• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8A
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• pp.1177-1185
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• 2000

In this paper, We report on the performance issues faced by TCP based applications on satellite link having long propagation delay and high probability of bit erros and propose ENA(Error Notification Ack) algorithm for TCP Performance Enhancement. TCP Protocol cannot distinguish errored segments(in noisy medium) from losses of genuine network congestion and react as if there is network congestion. Therefore, Slow Start and Congestion avoidance mechanism are initiated. It happen this case in satellite link. Therefore it reduce the transmission rate and drop the performance. So, in this paper We propose ENA algorithm which is distinguished errored segments from losses of network congestion. And We propose the method of algorithm's implementation. And We evaluate the Performance of Tahoe, Reno, Sack TCP with ENA. As results, TCP Performance is better.

• Journal of Digital Convergence
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• v.6 no.4
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• pp.137-145
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• 2008

Embedded industry has emerged as one of the important industry for u-IT based application service. Technology development related to embedded hardware and software provides the base for the development of U-IT convergence industry. This study intends to suggest a research model to investigate the influence of industry, organization, technology factors on technology performance in the embedded companies. This study adopted research variables such as global network, local network, industry intensity, and technology capability as independent variables, with technology performance as a dependent variable from the existing literatures. The purpose of this study is to analyze the influence of industrial and organizational factors on technology performance of embedded companies SCM systems, including the moderating effect of government support. 94 companies data were collected by survey. The result of this empirical study is summarized as follows. First, local network and technology capability are the important determinants to influence technology performance of embedded companies in direct effect model. Second, global network and industry intensity has more positive influence on technology performance of embedded companies through a moderating variable of government support.

• Journal of Family Resource Management and Policy Review
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• v.17 no.4
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• pp.85-100
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• 2013

The purposes of this study are to explore the effect of the network characteristics of Healthy Family Support Center on its performance, and also to investigate the mediating effect of the organizational properties on the performance. We used the data from 148 healthy family support centers in National Survey in Korea. The analytic sample for this study consists of 102 responses.(response rate=68.9%) Multivariate regression model estimated the effects of the network's structural, interactive and functional characteristics and the interaction between the network's characteristics and organizational properties on the performance The findings of this study demonstrate that healthy family support centers with higher closeness centrality and with better functional characteristics reported more performances. Moreover, Centers that are more independent in organizational properties showed higher performances. However, the findings did not show that the interaction between the network's characteristics and organizational properties mediates on the performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1668-1688
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• 2012

Cooperative communications and network coding schemes have been proposed to increase system throughput for ad hoc networks. In this paper, we present throughput and delay analysis of the new network coding-enabled cooperative MAC protocol called NC-MAC, which has been proposed by us in order to significantly enhance system performance. This protocol introduces an approach that can accommodate both cooperative communication and network coding for wireless ad hoc networks by slightly increasing overhead and modifying standards. The protocol's performance is evaluated using mathematical analysis and computer simulation and two performance measures, system throughput and average channel access delay, are used for a performance comparison with previous schemes. It is assumed that all the frames exchanged over a wireless channel are susceptible to transmission errors, which is a new but more reasonable assumption differentiating this research from previous research. Numerical results show this protocol provides significantly enhanced system performance compared with conventional cooperative MAC protocols used in previous research. For instance, system performance is 47% higher using the NC-MAC protocol than when using the rDCF protocol.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.310-314
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• 2023

The purpose of this study is to predict the remaining capacity of lithium-ion batteries and evaluate their performance using five artificial intelligence models, including linear regression analysis, decision tree, random forest, neural network, and ensemble model. We is in the study, measured Excel data from the CS2 lithium-ion battery was used, and the prediction accuracy of the model was measured using evaluation indicators such as mean square error, mean absolute error, coefficient of determination, and root mean square error. As a result of this study, the Root Mean Square Error(RMSE) of the linear regression model was 0.045, the decision tree model was 0.038, the random forest model was 0.034, the neural network model was 0.032, and the ensemble model was 0.030. The ensemble model had the best prediction performance, with the neural network model taking second place. The decision tree model and random forest model also performed quite well, and the linear regression model showed poor prediction performance compared to other models. Therefore, through this study, ensemble models and neural network models are most suitable for predicting the remaining capacity of lithium-ion batteries, and decision tree and random forest models also showed good performance. Linear regression models showed relatively poor predictive performance. Therefore, it was concluded that it is appropriate to prioritize ensemble models and neural network models in order to improve the efficiency of battery management and energy systems.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3367-3378
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• 1999

ATM technology, which acts as a representative high-speed bandwidth technology, plays an important role in Internet environment. ATM network, supporting QoS(Quality of Service) and various traffic characters in high speed, configures many VPC(Virtual Path Connection)/VCC(Virtual Channel Connection). It is important to guarantee the QoS of each connection and it is necessary for the network manager to search element affecting the QoS of VPC/VCC and to control ATM network correctly. In the paper, the management information of VPC/VCC, that ATM network manager Using the fault notification for ATM switch, we can manage the configuration, fault and performance of ATM network. Thus, we extracted the configuration, fault and performance monitoring item from the ATM-MIB and SNMP M4 Network Element View MIB. And we designed the ATM network configuration, fault and performance management system based on the extracted item.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.180.3-180
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• 2001

In recent years, the remarkable development of communication network technology with the increasing demand of B-ISDN service helps the higg-speed ATM network to be applied a fully integrated global network. The considerable issue of high-speed communication network is a performance of service-link and stability of network queue. In this paper, we propose a feedback control algorithm and PID control method to improve the performance of service-link and stability of network queue and confirm upgraded traffic performance of the high-speed ATM network.

• 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 Institute of Telematics and Electronics S
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• v.34S no.3
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• pp.12-23
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• 1997

In this paper, we propose a new cell switch fabric for increasing the performance of ATM switching systems. Proposed switching network consists of a sorting network and a routing network. Both of these are multistage networks where each stage performs a fixed permutation on the incoming lines, and then routes them through a clumn of 2x2 switching elements. It is designed for distributing inputs and parallel processing to reduce the hardware complexity and obtain high performance of switching network. The structure and the operation of th eswitching network aredescribed and the performanceof the switching network is anlyzed under uniform traffic models. In this result, though the size of proposed network is increased the large scale, it has always the same throughput as the that of genral output queueing system with N=2. So, it is found that our proposed network is appropriate for the high apeed and lrger size of ATM switching systems.

• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.776-782
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• 2018

After CNN basic structure was introduced by LeCun in 1989, there has not been a major structure change except for more deep network until recently. The deep network enhances the expression power due to improve the abstraction ability of the network, and can learn complex problems by increasing non linearity. However, the learning of a deep network means that it has vanishing gradient or longer learning time. In this study, we proposes a CNN structure with MLP layer. The proposed CNNs are superior to the general CNN in their classification performance. It is confirmed that classification accuracy is high due to include MLP layer which improves non linearity by experiment. In order to increase the performance without making a deep network, it is confirmed that the performance is improved by increasing the non linearity of the network.