Search results for: genetic variations

Authors: Abdoulie K. Ceesay

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Within the sequence of the whole genome, it is known that 99.9% of the human genome is similar, whilst our difference lies in just 0.1%. Among these minor dissimilarities, the most common type of genetic variations that occurs in a population is SNP, which arises due to nucleotide substitution in a protein sequence that leads to protein destabilization, alteration in dynamics, and other physio-chemical properties’ distortions. While causing variations, they are equally responsible for our difference in the way we respond to a treatment or a disease, including various cancer types. There are two types of SNPs; synonymous single nucleotide polymorphism (sSNP) and non-synonymous single nucleotide polymorphism (nsSNP). sSNP occur in the gene coding region without causing a change in the encoded amino acid, while nsSNP is deleterious due to its replacement of a nucleotide residue in the gene sequence that results in a change in the encoded amino acid. Predicting the effects of cancer related nsSNPs on protein stability, function, and dynamics is important due to the significance of phenotype-genotype association of cancer. In this thesis, Data of 5 oncogenes (ONGs) (AKT1, ALK, ERBB2, KRAS, BRAF) and 5 tumor suppressor genes (TSGs) (ESR1, CASP8, TET2, PALB2, PTEN) were retrieved from ClinVar. Five common in silico tools; Polyphen, Provean, Mutation Assessor, Suspect, and FATHMM, were used to predict and categorize nsSNPs as deleterious, benign, or neutral. To understand the impact of each variation on the phenotype, Maestro, PremPS, Cupsat, and mCSM-NA in silico structural prediction tools were used. This study comprises of in-depth analysis of 10 cancer gene variants downloaded from Clinvar. Various analysis of the genes was conducted to derive a meaningful conclusion from the data. Research done indicated that pathogenic variants are more common among ONGs. Our research also shows that pathogenic and destabilizing variants are more common among ONGs than TSGs. Moreover, our data indicated that ALK(409) and BRAF(86) has higher benign count among ONGs; whilst among TSGs, PALB2(1308) and PTEN(318) genes have higher benign counts. Looking at the individual cancer genes predisposition or frequencies of causing cancer according to our research data, KRAS(76%), BRAF(55%), and ERBB2(36%) among ONGs; and PTEN(29%) and ESR1(17%) among TSGs have higher tendencies of causing cancer. Obtained results can shed light to the future research in order to pave new frontiers in cancer therapies.

Keywords: tumor suppressor genes (TSGs), oncogenes (ONGs), non synonymous single nucleotide polymorphism (nsSNP), single nucleotide polymorphism (SNP)

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Authors: Ahmed Tarek, Ahmed Alveed

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In the theory of computing, there are a wide variety of direct and indirect proof techniques. However, mathematical induction (MI) stands out to be one of the most powerful proof techniques for proving hypotheses, theorems, and new results. There are variations of mathematical induction-based proof techniques, which are broadly classified into three categories, such as structural induction (SI), weak induction (WI), and strong induction (SI). In this expository paper, several different variants of the mathematical induction techniques are explored, and the specific scenarios are discussed where a specific induction technique stands out to be more advantageous as compared to other induction strategies. Also, the essential difference among the variants of mathematical induction are explored. The points of separation among mathematical induction, recursion, and logical deduction are precisely analyzed, and the relationship among variations of recurrence relations, and mathematical induction are being explored. In this context, the application of recurrence relations, and mathematical inductions are considered together in a single framework for codewords over a given alphabet.

Keywords: alphabet, codeword, deduction, mathematical, induction, recurrence relation, strong induction, structural induction, weak induction

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Authors: Rachana Tank, Donald. M. Lyall, Kristin Flegal, Joey Ward, Jonathan Cavanagh

