Search results for: genetic algorithm

Authors: Sajad Haghshenas

Abstract:

Emerging evidence from clinical, genetic, and animal model studies suggests that the N-methyl-D-aspartate (NMDA) glutamate receptors (NMDAR) may contribute to the pathophysiology and aetiology of neurological and psychiatric disorders and the patients with impaired NMDR receptors experience psychological symptoms. Therefore, we hypothesised that NMDAR receptors play a key role in the development of attention deficit hyperactivity disorder (ADHD). In this comparative analytical study, we utilized western blotting method to assay the expression levels of NMDA subunits NR1 and NR2 in the blood plasma of 50 male individuals diagnosed with ADHD in comparison to 20 healthy controls. The findings from the western blotting analysis provide support for the hypothesis that individuals with ADHD exhibit significantly lower levels of NR1/2 receptors compared to those without the disorder. Further research is needed to explore the potential causal relationship between reduced NR1/NR2 receptor levels and the development of ADHD.

Keywords: expression, glutamate receptors, NR1, NR2, ADHD

Procedia PDF Downloads 60

Authors: Min Wang, Sergey Utev

Abstract:

The lessons from the 2007-09 global financial crisis have driven scientific research, which considers the design of new methodologies and financial models in the global market. The quantum mechanics approach was introduced in the unpredictable stock market modeling. One famous quantum tool is Feynman path integral method, which was used to model insurance risk by Tamturk and Utev and adapted to formalize the path-dependent option pricing by Hao and Utev. The research is based on the path-dependent calculation method, which is motivated by the Feynman path integral method. The path calculation can be studied in two ways, one way is to label, and the other is computational. Labeling is a part of the representation of objects, and generating functions can provide many different ways of representing share price paths. In this paper, the recent works on graphical theoretical construction of individual share price path via matroid is presented. Firstly, a study is done on the knowledge of matroid, relationship between lattice path matroid and Tutte polynomials and ways to connect points in the lattice path matroid and Tutte polynomials is suggested. Secondly, It is found that a general binary tree can be validly constructed from a connected lattice path matroid rather than general lattice path matroid. Lastly, it is suggested that there is a way to represent share price paths via a general binary tree, and an algorithm is developed to construct share price paths from general binary trees. A relationship is also provided between lattice integer points and Tutte polynomials of a transversal matroid. Use this way of connection together with the algorithm, a share price path can be constructed from a given connected lattice path matroid.

Keywords: combinatorial construction, graphical representation, matroid, path calculation, share price, Tutte polynomial

Procedia PDF Downloads 123

Authors: Fatimazahrae Elbakri, Azeddine Ibrahimi, Meryem Lemrani, Dris Belghyti

Abstract:

Leishmaniasis represents a major public health problem because of the number of cases recorded each year and the wide distribution of the disease. It is a parasitic disease of flagellated protozoa transmitted by the bite of certain species of sandfly, causing a spectrum of clinical pathology in humans ranging from disfiguring skin lesions to fatal visceral leishmaniasis. Cutaneous leishmaniasis due to Leishmania major is a polymorphic disease; in fact, the infection can be asymptomatic, localized, or disseminated. The objective of this work is to determine the genomic diversity that contributes to clinical variability by trying to identify the variation in chromosome number and to extract SNPs and SNPs and InDels; it is based on four sequences (WGS) of Leishmania major available on NCBI in Fastq form, from three countries: Tunisia, Algeria, and Israel, the analysis is set up from a pipeline to facilitate the discovery of genetic diversity, in particular SNP and chromosomal somy.

Keywords: Leshmania major, cutaneous Leishmania, NGS, genomic, somy, variant calling

Procedia PDF Downloads 63

Authors: Saeedeh Salimi, Farzaneh Farajian- Mashhadi, Ehsan Tabatabaei, Mahnaz Shahrakipoor, Minoo Yaghmaei, Mojgan Mokhtari

Abstract:

Purpose: Estrogen receptor-α (ERα) plays an essential role in the adaptation of increased uterine blood flow during gestation. Therefore ERα gene could be a possible candidate for preeclampsia(PE) susceptibility. In the current study, we aimed to investigate the association of the ERα gene polymorphisms and PE in an Iranian population. Methods: One hundred ninety-two pregnant women with PE and 186 normotensive women were genotyped for ERα gene (PvuII and XbaI) polymorphisms by PCR-RFLP method. Results: The frequency of alleles and genotypes of ERα PvuII and XbaI polymorphisms were not different between PE and normotensive control women. However, higher frequency of GG genotype was observed in women with severe PE compared to mild PE (OR, 1.8 [95% CI, 1.1 to 3]; P = 0.02) and in severe PE compared to normotensive women [OR= 1.8(1.1-3), P=0.02] after adjusting for age, ethnicity and primiparity. Conclusions: The GG genotype of ERα XbaI polymorphism could be a genetic risk factor for PE predisposition.

Keywords: estrogen receptor-α, polymorphism, gene, preeclampsia

Procedia PDF Downloads 291

Authors: Amara Prakasa Rao, N. V. S. N. Sarma

Abstract:

This paper describes the synthesis of linear array geometry with minimum sidelobe level and null control using the Taguchi method. Based on the concept of the orthogonal array, Taguchi method effectively reduces the number of tests required in an optimization process. Taguchi method has been successfully applied in many fields such as mechanical, chemical engineering, power electronics, etc. Compared to other evolutionary methods such as genetic algorithms, simulated annealing and particle swarm optimization, the Taguchi method is much easier to understand and implement. It requires less computational/iteration processing to optimize the problem. Different cases are considered to illustrate the performance of this technique. Simulation results show that this method outperforms the other evolution algorithms (like GA, PSO) for smart antenna systems design.

