles the cluster structure changes caused by node mobility. The rationality of the proposed algorithm is proven. Simulation results in the NS-2 and VanetMobiSim integrated environment demonstrate the performance advantages.

• Bulletin of the Korean Chemical Society
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• v.31 no.10
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• pp.2806-2808
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• 2010

The structure of 3-aminophenol $(CO_2)_1$ cluster was computationally studied both in the ground and the lowest singlet excited electronic states. The ground state structure and binding energy of the cluster was investigated using the second-order M$\ddoot{o}$ller-Plesset perturbation theory (MP2) at the complete basis set (CBS) limit. The excited state geometry of the cluster was obtained at the second-order approximate coupled cluster (CC2) level with cc-pVDZ basis set, and the $S_0-S_1$ absorption spectrum was simulated by calculating Franck-Condon overlap integral. The ground state geometry of the global minimum with a very high binding energy of 4.3 kcal/mol was found for the cluster, due to the interaction between amino group and $CO_2$ in addition to the strong $\pi-\pi$ interaction between the aromatic ring and $CO_2$. The excited state geometry shows a very big shift in the position of $CO_2$ compared to the ground state geometry, which results in low intensity and broad envelope in the Franck-Condon simulation.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.107-112
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• 2022

Nowadays clusters are recognized as an important instrument for promoting industrial development, innovation, competitiveness and growth. An educational cluster is a set of interrelated vocational educational institutions of various levels that are united by industry with each other and are connected by partnership with industry enterprises. This article attempts to develop and describe cluster model of university students' multilingual training. The purpose of this study is to describe multilingual training of university students and their polycultural competencies formation and to define the process of multilingual training in form of a cluster. The authors consider clusters as an integral part of the educational campus within the concept framework of Shadrinsk State Pedagogical University. To determine the essence of the concept of a cluster model of university students' multilingual training, theoretical, empirical, observational, and diagnostic methods were implemented, such as a review of scientific literature, a compilation of best practices, observation, statistical methods, etc. The authors analyzed the programs of partner universities and organized international webinars and internships for bachelors and masters abroad and developed online courses "Foreign language for undergraduate students and masters". Experimental data obtained during the implementation of cluster training show the effectiveness of the formation of students' polycultural competencies.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.4
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• pp.391-407
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• 2023

The state of Baden-Württemberg has one of the strongest regional economies in Germany and is known as one of the most innovative regions in both Germany and Europe. Clusters have played a central role in innovation strategies. The article analyzes the current cluster policy in Baden-Württemberg. The Baden-Württemberg cluster policy has systematically supported the development of clusters, cluster initiatives, and state-wide networks. It has also provided increasing support to regions in developing and implementing innovation and networking activities. The cluster policy has specifically focused on promoting collaborations across different industries and technologies, as well as implementing measures for internationalization. The goal of the Baden-Württemberg state cluster policy was to professionalize cluster management and improve its quality. The cluster policy in Baden-Württemberg has adopted a bottom-up approach and utilized various measures and instruments to promote dialogue. The cluster policy in Baden-Württemberg has established a dedicated cluster agency responsible for developing strategies and implementing individual measures.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.75-84
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• 2022

The efficiency of the regional fiscal policy implementation is based on the achievement of target criteria in the formation and distribution of own financial resources of local budgets, reducing their deficit and reducing dependence on transfers. It is also relevant to compare the development of financial autonomy of regions in the course of decentralisation of fiscal relations. The study consists in the cluster analysis of the effectiveness of fiscal policy implementation in the context of 24 regions and the capital city of Kyiv (except for temporarily occupied territories) under conditions of fiscal decentralisation. Clustering of the regions of Ukraine by 18 indicators of fiscal policy implementation efficiency was carried out using Ward's minimum variance method and k-means clustering algorithm. As a result, the regions of Ukraine are grouped into 5 homogeneous clusters. For each cluster measures were developed to increase own revenues and minimize dependence on official transfers to increase the level of financial autonomy of the regions. It has been proved that clustering algorithms are an effective tool in assessing the effectiveness of fiscal policy implementation at the regional level and stimulating further expansion of financial decentralisation of regions.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.96-102
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• 2022

