• 대한지구과학교육학회지
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• 제9권1호
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• pp.88-96
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• 2016

The purpose of this study is to examine the effects of Jigsaw small inquiry method on science academic achievement and scientific attitudes. For this study, two classes of six graders were divided into a research group and a comparative group. The classes were pre-tested in order to ensure the same standard. The research group had the science class with Jigsaw small inquiry method, and the comparative group had the class with a teacher centered lectures for 12 classes for 12 weeks. The Jigsaw small inquiry method was focused on the introduction stage, the whole group activities, professional group activities, restart the whole group activities, supplementary structured study guide, results announced, and excellent group rewards. To prove the effects of this study, science learning motivation was split up based on the attention power, relation, confidence, and sense of satisfaction. The results of this study are as follows. First, Jigsaw small inquiry method is effective in science academic achievement. Second, Jigsaw small inquiry method is effective in scientific attitudes. Also, Jigsaw small inquiry method was approved by students. Consequently, Jigsaw small inquiry method had the great effects on developing science academic achievement for the elementary science class. That means the science class with Jigsaw small inquiry method has potential to develop science academic achievement and scientific attitudes.

• Advances in aircraft and spacecraft science
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• 제5권3호
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• pp.295-318
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• 2018

This research studies thermo-elastic behavior of rotating micro discs that are employed in various micro devices such as micro gas turbines. It is assumed that material is functionally graded with a variable profile thickness, density, shear modulus and thermal expansion in terms of radius of micro disc and as a power law function. Boundary condition is considered fixed-free with uniform thermal loading and elastic field is symmetric. Using incompressible material's constitutive equation, we extract governing differential equation of four orders; to solution this equation, we utilize general differential quadrature (GDQ) method and the results are schematically pictured. The obtained result in a particular case is compared with another work and coincidence of results is shown. We will find out that surface effect tends to split micro disc's area to compressive and tensile while nonlocal parameter tries to converge different behaviors with each other; this convergence feature make FGIMs capable to resist in high temperature and so in terms of thermo-elastic behavior we can suggest, using FGIMs in micro devices such as micro turbines (under glass transition temperature).

• Nuclear Engineering and Technology
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• 제34권4호
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• pp.382-395
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• 2002

An experimental study on transient critical heat flux (CHF) under flow coastdown has been performed for the water flow in a non-uniformly heated vertical annulus under low flow and a wide range of pressure conditions. The objectives of this study are to systematically investigate the effect of the flow transient on the CHF and to compare the transient CHF with steady-state CHF The transient CHF experiments have been performed for three kinds of flow transient modes based on the coastdown data of a nuclear power plant reactor coolant pump. At the same inlet subcooling, system pressure and heat flux, the effect of the initial mass flux on the critical mass flux can be negligible. However, the effect of the initial mass flux on the time-to- CHF becomes large as the heat flux decreases. The critical mass flux has the largest value for slow flow reduction rate. There is a pressure effect on the ratio of the transient CHF data to steady-state CHF data. Except under low system pressure conditions, the flow transient CHF was revealed to be conservative compared with the steady-state CHF data. Bowling CHF correlation and thermal hydraulic system code MARS show promising results for the prediction of CHF occurrence .

• Nuclear Engineering and Technology
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• 제39권4호
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• pp.337-348
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• 2007

A fuzzy neural network model is presented to predict residual stress for dissimilar metal welding under various welding conditions. The fuzzy neural network model, which consists of a fuzzy inference system and a neuronal training system, is optimized by a hybrid learning method that combines a genetic algorithm to optimize the membership function parameters and a least squares method to solve the consequent parameters. The data of finite element analysis are divided into four data groups, which are split according to two end-section constraints and two prediction paths. Four fuzzy neural network models were therefore applied to the numerical data obtained from the finite element analysis for the two end-section constraints and the two prediction paths. The fuzzy neural network models were trained with the aid of a data set prepared for training (training data), optimized by means of an optimization data set and verified by means of a test data set that was different (independent) from the training data and the optimization data. The accuracy of fuzzy neural network models is known to be sufficiently accurate for use in an integrity evaluation by predicting the residual stress of dissimilar metal welding zones.

• 한국보육지원학회지
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• 제18권4호
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• pp.1-16
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• 2022

Objective: The purpose of this study is to test the psychometric properties of the Maternal Emotion Coaching Questionnaire (MECQ, Lim et al., 2018) in order to measure emotion coaching in mothers of preschoolers. Methods: A total of 316 preschoolers and their mothers participated in this study. Maternal emotion coaching was assessed by self-report and child emotion regulation ability was evaluated by the teacher. Data were analyzed with chi-square tests, reliability analysis, confirmatory factor analysis, latent profile analysis, and F-test. Results: Each item of the MECQ showed proper discriminative power. The MECQ and each subscale demonstrated adequate internal consistency and split-half reliability. Evidence of construct validity was provided by confirmatory factor analysis. The five-factor model including maternal attention, awareness, acceptance, empathy, and guidance showed a good fit. Results of the latent profile analysis revealed three profiles of emotion coaching: excellent, good, and poor. Preschoolers with mothers in the poor coaching profile showed significantly lower emotion regulation ability compared to those in the excellent or good coaching profiles, which suggested discriminative validity of the MECQ. Conclusion/Implications: The MECQ presents a reliable and valid tool to assess emotion coaching in mothers of preschool children and can thus be effectively used for mothers of preschoolers.

