• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.469-474
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• 1997

To provide tile information ell severe accident progression is very important for advanced or new type of nuclear power plant (NPP) design. A parametric study, therefore was performed to investigate the effect of thermal hydraulic design parameters ell severe accident progression of pressurized water reactors (PWRs), Nine parameters, which are considered important in NPP design or severe accident progression, were selected among the various thermal hydraulic design parameters. The backpropagation neural network (BPN) was used to determine parameters, which might more strongly affect the severe accident progression, among mile parameters. For training. different input patterns were generated by the latin hypercube sampling (LHS) technique and then different target patterns that contain core uncovery time and vessel failure time were obtained for Young Gwang Nuclear (YGN) Units 3&4 using modular accident analysis program (MAAP) 3.0B code. Three different severe accident scenarios, such as two loss of coolant accidents (LOCAs) and station blackout(SBO), were considered in this analysis. Results indicated that design parameters related to refueling water storage tank (RWST), accumulator and steam generator (S/G) have more dominant effects on the progression of severe accidents investigated, compared to tile other six parameters.

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.485-493
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• 2007

This paper deals with the problem of detection of induction motor incipient faults. Artificial Neural Network (ANN) approach is applied to detect two types of incipient faults (1). Interturn insulation and (2) Bearing wear faults in single-phase induction motor. The experimental data for five measurable parameters (motor intake current, rotor speed, winding temperature, bearing temperature and the noise) is generated in the laboratory on specially designed single-phase induction motor. Initially, the performance is tested with two inputs i.e. motor intake current and rotor speed, later the remaining three input parameters (winding temperature, bearing temperature and the noise) were added sequentially. Depending upon input parameters, the four ANN based fault detectors are developed. The training and testing results of these detectors are illustrated. It is found that the fault detection accuracy is improved with the addition of input parameters.

• International Journal of Industrial Entomology and Biomaterials
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• v.20 no.2
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• pp.69-74
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• 2010

Feeding is an important aspect of insect nutrition which in turn supports growth, development, reproduction and survival. The impact of quantitative feeding on nutritional parameters of fifth instar Antheraea mylitta larvae was studied by providing fresh leaves of Terminalia tomentosa for 1 to 4 times a day. All the parameters improved upon providing fresh diets more times over the single diet (1FD). The absolute body weight increased with increase in number of feeds/day significantly (P<0.001). While the maximum weight recorded was 29.61 g in 1FD, the respective weights for two feeds/day (2FD), three feeds/day (3FD) and four feeds/day (4FD) were 39.41 g, 40.63 g and 42.66 g respectively. Feeding period and instar duration were declined (P<0.001) and survival increased significantly (P<0.001) upon increase in the number of diets. Nutritional indices like ingestion, digestion, relative consumption rate (RCR), relative growth rate (RGR) and gain in body weight increased significantly with the increase in number of feeds/day, but approximate digestibility (AD) and efficiency of conversion of ingested food (ECI) declined, while efficiency of conversion of digested food (ECD) did not change.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.44-51
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• 1998

Two-step neural network is designed for determining electrical discharge machining parameters in low erosion. The first neural network, which is used as a classification network, checks whether the current conditions are appropriate to electrical discharge machining in low tool erosion. If the conditions are appropriate to EDM in low erosion, suitable EDM parameters are generated by the second neural network. Theoretically known EDM conditions are produced and also utilized for training the second neural network. The trained neural network is tested how well suitable EDM machining conditions are generated under unknown machining situations Experimental result shows that the proposed two-step neural network approach could be effectively used for determining EDM parameters in low tool erosion. The results also have a practical contribution to EDM area in that it could be applied for maintaining low tool wear as well as obtaining maximum machining rates simultaneously.

• Journal of Sensor Science and Technology
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• v.30 no.5
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• pp.286-289
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• 2021

Image classification is one of the fundamental applications of computer vision. It enables a system to identify an object in an image. Recently, image classification applications have broadened their scope from computer applications to edge devices. The convolutional neural network (CNN) is the main class of deep learning neural networks that are widely used in computer tasks, and it delivers high accuracy. However, CNN algorithms use a large number of parameters and incur high computational costs, which hinder their implementation in edge hardware devices. To address this issue, this paper proposes a lightweight image classifier that provides good accuracy while using fewer parameters. The proposed image classifier diverts the input into three paths and utilizes different scales of receptive fields to extract more feature maps while using fewer parameters at the time of training. This results in the development of a model of small size. This model is tested on the CIFAR-10 dataset and achieves an accuracy of 90% using .26M parameters. This is better than the state-of-the-art models, and it can be implemented on edge devices.

• Journal of Life Science
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• v.22 no.5
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• pp.569-574
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• 2012

This study was conducted to investigate the effect of exercise on oxidative stress, nerve growth, and hepatocyte growth factors in obese children. After 12 weeks of aerobic exercise training, the aforementioned parameters before and after the training were compared. As a result, the nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) were shown to be lower in the OT than in the NT before and after the training, respectively ($p$ <0.05). The NGF was shown to have increased in both groups after the training ($p$ <0.05). The hepatocyte growth factor (HGF) was shown to be higher in the OT than in the NT before the training ($p$ <0.05), with no difference found afterwards. The malondialdehyde (MDA), ox-LDL, and 8-OHdG (Oxo-2'-deoxyguanosine) were shown to be higher in the OT than in the NT ($p$ <0.05). For ox-LDL, a difference was found between before and after the training ($p$ <0.05). The results of this study showed that obesity induced oxidative stress and caused the abnormalities of nerve and HGF secretion in obese children, and that the 12 weeks of aerobic exercise increased NGF levels, thereby promoting the development of neurogenesis in children.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.8
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• pp.3319-3323
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• 2015