Keywords: array factor, beamforming, null placement, optimization method, orthogonal array, Taguchi method, smart antenna system

Procedia PDF Downloads 374

Authors: Mafel Obhuo, Dodeye I. Igbong, Duabari S. Aziaka, Pericles Pilidis

Abstract:

An important feature of the exploitation of associated gas as fuel for gas turbine engines is a declining supply. So when exploiting this resource, the divestment of prime movers is very important as the fuel supply diminishes with time. This paper explores the influence of engine degradation on the timing of divestments. Hypothetical but realistic gas turbine engines were modelled with Turbomatch, the Cranfield University gas turbine performance simulation tool. The results were deployed in three degradation scenarios within the TERA (Techno-economic and environmental risk analysis) framework to develop economic models. An optimisation with Genetic Algorithms was carried out to maximize the economic benefit. The results show that degradation will have a significant impact. It will delay the divestment of power plants, while they are running less efficiently. Over a 20 year investment, a decrease of $0.11bn, $0.26bn and $0.45bn (billion US dollars) were observed for the three degradation scenarios as against the clean case.

Keywords: economic return, flared associated gas, net present value, optimization

Procedia PDF Downloads 119

Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

Abstract:

Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

Procedia PDF Downloads 72

Authors: A. Bhartiya, S. Botchway, M. Yusuf, I. Robinson

Abstract:

Chromatin condensation is maintained by DNA-based proteins and some divalent cations (Mg²⁺, Ca²⁺, etc.). Condensation process during cell division maintains structural and functional organizations of chromosomes by transferring genetic information correctly to daughter cells. Fluorescence Lifetime Imaging (FLIM) technique measures the fluorescence decay of fixed human chromosomes by calculating the lifetime of fluorophores at a pixel x of the arrival of each photon as a function of time delay t, following excitation with a laser pulse. Fixed metaphase human chromosomes were labelled with DNA-binding dye, DAPI and later DAPI fluorescence lifetime measured using multiphoton microscopy. 5 out of 23 pairs of human chromosomes shown shorter lifetime at the centromere region, differentiating proportion of compaction along the length of chromosomes. Different lifetime was observed in a condensed and de-condensed chromosome. It clearly indicates the involvement of divalent cations in the process of condensation.

Keywords: divalent cations, FLIM (Fluorescence Lifetime Imaging), human chromosomes, multiphoton microscopy

Procedia PDF Downloads 264

Authors: Narin Salehiyan, Ramin Ghasemi Shayan

Abstract:

In order to investigate coronavirus RNA replication, transcription, recombination, protein processing and transport, virion assembly, the identification of coronavirus-specific cell receptors, and polymerase processing, the manipulation of coronavirus clones and complementary DNAs (cDNAs) of defective-interfering (DI) RNAs is the subject of this chapter. The idea of the Covid genome is nonsegmented, single-abandoned, and positive-sense RNA. When compared to other RNA viruses, its size is significantly greater, ranging from 27 to 32 kb. The quality encoding the enormous surface glycoprotein depends on 4.4 kb, encoding a forcing trimeric, profoundly glycosylated protein. This takes off exactly 20 nm over the virion envelope, giving the infection the appearance-with a little creative mind of a crown or coronet. Covid research has added to the comprehension of numerous parts of atomic science as a general rule, like the component of RNA union, translational control, and protein transport and handling. It stays a fortune equipped for creating startling experiences.

Keywords: covid-19, corona, virus, genome, genetic

Procedia PDF Downloads 57

Authors: M. Nekri, A. Khelladi

Abstract:

The world wide web network is a network with a complex topology, the main properties of which are the distribution of degrees in power law, A low clustering coefficient and a weak average distance. Modeling the web as a graph allows locating the information in little time and consequently offering a help in the construction of the research engine. Here, we present a model based on the already existing probabilistic graphs with all the aforesaid characteristics. This work will consist in studying the web in order to know its structuring thus it will enable us to modelize it more easily and propose a possible algorithm for its exploration.

Keywords: clustering coefficient, preferential attachment, small world, web community

Procedia PDF Downloads 260

Authors: Sergio A. Navarro Tuch, Martin Rogelio Bustamante Bello, Leopoldo Julian Lechuga Lopez

Abstract:

In recent years, Mexico’s population has seen a rise of different physiological and mental negative states. Two main consequences of this problematic are deficient work performance and high levels of stress generating and important impact on a person’s physical, mental and emotional health. Several approaches, such as the use of audiovisual stimulus to induce emotions and modify a person’s emotional state, can be applied in an effort to decreases these negative effects. With the use of different non-invasive physiological sensors such as EEG, luminosity and face recognition we gather information of the subject’s current emotional state. In a controlled environment, a subject is shown a series of selected images from the International Affective Picture System (IAPS) in order to induce a specific set of emotions and obtain information from the sensors. The raw data obtained is statistically analyzed in order to filter only the specific groups of information that relate to a subject’s emotions and current values of the physical variables in the controlled environment such as, luminosity, RGB light color, temperature, oxygen level and noise. Finally, a neural network based control algorithm is given the data obtained in order to feedback the system and automate the modification of the environment variables and audiovisual content shown in an effort that these changes can positively alter the subject’s emotional state. During the research, it was found that the light color was directly related to the type of impact generated by the audiovisual content on the subject’s emotional state. Red illumination increased the impact of violent images and green illumination along with relaxing images decreased the subject’s levels of anxiety. Specific differences between men and women were found as to which type of images generated a greater impact in either gender. The population sample was mainly constituted by college students whose data analysis showed a decreased sensibility to violence towards humans. Despite the early stage of the control algorithm, the results obtained from the population sample give us a better insight into the possibilities of emotional domotics and the applications that can be created towards the improvement of performance in people’s lives. The objective of this research is to create a positive impact with the application of technology to everyday activities; nonetheless, an ethical problem arises since this can also be applied to control a person’s emotions and shift their decision making.