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Alzheimer’s research UK estimates by 2050, 2 million individuals will be living with Late Onset Alzheimer’s disease (LOAD). However, individuals experience considerable cognitive deficits and brain pathology over decades before reaching clinically diagnosable LOAD and studies have utilised gene candidate studies such as genome wide association studies (GWAS) and polygenic risk (PGR) scores to identify high risk individuals and potential pathways. This investigation aims to determine whether high genetic risk of LOAD is associated with worse brain MRI and cognitive performance in healthy older adults within the UK Biobank cohort. Previous studies investigating associations of PGR for LOAD and measures of MRI or cognitive functioning have focused on specific aspects of hippocampal structure, in relatively small sample sizes and with poor ‘controlling’ for confounders such as smoking. Both the sample size of this study and the discovery GWAS sample are bigger than previous studies to our knowledge. Genetic interaction between loci showing largest effects in GWAS have not been extensively studied and it is known that APOE e4 poses the largest genetic risk of LOAD with potential gene-gene and gene-environment interactions of e4, for this reason we  also analyse genetic interactions of PGR with the APOE e4 genotype. High genetic loading based on a polygenic risk score of 21 SNPs for LOAD is associated with worse brain MRI and cognitive outcomes in healthy individuals within the UK Biobank cohort. Summary statistics from Kunkle et al., GWAS meta-analyses (case: n=30,344, control: n=52,427) will be used to create polygenic risk scores based on 21 SNPs and analyses will be carried out in N=37,000 participants in the UK Biobank. This will be the largest study to date investigating PGR of LOAD in relation to MRI. MRI outcome measures include WM tracts, structural volumes. Cognitive function measures include reaction time, pairs matching, trail making, digit symbol substitution and prospective memory. Interaction of the APOE e4 alleles and PGR will be analysed by including APOE status as an interaction term coded as either 0, 1 or 2 e4 alleles. Models will be adjusted partially for adjusted for age, BMI, sex, genotyping chip, smoking, depression and social deprivation. Preliminary results suggest PGR score for LOAD is associated with decreased hippocampal volumes including hippocampal body (standardised beta = -0.04, P = 0.022) and tail (standardised beta = -0.037, P = 0.030), but not with hippocampal head. There were also associations of genetic risk with decreased cognitive performance including fluid intelligence (standardised beta = -0.08, P<0.01) and reaction time (standardised beta = 2.04, P<0.01). No genetic interactions were found between APOE e4 dose and PGR score for MRI or cognitive measures. The generalisability of these results is limited by selection bias within the UK Biobank as participants are less likely to be obese, smoke, be socioeconomically deprived and have fewer self-reported health conditions when compared to the general population. Lack of a unified approach or standardised method for calculating genetic risk scores may also be a limitation of these analyses. Further discussion and results are pending.

Keywords: Alzheimer's dementia, cognition, polygenic risk, MRI

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Authors: Walid Moudani, Ahmad Shahin

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This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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Authors: Inigo de Miguel Beriain

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Genetic data of deceased persons are of great interest for both biomedical research and clinical use. This is due to several reasons. On the one hand, many of our diseases have a genetic component; on the other hand, we share genes with a good part of our biological family. Therefore, it would be possible to improve our response considerably to these pathologies if we could use these data. Unfortunately, at the present moment, the status of data on the deceased is far from being satisfactorily resolved by the EU data protection regulation. Indeed, the General Data Protection Regulation has explicitly excluded these data from the category of personal data. This decision has given rise to a fragmented legal framework on this issue. Consequently, each EU member state offers very different solutions. For instance, Denmark considers the data as personal data of the deceased person for a set period of time while some others, such as Spain, do not consider this data as such, but have introduced some specifically focused regulations on this type of data and their access by relatives. This is an extremely dysfunctional scenario from multiple angles, not least of which is scientific cooperation at the EU level. This contribution attempts to outline a solution to this dilemma through an alternative proposal. Its main hypothesis is that, in reality, health data are, in a sense, a rara avis within data in general because they do not refer to one person but to several. Hence, it is possible to think that all of them can be considered data subjects (although not all of them can exercise the corresponding rights in the same way). When the person from whom the data were obtained dies, the data remain as personal data of his or her biological relatives. Hence, the general regime provided for in the GDPR may apply to them. As these are personal data, we could go back to thinking in terms of a general prohibition of data processing, with the exceptions provided for in Article 9.2 and on the legal bases included in Article 6. This may be complicated in practice, given that, since we are dealing with data that refer to several data subjects, it may be complex to refer to some of these bases, such as consent. Furthermore, there are theoretical arguments that may oppose this hypothesis. In this contribution, it is shown, however, that none of these objections is of sufficient substance to delegitimize the argument exposed. Therefore, the conclusion of this contribution is that we can indeed build a general framework on the processing of personal data of deceased persons in the context of the GDPR. This would constitute a considerable improvement over the current regulatory framework, although it is true that some clarifications will be necessary for its practical application.

Keywords: collective data conceptual issues, data from deceased people, genetic data protection issues, GDPR and deceased people

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Authors: Asma'u Mahe, Abdullahi A. Imam, Adamu J. Alhassan, Nasiru Abdullahi, Sadiya A. Bichi, Nura Lawal, Kamaluddeen Babagana

