• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.1
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• pp.16-24
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• 2005

The goal of the present paper is to show the optimum design and operation conditions on 6 kW solar water heating system by using computer simulation with verified modelling. As the object functions, we took not only the amount of acquired and auxiliary heat but LCC, which has a relative importance and decisive role in economy. As expected, the maximum heat is acquired at the slope of collector with the equal degree to the latitude, facing the south. The capacity increase of the circulation pump and the storage tank lead to the increase of acquired heat and the decrease of auxiliary heat, but do not necessarily give economical advantages owing to additional electrical power consumption. In the present system, the minimum LCC can be obtained at the storage tank volume of 450 L and the mass flow rate of 0.344 kg/s.

• Journal of The Korean Astronomical Society
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• v.48 no.3
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• pp.165-175
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• 2015

We investigate physical properties of the nearby (∼ 7.5 pc) astrometric binary μ Cas in the context of standard evolutionary theory. Based on the spectroscopically determined relative abundances ([α/Fe] ≳ +0.4 dex, [Fe/H] ∼ −0.7 dex), all physical inputs such as opacities and equation of state are consistently generated. By combining recent spectroscopic analyses with the astrometric observations from the HIPPARCOS parallaxes and the CHARA array, the evolutionary model grids have been constructed. Through the statistical evaluation of the χ²-minimization among alternative models, we find a reliable evolutionary solution (M_A, M_B, t_age) = (0.74 M_⊙, 0.19 M_⊙, 11 Gyr) which excellently satisfies observational constraints. In particular, we find that the helium abundance of μ Cas is comparable with the primordial helium contents (Y_p ∼ 0.245). On the basis of the well-defined stellar parameters of the primary star, the internal structure and the p-mode frequencies have been estimated. From our seismic computation, μ Cas is expected to have a first order spacing ∆ν ∼ 169 μHz. The ultimate goal of this study is to describe physical processes inside a low-mass star through a complete modelling from the spectroscopic observation to the evolutionary computation.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.1
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• pp.29-36
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• 2016

In shipbuilding and offshore plant construction, pipe-stools of various types are installed. Moreover, these are many quantities but they must be installed in a successive manner. Due to these characteristics the pipe-stool installation processes easily tends to cause the schedule delays in the overall production processes. In order to reduce delay, the goal of this study is to predicts production’s lead time before manufacturing. Through this predictions it’s expected to reduce total production’s lead time by improving it's process. First of all, we made MLR(Multiple Linear Regression) and PLSR(Partial Least Square Regression) model to predict pipe-spool's lead time and then compared predictability of MLR and PLSR model. If a explanatory variable is added, it will be possible to predict results precisely.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3182-3195
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• 2021

The implementation and validation of multi-dimensional (multi-D) features in thermal-hydraulic system codes aims to extend the application of these codes towards multi-scale simulations. The main goal is the simulation of large-scale three-dimensional effects inside large volumes such as piping or vessel. This novel approach becomes especially relevant during the simulation of accidents with strongly asymmetric flow conditions entailing density gradients. Under such conditions, coolant mixing is a key phenomenon on the eventual variation of the coolant temperature and/or boron concentration at the core inlet and on the extent of a local re-criticality based on the reactivity feedback effects. This approach presents several advantages compared to CFD calculations, mainly concerning the model size and computational efforts. However, the range of applicability and accuracy of the newly implemented physical models at this point is still limited and needs to be further extended. This paper aims at contributing to the validation of the multi-D features of the system code ATHLET based on the simulation of the Tests 1.1 and 2.1, conducted at the test facility ROCOM. Overall, the multi-D features of ATHLET predict reasonably well the evolution from both experiments, despite an observed overprediction of coolant mixing at the vessel during both experiments.

• Asia-Pacific Journal of Business
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• v.9 no.4
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• pp.99-117
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• 2018

This study has investigated Linear Programming (LP) applications to special decision making problems in managerial accounting with the help of spreadsheet Solver tools. It uses scenario approaches to case examples having three products and three resources in make-and-supply business operations, which is applicable to cases having more variables and constraints. Integer Programmings (IP) are applied in order to model situations when products are better valued in integer values or logical constraints are required. Three cases in one-time-only special order decisions include Goal Programming approach, Knapsack problems with 0/1 selections, and fixed-charge 0/1 integer modelling techniques for set-up operation costs. For the decisions in outsourcing problems, opportunity-costs of resources expressed by shadow-prices are considered to determine their precise contributions. It has also shown that the improvement in work-shop operation for an unprofitable product must overcome its 'reduced cost' by the sum of direct manufacturing cost savings and its shadow-price contributions. This paper has demonstrated how various real situations of special decision problem in managerial accounting can be approached without mistakes by using LP's and IP's, and how students both in accounting and management science can acquire LP skills in their education.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.117-127
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• 2023

