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.

Traffic Density Classification Using Sound Datasets: An Empirical Study on Traffic Flow at Asymmetric Roads

Abstract: Recently, with the rapid growth of Deep Learning models for solving complicated classification problems, urban sound classification techniques have been attracted more attention. In this paper, we take an investigation on how to apply this approach for the transportation domain. Specifically, traffic density classification based on the road sound datasets, which have been recorded and preprocessed on the urban road network, is taken into account. In particular, state-of-the-art methods for analyzing and extracting sound datasets have taken into account for the classification problem of traffic flow. Consequently, this study focuses on three main processes which are: i) generating image representation for the sequences of the road sound datasets; ii) proposing a convolutional neural network model for the feature extraction; iii) adopting a hybrid approach for the classification stage by combining convolutional neural network with other machine learning models. Regarding the experiment, the road sound dataset has been collected at an urban asymmetric road with different time periods (e.g., morning and evening) in order to evaluate our proposed method. Specifically, the implementations show promising results in which the accuracies are able to achieve from 92% to 95% for classifying traffic densities with different time periods.

Valuations using royalty data in the life sciences area—focused on anticancer and cardiovascular therapies

Abstract: This research seeks to answer the basic question, “How can we build up the formula to estimate the proper royalty rate and up-front payment using the data I can get simply as input?” This paper suggests a way to estimate the proper royalty rate and up-front payment using a formula derived from the regression of historical royalty dataset. This research analyzes the dataset, including the royalty-related data like running royalty rate (back-end payments) and up-front payment (up-front fee + milestones), regarding drug candidates for specific drug classes, like anticancer or cardiovascular, by regression analysis. Then, the formula to predict royalty-related data is derived using the attrition rate for the corresponding development phase of the drug candidate for the license deal and the revenue data of the license buyer (licensee). Lastly, the relationship between the formula to predict royalty-related data and the expected net present value is investigated. For the anticancer (antineoplastics) and cardiovascular drug classes, the formula to predict the royalty rate and up-front payment is as follows. $$ \mathrm{X}=\left(\mathrm{Attrition}\kern0.5em \mathrm{Rate}\kern0.5em \ast \kern0.5em \mathrm{Licensee}\kern0.5em \mathrm{Revenue}\right)/100 $$ $$ $$ (1) $$ \begin{array}{l}\mathrm{Royalty}\kern0.5em \mathrm{Rate}=\left(1+\mathrm{a}*\mathrm{X}\right)/\left(\mathrm{b}+\mathrm{c}*\mathrm{X}\right)=\\ {}\left(1+\hbox{--} 5.14147\mathrm{E}\hbox{-} 09*\mathrm{X}\right)/\left(0.128436559+\hbox{--} 6.37\mathrm{E}\hbox{--} 10*\mathrm{X}\right)\end{array} $$ (2) $$ \begin{array}{l}\mathrm{Upfront}\kern0.5em \mathrm{payment}\kern0.5em \left(\mathrm{Up}\hbox{-} \mathrm{front}+\mathrm{Milestones}\right)=\left(\mathrm{a}+\mathrm{X}\right)/\left(\mathrm{b}+\mathrm{c}*\mathrm{X}\right)=\\ {}\left(\hbox{--} 133620928.7+\mathrm{X}\right)/\left(\hbox{--} 3.990489631+2.04191\mathrm{E}\hbox{--} 08*\mathrm{X}\right)\end{array} $$ $$ \mathrm{X}=\left(\mathrm{Attrition}\ \mathrm{Rate}\ *\ \mathrm{Licensee}\ \mathrm{Revenue}\right)/100 $$ $$ $$ (3) $$ \begin{array}{l}\mathrm{Royalty}\kern0.5em \mathrm{Rate}=\mathrm{y}0+\mathrm{a}/\mathrm{X}+\mathrm{b}/{\mathrm{X}}^2=\\ {}9.26\mathrm{e}+0+\left(-8.528+5\right)/\mathrm{X}+1.744\mathrm{e}+10/{\mathrm{X}}^2\end{array} $$ (4) $$ \begin{array}{l}\mathrm{Upfront}\kern0.5em \mathrm{payment}\kern0.5em \left(\mathrm{Up}\hbox{-} \mathrm{front}+\mathrm{Milestone}\right)=\mathrm{y}0+\mathrm{ax}+\mathrm{b}{\mathrm{x}}^2\\ {}=7.103\mathrm{e}+6+\left(\hbox{--} 3.990489631\right)*\mathrm{X}+\left(\hbox{--} 1.536\mathrm{e}\hbox{--} 12\right)*{\mathrm{X}}^2\end{array} $$ In the case of Equations Equation 2 and Equation 4, it is statistically meaningful (R2: 039–0.41); however, in the case of Equations Equation 1 and Equation 3, it has a weak relationship (R2: 022–0.28), thus requiring further study. This research is limited to the relationship between two drug classes—anticancer (antineoplastics) and cardiovascular—and royalty-related data. Valuation for the drug candidate within a specific drug class can be possible, and the royalty rate can be a variable according to drug class and licensee revenue.

