• Journal of Advanced Marine Engineering and Technology
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• v.38 no.6
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• pp.716-722
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• 2014

In order to design the speed controller of the DC motor system, firstly, parameters estimation of the system must be preceded. In this paper, we proposed the application of genetic algorithm(GA) optimization in estimating the parameters of DC motor. Estimated models are considered both first and second order models, and each estimated model is optimized by minimizing three different types of the evaluation function of GA. Also, GA is imported in comparison with estimation result of numerical analysis method because of its power in searching entire solution space with more probability of finding the global optimum. Data for parameter estimation is acquired from input and output signals of the actual experiment device and the butterworth filter also designs for removing noise in the signals. Finally comparison between real data of the actual device and estimated models is presented to indicate effectiveness and resolution of proposed identification method.

• The Plant Pathology Journal
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• v.32 no.1
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• pp.58-64
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• 2016

Bacterial wilt of tomatoes caused by Ralstonia solanacearum is a devastating disease that limits the production of tomato in Korea. The best way to control this disease is using genetically resistant tomato plant. The resistance degree to R. solanacearum was evaluated for 285 tomato accessions conserved in the National Agrobiodiversity Center of Rural Development Administration. These accessions of tomato were originated from 23 countries. Disease severity of tomato accessions was investigated from 7 days to 14 days at an interval of 7 days after inoculation of R. solanacearum under greenhouse conditions. A total of 279 accessions of tomato germplasm were susceptible to R. solanacearum, resulting in wilt and death in 70 to 90% of these plants. Two tomato accessions were moderately resistant to R. solanacearum. Only four accessions showed high resistance against R. solanacearum. No distinct symptom of bacterial wilt appeared on the resistant tomato germplasms for up to 14 days after inoculation of R. solanacearum. Microscopy of resistant tomato stems infected with R. solanacearum revealed limited bacterial spread with thickening of pit membrane and gum production. Therefore, these four resistant tomato germplasms could be used in tomato breeding program against bacterial wilt.

• The Plant Pathology Journal
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• v.36 no.1
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• pp.11-28
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• 2020

Faba bean (Vicia faba L.) is one of the most important legume crops in Egypt. However, production of faba bean is affected by several diseases including fungal diseases. Fusarium wilt incited by Fusarium oxysporum Schlecht. was shown to be the most common wilt disease of faba bean in Assiut Governorate. Evaluation of 16 faba bean genotypes for the resistance to Fusarium wilt was carried out under greenhouse conditions. Three molecular marker systems (inter-simple sequence repeat [ISSR], sequence related amplified polymorphism [SRAP], and simple sequence repeat [SSR]) and a biochemical marker (protein profiles) were used to study the genetic diversity and detect molecular and biochemical markers associated with Fusarium wilt resistance in the tested genotypes. The results showed that certain genotypes of faba bean were resistant to Fusarium wilt, while most of the genotypes were highly susceptible. The percentage of disease severity ranged from 32.83% in Assiut-215 to 64.17% in Misr-3. The genotypes Assiut-215, Roomy-3, Marut-2, and Giza2 were the most resistant, and the genotypes Misr-3, Misr-1, Assiut-143, Giza-40, and Roomy-80 performed as highly susceptible. The genotypes Assiut-215 and Roomy-3 were considered as promising sources of the resistance to Fusarium wilt. SRAP markers showed higher polymorphism (82.53%) compared with SSR (76.85%), ISSR markers (62.24%), and protein profile (31.82%). Specific molecular and biochemical markers associated with Fusarium wilt resistance were identified. The dendrogram based on combined data of molecular and biochemical markers grouped the 16 faba bean genotypes into three clusters. Cluster I included resistant genotypes, cluster II comprised all moderate genotypes and cluster III contained highly susceptible genotypes.

• Journal of Life Science
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• v.21 no.3
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• pp.468-472
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• 2011

DNA marker is a powerful tool for plant genetics and breeding. In this study, 995 SSR markers were employed with chilling resistant cucumber, known as 'NC76', and chilling susceptible cucumber, known as 'GY14'. Using 2% agarose gel electrophoresis, 145 SSR markers were identified as length variation markers between 'NC76' and 'GY14'. The SSR markers that showed no length polymorphism were then screened using high resolution melting analysis technique and additional 30 polymorphic SSR markers were identified. As a preliminary evaluation for mapping, 20 markers among these 175 markers were employed to a $F_2$ population of 'NC76' x 'GY14' cross. Linkage analysis revealed 13 markers that joined into six linkage groups and seven markers that remained unlinked. This result indicates that these 175 markers could be used for construction of a genetic map using a cross between 'NC76' and 'GY14' for further investigation in developing markers related to resistance to chilling in cucumbers.

