• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.11-14
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• 2008

웹 2.0 환경에서 인터넷 사용자가 생성하는 정보는 폭발적인 규모로 증가하고 있다. 또한 UCC 등의 사용자 참여 서비스 및 VOD, IPTV 등의 대용량 서비스가 본격화 되고 있다. 그러나 이러한 데이타 전송량 증가 속도를 네트워크 전송 설비의 증설이 따라가지 못하고 있는 실정이다. 이를 극복하기 위해 P2P 기술을 이용하고 있지만 대부분의 P2P 기술들은 실제 물리적인 네트워크 상태를 고려하지 않고 응용 계층만을 고려하기 때문에 데이타 전송의 비효율이 발생하게 된다. 게다가 이러한 비효율을 해결하기 위한 방안들은 분산형 Pure P2P 시스템이나 구조적 P2P 시스템에 대한 연구가 대부분이고 비구조적 중앙 집중형에 대한 연구는 없는 실정이다. 본 논문에서는 물리적인 네트워크 정보와 그래프 클러스터링 기법을 적용한 계층적 클러스터링 방법을 이용하여 실제 기업에서 운영하는 중앙 집중형 P2P 시스템에서 성능을 향상 시킬 수 있는 기법을 제안한다. 그리고 이를 통해 기존의 기법들이 가지고 있는 과도한 메시지 교환, 고정된 랜드마크의 유지 등의 문제점을 보완하여 대규모 데이타의 효율적인 전송을 가능케 하는 실제적인 P2P 환경에 적합한 오버레이 네트워크 모듈을 구현하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.475-478
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• 2019

웹어플리케이션의 발전에 따라 자바스크립트 런타임 플랫폼인 Node.js 의 사용도 증가하고 있다. 개발자들은 Node.js 의 다양한 모듈을 활용하여 프로그래밍을 하게 되는데, Node.js 모듈 보안의 중요성에 비하여 모듈 취약점 분석은 충분히 이루어지지 않고 있다. 본 논문에서는 소스코드의 구조를 트리 형태로 표현하는 Abstract Syntax Tree 와 소스코드의 실행 흐름 및 변수의 흐름을 그래프로 나타내는 Control Flow Graph/Data Flow Graph 가 Node.js 모듈 취약점 분석에 효율적으로 활용될 수 있음을 서술하고자 한다. Node.js 모듈은 여러 스크립트 파일로 나누어져 있다는 점과 사용자의 입력이 분명하다는 특징이 있다. 또한 자바스크립트 언어를 사용하므로 선언된 변수들의 타입에 따라 적용되는 범위인 scope 가 다르게 적용된다는 특징이 있다. 본 논문에서는 이러한 Node.js 모듈의 특징을 고려하여 Abstract Syntax Tree 및 Control Flow Graph/Data Flow Graph 을 어떻게 생성하고 취약점 분석에 활용할 것인지에 대한 방법론을 제안하고, 실제 분석에 활용할 수 있는 코드 구현을 통하여 구체화시키고자 한다.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.636-641
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• 2018

In recent years, the Internet of things has grown rapidly and is being used in many fields. The function of an Internet device isto collect information in various environments and to provide useful information to users. Due to recent developments in technology, the kinds of Internet devices are increasing and the prices are getting cheaper. In addition, many open source platforms that are easy to use have been developed and are providing convenience to users. In this paper, wireless data transmission and cloud server system based on ESP-12E NodeMCU module was designed and sensor information collected from Internet devices was transmitted to cloud server through WiFi wireless communication. The collected sensor data was saved by creating channel and field in the cloud server and the data of each field was visualized as a graph.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.826-829
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• 2020

스포츠팀 운영에 있어서 경기 중 상황에 대한 통계와 분석을 통해 좋은 성과를 내는 것은 스포츠 야구 종목의 Sabermetrics를 통해 이미 증명된 바가 있다. 한편, 축구에서는 최근 들어 선수의 역량을 평가하기 위하여 객관적인 시각에서 슈터(Shooter)에게 주어진 기회, 즉 슈팅 상황을 바라보는 기대 득점(Expected Goal; 이하 xG)이라는 지표가 등장하였으나, 객관성이라는 평가 의도와 다르게 경기 내 각각의 슈팅 상황을 정의하는 것에 있어 축구 분석관들의 주관성에 의존하는 한계성을 지녔다. 본 논문은 xG를 산출하는 방식에 있어서 기존의 주관성을 배제하고 인공지능을 통해 상황을 정의하여 객관적인 평가지표를 지향하며 유의미한 통계적 수치를 지닌 xG를 도출함으로써 결과 위주의 분석만이 존재하던 축구 종목에 있어서 경기 중 상황에 대한 객관적인 판단 및 정의에 대한 방향성을 제시한다. 또한, 본 논문에서의 인공지능은 국내 K리그 슈팅 데이터를 통해 학습되어 K리그 내 전략적인 상황들에 대한 특화된 xG를 도출하며, 이를 웹을 통해 K리그 내 선수 개개인에 대해서 시계열, 상대 팀, 슈팅 위치별 그래프로 시각화하여 제공하는 시스템을 구축함으로써 K리그를 기준으로 선수에 대한 평가 및 경기 운영에 기여할 수 있는 기대 득점 분석 서비스를 제공한다.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.87-102
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• 2009

