• Computers and Concrete
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• 제14권3호
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• pp.327-345
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• 2014

This paper presents the application of multi-gene genetic programming (MGP) technique for modeling the bond strength of ribbed steel bars in concrete. In this regard, the experimental data of 264 splice beam tests from different technical papers were used for training, validating and testing the model. Seven basic parameters affecting on the bond strength of steel bars were selected as input parameters. These parameters are diameter, relative rib area and yield strength of steel bar, minimum concrete cover to bar diameter ratio, splice length to bar diameter ratio, concrete compressive strength and transverse reinforcement index. The results show that the proposed MGP model can be alternative approach for predicting the bond strength of ribbed steel bars in concrete. Moreover, the performance of the developed model was compared with the building codes' empirical equations for a complete comparison. The study concludes that the proposed MGP model predicts the bond strength of ribbed steel bars better than the existing building codes' equations. Using the proposed MGP model and building codes' equations, a parametric study was also conducted to investigate the trend of the input variables on the bond strength of ribbed steel bars in concrete.

• Journal of Electrical Engineering and Technology
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• 제7권1호
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• pp.109-114
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• 2012

In this paper, we utilize training strategy of hidden Markov model (HMM) to use in versatile issues such as classification of time-series sequential data such as electric transient disturbance problem in power system. For this, an automatic means of optimizing HMMs would be highly desirable, but it raises important issues: model interpretation and complexity control. With this in mind, we explore the possibility of using genetic algorithm (GA) and harmony search (HS) algorithm for optimizing the HMM. GA is flexible to allow incorporating other methods, such as Baum-Welch, within their cycle. Furthermore, operators that alter the structure of HMMs can be designed to simple structures. HS algorithm with parameter-setting free technique is proper for optimizing the parameters of HMM. HS algorithm is flexible so as to allow the elimination of requiring tedious parameter assigning efforts. In this paper, a sequential data analysis simulation is illustrated, and the optimized-HMMs are evaluated. The optimized HMM was capable of classifying a sequential data set for testing compared with the normal HMM.

• Journal of Interdisciplinary Genomics
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• 제3권2호
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• pp.41-46
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• 2021

Inherited platelet function disorders (IPFDs) are a disease group of heterogeneous bleeding disorders associated with congenital defects of platelet functions. Normal platelets essential role for primary hemostasis by adhesion, activation, secretion of granules, aggregation, and procoagulant activity of platelets. The accurate diagnosis of IPFDs is challenging due to unavailability of important testing methods, including light transmission aggregometry and flow cytometry, in several medical centers in Korea. Among several IPFDs, Glanzmann thrombasthenia (GT) is a most representative IPFD and is relatively frequently found compare to the other types of rarer IPFDs. GT is an autosomal recessive disorder caused by mutations of ITGA2B or ITGB3. There are quantitative or qualitative defects of the GPIIb/IIIa complex in platelet, which is the binding receptor for fibrinogen, von Willbrand factor, and fibronectin in GT patients. Therefore, patients with GT have normal platelet count and normal platelet morphology, but they have severely decreased platelet aggregation. Thus, GT patients have a very severe hemorrhagic phenotypes that begins at a very early age and persists throughout life. In this article, the general contents about platelet functions and respective IPFDs, the overall contents of GT, and the current status of genetic diagnosis of GT in Korea will be reviewed.

• Computers and Concrete
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• 제30권3호
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• pp.225-236
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• 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.

