• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.83-89
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• 2021

With the recent development of information and communication technology, there have been many attempts to apply various IT technologies in the railway field. Until now, the safety control system has been installed at the site and operated using actual data, but there is a problem that it is difficult to verify the function of the railway safety control system in that no accidents occur in real situations. In this study, accident data is generated randomly to verify that the safety control system is functioning properly, and to this end, simulation data is prepared according to the simulator, accident scenario and scenario. Real-time railway safety monitoring system collects and transmits data from interface devices to common protocol called DDS.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.23-30
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• 2021

Due to the recent advancements of mobile telecommunication technology and high mobile phone penetration rate, researches on emergency text alert service for enhancing the accessibility have been actively conducted. The worldwide spread of COVID-19 further accelerates the efforts for the alert services. Existing emergency text services are simple and efficient. However, unclear reception area may cause unintended alert messages frequently. In this paper, we analyze survey results regarding the 5G-based text-alert services to derive service requirements for technological advancement. Then we propose an emergency disaster text service scenario using Active Geo-Targeting that enables active disaster text reception of terminals. In addition, we newly define an interface protocol that is CIB(Control Information Block) to operate the proposed scenario.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.64-69
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• 2018

Automatic test equipment for field maintenance of aircraft mounted equipment is effective for integrated design when operating a small number of aircraft for special purposes. The integrated automatic test equipment identifies commonly used interfaces and is used for branching or generating routes for each unit under test specific inspection. High-precision signals such as RTD, TC, and analog voltage can cause measurement errors due to conduction resistance during signal branching and connection when generating branches and paths. The measurement error caused by the resistance of the wire leads to a lot of restrictions in designing the equipment to be inspected. In this paper, we propose a method of calibrating highly accurate signals of an integrated automatic inspection equipment that minimizes measurement errors of analog voltage and high - precision signals.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.261-270
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• 2010

An integrated simulation engine provides tools, services, and standards to support various activities in the entire M&S from modeling and simulation to analysis of the simulation results. Many countries have developed integrated simulation engines to efficiently assist complex M&S activities. However, we do not have domestic simulation engines especially designed for defense M&S, therefore, developing M&S softwares still remains as a hard task with high cost and tine. OpenSIM(Open Simulation engine for Interoperable Models) is an integrated simulation engine and provides tools, services and standard interfaces for weapons analysis. OpenSIM's services are comprised of classes, member functions and data attributes which are commonly used in modeling, simulating and analyzing weapons systems. In this paper, we introduce OpenSIM's services in C++ APIs and illustrate them through an ASM example(Air to Surface Missile).

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.855-864
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• 2013

Decision tree classification is one of the important problems in data mining fields and data minings have been important tasks in the fields of large database technologies. Therefore the coupling efforts of data mining systems and database systems have led the developments of database primitives supporting data mining functions such as decision tree classification. These primitives consist of the special database operations which support the SQL implementation of decision tree classification algorithms. These primitives have become the consisting modules of database systems for the implementations of the specific algorithms. There are two aspects in the developments of database primitives which support the data mining functions. The first is the identification of database common primitives which support data mining functions by analysis. The other is the provision of the extended mechanism for the implementations of these primitives as an interface of database systems. In data mining, some primitives want be stored in DBMS is one of the difficult problems. In this paper, to solve of the problem, we describe the database primitives which construct and apply the optimized decision tree classifiers. Then we identify the useful operations for various classification algorithms and discuss the implementations of these primitives on the commercial DBMS. We implement these primitives on the commercial DBMS and present experimental results demonstrating the performance comparisons.

• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.141-158
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• 2008

In this paper, we developed the GML Map Server which visualized the map based on GML as international standard for exchanging the common format map and for interoperability of GIS information. And also, it should transmit effectively GML map into the mobile device by using dynamic map partition and caching. It manages a partition based on the visualization area of a mobile device in order to visualize the map to a mobile device in real time, and transmits the partition area by serializing it for the benefit of transmission. Also, the received partition area is compounded in a mobile device and is visualized by being partitioned again as four visible areas based on the display of a mobile device. Then, the area is managed by applying a caching algorithm in consideration of repetitiveness for a received map for the efficient operation of resources. Also, in order to prevent the delay in transmission time as regards the instance density area of the map, an adaptive map partition mechanism is proposed for maintaining the regularity of transmission time. GML Map Server can trace the position of mobile device with WIPI environment in this paper. The field emulator can be created mobile devices and mobile devices be moved and traced it's position instead of real-world. And we developed POIM(POI Management) for management hierarchically POI information and for the efficiency POI search by using the individual tagging technology with visual interface.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1027-1042
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• 2004

