• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.326-338
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• 2003

The objective of a neural network design and model selection is to construct an optimal network with a good generalization performance. However, training data include noises, and the number of training data is not sufficient, which results in the difference between the true probability distribution and the empirical one. The difference makes the teaming parameters to over-fit only to training data and to deviate from the true distribution of data, which is called the overfitting phenomenon. The overfilled neural network shows good approximations for the training data, but gives bad predictions to untrained new data. As the complexity of the neural network increases, this overfitting phenomenon also becomes more severe. In this paper, by taking statistical viewpoint, we proposed an integrative process for neural network design and model selection method in order to improve generalization performance. At first, by using the natural gradient learning with adaptive regularization, we try to obtain optimal parameters that are not overfilled to training data with fast convergence. By adopting the natural pruning to the obtained optimal parameters, we generate several candidates of network model with different sizes. Finally, we select an optimal model among candidate models based on the Bayesian Information Criteria. Through the computer simulation on benchmark problems, we confirm the generalization and structure optimization performance of the proposed integrative process of teaming and model selection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7B
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• pp.585-597
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• 2004

In this paper, we propose the functional models of optical burst switching (OBS) routers to apply GMPLS (Generalized Multiprotocol Label Switching) to optical networks based on OBS. In addition, we introduce a connection admission control (CAC) algorithms which are operated in this models and can accommodate the required QoS. Firstly, the characteristics of current GMPLS and OBS for the optical Internet are basically considered. With this consideration, the models are proposed to accept OBS features which include the recognition of data boundary with control information and the statistical multiplexing in terms of bursts. Secondly, we use an offset time decision (OTD) algorithm on behalf of controlling the connection admission with taking QoS parameters such as burst loss rate(BLR) and service-differentiation ratio(SDR) into consideration. The proposed CAC algorithms use the offered load of LSP (Label Switched Path), wavelength information, and QoS parameters as inputs of OTD algorithm. A call setup request will be accepted when the offset time decided by OTD algorithm is reasonable for guaranteeing its requested QoS. Simulation is used for performance evaluation. Results show the proposed schemes can guarantee the required QoS and those are better than the previous one in terms of channel utilization.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.71-78
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• 2018

Transportation is gradually changing into the era of V2X and autonomous cars. Accurate judgement of traffic conditions is an important indicator of route choice or autonomous driving. There are many ways to use probes car such as taxis, as a way to identify accurate traffic conditions. These methods may vary depending on the characteristics of the probe vehicle, and there is a problem with the cost. The V2X vehicle can solve these problems and collect traffic information in real time. If all vehicles are of V2X vehicle, these issues are expected to be resolved briefly. However, if the communication information of a V2X vehicle is represented by a traffic representative in a traffic with only V2X, the traffic information of some V2X vehicles will be able to collect traffic information. To accomplish this, a virtual network and transport were created and various scenarios were performed through SUMO simulations. It has been analyzed that 3-5 % of V2 vehicles are capable of representative the road traffic characteristics. In the future, various follow-up studies are planned.

• Korean Journal of Construction Engineering and Management
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• v.7 no.1 s.29
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• pp.138-147
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• 2006

Construction companies have been interested in the construction duration which importantly affects the performance and the success of the construction projects in accordance with the systemic changes such as five days per week system, introduction of construction duration reduction bidding system and post sale system nowadays. It is also very important to estimate and forecast properly the construction duration as the construction companies compete for the projects in the situation of construction market reduction and the lowest bidding system. Recognizing the importance about the construction duration, the researches about comparing and analyzing or estiamting the construction duration have been performed. However, comparing studies about the construction duraion have been limited to the apartment and office building in domestic area. Many studies about forecasting construction duration have been performed through stochastic analysis and simulations. Little research has been addressed the comparison analysis of the real construction duration about the mix-use building and officetel building which occured according to the changes of the building requirements. Therefore, the objective of this study is to compare and analyze the real construction duration and the hypothetical construction duration about the mix-use building and officetel building of the domestic companies. Moreover, we select the most competitve construction company to get the strengths and analyze the competitive advatages of the construction companies about construction duration.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.12-21
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• 2012

IEEE 802.11 MAC protocol standard, DCF(CSMA/CA), is originally designed to ensure the fair channel access between mobile nodes sharing the local wireless channel. It has been, however, revealed that some misbehavior nodes transmit more data than other nodes through artificial means in hot spot area spreaded rapidly. The misbehavior nodes may modify the internal process of their MAC protocol or interrupt the MAC procedure of normal nodes to achieve more data transmission. This problem has been referred to as a selfish node problem and almost literatures has proposed methods of analyzing the MAC procedures of all mobile nodes to detect the selfish nodes. However, these kinds of protocol analysis methods is not effective at detecting all kinds of selfish nodes enough. This paper address this problem of detecting selfish node using Tsallis-Entropy which is a kind of statistical method. Tsallis-Entropy is a criteria which can show how much is the density or deviation of a probability distribution. The proposed algorithm which operates at a AP node of wireless LAN extracts the probability distribution of data interval time for each node, then compares the one with a threshold value to detect the selfish nodes. To evaluate the performance of proposed algorithm, simulation experiments are performed in various wireless LAN environments (congestion level, how selfish node behaviors, threshold level) using ns2. The simulation results show that the proposed algorithm achieves higher successful detection rate.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.4
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• pp.17-27
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• 2007