• Childhood Kidney Diseases
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• 제27권2호
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• pp.70-75
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• 2023

Dent disease is a rare inherited kidney tubulopathy caused by mutations in either the CLCN5 (Dent disease 1) or OCRL1 (Dent disease 2) genes, and which is often underdiagnosed in practice. A diagnosis is clinically suspected in patients with low-molecular-weight proteinuria, hypercalciuria, and one of the following: hematuria, nephrolithiasis, nephrocalcinosis, hypophosphatemia, or chronic kidney disease. Inheritance is X-linked recessive, meaning, these symptoms are generally only found in males; female carriers may have mild phenotypes. Genetic testing is only a method to confirm the diagnosis, approximately 25% to 35% of patients have neither the CLCN5 nor OCRL1 pathogenic variants (Dent disease 3), making diagnosis more challenging. The genotype-phenotype correlations are not evident with the limited clinical data available. As with many other genetic diseases, the management of patients with Dent disease concentrates on symptom relief rather than any causative process. The current treatments are mainly supportive to reduce hypercalciuria and prevent nephrolithiasis. Chronic kidney disease progresses to end-stage between the ages of the third to fifth decades in 30% to 80% of affected males. In this review, we aimed to summarize the literature on Dent disease and reveal the clinical characteristics and molecular basis of Korean patients with Dent disease.

• Journal of Genetic Medicine
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• 제16권2호
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• pp.76-80
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• 2019

About 15% to 20% of all clinically recognized pregnancies result in spontaneous abortion or miscarriage, and chromosomal anomalies can be identified in up to 50% of first trimester miscarriages. Chromosomal microarray analysis (CMA) is currently considered first-tier testing for detecting fetal chromosomal abnormalities and is supported by the absence of cell culture failure or erroneous results due to cell contamination in pregnancy loss. Triploidy is a lethal chromosome number abnormality characterized by an extra haploid set of chromosomes. Triploidy is one of the most common chromosomal aberrations in first trimester spontaneous abortions. Here, we report two cases of triploidy abortion that were not detected using array comparative genomic hybridization-based CMA. The aim of this report was to remind clinicians of the limitations of chromosomal testing and the misdiagnosis that can result from biased test selection.

• Journal of Computing Science and Engineering
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• 제2권3호
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• pp.274-300
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• 2008

Software testing cost can be reduced if the process of testing is automated. However, the test data generation task is still performed mostly by hand although numerous theoretical works have been proposed to automate the process of generating test data and even commercial test data generators appeared on the market. Despite prolific research reports, few attempts have been made to evaluate and characterize those techniques. Therefore, a lot of works have been proposed to automate the process of generating test data. However, there is no overall evaluation and comparison of these techniques. Evaluation and comparison of existing techniques are useful for choosing appropriate approaches for particular applications, and also provide insights into the strengths and weaknesses of current methods. This paper conducts experiments on four representative test data generation techniques and discusses the experimental results. The results of the experiments show that the genetic algorithm (GA)-based test data generation performs the best. However, there are still some weaknesses in the GA-based method. Therefore, we modify the standard GA-based method to cope with these weaknesses. The experiments are carried out to compare the standard GA-based method and two modified versions of the GA-based method.

• Asian-Australasian Journal of Animal Sciences
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• 제30권8호
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• pp.1074-1080
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• 2017

Objective: The growth, carcass and retail cut yield records on 1,428 Hanwoo steers obtained through progeny testing were analyzed in this study, and their heritability and genetic relationships among the traits were estimated using animal models. Methods: Two different models were compared in this study. Each model was fitted for different fixed class effects, date of slaughter for carcass traits and batch of progeny test live measurement traits, and a choice of covariates (carcass weight in Model 1 or backfat thickness in Model 2) for carcass traits. Results: The differences in body composition among individuals were deemed being unaffected by their age at slaughter, except for carcass weight and backfat thickness. Heritability estimates of body size measurements were 0.21 to 0.36. Heritability estimates of retail cut percentage were high (0.56 from Model 1 and 0.47 from Model 2). And the heritability estimates for loin muscle percentage were 0.36 from Model 1 and 0.42 from Model 2, which were high enough to consider direct selection on carcass cutability traits as effective. The genetic correlations between body size measurements and retail cut ratio (RCR) were close to zero. But, some negative genetic correlations were found with chest girths measured at yearling (Model 1) or at 24 months of age or with chest widths. Loin muscle ratio (LMR) was genetically negatively correlated with body weights or body size measurements, in general in Model 1. These relationships were low close to zero but positive in Model 2. Phenotypic correlation between cutability traits (RCR, LMR) and live body size measurements were moderate and negative in Model 1 while those in Model 2 were all close to zero. Conclusion: Therefore, the body weights or linear body measurements at an earlier age may not be the most desirable selection traits for exploitation of correlated responses to improve loin muscle or lean meat yield.

