• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.191-203
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• 2019

The problem of examining how well an assumed distribution fits the data of a sample is of significant and must be examined prior to any inferential process. The observed failure time data of items are often not wholly available in reliability and life-testing studies. Lowering the expense and period associated with tests is important in statistical tests with censored data. Goodness-of-fit tests for perfect data can no longer be used when the observed failure time data are progressive Type II censored (PC) data. Therefore, we propose goodness-of-fit test statistics and a graphical method based on generalized Lorenz curve for PC data from a location-scale distribution. The power of the proposed tests is then assessed through Monte Carlo simulations. Finally, we analyzed two real data set for illustrative purposes.

• Journal of Korea Entertainment Industry Association
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• v.14 no.2
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• pp.109-118
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• 2020

This study examines the relative usefulness of the TPB and Extended TPB with the addition of the "Battery" variable to participants in marine sports experiences. The characteristics of behavioral theories (attitude, subjective norms, perceived behavioral control, and revisit intention) were compared. A total of 420 questionnaires were distributed and surveyed using the convenience sampling method to the general public who participated in the marine sports experience in S city in 2019. Finally, 385 copies of valid samples were extracted, except for the questionnaire. The following analyzes were performed using SPSS 21.0 and AMOS 21.0. Frequency analysis, confirmatory factor analysis, concept reliability, AVE value, Cronbach's α correlation analysis, hierarchical regression analysis, and independent sample t-test were performed. First, in the TPB, three predictors were found to have a positive effect on revisit intention. Attitudes, subjective norms, and prior knowledge, except for behavioral control, were found to have a positive effect. Second, the explanatory power to explain the return intention was 51.8% (3.3% more than plan behavior theory, p = .000). It can be seen that when prior knowledge is added as a new variable, it is an important factor in explaining intention to return. Third, prior knowledge variables were classified into high and low groups to compare the characteristics of the extended planning behavior theory. The results of the analysis showed that the group with higher prior knowledge had a higher mean value for the constituent variables of the extended planning behavior theory.

• Communications of Mathematical Education
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• v.35 no.4
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• pp.359-376
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• 2021

In this study, in accordance with the research trend that the learner's emotions expressed positively or negatively in mathematics learning or the learner's beliefs and attitudes toward mathematics learning affect the results of mathematics learning, the learner's emotions and affective factors are analyzed in the learner's own learning. A power that can be adjusted according to a goal or purpose is needed, and I tried to explain this power through meta-affect. To this end, the meaning of the definitional and conceptual factors of meta-affect was explored based on prior studies. Affective factors of meta-affect were viewed as emotions, attitudes, and beliefs, and conceptual factors of meta-affect were viewed as awareness, evaluating, controlling, utilization, and monitoring, and the meaning of each conceptual factor was also defined. In this study, the conceptual factors and meanings of meta-affect in terms of using them to help in learning mathematics by controlling them, beyond the identification or examination of the characteristics of the affective factors, which are meaningfully dealt with in the field of mathematics education.

• Journal of Digital Contents Society
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• v.17 no.3
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• pp.157-164
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• 2016

Solar power generation influenced by the weather. Using the weather forecast information, it is possible to predict the short-term solar power generation in the future. However, in limited circumstances such as islands or mountains, it can not be use weather forecast information by the disconnection of the network, it is impossible to use solar power generation prediction model using weather forecast. Therefore, in this paper, we propose a system that can predict the short-term solar power generation by using the information that can be collected by the system itself. We developed a short-term prediction model using the prior information of temperature and power generation amount to improve the accuracy of the prediction. We showed the usefulness of proposed prediction model by applying to actual solar power generation data.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.4
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• pp.25-32
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• 2011

A control system has been developed by korean engineers for 500MW korean standard type fossil power plant with the advent of retrofit of old control system. The developed control system is required to verify in terms of function and reliability prior to application to a power plant because a power plant is a very important facility in the industry. It is difficult to secure the enough period for installing the control system and commissioning due to the gradual increase of power demand and competitive power market environment. It is essential to verify the control system in order to reduce trial and error cases during overhaul period for application of control system to the power plant. This paper shows the case study of a functional test of a station of control system for power plant.

