• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제3권1호
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• pp.45-52
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• 2004

There are many cities installing ITS(Intelligent Transportation Systems) and running TMC(Trafnc Management Center) to improve mobility and safety of roadway transportation by providing roadway information to drivers. There are many devices in ITS which collect real-time traffic data. We can obtain many valuable traffic data from the devices. But it's impossible to avoid missing traffic data for many reasons such as roadway condition, adversary weather, communication shutdown and problems of the devices itself. We couldn't do any secondary process such as travel time forecasting and other transportation related research due to the missing data. If we use the traffic data to produce AADT and DHV, essential data in roadway planning and design, We might get skewed data that could make big loss. Therefore, He study have explored some imputation techniques such as heuristic methods, regression model, EM algorithm and time-series analysis for the missing traffic volume data using some evaluating indices such as MAPE, RMSE, and Inequality coefficient. We could get the best result from time-series model generating 5.0$\%$, 0.03 and 110 as MAPE, Inequality coefficient and RMSE, respectively. Other techniques produce a little different results, but the results were very encouraging.

• Korean Journal of Remote Sensing
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• 제14권4호
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• pp.376-391
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• 1998

Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제10권1호
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• pp.1-5
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• 2010

Recently emphasizing the importance of security such as national major institutions' facilities or major industrial facilities for the maintenance of security/crime prevention due to specialization of the Green Information Technology(G-IT) and Green Ubiquitous Technology(G-UT) industry fields, The Security System Building linked high technology within the government-related organization, enterprise and army the military is urgently required. This paper is about the green USN intelligent an unmanned guard MUX system that receive the signals, from alarm device within surveillance area, with various ways of communication techniques and then transmit to local control center and remote control server trough TCP/IP network. This study enables the mutual senergy effect by realizing a total solution of an unmanned guard system and also significantly contributes to the global/domestic market expansion. That can be applied to the crime prevention/security fields in the Green Ubiquitous Environment Implemented Business(survalance-Home, Gu-City, Gu-Health, etc.), and will contribute to expand companies with international competitiveness that can provide the Green Ubiquitous Vision(Gu-Vision).

• Journal of the Korean Institute of Intelligent Systems
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• 제12권6호
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• pp.531-536
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• 2002

In this paper, we have applied Genetic Algorithms(GAs) to Intrusion Detection System(TDS), and then proposed and simulated the misuse detection model firstly. We have implemented with the KBD contest data, and tried to simulated in the same environment. In the experiment, the set of record is regarded as a chromosome, and GAs are used to produce the intrusion patterns. That is, the intrusion rules are generated. We have concentrated on the simulation and analysis of classification among the Data Mining techniques and then the intrusion patterns are produced. The generated rules are represented by intrusion data and classified between abnormal and normal users. The different rules are generated separately from three models "Time Based Traffic Model", "Host Based Traffic Model", and "Content Model". The proposed system has generated the update and adaptive rules automatically and continuously on the misuse detection method which is difficult to update the rule generation. The generated rules are experimented on 430M test data and almost 94.3% of detection rate is shown.3% of detection rate is shown.

• Journal of Digital Convergence
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• 제12권12호
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• pp.345-350
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• 2014

According to the necessity of smart working with various mobile devices, and the increasing services based on the converged infrastructures such as Cloud, Wearable Computing, Next Generation Wired/Wireless Mobile Networks, the network reliability has been one of the most important things. However, the research related to the network reliability is still insufficient. To solve these problems, we propose the ISNTC (Intelligent Safe Network Technology based on Cloud), which uses the safe network technique based on SDN, to be adopted to the smart working environments. The proposed ISNTC guarantees secure data forwarding through the synchronized transmission path and timing. We have verified the throughput which outperformed the existing techniques through the computer simulations using OPnet.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제6권3호
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• pp.24-32
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• 2007

Variable message sign (VMS), which is used for providing real-time information on traffic conditions and accident occurrences, is one of the important components of intelligent transportation systems. It is essential that the scheme of VMS message phase and duration should be designed with the consideration of drivers' message reading time that will be depended on various causal factors, such as the amount of VMS messages, drivers' travel speed, and geometric conditions. However, there have been not much efforts to explore the relationships between the drivers' message reading time and the above causal factors. Driving simulator experiments were conducted to obtain drivers' message reading time with respect to the amount of VMS messages, drivers' travel speed, and different geometric conditions. Regression modeling techniques were applied to develop an estimation model for drivers' message reading time. Probabilistic outcomes of the proposed model would be greatly utilized to design proper VMS message phase and duration.

• Journal of the Korean Institute of Intelligent Systems
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• 제14권4호
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• pp.390-395
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• 2004

A semiconductor manufacturing process is the complicate and dynamic process, and consists of many sub-processes. An etching process is the most important process in the semiconductor fabrication. In this paper, the decision support system based upon data mining and knowledge discovery is an important factor to improve the productivity and yield. The proposed decision support system consists of a neural network model and an inference system based on fuzzy logic Firstly, the product results are predicted by the neural network model constructed by the product patterns that represent the quality of the etching process. And the product patters are classified by expert's knowledge. Finally, the product conditions are estimated by the fuzzy inference system using the rules extracted from the classified patterns. Prediction of product qualities can be linked to each input and process variables. We employ data mining and intelligent techniques to find the best condition of the etching process. The proposed decision support system is efficient and easy to be implemented for the process management based upon expert's knowledge.

• Journal of the Korean Institute of Intelligent Systems
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• 제23권6호
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• pp.551-557
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• 2013

In intelligent robot research, hand gesture recognition has been an important issue. And techniques that recognize simple gestures are commercialized in smart phone, smart TV for swiping screen or volume control. For gesture recognition, robust hand detection is important and necessary but it is challenging because hand shape is complex and hard to be detected in cluttered background, variant illumination. In this paper, we propose efficient hand detection algorithm for detecting pointing hand for recognition of place where user pointed. To minimize false detections, ROIs are generated within the compact search region using skin color detection result. The ROIs are verified by HOG-SVM and pointing direction is computed by both detection results of head-shoulder and hand. In experiment, it is shown that proposed method shows good performance for hand detection.

• Journal of the Korea Institute of Information Security & Cryptology
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• 제30권1호
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• pp.157-167
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• 2020

The big data and artificial intelligence technology, which has provided the foundation for the recent 4th industrial revolution, has become a major driving force in business innovation across industries. In the field of information security, we are trying to develop and improve an intelligent security system by applying these techniques to large-scale log data, which has been difficult to find effective utilization methods before. The quality of security log big data, which is the basis of information security AI learning, is an important input factor that determines the performance of intelligent security system. However, the difference and complexity of log data by various product has a problem that requires excessive time and effort in preprocessing big data with poor data quality. In this study, we research and analyze the cases related to log data collection of various firewall. By proposing firewall log data collection format standard, we hope to contribute to the development of intelligent security systems based on security log big data.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제19권11호
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• pp.2534-2539
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• 2015

Method for regulating voltage using a generator voltage regulating device (AVR) is divided in an existing analog system and a digital replacement. Typically, to adjust the voltage by using a brushless excitation system of the type to be reduced for a voltage change under all. The control method of the AVR as a PID (proportional-integral-differential) control method is widely used. However, the control scheme is to reduce the transient response of the control parameters of the controller to the control object. Therefore, if the control target should change, there is a problem, reset the parameters of the controller again. In this study, without having to reset the parameters of the controller for the parameter variations to be controlled iPID (intelligent PID) using a controller designed to obtain a generator AVR system voltage variation is small in response to full load is applied to and through simulations and experiments improved transient response.