• Asian-Australasian Journal of Animal Sciences
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• 제18권9호
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• pp.1209-1216
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• 2005

This study aimed to use field data collected by the Hokkaido Dairy Cattle Milk Recording and Testing programs to estimate genetic parameters for concentration of milk urea nitrogen (MUN) and predicted Digestive Crude Protein Percentage of requirement (DCPun). Edited data consisted of 5,797,500 test-day records of MUN and yields of milk, fat, and protein obtained from 783,271cows in Holstein herds in Hokkaido, Japan. Data were divided into four datasets; for the first, second, third and fourth lactations. Two analyses were performed on data from each lactation. First, ANOVA was used to estimate the significance of the effects of several environmental factors on MUN and DCPun, after absorbing the Herd-Test-Day (HTD) effects. The effects of DIM and age.season effects had significant impact on MUN and DCPun. The second used a multi-traits repeatability model (MTRM) to estimate heritabilities and genetic correlations of milk with MUN and DCPun. Heritability estimates for MUN and DCPun in the first, second, and third lactations were 0.21:0.16, 0.20:0.16, and 0.20:0.18, respectively. Genetic correlations for milk with MUN and DCPun in the first, second, and third lactations were 0.02 - 0.17, and -0.25 - -0.39, respectively. The results indicate that MUN and DCPun are possibly effective tools for improving the energy balance, but that the relationships between MUN and other economically important traits such as feed efficiency, metabolic disease and fertility are still necessary.

• Asian-Australasian Journal of Animal Sciences
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• 제19권6호
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• pp.784-788
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• 2006

Microsatellite polymorphism and the genetic relationship were estimated using genotype information of 305 horses from 11 microsatellite loci. The breeds include the indigenous Korean breeds, Korean native horse (102) and Jeju racing horse (56) together with Japan Hokkaido horse (5), Mongolian horse (19), Thoroughbred horse (108), Quarter horse (11) and Przewalskii horse (4). Allelic frequencies, the number of alleles per locus were estimated by direct counting from observed genotype, and genetic variability was computed using the CERVUX software and DISPAN. The number of alleles per locus varied from 6 (HMS6) to 18 (ASB17) with an average value of 10.45 in horse breeds. The expected total heterozygosity ($H_T$) and coefficient of gene differentiation ($G_{ST}$) ranged 0.764-0.921 (the average value was 0.830) and 0.102-0.266 (the average value was 0.180) in horse breeds, respectively. Four populations (Przewalskii horse, Japan Hokkaido horse, Quarter horse, Thoroughbred horse) showed lower heterozygosity than the average value (the average value was 0.710). The expected heterozygosity within breed ($H_S$) and mean no. of observed alleles ranged from $0.636{\pm}0.064$ (Japan Hokkaido horse) to $0.809{\pm}0.019$ (Mongolian horse), and from 2.73 (Przewalskii horse) to 8.27 (Korean native horse), respectively. The polymorphic information content (PIC) ranged from 0.490 (Przewalskii horse) to 0.761 (Mongolian horse) with an average value of 0.637 in horse breeds. The results showed three distinct clusters with high bootstrap support: the Korean native horse cluster (Korean native horse, Mongolian horse), the European cluster (Przewalskii horse, Thoroughbred horse), and other horse cluster (Jeju racing horse, Japan Hokkaido horse, and Quarter horse). A relatively high bootstrap value was observed for the Korean native horse cluster and European cluster (87%), and the Korean native horse and Mongolian horse (82%). Microsatellite polymorphism data were shown to be useful for estimating the genetic relationship between Korean native horse and other horse breeds, and also be applied for parentage testing in those horse breeds.