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Malaria is a disease with global health significance. It is caused by parasites and transmitted by Anopheles mosquitoes. Increase in insecticide resistance threatens the disease vector control. The strength of selection pressure acting on a mosquito population in relation to insecticide resistance can be assess by determining the genetic diversity of a fragment spanning exon- 20 of IIS6 of the voltage gated sodium channel (VGSC). Larval samples reared to adulthood were identified and kdr (knock down resistance) profile was determined. The DNA sequences were used to assess the patterns of genetic differentiation by determining the levels of genetic variability between the Anopheles mosquitoes. Genetic differentiation of the Anopheles mosquitoes based on a portion of the voltage gated sodium channel gene was obtained. Polymorphisms were detected; sequence variation and analysis were presented as a phylogenetic tree. Phylogenetic tree of VGSC haplotypes was constructed for samples of the Anopheles mosquitoes using the maximum likelihood method in MEGA 6.0 software. DNA sequences were edited using BioEdit sequence editor. The edited sequences were aligned with reference sequence (Kisumu strain). Analyses were performed as contained in dnaSP 5.10. Results of genetic parameters of polymorphism and haplotype reconstruction were presented in count. Twenty sequences were used for the analysis. Regions selected were 1- 576, invariable (monomorphic) sites were 460 while variable (polymorphic) sites were 5 giving the number of total mutations observed in this study. Mutations obtained from the study were at codon 105: TTC- Phenylalanine replaces TCC- Serine, codon 513: TAG- Termination replaces TTG- Leucine, codon 153, 300 and 553 mutations were non-synonymous. From the constructed phylogenetic tree, some groups were shown to be closer with Exon20Gambiae Kisumu (Reference strain) having some genetic distance, while 5-Exon20Gambiae-F I13.ab1, 18-Exon20Gambiae-F C17.ab1, and 2-Exon20Gambiae-F C13.ab1 clustered together genetically differentiated away from others. Mutations observed in this study can be attributed to the high insecticide resistance profile recorded in the study areas. Haplotype networks of pattern of genetic variability and polymorphism for the fragment of the VGSC sequences of sampled Anopheles mosquitoes revealed low haplotypes for the present study. Haplotypes are set of closely linked DNA variation on X-chromosome. Haplotypes were scaled accordingly to reflect their respective frequencies. Low haplotype number, four VGSC-1014F haplotypes were observed in this study. A positive association was previously established between low haplotype number of VGSC diversity and pyrethroid resistance through kdr mechanism. Significant values at (P < 0.05) of Tajima D and Fu and Li D’ were observed for some of the results indicating possible signature of positive selection on the fragment of VGSC in the study. This is the first report of VGSC-1014F in the study site. Based on the results, the mutation was present in low frequencies. However, the roles played by the observed mutations need further investigation. Mutations, environmental factors among others can affect genetic diversity. The study area has recorded increase in insecticide resistance that can affect vector control in the area. This finding might affect the efforts made against malaria. Sequences were deposited in GenBank for Accession Number.

Keywords: anopheles mosquitoes, insecticide resistance, kdr, malaria, voltage gated sodium channel

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Authors: Arslan Ellahi, Syed Amjad Hussain

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Software Testing is a vital process in software development life cycle. We can attain the quality of software after passing it through software testing phase. We have tried to find out automatic test data generation techniques that are a key research area of software testing to achieve test automation that can eventually decrease testing time. In this paper, we review some of the approaches presented in the literature which use evolutionary search based algorithms like Genetic Algorithm, Particle Swarm Optimization (PSO), etc. to validate the test data generation process. We also look into the quality of test data generation which increases or decreases the efficiency of testing. We have proposed test data generation techniques for model-based testing. We have worked on tuning and fitness function of PSO algorithm.

Keywords: search based, evolutionary algorithm, particle swarm optimization, genetic algorithm, test data generation

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Authors: Revalin Herdianto

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Recent climate changes increase uncertainties in vegetation conditions such as health and biomass globally and locally. The detection is, however, difficult due to the spatial and temporal scale of vegetation coverage. Due to unique vegetation response to its environmental conditions such as water availability, the interplay between vegetation dynamics and hydrologic conditions leave a signature in their feedback relationship. Vegetation indices (VI) depict vegetation biomass and photosynthetic capacity that indicate vegetation dynamics as a response to variables including hydrologic conditions and microclimate factors such as rainfall characteristics and land surface temperature (LST). It is hypothesized that the signature may be depicted by VI in its relationship with other variables. To study this signature, several catchments in Asia, Australia, and Indonesia were analysed to assess the variations in hydrologic characteristics with vegetation types. Methods used in this study includes geographic identification and pixel marking for studied catchments, analysing time series of VI and LST of the marked pixels, smoothing technique using Savitzky-Golay filter, which is effective for large area and extensive data. Time series of VI, LST, and rainfall from satellite and ground stations coupled with digital elevation models were analysed and presented. This study found that the hydrologic response of vegetation to rainfall variations may be shown in one hydrologic year, in which a drought event can be detected a year later as a suppressed growth. However, an annual rainfall of above average do not promote growth above average as shown by VI. This technique is found to be a robust and tractable approach for assessing catchment dynamics in changing climates.

