• Journal of Digital Convergence
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• v.13 no.5
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• pp.169-176
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• 2015

Virtual Private Network is a method which can use as a private network using private line. The quality of security of virtual private network is influenced by security auditability, cryptographic support, user data protection, access control, etc., and efficiency is influenced by throughput, latency, the number of cession, etc. In this paper, we constructed a evaluation model based on CC(ISO/IEC 15408) and the quality evaluation standard ISO/IEC 25000 series to evaluate the quality level about efficiency with security performance of virtual private network. We think that this study will contribute to construct the system which can evaluate the quality of virtual private network based on CC and ISO quality evaluation standard.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.441-457
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• 2014

Observed from the recent performance evaluation of clustering schemes in wireless sensor networks, we found that most of them did not consider various sensor characteristics and its application environment. Without considering these, the performance evaluation results are difficult to be trusted because these networks are application-specific. In this paper, for the fair evaluation, we measured several clustering scheme's performance variations in accordance with sensor data pattern, number of sensors per node, density of points of interest (data density) and sensor coverage. According to the experiment result, we can conclude that clustering methods are easily influenced by POI variation. Network lifetime and data accuracy are also slightly influenced by sensor coverage and number of sensors. Therefore, in the case of the clustering scheme that did not consider various conditions, fair evaluation cannot be expected.

• International Journal of Naval Architecture and Ocean Engineering
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• v.4 no.4
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• pp.374-385
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• 2012

The indoor noise of a ship is usually determined using the A-weighted sound pressure level. However, in order to better understand this phenomenon, evaluation parameters that more accurately reflect the human sense of hearing are required. To find the level of the satisfaction index of the noise inside a naval vessel such as "Loudness" and "Annoyance", psycho-acoustic evaluation of various sound recordings from the naval vessel was performed in a laboratory. The objective of this paper is to develop a single index of "Loudness" and "Annoyance" for noise inside a naval vessel according to a psycho-acoustic evaluation by using psychological responses such as Noise Rating (NR), Noise Criterion (NC), Room Criterion (RC), Preferred Speech Interference Level (PSIL) and loudness level. Additionally, in order to determine a single index of satisfaction for noise such as "Loudness" and "Annoyance", with respect to a human's sense of hearing, a back-propagation neural network is applied.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.149-159
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• 1998

The importance of soundness and safety evaluation in weld zone using by the ultrasonic wave has been recently increased rapidly because of the collapses of huge structures and safety accidents. Especially, the ultrasonic method that has been often used for a major non-destructive testing(NDT) technique in many engineering fields plays an important role as a volume test method. Hence, the defecting any defects of weld Bone in austenitic stainless steel type 304 using by ultrasonic wave and neural network is explored in this paper. In order to detect defects, a distance amplitude curve on standard scan sensitivity and preliminary scan sensitivity represented of the relation between ultrasonic probe, instrument, and materials was drawn based on a quantitative standard. Also, a total of 93％ of defect types by testing 30 defect patterns after organizing neural network system, which is learned with an accuracy of 99％, based on ultrasonic evaluation is distinguished in order to classify defects such as holes or notches in experimental results. Thus, the proposed ultrasonic wave and neural network is useful for defect detection and Ultrasonic Non-Destructive Evaluation(UNDE) of weld zone in austenitic stainless steel 304.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.179-185
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• 2015

In this paper, we research the IPTV that is the convergence technique of TV and network technique and performed the performance evaluation of picture quality of IPTV in the situation of increasing the network traffic in the Internet environment. To do this, we constructed the mock Internet network similar to the real Internet environment and measured the quality of received video using V-Factor model according to the increase of network traffic, and analyzed the result of the experiment. Making use of the result of this paper for the threshold value of V-Factor, the measured factor of network performance, the measured factor of video performance in the watchable IPTV video quality.

