• Journal of Practical Engineering Education
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• v.16 no.1_spc
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• pp.51-58
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• 2024

This paper examines the differences between the Korean and American stock markets using the Kospi and S&P 500 indices and discusses policy implications through them. To this end, in addition to the existing time series analysis method, a deep learning method was used to compare markets, and the comparison was made in terms of stock price forecasting ability and data generation ability. In monthly data, the difference between time series was not large, and in daily data, the difference in terms of stability was weak, and there was no significant difference in predictive power or simulation data generation. As shown in the results of this study, if there is not much difference in market price movement patterns between Korea and the United States, tax benefits for long-term stocks investment will be effective against the side effects of short selling.

• Korean Educational Research Journal
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• v.40 no.1
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• pp.1-16
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• 2019

The purpose of this study is to explore the relationship between parental attitudes, teachers' autonomy support as perceived by high school students, and the self-directed learning abilities of high school students. A total of 341 high school students from South Korea participated in the study. A survey instrument was used to measure parental attitudes, teacher autonomy support, and students' self-directed learning ability. The results of the study are as follows. First, the rearing attitudes of parents were perceived by the participants as oriented more toward being attainable and relatively less self-directed. There were no significant differences between male and female students, though male students were more likely to perceive their parents' attitudes as more attainable-oriented. The results also show that, in terms of self-directed learning skills among high school students, the more goal-oriented, compassionate, and autonomous the parental attitudes are, the likelier are students to have developed self-directed learning skills. Second, the male students were more aware of the autonomy support of teachers than were the female students. This shows that the results have significant predictive power over the self-directed learning ability among high school students. Accordingly, the perception of autonomy support by teachers affects the development of self-directed learning among students. We can therefore conclude that self-directed learning skills develop most effectively in students who are supported by their teachers.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.39-50
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• 2007

This study investigated how drivers' cognitive characteristics, such as perception-motor skills and safety-seeking motivation; personal characteristics, such as sensation-seeking disposition coping with physical and social dangers; their self-perceived driving ability; and their normal driving behaviors influence the number of driving violations. 352 drivers participated in the study. MANOVA was performed in order to test the differences in their driving behaviors according to their level of sensation-seeking disposition and driving ability, and Structural Equation Modeling was used to examine the causal relationships among their demographic characteristics, sensation-seeking dispositions, driving ability, driving behaviors and the number of violations. The results indicated that drivers who had higher perception-motor skills seemed to be careful with pedestrians. From the results, drivers who had somewhat higher safety-seeking motivation tended to violate fewer traffic regulations intentionally or accidentally and showed more positive driving behaviors. Furthermore, drivers who had higher perception-motor skills, higher sensation-seeking disposition, and lower safety-seeking motivation had a tendency to violate intentionally more traffic regulations. The older drivers showed driving behaviors that were careful of pedestrians. The drivers who had higher sensation-seeking disposition and longer driving careers violated more traffic regulations, both intentionally and accidentally. Results from LISREL indicated that the predictive variables directly or indirectly influenced on drivers' violation numbers ($x^2$=341.62(p=.00), GFI=.94. RMR=.10).

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.2
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• pp.91-98
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• 2017

Background & Object: Basic daily activity screening tool such as the Modified Barthel Index (MBI) has been used commonly in rehabilitation clinic and community based rehabilitation setting. Previous studies have shown the significant relations between the level of daily activities and driving ability on stroke or elderly people. However, there is a lack of studies to investigate the usefulness of MBI on prediction of driving ability for stroke patient. This study was to predict driving abilities of stroke survivor using Korean version Modified Barthel Index (K-MBI). Methods: A sample of 48 patients with stroke in rehabilitation hospital was recruited. All participants were tested level of basic daily activities using K-MBI. The driving ability of participants was tested using virtual reality driving simulator. The predictive validity was calculated of the K-MBI among pass or fail group of driving simulator test using receiver operating characteristics curves. Results: The cut-off score of >86.5 on the K-MBI is proper sensitivity to predict on driving performance ability. Conclusion: This pilot result offers clinical reference to therapists and caregivers for reasoning on driving recommendation period during rehabilitation stage of stroke survivors. Further studies need to identify prediction using real on-road test in a large population group.

• Journal of Microbiology
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• v.45 no.2
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• pp.98-104
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• 2007

Chlorophyll ${\alpha}$ concentration and cyanobacterial cell density are regularly employed as dual criteria for determinations of the alert level for cyanobacterial bloom. However, chlorophyll ${\alpha}$ is not confined only to the cyanobacteria, but is found universally in eukaryotic algae. Furthermore, the determination of cyanobacterial cell counts is notoriously difficult, and is unduly dependent on individual variation and trained skill. A cyanobacteria-specific parameter other than the cell count or chlorophyll ${\alpha}$ concentration is, accordingly, required in order to improve the present cyanobacterial bloom alert system. Phycocyanin has been shown to exhibit a strong correlation with a variety of bloom-related factors. This may allow for the current alert system criteria to be replaced by a three-stage alert system based on phycocyanin concentrations of 0.1, 30, and $700\;{\mu}g/L$. This would also be advantageous in that it would become far more simple to conduct measurements without the need for expensive equipment, thereby enabling the monitoring of entire lakes more precisely and frequently. Thus, an alert system with superior predictive ability based on highthroughput phycocyanin measurements appears feasible.