The enhanced distributed channel access (EDCA) of IEEE 802.11e has been standardized for supporting Quality of Service (QoS) in wireless LANs. In the EDCA, support of QoS can be achieved statistically by reducing the probability of medium access for lower priority traffics. In other words, it provides statistical channel access rather than deterministically prioritized access to high priority traffic. Therefore, lower priority traffics affect the performance of higher priority traffics. Consequently, at the high loads, the EDCA does not guarantee the QoS of multimedia applications such as voice and video even though it provides higher priority. In this paper, we propose a simple and effective scheme, called deterministic priority channel access (DPCA), for improving the QoS performance of the EDCA mechanism. In order to provide guaranteed priority channel access to multimedia applications, the proposed scheme uses a busy tone for limiting the transmissions of lower priority traffics when higher priority traffic has data packets to send. Performance of the proposed scheme is investigated by numerical analysis and simulation. Our results show that the proposed scheme outperforms the EDCA in terms of throughput, delay, jitter, and drop under a wide range of contention levels.

• Journal of the Korean Geophysical Society
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• v.3 no.3
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• pp.161-174
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• 2000

Bayesian inversion is a stable approach to infer the subsurface structure with the limited data from geophysical explorations. In geophysical inverse process, due to the finite and discrete characteristics of field data and modeling process, some uncertainties are inherent and therefore probabilistic approach to the geophysical inversion is required. Bayesian framework provides theoretical base for the confidency and uncertainty analysis for the inference. However, most of the Bayesian inversion require the integration process of high dimension, so massive calculations like a Monte Carlo integration is demanded to solve it. This method, though, seemed suitable to apply to the geophysical problems which have the characteristics of highly non-linearity, we are faced to meet the promptness and convenience in field process. In this study, by the Gaussian approximation for the observed data and a priori information, fast Bayesian inversion scheme is developed and applied to the model problem with electric well logging and dipole-dipole resistivity data. Each covariance matrices are induced by geostatistical method and optimization technique resulted in maximum a posteriori information. Especially a priori information is evaluated by the cross-validation technique. And the uncertainty analysis was performed to interpret the resistivity structure by simulation of a posteriori covariance matrix.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.5
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• pp.37-45
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• 2004

As Internet technologies are mature, many new applications that are different characteristics are emerging. Recently we see wide use of P2P(Peer to Peer) applications of which traffic shows different statistical characteristics compared with traditional application such as web(HTTP) and FTP(File Transfer Protocol). In this paper, we measured subscriber network of KT(Korea Telecom) to analyze P2P traffic characteristics. We show flow characteristics of measured traffic. We also estimate Hurst parameter of P2P traffic and compare self-similarity with web traffic. Analysis results indicate that P2P traffic is much bustier than web traffic and makes both upstream traffic and downstream traffic be symmetric. To predict parameters related QoS such as packet loss and delays we model P2P traffic using two self-similar traffic models and predict both loss probability and mm delay then compare their accuracies. With simulation we show that the self-similar traffic models we derive predict the performance of P2P traffic accurately and thus when we design a network or evaluate its performance, we can use the P2P traffic model as reference input traffic.

• Journal of the Korean Society for Marine Environment & Energy
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• v.14 no.2
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• pp.138-145
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• 2011

In this paper time series wave data are simulated by the Monte Calo method using random numbers to generate random phases of the wave signal. The simulated wave signasl are used to study the characteristics of freak waves. Various sea states are represented by combinations of the significant wave height $H_s$ defined in the spectrum method and the significant wave steepness $S_s$. For a fixed value of $S_s$, the probability of the occurrence of the freak wave is decreased as $H_s$ increases. For a fixed value of $H_s$ the probability of the occurrence of the freak wave increases as $S_s$ increases. The average value of the maximum wave height increase as $S_s$ increases, but the average height of freak wave remains the same and the value approaches two times of $H_s$. For the fixed value of $S_s$, average kurtosis of wave elevation increases as $H_s$ increases, but for a fixed $H_s$, the average kurtosis decreases as $S_s$ increases. The average of abnormality index(AI) is around 2.11 irregardless of $H_s$ and $S_s$. The maximum value of AI lies between 2.5 - 3.0. Therefore it is conjectured that AI maximum due to linear focusing is 3.0.

• Journal of Food Hygiene and Safety
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• v.24 no.1
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• pp.63-68
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• 2009

The statistics probability approach for microbial risk assessment (MRA) has been recognized as an efficient method because this probability approach, which can be presented the diversity, variability, and uncertainty for the environmental factors of food processing, provide better realistic results than point estimate. This study was conducted to determine of probability statistics for the environmental factors of the pork-cutting processing i.e. the processing time, the pork meat temperature, and processing room temperature etc. As the input parameters for the MRA, triangular distribution and normal distribution were selected as an efficient probability distribution model, these distributions were analyzed by the simulation. The simulation results showed the processing time estimated 53 min as mean (5% - 22 min and 95% - 98 min), pork meat temperature estimated $4.83^{\circ}C$ as mean (5% - $2.25^{\circ}C$ and 95% - $7.12^{\circ}C$, 48.78% exceed $5^{\circ}C$), and processing room temperature estimated $17^{\circ}C$ as mean (5% - $10.92^{\circ}C$ and 95% - $22.56^{\circ}C$, 71.178% exceed $15^{\circ}C$).