• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.9-13
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• 2005

Computer security has become a critical issue with the rapid development of business and other transaction systems over the Internet. The application of artificial intelligence, machine learning and data mining techniques to intrusion detection systems has been increasing recently. But most research is focused on improving the classification performance of a classifier. Selecting important features from input data leads to simplification of the problem, and faster and more accurate detection rates. Thus selecting important features is an important issue in intrusion detection. Another issue in intrusion detection is that most of the intrusion detection systems are performed by off-line and it is not a suitable method for a real-time intrusion detection system. In this paper, we develop the real-time intrusion detection system, which combines an on-line feature extraction method with the Least Squares Support Vector Machine classifier. Applying the proposed system to KDD CUP 99 data, experimental results show that it has a remarkable feature extraction and classification performance compared to existing off-line intrusion detection systems.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.183-192
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• 2017

k-nearest neighbor (K-NN) is a well-known classification algorithm, being feature space-based on nearest-neighbor training examples in machine learning. However, K-NN, as we know, is a lazy learning method. Therefore, if a K-NN-based system very much depends on a huge amount of history data to achieve an accurate prediction result for a particular task, it gradually faces a processing-time performance-degradation problem. We have noticed that many researchers usually contemplate only classification accuracy. But estimation speed also plays an essential role in real-time prediction systems. To compensate for this weakness, this paper proposes correlation coefficient-based clustering (CCC) aimed at upgrading the performance of K-NN by leveraging processing-time speed and plurality rule-based density (PRD) to improve estimation accuracy. For experiments, we used real datasets (on breast cancer, breast tissue, heart, and the iris) from the University of California, Irvine (UCI) machine learning repository. Moreover, real traffic data collected from Ojana Junction, Route 58, Okinawa, Japan, was also utilized to lay bare the efficiency of this method. By using these datasets, we proved better processing-time performance with the new approach by comparing it with classical K-NN. Besides, via experiments on real-world datasets, we compared the prediction accuracy of our approach with density peaks clustering based on K-NN and principal component analysis (DPC-KNN-PCA).

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1055-1064
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• 2003

In many automated systems, such as manufacturing systems and process plants, a fieldbus is a very important component for the exchange of various and sometimes crucial information. Some of the information has a tendency to rapidly lose its value as time elapses after its creation. Such information or data is called real-time data that includes sensor values and control commands. In order to deliver these data in time, the fieldbus network should be tailored to have short delay with respect to the individual time limit of various data. Fine-tuning the network for a given traffic requires the knowledge on the relationship between the protocol parameters such as timer values and the performance measure such as network delay. This paper presents a mathematical performance model to calculate communication delays of the Profibus-FMS network when the timer value and the traffic characteristics are given.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.154-161
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• 2014

In this research we investigate motion controller performance for mobile robots according to changes in the control loop sampling time. As a result, we suggest a proper range of the sample time, which can minimize final posture errors while improving tracking capability of the controller. For controller implementation into real mobile robots, we use a smooth and continuous motion controller, which can respect robot's path curvature limitation. We examine motion control performance in experimental tests while changing the control loop sampling time. Toward this goal, we compare and analyze experimental results using two different mobile robot platforms; one with real-time control and powerful hardware capability and the other with non-real-time control and limited hardware capability.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.55-67
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• 2012

Real-time image georeferencing is required to generate spatial information rapidly from the image sequences acquired by multi-sensor systems. To complement the performance of position/attitude sensors and process in real-time, we should employ on-line aerial triangulation based on a sequential estimation algorithm. In this study, we thus attempt to derive an efficient on-line aerial triangulation algorithm for real-time georeferencing of image sequences. We implemented on-line aerial triangulation using the existing Given transformation update algorithm, and a new inverse normal matrix update algorithm based on observation classification, respectively. To compare the performance of two algorithms in terms of the accuracy and processing time, we applied these algorithms to simulated airborne multi-sensory data. The experimental results indicate that the inverse normal matrix update algorithm shows 40 % higher accuracy in the estimated ground point coordinates and eight times faster processing speed comparing to the Given transformation update algorithm. Therefore, the inverse normal matrix update algorithm is more appropriate for the real-time image georeferencing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.26-33
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• 2018

