• Journal of Korean Elementary Science Education
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• v.20 no.2
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• pp.239-254
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• 2001

The in-depth learning course newly established in the 7th National Curriculum of Science is for students who have mastered regular subject matters on a science topic and want to learn it more deeply or by different ways. Individual learners have their own unique intellectual properties. The study examined the effects of in-depth science learning using multiple intelligence activities on the science inquiry abilities and interests of elementary school children. This study involved two fifth-grade science classes in Busan. Each class was assigned to comparison and experimental group. The science topics covered during the period of the study were Units of Matter and Earth. After studying each regular content formulated by the National Curriculum, the students of comparison group experienced traditional practices of in-depth science, whereas those of experimental one performed the Multiple Intelligence(MI) activities related to the content. Students of both groups were pre- and posttested using the inventories of Science Inquiry Ability and Science Interest. Also, after instruction on the topics, students were interviewed to collect more information related to their loaming. The results are as follows. First, the science inquiry abilities of children were increased by using activities based on MI during the in-depth science teaming. Two inquiry processes, that is, the Prediction which is regarded as one of the basic process skills in science and the Generalization regarded as one of integrated process skills showed statistically significant differences between the groups, although the differences of other skills not significant but more improvements in experimental group than comparison one. Second, the in-depth science loaming through MI contributed to the increasing of interests of the children in science. The scores on Science Interest measured in pretest and posttest with the two groups showed st statistically significant difference. For interest in science instruction, children of experimental group showed high level of interest for the various MI activities, and, although the comparison groups' level of the interest was low, they revealed that they want to experience the MI activities in future instruction of science. Interviews with the children randomly selected from the experimental group when they completed the in-depth programs showed that most of them had much interest in MI activities. Especially, they attributed significant meanings to the experiences of teaming with their friends and doing activities that they want to do. These findings have important implications about usefulness of MI in science instruction. The results also highlight the need for science teachers to provide a variety of experiences and to create environments which encourage the children to use MI to learn a science topic.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.8 no.1
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• pp.1-7
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• 2010

In the present work, an electrowinning process in the LiCl-KCl/Cd system is considered to model and analyze the electrotransport of the actinide and rare-earth elements. A simple dynamic modeling of this process was performed by taking into account the material balances and diffusion-controlled electrochemical reactions in a diffusion boundary layer at an electrode interface between the molten salt electrolyte and liquid cadmium cathode. The proposed modeling approach was based on the half-cell reduction reactions of metal chloride occurring on the cathode. This model demonstrated a capability for the prediction of the concentration behaviors, a faradic current of each element and an electrochemical potential as function of the time up to the corresponding electrotransport satisfying a given applied current based on a galvanostatic electrolysis. The results of selected case studies including five elements (U, Pu, Am, La, Nd) system are shown, and a preliminary simulation is carried out to show how the model can be used to understand the electrochemical characteristics and provide better information for developing an advanced electrowinner.

• Journal of the Korean Institute of Telematics and Electronics
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• v.16 no.4
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• pp.36-46
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• 1979

Using N_ Ch silicon gate technology . the capacitors and transistors with various dimenssion were fabricated. Although the applied process was somewhat standard the conditions of ion implantation for the gate were varied by changing the implant energies from 30keV to 60keV for B and from 100 keV to 175keV for P . The doses of the implant also changed from 3 $\times$ 10 /$\textrm{cm}^2$ to 5 $\times$ 10 /$\textrm{cm}^2$ for B and from 4$\times$ 10 /$\textrm{cm}^2$ to 7 $\times$ 10 /$\textrm{cm}^2$ for P . The D. C. parameters such as threshold voltage. substrate doping level, the degree of inversion, capacitance. flat band voltage, depletion layer width, gate oxide thickless, surface states, motile charge density, electron mobility. leakage current were evaluated and also compared with the corresponing theoretical values and / or good numbers for application. The threshold voltages measured using curve tracer and C-V plot gave good agreements with the values calculated from SUPREM II which has been developed by Stanford University process group. The threshold vol tapes with back gate bias were used to calculate the change of the substrate doping level. The measured subthreshold slope enabled the prediction of the degree of inversion The D. C. testing results suggest the realized capacitors and transistors are suited for the memory applications.

• Korean Chemical Engineering Research
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• v.55 no.2
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• pp.190-194
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• 2017

The combustion properties for the prevention of the fire and explosion in the work place are flash point, explosion limit, autoignition temperature (AIT) etc.. The using of the corrective combustion properties of the MSDS (Material Safety Data Sheet) of the handling substance for the chemical process safety is very important. For the safe handling of benzyl alcohol which is widely used in the chemical industry, the flash point and the AIT were measured. And, the lower explosion limit (LEL) of benzyl alcohol was calculated by using the lower flash point which obtained in the experiment. The flash points of benzyl alcohol by using the Setaflash and Pensky-Martens closed-cup testers measured $90^{\circ}C$ and $93^{\circ}C$, respectively. The flash points of benzyl alcohol by using the Tag and Cleveland open cup testers are measured $97^{\circ}C$ and $100^{\circ}C$. The experimental AIT of benzyl alcohol by ASTM 659E tester was measured as $408^{\circ}C$. The LEL of benzyl alcohol measured by Setaflash closed-cup apparatus was calculated as 1.17 vol% at $90^{\circ}C$. In this study, it was to possible predict the LEL by using the lower flash point of benzyl alcohol which measured by Setaflash closed-cup tester.

