• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.468-480
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• 2021

Realistic real-time rain streaks rendering has been treated as a very difficult problem because of various natural phenomena. Also, in creating and managing a large number of particles, a large amount of computer resources had to be used. Therefore, in this paper, we propose a more efficient real-time rain streaks rendering algorithm by generating view-dependent rain particles and expressing a large amount of rain even with a small number. By creating a 'rain space' dependent on the field of view of the camera moving in real time, particles are rendered only in that space. Accordingly, even if a small number of particles are rendered, since the rendering is performed in a limited space, an effect of rendering a very large amount of particles can be obtained. This enables very efficient real-time rendering of rain streaks.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.36-41
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• 2022

In the 21st century, information collection and information provision based on digital informatization and intelligent automation are emerging as one of the social problems in the society for the elderly and the vulnerable groups in the welfare society including the disabled, and various methods are being studied to find realistic alternatives. Among these factors, the problem of the elderly living alone is emerging as the most serious, and as a realistic approach to solve some problems by applying information devices, it is a monitoring system using the Internet of Things(IoT). The need for an optimized system is emerging. In this study, the state of the elderly and the elderly living alone can be measured remotely by applying IoT technology. We present the research cases of a Breathing Sensor-based Smart Monitoring System that is used as a smart information system and used as a monitoring system for the elderly and infirm when it is identified as deceased through state detection

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.17-24
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• 2006

We consider the sensor location problem (SLP) on a given sensor field. We present the sensor field as grid of points. There are several types of sensors which have different detection ranges and costs. If a sensor is placed in some point, the points inside of its detection range can be covered. The coverage ratio decreases with distance. The problem we consider in this thesis is called multiple-type differential coverage sensor location problem (MDSLP). MDSLP is more realistic than SLP. The coverage quantities of points are different with their distance form sensor location in MDSLP. The objective of MDSLP is to minimize total sensor costs while covering every sensor field. This problem is known as NP-hard. We propose a new integer programming formulation of the problem. In comparison with the previous models, the new model has a smaller number of constraints and variables. This problem has symmetric structure in its solutions. This group is used for pruning in the branch-and-bound tree. We solved this problem by branch-and-cut(B&C) approach. We tested our algorithm on about 60 instances with varying sizes.

• Journal of the Korean Institute of Navigation
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• v.14 no.1
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• pp.21-38
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• 1990

This paper discusses the various modes of operations of cargo ships which are liner operations, tramp shipping and industrial operations, and mathematical programming, simulation , and heuristic method that can be used to solve ships routing and scheduling problems for each of these operations. In particular, this paper put emphasis on a crude oil tanker scheduling problem. The problem is to achieve an optimal sequence of cargoes or an optimal schedule for each ship in a given fleet during a given period. Each cargo is characterized by its type, size, loading and discharging ports, loading and discharging dates, cost, and revenue. Our approach is to enumerate all feasible candidate schedate schedules for each ship, where a candidate schedule specifies a set of cargoes that can be feasibly carried by a ship within the planning horizon , together with loading and discharging dates for each cargo in the set. Provided that candidate schedules have been generated for each ship, the problem of choosing from these an optimal schedule for each ship is formulated as a set partitioning problem, a set packing problem, and a integer generalized network problem respectively. We write the PASCAL programs for schedule generator and apply our approach to the crude oil tanker scheduling problem similar to a realistic system.

• Journal of Radiation Protection and Research
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• v.42 no.4
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• pp.212-221
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• 2017

