• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.102-109
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• 2021

Since the 4th Industrial Revolution is implemented based on superintelligence, new insights must be provided through convergence studies with other fields to find optimal solutions to create new ideas. In this paper, we intende to present improvement measures for probability and statistical education, which is an athlete's subject on data analysis and processing in the ICT(Information & Communication Technologies) field in the era of superintelligence of the 4th industrial revolution. This paper aims to strengthen competitiveness through early development and commercialization of new technologies by presenting probabilities and statistical curriculums that require linkage in the ICT field. Second, it is necessary to present an educational system diagram linking probabilities and statistics in the ICT field to prepare a mid- to long-term response strategy for ICT education in response to innovative changes. Third, through a survey, we intend to present an effective educational operation plan linking probability and statistics to ICT major subjects by analyzing the perception of probability, statistical importance, and utilization of majors in this field.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.157-161
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• 2023

Reliability is one of the computable quality features of the software. To assess the reliability the software reliability growth models(SRGMS) are used at different test times based on statistical learning models. In all situations, Tradational time-based SRGMS may not be enough, and such models cannot recognize errors in small and medium sized applications.Numerous traditional reliability measures are used to test software errors during application development and testing. In the software testing and maintenance phase, however, new errors are taken into consideration in real time in order to decide the reliability estimate. In this article, we suggest using the Weibull model as a computational approach to eradicate the problem of software reliability modeling. In the suggested model, a new distribution model is suggested to improve the reliability estimation method. We compute the model developed and stabilize its efficiency with other popular software reliability growth models from the research publication. Our assessment results show that the proposed Model is worthier to S-shaped Yamada, Generalized Poisson, NHPP.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.8
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• pp.989-996
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• 2010

Statistical regression and/or interpolation models have been used for data analysis and response prediction using the results of the physical experiments and/or computer simulations in structural engineering fields. These models have been employed during the last decade to develop a variety of design methodologies. However, these models only handled responses with respect to space variables such as size and shape of structures and cannot handle time-variant dynamic responses, i.e. response varying with time. In this research, statistical space-time metamodels based on multiple response approach that can handle responses with respect to both space variables and a time variable are proposed. Regression and interpolation models such as the response surface model (RSM) and kriging model were developed for handling time-variant dynamic responses of structural engineering. We evaluate the accuracies of the responses predicted by the two statistical space-time metamodels by comparing them with the responses obtained by the physical experiments and/or computer simulations.

• Smart Structures and Systems
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• v.17 no.1
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• pp.107-122
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• 2016

We propose an effective methodology using electromechanical impedance characteristics for estimating the remaining tensile force of tendons and simultaneously detecting damages of the anchorage blocks. Once one piezoelectric patch is attached on the anchor head and the other is bonded on the bearing plate, impedance responses are measured through these two patches under varying tensile force conditions. Then statistical indices are calculated from the impedances, and two types of relationship curves between the tensile force and the statistical index (TE Curve) and between statistical indices of two patches (SR Curve) are established. Those are considered as database for monitoring both the tendon and the anchorage system. If damage exists on the bearing plate, the statistical index of patch on the bearing plate would be out of bounds of the SR curve and damage can be detected. A change in the statistical index by damage is calibrated with the SR curve, and the tensile force can be estimated with the corrected index and the TE Curve. For validation of the developed methodology, experimental studies are performed on the scaled model of an anchorage system that is simplified only with 3 solid wedges, a 3-hole anchor head, and a bearing plate. Then, the methodology is applied to a real scale anchorage system that has 19 strands, wedges, an anchor head, a bearing plate, and a steel duct. It is observed that the proposed scheme gives quite accurate estimation of the remaining tensile forces. Therefore, this methodology has great potential for practical use to evaluate the remaining tensile forces and damage status in the post-tensioned structural members.

• Structural Engineering and Mechanics
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• v.20 no.1
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• pp.85-110
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• 2005

This paper aims at formulating various statistical models for the study of a ten year Weigh-in-Motion (WIM) data collected from various WIM stations in Hong Kong. In order to study the bridge live load model it is important to determine the mathematical distributions of different load affecting parameters such as gross vehicle weights, axle weights, axle spacings, average daily number of trucks etc. Each of the above parameters is analyzed by various stochastic processes in order to obtain the mathematical distributions and the Maximum Likelihood Estimation (MLE) method is adopted to calculate the statistical parameters, expected values and standard deviations from the given samples of data. The Kolmogorov-Smirnov (K-S) method of approach is used to check the suitability of the statistical model selected for the particular parameter and the Monte Carlo method is used to simulate the distributions of maximum value stochastic processes of a series of given stochastic processes. Using the statistical analysis approach the maximum value of gross vehicle weight and axle weight in bridge design life has been determined and the distribution functions of these parameters are obtained under both free-flowing traffic and dense traffic status. The maximum value of bending moments and shears for wide range of simple spans are obtained by extrapolation. It has been observed that the obtained maximum values of the gross vehicle weight and axle weight from this study are very close to their legal limitations of Hong Kong which are 42 tonnes for gross weight and 10 tonnes for axle weight.

