• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.2
• /
• pp.227-232
• /
• 2003

Recently, support vector learning attracts an enormous amount of interest in the areas of function approximation, pattern classification, and novelty detection. One of the main reasons for the success of the support vector machines(SVMs) seems to be the availability of global and sparse solutions. Among the approaches sharing the same reasons for success and exhibiting a similarly good performance, we have KFD(kernel Fisher discriminant) approach. In this paper, we consider the problem of function approximation utilizing both predetermined basis functions and the KFD approach for regression. After reviewing support vector regression, semi-parametric approach for including predetermined basis functions, and the KFD regression, this paper presents an extension of the conventional KFD approach for regression toward the direction that can utilize predetermined basis functions. The applicability of the presented method is illustrated via a regression example.

• Journal of information and communication convergence engineering
• /
• v.17 no.2
• /
• pp.117-127
• /
• 2019

In software engineering, to ensure reliability between systems, describing both system architecture and assurance arguments between system elements is considered necessary. There are proposals for system architecture assurance, but use of these traditional methods often requires development of different diagrams using different editors. Because the visual sense of the traditional methods is inadequate, errors readily occur when manipulating different diagrams. Therefore, it is essential that the assurance of dependability between components and systems is visualized and easy to understand. In this paper, an integrated approach to describe the relationship between system actors and system architecture is proposed, and this approach is clarified using an enterprise architecture modeling language. A case study is carried out and comparison to the traditional approach $d^*$ framework is explained. The comparison results show that the proposed approach is more suitable for ensuring dependability in system architecture.

• Journal of the Korean Society of Systems Engineering
• /
• v.14 no.2
• /
• pp.49-57
• /
• 2018

The main objective of this paper is come up with methodology approach for FPGA-based system in verification and validation lifecycle regarding software reliability using system engineering approach. The steps of both reverse engineering and re-engineering are carried out to implement an FPGA-based of safety critical system in Nuclear Power Plant. The reverse engineering methodology is applied to elicit the requirements of the system as well as gain understanding of the current life cycle and V&V activities of FPGA based-system. The re-engineering method is carried out to get a new methodology approach of software reliability, particularly Software Reliability Growth Model. For measure the software reliability of a given FPGA-based system, the following steps are executed as; requirements definition and measurement, evaluation of candidate reliability model, and the validation of the selected system. As conclusion, a new methodology approach for software reliability measurement using software reliability growth model is developed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.2
• /
• pp.494-510
• /
• 2024

Internet users are exposed to sophisticated cyberattacks that intrusion detection systems have difficulty detecting. Therefore, research is increasing on intrusion detection methods that use artificial intelligence technology for detecting novel cyberattacks. Unsupervised learning-based methods are being researched that learn only from normal data and detect abnormal behaviors by finding patterns. This study developed an anomaly-detection method based on unsupervised machines and deep learning for a network intrusion detection system (NIDS). We present a hybrid anomaly detection approach based on unsupervised learning techniques using the autoencoder (AE), Isolation Forest (IF), and Local Outlier Factor (LOF) algorithms. An oversampling approach that increased the detection rate was also examined. A hybrid approach that combined deep learning algorithms and traditional machine learning algorithms was highly effective in setting the thresholds for anomalies without subjective human judgment. It achieved precision and recall rates respectively of 88.2% and 92.8% when combining two AEs, IF, and LOF while using an oversampling approach to learn more unknown normal data improved the detection accuracy. This approach achieved precision and recall rates respectively of 88.2% and 94.6%, further improving the detection accuracy compared with the hybrid method. Therefore, in NIDS the proposed approach provides high reliability for detecting cyberattacks.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.23 no.1
• /
• pp.38-47
• /
• 2014

This paper describes the application of discrete event systems theory to the design of an automated laboratory system. Current automated laboratory systems typically consist of several interacting processes that must be carefully sequenced to avoid any possible process conflicts. Discrete Event Systems (DES) theory and Supervisory Control Theory (SCT) can be applied together as effective methods of modeling the system dynamics and designing supervisory controllers to precisely sequence the many processes that such systems might involve. Classical approaches to supervisory controller design tend to result in complex controller structures that are difficult to implement, maintain, and upgrade. In this paper, a new approach to designing supervisory controllers for automated laboratory systems is introduced. This new approach uses a modular controller structure that is easier to implement, maintain, and upgrade, and deals with "state explosion" issues in a novel and efficient way.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.2
• /
• pp.138-146
• /
• 2007

The analysis and design method for achieving robust stabilization of Decentralized Dynamic Surface Control (DDSC) is presented for a class of interconnected nonlinear systems. While a centralized design approach of DSC was developed in [1], the decentralized approach to deal with large-scale interconnected systems is proposed under the assumption that interconnected functions among subsystems are unknown but bounded. To provide a closed-loop form with provable stability properties, augmented error dynamics for N nonlinear subsystems with DDSC are derived. Then, the reachable set for errors of the closed-loop systems will be approximated numerically in the form of an ellipsoid in the framework of convex optimization. Finally, a numerical algorithm to calculate the $L_2$ gain of the augmented error dynamics is presented.

