• International Journal of Aeronautical and Space Sciences
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• v.11 no.2
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• pp.136-144
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• 2010

This paper presents an algorithm for planning waypoints for the operation of a surveillance mission using cooperative unmanned aerial vehicles (UAVs) in a given map. This algorithm is rather simple and intuitive; therefore, this algorithm is easily applied to actual scenarios as well as easily handled by operators. It is assumed that UAVs do not possess complete information about targets; therefore, kinematics, intelligence, and so forth of the targets are not considered when the algorithm is in operation. This assumption is reasonable since the algorithm is solely focused on a surveillance mission. Various parameters are introduced to make the algorithm flexible and adjustable. They are related to various cost functions, which is the main idea of this algorithm. These cost functions consist of certainty of map, waypoints of co-worker UAVs, their own current positions, and a level of interest. Each cost function is formed by simple and intuitive equations, and features are handled using the aforementioned parameters.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.197-205
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• 1994

Security of a power system refers to its robustness relative to a set of imminent disturbances (contingencies) during operation. The socially optimal solution for the actuall level of generation/consumption has been well-known spot pricing at shot-run marginal cost. The main disadvantage of this approach arises because serious contingencies occur quite infrequently. Thus by establishing contractual obligations for contingency offering before an actual operation time through decision feedback we can obtain socially optimal level of system security. Under probabilistic precontract pricing the operating point is established at equal incremental cost of the expected short-run and collapse cost of each participant. Rates for power generation/consumption and for an offer to use during a contingency, as well as information on the probability distribution of contingency need for each participant, are derived so that individual optimization will lead to the socially optimal solution in which system security is optimized and the aggregate benefit is maxmized.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.34-35
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• 2006

This paper presents an information collection and a novel inference technique for evaluation of power system operation state. In most developing countries, power demands are steadily increasing and consequently power systems are becoming larger and more complicated. In addition, power system deregulations further complicate the power system operational tasks, which are resulted in prevailing wide area blackouts worldwide. In this paper, we proposed an effective information collection and operating state evaluation methods using a knowledge-based system. The RTS-79 24 bus system is used as a test system. The power system model is composed with JESS templates and included in the knowledge-base as a part of fixed facts. Dynamic informations are collected from various analysis results and actual operational data. Inferences are performed with rules expressed with terms in different abstraction levels. Future research will be concentrated on intelligent contingency selections for preventing wide area blackouts.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1028-1031
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• 1996

Dynamic scheduling is very important in constructing CIM and improving productivity of chemical processing systems. Computation at the scheduling level requires mostly a long time to generate an optimal schedule, so it is difficult to immediately respond to actual process events in real-time. To solve these problems, we developed dynamic scheduling algorithms such as DSMM(Dynamic Shift Modification Method), PUOM(Parallel Unit Operation Method) and UVVM(Unit Validity Verification Method). Their main functions are to minimize the effects of unexpected disturbances such as process time variations and unit failure, to predict a makespan of the updated dynamic schedule and to modify schedule desirably in real-time responding to process time variations. As a result, the algorithms generate a new pertinent schedule in real-time which is close to the original schedule but provides an efficient way of responding to the variation of process environment. Examples in a shampoo production batch process illustrate the efficiency of the algorithms.

• Korean Journal of Computational Design and Engineering
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• v.4 no.3
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• pp.247-258
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• 1999

With the contemporary CAD/CAM system, where the tool path is generated and verified purely based on the geometric operation, geometric accuracy of the machined surface cannot be guaranteed dut to the cutting mechanics, meaning that the cutting mechanics should be incorporated in some fashion. In this paper, we incorporate the instantaneous cutting force and the tool deflection phenomena in predicting the machined surface for the finish-cut and milling operation. For the given NC dat including cutting conditions, the developed algorithm computes cutting force and deflection amount along the tool trajectory, and outputs the 3D graphic model of the machined surface together with error analysis. The validity and accuracy of the presented method has been tested by the actual cutting experiments. Experimental results and accuracy enhancement method together with implementing architecture of the VMCS (Virtual Machining CAM System) are discussed in the paper.

• Korean Journal of Construction Engineering and Management
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• v.2 no.4 s.8
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• pp.92-97
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• 2001

The level of awareness and actual implementation of integration and computerization in the construction industry is growing. However, it is not clear at this point how to assess the extent of their impact and to identify in which ways they better support the construction projects related to their success. The objectives of this research are the development of a model to evaluate the impact of integration and computerization on construction projects and the recommendation of guidelines for companies in identifying suitable ways for them to incorporate integration and computerization Into their operation. The developed conceptual model has been found robust enough to be used as a benchmarking tool in evaluating the performance of the construction process and to strategize its future operation.

• The KSFM Journal of Fluid Machinery
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• v.10 no.3 s.42
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• pp.33-38
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• 2007

Fan selection procedure and fan noise evaluation method are presented for the system electronic cooling by combining FNM(Flow Network Model) and fan noise correlation model. Internal flow paths and distribution in electronic system we analyzed by using the FNM with the flow resistances for flow elements of the system. Based on the fan operation point predicted from the FNM analysis results, the present fan noise model predicts overall sound power, pressure levels and spectrum. The predictions of the flow distribution, the fan operation and the noise level in electronic system by the present method are well agreed with 3-D CFD and actual test results.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.6
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• pp.743-754
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• 2015

FASCAM is a newly introduced mean against enemy fire power and supposed to be scattered on base areas in front of a tunnel so as to deter maneuver and shooting of enemy artilleries. However, for its characteristics different from conventional munitions, only a few studies have been undertaken on operations system using this new measure. In this research, we propose a procedure to describe and analyze mathematically an operation system for suppression of enemy fire power using FASCAM. Two suggested simulation methods, impact point generation and density integration, both can describe the actual operation rationally and each has advantages of its own respectively. Further, we demonstrated an example analysis to derive an optimal suppression plan based on the proposed procedure.

• Journal of information and communication convergence engineering
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• v.18 no.3
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• pp.167-175
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• 2020

The net income per unit area from crop production could be the most critical consideration for agricultural producers during cultivation planning. This paper proposes a scheme for predicting the net income per unit area based on machine learning and related calculations. This scheme predicts rice production and operation costs by applying climate and price index data. The rice price is also predicted by applying rice production and operation cost data. Finally, these predicted results are employed to calculate the predicted net income, which is compared with the actual net income. Consequently, the proposed scheme shows a meaningful degree of conformity, which indicates the potential of machine learning for predicting various aspects of agricultural production.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.123.2-123
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• 2001

It is difficult to determine the feeding rate of coagulant in the water treatment plant, due to nonlinearity, multivariables and slow response characteristics, etc. To deal with this difficulty, the neuro-fuzzy system and the genetic-fuzzy system were used in determining the feeding rate of the coagulant. The fuzzy system is excellently robust in multi-variables and nonlinear problems. Therefore it uses basic algorithm, but it is difficult to construct of the fuzzy parameter such as the rule table and the membership function, Therefore we made the neuro-fuzzy system and the genetic-fuzzy system with the fusion of learning algorithms and compared the performance of the two fuzzy systems. To apply these algorithms, we made the rule table, membership function from the actual operation data of the water treatment plant. We determined optimized feeding rate of coagulant using the fuzzy operation, and also compared ...