• The Journal of Society for e-Business Studies
• /
• v.6 no.2
• /
• pp.25-38
• /
• 2001

ATM is the transport method for the broadband integrated services digital networks(B-ISDN). It may replace existing LAN, MAN and WAN technologies such as CSMA/CD, FDDI, Frame relay, X.25, etc. But it is more complicate than existing network technologies. One of the main difficulties in ATM network is performance management. Specifically, the problems are evaluating the performance and tuning the values of the performance parameters, The goal of this paper is to introduce a system architecture designed for ATM network performance management, The major ingredients of the system are generic performance parameters In be measured from ATM network, performance evaluation models and decision criteria concerning the network performance. In this paper, general requirements for performance management application in ATM network are discussed.

• Journal of the Korean Society for Precision Engineering
• /
• v.11 no.4
• /
• pp.126-137
• /
• 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. Importance of perfomance management is growing as many functions 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 determine the magnitude and direction of parameter adjustment. This paper is the first 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 performance evaluation which utilizes the principle of perturbation analysis of discrete event dynamic systems. The developed algorithm can estimate the network performance under a perturbed protocol parameter setting from observations of the network operations under a nominal parameter setting.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.6B
• /
• pp.993-1001
• /
• 2000

This research features a method that quantitatively evaluates the performance of edge detection algorithms. Contrary to conventional methods that evaluate the performance of edge detection as a function of the amount of noise added to he input image, the proposed method is capable of assessing the performance of edge detection algorithms based on chosen parameters that influence the performance of edge detection. We have proposed a quantitative measure, called average performance index, that compares the average performance of different edge detection algorithms. We have applied the method to the commonly used edge detectors, Sobel, LOG(Laplacian of Gaussian), and Canny edge detectors for noisy images that contain straight line edges and curved line edges. Two kinds of noises i.e, Gaussian and impulse noises, are used. Experimental results show that our method of quantitatively evaluating the performance of edge detection algorithms can facilitate the selection of the optimal dge detection algorithm for a given task.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2015.08a
• /
• pp.132-132
• /
• 2015

Virtual metrology (VM) model based on plasma information (PI) parameter for C4F8 plasma-assisted oxide etching processes is developed to predict and monitor the process results such as an etching rate with improved performance. To apply fault detection and classification (FDC) or advanced process control (APC) models on to the real mass production lines efficiently, high performance VM model is certainly required and principal component regression (PCR) is preferred technique for VM modeling despite this method requires many number of data set to obtain statistically guaranteed accuracy. In this study, as an effective method to include the 'good information' representing parameter into the VM model, PI parameters are introduced and applied for the etch rate prediction. By the adoption of PI parameters of b-, q-factors and surface passivation parameters as PCs into the PCR based VM model, information about the reactions in the plasma volume, surface, and sheath regions can be efficiently included into the VM model; thus, the performance of VM is secured even for insufficient data set provided cases. For mass production data of 350 wafers, developed PI based VM (PI-VM) model was satisfied required prediction accuracy of industry in C4F8 plasma-assisted oxide etching process.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.3
• /
• pp.273-283
• /
• 2000

In this paper we suggest an optimal design method of Fuzzy-Neural Networks(FNN) model for complex and nonlinear systems. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM(Hard C-Means) Clustering Algorithm to find initial parameters of the membership function. The parameters such as parameters of membership functions learning rates and momentum weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. According to selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity (distribution of I/O data we show that it is available and effective to design and optimal FNN model structure with a mutual balance and dependency between approximation and generalization abilities. This methodology sheds light on the role and impact of different parameters of the model on its performance (especially the mapping and predicting capabilities of the rule based computing). To evaluate the performance of the proposed model we use the time series data for gas furnace the data of sewage treatment process and traffic route choice process.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.5
• /
• pp.79-84
• /
• 2017

This paper is a multi-input multi-path (Multiple-input multiple-output: MIMO) using a space-alternating generalized expectation maximization(SAGE) algorithm in the parameter channel and determine the channel estimation performance. Estimated by the algorithm, SAGE time-varying channel environment, the channel parameters estimated from the parameters of the channel measured in the island region 781 of the band in order to compare the performance and compares the original data. This allows you to check the performance of the algorithm SAGE and is highly stable to delay spread (Delay Spread), the diffusion angle of arrival (Arrive of Angular Spread) performance in terms of accuracy down through the SAGE algorithm for estimating a more general calculation parameters.

