• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.1-10
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• 1998

Process planning is a very complex task and requires the dynamic informatioon of shop foor and market situations. Process plan selection is one of the main problems in the process planning. In this paper, we propose a new process plan selection model considering operation flexibility for the computer aided process planing. The model is formulated as a 0-1 integer programming considering realistic shop factors such as production volume, machining time, machine capacity, transportation time and capacity of tractors such as production volume, machining time, machine capacity, transportation time capacity of transfer device. The objective of the model is to minimize the sum of the processing and transportation time for all parts. A genetic algorithm a, pp.oach is developed to solve the model. The efficiency of the proposed a, pp.oach is verified with numerical examples.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2545-2547
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• 2000

In this paper, a hybrid fuzzy controller using genetic algorithm based on parameter estimation mode to obtain optimal control parameter is presented. First, The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PID's output in steady state by a fuzzy variable, namely, membership function of weighting coefficient. Second, genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller utilizing the conventional methods for finding PID parameters and estimation mode of scaling factor. The algorithms estimates automatically the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules according to the rate of change and limitation condition of control input. Computer simulations are conducted to evaluate the performance of proposed hybrid fuzzy controller. ITAE, overshoot and rising time are used as a performance index of controller.

• Structural Engineering and Mechanics
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• v.17 no.5
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• pp.707-725
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• 2004

An optimal design method with nonlinear elastic analysis is presented. The proposed nonlinear elastic method overcomes the drawback of the conventional LRFD method that accounts for nonlinear effect by using the moment amplification factors of $B_1$ and $B_2$. The genetic algorithm used is a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are employed to look for high performance ones among sections in the database. They are satisfied with the constraint functions and give the lightest weight to the structure. The objective function taken is the total weight of the steel structure and the constraint functions are strength, serviceability, and ductility requirement. Case studies of a planar portal frame, a space two-story frame, and a three-dimensional steel arch bridge are presented.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.1
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• pp.36-43
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• 2003

This paper presents an optimal tuning method for Fuzzy Logic Controller (FLC) of current controller for HVDC using Genetic Algorithm(GA). GA is probabilistic search method based on genetics and evolution theory. The scaling factors of FLC are tuned by using real-time GA. The proposed tuning method is applied to the scaled-down HVDC simulator at Korea Electrotechnology Research Institute(KERI). Experimental result shows that disturbances are well-damped and the dynamic performances of FLC have the better responses than those of PI controller for small and large disturbances such as ULTC tap change, reference DC current change and DC ground fault.

• Journal of Microbiology
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• v.43 no.spc1
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• pp.85-92
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• 2005

An early step in the pathogenesis of non-typhoidal Salmonella species is the ability to penetrate the intestinal epithelial monolayer. This process of cell invasion requires the production and transport of secreted effector proteins by a type III secretion apparatus encoded in Salmonella pathogenicity island I (SPI-1). The control of invasion involves a number of genetic regulators and environmental stimuli in complex relationships. SPI-1 itself encodes several transcriptional regulators (HilA, HilD, HilC, and InvF) with overlapping sets of target genes. These regulators are, in turn, controlled by both positive and regulators outside SPI-1, including the two-component regulators BarA/SirA and PhoP/Q, and the csr post-transcriptional control system. Additionally, several environmental conditions are known to regulate invasion, including pH, osmolarity, oxygen tension, bile, $Mg^{2+}$ concentration, and short chain fatty acids. This review will discuss the current understanding of invasion control, with emphasis on the interaction of environmental factors with genetic regulators that leads to productive infection.

• Bulletin of the Korean Chemical Society
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• v.19 no.5
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• pp.544-548
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• 1998

A Monte Carlo simulation incorporated with the genetic algorithm is presented to describe the defect known as "transition from Y-to X-type deposition" of the cadmium arachidate Langmuir-Blodgett multilayer film. Simulation is performed based on the detachment models of XY-type deposition. The transition is simulated by introducing a probability of surface molecule detachment considering interaction between neighboring molecules. The genetic algorithm is incorporated into Monte Carlo simulation to get the optimum value of the probability factors. The distribution of layers having different thickness predicted by the simulation correlates well with the measured distribution of thickness using the small-angle X-ray reflectivity. The effect of chain length and subphase temperature on the detachment probability are investigated using the simulation. Simulation results show that an increase (or a decrease) of two hydrocarbon chain is roughly equivalent to the detachment probability to a temperature decrease (or increase) of 15 K.

• Genomics & Informatics
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• v.19 no.1
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• pp.3.1-3.12
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• 2021

Functional interpretation of noncoding genetic variants associated with complex human diseases and traits remains a challenge. In an effort to enhance our understanding of common germline variants associated with lung cancer, we categorize regulatory elements based on eight major cell types of human lung tissue. Our results show that 21.68% of lung cancer-associated risk variants are linked to noncoding regulatory elements, nearly half of which are cell type-specific. Integrative analysis of high-resolution long-range chromatin interactome maps and single-cell RNA-sequencing data of lung tumors uncovers number of putative target genes of these variants and functionally relevant cell types, which display a potential biological link to cancer susceptibility. The present study greatly expands the scope of functional annotation of lung cancer-associated genetic risk factors and dictates probable cell types involved in lung carcinogenesis.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.219-226
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• 2018

