• Journal of Mechanical Science and Technology
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• v.16 no.1
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• pp.75-82
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• 2002

A simultaneous optimal design problem of structural and control systems is discussed by taking a 3-D truss structure as an object. We use descriptor forms for a controlled object and a generalized plant because the structural parameters appear naturally in these forms. We consider a minimum weight design problem for structural system and disturbance suppression problem for the control system. The structural objective function is the structural weight and the control objective function is $H_{\infty}$ norm from the disturbance input to the controlled output in the closed-loop system. The design variables are cross sectional areas of the truss members. The conditions for the existence of controller are expressed in terms of linear matrix inequalities (LMI) By minimizing the linear sum of the normalized structural objective function and control objective function, it is possible to make optimal design by which the balance of the structural weight and the control performance is taken. We showed in this paper the validity of simultaneous optimal design of structural and control systems.

• Journal of the Optical Society of Korea
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• v.14 no.4
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• pp.431-437
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• 2010

A stack of gradient-index (GRIN) rod lenses cannot be used for coherent anti-Stokes Raman scattering (CARS) microendoscopy for insertion to internal organs through a surgical keyhole with minimal invasiveness. That's because GRIN lens has large amount of inherent chromatic aberrations in spite of absolutely requiring a common focus for pump and Stokes beam with each frequency of ${\omega}_p$ and ${\omega}_S$. For this endoscopic purpose, we need to develop a long slender probe-type objective, namely probe-type microscope objective (PMO). In this paper, we introduce the structure, the working principle, and the design techniques of PMO which is composed of a probe-type lens module (PLM) and an adaptor lens module (ALM). PLM is first designed for a long slender type and ALM is successively designed by using several design parameters from PLM for eliminating optical discords between scanning unit and PLM. A combined module is optimized again to eliminate some coupling disparities between PLM and ALM for the best PMO. As a result, we can obtain a long slender PMO with perfectly diffraction-limited performance for pump beam of 817 nm and Stokes beam of 1064 nm.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1027-1037
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• 2017

Penetration of renewable energy sources makes the modern interconnected power systems to have more intelligence and flexibility in the control. Hence, it is essential to maintain the system frequency and tie-line power exchange at nominal values using Load Frequency Control (LFC) for efficient, economic and reliable operation of power systems. In this paper, intelligent tuning of the Proportional Integral Derivative (PID) controller for LFC in an interconnected power system is considered as a main objective. The chosen problem is formulated as an optimization problem and the optimal gain parameters of PID controllers are computed with three innovative swarm intelligent algorithms named Particle Swarm Optimization (PSO), Bacterial Foraging Optimization Algorithm (BFOA) and hybrid Bacterial Foraging Particle Swarm Optimization (BFPSO) and a comparative study is made between them. A new objective function designed with necessary time domain specifications using weighted sum approach is also offered in this report and compared with conventional objective functions. All the simulation results clearly reveal that, the hybrid BFPSO tuned PID controller with proposed objective function has better control performances over other optimization methodologies.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.578-587
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• 2012

One of the key elements in the emerging, packet-based long term evolution (LTE) cellular systems is the deployment of multiple femtocells for the improvement of coverage and data rate. However, arbitrary overlaps in the coverage of these femtocells make the handover operation more complex and challenging. As the existing handover strategy of LTE systems considers only carrier to interference plus noise ratio (CINR), it often suffers from resource constraints in the target femtocell, thereby leading to handover failure. In this paper, we propose a new efficient, multi-objective handover solution for LTE cellular systems. The proposed solution considers multiple parameters like signal strength and available bandwidth in the selection of the optimal target cell. This results in a significant increase in the handover success rate, thereby reducing the blocking of handover and new sessions. The overall handover process is modeled and analyzed by a three-dimensional Markov chain. The analytical results for the major performance metrics closely resemble the simulation results. The simulation results show that the proposed multi-objective handover offers considerable improvement in the session blocking rates, session queuing delay, handover latency, and goodput during handover.