• Journal of Ocean Engineering and Technology
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• v.18 no.6 s.61
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• pp.8-15
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• 2004

Wave power distribution is investigated to determine the optimal sites for wave power generation at Jeju sea which has the highest wave energy density in the Korean coastal waters. The spatial and seasonal variation of wave power per unit length is calculated in the Jeju sea area based on the monthly mean wave data from 1979 to 2002 which is produced by the SWAN wave model simulation in prior research. The selected favorable locations for wave power generation are compared in terms of magnitude of wave energy density and distribution characteristics of wave parameters. The results suggest that Chagui-Do is the most optimal site for wave power generation in the Jeju sea. The seasonal distribution of wave energy density reveals that the highest wave energy density occurs in the northwest sea in the winter and it is dominated by wind waves, while the second highest one happens at south sea in the summer and it is dominated by a swell sea. The annual average of wave energy density shows that it gradually increases from east to west of the Jeju sea. At Chagui-Do, the energy density of the sea swell sea is relatively uniform while the energy density of the wind waves is variable and strong in the winter.

• Journal of Advanced Navigation Technology
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• v.13 no.4
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• pp.566-576
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• 2009

The primary purpose of this study is not only to understand the concept of event service quality but also to identify the service experimental factor for the better measure of sales promotion event service quality. The major findings from the study were as follows: There was difference influence power in event service quality, the experimental factor is more important than prior service quality factors such as reliability, assurance, tangibles, empathy and responsiveness. Also, customer's satisfaction was influenced by their behavioral intention such as overall reusing intention and recommendation intention. In conclusion, this study is especially meaningful that experimental factor is more important than prior service quality factors and will help the airline marketing staff in charge to build up their strategy for maintaining customer. And it is hoped that this study has been helpful to comprehend relationship among the service quality factor that have strong effects on increasing airline's profitability.

• The Journal of Industrial Distribution & Business
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• v.13 no.10
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• pp.15-22
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• 2022

Purpose: In the manufacturing sector, VDI (Virtual Desktop Infrastructure) offers advantages to the organizations, such as allowing manufacturers access to the system from any location. The most important things are understanding what the user needs, avoiding under-provisioning, network preparation. This research is to provide useful practical l implementations of VDI in manufacturing industry based on numerous prior studies. Research design, data and methodology: This research has conducted the qualitative content analysis (QCA). When conducting this research, the present author assumed that it is crucial to create the procedures and processes that will be used to acquire the text data needed to structure or solve problems. Results: According to the prior literature analysis, there are five suggestions to implement successful VDI for manufacturing sector. The five solutions are (1) Creation of the machines, (2) Direct users to an available 'Virtual Machine', (3) 'Virtual Machine Power Management', (4) Performance monitoring, and (5) Review security. Conclusions: The research clearly details how VDI can be implemented on a manufacturer platform and how it can be connected to hundreds of users. The author can conclude that connecting hundreds of users can be done using the remote connection of devices and encourage manufacturers to work from different areas.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.17-28
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• 2023

Today Agriculture segment is a significant supporter of Indian economy as it represents 18% of India's Gross Domestic Product (GDP) and it gives work to half of the nation's work power. Farming segment are required to satisfy the expanding need of food because of increasing populace. Therefore, to cater the ever-increasing needs of people of nation yield prediction is done at prior. The farmers are also benefited from yield prediction as it will assist the farmers to predict the yield of crop prior to cultivating. There are various parameters that affect the yield of crop like rainfall, temperature, fertilizers, ph level and other atmospheric conditions. Thus, considering these factors the yield of crop is thus hard to predict and becomes a challenging task. Thus, motivated this work as in this work dataset of different states producing different crops in different seasons is prepared; which was further pre-processed and there after machine learning techniques Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, Ridge Regression, Polynomial Regression, Linear Regression are applied and their results are compared using python programming.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.86-92
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• 2016

Upon detecting a frequency event in a power system, the stepwise inertial control (SIC) of a wind turbine generator (WTG) instantly increases the power output for a preset period so as to arrest the frequency drop. Afterwards, SIC rapidly reduces the WTG output to avert over-deceleration (OD). However, such a rapid output reduction may act as a power deficit in the power system, and thereby cause a second frequency dip. In this paper, a hybrid reference function for the stable SIC of a doubly-fed induction generator is proposed to prevent OD while improving the frequency nadir (FN). To achieve this objective, a reference function is separately defined prior to and after the FN. In order to improve the FN when an event is detected, the reference is instantly increased by a constant and then maintained until the FN. This constant is determined by considering the power margin and available kinetic energy. To prevent OD, the reference decays with the rotor speed after the FN. The performance of the proposed scheme was validated under various wind speed conditions and wind power penetration levels using an EMTP-RV simulator. The results clearly demonstrate that the scheme successfully prevents OD while improving the FN at different wind conditions and wind power penetration levels. Furthermore, the scheme is adaptive to the size of a frequency event.