Collaborative filtering has been most popular approach to recommend items in online recommender systems. However, collaborative filtering is known to suffer from data sparsity problem. As a simple way to overcome this problem in literature, Jaccard index has been adopted to combine with the existing similarity measures. We analyze performance of such combination in various data environments. We also find optimal weights of factors in the combination using a genetic algorithm to formulate a similarity measure. Furthermore, optimal weights are searched for each user independently, in order to reflect each user's different rating behavior. Performance of the resulting personalized similarity measure is examined using two datasets with different data characteristics. It presents overall superiority to previous measures in terms of recommendation and prediction qualities regardless of the characteristics of the data environment.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.31-31
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• 2022

Rice contains a wealth of genetic diversity, both within Oryza sativa and in related A-genome species. Decades of genetic research into this diversity have identified dozens of major genes contributing to a wide variety of important traits, including disease resistance, abiotic stress tolerance (drought, salinity, submergence, heat, cold etc.), grain quality, flowering date and maturity and plant architecture. Yet despite these opportunities, very few of the major genes and QTLs known have been successfully applied through rice breeding programs to produce sustained changes in farmer's fields. This presentation will briefly examine some of the factors limiting application of major genes in the mainstream breeding programs, and steps that have been taken to alleviate those limitations. As a result of these interventions, dozens of major genes that were previously unavailable to breeders are now being used confidently in the variety development process. Case studies will be discussed of genes critical for blast resistance worldwide, rice yellow mottle virus for Africa, and new validated QTLs for salinity tolerance.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.2
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• pp.151-157
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• 2005

Sheep production is affected by genetic and non-genetic factors. A knowledge of these factors is essential for efficient management and for the accurate estimation of breeding values. The objective of this study was to establish the non-genetic factors which affect birth weight and weaning weight in Dorper, Mutton Merino and indigenous Sabi sheep breeds. A total of 2,625 birth and weaning weight records from Grasslands Research Station collected from 1991 through 1993, were used. The records were collected from indigenous Sabi (939), Dorper (807) and Mutton Merino (898) sheep. A mixed classification model containing the fixed effects of year, birth status and sex was used for identification of non-genetic factors. Sire within breed was included as a random effect. Two factor interactions and three factor interactions were important in indigenous Sabi, Mutton Merino and Dorper sheep. The mean birth weights were 4.37${\pm}$0.04 kg, 4.62${\pm}$0.04 kg and 3.29${\pm}$0.04 kg for Mutton Merino, Dorper and Sabi sheep, respectively. Sire had significant effects (p<0.05) on birth weight in Mutton Merino and indigenous Sabi sheep. Year of lambing had significant effects (p<0.05) on birth weight in indigenous Sabi, Mutton Merino and Dorper sheep. The effect of birth status was non significant in Dorper and Mutton Merino sheep while effect of birth status was significant on birth weight in indigenous Sabi sheep. In Indigenous Sabi sheep lambs born as singles (3.30${\pm}$0.05 kg) were 0.23 kg heavier than twins (3.07${\pm}$0.05 kg), in Mutton Merino lambs born as singles (3.99${\pm}$0.08 kg) were 0.07 kg heavier than twins (3.92${\pm}$0.08 kg) and in Dorper lambs born as singles (4.41${\pm}$0.04 kg) were 0.02 kg heavier than twins (4.39${\pm}$0.04 kg). On average males were heavier than females (p<0.05) weighing (3.32${\pm}$0.04 kg vs. 3.05${\pm}$0.07 kg) in indigenous Sabi, 4.73${\pm}$0.03 kg vs. 4.08${\pm}$0.05 in Dorper and 4.26${\pm}$0.07 kg vs. 3.66${\pm}$0.09 kg in Mutton Merino sheep. Two way factor interactions of sire*year, year*sex and sex*birth status had significant effects (p<0.05) on birth weight in indigenous Sabi, Mutton Merino and Dorper sheep while the effect of year*birth status was non significant on birth weight in Indigenous Sabi sheep. The three way factor interaction of year*sex*birth status had a significant effect (p<0.01) on birth weight in indigenous Sabi and Mutton Merino. Tupping weight fitted as a covariate had significant effects (p<0.001) on birth weight in indigenous Sabi, Mutton Merino and Dorper sheep. The mean weaning weights were 17.94${\pm}$0.31 kg, 18.19${\pm}$0.28 kg and 14.39${\pm}$0.28 kg for Mutton Merino, Dorper and Indigenous Sabi sheep, respectively. Effects of sire and sire*year were non significant on weaning weight in Dorper and Mutton Merino while year, sex and sex*year interaction had significant effects (p<0.001) on weaning weight. On average males were heavier than females (p<0.001) at weaning. The respective weaning weights were 18.05${\pm}$0.46 kg, 18.68${\pm}$0.19 kg, 14.14${\pm}$0.15 kg for males and 16.64${\pm}$0.60 kg, 16.41${\pm}$0.31 kg, 12.64${\pm}$0.32 kg for females in Mutton Merino, Dorper and Indigenous Sabi sheep. Lambs born as singles were significantly heavier at weaning than twins, 0.05 kg, 0.06 kg and 0.78 kg for Mutton Merino, Dorper and Indigenous Sabi sheep, respectively. Effect of tupping weight was highly significant on weaning weight. The three way factor interaction year*sex*birth status had a significant effect (p<0.01) on weaning weight. Correction for environmental effects is necessary to increase accuracy of direct selection for birth weight and weaning weight.