• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.177-186
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• 2015

The main objective of this study was to assess the applicability of IoT (Internet of Things)-based flood management under climate change by developing intelligent water level monitoring platform based on IoT. In this study, Arduino Uno was selected as the development board, which is an open-source electronic platform. Arduino Uno was designed to connect the ultrasonic sensor, temperature sensor, and data logger shield for implementing IoT. Arduino IDE (Integrated Development Environment) was selected as the Arduino software and used to develop the intelligent algorithm to measure and calibrate the real-time water level automatically. The intelligent water level monitoring platform consists of water level measurement, temperature calibration, data calibration, stage-discharge relationship, and data logger algorithms. Water level measurement and temperature calibration algorithm corrected the bias inherent in the ultrasonic sensor. Data calibration algorithm analyzed and corrected the outliers during the measurement process. The verification of the intelligent water level measurement algorithm was performed by comparing water levels using the tape and ultrasonic sensor, which was generated by measuring water levels at regular intervals up to the maximum level. The statistics of the slope of the regression line and $R^2$ were 1.00 and 0.99, respectively which were considered acceptable. The error was 0.0575 cm. The verification of data calibration algorithm was performed by analyzing water levels containing all error codes in a time series graph. The intelligent platform developed in this study may contribute to the public IoT service, which is applicable to intelligent flood management under climate change.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.1049-1057
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• 2017

In-vehicle multimedia systems are one of the most important factors in the automotive industry. Especially, multimedia systems are more important in advanced commercial vehicles such as premium express buses. In this paper, we proposed a multimedia streaming system architecture using MEP(MOST Ethernet Packets) for premium express buses based on MOST150. We have designed and implemented the prototype of proposed multimedia streaming system. We have designed a board based on i.MX6 to operate a proposed multimedia streaming system. The software has designed a multimedia system for premium express buses based on Android which is an open source platform. MOST(Media Oriented Systems Transport) is a high-speed multimedia network technology for in-vehicle multimedia system. The MOST network is able to manage up to 64 devices and ring topology is used basically. In addition, the MOST Network meets EMI(Electro-Magnetic Interference)/ EMC(Electro-Magnetic Compatibility) requirements because it uses plastic optical fibers(POF).

• Journal of Information Science Theory and Practice
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• v.3 no.2
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• pp.16-30
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• 2015

The term megajournal is used to describe publication platforms, like PLOS ONE, that claim to incorporate peer review processes and web technologies that allow fast review and publishing. These platforms also publish without the constraints of periodic issues and instead publish daily. We conducted a yearlong bibliometric profile of a sample of articles published in the first several months after the launch of PeerJ, a peer reviewed, open access publishing platform in the medical and biological sciences. The profile included a study of author characteristics, peer review characteristics, usage and social metrics, and a citation analysis. We found that about 43% of the articles are collaborated on by authors from different nations. Publication delay averaged 68 days, based on the median. Almost 74% of the articles were coauthored by males and females, but less than a third were first authored by females. Usage and social metrics tended to be high after publication but declined sharply over the course of a year. Citations increased as social metrics declined. Google Scholar and Scopus citation counts were highly correlated after the first year of data collection (Spearman rho = 0.86). An analysis of reference lists indicated that articles tended to include unique journal titles. The purpose of the study is not to generalize to other journals but to chart the origin of PeerJ in order to compare to future analyses of other megajournals, which may play increasingly substantial roles in science communication.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.670-686
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• 2017

MapReduce (MRV1), a popular programming model, proposed by Google, has been well used to process large datasets in Hadoop, an open source cloud platform. Its new version MapReduce 2.0 (MRV2) developed along with the emerging of Yarn has achieved obvious improvement over MRV1. However, MRV2 suffers from long finishing time on certain types of jobs. Speculative Execution (SE) has been presented as an approach to the problem above by backing up those delayed jobs from low-performance machines to higher ones. In this paper, an adaptive SE strategy (ASE) is presented in Hadoop-2.6.0. Experiment results have depicted that the ASE duplicates tasks according to real-time resources usage among work nodes in a cloud. In addition, the performance of MRV2 is largely improved using the ASE strategy on job execution time and resource consumption, whether in a multi-job environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.621-623
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• 2021

Open science policies are spreading that disclose, share, and utilize research results produced through government public funds. As a policy to revitalize open science, interest in research support services that allow easy search, access, and reuse of results is increasing. To support services to provide researchers with various information, we propose a research resource knowledge graph model to meaningfully express the relationship between the scattered various outcome data. In this paper, it contributes to the improvement of the service of the national research data platform DataON by meaningfully connecting national R&D task information, researcher information, performance information, and research data information.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.19-27
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• 2016

Advance in Information and Communication Technology (ICT) is intensely influenced to increase importance of Software on global ICT industries. The trend of technological development has been transformed from hardware-oriented environment to software-oriented environment. This industrial transformation brought novel trend to Software market. Open Source Software (OSS) has been widely distributed for private uses. At the same time, many governmental offices are planning to expand the use of OSS. In this paper, we analyze the strength and weaknesses of OSSs for both Web and WAS servers based on 4 types of testing environments which are created by the combination of 5 selected OSSs. We anticipated to learn the optimal system architecture design for the next generation of V-World through this research.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.437-456
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• 2021