• Convergence Security Journal
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• v.17 no.1
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• pp.31-38
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• 2017

As the cyber-attacks through the networks advance, it is difficult for the intrusion detection system based on the simple rules to detect the novel type of attacks such as Advanced Persistent Threat(APT) attack. At present, many types of research have been focused on the application of machine learning techniques to the intrusion detection system in order to detect previously unknown attacks. In the case of using the machine learning techniques, the performance of the intrusion detection system largely depends on the feature set which is used as an input to the system. Generally, more features increase the accuracy of the intrusion detection system whereas they cause a problem when fast responses are required owing to their large elapsed time. In this paper, we present a network intrusion detection system based on artificial neural network, which adopts a multi-objective genetic algorithm to satisfy the both requirements: accuracy, and fast response. The comparison between the proposing approach and previously proposed other approaches is conducted against NSL_KDD data set for the evaluation of the performance of the proposing approach.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• 대한생식의학회:학술대회논문집
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• 2003.12a
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• pp.21-30
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• 2003

As a result of the technological advance provided by intracytoplasmic sperm injection (ICSI) in 1992, the evaluation and treatment of the infertile male has changed significantly. Many men who were previously thought to be irreversibly infertile have the potential to initiate their own biologic pregnancy. However, not all men having impaired semen parameter are ideal candidates for ICSI for numerous reasons including a lack of addressing the underlying problem causing the male infertility, unknown genetic consequences, and cost-effectiveness issues. In this era of ICSI, the fundamental approach to the male with suspected subfertility is unchanged and is based on a history, physical examination, and focused laboratory testing. The urologist should approach the patient with an intent to identify remediable causes of subfertility given the specific clinical situation. For instance, should a gentleman have his varicocele repaired or vasectomy reversed, or should he proceed directly with ICSI? If no factors can be improved in a timely manner, then ICSI should be considered using the available sperm. Examples of recent advances include the diagnosis and treatment of ejaculatory duct obstruction, indications and techniques for performing testis biopsy, and technique for sperm harvesting. In addition, potential genetic causes of male subfertility should be diagnosed and discussed with the patient. Cystic fibrosis gene mutation, karyotype abnormallities, and Y-chromosome microdeletions all have recently been identified as causative for male infertility in otherwise phenotypically normal men. With recently evolved diagnostic and therapeutic techniques now available for the infertile couple, even the most severe male factor problems in patients previously considered irreversibly infertile are now potentially treatable. The physician should be aware of the availability and limitations of these new and exciting reproductive technologies because they will allow him to provide timely and more effective therapy for the infertile couple. An understanding of these advances by all physicians is important as we progress into the $21^{st}$ century

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1202-1211
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• 2018

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

• Journal of Genetic Medicine
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• v.17 no.1
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• pp.43-46
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• 2020

The Shprintzen-Goldberg syndrome (SGS) is an extremely rare genetic disorder caused by heterozygous variant in SKI. SGS is characterized by neurodevelopmental impairment with skeletal anomaly. Recognition of SGS is sometimes quite challenging in practice because it has diverse clinical features involving skeletal, neurological, and cardiovascular system. Here we report a case of a 6-month-old boy who initially presented with developmental delay and marfanoid facial features including prominent forehead, hypertelorism, high arched palate and retrognathia. He showed motor developmental delay since birth and could not control his head at the time of first evaluation. His height was above 2 standard deviation score. Arachnodactyly, hypermobility of joints, skin laxity, and pectus excavatum were also noted. Sequencing for FBN1 was negative, however, a novel missense variant, c.350G>A in SKI was identified by sequential whole exome sequencing. To our knowledge, this is the first case with SGS with phenotypic features of SGS overlapping with those of the Marfan syndrome, diagnosed by next generation sequencing in Korea.

• Journal of Food Hygiene and Safety
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• v.29 no.4
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• pp.383-390
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• 2014

The safety of a new natural plant composition (ADP) was assessed on the genotoxicity study and 14-day repeat dose toxicity study. ADP contains a mixed water extract obtained from the mixture of Phellodendron cortex (Phellodendron amurense) and Anemarrhena rhizoma (Anemarrhena asphodeloides), and poses the contractile properties mediated by alpha-adrenoceptor of the prostate and urethra as well as antioxidant and anti-inflammatory properties. In order to evaluate genetic safety, in vivo micronucleus test was performed in ICR mice orally administered with three dose levels of 1250, 2500, 5000 mg/kg body weight, and vehicle and positive control. In the 14 days study, Sprague-Dawley rats were treated with ADP at the dose levels of 500, 1000, 2000 mg/kg once a day, and clinical signs, body weights, hematology, serum biochemistry, necropsy findings and organ weights were monitored and examined. In experimental results, ADP treatment, compared with vehicle control, did not induce the micronucleated erythrocytes from mouse bone marrow. In the 14 days study, any significant and toxicological differences in all measurements of parameters were not observed in ADP treatment groups of animals, compared with vehicle treatment. The No-Observed-Adverse-Effect-Level (NOAEL) of ADP in the 14 days study was determined to be greater than 2000 mg/kg/day in both sexes.