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This paper proposes an efficient masking method for the block cipher SEED that is standardized in Korea. The nonlinear parts of SEED consist of two S-boxes and modular additions. However, the masked version of these nonlinear parts requires excessive RAM usage and a large number of operations. Protecting SEED by the general masking method requires 512 bytes of RAM corresponding to masked S-boxes and a large number of operations corresponding to the masked addition. This paper proposes a new-style masked S-box which can reduce the amount of operations of the masking addition process as well as the RAM usage. The proposed masked SEED, equipped with the new-style masked S-box, reduces the RAM requirements to 288 bytes, and it also reduces the processing time by 38% compared with the masked SEED using the general masked S-box. The proposed method also applies to other block ciphers with the same nonlinear operations. [ABSTRACT FROM AUTHOR]

Current KEPCO's distribution automation system (DAS) provides a very effective restoration solution for the single fault case but cannot handle multiple faults. This paper proposes a two-step restoration scheme—sequential and simultaneous restoration--for multiple fault cases. Efficiency has been achieved by introduction of restoration performance index (RPI) and load-balancing algorithm. Test results to show effectiveness of the proposed scheme are presented, and field experience of DAS in Korea is described as well. [ABSTRACT FROM AUTHOR]

There are several methods available in measuring food taste. The sensory evaluation, for instance, is a typical method for panels to test of taste and recognize smell with their nose by measuring the degree of taste characteristic, intensity, and pleasure. There are many issues entailed in the traditional sensory evaluation method such as forming a panel and evaluation cost; moreover, it is only localized in particular areas. Accordingly, this paper aimed to select food in one particular area, and compare and review the content between sensory evaluations using a taste biological sensor, as well as presenting an analysis of brainwaves using EEG and finally a proposal of a new method for sensory evaluation. In this paper, the researchers have conducted a sensory evaluation whereas a maximum of nine points were accumulated by purchasing eight types of rice wine. These eight types of Makgeolli were generalized by generating multidimensional data with the use of TS-5000z, thus learning mapping points and scaling them. The contribution of this paper, therefore, is to overcome the disadvantages of the sensory evaluation with the usage of the suggested taste biological sensor system. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic programming algorithm to draw optimal intermodal freight routing with regard to international logistics of container cargo for export and import. This study looks into the characteristics of intermodal transport using multi-modes, and presents a Weighted Constrained Shortest Path Problem (WCSPP) model. This study draws Pareto optimal solutions that can simultaneously meet two objective functions by applying the Label Setting algorithm, a type of Dynamic Programming algorithms, after setting the feasible area. To improve the algorithm performance, pruning rules have also been presented. The algorithm is applied to real transport paths from Busan to Rotterdam, as well as to large-scale cases. This study quantitatively measures the savings in both transport cost and time by comparing single transport modes with intermodal transport paths. Last, this study applies a mathematical model and MADM model to the multiple Pareto optimal solutions to estimate the solutions. [ABSTRACT FROM AUTHOR]

Abstract: A large AC generator is an important component of the power system. Researches on the AC generator relaying for the next-generation ECMS and an efficient operation of protection control system are necessary. These require developments on detailed generator modeling and internal fault analysis, and prototyping for multifunctional IED device dedicated to next-generation production. In this paper, over-excitation relaying algorithm is one of the main protection elements which have an important role in DGPS(Digital Generator Protection System), was proposed. This paper first briefly introduces a principles of over-excitation and DFT-based gain compensation algorithm was adopted for the frequency measurement. Subsequently, protection scheme of over-excitation was presented. The 765[kV] modeling data of South Korea using EMTP-RV was used for simulations. The simulation result of over-excitation relaying are also provided. [Copyright &y& Elsevier]

River runoff predictions in ungauged basins are one of the major challenges in hydrology. In the past, the approach using a physical-based conceptual model was the main approach, but recently, a solution using a data-driven model has been evaluated as more appropriate through several studies. In this study, a new data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed. An advantage of recurrent neural networks is that they can learn long-term dependencies between inputs and outputs provided to the network. Decision tree-based algorithms, combined with recurrent neural networks, serve to reflect topographical information treated as constants and can identify the importance of input features. We tested the proposed approach using data from 25 watersheds publicly available on the Korean government's website. The potential of the proposed approach as a regional hydrologic model is evaluated in the view that one regional model predicts river runoff in various watersheds using the leave-one-out cross-validation regionalization setup. [ABSTRACT FROM AUTHOR]

By 2026, Korea is expected to surpass the UN's definition of an aged society and reach the level of a superaged society. With an aging population come increased disorders involving the spine. To prevent unnecessary spinal surgery and support scientific diagnosis of spinal disease and systematic prediction of treatment outcomes, we have been developing e-Spine, which is a computer simulation model of the human spine. In this paper, we present the Korean spine database and automatic surface mesh intersection algorithm to construct e-Spine. To date, the Korean spine database has collected spine data from 77 cadavers and 298 patients. The spine data consists of 2D images from CT, MRI, or X-ray, 3D shapes, geometry data, and property data. The volume and quality of the Korean spine database are now the world's highest ones. In addition, our triangular surface mesh intersection algorithm automatically remeshes the spine-implant intersection model to make it valid for finite element analysis (FEA).This makes it possible to run the FEA using the spine-implant mesh model without any manual effort. Our database and surface mesh intersection algorithm will offer great value and utility in the diagnosis, treatment, and rehabilitation of patients suffering from spinal diseases. [ABSTRACT FROM AUTHOR]

