• Journal of Information Processing Systems
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• v.18 no.3
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• pp.389-401
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• 2022

The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.43-43
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• 2018

Mutation breeding by radiation is useful for improving various crop species. Up to now, a total of 170 soybean mutant varieties have been released in the world, which is the second most registered varieties after rice. Despite the economic importance of soybean, there have been no TRAP marker system studies on genetic relationships between/among mutant lines. To develop a strategy of Mutant Diversity Pool (MDP) conservation, a study on the genetic diversity of 210 soybean mutant lines (8 cultivars and 202 mutants) was performed through a TRAP analysis. Sixteen primer combinations amplified a total of 551 fragments. The highest (84.00%) and lowest (32.35%) polymorphism levels were obtained with primers MIR157B + Ga5 and B14G14B + Ga3, respectively. The mean PIC values 0.15 varied among the primer combination ranging from 0.07 in B14G14B + Sal2 to 0.23 in MIR157B + Sa4. Phylogenetic, principal component analysis (PCA) and structure analysis indicated that the 210 lines belong to four groups based on the 16 combination TRAP markers. AMOVA showed 21.0% and 79.0% variations among and within the population, respectively. Overall, the genetic similarity of each cultivar and its mutants were higher than within other mutant populations. Our results suggest that the TRAP marker system may be useful for assessing the genetic diversity among soybean mutants and help to improve our knowledge of soybean mutation breeding.

• Journal of KIISE
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• v.43 no.2
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• pp.204-211
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• 2016

In this paper, we propose an automatic melody composition system that can generate a sophisticated melody by adding non-harmony tone in the given chord progression. An overall procedure consists of two steps, which are the rhythm generation and melody generation parts. In the rhythm generation part, we designed new fitness functions for rhythm that can be controlled by a user setting parameters. In the melody generation part, we designed new fitness functions for melody based on harmony theory. We also designed evolutionary operators that are conducted by considering a musical context to improve computational efficiency. In the experiments, we compared four metaheuristics to optimize the rhythm fitness functions: Simple Genetic Algorithm (SGA), Elitism Genetic Algorithm (EGA), Differential Evolution (DE), and Particle Swarm Optimization (PSO). Furthermore, we compared proposed genetic algorithm for melody with the four algorithms for verifying performance. In addition, composition results are introduced and analyzed with respect to musical correctness.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.7
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• pp.81-91
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• 2006

Recently, G.A studies have studied and demonstrated that artificial intelligence like G.A networks, G.A PI controller. The design techniques of PI controller using G.A with the newly proposed teaming algorithm was presented, and the designed controller with AC servo motor system. The goal of this paper is to design the AC servo motor using genetic algorithm and to control drive robot. And in this paper, we propose a genetic algorithms approach to find an optimal or near optimal input variables for genetic algorithm PI controller. Our experimental results show that this approach increases overall classification accuracy rate significantly. Finally, we executed for the implementation of high performance speed control system. It is used a 16-bit DSP, IMS320LF2407, which is capable of the high speed and floating point calculation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.100-111
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• 2009

Cognitive radio is an advanced technology for efficient utilization of under-utilized spectrum via spectrum sensing. CR users should move from current allocating channel to empty channel to avoid the interference to the primary user if the primary user is allocating that channel. Thus, CR system cannot support the CR user's QoS(Quaiity of Service). In this paper, we propose dynamic frequency selection method based on Genetic Algorithm with power control. It is to find the optimization channel for satisfying various CR user's needs with the power control method to minimize the CR user's interference to the primary user. And, we propose the Genetic Algorithm(GA) which determines the best configuration for CR communication systems. The computer simulation results show that the proposed method guaranteed the primary user's decodability and the optimized solution for various channel status.

