• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.4
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• pp.359-366
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• 2022

In this study, the load fluctuation of the main engine is considered to be a disturbance for the jacket coolant temperature control system of the low-speed two-stroke main diesel engine on the ships. A nonlinear PID temperature control system with satisfactory disturbance rejection performance was designed by rapidly transmitting the load change value to the controller for following the reference set value. The feed-forwarded load fluctuation is considered the set points of the dual loop control system to be changed. Real-coded genetic algorithms were used as an optimization tool to tune the gains for the nonlinear PID controller. ITAE was used as an evaluation function for optimization. For the evaluation function, the engine jacket coolant outlet temperature was considered. As a result of simulating the proposed cascade nonlinear PID control system, it was confirmed that the disturbance caused by the load fluctuation was eliminated with satisfactory performance and that the changed set value was followed.

• The Journal of the Acoustical Society of Korea
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• v.27 no.6
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• pp.263-270
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• 2008

The performance of an ultrasonic array sensor is determined by the properties of constituent materials and the effects of many structural parameters. In this study, with the finite element method, variation of the performances of an ultrasonic array sensor was analyzed in relation to its structural variables. Based on the analysis result, the structure of the ultrasonic array sensor was optimized to provide the highest sensitivity while satisfying such requirements as fractional bandwidth, center frequency and -20 dB pulse length. The optimization was carried out with the SQP-PD method for a target function composed of the ultrasonic array sensor performance. The optimized ultrasonic array sensor satisfied all the required specifications to be applicable to medical imaging diagnosis. The design technology in this paper can be utilized for other ultrasonic array sensors of a similar structure.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.3
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• pp.71-84
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• 2024

Artificial intelligence can be cited as a key linkage technology for expanding drones' application fields, and drones combined with artificial intelligence are expected to improve drones' operational capabilities based on algorithms that can solve complex tasks through learning. The purpose of this study is to analyze various latest research cases that apply deep reinforcement learning to drones to solve limitations for performing swarm flight and to propose a new research direction that applies them to multi-agent communication optimization technology. The process of the research is to investigate and analyze the methods for efficient operation of control and communication technologies required for swarm flight to be successful, and to apply algorithms that have the advantage of exchanging richer feedback between agents and having less learning than conventional methods when learning deep reinforcement learning algorithms. It is expected that the efficiency and performance of learning communication protocols optimized for swarm flight will be improved, which will increase the efficiency of mission performance when exploring or scouting large areas through swarm flight in the future.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.3
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• pp.75-85
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• 2024

Airpower is a crucial force for suppressing military threats and achieving victory in wars. This study evaluates newly introduced fighter forces, considering factors such as fighter performance and power index, operational environment, capacity of each airbase, survivability, and force sustainment capability to determine the optimal deployment plan that maximizes operational effectiveness and efficiency. Research methods include optimization techniques such as MIP(mixed integer programming), allocation problems, and experimental design. This optimal allocation mathematical model is constructed based on various constraints such as survivability, mission criticality, and aircraft's performance data. The scope of the study focuses the fighter force and their operational radius is limited to major Air Force and joint operations, such as air interdiction, defensive counter-air operations, close air support, maritime operations and so on. This study aims to maximize the operational efficiency and effectiveness of fighter aircraft operations. The results of proposed model through experiments showed that it was for superior to the existing deployment plan in terms of operation and sustainment aspects when considering both wartime and peacetime.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.79-89
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• 2016

In this paper, we proposed the object classification method using genetic and dynamic random forest consisting of optimal combination of unit tree. The random forest can ensure good generalization performance in combination of large amount of trees by assigning the randomization to the training samples and feature selection, etc. allocated to the decision tree as an ensemble classification model which combines with the unit decision tree based on the bagging. However, the random forest is composed of unit trees randomly, so it can show the excellent classification performance only when the sufficient amounts of trees are combined. There is no quantitative measurement method for the number of trees, and there is no choice but to repeat random tree structure continuously. The proposed algorithm is composed of random forest with a combination of optimal tree while maintaining the generalization performance of random forest. To achieve this, the problem of improving the classification performance was assigned to the optimization problem which found the optimal tree combination. For this end, the genetic algorithm methodology was applied. As a result of experiment, we had found out that the proposed algorithm could improve about 3~5% of classification performance in specific cases like common database and self infrared database compare with the existing random forest. In addition, we had shown that the optimal tree combination was decided at 55~60% level from the maximum trees.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.12
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• pp.1065-1072
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• 2014