Keywords: data analysis, emotional domotics, performance improvement, neural network

Procedia PDF Downloads 123

Authors: Anne M. Denton, Rahul Gomes, David W. Franzen

Abstract:

High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.

Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression

Procedia PDF Downloads 116

Authors: Animish Jain

Abstract:

This study deals with using Multiplicative Weight Update within artificial intelligence and machine learning to create models that can diagnose skin cancer using microscopic images of cancer samples. In this study, the multiplicative weight update method is used to take the predictions of multiple models to try and acquire more accurate results. Logistic Regression, Convolutional Neural Network (CNN), and Support Vector Machine Classifier (SVMC) models are employed within the Multiplicative Weight Update system. These models are trained on pictures of skin cancer from the ISIC-Archive, to look for patterns to label unseen scans as either benign or malignant. These models are utilized in a multiplicative weight update algorithm which takes into account the precision and accuracy of each model through each successive guess to apply weights to their guess. These guesses and weights are then analyzed together to try and obtain the correct predictions. The research hypothesis for this study stated that there would be a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The SVMC model had an accuracy of 77.88%. The CNN model had an accuracy of 85.30%. The Logistic Regression model had an accuracy of 79.09%. Using Multiplicative Weight Update, the algorithm received an accuracy of 72.27%. The final conclusion that was drawn was that there was a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The conclusion was made that using a CNN model would be the best option for this problem rather than a Multiplicative Weight Update system. This is due to the possibility that Multiplicative Weight Update is not effective in a binary setting where there are only two possible classifications. In a categorical setting with multiple classes and groupings, a Multiplicative Weight Update system might become more proficient as it takes into account the strengths of multiple different models to classify images into multiple categories rather than only two categories, as shown in this study. This experimentation and computer science project can help to create better algorithms and models for the future of artificial intelligence in the medical imaging field.

Keywords: artificial intelligence, machine learning, multiplicative weight update, skin cancer

Procedia PDF Downloads 58

Authors: Mariia A. Parfenenko, Ilya S. Dantsev, Sergei V. Bochenkov, Natalia V. Vinogradova, Olga S. Groznova, Victoria Yu. Voinova

Abstract:

Introduction: Autism is the most common neurodevelopmental disorder. Autism is characterized by difficulties in social interaction and adherence to stereotypic behavioral patterns and frequently co-occurs with epilepsy, intellectual disabilities, connective tissue disorders, and other conditions. CHD8 codes for chromodomain-helicase-DNA-binding protein 8 - a chromatin remodeler that regulates cellular proliferation and neurodevelopment in embryogenesis. CHD8 is one of the genes most frequently involved in autism. Patients and methods: 2 unrelated male patients, P3 and P12, aged 3 and 12 years old, underwent whole genome sequencing, which determined that they both had different likely pathogenic variants, both previously undescribed in literature. Sanger sequencing later determined that P12 inherited the variant from his affected mother. Results: P3 and P12 presented with autism, a developmental delay, ataxia, sleep disorders, overgrowth, and macrocephaly, as well as other clinical features typically present in patients with causative variants in CHD8. The mother of P12 also has autistic traits, as well as ataxia, hypotonia, sleep disorders, and other symptoms. However, P3 and P12 also have different cardiac abnormalities. P3 had signs of a repolarization disorder: a flattened T wave in the III and aVF derivations and a negative T wave in the V1-V2 derivations. He also had structural valve anomalies with associated regurgitation, local contractility impairment of the left ventricular, and diastolic dysfunction of the right ventricle. Meanwhile, P12 had Wolff-Parkinson-White syndrome and underwent radiofrequency ablation at the age of 2 years. At the time of observation, P12 had mild sinus arrhythmia and an incomplete right bundle branch block, as well as arterial hypertension. Discussion: Cardiac abnormalities were not previously reported in patients with causative variants in CHD8. The underlying mechanism for the formation of those abnormalities is currently unknown. However, the two hypotheses are either a disordered interaction with CHD7 – another chromodomain remodeler known to be directly involved in the cardiophenotype of CHARGE syndrome – a rare condition characterized by coloboma, heart defects and growth abnormalities, or the disrupted functioning of CHD8 as an A-Kinase Anchoring Protein, which are known to modulate cardiac function. Conclusion: We observed 2 unrelated autistic males with likely pathogenic variants in CHD8 that presented with typical symptoms of CHD8-related neurodevelopmental disorder, as well as cardiac abnormalities. Cardiac abnormalities have, until now, been considered uncharacteristic for patients with causative variants in CHD8. Further accumulation of data, including experimental evidence of the involvement of CHD8 in heart formation, will elucidate the mechanism underlying the cardiophenotype of those patients. Acknowledgements: Molecular genetic testing of the patients was made possible by the Charity Fund for medical and social genetic aid projects «Life Genome.»

