• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.561-571
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• 2019

Programming education generally includes problem analysis process, automation through algorithms and programming, and generalization process. It is a good software education method for students in improving computing thinking. However, it was found that beginners had difficulties in understanding instruction usage, writing algorithms, and implementing programming. In this study, we developed a game programming education model and curriculum for programming education of pre-service teachers. The 4E model consisted of empathy, exploration, engagement and evaluation. In addition, it is configured to learn game core elements and core command blocks by each stage. To help the pre-service teachers understand the use of various programming blocks, a three-step teaching and learning method was presented, consisting of example learning, self-game creation, and team-based projects. As a result of applying and verifying the curriculum for 15 weeks, it showed significant results in the 4E model and pre-service teachers' perception of block programming competence and the level of computational thinking on the submitted game project results was also high.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.832-835
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• 2003

The objective of this study is to investigate the possibility of chemical process synthesis purely based on mathematical programming when given an objective, feed conditions, product specifications, and model equations for available process units. A method based on a state space approach is proposed, and applied to an example problem with a reactor, a heat exchanger, and a separator. The results indicate that a computer can automatically synthesize an optimal process without any heuristics or expertise in process design provided that global optimization techniques are improved to be suitable for large problems.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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• pp.71-84
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• 2009

This paper considers a remanufacturing and purchasing planning problem, in which either used products(or wastes) are remanufactured or remanufactured products(or final products) are purchased to satisfy dynamic demands of remanufactured products over a discrete and finite time horizon. Also, as remanufactured products are purchased more than or equal to a special quantity Q, a discount price policy is applied. The problem assumes that the related cost(remanufacturing and inventory holding costs of used products, and the purchasing and inventory holding costs of remanufactured products) functions are concave and backlogging is not allowed. The objective of this paper is to determine the optimal remanufacturing and purchasing policy that minimizes the total cost to satisfy dynamic demands of remanufactured products. This paper characterizes the properties of the optimal policy and then, based on these properties, presents a dynamic programming algorithm to find the optimal policy. Also, a network-based procedure is proposed for the case of a large quantity of low cost used products. A numerical example is then presented to demonstrate the procedure of the proposed algorithm.

• Journal of Communications and Networks
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• v.16 no.3
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• pp.293-300
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• 2014

As energy harvesting communication systems emerge, there is a need for transmission schemes that dynamically adapt to the energy harvesting process. In this paper, after exhibiting a finite-horizon online throughput-maximizing scheduling problem formulation and the structure of its optimal solution within a dynamic programming formulation, a low complexity online scheduling policy is proposed. The policy exploits the existence of thresholds for choosing rate and power levels as a function of stored energy, harvest state and time until the end of the horizon. The policy, which is based on computing an expected threshold, performs close to optimal on a wide range of example energy harvest patterns. Moreover, it achieves higher throughput values for a given delay, than throughput-optimal online policies developed based on infinite-horizon formulations in recent literature. The solution is extended to include ergodic time-varying (fading) channels, and a corresponding low complexity policy is proposed and evaluated for this case as well.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.71-79
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• 2014

This paper discusses a method for the determination of frequency control reserve requirement with consideration of the interaction between ex-ante planning and real-time balancing. In proposed method, we consider the fact that the delivered energy for tertiary control reserve is determined based on required capacity for secondary control reserve and the expected amount of load errors. Uncertain load errors are derived by Brownian motion, an optimization method is suggested using a stochastic programming. In a short, we propose an interactive dependent method for determining secondary control reserve requirement based on the principle that it satisfies to minimize the total cost. As a result, this paper provides will analyze for an example model to demonstrate the capabilities of the method.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.26-29
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• 2012

In order to deal with the classification problems of type-2 fuzzy training samples on generalized credibility space. Firstly the type-2 fuzzy training samples are reduced to ordinary fuzzy samples by the mean reduction method. Secondly the definition of strong fuzzy linear separable data for type-2 fuzzy samples on generalized credibility space is introduced. Further, by utilizing fuzzy chance-constrained programming and classic support vector machine, a support vector machine based on type-2 fuzzy training samples and established on generalized credibility space is given. An example shows the efficiency of the support vector machine.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.735-738
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• 1998

To develop an effective virtual prototyping methodology for the PLC(Programmable Logic Controller) based real-time systems, a conversion algorithm from RLL(Relay Ladder Logic) to statechart is presented in this paper. The RLL is the main programming language to represent the operation of the PLC, and the statechart is the most widely used tool in the field of virtual prototyping in order to represent the behaviour of real-time systems. A virtual prototyping for an example case is implemened to evaluate the benefit of the proposed algorithm.

• Journal of information and communication convergence engineering
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• v.9 no.1
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• pp.21-26
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• 2011

In this paper, we suggest the object-oriented methodology for the design and implementation scheme for the program development in the application of control and instrumentation such as the detection system of RFID defective tags which needs the embedded programming. We apply the design methodology of UML in the system design phase, and suggest the implementation scheme of LabVIEW programs using LVOOP(LabVIEW Object Oriented Programming)in which make it possible to write the object-oriented programming. We design the class diagram and the sequence diagram using UML, and write the classes of LVOOP from the designed class diagram and the main VI from the sequence diagram, respectively. We show that it is possible to develop the embedded programs such as the RFID application through the implementation example of the detection system of RFID defective tags in this paper. And, we obtain the advantages based on the object-oriented design and implementation using the LVOOP approach such as the development of LabVIEW programs by adding the classes and the concept of object of the object-oriented language to LabVIEW.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1215-1219
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• 2006

Scheduling plays an important role in the process management in terms of providing profit-maximizing operation sequence of multiple orders and estimating completion times of them. In order to takes its full potential, varying conditions should be properly reflected in computing the schedule. The adjustment of scheduling decisions has to be made frequently in response to the occurrence of variations. It is often challenging because their model has to be adjusted and their solutions have to be computed within short time period. This paper employs Model Predictive Control(MPC) principles for updating the process condition in the scheduling model. The solutions of the resulting problems considering variations are computed using parametric programming techniques. The key advantage of the proposed framework is that repetition of solving similar programming problems with decreasing dimensionis avoided and all potential schedules are obtained before the execution of the actual processes. Therefore, the proposed framework contributes to constructing a robust decision-support tool in the face of varying environment. An example is solved to illustrate the potential of the proposed framework with remarks on potential wide applications.

• Smart Structures and Systems
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• v.5 no.1
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• pp.69-79
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• 2009

A non-clipped semi-active stochastic optimal control strategy for nonlinear structural systems with MR dampers is developed based on the stochastic averaging method and stochastic dynamical programming principle. A nonlinear stochastic control structure is first modeled as a semi-actively controlled, stochastically excited and dissipated Hamiltonian system. The control force of an MR damper is separated into passive and semi-active parts. The passive control force components, coupled in structural mode space, are incorporated in the drift coefficients by directly using the stochastic averaging method. Then the stochastic dynamical programming principle is applied to establish a dynamical programming equation, from which the semi-active optimal control law is determined and implementable by MR dampers without clipping in terms of the Bingham model. Under the condition on the control performance function given in section 3, the expressions of nonlinear and linear non-clipped semi-active optimal control force components are obtained as well as the non-clipped semi-active LQG control force, and thus the value function and semi-active nonlinear optimal control force are actually existent according to the developed strategy. An example of the controlled stochastic hysteretic column is given to illustrate the application and effectiveness of the developed semi-active optimal control strategy.