• Journal of Biosystems Engineering
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• v.25 no.5
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• pp.409-414
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• 2000

A machine vision system was built to obtain single stationary image from an egg. This system includes a CCD camera, an image processing board and a lighting system. A computer program was written to acquire, enhance and get histogram from an image. To minimize the evaluation time, the artificial neural network with the histogram of the image was used for eggshell evaluation. Various artificial neural networks with different parameters were trained and tested. The best network(64-50-1 and 128-10-1) showed an accuracy of 87.5% in evaluating eggshell. The comparison test for the elapsed processing time per an egg spent by this method(image processing and artificial neural network) and by the processing time per an egg spent by this method(image processing and artificial neural network) and by the previous method(image processing only) revealed that it was reduced to about a half(5.5s from 10.6s) in case of cracked eggs and was reduced to about one-fifth(5.5s from 21.1s) in case of normal eggs. This indicates that a fast eggshell evaluation system can be developed by using machine vision and artificial neural network.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.89-100
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• 2021

Smart Grid Network (SGN) is a next generation electrical power network which digitizes the power distribution grid and achieves smart, efficient, safe and secure operations of the electricity. The backbone of the SGN is information communication technology that enables the SGN to get full control of network station monitoring and analysis. In any network where communication is involved security is essential. It has been observed from several recent incidents that an adversary causes an interruption to the operation of the networks which lead to the electricity theft. In order to reduce the number of electricity theft cases, companies need to develop preventive and protective methods to minimize the losses from this issue. In this paper, we have introduced a machine learning based SVM method that detects malicious nodes in a smart grid network. The algorithm collects data (electricity consumption/electric bill) from the nodes and compares it with previously obtained data. Support Vector Machine (SVM) classifies nodes into Normal or malicious nodes giving the statues of 1 for normal nodes and status of -1 for malicious -abnormal-nodes. Once the malicious nodes have been detected, we have done a trust evaluation based on the nodes history and recorded data. In the simulation, we have observed that our detection rate is almost 98% where the false alarm rate is only 2%. Moreover, a Trust value of 50 was achieved. As a future work, countermeasures based on the trust value will be developed to solve the problem remotely.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.20
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• pp.47-53
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• 1989

This paper presents an algorithm CAPFACT to evaluate the reliability of a capacitated two terminal network such as a communication network, a power distribution network, and a pipeline network. The network is good(working) if and only if it is possible to transmit successfully the required system capacity from one specified terminal to the other. This paper defines new Capacitated series-parallel reduction to be applied to a series-parallel structure of the network. New Capacitated factoring method is applied to a non-series-parallel structure. The method is based on the factoring theorem given by Agrawal and Barlow. According to the existing studies on the reliability evaluation of the network that the capacity is not considered, the factoring method using reduction is efficient. The CAPFACT is more efficient than Aggarwal algorithm which enumerated and combined the paths. The efficiency is proved by the result of testing the number of operations and cpu time on FORTRAN compiler of VAX-11/780 at Hanyang University.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.120-128
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• 1993

In this paper, an implementation of high-speed parallel processing system for neural network design on the multicomputer network is presented. Linear speedup expandability is increased by reducing the synchronization penalty and the communication overhead. Also, we presented the parallel processing models and their performance evaluation models for each of the parallization methods of the neural network. The results of the experiments for the character recognition of the neural network bases on the proposed system show that the proposed approach has the higher linear speedup expandability than the other systems. The proposed parallel processing models and the performance evaluation models could be used effectively for the design and the performance estimation of the neural network on the multicomputer network.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.6
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• pp.1034-1044
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• 2016

This study seeks a method to objectively evaluate sensibility based on Big Data in the field of design. In order to do so, this study examined the sensibility responses on design factors for the public through a network analysis of texts displayed in social media. 'Hanbok', a formal clothing that represents Korea, was selected as the subject for the research methodology. We then collected 47,677 keywords related to Hanbok from 12,000 posts on Naver blogs from January $1^{st}$ to December $31^{st}$ 2015 and that analyzed using social matrix (a Big Data analysis software) rather than using previous survey methods. We also derived 56 key-words related to design elements and sensibility responses of Hanbok. Centrality analysis and CONCOR analysis were conducted using Ucinet6. The visualization of the network text analysis allowed the categorization of the main design factors of Hanbok with evaluation terms that mean positive, negative, and neutral sensibility responses. We also derived key evaluation factors for Hanbok as fitting, rationality, trend, and uniqueness. The evaluation terms extracted based on natural language processing technologies of atypical data have validity as a scale for evaluation and are expected to be suitable for utilization in an index for sensibility evaluation that supplements the limits of previous surveys and statistical analysis methods. The network text analysis method used in this study provides new guidelines for the use of Big Data involving sensibility evaluation methods in the field of design.