Keywords: vegetation indices, land surface temperature, vegetation dynamics, catchment

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Authors: M. M. A. Abdalla, M. H. Aboul-Nasr, Shimaa H. Mosallam

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Ten RAPD markers were used to detect the genetic variability and relationships among four broccoli and three cabbage genotypes. The results of RAPD analysis showed that all the five primers surveyed detected polymorphism for all broccoli genotypes. A total of 39 DNA bands were amplified by the 5 primers from all genotype and 21 of these fragments showed polymorphism (53.85%). The rest of these bands (46.15%) were common between the four genotypes. On the other hand, all of the 7 primers surveyed, used with cabbage, detected polymorphism among all cabbage genotype. A total of 69 DNA bands were amplified by the 7 primers from all genotypes and 23 of these fragments showed polymorphism (33.33%). The rest of these bands (66.67%) were common between the three genotypes. The investigation suggested that the RAPD approach showed considerable potential for identifying and discriminating broccoli and cabbage genotypes.

Keywords: Brassica oleracea, genotypes, genetic markers, varietal identification, DNA polymorphism, RAPD markers

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Authors: Zeinab Haji Abolhasani, Romeo Marian, Lee Luong

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This paper and its companions (Part II, Part III) will concentrate on optimizing a class of supply chain problems known as Multi- Commodities Consumer Supply Chain (MCCSC) problem. MCCSC problem belongs to production-distribution (P-D) planning category. It aims to determine facilities location, consumers’ allocation, and facilities configuration to minimize total cost (CT) of the entire network. These facilities can be manufacturer units (MUs), distribution centres (DCs), and retailers/end-users (REs) but not limited to them. To address this problem, three major tasks should be undertaken. At the first place, a mixed integer non-linear programming (MINP) mathematical model is developed. Then, system’s behaviors under different conditions will be observed using a simulation modeling tool. Finally, the most optimum solution (minimum CT) of the system will be obtained using a multi-objective optimization technique. Due to the large size of the problem, and the uncertainties in finding the most optimum solution, integration of modeling and simulation methodologies is proposed followed by developing new approach known as GASG. It is a genetic algorithm on the basis of granular simulation which is the subject of the methodology of this research. In part II, MCCSC is simulated using discrete-event simulation (DES) device within an integrated environment of SimEvents and Simulink of MATLAB® software package followed by a comprehensive case study to examine the given strategy. Also, the effect of genetic operators on the obtained optimal/near optimal solution by the simulation model will be discussed in part III.

Keywords: supply chain, genetic algorithm, optimization, simulation, discrete event system

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Authors: Manvender Singh

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Temperature is one of the most important climatic parameter for explaining the geographic distribution of ectothermic species. Empirical investigations on norms of the reaction according to developmental temperatures are helpful in analyzing the adapture capacity of a species which may be related to its ecological niche. In the present investigation, we have compared the effects of developmental temperatures on fecundity, hatchability, viability, and duration of development in five natural populations of Drosophila bipectinata along the latitudinal range. The clinal patterns for fecundity, as well as ovariole number, were observed which showed significant positive correlation (r=0.97). Similarly, hatchability and duration of development also revealed a positive correlation with latitude. Hence, suggesting the role of natural selection in maintaining the genetic divergence for life history traits along the north-south transect of the Indian Subcontinent.

Keywords: growth temperature, fecundity, hatchability, viability, duration of development, Drosophila

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Authors: Rofida Gamal, Mostafa Mohammed, Mariam Adel, Marwa Gamal, Marwa kamal, Ayat Saber, Maha Mamdouh, Amira Emad, Mai Ramadan

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Lynch Syndrome is an inherited genetic condition associated with an increased risk of colorectal and other cancers. Detecting Lynch Syndrome in individuals is crucial for early intervention and preventive measures. This study proposes a computational pipeline for Lynch Syndrome detection by integrating alignment, variant calling, and annotation. The pipeline leverages popular tools such as FastQC, Trimmomatic, BWA, bcftools, and ANNOVAR to process the input FASTQ file, perform quality trimming, align reads to the reference genome, call variants, and annotate them. It is believed that the computational pipeline was applied to a dataset of Lynch Syndrome cases, and its performance was evaluated. It is believed that the quality check step ensured the integrity of the sequencing data, while the trimming process is thought to have removed low-quality bases and adaptors. In the alignment step, it is believed that the reads were accurately mapped to the reference genome, and the subsequent variant calling step is believed to have identified potential genetic variants. The annotation step is believed to have provided functional insights into the detected variants, including their effects on known Lynch Syndrome-associated genes. The results obtained from the pipeline revealed Lynch Syndrome-related positions in the genome, providing valuable information for further investigation and clinical decision-making. The pipeline's effectiveness was demonstrated through its ability to streamline the analysis workflow and identify potential genetic markers associated with Lynch Syndrome. It is believed that the computational pipeline presents a comprehensive and efficient approach to Lynch Syndrome detection, contributing to early diagnosis and intervention. The modularity and flexibility of the pipeline are believed to enable customization and adaptation to various datasets and research settings. Further optimization and validation are believed to be necessary to enhance performance and applicability across diverse populations.

