• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.111-121
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• 2007

A transit assignment model can forecast the behaviors of transit users. thereby playing an important role In the evaluation of transit policies. Most existing transit assignment models are based on the models for passenger cars; therefore they cannot reflect the specific characteristics of transit modes. In addition most of the existing models are based on a single transit mode (bus or rail), and they cannot forecast the behaviors of transit users in a changing mass transportation system. The goal of this study is to overcome these problems with the exiting models and to develop a more realistic model. The newly developed model is based on mixed transit modes and is a stochastic model that can reflect the different preferences of each transit user for travel time and transfering. Data gathered from the Seoul metropolitan area's smart card are used to calibrate this model. This study is expected to be used for the evaluation of transportation policies and to attribute the development of transit revitalization strategies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.1
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• pp.167-174
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• 2018

This study attempts to construct a model of optimal headway, focusing on a practical applicability to bus transit operation. Examining the existing bus operation and scheduling plans imposed by Busan City, we found that the plans failed to reasonably take into account such realities as varying traffic and operational conditions. The model is thus developed to derive the hourly optimal headway by routes satisfying the real-world conditions: varying hourly demand and cycle time, applying the model to routes 10 and 27 as examples. To do so, we collect big-dataset generated by smart card system and BIMS (Bus Inforamtion Management System). It is expected that the results of this study wil be a basis for further refined research in this field as well as for preparing practical timetables for bus operation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3836-3854
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• 2022

The student group division is benefit for universities to do the student management based on the group profile. With the widespread use of student smart cards on campus, especially where students living in campus residence halls, students' daily activities on campus are recorded with information such as smart card swiping time and location. Therefore, it is feasible to depict the students with the daily activity data and accordingly group students based on objective measuring from their campus behavior with some regular student attributions collected in the management system. However, it is challenge in feature representation due to diverse forms of the student data. To effectively and comprehensively represent students' behaviors for further student group division, we proposed to adopt activity data from student smart cards and student attributes as input data with taking account of activity and attribution relationship types from different perspective. Specially, we propose a novel student group division method based on a multi-view student attribute heterogeneous information network (MSA-HIN). The network nodes in our proposed MSA-HIN represent students with their multi-dimensional attribute information. Meanwhile, the edges are constructed to characterize student different relationships, such as co-major, co-occurrence, and co-borrowing books. Based on the MSA-HIN, embedded representations of students are learned and a deep graph cluster algorithm is applied to divide students into groups. Comparative experiments have been done on a real-life campus dataset collected from a university. The experimental results demonstrate that our method can effectively reveal the variability of student attributes and relationships and accordingly achieves the best clustering results for group division.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.159-166
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• 2013

Recently, because the interest and needs in privacy protection are growing, smartcard-based remote user authentication schemes have been actively studied to provide the user anonymity. In 2008, Kim et al. first proposed an authentication scheme in order to ensure the user anonymity against both external attackers and the remote server and track malicious users with the help of a trusted trace sever. However, in 2010, Lee et al. showed that Kim et al.'s scheme cannot provide the user anonymity against remote server, which is because the server can trace users without any help of the trace server, and then proposed a improved scheme. On the other hand, in 2010, Horng et al. proposed an authentication scheme with non-tamper resistant smart cards, in which the non-tamper resistant smart card means that an attacker may find out secret information stored in the smart card through special data analysis techniques such as monitoring power consumption, to be secure against a variety of attacks and to provide the user anonymity against external attackers. In this paper, we will propose a remote user authentication scheme with non-tamper resistant smart cards not only to ensure the user anonymity against both external attackers and the remote server but also to track malicious users with only the help of a trusted trace sever.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.873-882
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• 2017

Smart cards are currently used in about 150 locales, including the metropolitan ares, and are utilized as a policy base for various public areas, including public transportation, bus fares, and public transportation requirements. However, excluding the metropolitan area and some metropolitan areas, there are many areas where the existing BIS data was unable to match station information on the data and Smart cards itself are not available on the bus stop information by the line. The purpose of this research was to produce bus stop information generated by the bus stop based on the bus route, and the actual stop information generated by the model presented in the study was derived by matching the actual station information.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.2 s.40
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• pp.87-93
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• 2007

Over the years, Advanced Public Transportation System (APTS) has been implemented to manage and operate public transportation system. With the expanding mass spatio-temporal data such as comprehensive spatial information of each individual passenger and public transportation vehicle, it has been required to consolidate and analyze these multiple data sets from various sources. This paper demonstrates how GIS is utilized for the consolidation of massive transit related spatio-temporal information. And it presents effective applications to improve transit planning process and support transit related decision-making activities. GIS based system is used to combine multi-agents' data in the areas of transit operation and individual transit ride and transfer management. Due to the unique comprehensiveness and the level of detail of the data provide by the Seoul Transit system, this GIS based information consolidation is the first in its class. Based on the integrated database, this paper describes the effective and efficient GIS based analysis deployed in a transportation system planning process. The data integration systems and analytic models developed in this paper can be transferred and applied by any municipal governments provided that the appropriate data is available.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.102-108
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• 2019