• International Journal of Automotive Technology
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• v.6 no.2
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• pp.141-148
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• 2005

In order to reduce the time and costs of improving the performance of vehicle suspensions, the techniques for optimizing damping and air spring characteristic were proposed. A full vehicle model for a bus is constructed with a car body, front and rear suspension linkages, air springs, dampers, tires, and a steering system. An air spring and a damper are modeled with nonlinear characteristics using experimental data and a curve fitting technique. The objective function for ride quality is WRMS (Weighted RMS) of the power spectral density of the vertical acceleration at the driver's seat, middle seat and rear seat. The objective function for handling performance is the RMS (Root Mean Squares) of the roll angle, roll rate, yaw rate, and lateral acceleration at the center of gravity of a body during a lane change. The design variables are determined by damping coefficients, damping exponents and curve fitting parameters of air spring characteristic curves. The Taguchi method is used in order to investigate sensitivity of design variables. Since ride and handling performances are mutually conflicting characteristics, the validity of the developed optimum design procedure is demonstrated by comparing the trends of ride and handling performance indices with respect to the ratio of weighting factors. The global criterion method is proposed to obtain the solution of multi-objective optimization problem.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.5
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• pp.535-543
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• 2014

In the robust optimization field, the robustness of the objective function emphasizes an insensitive design. In general, the robustness of the objective function can be achieved by reducing the change of the objective function with respect to the variation of the design variables and parameters. However, in conventional methods, when an insensitive design is emphasized, the performance of the objective function can be deteriorated. Besides, if the numbers of the design variables are increased, the numerical cost is quite high in robust optimization for nonlinear programming problems. In this research, the robustness index for the objective function and a process of robust optimization are proposed. Moreover, a method using the supremum of linearized functions is also proposed to reduce the computational cost. Mathematical examples are solved for the verification of the proposed method and the results are compared with those from the conventional methods. The proposed approach improves the performance of the objective function and its efficiency.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.45-47
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• 2006

Cleft palate is a congenital deformity condition with separation of the two sides of the lip resulting in nose deformity. Evaluation of surgical corrections and outcome assessments for nose deformity due to the cleft lip depends mainly on doctor's subjective judgment. An objective method for evaluation of the condition and surgical outcome of nose deformity due to the cleft palate is needed. This study aimed at objective assessment of a cleft palate nose deformity condition by analyzing the following parameters obtained from photographic images of a cleft palate patients: (1) angle difference between two nostril axes. (2) center of the nostril and distance between two centers. (3) overlapped area of two nostrils, and (4) the overlapped area ratio of the two nostrils. A regression equation of doctor's grades was obtained using the eight parameters. Three plastic surgeons gave us the grades for the each photographic image by 10 increments with maximum grade of 100. The average reproducibility of the grades given by the three plastic surgeons and the three laymen using the developed program was $10.8{\pm}4.6%$ and $7.4{\pm}1.8%$, respectively. Kappa values representing the degree of consensus of the plastic surgeons and the three laymen were 0.43 and 0.83. respectively. Correlation coefficient of the grades evaluated by the surgeons and obtained by the neural network was 0.798. In conclusion. the developed neural network model provided us better reproducibility and much better consensus than doctor's subjective evaluation in addition to objectiveness and easy application.

• Structural Engineering and Mechanics
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• v.84 no.1
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• pp.17-33
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• 2022

An experimental study is carried out to investigate the performance of the cutting tool regarding the insert wear, surface roughness, cutting forces, cutting power and material removal rate of three coated carbides GC2015 (TiCN-Al₂O₃-TiN), GC4215 (Al₂O₃-Ti(C,N)) and GC1015 (TiN) during the dry turning of AISI4140 steel. For this purpose, a Taguchi design (L₉) was adopted for the planning of the experiments, the effects of cutting parameters on the surface roughness (R_a), tangential cutting force (F_z), the cutting power (P_c) and the material removal rate (MRR) were studied using analysis of variance (ANOVA), the response surface methodology (RSM) was used for mathematical modeling, with which linear mathematical models were developed for forecasting of R_a, F_z, P_c and MRR as a function of cutting parameters (V_c, f, and a_p). Then, Multi-Objective Ant Lion Optimizer (MOALO) has been implemented for multi-objective optimization which allows manufacturers to enhance the production performances of the machined parts. Furthermore, in order to characterize and quantify the flank wear of the tested tools, some machining experiments were performed for 5 minutes of turning under a depth of 0.5 mm, a feed rate of 0.08 mm/rev, and a cutting speed of 350 m/min. The wear results led to a ratio (V_B-GC4215/V_B-GC2015) of 2.03 and (V_B-GC1015/V_B-GC2015) of 4.43, thus demonstrating the efficiency of the cutting insert GC2015. Moreover, SEM analysis shows the main wear mechanisms represented by abrasion, adhesion and chipping.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.642-652
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• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.