• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.1
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• pp.3-16
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• 1992

We present a modified Tank and Hopfield's neural network model for solving Linear Programming problems. We have found the fact that the Tank and Hopfield's neural circuit for solving Linear Programming problems has some difficulties in guaranteeing convergence, and obtaining both the primal and dual optimum solutions from the output of the circuit. We have identified the exact conditions in which the circuit stops at an interior point of the feasible region, and therefore fails to converge. Also, proper scaling of the problem parameters is required, in order to obtain a feasible solution from the circuit. Even after one was successful in getting a primal optimum solution, the output of the circuit must be processed further to obtain a dual optimum solution. The modified model being proposed in the paper is designed to overcome such difficulties. We describe the modified model and summarize our computational experiment.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.81-94
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• 1986

A shortest path dynamic programming formulation is proposed and attemped to solve an uncapacitated expansion sequencing problem. It is also compared with the Extended Binary State Space approach with total capacity. Difficulties and merits associated with the formulation are discussed. The shortest path dynamic programming lacks the separability condition and an optimal solution is not guaranteed. However it has other merits and seems to be the practical solution procedure for the expansion sequencing problem in a sense that it finds near optimal solution with less state evaluations.

• IE interfaces
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• v.23 no.1
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• pp.1-11
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• 2010

There are various ways to manage the patient flow of the hospital outpatient system. However, it is difficult to apply many implementation solutions to the real outpatient system at once. Because first, the expected effects of each different solution are very much depend on the real situation of the system and applied other solutions, and second, owing to the limited resources, each solution should be implemented according to the priority. In order to overcome these difficulties, this paper focuses on proposing the comprehensive subset of implementation solutions, which is one of the most effective among various kinds of subsets, and verifying the effects of it. The comprehensive subset of solutions is derived from conducting design of experiments and simulation which determine the optimum set of different solutions and analyze the particular interactions and priority order among them. This implementation strategy can solve the difficulties of applying different kinds of various solutions to the hospital outpatient system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.15-22
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• 1996

Methods to find an optimal solution that is the function of the design variables satisfying all constraints have been studied, there are still many difficulties to apply them to optimal design problems. A method to solve the above difficulties is developed by using Genetic Algorithms. but, several problems that conventional GAs are ill defined are application of penalty function that can be adapted to transform a constrained optimization problem into an unconstrained one and premature convergence of solution. Thus, we developed an modified GAs to solve this problems, and two examples are given to demonstrate the effectiveness of the methodology developed in this paper.

• Journal of Korean Public Health Nursing
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• v.23 no.1
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• pp.113-128
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• 2009

Purpose: To explore the barriers and solutions of immunization programs for children among vulnerable classes in the position of service providers in Community health centers. Method: Data were collected through focus group interviews with 3 groups (17 providers), and were analyzed according to the analytic method of Morgan (1998) and Krueger (1998). Results: The following five categories were identified: difficulties in obtaining a list of children among vulnerable classes, difficulties in first contact with them, difficulties in up-to-date immunization, various difficulties according to the types of vulnerable family and suggestions of solution. These results indicated that there are many difficulties in providing expanded immunization service for children among vulnerable classes in terms of manpower, cooperation of departments in public health centers and linkages between health and welfare. Finally, the characteristics of the types of vulnerable family need to be elucidated. Conclusion: To increase immunization rates among children of vulnerable classes, policies need to be prepared at the public health organization itself and the linkages between health and welfare and need for hiring additional personnel.

• Journal of Astronomy and Space Sciences
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• v.31 no.2
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• pp.121-130
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• 2014

Essential ideas, successes, and difficulties of Areal Density Analysis (ADA) for color-magnitude diagrams (CMD's) of resolved stellar populations are examined, with explanation of various algorithms and strategies for optimal performance. A CMD-generation program computes theoretical datasets with simulated observational error and a solution program inverts the problem by the method of Differential Corrections (DC) so as to compute parameter values from observed magnitudes and colors, with standard error estimates and correlation coefficients. ADA promises not only impersonal results, but also significant saving of labor, especially where a given dataset is analyzed with several evolution models. Observational errors and multiple star systems, along with various single star characteristics and phenomena, are modeled directly via the Functional Statistics Algorithm (FSA). Unlike Monte Carlo, FSA is not dependent on a random number generator. Discussions include difficulties and overall requirements, such as need for fast evolutionary computation and realization of goals within machine memory limits. Degradation of results due to influence of pixelization on derivatives, Initial Mass Function (IMF) quantization, IMF steepness, low Areal Densities ($\mathcal{A}$), and large variation in $\mathcal{A}$ are reduced or eliminated through a variety of schemes that are explained sufficiently for general application. The Levenberg-Marquardt and MMS algorithms for improvement of solution convergence are contained within the DC program. An example of convergence, which typically is very good, is shown in tabular form. A number of theoretical and practical solution issues are discussed, as are prospects for further development.

• Proceedings of the KIEE Conference
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• 2003.10b
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• pp.286-288
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• 2003

Accidents at level crossing where railways and roads cross cause many casualties because of collision of cars etc and it also has a risk of the 2nd accident of trains. it is the most vulnerable point in the railway safety. Fundamental solution for accidents at level crossing is making the crossings cubic. but it can't be easily progressed because of environmental and financial difficulties. every kind of anti-accident measures are being strived for. one of the strived results is level crossing obstacle detector which automatically detects obstacles like defected cars etc in the middle of level crossing and transmits the information of obstacles to the approaching train. However present level crossing obstacle auto detector needs high expenses to be installed and has difficulties that lenses of beam transmitter, beam receiver should be cleaned in snowing winter. this document reviews level crossing obstacle auto detector using ultrasonic sensor to measure these difficulties.

• Journal for History of Mathematics
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• v.16 no.3
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• pp.1-26
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• 2003

Gougu Rule for the right triangles is the Chinese Pythagorean theorem. In the late age of the Chosun Dynasty, mathematicians of Chosun pioneered the study of the Chinese Nine Chapters and other advanced mathematical problems as well as the Easternism in spite of the various difficulties after the Imchinoeran(임진왜란), Chungyuchairan(정유재란) and Byungchahoran(병자호란) The technologies of the addition and addition twice are the methods of the solution of the problems in the right triangles. This paper is intended to introduce some problems using these methods of solution.

• Bulletin of the Korean Mathematical Society
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• v.44 no.3
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• pp.547-567
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• 2007

We obtain spatial-temporal decay rates of weak solutions of incompressible flows in exterior domains. When a domain has a boundary, the pressure term yields difficulties since we do not have enough information on the pressure term near the boundary. For our calculations we provide an idea which does not require any pressure information. We also estimated the spatial and temporal asymptotic behavior for strong solutions.

• IE interfaces
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• v.7 no.3
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• pp.193-199
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• 1994

The purpose of this paper is to develop a method of the sensitivity analysis that can be applicable to a degenerate tree solution of the minimum cost flow problem. First, we introduce two types of sensitivity analysis. A sensitivity analysis of Type 1 is the well known method applicable to a spanning tree solution. However, this method have some difficulties in case of being applied to a degenerate tree solution. So we propose a sensitivity analysis of Type 2 that keeps solutions of upper bounds remaining at upper bounds, those of lower bounds at lower bounds, and those of intermediate values at intermediate values. For the cost coefficient, we present a method that the sensitivity analysis of Type 2 is solved by using the method of a sensitivity analysis of Type 1. Besides we also show that the results of sensitivity analysis of Type 2 are union set of those of Type 1 sensitivity analysis. For the right-hand side constant or the capacity, we present a simple method for the sensitivity analysis of Type 2 which uses arcs with intermediate values.