• Electronics and Telecommunications Trends
• /
• v.30 no.4
• /
• pp.1-11
• /
• 2015

Quantified Self란 개인의 일상활동에서 신체적 정신적 상태를 센싱 및 트래킹하여 이를 수치화함으로써 자신의 상태를 분석하고 삶의 질을 개선하기 위한 방법을 연구하여 실생활에 적용하는 활동을 의미한다. 이는 최근 헬스와 피트니스에 활용 가능한 개인 센서 및 웨어러블 기기의 급속한 보급과 다양한 개인 정보 트래킹 기기의 출현으로 개인의 일상경험을 모니터링하고, 생성되는 정보를 수집, 통합 분석을 통해 새로운 개인화 서비스를 제공하기 위한 기술개발 이슈로 주목받고 있다. Quantified Self 데이터는 초기의 수작업으로 트래킹하여 수집한 소량의 관리 가능한 데이터 세트에서 점차 대용량의 Quantified Self 빅데이터 세트로 크기가 증가하고 있으며, 개인정보의 통합분석을 위한 빅데이터 모델과 자동적인 셀프-트래킹 플랫폼으로서의 웨어러블 컴퓨터 기술과 응용의 기대치를 증가시키고 있다. 본고에서는 Quantified Self 정의와 기술 및 서비스 동향에 대해 살펴보고, 웨어러블 센싱 기반 트래킹 기기의 개발사례와 Quantified Self의 주요이슈와 미래전망에 대해 조망해 본다.

• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.1-18
• /
• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.25-41
• /
• 2014

Recently, the number of social media users has increased rapidly because of the prevalence of smart devices. As a result, the amount of real-time data has been increasing exponentially, which, in turn, is generating more interest in using such data to create added value. For instance, several attempts are being made to analyze the relevant search keywords that are frequently used on new portal sites and the words that are regularly mentioned on various social media in order to identify social issues. The technique of "topic analysis" is employed in order to identify topics and themes from a large amount of text documents. As one of the most prevalent applications of topic analysis, the technique of issue tracking investigates changes in the social issues that are identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has two limitations. First, when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. This creates practical limitations in the form of significant time and cost burdens. Therefore, this traditional approach is difficult to apply in most applications that need to perform an analysis on the additional period. Second, the issue is not only generated and terminated constantly, but also one issue can sometimes be distributed into several issues or multiple issues can be integrated into one single issue. In other words, each issue is characterized by a life cycle that consists of the stages of creation, transition (merging and segmentation), and termination. The existing issue tracking methods do not address the connection and effect relationship between these issues. The purpose of this study is to overcome the two limitations of the existing issue tracking method, one being the limitation regarding the analysis method and the other being the limitation involving the lack of consideration of the changeability of the issues. Let us assume that we perform multiple topic analysis for each multiple period. Then it is essential to map issues of different periods in order to trace trend of issues. However, it is not easy to discover connection between issues of different periods because the issues derived for each period mutually contain heterogeneity. In this study, to overcome these limitations without having to analyze the entire period's documents simultaneously, the analysis can be performed independently for each period. In addition, we performed issue mapping to link the identified issues of each period. An integrated approach on each details period was presented, and the issue flow of the entire integrated period was depicted in this study. Thus, as the entire process of the issue life cycle, including the stages of creation, transition (merging and segmentation), and extinction, is identified and examined systematically, the changeability of the issues was analyzed in this study. The proposed methodology is highly efficient in terms of time and cost, as it sufficiently considered the changeability of the issues. Further, the results of this study can be used to adapt the methodology to a practical situation. By applying the proposed methodology to actual Internet news, the potential practical applications of the proposed methodology are analyzed. Consequently, the proposed methodology was able to extend the period of the analysis and it could follow the course of progress of each issue's life cycle. Further, this methodology can facilitate a clearer understanding of complex social phenomena using topic analysis.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.99-110
• /
• 2009

Currently, there are many applications being developed based on sensor network technology. A tracking method for moving objects in sensor network is one of the main issue of this field. There is a little research on this issue, but most of the existing work has two problems. The first problem is a communication overhead for visiting sensor nodes many times to track a moving object. The second problem is an disability for dealing with many moving objects at a time. To resolve the problems, we, in this paper, propose a signature-based tracking method using efficient data aggregation for moving objects, called SigMO-TRK. For this, we first design a local routing hierarchy tree to aggregate moving objects' trajectories efficiently by using a space filtering technique. Secondly, we do the tracking of all trajectories of moving objects by using signature in a efficient way, our approach generates signatures to method. In addition, by extending the SigMO-TRK, we can retrieve the similar trajectories of moving objects for given a query. Finally, by using the TOSSIM simulator, we show that our signature-based tracking method outperforms the existing tracking method in terms of energy efficiency.

