• Journal of Welding and Joining
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• v.31 no.5
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• pp.26-34
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• 2013

Boiler equipment in power plant is always being operated in harsh conditions and severely exposed to the extreme environment of high temperature. Therefore periodically the state of devices should be checked, diagnosed, and analyzed to ensure the reliability of the equipment. Traditionally, such a diagnosis is based one or two physical properties of the sample taken from the equipment like hardness, microstructure, etc.. However, to enhance the confidence of the diagnosis, it is necessary to synthesize those properties together. This paper is to propose such a synthetic procedure for T23 which was developed to be used in $569^{\circ}C/596^{\circ}C$ condition. Creep test and accelerated degradation test were performed simultaneously, and the physical properties such as microstructure, tensile strength, yield strength, hardness, and indentation properties were measured. This paper proposes a method of determining the remaining life by quantitative comparison. It will provide the basis of evaluating life assessment more objective and reliable.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.90-95
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• 2000

In order to enhance the confidence in the mobile communication and improve the performance of the bit error, we have been using coding method. In the case of this, we have to add redundancy bits by using error correcting codes such as the block or convolutional codes. However, the result of redundancy bits causes to improve confidence. but to drop the efficiency in the bandwidth. We have studied coding method that we are able to get the good coding gain without any changes in the data transmission rates in the limited bandwidth. In this Paper, we design TCM(Trellis Coded Modulation) which was proposed by Ungerboeck and MTCM(Multiple TCM), with multiplicity(k＝2), which was proposed by Divsalar, using the optimum encoder. As state number is varied in the optimum encoder, we compare the performance of the TCM and MTCM by using Monte Carlo simulation.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.3
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• pp.83-95
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• 1997

This study was conducted to derive optimal design floods by Gamma distribution models of the annual maximum series at eight watersheds along Geum , Yeong San and Seom Jin river Systems, Design floods obtained by different methods for evaluation of parameters and for plotting positions in the Gamma distribution models were compared by the relative mean errors and graphical fit along with 95% confidence interval plotted on Gamma probability paper. The results were analyzed and summarized as follows. 1.Adequacy for the analysis of flood flow data used in this study was confirmed by the tests of Independence, Homogeneity and detection of Outliers. 2.Basic statistics and parameters were calculated by Gamma distribution models using Methods of Moments and Maximum Likelihood. 3.It was found that design floods derived by the method of maximum likelihood and Hazen plotting position formular of two parameter Gamma distribution are much closer to those of the observed data in comparison with those obtained by other methods for parameters and for plotting positions from the viewpoint of relative mean errors. 4.Reliability of derived design floods by both maximum likelihood and method of moments with two parameter Gamma distribution was acknowledged within 95% confidence interval.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1147-1154
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• 2010

One of the important goals in data mining is to discover and decide the relationships between different variables. Association rules are required for this technique and it find meaningful rules by quantifying the relationship between two items based on association measures such as support, confidence, and lift. In this paper, we presented the evaluation criteria of weighted association rule considering item RFM scores as importance of items. Original RFM technique has been used most widely applied method using customer information to find the most profitable customers. And then we compared general association rule technique with weighted association rule technique through the simulation data.

• Structural Engineering and Mechanics
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• v.29 no.2
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• pp.187-201
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• 2008

Earthquake induced hysteretic energy demand for a structure can be used as a limiting value of a certain performance level in seismic design of structures. In cases where it is larger than the hysteretic energy dissipation capacity of the structure, failure will occur. To be able to select the limiting value of hysteretic energy for a particular earthquake hazard level, it is required to define the variation of hysteretic energy in terms of probabilistic terms. This study focuses on the probabilistic evaluation of earthquake induced worst failure probability and approximate confidence intervals for inelastic single-degree-of-freedom (SDOF) systems with a typical steel moment connection based on hysteretic energy. For this purpose, hysteretic energy demand is predicted for a set of SDOF systems subject to an ensemble of moderate and severe EQGMs, while the hysteretic energy dissipation capacity is evaluated through the previously published cyclic test data on full-scale steel beam-to-column connections. The failure probability corresponding to the worst possible case is determined based on the hysteretic energy demand and dissipation capacity. The results show that as the capacity to demand ratio increases, the failure probability decreases dramatically. If this ratio is too small, then the failure is inevitable.