A Software Component is a module that is reused among a lot of projects, systems, and companies rather than a single application. Components can be reused in various systems if they provide not only the common functionalities required in many applications but also the diverse aspects to be customized for being suitable for customers' demands. From the development phase, components should be designed and developed considering the variable aspects they have for convenient customization. Easily customized components can be frequently reused in lots of applications. In the literature, there are some modeling and customizing techniques. But they suggested only conceptual or basic methods based on Object-Oriented. And the practical instructions for reusing component were not provided sufficiently. Moreover, there are few techniques that consider the proper variability types components have. Thus, those techniques are not appropriate for applying to black box component completely developed and released. In this paper, we classify variabilities that components have in functional aspect into two categories. The one is logic variability, and the other is workflow variability. For each classified variability, we propose the three kind of modeling techniques, which are selection, plug in and externalization. Also detailed instructions for practical design and application are provided.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.246-250
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• 2008

This paper presents the design of network vulnerability analysis system which can integrate various vulnerability assessment tools to improve the preciseness of the vulnerability scan result. Manual checking method performed by a security expert is the most precise and safe way. But this is not appropriate for the large-scale network which has a lot of systems and network devices. Therefore automatic scanning tool is recommended for fast and convenient use. The scanning targets may be different according to the kind of vulnerability scanners, or otherwise even for the same scanning target, the scanning items and the scanning results may be different by each vulnerability scanner, Accordingly, there are the cases in which various scanners, instead of a single scanner, are simultaneously utilized with the purpose of complementing each other. However, in the case of simultaneously utilizing various scanners on the large-scale network, the integrative analysis and relevance analysis on vulnerability information by a security manager becomes time-consumable or impossible. The network vulnerability analysis system suggested in this paper provides interface which allows various vulnerability assessment tools to easily be integrated, common policy which can be applied for various tools at the same time, and automated integrative process.

• Journal of KIISE
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• v.44 no.6
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• pp.587-594
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• 2017

Recently, motor imagery electroencephalogram(EEG) based Brain-Computer Interface(BCI) systems have received a significant amount of attention in various fields, including medicine and engineering. The Common Spatial Pattern(CSP) algorithm is the most commonly-used method to extract the features from motor imagery EEG. However, the CSP algorithm has limited applicability in Small-Sample Setting(SSS) situations because these situations rely on a covariance matrix. In addition, large differences in performance depend on the frequency bands that are being used. To address these problems, 4-40Hz band EEG signals are divided using nine filter-banks and Regularized CSP(R-CSP) is applied to individual frequency bands. Then, the Mutual Information-Based Individual Feature(MIBIF) algorithm is applied to the features of R-CSP for selecting discriminative features. Thereafter, selected features are used as inputs of the classifier Least Square Support Vector Machine(LS-SVM). The proposed method yielded a classification accuracy of 87.5%, 100%, 63.78%, 82.14%, and 86.11% in five subjects("aa", "al", "av", "aw", and "ay", respectively) for BCI competition III dataset IVa by using 18 channels in the vicinity of the motor area of the cerebral cortex. The proposed method improved the mean classification accuracy by 16.21%, 10.77% and 3.32% compared to the CSP, R-CSP and FBCSP, respectively The proposed method shows a particularly excellent performance in the SSS situation.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.837-850
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• 2002

In this paper, we propose an EEG-based response time prediction method during a yes/no cognitive decision task. In the experimental task, a subject goes through responding of visual stimulus, understanding the given problem, controlling hand motions, and hitting a key. Considering the subject's varying brain activities, we model subjects' mental states with defining CT (cut time), ST (selection time), and RP (repeated period). Based on the assumption between ST and RT in the mental model, we predict subjects' response time by detection of selection time. To recognize the subjects' selection time ST, we extract 3 types of feature from the filtered brain waves at frequency bands of $\alpha$, $\beta$, ${\gamma}$ waves in 4 electrode pairs combined by spatial relationships. From the extracted features, we construct specific rules for each subject and meta rules including common factors in all subjects. Applying the ST detection rules to 8 subjects gives 83% success rates and also shows that the subjects will hit a key in 0.73 seconds after ST detected. To validate the detection rules and parameters, we test the rules for 2 subjects among 8 and discuss about the experimental results. We expect that the proposed detection method can be a basic technology for brain-computer-interface by combining with left/right hand movement or yes/no discrimination methods.