• Journal of Digital Convergence
• /
• v.18 no.6
• /
• pp.17-32
• /
• 2020

This study analyzes the regulatory issues of stakeholders, the firm, the government, and the individual, in the data industry using the principal-agent theory. While the importance of data driven economy is increasing rapidly, policy regulations and restrictions to use data impede the growth of data industry. We applied descriptive case analysis methodology using principal-agent theory. From our analysis, we found several meaningful results. First, key policy actors in data industry are data firms and the government among stakeholders. Second, two major concerns are that firms frequently invade personal privacy and the global companies obtain monopolistic power in data industry. This paper finally suggests policy and strategy in response to regulatory issues. The government should activate the domestic agent system for the supervision of global companies and increase data protection. Companies need to address discriminatory regulatory environments and expand legal data usage standards. Finally, individuals must embody an active behavior of consent.

• Journal of Information Technology Services
• /
• v.13 no.4
• /
• pp.275-287
• /
• 2014

Recently, the volume of unstructured text data generated by various social media has been increasing rapidly; consequently, the use of text mining to support decision-making has also been growing. In particular, academia and industry are paying significant attention to topic analysis in order to discover the main issues from a large volume of text documents. Topic analysis can be regarded as static analysis because it analyzes a snapshot of the distribution of various issues. In contrast, some recent studies have attempted to perform dynamic issue tracking, which analyzes and traces issue trends during a predefined period. However, most traditional issue tracking methods have a common limitation : when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. Additionally, traditional issue tracking methods do not concentrate on the transition of individuals' interests from certain issues to others, although the methods can illustrate macro-level issue trends. In this paper, we propose an individual interests tracking methodology to overcome the two limitations of traditional issue tracking methods. Our main goal is not to track macro-level issue trends but to analyze trends of individual interests flow. Further, our methodology has extensible characteristics because it analyzes only newly added documents when the period of analysis is extended. In this paper, we also analyze the results of applying our methodology to news articles and their access logs.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.1
• /
• pp.91-96
• /
• 2022

With the development of the cloud industry, various efforts are being made to improve resource efficiency and environmental continuity in software development and operation methods. However, in constructing a conventional structure of structural scheme, if the functionality is improved and added, it has a problem that the efficiency of full build arrangement is reduced for the changed source. In this paper, if a problem occurs in a solution service company, communication between the development department and the operation department can be facilitated and responded quickly, and the latest source updated during processing of the problem is the management system, provided is a system that can take advantage of CI tools and continuously integrate them. As communication through the proposed system is smooth, it is expected that unnecessary work can be reduced and the speed of development can be improved.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10b
• /
• pp.304-307
• /
• 2006

현재 센서네트워크 분야는 여러 방면에서 이슈가 되고 있다. 해양 센서네크워크는 지상에서의 전파를 사용할 수 없으므로 음향(Acoustic)파를 사용한다. 일정거리만큼만 음파가 도달하는 환경에서 원하는 노드를 찾아가는 최적화 문제는 NP complete한 TSP 문제이다. 최적경로를 찾았을 경우 음파의 에너지 손실 또한 저전력으로 사용된다. 본 논문에서는 최적탐색기법인 유전자알고리즘을 사용하여 목적노드를 찾기위한 최적경로를 시뮬레이션 해 보았다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2018.07a
• /
• pp.437-438
• /
• 2018

최근 ICT산업의 주요 이슈인 가상현실(Virtual Reality, VR)은 다수의 IT기업들이 투자를 아끼지 않고 있다. 본 논문에서는 3D 디스플레이의 대표적인 HMD에 대한 장점인 몰입감, 공간감, 헤드트래킹에 대해 이해를 위해 HTC Vive을 이용해 Unreal Engine4 V4.19 게임엔진의 Level과 Gameinstance와 Actor에 대한 상호작용과 Timeline과 Random함수에 대한 이해를 기반으로 VR환경 FPS(First Person Shooter)게임 콘텐츠를 개발하였다.

• 한국IT서비스학회:학술대회논문집
• /
• 2006.11a
• /
• pp.517-522
• /
• 2006

본 논문은 RFID를 활용하여 자동차 제조 분야의 Traceability 구축 사례를 연구한 것이다. 전통적인 자동차 제조 환경 분석을 통하여 자동차 제조 분야의 Traceability 구축의 필요성과 RFID 기술의 적용 가능성을 분석하였다. RFID 기술을 활용한 통한 Traceability 구축을 위한 제조 및 공급망 관련 프로세스의 변경 내용 및 효과에 대하여 분석하였다. 실제 사례 기업은 Traceability 구축을 통하여 기존의 일 단위 결산 재고방식에서 실시간 재고방식으로 전환할 수 있게 되었으며, 상주원의 재고량 판단으로 부품 공급 시기와 양을 결정했던 방식에서 실시간 정보전달로 입고와 불출량 결정할 수 있게 되어 사내부품고의 최소 최적화가 가능하게 되었으며, 납입지시 신뢰도 향상 및 정보이용범위 확대(트래킹, 품질정보 등)를 통한 오보충 및 재고 진부화 방지 효과를 얻고 있다. 본 논문은 사례 기업의 Traceability 구축 과정에서 프로세스 변경, 관리 내용의 변경, RFID 기술의 적용 부분, 협력사와의 협업 등에 관련된 주요 이슈에 대하여 분석하여 향후 관련 분야의 Traceability 구축시 고려 요소 및 시사점을 제시하였다.