Keywords: Lynch Syndrome, computational pipeline, alignment, variant calling, annotation, genetic markers

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Authors: Rasime Kalkan, Emine Ikbal Atli, Ali Arslantaş, Muhsin Özdemir, Sevilhan Artan

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Glioblastoma (WHO grade IV), is the malignant form of brain tumor, the genetic background of the GBM is highly variable. The tumor mass of a GBM is multilayered and every tumor layer shows distinct characteristics with a different cell population. The treatment planning of GBM should be focused on the tumor genetic characteristics. We screened primary glioblastoma multiforme (GBM) in a population-based study for MGMT and RARβ methylation and IDH1 mutation correlated them with clinical data and treatment. There was no correlation between MGMT-promoter methylation and overall survival. The overall survival time of the patients with methylated RARβ was statically (OS;p<0,05) significance between the patients who were treated with chemotherapy and radiotherapy. Here we showed the status of IDH1 gene associatied with younger age. We demonstrated that the together with MGMT gene the RARβ gene should be used as a potantial treatment decision marker for GBMs.

Keywords: RARβ, primary glioblastoma multiforme, methylation, MGMT

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Authors: Rajendra K. Meena, Maneesh S. Bhandari, Santan Barthwal, Harish S. Ginwal

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Microsatellite markers are the most valuable tools for the characterization of plant genetic resources or population genetic analysis. Since it is codominant and allelic markers, utilizing them in polyploid species remained doubtful. In such cases, the microsatellite marker is usually analyzed by treating them as a dominant marker. In the current study, it has been showed that despite losing the advantage of co-dominance, microsatellite markers are still a powerful tool for genotyping of polyploid species because of availability of large number of reproducible alleles per locus. It has been studied by genotyping of 19 subpopulations of Dendrocalamus hamiltonii (hexaploid bamboo species) with 17 polymorphic simple sequence repeat (SSR) primer pairs. Among these, ten primers gave typical banding pattern of microsatellite marker as expected in diploid species, but rest 7 gave an unusual pattern, i.e., more than two bands per locus per genotype. In such case, genotyping data are generally analyzed by considering as dominant markers. In the current study, data were analyzed in both ways as dominant and co-dominant. All the 17 primers were first scored as nonallelic data and analyzed; later, the ten primers giving standard banding patterns were analyzed as allelic data and the results were compared. The UPGMA clustering and genetic structure showed that results obtained with both the data sets are very similar with slight variation, and therefore the SSR marker could be utilized to characterize polyploid species by considering them as a dominant marker. The study is highly useful to widen the scope for SSR markers applications and beneficial to the researchers dealing with polyploid species.

Keywords: microsatellite markers, Dendrocalamus hamiltonii, dominant and codominant, polyploids

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Authors: Awais Ahmed, Atif Rana, Haseeb Zia, Maham Jahangir, Rashed Nazir, Faisal Dar

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Purpose: Biliary complications represent the most common cause of morbidity in living related liver donor transplantation and detailed preoperative evaluation of biliary anatomic variants is crucial for safe patient selection and improved surgical outcomes. Purpose of this study is to determine the accuracy of preoperative MRCP in predicting biliary variations when compared to intraoperative cholangiography in living related liver donors. Materials and Methods: From 44 potential donors, 40 consecutive living related liver donors (13 females and 28 males) underwent donor hepatectomy at our centre from April 2012 to August 2013. MRCP and IOC of all patients were retrospectively reviewed separately by two radiologists and a transplant surgeon.MRCP was performed on 1.5 Tesla MR magnets using breath-hold heavily T2 weighted radial slab technique. One patient was excluded due to suboptimal MRCP. The accuracy of MRCP for variant biliary anatomy was calculated. Results: MRCP accurately predicted the biliary anatomy in 38 of 39 cases (97 %). Standard biliary anatomy was predicted by MRCP in 25 (64 %) donors (100% sensitivity). Variant biliary anatomy was noted in 14 (36 %) IOCs of which MRCP predicted precise anatomy of 13 variants (93 % sensitivity). The two most common variations were drainage of the RPSD into the LHD (50%) and the triple confluence of the RASD, RPSD and LHD (21%). Conclusion: MRCP is a sensitive imaging tool for precise pre-operative mapping of biliary variations which is critical to surgical decision making in living related liver transplantation.

Keywords: intraoperative cholangiogram, liver transplantation, living related donors, magnetic resonance cholangio-pancreaticogram (MRCP)

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Authors: Ezio Bassi, Francesco Vercesi, Francesco Benzi

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The aim of this study is to evaluate the potentiality of synchronous reluctance motors for lift systems by also evaluating the vibroacoustic behaviour of the motor. Two types of synchronous machines are designed, analysed, and compared with an equivalent induction motor, which is the more common solution in such gearbox applications. The machines' performance are further improved with optimization procedures based on multiobjective optimization genetic algorithm (MOGA). The difference between the two synchronous motors consists in the rotor geometry; a symmetric and an asymmetric rotor design were investigated. The evaluation of the vibroacoustic performance has been conducted with a multi-variable model and finite element software taking into account electromagnetic, mechanical, and thermal features of the motor, therefore carrying out a multi-physics analysis of the electrical machine.

