• Journal of Korea Spatial Information System Society
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• v.5 no.2 s.10
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• pp.91-103
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• 2003

There are currently tremendous amount of geotechnical information saved, which has been qcquired for essential application of site selection, plan, design, constructin, repari in the builing work. However, due to the lack of the location data attribute, there has been a trouble in its analysis and GIS implementation. In this study, the geotechnical information aquisition program(PGeo) for real-time database in the field and geotechnical information reporting program(GeoReport) by Web-GIS for additional data input and its reporting function has been developed.

• Journal of the Korea Computer Graphics Society
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• v.19 no.1
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• pp.1-9
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• 2013

Color plays a fundamental and important role in various areas, it has become important to choose colors which fits the purpose and also harmonious. The goal of this study is to reduce the difficulties of choosing the color and get the colors with high satisfaction when users want to choose multiple colors. To do this, we extracted and analysed a large number of colors in color database. And We designed an interface applied to high preference color combination rule. We also evaluated the usability and user satisfaction of the interface. The results showed that the functionality of the developed interface is more useful and is more satisfied than that of the conventional interface.

• Journal of the Korean Society for Railway
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• v.7 no.1
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• pp.20-25
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• 2004

Railroad geotechnical information management system was developed by using Web GIS and DB in this study. The standardization of railroad geotechnical information is progressed by classifying three groups as like basic informations, vibration informations along railway lines and design drawings. The basic informations consisted of basic and dynamic properties of soils, geophysical exploration and seismic survey/exploration. And the specification for 'human exposure to whole-body vibration' was adopted to construct the vibration informations along railway lines. The informations as like drawings and photographs were saved by changing to graphic files in the standardization of design drawings. In the case of standardization of geographical information, the topographical maps(NGIS, 1:5000) were primarily used as digital maps. Another digital maps(KRRI, 1:5000) and their geographical DB based on NGI code system were added on this maps. The standardized informations were used to construct their database. And railroad information management system was developed using Entity-Relation(ER) model which had a good feasibility for expansion and transition to other system in designing stage of database. This system consisted of layer selection, search and analysis of geotechnical informations and Zeus DB was adopted for GIS operating and user interface. This system could be a good tool for saving, searching and analyzing the geotechnical and geophysical informations. These DB systems would offered the basic informations to plans, design and construction of railroad lines etc. in practical use.

• Journal of Information Science Theory and Practice
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• v.7 no.2
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• pp.23-31
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• 2019

We report results of selection-bias-free approaches to the analysis of the impact of open access (OA) models on citation metrics. We studied reference groups of Gold and Green OA articles and the group of non-OA (Paywall) articles with the new functionality of the Web of Science Core Collection database, the InCites platform of Clarivate Analytics, and the Dimensions database of Digital Science. For each reference group we obtained the values of the percent of cited articles and citation impact and their dependence on the depth of the citation period. Different research fields were analyzed in two schemas of the InCites platform. We report the higher values and growth rates of the citation metrics: citation impact and %Cited, in the OA reference groups over the Paywall group. The Green OA articles demonstrate the highest values of citation metrics among all the OA models. Dependence of the value of citation impact on citation period follows linear law with R2 values close to 0.9-1.0. The overall annual growth rates of citation impact of the Green OA, Gold OA, and the Paywall articles, k equal, respectively, 3.6, 2.4, and 1.4 in Dimensions and 4.6, 3.6, and 2.3 in the Web of Science Core Collection. We suppose that earlier results reported for the articles in pure OA journals vs. articles in Paywall journals were affected by the high citation impact of the Green and Hybrid OA articles that could not be elucidated in the Paywall journals at that time.

• Steel and Composite Structures
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• v.39 no.4
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• pp.471-491
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• 2021

In this study, we estimate the ultimate load of rectangular concrete-filled steel tubes (CFST) by developing a novel hybrid predictive model (ANN-BCMO) which is a combination of balancing composite motion optimization (BCMO) - a very new optimization technique and artificial neural network (ANN). For this aim, an experimental database consisting of 422 datasets is used for the development and validation of the ANN-BCMO model. Variables in the database are related with the geometrical characteristics of the structural members, and the mechanical properties of the constituent materials (steel and concrete). Validation of the hybrid ANN-BCMO model is carried out by applying standard statistical criteria such as root mean square error (RMSE), coefficient of determination (R²), and mean absolute error (MAE). In addition, the selection of appropriate values for parameters of the hybrid ANN-BCMO is conducted and its robustness is evaluated and compared with the conventional ANN techniques. The results reveal that the new hybrid ANN-BCMO model is a promising tool for prediction of the ultimate load of rectangular CFST, and prove the effective role of BCMO as a powerful algorithm in optimizing and improving the capability of the ANN predictor.

