• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.707-712
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• 1994

An Enhanced Shopfloor Oriented Programming(AESOP) system is developed as a programming utillity of the CNC turning machine. The developed system is specially designed to give a beginner the convenience for CNC part programming with graphical interaction between a machine operator and the AESOP system. The combination of process-oriented cycles and various contour programming as well as an immediate tool path verification support the easiness and swiftness of a part program generation in the shopfloor. Since the AESOP system has been designed to operate on the basis of MS-Windows in the PC-embedded CNC system, it is also useful for the training of the part programming by utilizing provailing personal computers in the educational department.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.5
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• pp.1074-1083
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• 1993

NC simulation has been used to replace the test cutting of NC machining. Although it can reduce the NC part programming effort, it still has a problem. If any error is found during the simulation, then the part has to be reprogrammed and it is time consumming. This paper presents a method for verifying and editing the NC code after the post-processing without going back to the part programming stage. A data structure and an algorithm to verify and edit the NC code interactively with the aid of graphics is introduced. Z-map method is used for the shaded image display and cross-sectional view display of the macined parts. The method was implemented in a IBM/PC-386 with MS-Windows software, and the multi-window function of the of the MS-Windows is used for the simultaneous editing and verification.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.451-458
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• 2003

Dynamic Programming Matching (DPM) is a mathematical optimization technique for sequentially structured problems, which has, over the years, played a major role in providing primary algorithms in pattern recognition fields. Most practical applications of this method in signature verification have been based on the practical implementational version proposed by Sakoe and Chiba [9], and is usually applied as a case of slope constraint p = 0. We found, in this case, a modified version of DPM by applying a heuristic (forward seeking) implementation is more efficient, offering significantly reduced processing complexity as well as slightly improved verification performance.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.43-52
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• 1996

This paper describes interactive computer procedures for design the forming sequences in cold forging. This system is implemented on the personal computer and its environment is a commercial AutoCAD system. The programming language. AutoLISP, was used for the configuration of the system. Since the process of metal forming can be considered as a transformation of geometry, treatment of the geometry of the part is a key in process planning. To recognize the part section geometry, the section entity representation, the section coordinate-redius representation and the section primitive geometru were adopted. This system includes six major modules such as input module, forging design module, forming sequence design module, die design module, FEM verification module and output module which are used independently or in all. The sequence drawing wigh all dimensions, which includes the dimensional tolerances and the proper sequence of operations, can generate under the environment of AutoCAD. The acceptable forming sequences can be verified further, using the FE simulation.

• Korean Journal of Computational Design and Engineering
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• v.4 no.4
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• pp.339-349
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• 1999

The punose of this paper is to introduce the comprehensive CAM system (called PosCAM) supporting various function requested from shop floor operators. PosCAM is comported of two subsystems (PosCAM I and PosCAM II) which are designed to make up for the contemporary CAD/CAM systems. PosCAM I is mainly for : a) verifying the part programs written in both custom macros and standard G-codes, b) enhancing machining productivity and quality with built-in cutting conditions and feedrate optimization algorithm. PosCAM II is for : a) efficiently managing the numerous part programs and tool data stored in CNC memory, and b) integratively controlling and monitoring various CNCs from the control center through RS-422 with DNC 2 protocol. The developed systems have been tested via various experiments, and can be Applied for the industrial CNC machine shop as a means for enhancing productivity. The PosCAM system has been implemented and successfully used in the Machine Shop Department of PosCAM since march 1998.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.730-735
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• 2014

This paper introduces a GP (Genetic Programming) based robust technique for the prediction of a heavy rain newsflash. The nature of prediction for precipitation is very complex, irregular and highly fluctuating. Especially, the prediction of heavy precipitation is very difficult. Because not only it depends on various elements, such as location, season, time and geographical features, but also the case data is rare. In order to provide a robust model for precipitation prediction, a nonlinear and symbolic regression method using GP is suggested. The remaining part of the study is to evaluate the performance of prediction for a heavy rain newsflash using a GP based nonlinear regression technique in Korean regions. Analysis of the feature selection is executed and various fitness functions are proposed to improve performances. The KLAPS data of 2006-2010 is used for training and the data of 2011 is adopted for verification.

• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.274-279
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• 2017

LCD(Liquid Crystal Display) panel cutting problem is a sort of two dimensional cutting stock problem. A cutting stock problem is problem that it minimizes the loss of the stock when a stock is cut into various parts. In the most research of the two dimensional cutting stock problem, it is supposed that the relative angle of a stock and parts is not important. Usually the angle is regarded as horizontal or perpendicular. In the manufacturing of polarizing film of LCD, the relative angle should be maintained at some specific angle because of the physical and/or chemical characteristics of raw material. We propose a mathematical model for solving this problem, a two-dimensional non-Guillotine cutting stock problem that is restricted by an arranged angle. Some example problems are solved by the C++ program using ILOG CPLEX classes. We could get the verification and validation of the suggested model based on the solutions.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.385-396
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• 2005

In this paper, a new structural approach to on-line signature verification is presented. A primitive pattern is defined as a part segmented by a local minimal position of speed. And a structural description of signature is composed of subpatterns which are defined as such forms as rotation shape, cusp shape and bell shape, acquired by composition of the primitives regarding the directional changes. As the matching method to find identical parts between two signatures, a modified DP(dynamic programming) matching algorithm is presented. And also, variation and complexity of local parts are computed from the training samples, and reference model and decision boundary are derived from these. Error rate, execution time and memory usage are compared among the functional approach, the parametric approach and the proposed structural approach. It is found that the average error rate can be reduced from 14.2% to 4.05% when the local parts of a signature are weighted and the complexity is used as a factor of decision threshold. Though the error rate is similar to that of functional approaches. time consumption and memory usage of the proposed structural approach are shown to be very effective.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• The Journal of Korean Association of Computer Education
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• v.22 no.6
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• pp.43-55
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• 2019

In the Fourth Industrial Revolution, a super-intelligent and super-connected society has arrived. Software is an important part of the core technologies of the Fourth Industrial Revolution. The ability to solve problems through software requires software education in that it is a core competency that everyone should have. Software education aims to improve Computational Thinking, which is the ability to solve problems through programming. Until now, most problem-solving programming learning models follow the traditional method of development: Waterfall model (Analysis-Design-Development-Test). In this model, if there is a problem in the preceding step, That could be found in the test phase. This takes a considerable amount of time and effort to find a solution to the problem and can be a burden on the programming learning. In this study, we proposed a Test-Driven Problem-Solving learning model using TDD (Test Driven Development) as Agile development method, and reviewed the appropriateness of the model through experts review. The verification results of the model showed positive evaluation results. In particular, the learning phase configuration of the model, helping in programming learning, helping of Computational Thinking improvement showed high rating, it is determined that there will be positive effects on Computational Thinking improvement through problem-solving programming learning when applying future learning.