Keywords: synchronous reluctance motor, vibro-acoustic, lift systems, genetic algorithm

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Authors: Omaima N. Ahmad AL-Allaf

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Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform

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Authors: Ousmane Youme, Jean Marie Dembele, Eugene Ezin, Christophe Cambier

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In recent years, the convolutional neural networks (CNN) architectures designed by evolution algorithms have proven to be competitive with handcrafted architectures designed by experts. However, these algorithms need a lot of computational power, which is beyond the capabilities of most researchers and engineers. To overcome this problem, we propose an evolution architecture under length constraints. It consists of two algorithms: a search length strategy to find an optimal space and a search architecture strategy based on a genetic algorithm to find the best individual in the optimal space. Our algorithms drastically reduce resource costs and also keep good performance. On the Cifar-10 dataset, our framework presents outstanding performance with an error rate of 5.12% and only 4.6 GPU a day to converge to the optimal individual -22 GPU a day less than the lowest cost automatic evolutionary algorithm in the peer competition.

Keywords: CNN architecture, genetic algorithm, evolution algorithm, length constraints

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Authors: Vivek Vaishnav, Shamim Akhtar Ansari

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Teak (Tectona grandis L.f.) belonging to plant family Lamiaceae and the most commercialized timber species is endemic to South-Asia. The adaptive fitness of the species metapopulation was evaluated through its genetic differentiation and assessing the influence of geo-climatic conditions. 290 genotypes were sampled from 29 locations of its natural distribution and the genetic data was incorporated with geo-climatic parameters. Through Bayesian approach based analysis of 43 highly polymorphic ISSR markers, six homogeneous clusters (0.8% genetic variability) were identified. The six clusters were found with the various regimes of the temperature range, i.e., I - 9.10±1.35⁰C, II -6.35±0.21⁰C, III -12.21±0.43⁰C, IV - 10.8±1.06⁰C, V - 11.67±3.04⁰C, and VI - 12.35±0.21⁰C. The population had a very high percentage of LD (21.48%) among the amplified loci possibly due to experiencing restricted gene flow as well as co-adaptation and association of distant/diverse loci/alleles as a result of the stabilized climatic conditions and countless cycles of historical recombination events on a large geological timescale. The same possibly accounts for the narrow distribution of teak as a climax species in the tropical deciduous forests of the country. The regions of strong LD in teak genome significantly associated with climatic parameters also reflect that the species is tolerant to the wide regimes of the temperature range and may possibly withstand global warming and climate change in the coming millennium.

Keywords: Bayesian analysis, inter simple sequence repeat, linkage disequilibrium, marker-geoclimatic association

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Authors: Arash Rahmani, Ahmad Ghanbari, Abbas Baghernezhad, Babak Safaei

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In the design of parallel manipulators, usually mean value of a dexterity measure over the workspace volume is considered as the objective function to be used in optimization algorithms. The mentioned indexes in a hybrid parallel manipulator (HPM) are quite complicated to solve thanks to infinite solutions for every point within the workspace of the redundant manipulators. In this paper, spatial isotropic design axioms are extended as a well-known method for optimum design of manipulators. An upper limit for the isotropy measure of HPM is calculated and instead of computing and minimizing isotropy measure, minimizing the obtained limit is considered. To this end, two different objective functions are suggested which are obtained from objective functions of comprising modules. Finally, by using genetic algorithm (GA), the best geometric parameters for a specific hybrid parallel robot which is composed of two modified Gough-Stewart platforms (MGSP) are achieved.

Keywords: hybrid manipulator, spatial isotropy, genetic algorithm, optimum design

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Authors: Chaouch Souad, Abdou Latifa, Larbi Chrifi Alaoui

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This paper deals with sensorless backstepping control of induction motor using MRAS technique associated to sliding mode approach. A high order genetic algorithm structure is used to approximate a control law designed by the Backstepping technique, and to find the best parameters globally optimized. However, the Backstepping control approach is unsuitable for high performance applications because the need of a speed sensor for increased accuracy and the absence of any error decay mechanism. In this paper a nonlinear observer, obtained by combining sliding mode structure and model reference adaptive system (MRAS), is designed for the rotor flux and rotor speed estimations. To validate the proposed method, the results are presented for showing the improved drive characteristics and performances.