• Journal of Distribution Science
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• v.4 no.2
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• pp.5-20
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• 2006

Retail is called location business because it is one of the most important factors to estimate management of stores for retailers who are going to sell products directly to customers. Retailers' management achievements are shown in sale in general. Therefore, retailers tend to focus on ways to increase the numbers of customers in order to raise sales. First of all, in this research, I am going to examine the most fundamental models such as Reilly's retail gravitation, converse model, huff probability model and multiful losit model in selecting stores. Secondly, I am going to provide the process and analyzing ways to predict estimated sales amount with the previous theory model. Also I am going to predict estimated sales amount of the department store L which is located in D metorpolitan city. Lastly, I am going to argue about the problem of this research and the next research subject. Our main goal is to provide ways to complement and inspect sales estimation models, which can be used in fields after taking characters of high class structure of Korea into consideration on the base of previous researches. According to the result of the research, my conclusion is that if the process of analysis and changing factors are complemented, revise model, which can reflect reality of Korea, will be provided. Therefore, in the future study, we have to build up theory models to suit for our retail market through critic reviews about the existing high class structure of Korea.

• Food Science and Preservation
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• v.12 no.4
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• pp.344-349
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• 2005

Microwave-assisted process (MAP) was applied to extract antioxidant-related components from Thymus quinquecostatus var. japonica Hara. Microwave power(2,450 MHz, $0{\sim}160$ W) and extraction time($1{\sim}5\;min$) were used as independent variables($X_i$) for central composite design to yield 10 different extraction conditions. Response surface methodology was applied to predict optimum extraction conditions for dependent variables of extracts, such as total yield, total phenolics, flavonoid, and electron donation ability depending on different powers and extraction times of MAP. Determination coefficients($R^2$) of regression equations for dependent variables were higher than 0.93 excluding that of total phenolics, and microwave power was predicted more influential than extraction time in MAP (p<0.05). The optimal extraction time for each dependent variable was ranged from 3.36 to 4.97 min, but microwave power showed wide ranges depending on variables. The superimposed contour maps for maximized dependent variables illustrated extraction conditions of 64 to 100 W in microwave power and 2.9 to 4.0 min in extraction time.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.97-117
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• 2021

Predicting term deposit subscriptions is one of representative financial marketing in banks, and banks can build a prediction model using various customer information. In order to improve the classification accuracy for term deposit subscriptions, many studies have been conducted based on machine learning techniques. However, even if these models can achieve satisfactory performance, utilizing them is not an easy task in the industry when their decision-making process is not adequately explained. To address this issue, this paper proposes an explainable scheme for term deposit subscription forecasting. For this, we first construct several classification models using decision tree-based ensemble learning methods, which yield excellent performance in tabular data, such as random forest, gradient boosting machine (GBM), extreme gradient boosting (XGB), and light gradient boosting machine (LightGBM). We then analyze their classification performance in depth through 10-fold cross-validation. After that, we provide the rationale for interpreting the influence of customer information and the decision-making process by applying Shapley additive explanation (SHAP), an explainable artificial intelligence technique, to the best classification model. To verify the practicality and validity of our scheme, experiments were conducted with the bank marketing dataset provided by Kaggle; we applied the SHAP to the GBM and LightGBM models, respectively, according to different dataset configurations and then performed their analysis and visualization for explainable term deposit subscriptions.

• Food Engineering Progress
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• v.21 no.2
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• pp.132-137
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• 2017

The purpose of this study was to optimize dough properties using response surface methodology (RSM) and to demonstrate the performances of dough prepared under optimized conditions. Dough mixed with yeast, margarine, salt, sugar and wheat flour was prepared by fermentation process. Hardness, cohesiveness and springiness of dough were selected as critical quality attributes. The critical formulations (yeast and water) and process (fermentation time) variables were selected as critical input variables based on preliminary experiment. Box-Behnken design (BBD) was used as RSM. As a result, the quardratic, the squared and the linear model respectively provided the most appropriate fit ($R^2$>90) and had no significant lack of fit (p>0.05) on critical quality attributes (hardness, cohesiveness and springiness). The accurate prediction of dough characteristics was possible from the selected models. It was confirmed by validation that a good correlation was obtained between the actual and predicted values. In conclusion, the methodologies using RSM in this study might be applicable to the optimization of fermented foods containing various wheat flour and yeast.

• (The)Study of the Eastern Classic
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• no.66
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• pp.163-191
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• 2017

In the Book 1 starting with the narrative, metaphor, prediction, implication and paradox shows the relationship and its significance of Lee Hye-ran and Ho Hong-mae. Especially, these techniques show the key and topic of this work of 'jealousy' and its conflicting 'unjealousy' being materialized and its background are being provided, and they play narrative roles of showing in advance the numerous incidents that occur within the relationship between the main characters. Especially, jealousy and unjealousy are shown through the two main female characters: the unjealousy is connected to with Lee Hye-ran to show the extreme womanhood to lead the narrative. Meanwhile, the jealousy that occurs from the affection and obsession towards one person, it disables Ho Hong-mae from having rational judgment, and maleficence from the jealousy cannot be stopped. Eventually, in the process of finishing the narrative, the jealousy is regarded as the issue of the family, and the cause of the jealousy is emphasized the man not being faithful to the family. Therefore, the solutions to the issues occurred from the jealousy are shown explicitly that it is in the proper management of the family by the man. Therefore, the narrative of is progressed while jealousy and unjealousy conflict, and in the process of repenting the character that shows the perfect womanhood realized in the fiction world and the most radical jealousy through such womanhood, this novel can be regarded as showing the ethical lesson.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.