• 신재생에너지
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• 제18권4호
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• pp.64-69
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• 2022

Double-sided photovoltaic (PV) modules have received significant attention in recent years as a technology that can achieve higher annual energy production rates than single-sided modules. The shingled technology is a promising method for manufacturing high-density and high-power modules. These modules are divided by laser and joined with electrically conductive adhesives. The output efficiency of the divided cells depends on the division pattern and the electrode pattern, making it important to understand the output characteristics. In this study, the output characteristics of large-area double-sided light-receiving shingled cells with different split patterns and electrode patterns were investigated. The M6 size, with 6 divisions in the electrode pattern, had the highest efficiency when using 142 front fingers and 146 rear fingers. The M10 size, with 7 divisions, had the highest output when using 150 fingers equally in the front and rear. The M12 size, also with 7 divisions, showed the highest output characteristics when using 192 front fingers and 208 rear fingers.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.506-515
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• 2023

This study is to find a method to learn engine sound after the start-up of a diesel generator installed in nuclear power plant with an unsupervised deep learning algorithm (CNN autoencoder) and a new method to predict the failure of a diesel generator using it. In order to learn the sound of a diesel generator with a deep learning algorithm, sound data recorded before and after the start-up of two diesel generators was used. The sound data of 20 min and 2 h were cut into 7 s, and the split sound was converted into a spectrogram image. 1200 and 7200 spectrogram images were created from sound data of 20 min and 2 h, respectively. Using two different deep learning algorithms (CNN autoencoder and binary classification), it was investigated whether the diesel generator post-start sounds were learned as normal. It was possible to accurately determine the post-start sounds as normal and the pre-start sounds as abnormal. It was also confirmed that the deep learning algorithm could detect the virtual abnormal sounds created by mixing the unusual sounds with the post-start sounds. This study showed that the unsupervised anomaly detection algorithm has a good accuracy increased about 3% with comparing to the binary classification algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권12호
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• pp.3310-3329
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• 2023

This work designs an eighteen-channel bidirectional Intensity Modulation with Direct Detection (IM/DD) Wavelength Division Multiplexing-Passive Optical Network (WDM-PON) system. The proposed system meets the requirement of the ITU-T 5G fronthaul link suggested design in G-series Recommendations-Supplement 66. The newly designed system, with a 25Gb/s/λ data rate (450Gbps as a system capacity), has been tested and simulated using OptiSystem V.19 software. The system has been evaluated by the BER with respect to variable the optical span and CW laser power. Based on the ITU-T recommendations, the simulation results demonstrate that this system might be used as an F1 and as an Fx 5G fronthaul link for functional split choices starting from options 1 to 7a. These options are required under 25Gbps/λ for each upstream and downstream link direction. Furthermore, the proposed system utilized a bidirectional single-mode optical fiber within short optical spans of up to 10 km. The proposed system is characterized by a low-cost, simple, DSP-free and amplifier-free system with a reasonable system capacity.

• Nuclear Engineering and Technology
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• 제56권4호
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• pp.1125-1134
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• 2024

This paper presents a validation study of the subchannel analysis code SLTHEN used for the core thermal-hydraulic design of the Prototype Gen-IV sodium-cooled fast reactor (PGSFR). To assess the performance of the ENERGY model of SLTHEN, four liquid metal heating experiments conducted by ORNL, WARD, and KIT with hexagonal assemblies of wire-wrapped rod bundles were analyzed. These experiments were performed with 19-and 61-pin bundles and varying power distributions of axial and radial peaking factors up to 1.4 and 3.0, respectively. The coolant subchannel temperatures measured at different axial locations were compared with the SLTHEN predictions with the Novendstern, Chiu-Rohsenow-Todreas (CRT), and Cheng-Todreas (CT) correlations for flow split and mixing in wire-wrapped pin bundles. The results showed that the SLTHEN predicts the measured subchannel temperatures reasonably well with root-mean-square errors of ~10 % and maximum errors of ~20 %. It was also observed that the CRT and CT correlations consistently outperform the Novendstern correlation.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2012년도 춘계학술대회
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• pp.88-90
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• 2012

본 논문은 rail-to-rail 입력 범위를 가지는 10-bit 10-MS/s 비동기 축차근사형 (SAR: successive approximation register) 아날로그-디지털 변환기 (ADC: analog-to-digital converter)를 제안한다. 제안된 SAR ADC는 커패시터 디지털-아날로그 변환기 (DAC: digital-to-analog converter), SAR 로직, 그리고 비교기로 구성된다. 외부에서 공급되는 클럭의 주파수를 낮추기 위해 SAR 로직과 비교기에 의해 비동기로 생성된 내부 클럭을 사용한다. 또한 높은 해상도를 구현하기 위해 오프셋 보정기법이 적용된 시간-도메인 비교기를 사용한다. 면적과 전력소모를 줄이기 위해 분할 캐패시터 기반 차동DAC를 사용한다. 설계된 비동기 SAR ADC는 0.18-um CMOS 공정에서 제작되며, core 면적은 $420{\times}140{\mu}m^2$이다. 1.8 V의 공급전압에서 0.818 mW의 전력 소모와 91.8 fJ/conversion-step의 FoM을 가진다.