Keywords: Backstepping Control, Induction Motor, Genetic Algorithm, Sliding Mode observer

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Authors: Olupemi E. Oludare

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This paper discusses the thematic structure of Yoruba popular music of Southwest Nigeria. It examines the use of themes and variations in early and contemporary Juju music. The work is an outcome of a research developed by the author in his doctoral studies at the University of Lagos, Nigeria, with the aim of analyzing the thematic and motivic developments in Yoruba popular genres. Observations, interviews, live recordings and CDs were used as methods for eliciting information. Field recordings and CDs of selected musical samples were also transcribed and notated. The research established the prevalent use of string of themes by Juju musicians as a compositional technique in moving from one musical section to another, as they communicate the verbal messages in their song. These themes consisting of the popular ‘call and response’ form found in most African music, analogous to the western ‘subject and answer’ style of the fugue or sonata form, although without the tonic–dominant relations. Due to the short and repetitive form of African melodies and rhythms, a theme is restated as a variation, where its rhythmic and melodic motifs are stylistically developed and repeated, but still retaining its recognizable core musical structure. The findings of this study showed that Juju musicians generally often employ a thematic plan where new themes are used to arrange the songs into sections, and each theme is developed into variations in order to further expand the music, eliminate monotony, and create musical aesthetics, serving as hallmark of its musical identity. The study established the musical and extra-musical attributes of the genre, while recommending further research towards analyzing the various compositional techniques employed in African popular genres.

Keywords: compositional techniques, popular music, theme and variation, thematic development

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Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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Authors: Juzhong Tan, William Kerr

Abstract:

Conching is one critical procedure in chocolate processing, where special flavors are developed, and smooth mouse feel the texture of the chocolate is developed due to particle size reduction of cocoa mass and other additives. Therefore, determination of the particle size and volatile compounds profile of cocoa bean is important for chocolate manufacturers to ensure the quality of chocolate products. Currently, precise particle size measurement is usually done by laser scattering which is expensive and inaccessible to small/medium size chocolate manufacturers. Also, some other alternatives, such as micrometer and microscopy, can’t provide good measurements and provide little information. Volatile compounds analysis of cocoa during conching, has similar problems due to its high cost and limited accessibility. In this study, a self-made electronic nose system consists of gas sensors (TGS 800 and 2000 series) was inserted to a conching machine and was used to monitoring the volatile compound profile of chocolate during the conching. A model correlated volatile compounds profiles along with factors including the content of cocoa, sugar, and the temperature during the conching to particle size of chocolate particles by genetic programming was established. The model was used to predict the particle size reduction of chocolates with different cocoa mass to sugar ratio (1:2, 1:1, 1.5:1, 2:1) at 8 conching time (15min, 30min, 1h, 1.5h, 2h, 4h, 8h, and 24h). And the predictions were compared to laser scattering measurements of the same chocolate samples. 91.3% of the predictions were within the range of later scatting measurement ± 5% deviation. 99.3% were within the range of later scatting measurement ± 10% deviation.

Keywords: cocoa bean, conching, electronic nose, genetic programming

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Authors: Pierre Moulis, Markus Herderich, Doris Rauhut, Patricia Ballestra

Abstract:

Nowadays, it is starting to be more frequent to detect wines with mousy off-flavor. The reasons behind this could be the significant decrease in sulphur dioxide, the increase in pH, and the trend for spontaneous fermentation in wine. This off-flavor can be produced by Brettanomyces bruxellensis or some Lactic acid bacteria. So far there is no study working on the influence of the genetic group on the production of these microorganisms. Objectives: The objectives of this research are to increase knowledge and to have a better understanding of the microbiological phenomena related to the production of the mousy off-flavor in the wine. Methodologies: In this research, microorganisms were screened in an N-heterocycle assay medium (this medium contained all known precursors) and the production of mousy compounds was quantified by Stir Bar Sorptive Extraction-Gas Chromatography-Mass Spectrometry (SBSE-GC-MS). Main contributions: Brettanomyces bruxellensis and Oenococcus oeni could produce mousiness at a different amount depending on the strain. But there is no group effect.

Keywords: mousy off-flavor, wine, Brettanomyces bruxellensis, Oenococcus oeni

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Authors: Fedili Benamar, Beloulou Mohamed Lamine, Ouahes Hassane, Ghattas Samir

Abstract:

Background and aims: While in Western countries, unilateral spinal anesthesia has been widely practiced for a long time, it remains little known in the local anesthesia community, and has not been the object of many studies. However, it is a simple, practical and effective technique. Our objective was to evaluate this practice in emergency anesthesia management in frail patients and to compare it with conventional spinal anesthesia. Methods: This is a prospective, observational, comparative study between hypobaric unilateral and conventional spinal anaesthesia for hip fracture surgery carried out in the operating room of the university military hospital of Staoueli. The work was spread over of 12-month period from 2019 to 2020. The parameters analyzed were hemodynamic variations, vasopressor use, block efficiency, postoperative adverse events, and postoperative morphine consumption. Results: -75 cases (mean age 72±14 years) -Group1= 41 patients (54.6%) divided into (ASA1=14.6% ASA2=60.98% ASA3=24.39%) single shoot spinal anaesthesia -Group2= 34 patients (45.3%) divided into (ASA1=2.9%, ASA2=26.4% ASA3=61.7%, ASA4=8.8%) unilateral hypobaric spinal anesthesia. -Hemodynamic variations were more severe in group 1 (51% hypotension) compared to 30% in group 2 RR=1.69 and odds ratio=2.4 -these variations were more marked in the ASA3 subgroup (group 1=70% hypotension versus group 2=30%) with an RR=2.33 and an odds ratio=5.44 -39% of group 1 required vasoactive drugs (15mg +/- 11) versus 32% of group 2 (8mg+/- 6.49) - no difference in the use of morphine in post-op. Conclusions: Within the limits of the population studied, this work demonstrates the clinical value of unilateral spinal anesthesia in ortho-trauma surgery in the frail patient.

