• Journal of the Korean Society of Propulsion Engineers
• /
• v.17 no.2
• /
• pp.71-83
• /
• 2013

Recently, the advanced condition monitoring methods such as the model-based method and the artificial intelligent method have been applied to maximize the availability as well as to minimize the maintenance cost of the aircraft gas turbines. Among them the non-linear GPA(Gas Path Analysis) method and the GA(Genetic Algorithms) have lots of advantages to diagnose the engines compared to other advanced condition monitoring methods such as the linear GPA, fuzzy logic and neural networks. Therefore this work applies both the non-linear GPA and the GA to diagnose AE3007 turbofan engine for an aircraft, and in case of having sensor noise and bias it is confirmed that the GA is better than the GPA through the comparison of two methods.

• Journal of Genetic Medicine
• /
• v.4 no.1
• /
• pp.1-5
• /
• 2007

Unprecedented amount of genetic information being generated from the result of Human Genome Project (HGP) and advances in genetic research is already forcing changes in the paradigm of health and disease. The ultimate goal of genetic medicine is to use genetic information and technology to develop new ways of treatment or even prevention of the disease on an individual level for 'personalized medicine'. Genetics is play ing an increasingly important role in the diagnosis, monitoring and management of common multifactorial diseases in addition to rare single-gene disorders. While wide range of genetic testing have provided benefits to patients and family, uncertainties surrounding test interpretation, the current lack of available medical options for the diseases, and risks for discrimination and social stigmatization may remain to be resolved. However an increasing number of genetic tests are becoming commercially available, including direct to consumer genetic testing, yet public is often unaw are of their clinical and social implications. The personal nature of information generated by a genetic test, its power to affect major life decisions and family members, and its potential misuse raise important ethical considerations. Therefore appropriate genetic counseling is needed for patient to be informed with the benefits, limitations and risks of genetic tests, prior to informed consent for the tests. Physician also should be familiar with the legal and ethical issues involved in genetic testing to tell patients how w ell a particular genetic risk factor relates with likelihood of disease, and be able to provide appropriate genetic counseling. Genetic counseling become a mandatory requirement as global standard for many genetic testing such as prenatal diagnosis, presymtomatic DNA diagnostic tests and cancer susceptibility gene test for familial cancer syndrome. In oder to meet the challenge of genetic medicine of 21 century in korean health care system, professional education program and certification board for medical genetics specialist including non-MD genetic counselors should be addressed by medical society and regulatory policy of national health insurance reimbursement for genetic counseling to be in place to promote the implementation of clinical genetic service including genetic counseling for proper genetic testing.

• Journal of Marine Bioscience and Biotechnology
• /
• v.11 no.2
• /
• pp.52-61
• /
• 2019

Over the past few decades, microalgae-based biotechnology conjugated with innovative CRISPR/Cas9-mediated genetic engineering has been attracted much attention for the cost-effective and eco-friendly value-added compounds production. However, the discharge of reproducible living modified organism (LMO) into environmental condition potentially causes serious problem in aquatic environment, and thus it is essential to assess potential environmental risk for human health. Accordingly, in this study, we monitored discharged genetically modified microalgae (GMM) near the research complex which is located in Daejeon, South Korea. After testing samples obtained from 6 points of near streams, several green-colored microalgal colonies were detected under hygromicin-containing agar plate. By identification of selection marker genes, the GMM was not detected from all the samples. For the lab-scale environmental risk assessment of GMM, acute toxicity test using rotifer Brachionus calcyflorus was performed by feeding GMM. After feeding, there was no significant difference in mortality between WT and transformant Chlamydomonas reinhardtii. According to further analysis of horizontal transfer of green fluorescence protein (GFP)-coding gene after 24 h of incubation in synthetic freshwater, we concluded that the GFP-expressed gene not transferred into predator. However, further risk assessments and construction of standard methods including prolonged toxicity test are required for the accurate ecological risk assessment.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.55 no.5
• /
• pp.742-750
• /
• 2022

This study aimed to monitor the distribution of Cobitidae in Korea by the identification of species using genetic analysis. Based on the genetic analysis, Cobitidae species in four of five domestic fish farms consisted of only Chinese muddy loach Misgurnus mizolepis, but muddy loach Misgurnus anguillicaudatus was also present it in one fish farm. In the case of imported Cobitidae species, in addition to Chinese muddy loach and muddy loach, the harmful species Paramisgurnus dabryanus, was also present. Chinese muddy loach accounted for 20%, 67%, and 60% of the S6, S7, and S8 samples, respectively. An analysis of the total length, body length, and weight showed that domestic Chinese muddy loach showed higher values than imported muddy loach, and imported Chinese muddy loach showed similar values to P. dabryanus. There were no significant differences in the country of origin of the three species. Thus, the mitochondrial cytochrome c oxidase subunit I gene sequence was analyzed and compared the verification of species identification. The three species of Cobitidae were genetically divided into three groups and determined to have genetic differences. These results indicate that it is necessary to reduce the heterogeneous mixing rate through discriminating species by genetic analysis.

• Computers and Concrete
• /
• v.30 no.3
• /
• pp.225-236
• /
• 2022

In this article, Multi-Gene Genetic Programming (MGGP) is proposed for the estimation of the compressive strength of concrete. MGGP is known to be a powerful algorithm able to find a relationship between certain input space features and a desired output vector. With respect to most conventional machine learning algorithms, which are often used as "black boxes" that do not provide a mathematical formulation of the output-input relationship, MGGP is able to identify a closed-form formula for the input-output relationship. In the study presented in this article, MGPP was used to predict the compressive strength of plain concrete, concrete with fly ash, and concrete with furnace slag. A formula was extracted for each mixture and the performance and the accuracy of the predictions were compared to the results of Artificial Neural Network (ANN) and Extreme Learning Machine (ELM) algorithms, which are conventional and well-established machine learning techniques. The results of the study showed that MGGP can achieve a desirable performance, as the coefficients of determination for plain concrete, concrete with ash, and concrete with slag from the testing phase were equal to 0.928, 0.906, 0.890, respectively. In addition, it was found that MGGP outperforms ELM in all cases and its' accuracy is slightly less than ANN's accuracy. However, MGGP models are practical and easy-to-use since they extract closed-form formulas that may be implemented and used for the prediction of compressive strength.