Keywords: autism spectrum disorders, chromodomain-helicase-DNA-binding protein 8, neurodevelopmental disorder, cardio phenotype

Procedia PDF Downloads 73

Authors: Yun-Hsuan Chang, Chih-Chun Huang, Ru-Band Lu

Abstract:

Dopamine, metabolized to 3,4-dihydroxyphenylacetic acid (DOPAC) by aldehyde dehydrogenase 2 (ALDH2), ALDH2*1/*1, and ALDH2*1/*2+ALDH*2/*2 equally carried in Han Chinese. The relationship between dopamine metabolic enzyme and cognitive performance in bipolar II disorder comorbid with anxiety disorder (AD) remains unclear. This study proposed to explore the association between ALDH2 polymorphisms, anxiety comorbidity in bipolar II disorder. One hundred and ninety-seven BPII with or without AD comorbidity were recruited and compared with 130 Health controls (HC). A polymerase chain reaction and restriction fragment length polymorphism analysis was used to determine genotypes for ALDH2, and neuropsychological battery was performed. Two factor analyses with AD comorbidity and ALDH2 showed a significant main effect of ALDH2 on attention and marginally significant interaction between AD and ALDH2 memory performance. The ALDH2 polymorphisms may play a different role in the neuropsychological performance on varied neuropsychological performance in BPII comorbid with and without AD.

Keywords: anxiety disorder, bipolar II disorder, comorbidity, genetic

Procedia PDF Downloads 619

Authors: Filip Varga, Nina Jeran, Martina Biosic, Zlatko Satovic, Martina Grdisa

Abstract:

Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip.), a species endemic to the eastern Adriatic coastline, is the source of natural insecticide pyrethrin. Pyrethrin is a mixture of six compounds (pyrethrin I and II, cinerin I and II, jasmolin I and II) that exhibits high insecticidal activity with no detrimental effects to the environment. A recently optimized matrix-solid phase dispersion method (MSPD), using florisil as the sorbent, acetone-ethyl acetate (1:1, v/v) as the elution solvent, and sodium sulfate anhydrous as the drying agent was utilized to extract the pyrethrins from 10 wild populations (20 individuals per population) distributed along the Croatian coast. All six components in the extracts were qualitatively and quantitatively determined by high-performance liquid chromatography with a diode array detector (HPLC-DAD). Pearson’s correlation index was calculated between pyrethrin compounds, and differences between the populations using the analysis of variance were tested. Additionally, the correlation of each pyrethrin component with spatio-ecological variables (bioclimate, soil properties, elevation, solar radiation, and distance from the coastline) was calculated. Total pyrethrin content ranged from 0.10% to 1.35% of dry flower weight, averaging 0.58% across all individuals. Analysis of variance revealed significant differences between populations based on all six pyrethrin compounds and total pyrethrin content. On average, the lowest total pyrethrin content was found in the population from Pelješac peninsula (0.22% of dry flower weight) in which total pyrethrin content lower than 0.18% was detected in 55% of the individuals. The highest average total pyrethrin content was observed in the population from island Zlarin (0.87% of dry flower weight), in which total pyrethrin content higher than 1.00% was recorded in only 30% of the individuals. Pyrethrin I/pyrethrin II ratio as a measure of extract quality ranged from 0.21 (population from the island Čiovo) to 5.88 (population from island Mali Lošinj) with an average of 1.77 across all individuals. By far, the lowest quality of extracts was found in the population from Mt. Biokovo (pyrethrin I/II ratio lower than 0.72 in 40% of individuals) due to the high pyrethrin II content typical for this population. Pearson’s correlation index revealed a highly significant positive correlation between pyrethrin I content and total pyrethrin content and a strong negative correlation between pyrethrin I and pyrethrin II. The results of this research clearly indicate high intra- and interpopulation diversity of Dalmatian pyrethrum with regards to pyrethrin content and composition. The information obtained has potential use in plant genetic resources conservation and biodiversity monitoring. Possibly the largest potential lies in designing breeding programs aimed at increasing pyrethrin content in commercial breeding lines and reintroduction in agriculture in Croatia. Acknowledgment: This work has been fully supported by the Croatian Science Foundation under the project ‘Genetic background of Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir/ Sch. Bip.) insecticidal potential’ - (PyrDiv) (IP-06-2016-9034).

Keywords: Dalmatian pyrethrum, HPLC, MSPD, pyrethrin

Procedia PDF Downloads 124

Authors: Hao Min Chuah, Tatsuya Yamazaki, Ryosui Iwasawa, Tatsumi Suto

Abstract:

In recent years, with the advancement of digital technology, the movement to introduce so-called ICT (Information and Communication Technology), such as computer technology and network technology, to civil engineering construction sites and construction sites is accelerating. As part of this movement, attempts are being made in various situations to reproduce actual sites inside computers and use them for designing and construction planning, as well as for training inexperienced engineers. The installation of wave-dissipating blocks on coasts, etc., is a type of work that has been carried out by skilled workers based on their years of experience and is one of the tasks that is difficult for inexperienced workers to carry out on site. Wave-dissipating blocks are structures that are designed to protect coasts, beaches, and so on from erosion by reducing the energy of ocean waves. Wave-dissipating blocks usually weigh more than 1 t and are installed by being suspended by a crane, so it would be time-consuming and costly for inexperienced workers to train on-site. In this paper, therefore, a block installation simulator is developed based on Unity 3D, a game development engine. The simulator computes porosity. Porosity is defined as the ratio of the total volume of the wave breaker blocks inside the structure to the final shape of the ideal structure. Using the evaluation of porosity, the simulator can determine how well the user is able to install the blocks. The voxelization technique is used to calculate the porosity of the structure, simplifying the calculations. Other techniques, such as raycasting and box overlapping, are employed for accurate simulation. In the near future, the simulator will install an automatic block installation algorithm based on combinatorial optimization solutions and compare the user-demonstrated block installation and the appropriate installation solved by the algorithm.

