Search results for: cartesian genetic programming

Authors: Mohammadali Abedini Sanigy, Jiangang Fei

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In this paper, a mathematical optimization model was developed to maximize the profit in a vegetable production planning problem. It serves as a decision support system that assists farmers in land allocation to crops and harvest scheduling decisions. The developed model can handle different rotation rules in two consecutive cycles of production, which is a common practice in organic production system. Moreover, different production methods of the same crop were considered in the model formulation. The main strength of the model is that it is not restricted to predetermined production periods, which makes the planning more flexible. The model is classified as a mixed integer programming (MIP) model and formulated in PYOMO -a Python package to formulate optimization models- and solved via Gurobi and CPLEX optimizer packages. The model was tested with secondary data from 'Australian vegetable growing farms', and the results were obtained and discussed with the computational test runs. The results show that the model can successfully provide reliable solutions for real size problems.

Keywords: crop rotation, harvesting, mathematical model formulation, vegetable production

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Authors: Ajay Wadhwa

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A Laboratory course on computational physics is different from the conventional lab course on other topics of physics like Mechanics, Heat, Optics, etc. because it involves active participation of the teacher as well as one-to-one interaction between teacher and the student. The course content requires the teacher to teach programming language as well as numerical methods along with their applications in physics. The task becomes more daunting when about 90% of the students in the class have no previous experience of any programming language. In the presented work, we have described a methodology for conducting the computational physics course by using the Google Drive and Dropitto.me cloud storage services. We have evaluated the performance in a class of sixty students by dividing them equally into four groups. One of the groups was made the peer group on whom the presented methodology was tested. The other groups were taught by using conventional method of classroom lectures. In order to assess our methodology, we analyzed the performance of students in four class tests. A study of certain statistical parameters like the mean, standard deviation, and Z-test hypothesis revealed that the cyber methodology based on cloud storage is more efficient than the conventional method of teaching.

Keywords: computational Physics, Z-test hypothesis, cloud storage, Google drive

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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: 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: Virupakshi Hiremata, Ratnakar M. Shet, Raghavendra Gunnaiah, Prashantha A.

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Muskmelon is a health-beneficial and refreshing dessert vegetable with a low shelf life. Mangalore melon, a genetic homeologue of muskmelon, has a shelf life of more than six months and is mostly used for culinary purposes. Understanding the genetics of shelf life, yield and yield-related traits and identification of markers linked to such traits is helpful in transfer of extended shelf life from Mangalore melon to the muskmelon through intra-specific hybridization. For QTL mapping, 276 F2 mapping population derived from the cross Arka Siri × SS-17 was genotyped with 40 polymorphic markers distributed across 12 chromosomes. The same population was also phenotyped for yield, shelf life and fruit quality traits. One major QTL (R2 >10) and fourteen minor QTLs (R2 <10) localized on four linkage groups, governing different traits were mapped in F2 mapping population developed from the intraspecific cross with a LOD > 5.5. The phenotypic varience explained by each locus varied from 3.63 to 10.97 %. One QTL was linked to shelf-life (qSHL-3-1), five QTLs were linked to TSS (qTSS-1-1, qTSS-3-3, qTSS-3-1, qTSS-3-2 and qTSS-1-2), two QTLs for flesh thickness (qFT-3-1, and qFT-3-2) and seven QTLs for fruit yield per vine (qFYV-3-1, qFYV-1-1, qFYV-3-1, qFYV1-1, qFYV-1-3, qFYV2-1 and qFYV6-1). QTL flanking markers may be used for marker assisted introgression of shelf life into muskmelon. Important QTL will be further fine-mapped for identifying candidate genes by QTLseq and RNAseq analysis. Fine-mapping of Important Quantitative Trait Loci (QTL) holds immense promise in elucidating the genetic basis of complex traits. Leveraging advanced techniques like QTLseq and RNA sequencing (RNA seq) is crucial for this endeavor. QTLseq combines next-generation sequencing with traditional QTL mapping, enabling precise identification of genomic regions associated with traits of interest. Through high-throughput sequencing, QTLseq provides a detailed map of genetic variations linked to phenotypic variations, facilitating targeted investigations. Moreover, RNA seq analysis offers a comprehensive view of gene expression patterns in response to specific traits or conditions. By comparing transcriptomes between contrasting phenotypes, RNA seq aids in pinpointing candidate genes underlying QTL regions. Integrating QTLseq with RNA seq allows for a multi-dimensional approach, coupling genetic variation with gene expression dynamics.

