• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1369-1378
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• 2017

The present paper reports the development of a computational code based on the Adaptive Group of Ink Drop Spread (AGIDS) for reconstruction of the neutron noise sources in reactor cores. AGIDS algorithm was developed as a fuzzy inference system based on the active learning method. The main idea of the active learning method is to break a multiple input-single output system into a single input-single output system. This leads to the ability to simulate a large system with high accuracy. In the present study, vibrating absorber-type neutron noise source in an International Atomic Energy Agency-two dimensional reactor core is considered in neutron noise calculation. The neutron noise distribution in the detectors was calculated using the Galerkin finite element method. Linear approximation of the shape function in each triangle element was used in the Galerkin finite element method. Both the real and imaginary parts of the calculated neutron distribution of the detectors were considered input data in the developed computational code based on AGIDS. The output of the computational code is the strength, frequency, and position (X and Y coordinates) of the neutron noise sources. The calculated fraction of variance unexplained error for output parameters including strength, frequency, and X and Y coordinates of the considered neutron noise sources were $0.002682{\sharp}/cm^3s$, 0.002682 Hz, and 0.004254 cm and 0.006140 cm, respectively.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.365-370
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• 2017

This study analyze correlation between weekdays data and special days data of different power demand patterns, and builds a separate data set, and suggests ways to reduce power demand prediction error by using deep learning network suitable for each data set. In addition, we propose a method to improve the prediction rate by adding the environmental elements and the separating element to the meteorological element, which is a basic power demand prediction elements. The entire data predicted power demand using LSTM which is suitable for learning time series data, and the special day data predicted power demand using DNN. The experiment result show that the prediction rate is improved by adding prediction elements other than meteorological elements. The average RMSE of the entire dataset was 0.2597 for LSTM and 0.5474 for DNN, indicating that the LSTM showed a good prediction rate. The average RMSE of the special day data set was 0.2201 for DNN, indicating that the DNN had better prediction than LSTM. The MAPE of the LSTM of the whole data set was 2.74% and the MAPE of the special day was 3.07 %.

• Journal of the Korea Convergence Society
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• v.7 no.2
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• pp.109-118
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• 2016

The purpose of this study was I cultivate practical ability to solve diverse and complex issues in the field of convergence and applied learning and practical training element through problem-based learning to preliminary sports leaders. Selected students in grades 3 to 28 Sports Science S university people to them as participants and through a qualitative case study methods, such as group interviews, participant observation, open questionnaire and the following results were obtained. First, the level of satisfaction on class was high and the class was evaluated with significant contemplation. Second, it has been collecting a variety of learning materials to understand, interpret and improve the ability to solve practical problems in the process of actively reconstruct their own knowledge structure. It also gave a positive impact on the creative and divergent thinking to accelerate the promotion of autonomy. Third, opinions about teamwork, sharing your thoughts with colleagues point is that you can see yourself in other people's positions were evaluated as positive effects.

• The Korea Journal of Herbology
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• v.35 no.5
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• pp.33-39
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• 2020

Objectives : Increasing evidence supports the biological and pharmacological activities of essential oils on the central nervous system such as pain, anxiety, attention, arousal, relaxation, sedation and learning and memory. The purpose of present work is to investigate the protective effect and molecular mechanism of cypress essential oil (CEO) against scopolamine (SCO)-induced cognitive impairments in C57BL/6 mice. Methods : A series of behavior tests such as Morris water maze, passive avoidance, and fear conditioning tests were conducted to monitor learning and memory functions. Immunoblotting and RT-PCR were also performed in the hippocampal tissue to determine the underlying mechanism of CEO. Results : SCO induced cognitive impairments as assessed by decreased step-through latency in passive avoidance test, relatively low freezing time in fear conditioning test, and increased time spent to find the hidden platform in Morris water maze test. Conversely, CEO inhalation significantly reversed the SCO-induced cognitive impairments in C57BL/6 mice comparable to control levels. To elucidate the molecular mechanisms of memory enhancing effect of CEO we have examined the expression of brain-derived neurotrophic factor (BDNF) in the hippocampus. CEO effectively elevated the protein as well as mRNA expression of BDNF via activation of cAMP response element binding protein (CREB). Conclusions : Our findings suggest that CEO inhalation effectively restored the SCO-impaired cognitive functions in C56BL/6 mice. This learning and memory enhancing effect of CEO was partly mediated by up-regulation of BDNF via activation of CREB.