In the field of remote sensing in Korea, starting in 2017, deep learning has begun to show efficient research results compared to existing research methods. Currently, research is being conducted to apply deep learning in almost all fields of remote sensing, from image preprocessing to applications. To analyze the research trend of deep learning applied to the remote sensing field, Korean domestic journal papers, published until October 2021, related to deep learning applied to the remote sensing field were collected. Based on the collected 60 papers, research trend analysis was performed while focusing on deep learning network purpose, remote sensing application field, and remote sensing image acquisition platform. In addition, open source data that can be effectively used to build training data for performing deep learning were summarized in the paper. Through this study, we presented the problems that need to be solved in order for deep learning to be established in the remote sensing field. Moreover, we intended to provide help in finding research directions for researchers to apply deep learning technology into the remote sensing field in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1048-1053
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• 2005

This paper presents design and integration of the ROBHAZ-DT3, which is a newly developed mobile robot system with chained double-track mechanisms. A passive adaptation mechanism equipped between the front and rear body enables the ROBHAZ-DT3 to have good adaptability to uneven terrains including stairs. The passive adaptation mechanism reduces energy consumption when moving on uneven terrain as well as its simplicity in design and remote control, since no actuator is necessary for adaptation. Based on this novel mobile platform, a rescue version of the ROBHAZ-DT3 with appropriate sensors and a semi-autonomous mapping and localization algorithm is developed to participate in the RoboCup2004 US-Open: Urban Search and Rescue Competition. From the various experiments in the realistic rescue arena, we can verify that the ROBHAZ-DT3 is reliable in traveling rugged terrain and the proposed mapping and localization algorithm are effective in the unstructured environment with uneven ground. The another application is an military robot for an EOD(Explosive Ordnance Disposal) and reconnaissance mission. The military version of the ROBHAZ-DT3 with a water disrupter, a thermal scope and a long distance wireless communication device is developed and sent to the area of military tactics in Iraq. Consequently, the feasibility of the military version of ROBHAZ-DT3 is verified.

• Korean Journal of Applied Biomechanics
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• v.20 no.2
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• pp.231-237
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• 2010

The moving trajectory of a golf ball is mainly determined by the angles of the clubface and the trajectory of the club shaft. This paper presents a computer program for analyzing the position and angles of the club while the club moves in a circular motion. For this purpose, a mathematical algorithm was developed and implemented on the experimental data(5 m and 10 m carries) using VC++ and OpenGL. A skilled female golfer(174 cm, 65 kg, 0 handicap) was participated in data collection for the short approach shots. An iron club(Titleist 52 degree, 91.5 cm length, 450 g mass), attached with five reflective markers(12 mm), was used to collect experimental data. However, exact 3D coordinates and angles of the clubface are not directly calculated from measured data. A reverse engineering platform(Minolta Vivid910 hardware and Rapidform software) was thus employed to acquire the scanned data of the clubface. The scanned data and measured data were first aligned by applying appropriate coordinate transformations, and then exact coordinates and angles of clubface could be obtained at each position during circular motion. The program(Club Motion Analysis 1.0) exports the open, heel, loft angles of the club.

• Journal of Distribution Science
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• v.16 no.7
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• pp.67-75
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• 2018

Purpose - In the 21st century, as information technology advances alongside the emergence of the 4th generation, industrial age, industrial environment has become individualized and customized. It is important to hire good quality employees for good service in the industry. The e-learning market is growing every year. Although e-learning companies are finding better quality employees in e-learning, it is not easy to find it. Companies also spend a lot of time and cost to find employee. On the employees side, they want to get a job freely when they want, but they cannot find their job easily. Furthermore, the labor market environment is changing fast. In the 4th generation, industrial age, employers require to find manpower whenever they need and want at little cost. So of their own accord, we have considered the necessity of management of human resources for employees and employers in e-learning. The purpose of this study is to propose a human cloud platform framework for enabling an efficient management of human resources in e-learning industry. Research design, data, and methodology - To pinpoint the items of a human cloud platform framework, the study was initiated according to the following process. First, items of competency relating to e-learning instructional designer was analyzed. Second, based on the items of information from this analysis, selection and validity verification took place with 5 e-learning specialists group. Third, the opinion of experts who were in charge of hiring in e-learning companies were collated with the questionnaire. Lastly, the human cloud platform framework was proposed based on opinion results. Results - The framework was comprised of 7 domains and 27 items in order to develop the human cloud platform for e-learning instructional designer. The analysis results showed that the most highly considered item were 'skill (4.60)' that employee already have the capability. Following this (in order) were 'project type (4.56)', 'work competency (4.56)', and 'strength area of instructional design (4.52)'. Conclusions - The 27 items in the human cloud platform framework were suggested in this study. Following this, we can consider to develop the human cloud platform for finding a job and hiring e-learning instructional designer easily. For successful platform operation, we need to consider reliability between employer and employee. In addition, we need quality assurance system based on operation has public confidence.