Keywords: QTL, shelf life, TSS, muskmelon and Mangalore melon

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

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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: Hongmei Chi

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The Blockchain has become a necessity for many different societal industries and ordinary lives including cryptocurrency technology, supply chain, health care, public safety, education, etc. Therefore, training our future blockchain developers to know blockchain programming vulnerability and I.T. students' cyber security is in high demand. In this work, we propose a framework including learning modules and hands-on labs to guide future I.T. professionals towards developing secure blockchain programming habits and mitigating source code vulnerabilities at the early stages of the software development lifecycle following the concept of Secure Software Development Life Cycle (SSDLC). In this research, our goal is to make blockchain programmers and I.T. students aware of the vulnerabilities of blockchains. In summary, we develop a framework that will (1) improve students' skills and awareness of blockchain source code vulnerabilities, detection tools, and mitigation techniques (2) integrate concepts of blockchain vulnerabilities for IT students, (3) improve future IT workers’ ability to master the concepts of blockchain attacks.

Keywords: software vulnerability detection, hands-on lab, static analysis tools, vulnerabilities, blockchain, active learning

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Authors: Mohammad Reza Esmaili

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After the occurrence of blackouts, the most important subject is how fast the electric service is restored. Power system restoration is an immensely complex issue and there should be a plan to be executed within the shortest time period. This plan has three main stages of black start, network reconfiguration and load restoration. In the black start stage, operators and experts may face several problems, for instance, the unsuccessful connection of the long high-voltage transmission line connected to the electrical source. In this situation, the generator may be tripped because of the unsuitable setting of its line charging mode or high absorbed reactive power. In order to solve this problem, the line charging process is defined as a nonlinear programming problem, and it is optimized by using GAMS software in this paper. The optimized process is performed on a grid that includes a 250 MW hydroelectric unit and a 400 KV transmission system. Simulations and field test results show the effectiveness of optimal planning.

Keywords: power system restoration, black start, line charging mode, nonlinear programming

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Authors: Omneya M. Helmy, Mona T. Kashef

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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: Maedeh Gharazi

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Distinguishing proof of entrepreneurial open doors in the field of nutrition counseling is a focal issue in utilizing nutrition experts and addressing the needs of patients with chronic diseases better. To this end, this review has been directed keeping in mind the end goal to investigate the supply and interest patterns of diabetes sustenance advising as a fundamental stride toward recognizing the entrepreneurial open doors for nutrition advisors in Tehran, Iran. To execute this expressive overview concentrate on, a survey in light of Likert scale was sent via email to 100 dynamic experts in the field of nutrition counseling services in Tehran, of whom 52 reacted to its inquiries. At that point, the mean estimations of members' reactions were ascertained utilizing SPSS programming and contrasted to each other. The outcome acquired in view of members' reactions uncovered that the requirement for "healthful guiding as a treatment group" was basically not met in diverse age, training and salary gatherings of diabetic patients. Along these lines, nutrition counseling as a treatment group can be considered as a suitable field for entrepreneurial exercises.

Keywords: nutrition counseling, chronic diseases, diabetes, likert scale, SPSS programming

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Authors: Nattachote Rugthaicharoencheep

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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

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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

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

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Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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Authors: Ngoc-Hieu Vu

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A study was conducted to estimate the record keeping, genetic selection, educational experience, and farm management effect on monthly milk yield per farm, average milk yield per cow, monthly milk revenue per farm, and monthly milk revenue per cow of dairy farms in the Southern region of Vietnam. The dataset contained 5448 monthly record collected from January 2013 to May 2015. Results showed that longer experience increased (P < 0.001) monthly milk yields and revenues. Better educated farmers produced more monthly milk per farm and monthly milk per cow and revenues (P < 0.001) than lower educated farmers. Farm that kept records on individual animals had higher (P < 0.001) for monthly milk yields and revenues than farms that did not. Farms that used hired people produced the highest (p < 0.05) monthly milk yield per farm, milk yield per cow and revenues, followed by farms that used both hire and family members, and lowest values were for farms that used family members only. Farms that used crosses Holstein in herd were higher performance (p < 0.001) for all traits than farms that used purebred Holstein and other breeds. Farms that used genetic information and phenotypes when selecting sires were higher (p < 0.05) for all traits than farms that used only phenotypes and personal option. Farms that received help from Vet, organization staff, or government officials had higher monthly milk yield and revenues than those that decided by owner. These findings suggest that dairy farmers should be training in systematic, must be considered and continuous support to improve farm milk production and revenues, to increase the likelihood of adoption on a sustainable way.