• Computers and Concrete
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• v.16 no.6
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• pp.919-932
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• 2015

This paper presents a new method for assessing the three-point-bending (3PB) strength of mortar beams in a non-destructive manner, based on neural network (NN) models. The models are based on the radial basis function (RBF) architecture and the fuzzy means algorithm is employed for training, in order to boost the prediction accuracy. Data for training the models were collected based on a series of experiments, where the cement mortar beams were subjected to various bending mechanical loads and the resulting pressure stimulated currents (PSCs) were recorded. The input variables to the NN models were then calculated by describing the PSC relaxation process through a generalization of Boltzmannn-Gibbs statistical physics, known as non-extensive statistical physics (NESP). The NN predictions were evaluated using k-fold cross-validation and new data that were kept independent from training; it can be seen that the proposed method can successfully form the basis of a non-destructive tool for assessing the bending strength. A comparison with a different NN architecture confirms the superiority of the proposed approach.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.8
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• pp.643-650
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• 2014

Gear transmission system is widely applied in engineering. As the problem of contact fatigue, wear, lubrication failure etc, the condition of gear teeth contacts will be worse. The vibration and sound signals in the gear system will be affected by the some failures like scuffing, abrasive wear and spalling due to the deterioration of gear teeth surface. By studying the estimation of specific film thickness, measurement of reduction in tooth thickness, visual examination of wear mechanisms on the gear teeth and their effects on the statistical parameters of vibration and sound signals, the research obtained the satisfactory results on accessing the surface fatigue wear in a spur gear system. The paper utilizes the relationship between statistical parameters obtained from sound signals and Stribeck curve to confirm the hypothesis of dependency of surface fatigue wear, specific film thickness.

• Journal of Construction Engineering and Project Management
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• v.2 no.2
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• pp.53-60
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• 2012

Accurate assessment of $CO_2$ emission from buildings requires gathering $CO_2$ emission data of various construction materials. Unfortunately, the amount of available data is limited in most countries. This study was conducted to present the $CO_2$ emission data of concrete, which is the most important construction material in Korea, by conducting a statistical analysis of the concrete mix proportion. Finally, regression models that can be used to estimate the $CO_2$ emission of concrete in all strengths were developed, and the validity of these models was evaluated using 24 and 35MPa concrete data. The validation test showed that the error ratio of the estimated value did not exceed a maximum of 5.33%. This signifies that the models can be used in acquiring the $CO_2$ emission data of concrete in all strengths. The proposed equations can be used in assessing the environmental impact of various construction structural designs by presenting the $CO_2$ emission data of all concrete types.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2124-2141
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• 2018

Recent studies have revealed the efficacy of incorporating delayed channel state information at transmit side (CSIT) in transmission scheme design. This paper focuses on transmit precoder design to maximize the ergodic sum-rate in a two-user Multiple-Input Single-Output (MISO) system with delayed and statistical CSIT. A new transmit strategy which precodes signals in all transmit slots is proposed in this paper, denoted as all time-slots precoding Alternative MAT (AAMAT). There is a common procedure in conventional delayed-CSIT based schemes, which is retransmitting the overheard interferences. Since the retransmitting signal is intended to both users, all previous schemes tend to use only one antenna. We however figure out an improvement in spectral efficiency could be realized if all antennas can be utilized. In this paper, we detail the design of the procoder which enabling all antennas and also we compute a lower bound of the ergodic sum-rate in an ideal condition. In addition, simulation results demonstrate the superiority of our proposed scheme.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.38-49
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• 2012

In this study, we analyze statistical characteristics of influent water quality in Daejeon waste water treatment plant and apply a stochastic model for data generation. In the analysis, the influent water quality data from year 2003 to 2008, except for year 2006, are used. Among water quality variables, we find strong correlations between BOD and T-N; T-N and T-P; BOD and T-P; $COD_{Mn}$ and T-P; and BOD and $COD_{Mn}$. We also find that different water quality variables follow different theoretical probability distribution functions, which also depends on whether the seasonal cycle is removed. Finally, we generate the influent water quality data using the multi-season 1st Markov model (Thomas-Fiering model). With model parameters calibrated for the period 2003~2005, the generated data for 2007~2008 are well compared with observed data showing good agreement in general. BOD and T-N are underestimated by the stochastic model. This is mainly due to the statistical difference in observed data itself between two periods of 2003~2005 and 2007~2008. Therefore, we expect the stochastic model can be applied with more confidence in the case that the data follows stationary pattern.