With the growth of Web 2.0, lots of services allow yours to post their personal information and useful knowledges on networked information spaces such as blogs and online communities etc. As the services are generalized, recent researches related to social network have gained momentum. However, most social network services do not support machine-processable semantic knowledge, so that the information cannot be shared and reused between different domains. Moreover, as explicit definitions of relationships between individual social entities do not be described, it is difficult to analyze social network for inferring unknown semantic relationships. To overcome these limitations, in this paper, we propose a social network analysis system with personal photographic data up-loaded by virtual community users. By using ontology, an informative connectivity between a face entity extracted from photo data and a person entity which already have social relationships was defined clearly and semantic social links were inferred with domain rules. Then the inferred links were provided to yours as a visualized graph. Based on the graph, more efficient social network analysis was achieved in online community.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.55-64
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• 2017

In this paper, we propose and implement an IoT based mobile smart monitoring system in the view point of safety inspection for solar power generation. The main features and contributions of proposed system are as follows. First, the proposed system model can evaluate periodically in the view point of safety inspection the conditions of the system and structure of solar power generation. Second, the proposed system automatically re-processes the measurement data of the system and structure for solar power generation and save it into database. Third, using the re-processed and saved information, the proposed system can provide the monitoring information with webpage form to both administrator and owner of solar power generation system, thus they can measure and confirm directly in the view point of safety inspection the conditions of the solar generation structure without visiting those places. Fourth, the provided web pages for the monitoring of solar power generation can be accessed regardless of the system structures. The performance evaluations of the proposed system show that the proposed monitoring system can save efficiently the data received from the sensors installed in the structure of solar power generation into the data base in the collecting server. And the proposed system can support that both administrator and user of solar power generation system access webpage in real time without considering places by using mobile phone and desktop computer and obtain the information for the conditions of the system and structure of solar power generation with graph forms.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.151-160
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• 2016

The purpose of this research is to investigate Korean popular attitudes and social perceptions of 'sharing economy' terminology at the current moment from a creative or socio-economic point of view. In Korea, this study discovers and interprets the objective and tangible annual changes and patterns of sociocultural collective intelligence that have taken place over the last five years by applying text mining in the big data analysis approach. By crawling and Googling, this study collected a significant amount of time series web meta-data with regard to the theme of the sharing economy on the world wide web from 2010 to 2014. Consequently, huge amounts of raw data concerning sharing economy are processed into the value-added meaningful 'word clouding' form of graphs or figures by using the function of word clouding with R programming. Till now, the lack of accumulated data or collective intelligence about sharing economy notwithstanding, it is worth nothing that this study carried out preliminary research on conducting a time-series big data analysis from the perspective of knowledge management and processing. Thus, the results of this study can be utilized as fundamental data to help understand the academic and industrial aspects of future sharing economy-related markets or consumer behavior.

• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.327-336
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• 2017

People spend most of their time in the indoor environment. Among the various indoor environmental factors, air and thermal environment directly affect human's health and efficiency of work. Therefore, efficient monitoring of indoor environment is highly important. For assisting the residents to understand the state of the indoor environment much easier and more intuitive, this paper analyze the visualization cases of the conventional indoor environment. Then explore the direction of improvement for the visualization method to propose a more effective visualization method. The approach of web and BIM(Building Information Model)-based visualization of indoor environment proposed in this study is composed of four major parts: 1) the generation of the model data of the building; 2) the generation of indoor environmental data; 3) the creation of visualization elements; 4) data mapping. Then it realized through the generating process of visualization results.

• 한국정보교육학회:학술대회논문집
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• 2011.01a
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• pp.91-101
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• 2011

The purpose of this paper is to quickly identify school parents, teachers, students, community needs and opinions for curriculum organizing and the implementation of an online survey system for operating educational activities. Online survey system should be implemented based on Limesurvey to reduce costs and administrative costs. Limesurvery is available without the development of the separate program and offers the form of web-based template system, complete design, layout. Also, Limesurvey offers basic statistical analysis of survey data. Limesurvey can be executed by installing the program on a web hosting, typing database information. Limesurvey can be made a graph of the statistical results. Besides, Limesurvery can be stored in the form of HTML, Word, Excel, CSV Files and can be stured as basic datas for SPSS or PASW, R data, other statistical processing programs. If we could be operate Limesurvey in the form of open source-based survey program in elementary school, we could be reduced teacher's unnecessary work for statistics and overcame the problem of offline survey system.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.83-96
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• 2018

Extracting keywords representing documents is very important because it can be used for automated services such as document search, classification, recommendation system as well as quickly transmitting document information. However, when extracting keywords based on the frequency of words appearing in a web site documents and graph algorithms based on the co-occurrence of words, the problem of containing various words that are not related to the topic potentially in the web page structure, There is a difficulty in extracting the semantic keyword due to the limit of the performance of the Korean tokenizer. In this paper, we propose a method to select candidate keywords based on semantic similarity, and solve the problem that semantic keyword can not be extracted and the accuracy of Korean tokenizer analysis is poor. Finally, we use the technique of extracting final semantic keywords through filtering process to remove inconsistent keywords. Experimental results through real web pages of small business show that the performance of the proposed method is improved by 34.52% over the statistical similarity based keyword selection technique. Therefore, it is confirmed that the performance of extracting keywords from documents is improved by considering semantic similarity between words and removing inconsistent keywords.