Global warming, one of the most serious aspects of climate change, can be expected to cause rising sea levels. These have in turn been linked to unprecedentedly large typhoons that can cause flooding of low-lying land, coastal invasion, seawater flows into rivers and groundwater, rising river levels, and aberrant tides. To prevent typhoon-related loss of life and property damage, it is crucial to accurately estimate storm-surge risk. This study therefore develops a statistical model for estimating such surges' probability based on surge data pertaining to Typhoon Maemi, which struck South Korea in 2003. Specifically, estimation of non-exceedance probability models of the typhoon-related storm surge was achieved via clustered separated peaks-over-threshold simulation, while various distribution models were fitted to the empirical data for investigating the risk of storm surges reaching particular heights. To explore the non-exceedance probability of extreme storm surges caused by typhoons, a threshold algorithm with clustering methodology was applied. To enhance the accuracy of such non-exceedance probability, the surge data were separated into three different components: predicted water level, observed water level, and surge. Sea-level data from when Typhoon Maemi struck were collected from a tidal-gauge station in the city of Busan, which is vulnerable to typhoon-related disasters due to its geographical characteristics. Fréchet, gamma, log-normal, generalized Pareto, and Weibull distributions were fitted to the empirical surge data, and the researchers compared each one's performance at explaining the non-exceedance probability. This established that Weibull distribution was better than any of the other distributions for modelling Typhoon Maemi's peak total water level. Although this research was limited to one city on the Korean Peninsula and one extreme weather event, its approach could be used to reliably estimate non-exceedance probabilities in other regions where tidal-gauge data are available. In practical terms, the findings of this study and future ones adopting its methodology will provide a useful reference for designers of coastal infrastructure. [ABSTRACT FROM AUTHOR]

Since every single test has some limitations for detecting toxigenic Clostridium difficile, multistep algorithms are recommended. This study aimed to compare the current, representative diagnostic algorithms for detecting toxigenic C. difficile, using VIDAS C. difficile toxin A&B (toxin ELFA), VIDAS C. difficile GDH (GDH ELFA, bioMérieux, Marcy-l’Etoile, France), and Xpert C. difficile (Cepheid, Sunnyvale, California, USA). In 271 consecutive stool samples, toxigenic culture, toxin ELFA, GDH ELFA, and Xpert C. difficile were performed. We simulated two algorithms: screening by GDH ELFA and confirmation by Xpert C. difficile (GDH + Xpert) and combined algorithm of GDH ELFA, toxin ELFA, and Xpert C. difficile (GDH + Toxin + Xpert). The performance of each assay and algorithm was assessed. The agreement of Xpert C. difficile and two algorithms (GDH + Xpert and GDH+ Toxin + Xpert) with toxigenic culture were strong (Kappa, 0.848, 0.857, and 0.868, respectively). The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of algorithms (GDH + Xpert and GDH + Toxin + Xpert) were 96.7%, 95.8%, 85.0%, 98.1%, and 94.5%, 95.8%, 82.3%, 98.5%, respectively. There were no significant differences between Xpert C. difficile and two algorithms in sensitivity, specificity, PPV and NPV. The performances of both algorithms for detecting toxigenic C. difficile were comparable to that of Xpert C. difficile. Either algorithm would be useful in clinical laboratories and can be optimized in the diagnostic workflow of C. difficile depending on costs, test volume, and clinical needs. [ABSTRACT FROM AUTHOR]

Polarimetric measurements are sensitive to the sizes, concentrations, orientations, and shapes of raindrops. Thus, rainfall rates calculated from polarimetric radar are influenced by the raindrop shapes and canting. The mean raindrop shape can be obtained from long-term raindrop size distribution (DSD) observations, and the shapes of raindrops can play an important role in polarimetric rainfall algorithms based on differential reflectivity (ZDR) and specific differential phase (KDP). However, the mean raindrop shape is associated with the variation of the DSD, which can change depending on precipitation types and climatic regimes. Furthermore, these relationships have not been studied extensively on the Korean Peninsula. In this study, we present a method to find optimal polarimetric rainfall algorithms for the Korean Peninsula by using data provided by both a twodimensional video disdrometer (2DVD) and the Bislsan Sband dual-polarization radar. First, a new axis-ratio relation was developed to improve radar rainfall estimations. Second, polarimetric rainfall algorithms were derived by using different axis-ratio relations. The rain gauge data were used to represent the ground truth situation, and the estimated radar-point hourly mean rain rates obtained from the different polarimetric rainfall algorithms were compared with the hourly rain rates measured by a rain gauge. The daily calibration biases of horizontal reflectivity (ZH) and differential reflectivity (ZDR) were calculated by comparing ZH and ZDR radar measurements with the same parameters simulated by the 2DVD. Overall, the derived new axis ratio was similar to the existing axis ratio except for both small particles (≼2 mm) and large particles (≽5.5 mm). The shapes of raindrops obtained by the new axis-ratio relation carried out with the 2DVD were more oblate than the shapes obtained by the existing relations. The combined polarimetric rainfall relations using ZDR and KDP were more efficient than the single-parameter rainfall relation for estimated 2DVD rainfall; however, the R(ZH, ZDR) algorithm showed the best performance for radar rainfall estimations, because the rainfall events used in the analysis consisted mainly of weak precipitation and KDP is relatively noisy at lower rain rates (≼10mmh-1). Some of the polarimetric rainfall algorithms can be further improved by new axis-ratio relations. [ABSTRACT FROM AUTHOR]

