• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권4호
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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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• 제31권10호
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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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• 제22권10호
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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.

• 한국경제지리학회지
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• 제26권4호
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• pp.391-407
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• 2023

바덴-뷔르템베르크주는 독일에서 가장 강력한 지역경제를 보유하고 있으며, 독일과 유럽에서 가장 혁신적인 지역 중 하나로 알려져 있다. 클러스터는 바덴-뷔르템베르크주의 혁신 전략에서 중추적 역할을 해 왔다. 이 논문은 바덴-뷔르템베르크주의 현대 클러스터 정책을 분석하는 것을 목표로 한다. 바덴-뷔르템베르크주의 클러스터 정책은 클러스터의 형성뿐만 아니라, 혁신 네트워크 활동을 체계적으로 지원해 왔다. 클러스터 정책은 특히 다양한 산업 및 기술 간의 협력 장려와 국제화를 위한 조치를 추진하는 데 초점을 맞추었다. 바덴-뷔르템베르크주의 클러스터 정책의 주요 목표는 클러스터 관리를 전문화하고, 클러스터의 품질을 제고하는 것이었다. 바덴-뷔르템베르크주의 클러스터 정책은 상향식 접근방법을 채택하여 대화를 촉진하기 위해 다양한 조치와 수단을 활용해 왔다. 또한 바덴-뷔르템베르크주의 클러스터 정책은 산업 클러스터 육성 전략을 개발하고 다양한 조치를 시행하는데 책임을 맡은 전담 클러스터 관리기관을 설치하여 운영해 오고 있다.

• International Journal of Computer Science & Network Security
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• 제22권7호
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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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• 제20권2호
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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.

• 천문학회보
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• 제43권2호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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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.

• 한국산학기술학회논문지
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• 제16권12호
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• pp.8550-8555
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• 2015

본 논문은 독일의 연방정부와 주정부 클러스터들을 통해서 한국정부에 주는 정책적 시사점을 찾는데 연구의 목적을 두었다. 제일 먼저 클러스터에 대한 이론적 배경을 알아보았다. 이어서 연구방법에 대해서 서술하였다. 그 다음으로는 본 연구의 중심인 독일 정부의 연방정부와 주정부의 클러스터정책에 대해서 각각 구체적으로 살펴보았다. 마지막 부분에서는 한국정부에 주는 시사점 및 향후 연구방향을 제시하였다. 본 연구에서 나타난 독일의 주정부와 연방정부의 클러스터들은 각각 경쟁과 협력을 동시에 하면서 EU정책의 틀 안에서 장기적으로 이루어짐을 알 수 있었다. 이러한 관점은 한국정부의 클러스터정책에 주는 시사점이며 또한 장기적으로 국제클러스터를 위한 발판을 마련할 필요가 있다고 할 수 있겠다.

• 한국컴퓨터정보학회논문지
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• 제12권2호
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• pp.141-150
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• 2007

본 논문에서는 센서 네트워크의 수명을 길게 하기 위해 각 센서 및 클러스터 헤드에서의 데이터 전송량을 줄이기 위한 방법을 제안한다. 센서의 에너지 소모를 줄이는 가장 중요한 요소는 전송되는 메시지 수를 줄이는 것이다. 본 논문에서는 노드의 에너지를 보다 효율적으로 사용하기 위해 노드의 클러스터 상태를 초기상태, 클러스터 헤드 상태 클러스터 멤버 상태, 비 전송 클러스터 헤드 상태, 비 전송 클러스터 멤버 상태, 수면 상태 등의 여섯 가지 상태로 분류해서 관리한다. 이는 일반적으로 필터의 폭을 넓혀 필터링을 많이 하는 것보다 필터링 효율은 증대시키면서 필터링에 따른 데이터 부정확성을 최소한 줄이는 효과를 가진다. 이 방법은 기존의 연구보다 더 효율적이고 효과적인 방법이다. 다양한 실험을 통해서, 제안한 방법이 다른 방법들보다 더 많은 메시지를 줄이고, 네트워크의 생존기간이 더 증가하였음을 보여준다.