• International Journal of Control, Automation, and Systems
• /
• v.6 no.3
• /
• pp.378-385
• /
• 2008

This paper aims to present a polynomial approach to the steady-state optimal filtering for delayed systems. The design of the steady-state filter involves solving one polynomial equation and one spectral factorization. The key problem in this paper is the derivation of spectral factorization for systems with delayed measurement, which is more difficult than the standard systems without delays. To get the spectral factorization, we apply the reorganized innovation approach. The calculation of spectral factorization comes down to two Riccati equations with the same dimension as the original systems.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.3
• /
• pp.254-262
• /
• 2008

In this paper, we propose an adaptive neural dynamic surface control (DSC) approach with $H_{\infty}$ tracking performance for full dynamics of nonlinear flight systems. It is assumed that the model uncertainties such as structured and unstrutured uncertainties, and external disturbances influence the nonlinear aircraft model. In our control system, self recurrent wavelet neural networks (SRWNNs) are used to compensate the model uncertainties of nonlinear flight systems, and an adaptive DSC technique is extended for the disturbance attenuation of nonlinear flight systems. All weights of SRWNNs are trained on-line by the smooth projection algorithm. From Lyapunov stability theorem, it is shown that $H_{\infty}$ performance nom external disturbances can be obtained. Finally, we present the simulation results for a nonlinear six-degree-of-freedom F-16 aircraft model to confirm the effectiveness of the proposed control system.

• Journal of Korean Neurosurgical Society
• /
• v.59 no.6
• /
• pp.564-569
• /
• 2016

Objective : This study used the intradural procedural time to assess the overall technical difficulty involved in surgically clipping an unruptured middle cerebral artery (MCA) aneurysm via a pterional or superciliary approach. The clinical and radiological variables affecting the intradural procedural time were investigated, and the intradural procedural time compared between a superciliary keyhole approach and a pterional approach. Methods : During a 5.5-year period, patients with a single MCA aneurysm were enrolled in this retrospective study. The selection criteria for a superciliary keyhole approach included : 1) maximum diameter of the unruptured MCA aneurysm <15 mm, 2) neck diameter of the MCA aneurysm <10 mm, and 3) aneurysm location involving the sphenoidal or horizontal segment of MCA (M1) segment and MCA bifurcation, excluding aneurysms distal to the MCA genu. Meanwhile, the control comparison group included patients with the same selection criteria as for a superciliary approach, yet who preferred a pterional approach to avoid a postoperative facial wound or due to preoperative skin trouble in the supraorbital area. To determine the variables affecting the intradural procedural time, a multiple regression analysis was performed using such data as the patient age and gender, maximum aneurysm diameter, aneurysm neck diameter, and length of the pre-aneurysm M1 segment. In addition, the intradural procedural times were compared between the superciliary and pterional patient groups, along with the other variables. Results : A total of 160 patients underwent a superciliary (n=124) or pterional (n=36) approach for an unruptured MCA aneurysm. In the multiple regression analysis, an increase in the diameter of the aneurysm neck (p<0.001) was identified as a statistically significant factor increasing the intradural procedural time. A Pearson correlation analysis also showed a positive correlation (r=0.340) between the neck diameter and the intradural procedural time. When comparing the superciliary and pterional groups, no statistically significant between-group difference was found in terms of the intradural procedural time reflecting the technical difficulty (mean${\pm}$standard deviation : $29.8{\pm}13.0min$ versus $27.7{\pm}9.6min$). Conclusion : A superciliary keyhole approach can be a useful alternative to a pterional approach for an unruptured MCA aneurysm with a maximum diameter <15 mm and neck diameter <10 mm, representing no more of a technical challenge. For both surgical approaches, the technical difficulty increases along with the neck diameter of the MCA aneurysm.

• Journal of the Korean Society of Systems Engineering
• /
• v.8 no.1
• /
• pp.29-39
• /
• 2012

The conventional systems engineering has been performed mainly based on documentation artifacts. Although the Document-Based Systems Engineering has played a very important role in developing and deploying systems, it is difficult for systems engineers to build, to clarify, and to reuse the operational, functional and physical views of the System of Interest (SOI) efficiently. An information-age approach to this problem is the Model-Based Systems Engineering which has been emerging as a very productive solution for stakeholders to define, and understand the desired systems easily, to communicate and collaborate efficiently among each other, and also to verify and validate the systems solutions effectively. This paper proposes a set of MBSE process, methods, and models for use during the systems analysis and design phase of the naval combat system development. An example application of the proposed approach was exercised and a set of artifacts was generated for an export combat system project to demonstrate its effectiveness.