• Journal of Integrative Natural Science
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• v.9 no.2
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• pp.113-120
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• 2016

Monopolar spindle 1 (Mps1) is an attractive cancer target due to its high expression levels in a wide range of cancer cells. Mps1 is a dual specificity kinase. It plays an essential role in mitosis. The high expression od Mps1 was observed in various grades of breast cancers. In the current study, we have developed a CoMFA model of pyridazine derivatives as Mps1 kinase inhibitors. The developed CoMFA model ($q^2=0.797$; ONC=6; $r^2=0.992$) exhibited a good predictive ability. The model was then validated by Leave out five, progressive sampling and bootstrapping and found to be robust. The analysis of the CoMFA contour maps depicted favorable and unfavorable regions to enhance the activity. Bulky positive substitution at $R^3$ position and Negative substitution in $R^1$ position is favored could increase the activity. In contrast, bulky substitution in $R^1$ position is not favored. Our results can be used in designing a potent Mps1 (TTK) inhibitor.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1033-1036
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• 2004

The study on speech recognition and understanding has been done for many years. In this paper, we propose a new type of recurrent neural network architecture for speech recognition, in which each output unit is connected to itself and is also fully connected to other output units and all hidden units [1]. Besides that, we also proposed the new architecture and the learning algorithm of recurrent neural network such as Backpropagation Through Time (BPTT, which well-suited. The aim of the study was to observe the difference of Arabic's alphabet like "alif" until "ya". The purpose of this research is to upgrade the people's knowledge and understanding on Arabic's alphabet or word by using Recurrent Neural Network (RNN) and Backpropagation Through Time (BPTT) learning algorithm. 4 speakers (a mixture of male and female) are trained in quiet environment. Neural network is well-known as a technique that has the ability to classified nonlinear problem. Today, lots of researches have been done in applying Neural Network towards the solution of speech recognition [2] such as Arabic. The Arabic language offers a number of challenges for speech recognition [3]. Even through positive results have been obtained from the continuous study, research on minimizing the error rate is still gaining lots attention. This research utilizes Recurrent Neural Network, one of Neural Network technique to observe the difference of alphabet "alif" until "ya".

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.1998-2008
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• 2020

Solenoid operated valves (SOV) play important roles in industrial process to control the flow of fluids. Solenoid valves can be found in so many industries as well as the nuclear plant. The ability to be able to detect the presence of faults and predicting the remaining useful life (RUL) of the SOV is important in maintenance planning and also prevent unexpected interruptions in the flow of process fluids. This paper proposes a fault diagnosis method for the alternating current (AC) powered SOV. Previous research work have been focused on direct current (DC) powered SOV where the current waveform or vibrations are monitored. There are many features hidden in the AC waveform that require further signal analysis. The analysis of the AC powered SOV waveform was done in the time and frequency domain. A total of sixteen features were obtained and these were used to classify the different operating modes of the SOV by applying a machine learning technique for classification. Also, a deep neural network (DNN) was developed for the prediction of RUL based on the failure modes of the SOV. The results of this paper can be used to improve on the condition based monitoring of the SOV.

• Computers and Concrete
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• v.19 no.6
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• pp.631-639
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• 2017

This study experimentally investigated the flexural capacity of a concrete beam reinforced with a newly developed GFRP bar that overcomes the lower modulus of elasticity and bond strength compared to a steel bar. The GFRP bar was fabricated by thermosetting a braided pultrusion process to form the outer fiber ribs. The mechanical properties of the modulus of elasticity and bond strength were enhanced compared with those of commercial GFRP bars. In the four-point bending test results, all specimens failed according to the intended failure mode due to flexural design in compliance with ACI 440.1R-15. The effects of the reinforcement ratio and concrete compressive strength were investigated. Equations from the code were used to predict the deflection, and they overestimated the deflection compared with the experimental results. A modified model using two coefficients was developed to provide much better predictive ability, even when the effective moment of inertia was less than the theoretical $I_{cr}$. The deformability of the test beams satisfied the specified value of 4.0 in compliance with CSA S6-10. A modified effective moment of inertia with two correction factors was proposed and it could provide much better predictability in prediction even at the effective moment of inertia less than that of theoretical cracked moment of inertia.

• Korean Journal of Child Studies
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• v.20 no.1
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• pp.135-145
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• 1999

Little is known about the relationship between fathers and their preadolescent children in Korea or about variations in fathering by SES and sex role orientation. The purpose of this exploratory research was to examine variation in contemporary Korean fathering (e.g., warmth of fathering, frequency of father involvement, and task share of father involvement) and its influence on children's sex role development. One hundred and twenty-nine fathers, mothers, and their 11-13-year-old children completed standardized survey questionnaires addressing their childrearing practices, parental role involvement, spousal support, and sex role orientations. Data were analyzed using MANOVAs, t-test, correlational analyses, and multiple regression analyses. Mothers reported more warmth in parenting than did fathers. Regardless of sex of child middle class fathers reported more warmth than lower class fathers and lower frequency of task share than lower class fathers. Regardless of SES, fathers with working wives reported higher levels of task share of involvement relative to their spouse. Fathers who were more frequently involved with their children tended to receive greater support from their wives for paternal involvement. There were no differences in parenting by sex of child nor was fathering associated with children's sex role orientation. Girls' femininity was related to fathers' masculinity. SES, maternal support, fathers' femininity, parents' education level, and maternal work status had predictive ability for the ecological view that fathering is a dynamic process predicted by personal characteristics as well as contextual factors.