• Journal of Industrial Convergence
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• v.17 no.3
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• pp.1-8
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• 2019

This study examined the constructivist perspective and the characteristics of informal learning in relation to work place learning of sports center leaders through a theoretical approach. For this reason, informal learning has important learning meaning because sports center leaders based on informal learning enable them to develop their professionalism through workplace learning in terms of experience and practice in promoting the process of growth and learning. Can be. In addition, the leaders in the sports center coaching sites lack formal learning opportunities in workplace learning compared to office workers in general companies. Therefore, the type of informal learning and the way to improve learning should be presented. This part is considered to be an educational element as an important factor for the professionalism of sports center leaders. In addition, the establishment of a workplace learning environment in personal, environmental, institutional and organizational aspects will help sports center leaders to increase their professionalism.

• Journal of KIBIM
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• v.11 no.3
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• pp.22-33
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• 2021

In order to maximize the use of BIM, all data related to individual elements in the model must be correctly assigned, and it is essential to check whether it corresponds to the IFC entity classification. However, as the BIM modeling process is performed by a large number of participants, it is difficult to achieve complete integrity. To solve this problem, studies on semantic integrity verification are being conducted to examine whether elements are correctly classified or IFC mapped in the BIM model by applying an artificial intelligence algorithm to the 2D image of each element. Existing studies had a limitation in that they could not correctly classify some elements even though the geometrical differences in the images were clear. This was found to be due to the fact that the geometrical characteristics were not properly reflected in the learning process because the range of the region to be learned in the image was not clearly defined. In this study, the CRF-RNN-based semantic segmentation was applied to increase the clarity of element region within each image, and then applied to the MVCNN algorithm to improve the classification performance. As a result of applying semantic segmentation in the MVCNN learning process to 889 data composed of a total of 8 BIM element types, the classification accuracy was found to be 0.92, which is improved by 0.06 compared to the conventional MVCNN.

• Journal of the Earthquake Engineering Society of Korea
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• v.26 no.2
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• pp.71-82
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• 2022

This paper presents the effect on the inelastic behavior and structural performance of concrete and filled steel pipe through a numerical method for reliable judgment under various load conditions of the CJS composite structural system. Variable values optimized for the CJS synthetic structural system and the effects of multiple variables used for finite element analysis to present analytical modeling were compared and analyzed with experimental results. The Winfrith concrete model was used as a concrete material model that describes the confinement effect well, and the concrete structure was modeled with solid elements. Through geometric analysis of shell and solid elements, rectangular steel pipe columns and steel elements were modeled as shell elements. In addition, the slip behavior of the joint between the concrete column and the rectangular steel pipe was described using the Surface-to-Surface function. After finite element analysis modeling, simulation was performed for cyclic loading after assuming that the lower part of the foundation was a pin in the same way as in the experiment. The analysis model was verified by comparing the calculated analysis results with the experimental results, focusing on initial stiffness, maximum strength, and energy dissipation capability.

• Journal of the Korean Society of Earth Science Education
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• v.6 no.1
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• pp.50-59
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• 2013

Prezi, which is an implemented software in the form of flash-based online presentation, is considered to be a new appropriate smart-learning tool. This study aimed to investigate an impact of project learning utilizing Prezi on the creativity, attitudes toward science and science process skills of scientific gifted children in elementary school. The results of this study were as follows; First, after project learning utilizing Prezi, their creativity was raised meaningfully, especially in sub-elements of patience, adaptability and variety of interestings. Second, project learning utilizing Prezi showed meaningful effect on their improvement of science process skill, especially in integrated science process skills. Third, project learning utilizing Prezi improved their attitudes toward science meaningfully. In almost sub-elements, except the element of ordinariness of scientist, positive meaningful improvements were showed.

• Journal of Internet Computing and Services
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• v.9 no.6
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• pp.127-139
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• 2008

The value of up-to-date Mobile PC such as UMPC (Ultra Mobile Personal Computer) is recognized greatly in learning environment that busywork such as characteristic of transfer easy and real time communication possibility etc. and conversation with a colleague student, free sending of studying data and public ownership etc. is required. Wish to recognize whether is acting relevant role in u - unfold learning that inflect UMPC in integration research model, and UMPC is u searching for relevant element at studying activity unfolding process u - integration Inquiry-Based Learning that present in Korean education & research information service (KERIS) at fifth-year student science time In primary school in this research. This research result could take charge role of UMPCs' studying-activity though there is persistent feedback with teacher among studying-activity although UMPC's role is utilized on constituent that can be related with studying-activity in learning process.