Backgroud Procurement of tumor tissue is mandatory for a mutation analysis in patients with non-small cell lung cancer. The purpose of this study was to evaluate the usefulness of bronchoscopic biopsy and endobronchial ultrasound-guided transbronchial needle aspiration ( EBUS-TBNA) biopsy for detecting epidermal growth factor receptor ( EGFR) and KRAS mutations in routine practice. Methods Tumor DNA was extracted from formalin-fixed paraffin-embedded tissues, and amplifications of exons 18-21 of EGFR and codons 12, 13 and 61 of KRAS were performed using polymerase chain reaction ( PCR). PCR products were subjected to direct sequencing in both directions. Results Of 211 consecutive specimens, 201 (95.3%) were available for EGFR mutation analysis, and 196 (92.9%) were adequate for KRAS mutation analysis. EGFR and KRAS mutations were detected in 14.9% and 5.4%, respectively. A median of 16 days was spent from biopsy to the final report for either EGFR or KRAS mutation status. The detection rates for both mutations were similar between bronchoscopic biopsy and EBUS-TBNA (P > 0.05). Female gender (53.3%), never smoker (63.3%), and adenocarcinoma (96.7%) were predominant in patients with EGFR mutations. Among patients with adenocarcinoma (n = 104), the frequencies of EGFR and KRAS mutations were 27.9% and 10.6%, respectively. Conclusions Small tissue samples obtained by bronchoscopic biopsy and EBUS-TBNA are sufficient for detecting EGFR and KRAS mutations in routine practice. Therefore, concurrent mutational analyses of small tissue samples should be considered at the time of initial diagnosis. [ABSTRACT FROM AUTHOR]

We evaluated the precision of land surface temperature (LST) operationally retrieved from the Korean multipurpose geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS). The split-window (SW)-type retrieval algorithm was developed through radiative transfer model simulations under various atmospheric profiles, satellite zenith angles, surface emissivity values and surface lapse rate conditions using Moderate Resolution Atmospheric Transmission version 4 (MODTRAN4). The estimation capabilities of the COMS SW (CSW) LST algorithm were evaluated for various impacting factors, and the retrieval accuracy of COMS LST data was evaluated with collocated Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The surface emissivity values for two SW channels were generated using a vegetation cover method. The CSW algorithm estimated the LST distribution reasonably well (averaged bias = 0.00 K, Root Mean Square Error (RMSE) = 1.41 K, correlation coefficient = 0.99); however, the estimation capabilities of the CSW algorithm were significantly impacted by large brightness temperature differences and surface lapse rates. The CSW algorithm reproduced spatiotemporal variations of LST comparing well to MODIS LST data, irrespective of what month or time of day the data were collected from. The one-year evaluation results with MODIS LST data showed that the annual mean bias, RMSE and correlation coefficient for the CSW algorithm were -1.009 K, 2.613 K and 0.988, respectively. [ABSTRACT FROM AUTHOR]

The portfolio management for trading in the stock market poses a challenging stochastic control problem of significant commercial interests to finance industry. To date, many researchers have proposed various methods to build an intelligent portfolio management system that can recommend financial decisions for daily stock trading. Many promising results have been reported from the supervised learning community on the possibility of building a profitable trading system. More recently, several studies have shown that even the problem of integrating stock price prediction results with trading strategies can be successfully addressed by applying reinforcement learning algorithms. Motivated by this, we present a new stock trading framework that attempts to further enhance the performance of reinforcement learning-based systems. The proposed approach incorporates multiple Q-learning agents, allowing them to effectively divide and conquer the stock trading problem by defining necessary roles for cooperatively carrying out stock pricing and selection decisions. Furthermore, in an attempt to address the complexity issue when considering a large amount of data to obtain long-term dependence among the stock prices, we present a representation scheme that can succinctly summarize the history of price changes. Experimental results on a Korean stock market show that the proposed trading framework outperforms those trained by other alternative approaches both in terms of profit and risk management. [ABSTRACT FROM AUTHOR]