• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8B
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• pp.716-729
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• 2003

As the public Internet and private internet have grown from small networks into large infrastructures, the need to more systematically manage the large number of network components within these networks has grown more important as well. The rapid growth of network size has brought into question the salability of the existing centralized model, such as SNMP(Simple Network Management Protocol) and CMIP(Common Management Information Protocol). Thus, for efficient network management, researches about mobile agent have also been performed recently. This paper presents analytical models of centralized approach based on SNMP protocol, distributed approach based on mobile agent, and mixed mode to make up for shortcomings of SNMP and mobile agent. We compare the performance of these analytical models based on network management response time. Experiment results show that performance of mobile agent and the nixed mode is less sensitive to the delay in WAN network environment. However, SNMP is more efficient for the simple network environment like LAN. We also propose an adaptive network management algorithm in consideration of network t environment. delay, task, and the number of nodes based on the results of analytical models. The results show that the adaptive network management algorithm can reduce the network management response time by 10% compared with either mobile agent or mixed mode network management algorithm.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.540-549
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• 2018

This paper proposes the method of active distribution network expansion planning considering distributed generation integration and distribution network reconfiguration. The distribution network reconfiguration is taken as the expansion planning alternative with zero investment cost of the branches. During the process of the reconfiguration in expansion planning, all the branches are taken as the alternative branches. The objective is to minimize the total costs of the distribution network in the planning period. The expansion alternatives such as active management, new lines, new substations, substation expansion and Distributed Generation (DG) installation are considered. Distribution network reconfiguration is a complex mixed-integer nonlinear programming problem, with integration of DGs and active managements, the active distribution network expansion planning considering distribution network reconfiguration becomes much more complex. This paper converts the dual-level expansion model to Second-Order Cone Programming (SOCP) model, which can be solved with commercial solver GUROBI. The proposed model and method are tested on the modified IEEE 33-bus system and Portugal 54-bus system.

• Journal of Biomedical Engineering Research
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• v.29 no.6
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• pp.502-511
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• 2008

This study was designed to develop a new algorithm to extract the voluntary EMG and the evoked EMG from a mixed EMG generated when the muscle is stimulated both voluntarily and by electrical stimulation in the FES system. The proposed parallel filter algorithm consists of three phases: (1) Fourier transform of the mixed EMG, (2) multiplication of the transformed signal to two frequency functions, and (3) inverse Fourier transform. Four incomplete spinal cord injured patients participated in the experiments to evaluate the algorithm by measuring the knee extensor torque and the EMG signals from the quadriceps. Two functions of the algorithms were evaluated: (1) extraction of the evoked EMG and (2) the voluntary EMG from the mixed EMG. The results showed that the algorithm enabled us to separate the two EMG components in real time from the mixed EMG. The algorithm can and will be used for estimating the voluntary torque and the evoked torque independently through an artificial neural network based on the two EMG components, and also for generating a trigger signal to control the on/off time of the FES system.

• Journal of Energy Engineering
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• v.28 no.4
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• pp.82-93
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• 2019

In this study, a new model is proposed to improve the problem of the decline of predict rate of heat demand on a particular date, such as a public holiday for the conventional heat demand forecasting system. The proposed model was the Four Season Mixed Heat Demand Prediction Neural Network Model, which showed an increase in the forecast rate of heat demand, especially for each type of forecast date (weekday/weekend/holiday). The proposed model was selected through the following process. A model with an even error for each type of forecast date in a particular season is selected to form the entire forecast model. To avoid shortening learning time and excessive learning, after each of the four different models that were structurally simplified were learning and a model that showed optimal prediction error was selected through various combinations. The output of the model is the hourly 24-hour heat demand at the forecast date and the total is the daily total heat demand. These forecasts enable efficient heat supply planning and allow the selection and utilization of output values according to their purpose. For daily heat demand forecasts for the proposed model, the overall MAPE improved from 5.3~6.1% for individual models to 5.2% and the forecast for holiday heat demand greatly improved from 4.9~7.9% to 2.9%. The data in this study utilized 34 months of heat demand data from a specific apartment complex provided by the Korea District Heating Corp. (January 2015 to October 2017).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1627-1634
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• 2021

