Korea Institute of Science and Technology Information

About: Korea Institute of Science and Technology Information is a facility organization based out in Daejeon, South Korea. It is known for research contribution in the topics: Gravitational wave & LIGO. The organization has 1152 authors who have published 2319 publications receiving 93849 citations. The organization is also known as: Korea Institute of Science and Technology Information & KISTI.

Accelerating molecular dynamics simulation using graphics processing unit

Abstract: We have developed CUDA-enabled version of a general purpose molecular dynamics simulation code for GPU. Imple-mentation details including parallelization scheme and performance optimization are described. Here we have focused on the non-bonded force calculation because it is most time consuming part in molecular dynamics simulation. Timing results using CUDA-enabled and CPU versions were obtained and compared for a biomolecular system containing 23558 atoms. CUDA-enabled versions were found to be faster than CPU version. This suggests that GPU could be a useful hardware for molecular dynamics simulation.

Prescriptive Analytics System for Scholar Research Performance Enhancement

Abstract: We introduce a prescriptive analytics system, InSciTe Advisory, to provide researchers with advice for their future research direction and strategy. It consists of two main parts: descriptive analytics and prescriptive analytics. Descriptive analytics provides results from research activity history as well as the research power index for the designated researcher. Prescriptive analytics suggests a group of role model researchers to the researcher, as well as methods to adopt their best practices. The prescription for the researcher is provided according to 5W1H questions and their corresponding answers. All of the analytical results and their explanations related to the given researcher are automatically generated and saved to a report. This researcher-centric prescriptive analytics framework is expected to be a useful tool to understand the designated researcher from the perspective of prescriptive and descriptive analytics. We evaluated user satisfaction results for InSciTe Advisory and Elsvier Scival by five test users. The result of the evaluation demonstrated that user satisfaction of InSciTe Advisory is 126.5% higher than Scival.

First observation of radiative B0→·K0γ decays and measurements of their time-dependent CP violation

Abstract: We report the first observation of the radiative decay B-0 -> phi K-0 gamma using a data sample of 772 x 10(6) B (B) over bar pairs collected at the Gamma(4S) resonance with the Belle detector at the KEKB asymmetric-energy e(+)e(-) collider. We observe a signal of 37 +/- 8 events with a significance of 5.4 standard deviations including systematic uncertainties. The measured branching fraction is B(B-0 ->phi K-0 gamma) = (2.74 +/- 0.60 +/- 0.32) x 10(-6), where the uncertainties are statistical and systematic, respectively. We also report the first measurements of time-dependent CP-violation parameters: S-phi K0s gamma = +0.74(-1.05)(+0.72)(stat)(-0.024)(+0.10)(syst) and A phi(0)(Ks)gamma = +0.35 +/- 0.58(stat)(-0.10)(+0.23)(syst). Furthermore, we measure B(B+ -> phi K+gamma) = (2.48 +/- 0.30 +/- 0.24) x 10(-6), A(CP) = -0.03 +/- 0.11 +/- 0.08, and find that the signal is concentrated in the M-phi K mass region near threshold.

Automated Detection of Influential Patents Using Singular Values

Abstract: Centrality measures such as degree centrality have been utilized to identify influential and important patents in a citation network. However, no existing centrality measures take into consideration information from the change of the similarity matrix. This paper presents a new centrality measure based on the change of a node similarity matrix. The proposed approach gives more intuitive understanding of the finding of the influential nodes. The present study starts off with the assumption that the change of matrix that may result from removing a given node would assess the importance of the node since each node make a contribution to the given similarity matrix between nodes. The various matrix norms using the singular values such as nuclear norm which is the sum of all singular values, are used for calculating the contribution of a given node to a node similarity matrix. In other words, we can obtain the change of matrix norms for a given node after we calculate the singular values for the case of the nonexistence and the case of existence of the node. Then, the node resulting in the largest change (i.e., decrease) of matrix norms can be considered as the most important node. Computation of singular values can be computationally intensive when the similarity matrix size is large. Therefore, the singular value update technique is also developed for the case of the network with large nodes. We compare the performance of our proposed approach with other widely used centrality measures using U.S. patents data in the area of information and security. Experimental results show that our proposed approach is competitive or even performs better compared to existing approaches.

Multidimensional visualization and clustering for multiobjective optimization of artificial satellite heat pipe design

Abstract: This study presents a newly developed approach for visualization of Pareto and quasi-Pareto solutions of a multiobjective design problem for the heat piping system in an artificial satellite. Given conflicting objective functions, multiobjective optimization requires both a search algorithm to find optimal solutions and a decision-making process for finalizing a design solution. This type of multiobjective optimization problem may easily induce equally optimized multple solutions such as Pareto solutions, quasi-Pareto solutions, and feasible solutions. Here, a multidimensional visualization and clustering technique is used for visualization of Pareto solutions. The proposed approach can support engineering decisions in the design of the heat piping system in artificial satellites. Design considerations for heat piping system need to simultaneously satisfy dual conditions such as thermal robustness and overall limitation of the total weight of the system. The proposed visualization and clustering technique can be a valuable design tool for the heat piping system, in which reliable decision-making has been frequently hindered by the conflicting nature of objective functions in conventional approaches.