• International Journal of Computer Science & Network Security
• /
• v.23 no.7
• /
• pp.131-140
• /
• 2023

Network security situational awareness systems helps in better managing the security concerns of a network, by monitoring for any anomalies in the network connections and recommending remedial actions upon detecting an attack. An Intrusion Detection System helps in identifying the security concerns of a network, by monitoring for any anomalies in the network connections. We have proposed a CRF based IDS system using genetic search feature selection algorithm for network security situational awareness to detect any anomalies in the network. The conditional random fields being discriminative models are capable of directly modeling the conditional probabilities rather than joint probabilities there by achieving better classification accuracy. The genetic search feature selection algorithm is capable of identifying the optimal subset among the features based on the best population of features associated with the target class. The proposed system, when trained and tested on the bench mark NSL-KDD dataset exhibited higher accuracy in identifying an attack and also classifying the attack category.

• Structural Engineering and Mechanics
• /
• v.87 no.3
• /
• pp.211-219
• /
• 2023

The structural health of a pipeline is usually assessed by visual inspection. In addition to the fact that this method is expensive and time consuming, inspection of the whole structure is not possible due to limited access to some points. Therefore, adopting a damage detection method without the mentioned limitations is important in order to increase the safety of the structure. In recent years, vibration-based methods have been used to detect damage. These methods detect structural defects based on the fact that the dynamic responses of the structure will change due to damage existence. Therefore, the location and extent of damage, before and after the damage, are determined. In this study, fuzzy genetic algorithm has been used to monitor the structural health of the pipeline to create a fuzzy automated system and all kinds of possible failure scenarios that can occur for the structure. For this purpose, the results of an experimental model have been used. Its numerical model is generated in ABAQUS software and the results of the analysis are used in the fuzzy genetic algorithm. Results show that the system is more accurate in detecting high-intensity damages, and the use of higher frequency modes helps to increase accuracy. Moreover, the system considers the damage in symmetric regions with the same degree of membership. To deal with the uncertainties, some error values are added, which are observed to be negligible up to 10% of the error.

• Smart Structures and Systems
• /
• v.10 no.4_5
• /
• pp.313-329
• /
• 2012

A challenging issue in design and implementation of an effective structural health monitoring (SHM) system is to determine where a number of sensors are properly installed. In this paper, research on the optimal sensor placement (OSP) is carried out on the Canton Tower (formerly named Guangzhou New Television Tower) of 610 m high. To avoid the intensive computationally-demanding problem caused by tens of thousands of degrees of freedom (DOFs) involved in the dynamic analysis, the three dimension finite element (FE) model of the Canton Tower is first simplified to a system with less DOFs. Considering that the sensors can be physically arranged only in the translational DOFs of the structure, but not in the rotational DOFs, a new method of taking the horizontal DOF as the master DOF and rotational DOF as the slave DOF, and reducing the slave DOF by model reduction is proposed. The reduced model is obtained by IIRS method and compared with the models reduced by Guyan, Kuhar, and IRS methods. Finally, the OSP of the Canton Tower is obtained by a kind of dual-structure coding based generalized genetic algorithm (GGA).

• Animal cells and systems
• /
• v.16 no.1
• /
• pp.41-49
• /
• 2012

Eighteen new polymorphic microsatellite markers were developed for the Korean mi-iuy croaker ($Miichthys$ $miiuy$, Perciformes, Sciaenidae), and allelic variability was compared between a wild population in Mokpo, Korea, and a hatchery population in Tongyeong, Korea. All loci were amplified readily and demonstrated allelic variability, with the number of alleles ranging from 5 to 37 in the wild population, and from 4 to 12 in the farmed population. The average observed and expected heterozygosities were estimated, respectively, to be 0.74 and 0.78 in the hatchery population samples, and 0.79 and 0.86 in the wild samples. These results indicate lower genetic variability in the hatchery population compared with the wild population, and significant genetic differentiation between the wild population and the hatchery samples ($F_{ST}$=0.058, P<0.001). These microsatellite loci may be valuable for future population genetic studies, monitoring changes in the genetic variation within stocks in a commercial breeding program, conservation genetics, and molecular assisted selective breeding of the mi-iuy croaker in the future.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1996.10a
• /
• pp.203-206
• /
• 1996

Prediction of firm bankruptcy have been extensively studied in accounting, as all stockholders in a firm have a vested interest in monitoring its financial performance. The objective of this paper is to develop the hybrid models for bankruptcy prediction. The proposed hybrid models are two phase. Phase one are (a) DA-assisted neural network, (b) Logit-assisted neural network, and (c) Genetic-assisted neural network. And, phase two are (a) DA-assisted Case based reasoning, and (b) Genetic-assisted Case based reasoning. In the variables selection, We are focusing on three alternative methods - linear discriminant analysis, logit analysis and genetic algorithms - that can be used empirically select predictors for hybrid model in bankruptcy prediction. Empirical results using Korean medium-sized firms data show that hybrid models are very promising neural network models and case based reasoning for bankruptcy prediction in terms of predictive accuracy and adaptability.