Background: Community pharmacists play an important role in tobacco control and adequate training on smoking cessation is essential. Materials and Methods: A quasi-experimental pre-test/post-test design was used. A one-day workshop on smoking cessation organized by Indonesian Pharmacists Association as part of PCE program was offered to 133 community pharmacists. The workshop consisted of a 3-hour lecture and a 3-hour role-play session. Pre-training and post-training surveys assessed the impact of training on parameters including knowledge, perceived role and self-efficacy with respect to smoking cessation counseling practices. Intention and ability to perform counseling using the 5A framework was assessed after training only. Results: After PCE, knowledge score significantly increased from $24.9{\pm}2.58$ to $35.7{\pm}3.54$ (p<0.001). Perceived role and self-efficacy in smoking cessation counseling also significantly increased from $25.8{\pm}2.73$ to $28.7{\pm}2.24$, and $27.6{\pm}4.44$ to $32.6{\pm}3.63$, respectively (p<0.001). After the workshop, most participants were willing to ask, advise, and assess patients who ready to quit, but were still less likely to assist in quitting plans and arranging follow up counseling. More than 75% pharmacists were able to perform cessation counseling and 65% of them can completely perform a 5A brief intervention. Conclusions: PCE can enhance pharmacists' knowledge, perceived role, self-efficacy in cessation counseling practices, and create willingness and ability to perform cessation counseling. Future training is recommended to improve skills in assisting quitting plans and arranging follow up.

• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.195-208
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• 1999

In the classification of satellite images, the representative of training of classes is very important factor that affects the classification accuracy. Hence, in order to improve the classification accuracy, it is required to optimize pre-classification stage which determines classification parameters rather than to develop classifiers alone. In this study, the normality of training are calculated at the preclassification stage using SPOT XS and LANDSAT TM. A correlation coefficient of multivariate Q-Q plot with 5% significance level and a variance of initial training are considered as an object function of genetic algorithm in the training normalization process. As a result of normalization of training using the genetic algorithm, it was proved that, for the study area, the mean and variance of each class shifted to the population, and the result showed the possibility of prediction of the distribution of each class.

• Translational and Clinical Pharmacology
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• v.26 no.4
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• pp.166-171
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• 2018

Although there are many commercially available training software programs for pharmacokinetics, they lack flexibility and convenience. In this study, we develop simulation software to facilitate pharmacokinetics education. General formulas for time courses of drug concentrations after single and multiple dosing were used to build source code that allows users to simulate situations tailored to their learning objectives. A mathematical relationship for a 1-compartment model was implemented in the form of differential equations. The concept of population pharmacokinetics was also taken into consideration for further applications. The source code was written using R. For the convenience of users, two types of software were developed: a web-based simulator and a standalone-type application. The application was built in the JAVA language. We used the JAVA/R Interface library and the 'eval()' method from JAVA for the R/JAVA interface. The final product has an input window that includes fields for parameter values, dosing regimen, and population pharmacokinetics options. When a simulation is performed, the resulting drug concentration time course is shown in the output window. The simulation results are obtained within 1 minute even if the population pharmacokinetics option is selected and many parameters are considered, and the user can therefore quickly learn a variety of situations. Such software is an excellent candidate for development as an open tool intended for wide use in Korea. Pharmacokinetics experts will be able to use this tool to teach various audiences, including undergraduates.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.2
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• pp.156-170
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• 2023

Objectives: This study conducted practical training to improve the proper usage of personal protective equipment(PPE), which greatly impacts workplace safety and health management. Personal protective equipment education was conducted through active participation, without theoretical modules, and aimed to identify the effects of repeated practical education and determine ways to increase participant satisfaction. Methods: Study data were analyzed using the IBM SPSS Statistics ver.29 software. First, participants' general characteristics were analyzed with frequency analysis. Second, the normality and equality of variances (Leven's test) were tested for the dependent variables prior to statistical analyses to determine the use of parametric tests. In general, normality is assumed when the sample size is 30 or more per the central limit theorem (Park et al., 2014). As our sample size of health management workers was 43, normality can be assumed. However, to ensure rigor of the study, we examined skewness and kurtosis. The results confirmed that the data were normally distributed. Third, the effects of repeated PPE training were analyzed using paired t-tests. Fourth, differences in satisfaction with PPE training according to the safety and health job position and safety and health certification were analyzed with t-test and Welch's t-test. For parameters that did not meet the assumption of equal variances, the Welch's t-test was performed. Results: Repeated PPE training improved the educational outcomes, and the improvements were significant in the 1st and 2nd respiratory PPE and safety and hygiene PPE training evaluations (p<.001). In terms of safety and health job position, repeated training led to improvements in educational outcomes, with significant improvements observed among supervisors and specialized health management institution workers in the 1st and 2nd training evaluations (p<.005). In terms of safety certification, repeated training led to improvements in educational outcomes, with significant improvements observed among both certified and non-certified individuals (p<.005). Regarding satisfaction with PPE training according to safety and health job positions, specialized health management institution workers showed greater satisfaction than supervisors, with significant differences in the satisfaction for expertise of lecture, work relevance, and lecturer's attitude (p<.001). Regarding satisfaction with PPE training according to safety and health certification, satisfaction was higher among certified individuals, with significant differences in satisfaction for work relevance and lecture attitude (p<.05) Conclusions: PPE education should be recommended to be provided as practical training. Repeated training can enhance educational outcomes for individuals with inadequate knowledge and understanding of PPE prior to education. For individuals with high levels of pre-existing knowledge and understanding of PPE, the results show that various training experiences should be provided to enhance their satisfaction. Therefore, it suggests that the workplace should actively seek educational media and methods to acquire expertise and skills in wearing personal protective equipment and improve the ability to use