• ETRI Journal
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• v.44 no.3
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• pp.462-475
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• 2022

Although researchers have proposed numerous techniques for speech emotion recognition, its performance remains unsatisfactory in many application scenarios. In this study, we propose a speech emotion recognition model based on a genetic algorithm (GA)-decision tree (DT) fusion of deep and acoustic features. To more comprehensively express speech emotional information, first, frame-level deep and acoustic features are extracted from a speech signal. Next, five kinds of statistic variables of these features are calculated to obtain utterance-level features. The Fisher feature selection criterion is employed to select high-performance features, removing redundant information. In the feature fusion stage, the GA is is used to adaptively search for the best feature fusion weight. Finally, using the fused feature, the proposed speech emotion recognition model based on a DT support vector machine model is realized. Experimental results on the Berlin speech emotion database and the Chinese emotion speech database indicate that the proposed model outperforms an average weight fusion method.

• Journal of Institute of Convergence Technology
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• v.11 no.1
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• pp.33-37
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• 2021

The application of multicopters using a battery is limited by the short endurance due to the low energy density. A propeller is one of crucial components that determine the performance of the multicopter. In the present study, a systematic method for predicting the endurance of multicopters is described. Propeller performance database are constructed using the data from UIUC Propeller Data Site. Using the 'trendline' function of MS Excel software, the performance of the commercial propellers are represented as a function of polynomials. The multicopter's endurance is computed iteratively using Peukert's Law and considering the voltage drop effect. We evaluated the endurance of multicopters that use commercial propellers. The endurance of the multicopter was within the range of 28 min. to 36 min. It is expected that the present method can be utilized for optimal propeller selection for the given multicopters.

• The Journal of Engineering Geology
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• v.33 no.2
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• pp.323-334
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• 2023

The vast volumes of data that are generated during site characterization and associated research for the disposal of high-level radioactive waste require effective data management to properly chronicle and archive this information. The Swedish Nuclear Fuel and Waste Management Company, SKB, established the SICADA database for site selection, evaluation, analysis, and modeling. The German Federal Company for Radioactive Waste Disposal, BGE, established ArbeitsDB, a database and document management system, and the ELO data system to manage data collected according to the Repository Site Selection Act. The U.K. Nuclear Waste Services established the Data Management System to manage any research and survey data pertaining to nuclear waste storage and disposal. The U.S. Department of Energy and Office of Civilian Radioactive Waste Management established the Technical Data Management System for data management and subsequent licensing procedures during site characterization surveys. The presented cases undertaken by these national agencies highlight the importance of data quality management and the scalability of data utilization to ensure effective data management. Korea should also pursue the establishment of both a data management concept for radioactive waste disposal that considers data quality management and scalability from a long-term perspective and an associated data management system.

• Genomics & Informatics
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• v.4 no.1
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• pp.45-47
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• 2006

D2GSNP is a web-based server for the selection of single nucleotide polymorph isms (SNPs) within genes related to human diseases. The D2GSNP is based on a relational database created by downloading and parsing OMIM, GAD, and dbSNP, and merging it with positional information of UCSC Golden Path. Totally our server provides 5,142 and 1,932 non-redundant disease genes from OMIM and GAD, respectively. With the D2GSNP web interface, users can select SNPs within genes responding to certain diseases and get their flanking sequences for further genotyping experiments such as association studies.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.157-172
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• 2013

There are many recommendation systems available to provide users with personalized services. Among them, the most frequently used in electronic commerce is 'collaborative filtering', which is a technique that provides a process of filtering customer information for the preparation of profiles and making recommendations of products that are expected to be preferred by other users, based on such information profiles. Collaborative filtering systems, however, have in their nature both technical issues such as sparsity, scalability, and transparency, as well as security issues in the collection of the information that becomes the basis for preparation of the profiles. In this paper, we suggest a movie recommendation system, based on the selection of optimal personal propensity variables and the utilization of a secure collaborating filtering system, in order to provide a solution to such sparsity and scalability issues. At the same time, we adopt 'push attack' principles to deal with the security vulnerability of collaborative filtering systems. Furthermore, we assess the system's applicability by using the open database MovieLens, and present a personal propensity framework for improvement in the performance of recommender systems. We successfully come up with a movie recommendation system through the selection of optimal personalization factors and the embodiment of a safe collaborative filtering system.