Keywords: 3D simulator, porosity, user interface, voxelization, wave-dissipating blocks

Procedia PDF Downloads 82

Authors: Sirous Eydivandi

Abstract:

Diacylglycerol-O-acyltransferase (DGAT1) gene encodes diacylglycerol transferase enzyme that plays an important role in glycerol lipid metabolism. DGAT1 is considered to be the key enzyme in controlling the synthesis of triglycerides in adipocytes. This enzyme catalyzes the final step of triglyceride synthesis (transform triacylglycerol (DAG) into triacylglycerol (TAG). A total of 20 DGAT1 gene sequences and corresponding amino acids belonging to 4 species include cattle, goats, sheep and yaks were analyzed, and the differentiation within and among the species was also studied. The length of the DGAT1 gene varies greatly, from 1527 to 1785 bp, due to deletion, insertion, and stop codon mutation resulting in elongation. Observed genetic diversity was higher among species than within species, and Goat had more polymorphisms than any other species. Novel amino acid variation sites were detected within several species which might be used to illustrate the functional variation. Differentiation of the DGAT1 gene was obvious among species, and the clustering result was consistent with the taxonomy in the National Center for Biotechnology Information.

Keywords: DGAT1gene, bioinformatic, ruminnants, biotechnology information

Procedia PDF Downloads 476

Authors: Rebiahi Sid Ahmed, Boutarfi Zakaria, Rahmoun Malika, Antonio Galvez

Abstract:

The objective of this study was to explore the possible correlation between resistance to antibiotics and tolerance to biocides in Gram-negative bacilli isolated from the University Hospital Center of Tlemcen. This study focused on 175 clinical isolates of Gram-negative bacilli, it is a question of exploring: their level and profile of resistance to antibiotics, their tolerance to biocides, as well as the identification of the genetic supports of this resistance. Enterobacter spp. was the most predominant bacterial genus, all isolates harbored at least one of the studied genes with significant resistance capacity. Our results show, in some cases, a possible positive correlation between the presence of biocide tolerance genes and those of antibiotic resistance; in fact, tolerance to biocides could be one of the co-selection factors for antibiotic resistance. The results of this study should encourage the good practice of hygiene measures as well as the rational use of antimicrobials in order to hinder the development and emergence of resistance in our hospital departments.Mots clés : Antibiotiques, Biocides, Enterobacter, Hôpital, Résistance,

Keywords: antibiotic, biocides, enterobacter, hospital, resistance

Procedia PDF Downloads 100

Authors: Gachara Grace, Kebira Anthony, Harvey Jagger, Wainaina James

Abstract:

Aflatoxin contamination of maize in Africa poses a major threat to food security and the health of many African people. In Kenya, aflatoxin contamination of maize is high due to the environmental, agricultural and socio-economic factors. Many studies have been conducted to understand the scope of the problem, especially at pre-harvest level. This research was carried out to gather scientific information on the fungi population, diversity and aflatoxin level during the post-harvest period. The study was conducted in three geographical locations of; Kitui, Kitale and Nakuru. Samples were collected from storage structures of farmers and transported to the Biosciences eastern and central Africa (BecA), International Livestock and Research Institute (ILRI) hub laboratories. Mycoflora was recovered using the direct plating method. A total of five fungal genera (Aspergillus, Penicillium, Fusarium, Rhizopus and Bssyochlamys spp.) were isolated from the stored maize samples. The most common fungal species that were isolated from the three study sites included A. flavus at 82.03% followed by A.niger and F.solani at 49% and 26% respectively. The aflatoxin producing fungi A. flavus was recovered in 82.03% of the samples. Aflatoxin levels were analysed on both the maize samples and in vitro. Most of the A. flavus isolates recorded a high level of aflatoxin when they were analysed for presence of aflatoxin B1 using ELISA. In Kitui, all the samples (100%) had aflatoxin levels above 10ppb with a total aflatoxin mean of 219.2ppb. In Kitale, only 3 samples (n=39) had their aflatoxin levels less than 10ppb while in Nakuru, the total aflatoxin mean level of this region was 239.7ppb. When individual samples were analysed using Vicam fluorometer method, aflatoxin analysis revealed that most of the samples (58.4%) had been contaminated. The means were significantly different (p=0.00<0.05) in all the three locations. Genetic relationships of A. flavus isolates were determined using 13 Simple Sequence Repeats (SSRs) markers. The results were used to generate a phylogenetic tree using DARwin5 software program. A total of 5 distinct clusters were revealed among the genotypes. The isolates appeared to cluster separately according to the geographical locations. Principal Coordinates Analysis (PCoA) of the genetic distances among the 91 A. flavus isolates explained over 50.3% of the total variation when two coordinates were used to cluster the isolates. Analysis of Molecular Variance (AMOVA) showed a high variation of 87% within populations and 13% among populations. This research has shown that A. flavus is the main fungal species infecting maize grains in Kenya. The influence of aflatoxins on human populations in Kenya demonstrates a clear need for tools to manage contamination of locally produced maize. Food basket surveys for aflatoxin contamination should be conducted on a regular basis. This would assist in obtaining reliable data on aflatoxin incidence in different food crops. This would go a long way in defining control strategies for this menace.

Keywords: aflatoxin, Aspergillus flavus, genotyping, Kenya

Procedia PDF Downloads 263

Authors: Emna Abid, Linda Chebbi, Yosra Mabrouk, Amel Labidi, Lamia Mansour

Abstract:

Werner syndrome (WS) is a rare genetic disorder inherited in an autosomal recessive pattern characterized by accelerated aging. While extensive research has been conducted on its systemic manifestations, the specific dental implications of WS remain poorly understood. The medical history and the oral health status of two patients diagnosed with WS were detailed. Our findings revealed a high prevalence of dental problems in both patients, including periodontitis, xerostomia, and temporomandibular joint disorders. This article aims to investigate the dental challenges faced by individuals with WS as well as the prosthetic options envisaged through two clinical cases contributing to a deeper understanding of the dental implications of WS and to choose the appropriate prosthetic solution in this population. Future research should focus on larger scale studies and clinical trials to validate these proposed strategies.