Big data was associated with three key concepts, volume, variety, and velocity. Securities and investment services produce and store a large data of text/numbers. They have also the most data per company on the average in the US. Gartner found that the demand for big data in finance was 25%, which was the highest. Therefore securities and investment companies produce the largest data such as text/numbers, and have the highest demand. And insurance companies and credit card companies are using big data more actively than banking companies in Korea. Researches on the use of big data in securities and investment companies have been found to be insignificant. We surveyed 22 major securities and investment companies in Korea for activating big data. We can see they actively use AI for investment recommend. As for big data of securities and investment companies, we studied open API. Of the major 22 securities and investment companies, only six securities and investment companies are offering open APIs. The user OS is 100% Windows, and the language used is mainly VB, C#, MFC, and Excel provided by Windows. There is a difficulty in real-time analysis and decision making since developers cannot receive data directly using Hadoop, the big data platform. Development manuals are mainly provided on the Web, and only three companies provide as files. The development documentation for the file format is more convenient than web type. In order to activate big data in the securities and investment fields, we found that they should support Linux, and Java, Python, easy-to-view development manuals, videos such as YouTube.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.59-67
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• 2015

A novel authentication mechanism is biometric authentication where users are identified by their measurable human characteristics, such as fingerprint, voiceprint, and iris scan. The technology of biometrics is becoming a popular method for engineers to design a more secure user authentication scheme. In terms of physiological and behavioral human characteristics, biometrics is used as a form of identity access management and access control, and it services to identity individuals in groups that are under surveillance. In this article, we review the biometric-based authentication protocol by Althobati et al. and provide a security analysis on the scheme. Our analysis shows that Althobati et al.'s scheme does not guarantee server-to-user authentication. The contribution of the current work is to demonstrate this by mounting threat of data integrity and bypassing the gateway node on Althobati et al.'s scheme. In addition, we analysis the security vulnerabilities of Althobati et al.'s protocol.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.12-28
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• 2017

The core of the transportation service, so-called Mobility 4.0 is the flexibility of the entire mobility and its implementation. By doing so, the most essential element is to build a platform to link a supply and a demand simultaneously. In other word, a comprehensive analytical framework is to be set with a data repository which can be periodically updated. With such circumstances, the entire trip chain including pedestrian movements is required to be thoroughly investigated and constructed at the viewpoint of the intermodal transit station. A few studies, however, have been attempted. In this study, the comprehensive analytical framework with the integrated mobility at intermodal transit station was proposed, which consisted of the three modules; 1) Data Repository Extracting from Smart Card DB, 2) Framework of Analyzing Integrated Mobility, and 3) Interpretation of the Integrated Mobility with GIS information and the other factors. A case study with the seven railway stations (Sadang, Sindorom, Samseong, Gwanghwanoon, Gangnam, Jamsil, Seoul Nat'l Univ. of Education) was conducted. The stations of the case study were clustered by the three groups with the statistical ground, and it is most likely to understand the effect of a variety of factors and a comprehensive data-driven analyses with the entire trip stages.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.233-243
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• 2008

Recognition for the importance and roles of public transportation is increasing because of traffic problems in many cities. In spite of this paradigm change, previous researches related with public transportation trip assignment have limits in some aspects. Especially, in case of multimodal public transportation networks, many characters should be considered such as transfers. operational time schedules, waiting time and travel cost. After metropolitan integrated transfer discount system was carried out, transfer trips are increasing among traffic modes and this takes the variation of users' route choices. Moreover, the advent of high-technology public transportation card called smart card, public transportation users' travel information can be recorded automatically and this gives many researchers new analytical methodology for multimodal public transportation networks. In this paper, it is suggested that the methodology for establishment of brand new multimodal public transportation networks based on computer programming methods using transportation card data. First, we propose the building method of integrated transportation networks based on bus and urban railroad stations in order to make full use of travel information from transportation card data. Second, it is offered how to connect the broken transfer links by computer-based programming techniques. This is very helpful to solve the transfer problems that existing transportation networks have. Lastly, we give the methodology for users' paths finding and network establishment among multi-modes in multimodal public transportation networks. By using proposed methodology in this research, it becomes easy to build multimodal public transportation networks with existing bus and urban railroad station coordinates. Also, without extra works including transfer links connection, it is possible to make large-scaled multimodal public transportation networks. In the end, this study can contribute to solve users' paths finding problem among multi-modes which is regarded as an unsolved issue in existing transportation networks.