• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.55-62
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• 2016

Economic and social damages are expected due to yellow dust, occurring every year in Korea and risk of citizens is getting higher accordingly. This study acquired tweet data for yellow dust, which had been the greatest since 2009 for 11 days before and after February 23, 2015. After that, it conducted an analysis on the issue words and association rule. Regarding acquired tweet data, the results of analyzing issue words by using open source R, statistics language shows that 'Mask' was ranked to be the highest, followed by health-related issue words. This indicates that people put the priority in the use of mask for keeping their health, as a result of the occurrence of yellow dust, and subsequently, they showed an interest in diseases, caused by yellow dust. In addition, yellow dust-related diseases, 'cold', 'rhinitis', 'flu', 'asthma', 'bronchitis' were found as issue words, revealing that people had a high concern on the disease occurrence of the respiratory system. The analytical results are judged to reflect the citizen's thought effectively in the process of establishing measures for the prevention of yellow dust.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.1
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• pp.57-65
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• 2016

Threat evaluation is a process to estimate the threat score which enemy aerial threat poses to defended assets. The objective of threat evaluation is concerned with making an engagement priority list for optimal weapon allocation. Traditionally, the threat evaluation of massive air threats has been carried out by air defence experts, but the human decision making is less effective in real aerial attack situations with massive enemy fighters. Therefore, automation to enhance the speed and efficiency of the human operation is required. The automatic threat evaluation by air defense experts who will perform multi-variable judgment needs formal models to accurately quantify their linguistic evaluation of threat level. In this paper we propose a threat evaluation model by using a fuzzy rule-based inference method. Fuzzy inference is an appropriate method for quantifying threat level and integrating various threat attribute information. The performance of the model has been tested with a simulation that reflected real air threat situation and it has been verified that the proposed model was better than two conventional threat evaluation models.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.71-81
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• 2018

Forklifts in a shipyard lift and transport heavy objects. Tasks occur dynamically and the rate of the task occurrence changes over time. Especially, the rate of the task occurrence is high immediately after morning and afternoon business hours. The weight of objects varies according to task characteristic, and a forklift also has the workable or allowable weight limit. In this study, we propose an online forklift dispatching algorithm based on nearest-neighbor dispatching rule using minimal cost assignment approach in order to attain the efficient operations. The proposed algorithm considers various types of forklift and multiple jobs at the same time to determine the dispatch plan. We generate dummy forklifts and dummy tasks to handle unbalance in the numbers of forklifts and tasks by taking their capacity limits and weights. In addition, a method of systematic forklift selection is also devised considering the condition of the forklift. The performance indicator is the total travel distance and the average task waiting time. We validate our approach against the priority rule-based method of the previous study by discrete-event simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.54-61
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• 1999

Objective of the research is to put the vast and complex fault tracking knowledge of human experts in semiconductor production line into the knowledge base of computer system. We mined the fault tracking knowledge of domain experts(engineers of production line) for the construction of knowledge base of the expert system. Object oriented fact models which increase the extensibility and reusability have been built. The rules are designed to perform the fault diagnosis of the items in production device. We have exploited the evidence accumulation method to assign check priority in rules. The major contribution is in the overall design and implementation of the nile base and related facts of the expert system in object oriented paradigm for the application of the system in fault diagnosis in semiconductor production line.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.4
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• pp.37-50
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• 1994

The efficiency of production system is mainly considered in the viewpoints of reducing the average flow time of products and increasing the throughput rate. The performance in these viewpoints is very depending on job dispatching of each machine in real time operation, in the case jobs are released dynamically. In this research, a heuristic dynamic dispatching method is suggested for a flow shop case where new jobs with random process times are released by an interarrival time distribution and the number of waiting jobs between each pair of machines are limited. The proposed method has been compared with some priority rule-based dispatching methods by simulation and found to be superior to them.

• IE interfaces
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• v.22 no.1
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• pp.10-16
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• 2009

In this paper, we propose an efficient search algorithm for finding an optimal schedule to minimize makespan, while avoiding deadlock situation in Flexible Manufacturing Systems (FMS) with finite capacity, in which each job needs to be processed in several job stages for completion. The proposed algorithm uses a modeling and control method based on Petri-net. Especially, we improve the efficiency of the search algorithm by using a priority rule and an efficient bounding function during the search procedure. The performance of the proposed algorithm is evaluated through a numerical experiment, showing that it holds considerable promise for providing an optimal solution efficiently comparing to past work.

• Journal of the Korean Society for Precision Engineering
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• v.7 no.3
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• pp.66-74
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• 1990

This paper presents a knowledge-based computer aided process planning system that automatically selects machine tools, machining operations and cutting tools and determines sequences of the machining operations for prismatic parts in die manufacturing. In the proposed system, parts are described by manufacturing features and grouped into part families based on the functions. Each part is repressented by a part frame which consists of basic data and manufacturing features. Knowledge for manufacturing is acquired from the domain expert and represented by frames. A decision model for selection of machine tools, machining operations and cutting tools and for determining sequences of the machining operations are developed by employing the Mealy machine in finite automata with output. The decision procedure and the order of priority which inputs manufacturing features into the Mealy machine are represented by rule for each part family. Backward chaining is used for the proposed system. The proposed system is implemented by using TURBO-PROLOG on the IBM PC/AT. A case study for the slide core is presented to show the function of the proposed system.

• IE interfaces
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• v.7 no.2
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• pp.107-120
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• 1994

This study introduces a scheduling policy to achieve unmanned operations in machining shops representing the feature of both FMS and machining centers. The proposed policy considers the practical constraints in the machining shops such as lot sizes, multiple pallets, and jig/fixtures. In addition, rescheduling to cope with extraordinary events(eg., arrival of high-priority jobs and breakdown of machines) is included. Basically, the scheduling policy consists of four procedures; (1) selection of a job according to dispatching rule, (2) selection of a machine, (3) assignment of jobs to a multiple pallet for the unmanned operation during a certain shift, and (4) prevention of unexpected machine idle caused by constraints on jig/fixture.

• Industrial Engineering and Management Systems
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• v.3 no.2
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• pp.100-115
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• 2004

The network representation and branch and bound algorithm with efficient lower and upper bounding procedures are developed to determine a global optimal production schedule on a machine that minimizes sequence-dependent setup cost and earliness/tardiness penalties. Lower bounds are obtained based on heuristic and Lagrangian relaxation. Priority dispatching rule with local improvement procedure is used to derive an initial upper bound. Two dominance criteria are incorporated in a branch and bound procedure to reduce the search space and enhance computational efficiency. The computational results indicate that the proposed procedure could optimally solve the problem with up to 40 jobs in a reasonable time using a personal computer.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1524-1529
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• 2005

Particle filter is a kind of conditional density propagation model. Its similar characteristics to both selection and mutation operator of evolutionary strategy (ES) due to its Bayesian inference rule structure, shows better performance than any other tracking algorithms. When a new object is entering the region of interest, particle filter sets which have been swarming around the existing objects have to move and track the new one instantaneously. Moreover, there is another problem that it could not track multiple objects well if they were moving away from each other after having been overlapped. To resolve reinitialization problem, we use competitive-AVQ algorithm of neural network. And we regard interfarme difference (IFD) of background images as potential field and give priority to the particles according to this IFD to track multiple objects independently. In this paper, we showed that the possibility of real-time object tracking as intelligent interfaces by simulating the deformable contour particle filters.