• Journal of Distribution Science
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• v.22 no.3
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• pp.105-112
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• 2024

Purpose: This study analyzed the relationship between corporate capacity and management performance in the Korean distribution industry during the COVID-19 pandemic. Research design, data and methodology: The data for this study used the 2021 KOTRA GCL Test Data, and multiple regression analysis was performed using SPSS 26. As corporate competency, human capital and related capital of intellectual capital theory were utilized, and the global network level of social network theory was also utilized. As an additional analysis, corporate characteristics factors were used. Results: First, the level of global mindset of human capital acted as a positive factor in management performance, and the level of professional manpower did not achieve significant results. Second, related capital acted as a positive factor in corporate performance. Third, from the perspective of social network theory, the global network level of companies acted as a positive factor in management performance. Finally, the relationship between corporate characteristics and management performance was marginally significant. Conclusions: In order to improve the business performance of a company in a market shock such as the COVID-19 pandemic, it is required to strengthen the level of network construction with customers and increase the level of intellectual capital that a company has.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.9
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• pp.569-575
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for high performance of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control Performance of the adaptive FNN controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation. and steady- state accuracy and transient response.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4C
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• pp.282-294
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• 2002

The modern telecommunication networks are composed of various network-type and are managed by various management technologies, such as TMN, SNMP, TINA etc. Furthermore, the network user's needs of real-time multimedia services are rapidly increasing. In order to guarantee the user-requested quality-of-service(QoS) and keep the network utilization at maximum, it is required to manage the network performance continuously after the network is deployed. The performance management function should provide the useful information for the network expansion and the capacity reallocation in the future. In this paper, we propose a DPE-based performance management architecture for the integrated management of the heterogeneous network elements with TMN and SNMP. We propose an approach to provide the Intranet traffic monitoring and analysis function using layered network management concept and distributed processing technology. The proposed architecture has been designed and implemented based on multiprocess and multithread structure to support concurrent processing. To manage the traffic according to the Intranet service categories, we implemented an ITMA(Intelligent Traffic Monitoring Agent) with packet capture library. With the proposed architecture, we could measure and analyze the real Intranet traffic of Yeungnam University.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.31-38
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• 2012

In this paper, requirements of GNSS receiver station installation are derived for optimizing the performance of network based GNSS precise positioning by concern of international organization(IGS, NGS) recommendation. Also a analysis method of network based GNSS precise positioning is suggested in order to evaluate the availability depending on various network configurations. To evaluate network candidates, a performance evaluation method is proposed for positioning of users according to a geometric configuration and the baseline distance. After the proposed method is used to Ochang region that is a the test area 6 network candidates are derived and the performance of positioning was analyzed. Finally, Ansung, Gongju, Eumsung, Boeun network configuration was selected as the best positioning performance. An optimal Receiving station network was selected using the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1119-1127
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• 2007

This paper is concerned with a performance analysis using a wired/wireless hybrid network based on Common Industrial Protocol(CIP). For the performance analysis, the data transmission time, average end-to-end delay and throughput between DeviceNet and the wireless devices are investigated. The experimental results show the performance in terms of the polling/COS service time of CIP based hybrid network.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.396-400
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• 2011

P2P(peer to Peer) network is a distributed network architecture composed of participants that make a portion of their resources directly available to other network participants, without the need for a central server. Currently, convergence network industry using wired and mobile are grows rapidly. So P2P protocols will be used between mobile and wired network. But current P2P protocols are focused on the wired networks only and there are no simulators for performance analysis of mobile P2P. In this paper, we design a P2P simulation system for performance analysis of P2P protocols in mobile, wired and convergence networks. It is constructed by a well-known mobile network simulator and wired based P2P protocol simulator. Finally we have implemented a smart TV test-bed using our P2P test-bed for convergence networks.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.19-27
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• 2023

In recent times, an exponential increase in Internet traffic has been observed as a result of advancing development of the Internet of Things, mobile networks with sensors, and communication functions within various devices. Further, the COVID-19 pandemic has inevitably led to an explosion of social network traffic. Within this context, considerable attention has been drawn to research on network traffic analysis based on machine learning. In this paper, we design and develop a new machine learning framework for network traffic analysis whereby normal and abnormal traffic is distinguished from one another. To achieve this, we combine together well-known machine learning algorithms and network traffic analysis techniques. Using one of the most widely used datasets KDD CUP'99 in the Weka and Apache Spark environments, we compare and investigate results obtained from time series type analysis of various aspects including malicious codes, feature extraction, data formalization, network traffic measurement tool implementation. Experimental analysis showed that while both the logistic regression and the support vector machine algorithm were excellent for performance evaluation, among these, the logistic regression algorithm performs better. The quantitative analysis results of our proposed machine learning framework show that this approach is reliable and practical, and the performance of the proposed system and another paper is compared and analyzed. In addition, we determined that the framework developed in the Apache Spark environment exhibits a much faster processing speed in the Spark environment than in Weka as there are more datasets used to create and classify machine learning models.

• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.1-6
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• 2010

Simulation analysis may be the essential means to either evaluate performance of systems or optimize system parameters for new design. Including many variations for design and implementation, MANET (Mobile Ad-hoc NETwork) is one target area of such an analysis. Since every node, however, included in the network has mobility, one MANET could be overlapped or merged with another one which use a different transport protocol. In order to communicate among nodes in this case, the new merged network should configure paths and addresses in advance. Configuring paths and addresses generates much overheads which ultimately cause delay in communicating data. Performance analysis is required to improve the data transport performance by minimizing overheads. This paper proposes a sound address auto-configuration method which is based on an on-demand manner and then presents modeling and performance analysis of the method. NS-2 simulation results verify that the proposed method can not only alleviate overheads, which are inevitably generated for address auto-configuration processes, and but also decentralize them in time.

• Smart Structures and Systems
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• v.26 no.2
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

• 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.