Keywords: adult progeria, clinical symptoms, oral manifestations, dental care, prosthetic management

Procedia PDF Downloads 29

Authors: Mohammad Y. Alfaifi

Abstract:

Anything that poses a challenge or a threat to our well-being is a stress. Understanding the genetic material and cellular response of rats threatened with Repeated swimming stress provides insights that can influence human health. The aim of the present study was to assess the genetical damage and cytological changes caused by exposure of the test organism (Rattus rattus) to forced swimming stress. For this purpose, animals have been submerged in water path 15 minutes daily for 2 weeks. Following that, we performed a micronuclei (MN) test using MNNCE (Micronucleated normocromatic erythrocytes) and MNPCE (Micronucleated polychromatic erythrocytes), NDI (Nuclear division index) and cytological parameters using NDCI (nuclear division cytotoxicity index), necrotic and apoptotic cells in rat's bone marrow samples. Results showed that there was a slightly but not significant increase in the frequency of micronucleated as well as in cytological parameters in bone marrow cells.

Keywords: submergence stress, micronucleus, NDI, NDCI, toxicity, chromosomal aberrations

Procedia PDF Downloads 378

Authors: M. D. Nirmani, K. L. N. Perera, G. H. Galhena

Abstract:

Dengue has become one of the most important arbo-viral disease in all tropical and subtropical regions of the world. Aedes aegypti, is the principal vector of the virus, vary in both epidemiological and behavioral characteristics, which could be finely measured through DNA sequence comparison at their population level. Such knowledge in the population differences can assist in implementation of effective vector control strategies allowing to make estimates of the gene flow and adaptive genomic changes, which are important predictors of the spread of Wolbachia infection or insecticide resistance. As such, this study was undertaken to investigate the phylogenetic relationships of Ae. aegypti from Galle and Colombo, Sri Lanka, based on the ribosomal protein region which spans between two exons, in order to understand the geographical distribution of genetically distinct mosquito clades and its impact on mosquito control measures. A 320bp DNA region spanning from 681-930 bp, corresponding to the ribosomal protein, was sequenced in 62 Ae. aegypti larvae collected from Galle (N=30) and Colombo (N=32), Sri Lanka. The sequences were aligned using ClustalW and the haplotypes were determined with DnaSP 5.10. Phylogenetic relationships among haplotypes were constructed using the maximum likelihood method under Tamura 3 parameter model in MEGA 7.0.14 including three previously reported sequences of Australian (N=2) and Brazilian (N=1) Ae. aegypti. The bootstrap support was calculated using 1000 replicates and the tree was rooted using Aedes notoscriptus (GenBank accession No. KJ194101). Among all sequences, nineteen different haplotypes were found among which five haplotypes were shared between 80% of mosquitoes in the two populations. Seven haplotypes were unique to each of the population. Phylogenetic tree revealed two basal clades and a single derived clade. All observed haplotypes of the two Ae. aegypti populations were distributed in all the three clades, indicating a lack of genetic differentiation between populations. The Brazilian Ae. aegypti haplotype and one of the Australian haplotypes were grouped together with the Sri Lankan basal haplotype in the same basal clade, whereas the other Australian haplotype was found in the derived clade. Phylogram showed that Galle and Colombo Ae. aegypti populations are highly related to each other despite the large geographic distance (129 Km) indicating a substantial genetic similarity between them. This may have probably arisen from passive migration assisted by human travelling and trade through both land and water as the two areas are bordered by the sea. In addition, studied Sri Lankan mosquito populations were closely related to Australian and Brazilian samples. Probably this might have caused by shipping industry between the three countries as all of them are fully or partially enclosed by sea. For example, illegal fishing boats migrating to Australia by sea is perhaps a good mean of transportation of all life stages of mosquitoes from Sri Lanka. These findings indicate that extensive mosquito migrations occur between populations not only within the country, but also among other countries in the world which might be a main barrier to the successful vector control measures.

Keywords: Aedes aegypti, dengue control, extensive mosquito migration, haplotypes, phylogeny, ribosomal protein

Procedia PDF Downloads 166

Authors: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar

Abstract:

Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.

Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks

Procedia PDF Downloads 159

Authors: Yuri Laevsky, Tatyana Nosova

Abstract:

The phenomenon of filtration gas combustion (FGC) had been discovered experimentally at the beginning of 80’s of the previous century. It has a number of important applications in such areas as chemical technologies, fire-explosion safety, energy-saving technologies, oil production. From the physical point of view, FGC may be defined as the propagation of region of gaseous exothermic reaction in chemically inert porous medium, as the gaseous reactants seep into the region of chemical transformation. The movement of the combustion front has different modes, and this investigation is focused on the low-velocity regime. The main characteristic of the process is the velocity of the combustion front propagation. Computation of this characteristic encounters substantial difficulties because of the strong heterogeneity of the process. The mathematical model of FGC is formed by the energy conservation laws for the temperature of the porous medium and the temperature of gas and the mass conservation law for the relative concentration of the reacting component of the gas mixture. In this case the homogenization of the model is performed with the use of the two-temperature approach when at each point of the continuous medium we specify the solid and gas phases with a Newtonian heat exchange between them. The construction of a computational scheme is based on the principles of mixed finite element method with the usage of a regular mesh. The approximation in time is performed by an explicit–implicit difference scheme. Special attention was given to determination of the combustion front propagation velocity. Straight computation of the velocity as grid derivative leads to extremely unstable algorithm. It is worth to note that the term ‘front propagation velocity’ makes sense for settled motion when some analytical formulae linking velocity and equilibrium temperature are correct. The numerical implementation of one of such formulae leading to the stable computation of instantaneous front velocity has been proposed. The algorithm obtained has been applied in subsequent numerical investigation of the FGC process. This way the dependence of the main characteristics of the process on various physical parameters has been studied. In particular, the influence of the combustible gas mixture consumption on the front propagation velocity has been investigated. It also has been reaffirmed numerically that there is an interval of critical values of the interfacial heat transfer coefficient at which a sort of a breakdown occurs from a slow combustion front propagation to a rapid one. Approximate boundaries of such an interval have been calculated for some specific parameters. All the results obtained are in full agreement with both experimental and theoretical data, confirming the adequacy of the model and the algorithm constructed. The presence of stable techniques to calculate the instantaneous velocity of the combustion wave allows considering the semi-Lagrangian approach to the solution of the problem.