• Nuclear Engineering and Technology
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• v.48 no.1
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• pp.144-152
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• 2016

Human capabilities, such as technical/nontechnical skills, have begun to be recognized as crucial factors for nuclear safety. One of the most common ways to improve human capabilities in general is training. The nuclear industry has constantly developed and used training as a tool to increase plant efficiency and safety. An integrated training framework was suggested for one of those efforts, especially during simulation training sessions of nuclear power plant operation teams. The developed training evaluation methods are based on measuring the levels of situation awareness of teams in terms of the level of shared confidence and consensus as well as the accuracy of team situation awareness. Verification of the developed methods was conducted by analyzing the training data of real nuclear power plant operation teams. The teams that achieved higher level of shared confidence showed better performance in solving problem situations when coupled with high consensus index values. The accuracy of nuclear power plant operation teams' situation awareness was approximately the same or showed a similar trend as that of senior reactor operators' situation awareness calculated by a situation awareness accuracy index (SAAI). Teams that had higher SAAI values performed better and faster than those that had lower SAAI values.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.109-116
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• 2018

In this study, we was compared the reliability performance of the software reliability model, which applied the Goel-Okumoto model developed using the exponential distribution, to the logarithmic function modifying the intensity function and the Rayleigh form. As a result, the log-type model is relatively smaller in the mean squared error compared to the Rayleigh model and the Goel-Okumoto model. The logarithmic model is more efficient because of the determination coefficient is relatively higher than the Goel-Okumoto model. The estimated determination coefficient of the proposed model was estimated to be more than 80% which is a useful model in the field of software reliability. Reliability has been shown to be relatively higher in the log-type model than the Rayleigh model and the Goel-Okumoto model as the mission time has elapsed. Through this study, software designer and users can identify the software failure characteristics using mean square error, decision coefficient. The confidence interval can be used as a basic guideline when applying the intensity function that reflects the characteristics of the lifetime distribution.

• Journal of Veterinary Clinics
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• v.36 no.6
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• pp.301-305
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• 2019

Wii^® balance board (WBB, Nintendo, Japan) is a device that can measure and record the center of pressure path length (CPPL) and 95% confidence ellipse area (Area 95) in relation to body sway. For evaluating measure of improvement after reconstruction of medial patellar luxation (MPL) in small sized dogs, A total of 6 dogs with limping and lameness gait attributed to Grade II, III or IV MPL were evaluated. Dogs were measured for difference of extension and flexion range of motion in the stifle (dROM), muscle mass, lameness, willingness to bear weight on the affected limb while standing, and willingness to lift the contralateral limb scores, CPPL and Area 95 of WBB on pre-surgery, post-surgery 4, 8 weeks. CPPL was significantly different on pre-surgery compared with post-surgery 8 weeks (p < 0.05). Except for CPPL, measured variables were significantly different on pre-surgery compared with post-surgery 4 and post-surgery 8 weeks (p < 0.01).

• Journal of the Korean Solar Energy Society
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• v.30 no.2
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• pp.46-53
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• 2010

In this paper the feasibility of wind power forecasting from MOS(Model Output Statistics) was evaluated at Gosan area in Jeju during February to Octoberin 2008. The observed wind data from wind turbine was compared with 24 hours and 48 hours forecasting wind data from MOS predicting. Coefficient of determination of measured wind speed from wind turbine and 24 hours forecasting from MOS was around 0.53 and 48 hours was around 0.30. These determination factors were increased to 0.65 from 0.53 and 0.35 from 0.30, respectively, when it comes to the prevailing wind direction($300^{\circ}\sim60^{\circ}$). Wind power forecasting ratio in 24 hours of MOS showed a value of 0.81 within 70% confidence interval and it also showed 0.65 in 80% confidence interval. It is suggested that the additional study of weather conditions be carried out when large error happened in MOS forecasting.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.179-184
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• 2021

In our study we performed a sentiments analysis from the images. For this purpose, we used 153 images that contain: people, animals, buildings, landscapes, cakes and objects that we divided into two categories: images that suggesting a positive or a negative emotion. In order to classify the images using the two categories, we created two models. The SAI-G model was created with Google's AutoML Vision service. The SAI-C model was created on the Clarifai platform. The data were labeled in a preprocessing stage, and for the SAI-C model we created the concepts POSITIVE (POZITIV) AND NEGATIVE (NEGATIV). In order to evaluate the performances of the two models, we used a series of evaluation metrics such as: Precision, Recall, ROC (Receiver Operating Characteristic) curve, Precision-Recall curve, Confusion Matrix, Accuracy Score and Average precision. Precision and Recall for the SAI-G model is 0.875, at a confidence threshold of 0.5, while for the SAI-C model we obtained much lower scores, respectively Precision = 0.727 and Recall = 0.571 for the same confidence threshold. The results indicate a lower classification performance of the SAI-C model compared to the SAI-G model. The exception is the value of Precision for the POSITIVE concept, which is 1,000.