• Journal of Communications and Networks
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• 제12권1호
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• pp.11-18
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• 2010

Diversity-multiplexing tradeoff (DMT) is an efficient tool to measure the performance of multiple-input and multiple-output (MIMO) systems and cooperative systems. Recently, cooperative multicast system with wireless network coding stretched tremendous interesting due to that it can drastically enhance the throughput of the wireless networks. It is desirable to apply DMT to the performance analysis on the multicast system with wireless network coding. In this paper, DMT is performed at the three proposed wireless network coding protocols, i.e., non-regenerative network coding (NRNC), regenerative complex field network coding (RCNC) and regenerative Galois field network coding (RGNC). The DMT analysis shows that under the same system performance, i.e., the same diversity gain, all the three network coding protocols outperform the traditional transmission scheme without network coding in terms of multiplexing gain. Our DMT analysis also exhibits the trends of the three network coding protocols' performance when multiplexing gain is changing from the lower region to the higher region. Monte-Carlo simulations verify the prediction of DMT.

• 한국전산유체공학회지
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• 제19권2호
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• pp.24-29
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• 2014

In this study, a parallel performance of CUPID-code has been investigated for both Ethernet and Infiniband network system to examine the effect of cache memory and network-speed. Bi-conjugate gradient solver of CUPID-code has been parallelised by using domain decomposition method and message passing interface (MPI). It is shown that the parallel performance of Ethernet-network system is worse than that of Infiniband-network system due to the slow network-speed and a small cache memory. It is also found that the parallel performance of each system deteriorates for a small problem due to the communication overhead, but the performance of Infiniband-network system is better than Ethernet-network system due to a much faster network-speed. For a large problem, the parallel performance depends less on network system.

• 유통과학연구
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• 제20권10호
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• pp.51-60
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• 2022

Purpose: The aim of this research is to study 1) the effects of internal factors (technological capability and entrepreneurial orientation) that affect Thailand's hotel business network capability. 2) the effects of external factors (government policy and trust relationship) that affect Thailand's hotel business network capability. 3) the impact of network capability on the firm performance. 4) the moderating effect of absorptive capacity between network capability and firm performance. Research design, data and methodology: The test model collected data from a mail survey of 164 hotel businesses in Thailand. The correlation and multiple regression were adopted to analyze and test the proposed hypotheses. Results: Interestingly, technological capability, entrepreneurship orientation, and trust relationship have a direct impact on network capability. However, network capability still does not have a significant relationship with firm performance in all dimensions. Surprisingly, the absorptive capacity does not have a moderating effect on the relationship of network capability on firm performance of hotel businesses in Thailand. Conclusions: This research found that the hotel business should focus on analyzing the external and internal environment as it affects network building, which will guide the creation of strategies for further increasing hotel distribution channels and competitive advantage.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.65-67
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• 2013

최근의 네트워크 장비들은 고성능이 요구되고, 또한 높은 네트워크 대역폭의 활용을 요구하고 있다. 이를 위해 점차 멀티 코어 프로세서를 사용한 고성능 네트워크 서버 장비를 개발 하는 추세이다. 이런 고성능과 높은 네트워크 처리율을 향상시키기 위한 방법으로 멀티 코어의 특성을 고려한 네트워크 서브시스템의 성능을 향상시키는 방법을 제시한다. 본 논문에서는 멀티 코어를 최대한 활용함으로 성능을 최적화 하고 통신 성능을 향상시키는 방법을 실험을 통해서 확인한다. 통신 프로세스의 성능 향상은 멀티 코어 프로세서 구조, 프로세스의 네트워크 집중도, 각 코어에 걸리는 오버헤드, 인터럽트 친화도에 따른 네트워크 처리량을 기반으로 해당 프로세스에 최적의 코어를 결정해 주도록 한다. 실험은 리눅스 커널에서 구현하였으며, 실험을 통해 네트워크 처리량을 30%까지 향상 시키고, 프로세서의 오버헤드는 최대 10%까지 줄여 리눅스 통신 프로세스의 성능 향상을 가져옴을 보여준다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.117-117
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• 2000

This paper presents experimental results for peformance management of a Profibus-FMS network. The performance management alms to maintain a uniform level of network performance at all stations under changing network traffic. The performance management algorithm monitors the performance of individual network stations and commands the stations to change their timer values in order to have comparable performance at all stations. In order to determine the amount of timer change, the algorithm employs a set of fuzzy rules. This algorithm has been evaluated on a Profibus network

• 한국정밀공학회지
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• 제11권4호
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• pp.138-147
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• 1994

Performance management of computer networks is intended to improve a given network performance in order for more efficient information exchange between subsystems of an integrated large-scale system. Improtance of performance management is growing as many function of the large- scale system depend on the quality of communication services provided by the network. The role of performance management is to manipulate the adjustable protocol parameters on line so that the network can adapt itself to a dynamic environment. This can be divided into two subtasks : performance evaluation to find how changes in protocol parameters affect the network performance and decision making to detemine the magnitude and direction of parameter adjustment. This paper is the second part of the two papers focusing on conceptual design, development, and evaluation of performance management for token bus networks. This paper specifically deals with the task of decision making which utilizes the principles of stochastic optimization and learning automata. The developed algorithm can adjuxt four timer settings of a token bus protocol based on the result of performance evaluation. The overall performance management has been evaluated for its efficacy on a network testbed.

