• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.5
• /
• pp.253-263
• /
• 2021

Traffic data collected using advanced equipment are highly valuable for traffic planning and efficient road operation. However, there is a problem regarding the reliability of the analysis results due to equipment defects, errors in the data aggregation process, and missing data. Unlike other detectors installed for each vehicle lane, radar detectors can yield different error types because they detect all traffic volume in multilane two-way roads via a single installation external to the roadway. For the traffic data of a radar detector to be representative of reliable data, the error factors of the radar detector must be analyzed. This study presents a field survey of variables that may cause errors in traffic volume collection by targeting the points where radar detectors are installed. Video traffic data are used to determine the errors in traffic measured by a radar detector. This study establishes three types of radar detector traffic errors, i.e., artificial, mechanical, and complex errors. Among these types, it is difficult to determine the cause of the errors due to several complex factors. To solve this problem, this study developed a radar detector traffic volume error analysis model using a multiple linear regression model. The results indicate that the characteristics of the detector, road facilities, geometry, and other traffic environment factors affect errors in traffic volume detection.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.5
• /
• pp.12-19
• /
• 2016

An average of 20 million individual transit unit activities per day on the Seoul-Gyeonggi-Incheon public transportation network are provided as transportation card analysis data by the metropolitan district (99.02% by 2014 standard, Humanlive, 2015.4). The metropolitan transportation card data can be employed in a comprehensive analysis of public transportation users' current transit patterns and by means of this, an effective use plan can be explored. In enhancing the existing information on the bus and rail integrated network of the metropolis with public transportation card data, the constraints in the existing methodology of metropolitan transit analysis, which functions on a zone unit origin and destination basis, can be overcome. Framework for metropolitan public transportation card data based integrated public transportation analysis, which consists of bus and rail integrated transport modes, is constructed, and through this, a single passenger's transit behavior transit volume can be approximated. This research proposes that in the use of metropolitan public transportation card data, integrated public transportation usage, as a part of individual passenger spatial movements, can be analyzed. Furthermore, metropolitan public transportation card usage data can provide insights into understanding not only movements of populations taking on transit activities, but also, characteristics of metropolitan local space.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.25 no.6
• /
• pp.1399-1410
• /
• 2015

Gartner is requiring companies to considerably change their survival paradigms insisting that companies need to understand and provide again the upcoming era of data competition. With the revealing of successful business cases through statistic algorithm-based predictive analytics, also, the conversion into preemptive countermeasure through predictive analysis from follow-up action through data analysis in the past is becoming a necessity of leading enterprises. This trend is influencing security analysis and log analysis and in reality, the cases regarding the application of the big data analysis framework to large-scale log analysis and intelligent and long-term security analysis are being reported file by file. But all the functions and techniques required for a big data log analysis system cannot be accommodated in a Hadoop-based big data platform, so independent platform-based big data log analysis products are still being provided to the market. This paper aims to suggest a framework, which is equipped with a real-time and non-real-time predictive analysis engine for these independent big data log analysis systems and can cope with cyber attack preemptively.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 1999.10a
• /
• pp.303-311
• /
• 1999

The amount of financial information in today's sophisticated large data bases is huge and makes comparisons between company performance difficult or at least very time consuming. The purpose of this paper is to investigate whether neural networks in the form of self-organizing maps can be used to manage the complexity in large data bases. This paper structures and analyzes accounting numbers in a large data base over several time periods. By using self-organizing maps, we overcome the problems associated with finding the appropriate underlying distribution and the functional form of the underlying data in the structuring task that is often encountered, for example, when using cluster analysis. The method chosen also offers a way of visualizing the results. The data base in this study consists of annual reports of more than 80 Korean companies with data from the year 1998.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.3
• /
• pp.254-259
• /
• 2015

In this paper, The wireless robot control system was proposed using Brain-computer interface(BCI) systems based on the steady-state visual evoked potential(SSVEP). Cross Power Spectral Density(CPSD) was used for analysis of electroencephalogram(EEG) and extraction of feature data. And Linear Discriminant Analysis(LDA) and Support Vector Machine(SVM) was used for patterns classification. We obtained the average classification rates of about 70% of each subject. Robot control was implemented using the results of classification of EEG and commanded using bluetooth communication for robot moving.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.4
• /
• pp.73-83
• /
• 2009