Keywords: spinal anaesthesia, vasopressor, morphine, hypobaric unilateral spinal anesthesia, ropivacaine, hip surgery, eldery, hemodynamic

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L. Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts as a motivating starting point. In this work, the authors extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zₚ, zₙ]. The zₚ component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zₙ component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach coined Augmented Posterior CDE (AP-CDE) only requires a simple modification of the common normalizing flow framework while significantly improving the interpretation of the latent component since zₚ represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of 𝑥-related variations due to factors such as lighting condition and subject id from the other random variations. Further, the experiments show that an unconditional NF neural network based on an unsupervised model of z, such as a Gaussian mixture, fails to generate interpretable results.

Keywords: conditional density estimation, image generation, normalizing flow, supervised dimension reduction

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Authors: Omneya M. Helmy, Mona T. Kashef

Abstract:

Aminoglycosides are used in treating a wide range of infections caused by both Gram-negative and Gram positive bacteria. The presence of 16S rRNA methyl transferases (16S-RMTase) is among the newly discovered resistance mechanisms that confer high resistance to clinically useful aminoglycosides. Cephalosporins are the most commonly used antimicrobials in Egypt; therefore, this study was conducted to determine the isolation frequency of 16S rRNA methyl transferases among third generation cephalosporin-resistant clinical isolates in Egypt. One hundred and twenty three cephalosporin resistant Gram-negative clinical isolates were screened for aminoglycoside resistance by the Kirby Bauer disk diffusion method and tested for possible production of 16S-RMTase. PCR testing and sequencing were used to confirm the presence of 16S-RMTase and the associated antimicrobial resistance determinants, as well as the genetic region surrounding the armA gene. Out of 123 isolates, 66 (53.66%) were resistant to at least one aminoglycoside antibiotic. Only one Escherichia coli isolate (E9ECMO) which was totally resistant to all tested aminoglycosides, was confirmed to have the armA gene in association with blaTEM-1, blaCTX-M-15, blaCTX-M-14 and aac(6)-Ib genes. The armA gene was found to be carried on a large A/C plasmid. Genetic mapping of the armA surrounding region revealed, for the first time, the association of armA with aac(6)-Ib on the same transposon. In Conclusion, the isolation frequency of 16S-RMTase was low among the tested cephalosporin-resistant clinical samples. However, a novel composite transposon has been detected conferring high-level aminoglycosides resistance.

Keywords: aminoglcosides, armA gene, β lactmases, 16S rRNA methyl transferases

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Authors: Nattachote Rugthaicharoencheep

Abstract:

This paper presents a feeder reconfiguration problem in distribution systems. The objective is to minimize the system power loss and to improve bus voltage profile. The optimization problem is subjected to system constraints consisting of load-point voltage limits, radial configuration format, no load-point interruption, and feeder capability limits. A method based on genetic algorithm, a search algorithm based on the mechanics of natural selection and natural genetics, is proposed to determine the optimal pattern of configuration. The developed methodology is demonstrated by a 33-bus radial distribution system with distributed generations and feeder capacitors. The study results show that the optimal on/off patterns of the switches can be identified to give the minimum power loss while respecting all the constraints.

Keywords: network reconfiguration, distributed generation capacitor placement, loss reduction, genetic algorithm

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Authors: D. Estrella, A. Silva, R. Zapata, H. Rubio

Abstract:

A total of 100 primary caregivers (mothers, fathers, grandparents) with at least one child or grandchild with a diagnosis of congenital bilateral profound deafness were assessed in order to evaluate the functionality of families with a deaf member, who was evaluated by specialists in audiology, molecular biology, genetics and psychology. After confirmation of the clinical diagnosis, DNA from the patients and parents were analyzed in search of the 35delG deletion of the GJB2 gene to determine who possessed the mutation. All primary caregivers were provided psychological support, regardless of whether or not they had the mutation, and prior and subsequent, the family APGAR test was applied. All parents, grandparents were informed of the results of the genetic analysis during the psychological intervention. The family APGAR, after psychological and genetic counseling, showed that 14% perceived their families as functional, 62% moderately functional and 24% dysfunctional. This shows the importance of psychological support in family functionality that has a direct impact on the quality of life of these families.

Keywords: deafness, psychological support, family, adaptation to disability

Procedia PDF Downloads 402