• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.411-425
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• 2023

Today, AI (Artificial Intelligence) technology is widely used in various fields, performing classification and regression tasks according to the purpose of use, and research is also actively progressing. Especially in the field of security, unexpected threats need to be detected, and unsupervised learning-based anomaly detection techniques that can detect threats without adding known threat information to the model training process are promising methods. However, most of the preceding studies that provide interpretability for AI judgments are designed for supervised learning, so it is difficult to apply them to unsupervised learning models with fundamentally different learning methods. In addition, previously researched vision-centered AI mechanism interpretation studies are not suitable for application to the security field that is not expressed in images. Therefore, In this paper, we use a technique that provides interpretability for detected anomalies by searching for and comparing optimization references, which are the source of intrusion attacks. In this paper, based on reference, we propose additional logic to search for data closest to real data. Based on real data, it aims to provide a more intuitive interpretation of anomalies and to promote effective use of an anomaly detection model in the security field.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.51-60
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• 2012

In this paper, we provide the analysis of device model and method between device models for compatible M&S V&V of the NetSPIN. First of all, we analysis features, structure, and classification of the NetSPIN. The second, as a part of reliable V&V process, we analysis network system modeling process, correlation between device modeling process for M&S of the NetSPIN. The third, we suggest making a kind of pool of reference model and module of devices for the increase factor of reuse between device model. We also, at the point view of M&S V&V, conclude that there is the validity of the fidelity in device modeling process. Through the analysis of the NetSPIN device model and suggestion of the method for higher compatibility between device modes, the development process of device model be clearly understood. Also we present the effective method of the development for reliable device mode as the point of V&V.

• Speech Sciences
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• v.15 no.2
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• pp.55-65
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• 2008

Recently, the multi-model based speech recognizer has been used quite successfully for noisy speech recognition. For the selection of the reference HMM (hidden Markov model) which best matches the noise type and SNR (signal to noise ratio) of the input testing speech, the estimation of the SNR value using the VAD (voice activity detection) algorithm and the classification of the noise type based on the GMM (Gaussian mixture model) have been done separately in the multi-model framework. As the SNR estimation process is vulnerable to errors, we propose an efficient method which can classify simultaneously the SNR values and noise types. The KL (Kullback-Leibler) distance between the single Gaussian distributions for the noise signal during the training and testing is utilized for the classification. The recognition experiments have been done on the Aurora 2 database showing the usefulness of the model compensation method in the multi-model based speech recognizer. We could also see that further performance improvement was achievable by combining the probability density function of the MCT (multi-condition training) with that of the reference HMM compensated by the D-JA (data-driven Jacobian adaptation) in the multi-model based speech recognizer.

• Journal of Korean Library and Information Science Society
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• v.48 no.4
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• pp.129-151
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• 2017

Information modeling that is broadly applied in digital archiving process privides conceptual process that can be used to guide the creation of descriptions for the objects of preservation. However, it has faced with the limitations on substantially applying to the creation of preservation metadata records. This research proposes the concept of Resource Cluster in order to address these problems and efficiently describe the objects of preservation during digital archiving process. It also constructed Preservation Description Framework (PDF) based on RDF in order to substantially manifest preservation descriptions. This framework combines the structure of OAIS Reference Model and Functional Requirements for Bibliographic Records (FRBR) and can be an alternative approach to the creation of preservation metadata in more efficient and effective ways.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.731-736
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• 1994

Experiment on a lab-scale pH process is carried out to evaluate the control performance of the neural linearizing control scheme(NLCS) using a radial basis function(RBF) network which was previously proposed by Kim and Park. NLCS was developed to overcome the difficulties of the conventional neural controllers which occur when they are applied to chemical processes. Since NLCS is applicable for the processes which are already controlled by a linear controller and of which the past operating data are enough, we first control the pH process with PI controller. Using the operating data with PI controller, the linear reference model is determined by optimization. Then, a IMC controller replaces the PI controller as a feedback controller. NLCS consists of the IMC controller and a RBF network. After the learning of the neural network is fully achieved, the dynamics of the process combined with the neural network becomes linear and close to that of the linear reference model and the control performance of the linear control improves. During the training, NLCS maintains the stability and the control performance of the closed loop system. Experimental results show that the NLCS performs better than PI controller and IMC for both the servo and the regulator problems.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.836-843
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• 2003

The automatic train control (ATC) system development project for the Automated Guideway Transit (AGT) system has high technical risk because the system is unmanned train control system using wireless technology which was unprecedented in train control industry of Korea. To overcome the technical risk during concept design phase of the ATC system development project, the integrated product team(IPT) carried out a reverse and reengineering process using a systems engineering design model. The generic systems engineering process is incorporated in the both reverse and reengineering process. As a result of the systems engineering effort, the IPT has built top layer systems engineering design model of the ATC subsystem. The purpose of this paper is to deliver the reverse and reengineering process which was used to develop the systems engineering design model of ATC system using a computer aided systems engineering tool. This study also shows that the model based reverse and reengineering process can reduce the technical risk by identifying the differences of requirement, functional and physical architecture between a reference system and a target system.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.3
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• pp.315-322
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• 2018

Due to the increasing demand for more rapid, precise and accurate geolocation of the targets on video frames from UAVs, an efficient and timely method for correcting sensor models of motion imagery is required. In this paper, we propose a method to adjust or correct sensor models of motion imagery frames using space resection via image matching with reference data. The proposed method adopts image matching between the motion imagery frames and the reference frames which are synthesized from reference data. Ground or reference control points are generated or selected through the matching process in near real time, and are used for space resection to get adjusted sensor models. Finally, more precise and accurate geolocation of the targets can possibly be done on the fly, and we have got the promising result on performance analysis in terms of the geolocation quality.

• Journal of Korea Technology Innovation Society
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• v.8 no.spc1
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• pp.323-336
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• 2005

Digital content industry is growing rapidly because of the property of high-speed networking and greater demand for digital fulltext-image. However, we know the fact that it is many difficulty in production and supply for good quality of content. Hereupon, we suggest digital fulltext-image service framework to protect copyright. More concretely, we propose integrated model and reference model to securely serve digital fulltext-image by recompositing core objects and reconstructing the value-chain structure of digital content industry to framework including the process(from its production (creators or copyrighters) to consumption (users or consumers)). Also, we construct the digital fulltext- image service system based on reference model and reconstruct its interface that occurs between core subjects.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.10
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• pp.748-754
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• 1987

A robustness analysis for model reference adaptive control(MRAC) system with plant uncertainty is discussed in this paper. The adaptive control system is designed under assumptions that the controlled plant is represented by a lst order nominal model and that the system is drived by a constant reference signal. When using general gradient method(GGM), it is shown that unmodelled dynamics in plant model can cause the instability of the overall control loop during the adaptation process. However, as the algorithm of least square method(LSM) is introduced, the global stability of the system can be hold. And it is also given that the boundedness of adjustable parameters may be verified using the concept of an equilibrium point analysis.

• Asia pacific journal of information systems
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• v.25 no.2
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• pp.356-369
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• 2015

Public sectors around the world utilize social media tools and technologies in their daily activities for a variety of purposes, including disseminating useful information, fostering mass collaboration, and enforcing laws and regulations. A number of social media-based government stage models have emerged to document this use. In this chapter, we conducted a qualitative meta-synthesis of four social media-based government models. These models include 1) the open government maturity model, 2) the social media utilization model, 3) the adoption process for social media, and 4) the social media-based engagement model. The concepts, metaphors, and themes contained in these developmental models are extracted through a series of in-depth semantic analyses of descriptions, resulting in a common frame of reference.