• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.187-192
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• 2017

In this paper, we have studied scale tools for measure programming task value and learning persistence at elementary school students. In order to develop complete test tools, we have improved the completeness by revising tests through stepwise verification. The first scales were constructed based on the previous studies. As a result of the content validity test, 5 out of 14 items of the task value test tool and 1 out of 10 items of the learning persistence test were not suitable. The second test tools were constructed by revising and supplementing the first scale, and consisted of 13 items of task value and 8 items of learning persistence. As a result of the contents validity test, all the items included in the test tool proved to be valid. The reliability of the secondary testing tools were also found to be reliable at ${\alpha}=.970$ and ${\alpha}=.975$, respectively.

• Journal of information and communication convergence engineering
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• v.18 no.4
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• pp.239-244
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• 2020

This study analyzed the influencing factors of learning engagement and teaching presence in online programming practice classes. The subjects of this study were students enrolled in an industrial specialized high school, who practiced creating Arduino circuits and programming using a web-based virtual practice tool called Tinkercad. This research adopted a tool that can measure task value, learning flow, learning engagement, and teaching presence. Based on this analysis, learning flow had a mediating effect between task value and online learning engagement, as well as between task value and teaching presence. Increasing learning engagement in online classes requires sensitizing the learners about task value, using hands-on platforms available online, and expanding interaction with instructors to increase learning flow of students. Furthermore, using virtual hands-on tools in online programming classes is relevant in increasing learning engagement. Future research tasks include: confirming the effectiveness of online learning engagement and teaching presence through pre- and post-tests, and conducting research on various practical subjects.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.19-30
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• 2013

Recently, the constrained index tracking problem, in which the task of trading a set of stocks is performed so as to closely follow an index value under some constraints, has often been considered as an important application domain for control theory. Because this problem can be conveniently viewed and formulated as an optimal decision-making problem in a highly uncertain and stochastic environment, approaches based on stochastic optimal control methods are particularly pertinent. Since stochastic optimal control problems cannot be solved exactly except in very simple cases, approximations are required in most practical problems to obtain good suboptimal policies. In this paper, we present a procedure for finding a suboptimal solution to the constrained index tracking problem based on approximate dynamic programming. Illustrative simulation results show that this procedure works well when applied to a set of real financial market data.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.737-742
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• 2011

Navigation problems include the task of determining the control input under various constraints for systems such as mobile robots subject to uncertain disturbance. Such tasks can be modeled as constrained stochastic control problems. In order to solve these control problems, one may try to utilize the dynamic programming(DP) methods which rely on the concept of optimal value function. However, in most real-world problems, this trial would give us many difficulties; for examples, the exact system model may not be known; the computation of the optimal control policy may be impossible; and/or a huge amount of computing resource may be in need. As a strategy to overcome the difficulties of DP, one can utilize ADP(approximate dynamic programming) methods, which find suboptimal control policies resorting to approximate value functions. In this paper, we apply recently proposed ADP methods to a class of navigation problems having complex constraints, and observe the resultant performance characteristics.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.1 no.1
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• pp.72-74
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• 1983

Traditionally, polynomials have been used to approximte functions with prescribed values at a number of points(called the knots) on a given interal on the real line. The method of splines recently developed is more flexible. It approximates a function in a piece-wise fashion, by means of a different polynomial in each subinterval. The cubic spline gas ets origins in beam theory. It possessed continuous first and second deriatives at the knots and is characterised by a minimum curvature property which es rdlated to the physical feature of minimum potential energy of the supported beam. Translated into mathematical terms, this means that between successive knots the approximation yields a third-order polynomial sith its first derivatives continuous at the knots. The minimum curvature property holds good for each subinterval as well as for the whole region of approximation This means that the integral of the square of the second derivative over the entire interval, and also over each subinterval, es to be minimized. Thus, the task of determining the spline lffers itself as a textbook problem in discrete computer programming, since the integral of ghe square of the second derivative can be obviously recognized as the criterion function whicg gas to be minimized. Starting with the initial value of the function and assuming an initial solpe of the curve, the minimum norm property of the curvature makes sequential decision of the slope at successive knots (points) feasible. It is the aim of this paper to derive the cubic spline by the methods of computer programming and show that the results which is computed the all the alues in each subinterval of the spline approximations.

• Science of Emotion and Sensibility
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• v.22 no.4
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• pp.15-30
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• 2019

The reduction of traffic accidents is a primary potential benefit of autonomous vehicles (AVs). However, the prevalence of AVs also arouses a key question: to what extent should a human wrest control back from AVs? Specifically, in an unavoidable situation of emergency, should an AV be able to decide between the safety of its own passengers and endangered pedestrians? Should AV programming include well-accepted decision rules about actionsto take in hypothetical situations? The current study (N = 103) examined individual/situational variables that could perform critical decision-making roles in AV related traffic accidents. The individual variable of attitudes toward AVs was assessed using the Self-driving Car Acceptance Scale. To investigate situational influences on decisional processes, the study's participants were assigned to one of two groups: the achievement value was activated in one group and the benevolence value was triggered in the other through the use of a sentence completion task. Thereafter, participants were required to indicate who should be protected from injury: the passengers of the concerned AV, or endangered pedestrians. Participants were also asked to record the extent to which they intended to buy an AV programmed to decide in favor of the greater good according to Utilitarian principles. The results suggested that participants in the "achievement value: driver perspective" groupexpressed the lowest willingness to sacrifice themselves to save several pedestrians in an unavoidable traffic accident. This group of participants was also the most reluctant to buy an AV programmed with utilitarian rules, even though there were significant positive relationships between members' acceptance of AVs and their expressed intention to purchase one. These findings highlight the role of the decisional processes involved in the "achievement value" pertaining to AVs. The paper finally records the limitations of the present study and suggests directions for future research.