The shape of an impeller splitter for a dual-inlet centrifugal blower was optimized to enhance the blower performance. Two design variable, the normalized chord and pitch of a splitter, were used to evaluate the blower performance and internal flow fields based on the three-dimensional flow analysis. The blower performance obtained using this numerical simulation had a maximum error of 4 percent compared to that in an experiment at the design flow condition. The shape optimization of the splitter successfully increased the blower efficiency and pressure by 3.65 and 1.14 percent compared to the reference values. The blower performance was increased by reducing the flow separation near the blade suction surface by optimizing the shape of the splitter, which produced a pressure increase at the outlet of the volute casing.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.283-292
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• 2008

The foremost criterion in the design of a Satellite Launch Vehicle(SLV) is its performance capability to boost the designated payload to the desired mission orbit; it starts from focusing on the SLV configuration to achieve the velocity requirements($}\Delta}V$) for the mission. In this paper we review an analytical approach which is suitable enough for preliminary conceptual design and is used previously to optimize stage configurations for Two Stage to Orbit SLV for Low Earth Orbit(LEO) Missions; we have extended this approach to Three Stage to Orbit SLV and compared different propellant options for the mission. The objective is to minimize the Gross Lift off Weight(GLOW). The primary performance figures of merit were the total inert weight of the SLV and the payload weight that the SLV could lift into LEO, given candidate propulsion systems. The optimization is achieved by configuring the $}\Delta}V$ between stages. A comparison of configurations of single-stage and multi-stage SLVs is made for different propellants. Based upon the optimized stage configurations a comparative performance analysis is made between Liquid and Solid fueled SLV. A 3 degree of freedom trajectory-analysis program is modeled in SIMULINK and used to conduct the performance analysis. Furthermore, a cost analysis is performed on our stage optimized SLVs. The cost estimation relationships(CER) used give us a comparison of development and fabrication costs for the Liquid vs. Solid fueled SLV in man years. The pros and cons of the production, operation ability, performance, responsiveness, logistics, price, shelf life, storage etc of both Solid and Liquid fueled SLVs are discussed. The statistics and data are used from existing or historical(real) SLV stages.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.453-460
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• 2019

The SR-DCSK(Short Reference Differential Chaos Shift Keying) is a variant of DCSK that improves data transmission speed and energy efficiency without additional complexity. However, even when the reference signal of the optimum length is applied, the BER performance of the SR-DCSK is not better than that of the conventional DCSK. In this paper, we propose a scheme to improve the performance of SR-DCSK by applying two scale factors (scale coefficients) to the reference signal and the information signal, respectively. And the performance of the proposed method is analyzed by BER using Gaussian Approximation. Based on the derived BER expressions, we minimize the BER for a given system parameter to optimize the ratio of the two coefficients. Simulation results confirm that the BER of the proposed method is much improved over the SR-DCSK when we apply the optimal ratio of the two scale factors.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.556-567
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• 1998

Robust design in industry is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise ratio(SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for robust design to solve the dual response problems without resorting to SN. Two examples illustrate this procedure. in the two different experimental design(product array, combined array) approaches.

• Tribology and Lubricants
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• v.20 no.5
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• pp.259-265
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• 2004

The sealing performance of O-rings is affected by working conditions such as applied pressure, operation temperature, pre-compressed ratio and material properties. In this paper, a pressurized and compressed elastomeric bi-polymer O-ring in which is inserted into a rectangular groove is analyzed by non-linear MARC finite element program based on the Taguchi experimental method. O-rings with 9 different profile models are analyzed for design parameters that are related to the diameter ratio between outer diameter and inner one of bi-polymer O-ring, compressive ratio, groove angle and groove depth. The calculated FEM results showed that the affection ratio of design parameter dlD, which may control sealing pressure of O-rings, is the most influential parameter among the groove angle, groove depth and compression ratio.