• International Journal of Air-Conditioning and Refrigeration
• /
• v.17 no.2
• /
• pp.68-73
• /
• 2009

In this paper, a numerical study has been carried out to investigate the influence of volute geometries on the performance of a sirocco fan. In order to achieve an optimum volute design and explain the interactions between the different geometric configurations in the volute system, three-dimensional computational fluid dynamics and the 'design of experiment' method have been applied. Several geometric parameters, such as the volute expansion angle, the cut-off position and the bell mouth shape, are employed to improve efficiency and performance. $2^k$ factorial designs were performed to screen the most influential parameters and interactions, and showed that the cut-off position and the bell mouth shape are the most significant parameters. The optimum design was selected as a result of the response surface methodology, and effects of these parameters and their interactions were presented. From the results of computational analyses and experimental data, the performance and efficiency of the sirocco fan were successfully improved. Also, detailed effects of geometric variables of the volute system on the fan performance were discussed.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.13 no.4
• /
• pp.135-144
• /
• 2005

The Effects of intake swirl and combustion parameters on the performance and emission characteristics in a V8 type turbocharged intercooler D.I. diesel engine of the displacement $16.7\iota$ were studied experimentally in this paper. Generally the swirl in the combustion process of diesel engine promotes mixing of the injection fuel and the intake air. Also, TCI diesel engine is put to practically use intercooler in order to increase boost efficiency which is cooled boost air. As a result of steady flow test, when the swirl ratio is increased, the mean flow coefficient is decreased, whereas the Gulf factor is increased. And through engine test, its can be effected to meet performance and emission by optimizing the main parameters; the swirl ratio is 2.25, compression ratio is 17.5, combustion bowl is re-entrant $8.5^{\circ}$, nozzle hole diameter is $\phi0.33^{\ast}3+\phi0.35^{\ast}2$, injection timing is BTDC $12^{\circ}CA$ and turbocharger is T02 model which are compressor 0.6A/R+46trim and turbine 1.0A/R+57trim.

• Explosives and Blasting
• /
• v.25 no.1
• /
• pp.67-77
• /
• 2007

The drill monitoring data are useful for the detection of abrupt and unexpected changes in ground renditions. This paper introduces a new approach to how drill performance parameters can be used for the prediction of quantitative rock mass properties ahead of tunnel face and the blasting design. The drill monitoring parameters available for the predictions include the instantaneous advance speed, thrust force, torque, tool pressure and penetration rate. The assessment of the drill monitoring parameters will be able to build a database provided that in-situ drill monitoring informations are accumulated and enable us to make a reasonable blast design based on quantitative assessment of rock mass.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.38 no.1
• /
• pp.139-152
• /
• 2013

The purpose of this study is to claim the validity of tuning the architecture of neural network models for multi-class classification. A neural network model for multi-class classification is basically constructed by building a series of neural network models for binary classification. Building a neural network model, we are required to set the values of parameters such as number of hidden nodes and weight decay parameter in advance, which draws special attention as the performance of the model can be quite different by the values of the parameters. For better performance of the model, it is absolutely necessary to have a prior process of tuning the parameters every time the neural network model is built. Nonetheless, previous studies have not mentioned the necessity of the tuning process or proved its validity. In this study, we claim that we should tune the parameters every time we build the neural network model for multi-class classification. Through empirical analysis using wine data, we show that the performance of the model with the tuned parameters is superior to those of untuned models.