Performance evaluation of modified genetic and swarm‐based optimization algorithms in damage identification problem

Abstract: An experimental verification of a damage detection process using novel optimization techniques such as modified real coded genetic algorithms and swarm-based algorithms is presented. Here, the objective function is defined as the sum of differences of the modal frequencies between intact and stiffness damaged state, which has to be minimized to identify the damage location and its severity in the process of model updating. In addition to the structural or damage variables such as the mass or stiffness of the numerical model, the profiles of modal frequency shifts are also damage-sensitive features. The iterative process that uses the proposed population-based optimization algorithms successfully identifies the local mass change of a test structure by updating the damage variables to fit the modal data of test structures such as a cantilevered beam and multibay truss frame. Copyright © 2011 John Wiley & Sons, Ltd.

Study of the K + π + π - final state in B + →J/ψK + π + π - and B + →ψ ' K + π + π -

Abstract: Using $535\ifmmode\times\else\texttimes\fi{}{10}^{6}$ $B$-meson pairs collected by the Belle detector at the KEKB ${e}^{+}{e}^{\ensuremath{-}}$ collider, we measure branching fractions of $(7.16\ifmmode\pm\else\textpm\fi{}0.10(\mathrm{stat})\ifmmode\pm\else\textpm\fi{}0.60(\mathrm{syst})\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}4}$ for ${B}^{+}\ensuremath{\rightarrow}J/\ensuremath{\psi}{K}^{+}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}$ and $(4.31\ifmmode\pm\else\textpm\fi{}0.20(\mathrm{stat})\ifmmode\pm\else\textpm\fi{}0.50(\mathrm{syst}))\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}4}$ for ${B}^{+}\ensuremath{\rightarrow}{\ensuremath{\psi}}^{\ensuremath{'}}{K}^{+}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}$. We perform amplitude analyses to determine the resonant structure of the ${K}^{+}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}$ final state in ${B}^{+}\ensuremath{\rightarrow}J/\ensuremath{\psi}{K}^{+}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}$ and ${B}^{+}\ensuremath{\rightarrow}{\ensuremath{\psi}}^{\ensuremath{'}}{K}^{+}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}$ and find that the ${K}_{1}(1270)$ is a prominent component of both decay modes. There is significant interference among the different intermediate states, which leads, in particular, to a striking distortion of the $\ensuremath{\rho}$ line shape due to the $\ensuremath{\omega}$. Based on the results of the fit to the ${B}^{+}\ensuremath{\rightarrow}J/\ensuremath{\psi}{K}^{+}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}$ data, the relative decay fractions of the ${K}_{1}(1270)$ to $K\ensuremath{\rho}$, $K\ensuremath{\omega}$, and ${K}^{*}(892)\ensuremath{\pi}$ are consistent with previous measurements, but the decay fraction to ${K}_{0}^{*}(1430)$ is significantly smaller. Finally, by floating the mass and width of the ${K}_{1}(1270)$ in an additional fit of the ${B}^{+}\ensuremath{\rightarrow}J/\ensuremath{\psi}{K}^{+}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}$ data, we measure a mass of $(1248.1\ifmmode\pm\else\textpm\fi{}3.3(\mathrm{stat})\ifmmode\pm\else\textpm\fi{}1.4(\mathrm{syst}))\text{ }\text{ }\mathrm{MeV}/{c}^{2}$ and a width of $(119.5\ifmmode\pm\else\textpm\fi{}5.2(\mathrm{stat})\ifmmode\pm\else\textpm\fi{}6.7(\mathrm{syst}))\text{ }\text{ }\mathrm{MeV}/{c}^{2}$ for the ${K}_{1}(1270)$.

Isospin-dependent pion in-medium effects on the charged-pion ratio in heavy ion collisions

Abstract: Using results from the chiral perturbation theory for the $s$-wave interaction and the $\ensuremath{\Delta}$-resonance model for the $p$-wave interaction of pions with nucleons, we evaluated the spectral functions of pions in asymmetric nuclear matter with unequal proton and neutron densities. We find that in hot dense neutron-rich matter the strength of the spectral function of positively charged pions at low energies is somewhat larger than that of negatively charged pions. In a thermal model, this isospin-dependent effect slightly reduces the ratio of negatively charged to positively charged pions that are produced in heavy ion collisions induced by radioactive beams. The relevance of our results to the determination of the nuclear symmetry energy from the measured ratio of negatively to positively charged pions produced in heavy ion collisions is discussed.