This paper introduces a low-power compact ADC circuit for analog Convolutional filter for low-power neural network accelerator SOC. While convolutional neural network accelerators can speed up the learning and inference process, they have drawback of consuming excessive power and occupying large chip area due to large number of multiply-and-accumulate operators when implemented in complex digital circuits. To overcome these drawbacks, we implemented an analog convolutional filter that consists of an analog multiply-and-accumulate arithmetic circuit along with an ADC. This paper is focused on the design optimization of a low-power 8bit SAR ADC for the analog convolutional filter accelerator We demonstrate how to minimize the capacitor-array DAC, an important component of SAR ADC, which is three times smaller than the conventional circuit. The proposed ADC has been fabricated in CMOS 65nm process. It achieves an overall size of 1355.7㎛², power consumption of 2.6㎼ at a frequency of 100MHz, SNDR of 44.19 dB, and ENOB of 7.04bit.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.267-271
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• 2000

Traffic analysis during past years used the Poisson distribution or Markov model, assuming an exponential distribution of packet queue arrival. Recent studies, however, have shown aperiodic and burst characteristics of network traffics. Such characteristics of data traffic enable the scalability of network, QoS, optimized design, when we analyze new traffic model having a self-similar characteristic. This paper analyzes the self-similar characteristics of a small-scale mixed traffic in a network simulation, the real network Traffic.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.263-267
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• 2000

Traffic analysis during past years used the Poisson distribution or Markov model, assuming an exponential distribution of packet queue arrival. Recent studies, however, have shown aperiodic and burst characteristics of network traffics Such characteristics of data traffic enable the scalability of network, QoS, optimized design, when we analyze new traffic model having a self-similar characteristic. This paper analyzes the self-similar characteristics of a small-scale mixed traffic in a network simulation, the real WAN delay time, TCP packet size, and the total network usage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.289-295
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• 2000

Traffic analysis during past years used the Poisson distribution or Markov model, assuming an exponential distribution of packet queue arrival. Recent studies, however, have shown aperiodic and burst characteristics of network traffics. Such characteristics of data traffic enable the scalability of network, QoS, optimized design, when we analyze new traffic model having a self-similar characteristic. This paper analyzes the self-similar characteristics of a small-scale mixed traffic in a network simulation, the real WAN delay time, TCP packet size, and the total network usage.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.2
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• pp.47-58
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• 2011

Snoop was suitably designed for wired and wireless network as having snoop agent module in BS(Base Station) which is connecting to both wired and wireless network in order to supplement the problems of TCP. This study examined performance difference by using the web traffic taken wide possession in current internet traffic. The web traffic has greater amount of traffic, shorter life time, and smaller size than other traffics. This study found that snoop producing performance improvement of wireless network in the network mixed with the wired and wireless lead performance loss when transmitting web traffic. This study found that in case of web traffic is transmitted it bring a performance improvement of web traffic as computing BWE((Bandwidth Expansion), and also found that this study prove of performance improvement by decreasing local retranmission.

• Korean Management Science Review
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• v.21 no.2
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• pp.15-25
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• 2004

Great effort has been exerted to redesign the supply chain network as a means to improve corporate competitiveness. In this study, we present a mathematical model and a solution system to help redesign corporate logistics networks. The objective of the model is to minimize total logistics costs. We applied the solution system to real problem cases. We use the model and the concept to develop decision support system that is based on C++ with the use of CPLEX callable library as a solution engine. We tested and verified the DSS for redesigning the network of a large Korean electronics company. Through various scenario analyses. we recommend to redesign their supply chain network that demonstrates the possibility of substantial logistics cost savings.