• Journal of Digital Contents Society
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• v.2 no.1
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• pp.51-61
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• 2001

The FLC(Fuzzy Logic Controller) is stronger to the disturbance and has the excellent characteristic to the overshoot of the initialized value than the classical controller, and also can carry out the proper control being out of all relation to the mathematical model and parameter value of the system. But it has the restriction which can't adopt the environment changes of the control system because of generating the fuzzy control rule through an expert's experience and the fixed value of the once determined control rule, and also can't converge correctly to the desired value because of haying the minute error of the controller output value. Now there are many suggested methods to eliminate the minute error, we also suggest the GA-FNNIC(Genetic Algorithm Fuzzy Neural Network Intelligence Controller) combined FLC with NN(Neural Network) and GA(Genetic Algorithm). In this paper, we compare the suggested GA-FNNIC with FLC and analyze the output characteristics, convergence speed, overshoot and rising time. Finally we show that the GA-FNNIC converge correctly to the desirable value without any error.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.3
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• pp.275-283
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• 2012

This paper presents a design method of a robust tracking controller satisfying multiple constraints using genetic algorithm. A robust $H_{\infty}$ constraint with loop shaping is used to address disturbance attenuation with error limits and a loop gain constraint is considered so as not to enlarge the tracking loop gain and bandwidth unnecessarily. The robust $H_{\infty}$ constraint is expressed by a matrix inequality and the loop gain constraint is considered as an objective function so that genetic algorithm can be applied. Finally, a robust tracking controller can be obtained by integrating genetic algorithm with LMI approach. The proposed tracking controller design method is applied to the track-following system of an optical DVD recording drive and is evaluated through the experimental results.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.619-624
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• 2011

This paper presents a controller design method for a robust control problem with multiple constraints using genetic algorithms and LMI design method. A robust $H_{\infty}$ constraint with loop shaping and pole placement is used to address disturbance attenuation with error limits and desired transient specifications, in spite of the plant uncertainties and disturbances. In addition, a loop gain constraint is considered so as not to enlarge the loop gain unnecessarily. The robust $H_{\infty}$ constraint and pole placement constraint can be expressed in terms of two matrix inequalities and the loop gain constraint can be considered as an objective function so that genetic algorithms can be applied. Accordingly, a robust controller can be obtained by integrating genetic algorithms with LMI approach. The proposed controller design method is applied to a track-following system of an optical disk drive and is evaluated through simulation results.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.2
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• pp.123-128
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• 2002

A fuzzy traffic controller with the control rules and the membership functions generated by using genetic algorithm is presented for crossroad management. Conventional fuzzy traffic controllers use control rules and membership functions generated by human operators. However, this approach does not guarantee the optimal solution to design fuzzy control system. Genetic algorithm is a good solution for an optimal problem requiring domain-specific knowledge that is often heuristic. In this paper, we use genetic algorithms to automatically determine the near optimal rules and their membership functions of fuzzy traffic controllers. The effectiveness of our method was shown through simulation of crossroad network.

• BMB Reports
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• v.28 no.3
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• pp.216-220
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• 1995

cDNA for human cholesteryl ester transfer protein (CETP), a potent atherogenic plasma protein that redistributes the neutral lipids among lipoproteins, was expressed in recombinant vaccinia virus-infected cells (CV-1). Two insertion vectors regulated by different promoters were constructed. The vectors were introduced into human thymidine kinase-negative ($TK^-$) 1438 cells infected with wild-type vaccinia virus (WR strain). Recombinant viruses were selected with 5-bromodeoxyuridine (BUdR) and X-gal and identified with DNA dot blot analysis (vSC11-CETP and vTM1-CETP). The CETP cDNA insert in the recombinant vaccinia virus genome was identified by Southern blot analysis. Transcription of CETP cDNA in CV-1 cells infected with recombinant vaccinia virus was monitored by Northern blot analysis using the CETP cDNA as a probe. Positive signals were detected at 1.8 kb in cells infected with vSC11-CETP and at 2.3 kb in cells infected with vTM1-CETP. The recombinant vaccinia virus-infected CV-1 cells were shown to produce functional CETP when the culture medium was subjected to the CETP assay.