Background: This study aims to calculate detector positions as a design of a radioactive source localizing radiation portal monitor (RPM) system using an improved genetic algorithm. Materials and Methods: To calculate of detector positions for a source localizing RPM system optimization problem is defined. To solve the problem, a modified iterative genetic algorithm (MIGA) is developed. In general, a genetic algorithm (GA) finds a globally optimal solution with a high probability, but it is not perfect at all times. To increase the probability to find globally optimal solution rather, a MIGA is designed by supplementing the iteration, competition, and verification with GA. For an optimization problem that is defined to find detector positions that maximizes differences of detector signals, a localization method is derived by modifying the inverse radiation transport model, and realistic parameter information is suggested. Results and Discussion: To compare the MIGA and GA, both algorithms are implemented in a MATLAB environment. The performance of the GA and MIGA and that of the procedures supplemented in the MIGA are analyzed by computer simulations. The results show that the iteration, competition, and verification procedures help to search for globally optimal solutions. Further, the MIGA is more robust against falling into local minima and finds a more reliably optimal result than the GA. Conclusion: The positions of the detectors on an RPM for radioactive source localization are optimized using the MIGA. To increase the contrast of the measurements from each detector, a relationship between the source and the detectors is derived by modifying the inverse transport model. Realistic parameters are utilized for accurate simulations. Furthermore, the MIGA is developed to achieve a reliable solution. By utilizing results of this study, an RPM for radioactive source localization has been designed and will be fabricated soon.

• Korean Management Science Review
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• v.4
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• pp.76-83
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• 1987

The machine-part group formation(MPGF) problem arises frequently in FMS planning. By viewing the problem as one of finding good assignments, a powerful solution algorithm is presented. The new algorithm solves the threshold dilemma found in previous solution procedures employing similarity coefficients. It also compared favorably with other existing MPGF algorithms by finding minimum exceptional elements for the tested problems. Furthermore the new algorithm can solve dynamic and more realistic MPGF problems by considering production volumes or costs. Such diverse machine-part relationship values were not considered in previous MPGF studies, which included only 0,1 incidence values. An example problem is solved where production volumes are the elements of MPGF incidence matrix.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.127-138
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• 1993

The Production Switching Heuristic (PSH) develope dby Mellichamp and Love (1978) has been suggested as a more realistic, practical and intuitively appealing approach to aggregate production planning (APP). In this researh, PSH has been modified to present a more sophisticated open grid search procedure for solving the APP problem. The effectiveness of this approach has been demonstrated by determining a better near-optimala solution to the classic paint factory problem. The performance of the modified production switching heuristic is then compared in the context of the paint factory problem with results obtained by other prominent APP models including LDR, PPP, and PSH to conclude that the modified PSH offers a better minimum cost solution than the original PSH model.

• Korean Management Science Review
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• v.29 no.3
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• pp.107-120
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• 2012

In this paper we propose an effective genetic algorithm for solving the integrated inventory and routing problem of supply chain composed of multi-warehouses and multi-retailers. Unlike extant studies dealing with integrated inventory and routing problem of supply chain, our model incorporates more realistic aspect such as positive inventory at the multi-warehouses under the assumption of inventory policy of power of two-replenishment-cycle. The objective is to determine replenishment intervals for the retailers and warehouses as well as the vehicles routes so that the total cost of delivery and inventory cost is minimized. A notable feature of our algorithm is that the procedure for evaluating the fitness of objective function has the computational complexity closing to linear function. Computational results show effectiveness of our algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.169-179
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• 1996

The object of this paper is to give an overview of one method of modeling and analysing situations involving inter-identification. Hypergame analysis is used as this approach. Hypergame analysis is one of what we call soft system approaches. In this paper, We first reformulate concept of the simple hypergame and define the hypergames with inter-identification as a system consisting of simple hypergames connected by the mutual identification. We propose a definition of solutions for them. Based on the formulation, We derives existence conditions of the solutions. We then apply the framework to a realistic problem. i. e, America-North korea conference problem to demonstrate the validity of the derived theoretical results as well as In obtain some suggestions to improve the problematic situation.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.3
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• pp.318-327
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• 2008

This paper considers a single-machine scheduling problem with availability constraints. In many realistic situations, machines may not be always available due to various reasons such as maintenance, breakdown and repair. However, most literature on scheduling assume that the machines are available at all times. This paper deals with a single-machine scheduling problem with periodic maintenance. If the maintenance decision is made jointly with the job scheduling, the system will be more effective. The objective is to minimize the total completion time of jobs. This problem is proved to be NP-hard in the strong sense. The proposed breaking heuristic(BH) algorithm rule is established by some theorems and conditions. Our computational results show that the BH algorithm is much more efficient than existing heuristic.