• 한국도로학회논문집
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• 제20권1호
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• pp.35-45
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• 2018

PURPOSES : This study examines the performance changes of road networks according to the strength of a disaster, and proposes a method for estimating the quantitative resilience according to the road-network performance changes and damage scale. This study also selected high-influence road sections, according to disasters targeting the road network, and aimed to analyze their hazard resilience from the network aspect through a scenario analysis of the damage recovery after a disaster occurred. METHODS : The analysis was conducted targeting Sejong City in South Korea. The disaster situation was set up using the TransCAD and VISSIM traffic-simulation software. First, the study analyzed how road-network damage changed the user's travel pattern and travel time, and how it affected the complete network. Secondly, the functional aspects of the road networks were analyzed using quantitative resilience. Finally, based on the road-network performance change and resilience, priority-management road sections were selected. RESULTS : According to the analysis results, when a road section has relatively low connectivity and low traffic, its effect on the complete network is insignificant. Moreover, certain road sections with relatively high importance can suffer a performance loss from major damage, for e.g., sections where bridges, tunnels, or underground roads are located, roads where no bypasses exist or they exist far from the concerned road, including entrances and exits to suburban areas. Relatively important roads have the potential to significantly degrade the network performance when a disaster occurs. Because of the high risk of delays or isolation, they may lead to secondary damage. Thus, it is necessary to manage the roads to maintain their performance. CONCLUSIONS : As a baseline study to establish measures for traffic prevention, this study considered the performance of a road network, selected high-influence road sections within the road network, and analyzed the quantitative resilience of the road network according to scenarios. The road users' passage-pattern changes were analyzed through simulation analysis using the User Equilibrium model. Based on the analysis results, the resilience in each scenario was examined and compared. Sections where a road's performance loss had a significant influence on the network were targeted. The study results were judged to become basic research data for establishing response plans to restore the original functions and performance of the destroyed and damage road networks, and for selecting maintenance priorities.

• Journal of information and communication convergence engineering
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• 제19권4호
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• pp.241-247
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• 2021

Particulate matter has emerged as a serious global problem, necessitating highly reliable information on the matter. Therefore, various algorithms have been used in studies to predict particulate matter. In this study, we compared the prediction performance of neural network models that have been actively studied for particulate matter prediction. Among the neural network algorithms, a deep neural network (DNN), a recurrent neural network, and long short-term memory were used to design the optimal prediction model using a hyper-parameter search. In the comparative analysis of the prediction performance of each model, the DNN model showed a lower root mean square error (RMSE) than the other algorithms in the performance comparison using the RMSE and the level of accuracy as metrics for evaluation. The stability of the recurrent neural network was slightly lower than that of the other algorithms, although the accuracy was higher.

• 전기학회논문지
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• 제58권12호
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• pp.2532-2537
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• 2009

For defect characterization in steam generator tubes in nuclear power plant, artificial neural network has been extensively used to classify defect types. In this paper, we study the effectiveness of Bagging for improving the performance of neural network for the classification of tube defects. Bagging is a method that combines outputs of many neural networks that were trained separately with different training data set. By varying the number of neurons in the hidden layer, we carry out computer simulations in order to compare the classification performance of bagging neural network and single neural network. From the experiments, we found that the performance of bagging neural network is superior to the average performance of single neural network in most cases.

• 경영과학
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• 제19권1호
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• pp.179-188
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• 2002

Ventures through technological innovation are increasingly suggested as one of the main engines for economic growth that can help control inflation and black trade balance. The Purpose of this study is to extract the network performance factors for ventures according to ventures life cycle. For the Purpose, the existing studies were examined into start-up company, entrepreneurial firm, smell firms with competitive advantage against large firms, and ventures network activity. And 63 samples from ventures in Korea were taken and analyzed empirically. The analyses and results are (1) the actual conditions of network activity on ventures; (2) the investigation of relationship between network activity and performance of ventures by venture's life cycle through the observations of Korean ventures. From the results, It Is also found that factors such as external environment and a ventures life cycle have been considered as the main influences on the performance of ventures. In addition, limitations and suggestions for further studies are noted.