• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.17-27
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• 2022

In this study, a deep learning-based network that can predict the aerodynamic characteristics of airfoils was designed, and the feasibility of the proposed network was confirmed by applying aerodynamic data generated by Xfoil. The prediction of aerodynamic characteristics according to the variation of airfoil thickness was performed. Considering the angle of attack, the coordinate data of an airfoil is converted into image data using signed distance function. Additionally, the distribution of the pressure coefficient on airfoil is expressed as reduced data via proper orthogonal decomposition, and it was used as the output of the proposed network. The test data were constructed to evaluate the interpolation and extrapolation performance of the proposed network. As a result, the coefficients of determination of the lift coefficient and moment coefficient were confirmed, and it was found that the proposed network shows benign performance for the interpolation test data, when compared to that of the extrapolation test data.

• ETRI Journal
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• v.46 no.3
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• pp.461-472
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• 2024

We propose a network traffic prediction model based on linear and nonlinear model combination. Network traffic is modeled by an autoregressive moving average model, and the error between the measured and predicted network traffic values is obtained. Then, an echo state network is used to fit the prediction error with nonlinear components. In addition, an improved slime mold algorithm is proposed for reservoir parameter optimization of the echo state network, further improving the regression performance. The predictions of the linear (autoregressive moving average) and nonlinear (echo state network) models are added to obtain the final prediction. Compared with other prediction models, test results on two network traffic datasets from mobile and fixed networks show that the proposed prediction model has a smaller error and difference measures. In addition, the coefficient of determination and index of agreement is close to 1, indicating a better data fitting performance. Although the proposed prediction model has a slight increase in time complexity for training and prediction compared with some models, it shows practical applicability.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.2
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• pp.170-174
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• 2009

This paper describes the wireless communication test environment for the Link-K system and shows the performance analysis of multiple access protocols. The test environment consists of data generator, modem, radio sets, attenuators, and antennas. In case of both CSMA and Roll-Call protocols, throughput performance and delay are measured. And test results are analyzed. The test results would be used for communication performance analysis and network design of Link-K system.

• KNOM Review
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• v.22 no.2
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• pp.39-47
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• 2019

There are several big data-driven advanced research activities such as meteorological climate information, high energy physics, astronomy research, satellite information data, and genomic research data on KREONET. Since the performance degradation occurs in the environment with the existing network security equipment, methods for preventing the performance degradation on the high-performance research-only network and for high-speed research collaboration are being studied. In addition, the recent issue of quantum computers has been a threat to security using the existing encryption system. In this paper, we construct quantum cryptography-based communication network through environment construction and high-performance transmission test that build physical security through quantum cryptography-based communication network in end-to-end high-speed research network. The purpose of this study is to analyze the effect on network performance when performing physical encryption and to use it as basic data for constructing high-performance research collaboration network.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.214-227
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• 2022

The successful implementation of green supply chain management(GSCM) practices requires a level of cooperation that can be difficult to conduct. Despite this challenge, limited scholarly attention has been paid to exploring how the implementation of GSCM practices can be effectively facilitated and enhanced through accumulated social capital with suppliers. Based on social capital theory, this study postulates that supplier network characteristics derived from social capital with key suppliers can be critical antecedents of GSCM, which in turn enhances the firm's environmental performance. To test hypotheses, data were collected from 330 firms in 15 countries, and structural equation modeling was employed. Results show that GSCM improves environmental performance, and structural and cognitive social capitals of the supplier network act as antecedents and lead to GSCM implementation.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.327-338
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• 2020

This study wants to test the nexus among resource orientation, market orientation, social network, and knowledge sharing toward organizational innovation, and the nexus between organizational innovation and MSMEs performance. Questionnaires and interviews are conducted with some MSMEs actors in Central Java Province, Indonesia, in Klaten Regency and Pekalongan City. These two areas have creative MSMEs, especially Batik MSMEs that have been very large and known worldwide. The sampling technique is done purposively with certain criteria for the respondents. The data analysis technique is done using Partial Least Square. This study provides recommendations about strategic practice and policy (resource and market), social network, and knowledge sharing in increasing organizational innovation, and the impact of organizational innovation toward MSMEs performance. It also offers a comprehensive model of the determinant factor of organizational innovation by considering the aspect of strategic orientation, social network, and knowledge sharing. Other unique aspects that are also important to consider are social network and the importance of knowledge sharing in improving MSMEs Performance. The respondents are still limited in two areas, namely, Pekalongan and Klaten, so it still cannot represent the whole population. These areas also have different orientation of production process approach, namely, synthetic and natural dyes.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.6
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• pp.44-50
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• 1997

This paper describes the design and test of an on-line non-invasive network performance monitor (hardware portion) for the SPAX parallel computer. The SPAX parallel computer supports up to 256 intel P6 processors with 4 P6 processors constituting a processign node. The nodes are interconnected with a dual two-level crossbar network calle dXcent-net. Since the performance of the SPAX parallel computer is highly dependent on the proper and efficient operation of the network, an on-line non-invasive network performance monitor (with hardware components) has been developed to aid in the monitoring and tunign of the Xcent-net. Successful testing of a prototype node monitor board and PC interface system shows that our monitor design provides a low-cost practical solution to this problem.

• Proceedings of the ESK Conference
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• 1993.10a
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• pp.21-30
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• 1993

This paper describes the development of a simulation model of nuclear power plant operators including cognitive aspects by using a network modeling soft ware, Micro-SAINT (System Analysis of Integrated Networks of Tasks) for the analysis of operator performance. Network model description based on Micro-SAINT includes tasks, resources, precedence relations among tasks, flow of information and PSFs (Performance Shaping Factors) on task performance. We have tried to evaluate the performance with several performance measures such as the number of tasks allocated, relative time presure among operators within a shift, for the selected test accident scenarior; small-break LOCA (Loss of Coolant Accident) in a PWR (Pressurized Water Reactor) type nuclear power plant.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.391-398
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• 2017

In this paper, we compared the performance of "Network Intrusion Detection System based on attack feature selection using fuzzy control language"[1] and "Intelligent Intrusion Detection System Model for attack classification using RNN"[2]. In this paper, we compare the intrusion detection performance of two techniques using KDD CUP 99 dataset. The KDD 99 dataset contains data sets for training and test data sets that can detect existing intrusions through training. There are also data that can test whether training data and the types of intrusions that are not present in the test data can be detected. We compared two papers showing good intrusion detection performance in training and test data. In the comparative paper, there is a lack of performance to detect intrusions that exist but have no existing intrusion detection capability. Among the attack types, DoS, Probe, and R2L have high detection rate using fuzzy and U2L has a high detection rate using RNN.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.549-551
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• 2004

This paper used OPNET to simulate video streaming service a test IP network and MPLS network with the traffic shaping that have with CQ_ LLQ algorithm, LSP of fixed bandwidth, policy of limitation users and measures parameters such as delay, throughput, packet loss. To verify the performance of video streaming service in IP network and MPLS network, two scenario that have same topology and traffic source. One is the simulation for best-effort service in pure IP network. The other is the simulation for QoS-enabled service in MPLS Network. Based on simulation result, the MPLS network with CQ_ LLQ algorithm and fixed LSP show advantage of the video streaming service QoS, specially delay and packet loss