Keywords: filtration gas combustion, low-velocity regime, mixed finite element method, numerical simulation

Procedia PDF Downloads 287

Authors: Mao Zhaofang, Xu Yida, Fang Kan, Fu Enyuan, Zhao Zhao

Abstract:

Nowadays, last-mile distribution plays an increasingly important role in the whole industrial chain delivery link and accounts for a large proportion of the whole distribution process cost. Promoting the upgrading of logistics networks and improving the layout of final distribution points has become one of the trends in the development of modern logistics. Due to the discrete and heterogeneous needs and spatial distribution of customer demand, which will lead to a higher delivery failure rate and lower vehicle utilization, last-mile delivery has become a time-consuming and uncertain process. As a result, courier companies have introduced a range of innovative parcel storage facilities, including pick-up points and lockers. The introduction of pick-up points and lockers has not only improved the users’ experience but has also helped logistics and courier companies achieve large-scale economy. Against the backdrop of the COVID-19 of the previous period, contactless delivery has become a new hotspot, which has also created new opportunities for the development of collection services. Therefore, a key issue for logistics companies is how to design/redesign their last-mile distribution network systems to create integrated logistics and distribution networks that consider pick-up points and lockers. This paper focuses on the introduction of self-pickup facilities in new logistics and distribution scenarios and the heterogeneous demands of customers. In this paper, we consider two types of demand, including ordinary products and refrigerated products, as well as corresponding transportation vehicles. We consider the constraints associated with self-pickup points and lockers and then address the location-routing problem with self-pickup facilities and heterogeneous demands (LRP-PFHD). To solve this challenging problem, we propose a mixed integer linear programming (MILP) model that aims to minimize the total cost, which includes the facility opening cost, the variable transport cost, and the fixed transport cost. Due to the NP-hardness of the problem, we propose a hybrid adaptive large-neighbourhood search algorithm to solve LRP-PFHD. We evaluate the effectiveness and efficiency of the proposed algorithm by using instances generated based on benchmark instances. The results demonstrate that the hybrid adaptive large neighbourhood search algorithm is more efficient than MILP solvers such as Gurobi for LRP-PFHD, especially for large-scale instances. In addition, we made a comprehensive analysis of some important parameters (e.g., facility opening cost and transportation cost) to explore their impacts on the results and suggested helpful managerial insights for courier companies.

Keywords: city logistics, last-mile delivery, location-routing, adaptive large neighborhood search

Procedia PDF Downloads 62

Authors: Abdullah Al Farwan, Ya Zhang

Abstract:

In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

Procedia PDF Downloads 150

Authors: Makda Aamir, Sood Aayushi, Syed Omar, Nihan Khuld, Iskander Peter, Ijaz Naeem, Sharma Nishant

Abstract:

Introduction:Glycogen Storage Disease Type-1 (GSD-1) is a rare phenomenon primarily affecting the liver and kidney. Excessive accumulation of glycogen and fat in liver, kidney, and intestinal mucosa is noted in patients with deficiency of Glucose-6-phosphatase deficiency. Patients with GSD-1 have a wide spectrum of symptoms, including hepatomegaly, hypoglycemia, lactic acidemia, hyperlipidemia, hyperuricemia, and growth retardation. Age of onset, rate of disease progression and its severity is variable in this disease.Case:An 18-year-old male with GSD-1a, Von Gierke’s disease, hyperuricemia, and hypertension presented to the hospital with nausea and vomiting. The patient followed an hourly cornstarch regimen during the day and overnight through infusion via a PEG tube. The complaints started at work, where he was unable to tolerate oral cornstarch. He washemodynamically stable on arrival. ABG showed pH 7.372, PaCO2 30.3, and PaO2 92.2. WBC 16.80, K+ 5.8, HCO3 13, BUN 28, Cr 2.2, Glucose 60, AST 115, ALT 128, Cholesterol 352, Triglycerides >1000, Uric Acid 10.6, Lactic Acid 11.8 which trended down to 8.0. CT abdomen showed hepatomegaly and fatty infiltration with the PEG tube in place.He was admitted to the ICU and started on D5NS for hypoglycemia and lactic acidosis. Per request by the patient’s pediatrician, he was transitioned to IV D10/0.45NS at 110mL/Hr to maintain blood glucose above 75 mg/L. Frequent accuchecks were done till he could tolerate his dietary regimen with cornstarch. Lactic acid downtrend to 2.9, and accuchecks ranged between 100-110. Cr improved to 1.3, and his home medications (Allopurinol and Lisinopril) were resumed. He was discharged in stable condition with plans for further genetic therapy work up.Discussion:Mainstay therapy for Von Gierke’s Disease is the prevention of metabolic derangements for which dietary and lifestyle changes are recommended. A low fructose and sucrose diet is recommended by limiting the intake of galactose and lactose to one serving per day. Hypoglycemia treatment in such patients is two-fold, utilizing both quick and stable release sources. Cornstarch has been one such therapy since the 1980s; its slow digestion provides a steady release of glucose over a longer period of time as compared with other sources of carbohydrates. Dosing guidelines vary from age to age and person to person, but it is highly recommended to check BG levels frequently to maintain a BG > 70 mg/dL. Associated high levels of triglycerides and cholesterol can be treated with statins, fibrates, etc. Conclusion:The management of hypoglycemia in GSD 1 disease presents various obstacles which could prove to be fatal. Due to the deficiency of G6P, treatment with a specialized hypoglycemic regimen is warranted. A D10 ½ NS infusion can be used to maintain blood sugar levels as well as correct metabolic or lactate imbalances. Infusion should be gradually weaned off after the patient can tolerate oral feeds as this can help prevent the risk of hypoglycemia and other derangements. Further research is needed in regards to these patients for more sustainable regimens.