Recently, various studies regarding introduction of RFID have been implemented in many industries including logistics field. The objective of this study are (i) to analyze an economical effect due to the introduction of RFID on ULS(Unit Load System) Pallet, (ii) to develop a model to estimate cost of RFID introduction, and (iii) to establish a foundation for activating introduction of RFID to the logistics field in order to increase efficiency. This study utilized data regarding fifty logistics companies' awareness of RFID usage. The result of the economical analysis showed B/C of 2.766 and NPV of 2.6 billion won, which implies significant benefit to the logistics industry. This study is meaningful in that it is the first study to quantitatively estimate the effect of RFID introduction on ULS pallet in Korea.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.9 no.2
• /
• pp.41-54
• /
• 2013

In this paper, We collected location based services of the user's past moving paths through the GPS. Using the collected by location-based services through the analysis of the similarity between the user's of service level agreement recommended of mobile contact area(SLA) proposed that can be. S-RCA method based on Service Level Agreement of the users in order to provide the service user's path distance, time, and to predict the direction of the movement paths and collect. The data collected by the interests and requirements of users through classification with the same interests and the needs of users to move between the analysis of the similarity between the path is used to analyze the results of analysis of the path-specific tolerance range (distance, time, and space) is determined according to the difference in the contact area. From a small area of the error range for users first to recommended and through their smartphones recommended contact area (S-RCA) to meet with the other party to make a choice of recommended methods. We verify through experiments that proposed method(S-RCA) a valid and reliable mobile contact area were recommended.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.13 no.4
• /
• pp.315-323
• /
• 2013

Vessel Traffic Service (VTS) is being used at ports and in coastal areas of the world for preventing accidents and improving efficiency of the vessels at sea on the basis of "IMO RESOLUTION A.857 (20) on Guidelines for Vessel Traffic Services". Currently, VTS plays an important role in the prevention of maritime accidents, as ships are required to participate in the system. Ships are diversified and traffic situations in ports and coastal areas have become more complicated than before. The role of VTS operator (VTSO) has been enlarged because of these reasons, and VTSO is required to be clearly aware of maritime situations and take decisions in emergency situations. In this paper, we propose a prediction table to improve the work of VTSO through the Cognitive Work Analysis (CWA), which analyzes the VTS work very systematically. The required data were collected through interviews and observations of 14 VTSOs. The prediction tool supports decision-making in terms of a proactive measure for the prevention of maritime accidents.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.2
• /
• pp.172-178
• /
• 2006

This paper presents a development of court auction information system using time series forecasting. The system forecast a highest bid price for claim analysis, and it is designed to offer an quota information by the bid price. For this realization, we implemented input interface of object data and web interface of information support. Input interface can be input, update and delete function and web interface is support some information of court auction object. We propose a forecasting method of a highest bid price for auto-claim analysis with real time information support and the results are verified the feasibility of the proposed method by experiment.

• Informatization Policy
• /
• v.26 no.2
• /
• pp.81-95
• /
• 2019

This study explores how the advanced data analysis capabilities of intelligent information technology are being utilized in politics. In particular, we focus on the fact that voter behavioral targeting in election campaigns comes into conflict with the democratic process in various ways. For this purpose, this study examines political micro-targeting and political bots. It is aimed at showing that these technology-based campaign techniques work as a factor preventing free expression of opinions and discussions, which are the core of democracy itself. Then we identify the attributes of the algorithm that affects them. As a result, this study suggests that the following issues might arise regarding intelligent information technology-based politics and democracy. First, inequality in political participation becomes more severe. Second, the public debate between voters gets more difficult. Third, superficial politics is prevalent. Fourth, single-issue politics and the exclusion of political representation is likely to increase. Fifth, political privacy might also be invaded. Based on our discussions, this study concludes that it is our role to find ways by which intelligent information technology and democracy can coexist.