• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1306-1325
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• 2019

As the world is moving towards digitization, data is generated from various sources at a faster rate. It is getting humungous and is termed as big data. The financial sector is one domain which needs to leverage the big data being generated to identify financial risks, fraudulent activities, and so on. The design of predictive models for such financial big data is imperative for maintaining the health of the country's economics. Financial data has many features such as transaction history, repayment data, purchase data, investment data, and so on. The main problem in predictive algorithm is finding the right subset of representative features from which the predictive model can be constructed for a particular task. This paper proposes a correlation-based method using submodular optimization for selecting the optimum number of features and thereby, reducing the dimensions of the data for faster and better prediction. The important proposition is that the optimal feature subset should contain features having high correlation with the class label, but should not correlate with each other in the subset. Experiments are conducted to understand the effect of the various subsets on different classification algorithms for loan data. The IBM Bluemix BigData platform is used for experimentation along with the Spark notebook. The results indicate that the proposed approach achieves considerable accuracy with optimal subsets in significantly less execution time. The algorithm is also compared with the existing feature selection and extraction algorithms.

• Economic and Environmental Geology
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• v.52 no.3
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• pp.243-250
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• 2019

The purpose of this study is to pro-actively respond to changes in government R&D policy and start to supplement the limitations of previous KIGAM R&D planning process. We looked out through the existing literature for a variety of R&D planning process, and analyzed the R&D planning process characteristics of each institution through the interview. As a result, we can be derived conclusions and implications from three sides, environmental analysis, demand excavation methods, R&D project configuration and selection method. In the case of environmental analysis and the overall need to enhance the skills and mega trend analysis by market trend analysis. And in the demand side, the institute need to establish challenging and specific R&D goals. In addition, in case of configuration and selection of R&D projects we derived several implications, such as convergence, SME support, resource analysis, selection of long-term project.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.209-211
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• 2022

YouTube, a video platform used by millions of people worldwide, provides a rapidly growing video service. This study aims to understand the characteristics and cultural differences of each country using the Kaggle dataset, one of the public datasets, and to show the usefulness of the public dataset. For this purpose, we analyze data from 11 countries, 15 categories, and about 1.1 million trending videos. This study adopts Python to obtain the number of videos by category for data analysis, the selection period of videos rapidly increasing in popularity, and the ratio of unique videos. In the future, based on machine learning, we plan to research to help diagnose individual videos and establish channel operation plans and strategies by predicting the selection possibility and selection period based on machine learning.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11c
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• pp.2355-2358
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• 2002

인터넷의 급격한 보급으로 음란외설 폭력정보와 같은 불건전 정보가 날로 증가하고 있으며 이러한 유해정보로 인해 청소년들에게 심각한 사회적인 문제를 초래하고 있다. 이에 따라, 본 논문에서는 기존의 보편화된 차단방식의 문제점을 해소하기 위해 등장한 인터넷 내용 등급제를 비교분석하고, 정보통신윤리위원회에서 제시한 등급기준을 토대로 PICS(Platform for Internet Content Selection) 기반의 선별 프로그램을 구현하고, 기존 차단 프로그램과 성능을 비교 평가하였다. 구현된 프로그램은 현재 실용화되는 기술과의 호환성을 유지하도록 시스템을 구성하였다.

• Journal of Arbitration Studies
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• v.30 no.1
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• pp.87-111
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• 2020

Smart contracts are implemented by blockchain technology, which stores the terms of the contracts of both parties on the blockchain. In the event of an international dispute over smart contracts and blockchains, no special solution has been proposed, such as the enactment of the International Unification Act. The blockchain platform which operates smart contracts is decentralized and operates through distributed nodes around the world without central servers, making it difficult to establish jurisdiction and governing laws. As an alternative to traditional dispute-solving methods, a new mediation model-smart arbitration-is being attempted. The arbitration process is likely to be a preferred means of resolving disputes over smart contracts in practice. There are many problems, such as the fairness of the arbitration center on the selection and judgment of arbitrators, the question of securing reliability, the question of the validity of the arbitration agreement, and how much the court can be involved in the case. Preparations at the national level, such as fostering blockchains and smart contract experts, and overhauling the legal system, are needed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2385-2390
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• 2009

Based on the detailed analysis of output characteristics of PV array and residential load usage pattern, a design method to calculate optimal battery capacity for stand-alone PV generation systems is proposed. And also, according to power flow Actual irradiation and temperature data are analyzed to compose a PV array simulator and also six representative home appliances are electrically modeled for load simulator, along with 24hours usage pattern. The surplus and insufficient power can be calculated from the proposed simulation platform, so that selection of an optimal battery capacity can be possible. The theoretical analysis and design process will be explained, along with informative simulation results.

• Genomics & Informatics
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• v.9 no.4
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• pp.189-193
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• 2011

Simple sequence repeats (SSRs) are ubiquitous short tandem duplications found within eukaryotic genomes. Their length variability and abundance throughout the genome has led them to be widely used as molecular markers for crop-breeding programs, facilitating the use of marker-assisted selection as well as estimation of genetic population structure. Here, we report a software application, "SSR-Primer Generator " for SSR discovery, SSR-primer design, and homology-based search of in silico amplicons from a DNA sequence dataset. On submission of multiple FASTA-format DNA sequences, those analyses are batch processed in a Java runtime environment (JRE) platform, in a pipeline, and the resulting data are visualized in HTML tabular format. This application will be a useful tool for reducing the time and costs associated with the development and application of SSR markers.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.95-101
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• 2020

In situations where mobile robots are operated either by autonomous systems or human operators, such as smart factories, priority-based teleoperation is crucial for the multiple operators with different priority to take over the right of the robot control without conflict. This paper proposes a priority-based teleoperation system for multiple operators to control the robots. This paper also introduces an efficient joystick-based robot control command generation algorithm for differential-drive mobile robots. The proposed system is implemented with ROS (Robot Operating System) and embedded control boards, and is applied to Pioneer 3AT mobile robot platform. The experimental results demonstrate the effectiveness of the proposed joystick control command algorithm and the priority-based control input selection.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.93-99
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• 1999

The service level of Metro stations is affected by the design criteria such as platform area, width and length of stairways, and the number of turnstile, etc. The Korean station design process utilizes peak-hour volume as design volume. Hourly volume, however, can not explicitly account for the variation of traffic and consequently the variation of the level of service within the one-hour time period. Movements in various areas inside of stations are simulated with a queueing network under various operating conditions. A discrete simulation tool called SIMUL8 was utilized. Based on the results, peak volume for 15 minutes period was recommended as a preferred base volume over the peak-hour volume for station design purpose to realistically account for user delays under. Simulation runs also confirmed that escalators have positive effects on passenger processing capacity and on securing stability of passenger flows in stations.

• Smart Structures and Systems
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• v.4 no.6
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• pp.711-726
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• 2008

A number of efforts had been sought to instrument bridges for the purpose of structural monitoring and assessment. The outcome of these efforts, as gauged by advances in the understanding of the definition of structural damage and their role in sensor selection as well as in the design of cost and data-effective monitoring systems, has itself been difficult to assess. The authors' experience with the design, calibration, and operation of a monitoring system for the Kishwaukee Bridge in Illinois has provided several lessons that bear upon these concerns. The systems have performed well in providing a continuous, low-cost monitoring platform for bridge engineers with immediate relevant information.