In many training institutions, the major advancement of Information Technology is having a profound impact on the way in which instructors teach and students learn, as well as how the two interact. The training process is continuing with the goal of enhancing the calibre of instruction and engagement. Top colleges and institutions have more recently developed a variety of Massive Open Online Courses (MOOC) systems centred on the development of new educational offering ways. These have not only captured the interest of students and scholars in the field of higher education, but also that of staff members in the private and public sectors. This study uses a Unified Theory of Acceptance and Use of Technology (UTAUT) model to assess the top MOOC providers and pinpoint the key elements influencing learner acceptance of MOOCs in Saudi Arabian training. A total of 382 government trainees in Saudi Arabia participated in an online survey, the results of which underwent analysis using structural equation modelling. This study identifies the key elements influencing Saudi government employee trainees' intentions to use MOOCs, with the findings indicating that the suggested model can account for 86.2% of user behaviour and 88.5% of user intentions.

• Journal of Korean Society of Rural Planning
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• v.4 no.1
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• pp.98-107
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• 1998

For efficient development of rural facilities, choice of their optimum locations would be an important issue, however, existing research works concentrated much more an allocation policy of urban industrial complex and public facilities than rural ones. In this study, because agricultural-cum-industrial complex has been the most widely developed representative one of rural facilities, it was selected as a case study facility. As a pre-study to system development, existing governmental location-decision system was checked and interviewing survey carried out to find out on-spot problems. And, being based on literature review and survey analysis results, 4-step optimum locational decision model was developed , formulation of locational goal system, ranking tabulation on components, determination of significance values of components, calculation of component scores. Finally, through the case study works on 3 sites, system applicability was checked, Considering together the simplicity problem of existing guidelines and the interviewing survey results favoring the diversified viewpoints, it would be necessary to develop multifaceted support system for locational decision making. 3-tier classification steps from the higher, middle to lower one were used and their underpinning viewpoints were sorted as on regional development, entrepreneurship, spatial rationality, from which a tentative locational goal system was formulated. Through the expert group checking, final locational goal system was determined having 3 of the higher classification items, 7 of the middle ones, 23 of the lower ogles. For ranking tabulation, 3 types of ranking criteria were arranged which were based on statistical analysis using mean and standard deviation(Type I ), its existence or not 1 good or not(Type E ), and the others(Type E ). From the significance evaluation results, regional development and entrepreneurship aspects were valued much higher than spatial rationality aspect. And, in the middle step, items as spread effects of regional economy, accessibility and social potentialities were highly valued while infrastructural development level and natural condition being low. The application results of the system to 3 case study total. However, the detailed ones differed among study the influencing effects on regional economy, and contrast greater the infrastructural development level. Conclusively, final evaluation values well represented the characteristics of each area. If this system be complemented and applied comprehensively by the successive studies, it would be developed to a general model of locational decision supporting system for rural facilities.

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.37-43
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• 2006

In 2006, the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC) plans to undertake (subject to receiving the necessary approvals) a Pilot program for $CO_2$ storage within a depleted gas reservoir. The Otway Basin Pilot Program (OBPP) aims to demonstrate that subsurface $CO_2$ storage is both economically and environmentally sustainable in Australia. This will be the first $CO_2$ storage program in the world to utilise a depleted gas reservoir and, hence, the experience gained will be a valuable addition to the range of international $CO_2$ storage programs that are underway or being planned. A key component of the OBPP is the design of an appropriate geophysical monitoring strategy that will allow the subsurface migration of the $CO_2$ plume to be tracked and to verify that containment has been successful. This paper presents the results from modelling the predicted gravity response to $CO_2$ injection into the Otway Basin reservoir, where the goal was to determine minimum volumes of $CO_2$ that may be detectable using non-seismic geophysical techniques. Modelling results indicate that gravity measurements at 10 m spacing within the existing observation well and the planned $CO_2$ injection well would provide excellent vertical resolution, even for the smallest $CO_2$ volume modelled (10000 tonnes), but resolving the lateral extent of the plume would not be possible without additional wells at closer spacing.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.99-109
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• 2021

In recent machine learning studies, in order to consider the quality and completeness of data, derivation of non-functional requirements for data has been proposed from the viewpoint of requirements engineering. In particular, requirements engineers have defined data requirements in machine learning. In this study, data requirements were derived at the data acquisition (DAQ) stage, where data is collected and stored before data preprocessing. Through this, it is possible to express the requirements of all data required in the existing DAQ system, the presence of tasks (functions) satisfying them, and the relationship between the requirements and functions. In addition, it is possible to elicit requirements and to define the relationship, so that a software design document can be produced, and a systematic approach and direction can be established in terms of software design and maintenance. This research using existing DAQ system cases, scenarios and use cases for requirements engineering approach are created, and data requirements for each case are extracted based on them, and the relationship between requirements, functions, and goals is illustrated through goal modeling. Through the research results, it was possible to extract the non-functional requirements of the system, especially the data requirements, from the DAQ system using requirements engineering.

• Smart Structures and Systems
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• v.22 no.5
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.