Keywords: von gierke, glycogen storage disease, hypoglycemia, genetic disease

Procedia PDF Downloads 94

Authors: Zanele D. Ngwenya, Mustapha Mohammed, Felix D. Dakora

Abstract:

Legumes are a major source of biological nitrogen, and therefore play a crucial role in maintaining soil productivity in smallholder agriculture in southern Africa. Through their ability to fix atmospheric nitrogen in root nodules, legumes are a better option for sustainable nitrogen supply in cropping systems than chemical fertilisers. For decades, farmers have been highly receptive to the use of rhizobial inoculants as a source of nitrogen due mainly to the availability of elite rhizobial strains at a much lower compared to chemical fertilisers. To improve the efficiency of the legume-rhizobia symbiosis in African soils would require the use of highly effective rhizobia capable of nodulating a wide range of host plants. This study assessed the morphogenetic diversity, photosynthetic functioning and relative symbiotic effectiveness (RSE) of groundnut, jack bean and soybean microsymbionts in Eswatini soils as a first step to identifying superior isolates for inoculant production. According to the manufacturer's instructions, rhizobial isolates were cultured in yeast-mannitol (YM) broth until the late log phase and the bacterial genomic DNA was extracted using GenElute bacterial genomic DNA kit. The extracted DNA was subjected to enterobacterial repetitive intergenic consensus-PCR (ERIC-PCR) and a dendrogram constructed from the band patterns to assess rhizobial diversity. To assess the N2-fixing efficiency of the authenticated rhizobia, photosynthetic rates (A), stomatal conductance (gs), and transpiration rates (E) were measured at flowering for plants inoculated with the test isolates. The plants were then harvested for nodulation assessment and measurement of plant growth as shoot biomass. The results of ERIC-PCR fingerprinting revealed the presence of high genetic diversity among the microsymbionts nodulating each of the three test legumes, with many of them showing less than 70% ERIC-PCR relatedness. The dendrogram generated from ERIC-PCR profiles grouped the groundnut isolates into 5 major clusters, while the jack bean and soybean isolates were grouped into 6 and 7 major clusters, respectively. Furthermore, the isolates also elicited variable nodule number per plant, nodule dry matter, shoot biomass and photosynthetic rates in their respective host plants under glasshouse conditions. Of the groundnut isolates tested, 38% recorded high relative symbiotic effectiveness (RSE >80), while 55% of the jack bean isolates and 93% of the soybean isolates recorded high RSE (>80) compared to the commercial Bradyrhizobium strains. About 13%, 27% and 83% of the top N₂-fixing groundnut, jack bean and soybean isolates, respectively, elicited much higher relative symbiotic efficiency (RSE) than the commercial strain, suggesting their potential for use in inoculant production after field testing. There was a tendency for both low and high N₂-fixing isolates to group together in the dendrogram from ERIC-PCR profiles, which suggests that RSE can differ significantly among closely related microsymbionts.

Keywords: genetic diversity, relative symbiotic effectiveness, inoculant, N₂-fixing

Procedia PDF Downloads 197

Authors: Minho Kwak, Suhwan Yun, Choonsoo Park

Abstract:

Nose shape optimizations of high-speed train are performed for the improvement of aerodynamic characteristics. Based on the commercial train, KTX-Sancheon, multi-objective optimizations are conducted for the improvement of the side wind stability and the micro-pressure wave following the optimization for the reduction of aerodynamic drag. 3D nose shapes are modelled by the Vehicle Modeling Function. Aerodynamic drag and side wind stability are calculated by three-dimensional compressible Navier-Stokes solver, and micro pressure wave is done by axi-symmetric compressible Navier-Stokes solver. The Maxi-min Latin Hypercube Sampling method is used to extract sampling points to construct the approximation model. The kriging model is constructed for the approximation model and the NSGA-II algorithm was used as the multi-objective optimization algorithm. Nose length, nose tip height, and lower surface curvature are design variables. Because nose length is a dominant variable for aerodynamic characteristics of train nose, two optimization processes are progressed respectively with and without the design variable, nose length. Each pareto set was obtained and each optimized nose shape is selected respectively considering Honam high-speed rail line infrastructure in South Korea. Through the optimization process with the nose length, when compared to KTX Sancheon, aerodynamic drag was reduced by 9.0%, side wind stability was improved by 4.5%, micro-pressure wave was reduced by 5.4% whereas aerodynamic drag by 7.3%, side wind stability by 3.9%, micro-pressure wave by 3.9%, without the nose length. As a result of comparison between two optimized shapes, similar shapes are extracted other than the effect of nose length.

Keywords: aerodynamic characteristics, design variable, multi-objective optimization, train nose shape

Procedia PDF Downloads 336