We aim to build predictive models for Airbnb's prices using a GPU-accelerated RAPIDS in a big data cluster. The Airbnb Listings datasets are used for the predictive analysis. Several machine-learning algorithms have been adopted to build models that predict the price of Airbnb listings. We compare the results of traditional and big data approaches to machine learning for price prediction and discuss the performance of the models. We built big data models using Databricks Spark Cluster, a distributed parallel computing system. Furthermore, we implemented models using multiple GPUs using RAPIDS in the spark cluster. The model was developed using the XGBoost algorithm, whereas other models were developed using traditional central processing unit (CPU)-based algorithms. This study compared all models in terms of accuracy metrics and computing time. We observed that the XGBoost model with RAPIDS using GPUs had the highest accuracy and computing time.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.33.2-33.2
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• 2018

Fossil galaxy cluster has a dominant central elliptical galaxy (${\Delta}M12$ >2 in 0.5Rvir) embedded in highly relaxed X-ray halo, which indicates dynamically stable and passively evolved system. These features are expected as a final stage of the cluster evolution in the hierarchical structure formation paradigm. It is known that Abell 2261(A2261 hereafter) is classified as a fossil cluster, but has unusual features such as a high central X-ray entropy (i.e., non-cool core system), which is not expected in normal fossil clusters. We perform a kinematic study with a spectroscopic data of 589 galaxies in the A2261 field. We define cluster member galaxies using the caustic method and discover a new second bright galaxy at ~1.5 Rvir (nearly the splash-back region). It implies the current fossil state of the cluster can break in the near future. In addition, with three independent substructure finding methods, we find that A2261 has many substructures within 3 Mpc from the center of the cluster. These findings support that A2261 is not in a dynamically stable state. We argue that A2261 is in a transitional phase of dynamical evolution of the galaxy cluster and maybe previously defined fossil cluster does not mean the final stage of the evolution of galaxy clusters.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.303-304
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• 2008

For the state estimation problem, the weighted least squares (WLS) method and the fast decoupled method are widely used at present. However, these algorithms can converge to local optimal solutions. Recently, modern heuristic optimization methods such as Particle Swarm Optimization (PSO) have been introduced to overcome the disadvantage of the classical optimization problem. However, heuristic optimization methods based on populations require a lengthy computing time to find an optimal solution. In this paper, we used PSO to search for the optimal solution of state estimation in power systems. To overcome the shortcoming of heuristic optimization methods, we proposed parallel processing of the PSO algorithm based on the PC cluster system. the proposed approach was tested with the IEEE-118 bus systems. From the simulation results, we found that the parallel PSO based on the PC cluster system can be applicable for power system state estimation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8550-8555
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• 2015

The research goal of this paper is to find the cluster policies for the federal and provincial governments through German Cluster Politics. This paper consists of five chapters. In the first chapter the theoretical background for the Cluster is examined. The next chapter details the research method for the federal and state German Cluster Policy study. The results of this paper show that the federal and state German Governments may co-operate or compete in cluster politics. Additionally, this research falls under EU Political Research under the umbrella of the EU. This cluster policy research also provides implications for the Korean Government in the long term.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.141-150
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• 2007

This paper proposes how to reduce the amount of data transmitted in each sensor and cluster head in order to lengthen the lifetime of sensor network. The most important factor of reducing the sensor's energy dissipation is to reduce the amount of messages transmitted. This paper proposed is to classify the node's cluster state into 6 categories in order to reduce both the number and amount of data transmission: Initial, Cluster Head, Cluster Member, Non-transmission Cluster Head, Non-transmission Cluster Member, and Sleep. This should increase the efficiency of filtering and decrease the inaccuracy of the data compared to the methods which enlarge the filter width to do more filtering. This method is much more efficient and effective than the previous work. We show through various experiments that our scheme reduces the network traffic significantly and increases the network's lifetime than existing methods.