A web application running on the Internet is causing many difficulties for a program developer, and it requires to process multiple sessions at the same time due to the occurrence of excessive traffic. Web applications should be able to process concurrent requests efficiently and in real time. Node.js is a single-threaded server-side JavaScript environment implemented in C and C ++ as one of the latest frameworks to implement event models across the entire stack. Nodes implement JavaScript quickly and robust to achieve the best performance using a JavaScript V8 engine developed by Google. In this paper, it will be explained the operation principle of Node.js, which is a lightweight real-time web server that can be implemented in JavaScript for real-time responsive web applications. In addition, this application was practically implemented through automatic alignment system for group scheduling to demonstrate event-based real-time response web processing.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1036-1039
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• 1996

The performance of real-time systems depends upon how well the tasks are scheduled within a cycle time and how fastly the response is made according to the occurrence of an external event. This paper presents the design of an effective real-time data acquisition system in order to gather the data from an automobile engine. This paper investigates an estimation and a restriction method of execution for aperiodic data. Also, the guarantee problem of real-time constraint is presented for periodic data. Through the experiments, the hard real-time guarantee problem of periodic data is studied and the damage problem of periodic data according to the increase of aperiodic tasks is analyzed.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.437-441
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• 2010

A new application area in which wireless sensor networks are applied requires the performance of more elaborated and complicated task and the completion of those tasks within a time limit. Until now, it is, however, insufficient to do research on the mechanism of handling interrupt based on real-time sensor operating systems which carefully consider the limitation of resources of sensor nodes and the property of tasks which is executed in a wireless sensor network area. In this paper, the requirements satisfying real-time in sensor operating systems are analyzed and based on this, a system is designed and implemented. In addition, the proposed mechanisms are confirmed by several verification methods, and the efficiency of the performance and the satisfaction of those requirements for real-time are verified by simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.8
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• pp.718-725
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• 2004

The real-time industrial network, often referred to as fieldbus, is an important element for intelligent manufacturing systems. Thus, in order to satisfy the real-time requirements of field devices, numerous fieldbus protocols have been announced. But, the application of fieldbus has been limited due to the high cost of hardware and the difficulty in interfacing with multi-vendor products. Therefore, as an alternative to fieldbus, the computer network technology, especially Ethernet (IEEE 802.3), is being adapted to the industrial environment. However, the crucial technical obstacle for Ethernet is its non-deterministic behavior that makes it inadequate for industrial applications where real-time data have to be delivered within a certain time limit. Recently, the development of switched Ethernet shows a very promising prospect for industrial application due to the elimination of uncertainties in the network operation resulting in much improved performance. This paper focuses on the application of the switched Ethernet with cascade structure for industrial communications. More specifically, this paper presents an analytical performance evaluation of switched Ethernet with cascade structure, and a case study about networked control system.

• Journal of IKEEE
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• v.24 no.2
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• pp.426-434
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• 2020

FMI is being researched as a standard for linking large-scale simulation of CPS. In order to guarantee the reliability of the results in large-scale simulations using FMI, event handling through time management techniques is required. This paper aims to guarantee real-time performance and accuracy in large-scale co-simulation environments such as CPS. Synchronize the wallclock time and simulation time to ensure real time. Also, to ensure the accuracy, before the simulation, the event is checked and the simulation is performed with the smallest step size while maintaining the real time until the event occurrence time. As a result, the events occurring in the co-simulation environment are processed immediately and sequentially, ensuring the real-time performance and minimizing the numerical integration error by maximizing the simulation resolution. In the experiment, the proposed method was processed immediately, and it was confirmed that the numerical integration error is reduced by about 1/5 unlike the existing time management method which does not guarantee the resolution.