• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.7
• /
• pp.1231-1237
• /
• 2022

In the present study, the optimization of the main particulars of a ship using AI-based design search techniques was investigated. For the design search techniques, the SHERPA algorithm by HEEDS was applied, and CFD analysis using STAR-CCM+ was applied for the calculation of resistance performance. Main particulars were automatically transformed by modifying the main particulars of the ship at the stage of preprocessing using JAVA script and Python. Small catamaran was chosen for the present study, and the main dimensions of the length, breadth, draft of demi-hull, and distance between demi-hulls were considered as design variables. Total resistance was considered as an objective function, and the range of displaced volume considering the arrangement of the outfitting system was chosen as the constraint. As a result, the changes in the individual design variables were within ±5%, and the total resistance of the optimized hull form was decreased by 11% compared with that of the existing hull form. Throughout the present study, the resistance performance of small catamaran could be improved by the optimization of the main dimensions without direct modification of the hull shape. In addition, the application of optimization using design search techniques is expected for the improvement in the resistance performance of a ship.

• Journal of information and communication convergence engineering
• /
• v.22 no.2
• /
• pp.98-108
• /
• 2024

Scrypt is a password-based key derivation function proposed by Colin Percival in 2009 that has a memory-hard structure. Scrypt has been intentionally designed with a memory-intensive structure to make password cracking using ASICs, GPUs, and similar hardware more difficult. However, in this study, we thoroughly analyzed the operation of Scrypt and proposed strategies to maximize computational parallelism in GPU environments. Through these optimizations, we achieved an outstanding performance improvement of 8284.4% compared with traditional CPU-based Scrypt computations. Moreover, the GPU-optimized implementation presented in this paper outperforms the simple GPU-based Scrypt processing by a significant margin, providing a performance improvement of 204.84% in the RTX3090. These results demonstrate the effectiveness of our proposed approach in harnessing the computational power of GPUs and achieving remarkable performance gains in Scrypt calculations. Our proposed implementation is the first GPU implementation of Scrypt, demonstrating the ability to efficiently crack Scrypt.

• Journal of Advanced Navigation Technology
• /
• v.14 no.3
• /
• pp.358-366
• /
• 2010

In the wireless network the congestion and delay occurs mainly when there are too many packets for the network to process or the sender transmits more packets than the receiver can accept. The congestion and delay is the reason of packet loss which degrades the performance of multimedia streaming. This paper proposes a novel transmission rate monitoring-based optimization mechanism to optimize packet loss and to improve QoS. The proposed scheme is based on the trade-off relationship between transmission rate monitoring and overhead monitoring. For this purpose this paper processes a source rate control-based optimization which optimizes congestion and delay. Performance evaluated RED, TFRC, and the proposed mechanism. The simulation results show that the proposed mechanism is more efficient than REC(Random Early Detection) mechanism and TFRC(TCP-friendly Rate Control) mechanism in packet loss rate, throughput rate, and average response rate.

• Transactions on Electrical and Electronic Materials
• /
• v.17 no.6
• /
• pp.341-350
• /
• 2016

The current study is dedicated to design a novel coordinated controller to effectively increase power system rotor angle stability. In doing so, the coordinated design of an AVR (automatic voltage regulator), PSS2B, and TCSC (thyristor controlled series capacitor)-based POD (power oscillation damping) controller is proposed. Although the recently employed coordination between a CPSS (conventional power system stabilizer) and a TCSC-based POD controller has been shown to improve power system damping characteristics, neglecting the negative impact of existing high-gain AVR on the damping torque by considering its parameters as given values, may reduce the effectiveness of a CPSS-POD controller. Thus, using a technologically viable stabilizer such as PSS2B rather than the CPSS in a coordinated scheme with an AVR and POD controller can constitute a well-established design with a structure that as a high potential to significantly improve the rotor angle stability. The design procedure is formulated as an optimization problem in which the ITSE (integral of time multiplied squared error) performance index as an objective function is minimized by employing an IPSO (improved particle swarm optimization) algorithm to tune adjustable parameters. The robustness of the coordinated designs is guaranteed by concurrently considering some operating conditions in the optimization process. To evaluate the performance of the proposed controllers, eigenvalue analysis and time domain simulations were performed for different operating points and perturbations simulated on 2A4M (two-area four-machine) power systems in MATLAB/Simulink. The results reveal that surpassing improvement in damping of oscillations is achieved in comparison with the CPSS-TCSC coordination.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.4
• /
• pp.423-434
• /
• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.

• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.28A no.1
• /
• pp.74-84
• /
• 1991

This paper presents an algorithm for technology-dependent logic optimization and technology mapping, and describes a performance-driven logic synthesis system, SILOS, implemented based on the proposed algorithm. The system analyzes circuits and resynthesizes the critical sections such that generated circuit operates opertes within time constraints, using only gate types supported by library for direct implementation. Experimental results show that the system can be a viable tool in synthesizing high-performance logic circuits.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.12 no.2
• /
• pp.9-22
• /
• 2008

This paper presents an integrated optimal design technique of a hybrid structure-damper system for improving the seismic performance of the structure. The proposed technique corresponds to the optimal distribution of the stiffness and dampers. The multi-objective optimization technique is introduced to deal with the optimal design problem of the hybrid system, which is reformulated into the multi-objective optimization problem with a constraint of target reliability in an efficient manner. An illustrative example shows that the proposed technique can provide a set of Pareto optimal solutions embracing the solutions obtained by the conventional sequential design method and single-objective optimization method based on weighted summation scheme. Based on the stiffness and damping capacities, three representative designs are selected among the Pareto optimal solutions and their seismic performances are investigated through the parametric studies on the dynamic characteristics of the seismic events. The comparative results demonstrate that the proposed approach can be efficiently applied to the optimal design problem for improving the seismic performance of the structure.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.34 no.9
• /
• pp.11-19
• /
• 2006

Design program was developed to determine the external shape of the supersonic axisymmetric inlet by combining conical flow solver and approximation technique of conical shock with gradient-based optimization algorithm. Inlet designs were carried out under various operation conditions through optimization with respectively two object functions which consist of pressure recovery and cowl drag and with constraints about shock position, cowl shape, and minimum throat area. New object function consisting of pressure recovery and drag of the external cowl was proposed and the optimized shapes from new object function were compared to the ones from the old object function which maximize only the pressure recovery. Through computations of inviscid and turbulent flow, was tested performance of the design program and performance estimated in design program agreed well with computation results for inlets designed under various flight conditions.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.4
• /
• pp.463-474
• /
• 2004

Game theory is a method of mathematical analysis developed to study the decision making process. In 1928, Von Neumann mathematically proved that every two-person, zero-sum game with many pure finite strategies for each player is deterministic. In the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) as introduced by Maynard Smith in 1982. Keeping pace with these game theoretical studies, the first computer simulation of coevolution was tried out by Hillis. Moreover, Kauffman proposed the NK model to analyze coevolutionary dynamics between different species. He showed how coevolutionary phenomenon reaches static states and that these states are either Nash equilibrium or ESS in game theory. Since studies concerning coevolutionary phenomenon were initiated, there have been numerous other researchers who have developed coevolutionary algorithms. In this paper we propose a new coevolutionary algorithm named Game theory based Coevolutionary Algorithm (GCEA) and we confirm that this algorithm can be a solution of evolutionary problems by searching the ESS. To evaluate this newly designed approach, we solve several test Multiobjective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by the coevolutionary algorithm and analyze the optimization performance of our algorithm by comparing the performance of our algorithm with that of other evolutionary optimization algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.3A
• /
• pp.249-253
• /
• 2006

We propose a new beamforming algorithm, which is based on simplex downhill optimization method in the presence of pilot channels in cdma2000 reverse-link, for the rake structure antenna array in DS/CDMA communication system. Our approach uses the desired signal(pilot) covariance matrix and the interference covariance matrix. The beamforming weights are made according to maximum SINR criteria using simplex downhill optimization procedure. Our proposed scheme provides lower computational load, better convergence speed, better performance than existingadaptive beamforming algorithm. The simplex downhill method is well suited to finding the optimal or sub-optimal weight vector, since they require only the value of the deterministic function to be optimized. The rake beamformer performances are also evaluated under several set of practical parameter values with regard to spatial channel model. We also compare the performance between conventional rake receiver and the proposed one under same receiving power.