Keywords: dairy farming, education, milk yield, Southern Vietnam

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Authors: Dale Dzemydiene, Aurelija Burinskiene, Arunas Miliauskas, Kristina Ciziuniene

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Data flow and the purpose of reporting the data are different and dependent on business needs. Different parameters are reported and transferred regularly during freight delivery. This business practices form the dataset constructed for each time point and contain all required information for freight moving decisions. As a significant amount of these data is used for various purposes, an integrating methodological approach must be developed to respond to the indicated problem. The proposed methodology contains several steps: (1) collecting context data sets and data validation; (2) multi-objective analysis for optimizing freight transfer services. For data validation, the study involves Grubbs outliers analysis, particularly for data cleaning and the identification of statistical significance of data reporting event cases. The Grubbs test is often used as it measures one external value at a time exceeding the boundaries of standard normal distribution. In the study area, the test was not widely applied by authors, except when the Grubbs test for outlier detection was used to identify outsiders in fuel consumption data. In the study, the authors applied the method with a confidence level of 99%. For the multi-objective analysis, the authors would like to select the forms of construction of the genetic algorithms, which have more possibilities to extract the best solution. For freight delivery management, the schemas of genetic algorithms' structure are used as a more effective technique. Due to that, the adaptable genetic algorithm is applied for the description of choosing process of the effective transportation corridor. In this study, the multi-objective genetic algorithm methods are used to optimize the data evaluation and select the appropriate transport corridor. The authors suggest a methodology for the multi-objective analysis, which evaluates collected context data sets and uses this evaluation to determine a delivery corridor for freight transfer service in the multi-modal transportation network. In the multi-objective analysis, authors include safety components, the number of accidents a year, and freight delivery time in the multi-modal transportation network. The proposed methodology has practical value in the management of multi-modal transportation processes.

Keywords: multi-objective, analysis, data flow, freight delivery, methodology

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Authors: Ferinar Moaidi, Mahdi Moaidi

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Environmental issues and the ever-increasing in demand of electrical energy make it necessary to have distributed generation (DG) resources in the power system. In this research, in order to realize the goals of reducing losses and improving the voltage profile in a microgrid, the allocation and sizing of DGs have been used. The proposed Genetic Algorithm (GA) is described from the array of artificial intelligence methods for solving the problem. The algorithm is implemented on the IEEE 33 buses network. This study is presented in two scenarios, primarily to illustrate the effect of location and determination of DGs has been done to reduce losses and improve the voltage profile. On the other hand, decisions made with the one-level assumptions of load are not universally accepted for all levels of load. Therefore, in this study, load modelling is performed and the results are presented for multi-levels load state.

Keywords: distributed generation, genetic algorithm, microgrid, load modelling, loss reduction, voltage improvement

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Authors: Ana Vieira, Fernando Lau, João Pedro Mortágua, Luís Cruz, Rui Santos

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The air transport impact on environment is more than ever a limitative obstacle to the aeronautical industry continuous growth. Over the last decades, considerable effort has been carried out in order to obtain quieter aircraft solutions, whether by changing the original design or investigating more silent maneuvers. The noise propagated by rotating surfaces is one of the most important sources of annoyance, being present in most aerial vehicles. Bearing this is mind, CEIIA developed a new computational chain for noise prediction with in-house software tools to obtain solutions in relatively short time without using excessive computer resources. This work is based on the new acoustic tool, which aims to predict the rotor noise generated during steady and maneuvering flight, making use of the flexibility of the C language and the advantages of GPU programming in terms of velocity. The acoustic tool is based in the Formulation 1A of Farassat, capable of predicting two important types of noise: the loading and thickness noise. The present work describes the most important features of the acoustic tool, presenting its most relevant results and framework analyses for helicopters and UAV quadrotors.

Keywords: rotor noise, acoustic tool, GPU Programming, UAV noise

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Authors: Alaa Sheta

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Economic Load Dispatch (ELD) is one of the vital optimization problems in power system planning. Solving the ELD problems mean finding the best mixture of power unit outputs of all members of the power system network such that the total fuel cost is minimized while sustaining operation requirements limits satisfied across the entire dispatch phases. Many optimization techniques were proposed to solve this problem. A famous one is the Quadratic Programming (QP). QP is a very simple and fast method but it still suffer many problem as gradient methods that might trapped at local minimum solutions and cannot handle complex nonlinear functions. Numbers of metaheuristic algorithms were used to solve this problem such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). In this paper, another meta-heuristic search algorithm named Differential Evolution (DE) is used to solve the ELD problem in power systems planning. The practicality of the proposed DE based algorithm is verified for three and six power generator system test cases. The gained results are compared to existing results based on QP, GAs and PSO. The developed results show that differential evolution is superior in obtaining a combination of power loads that fulfill the problem constraints and minimize the total fuel cost. DE found to be fast in converging to the optimal power generation loads and capable of handling the non-linearity of ELD problem. The proposed DE solution is able to minimize the cost of generated power, minimize the total power loss in the transmission and maximize the reliability of the power provided to the customers.

Keywords: economic load dispatch, power systems, optimization, differential evolution

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Authors: Mona Khabiri, Fahimeh Farahani

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The present study was an attempt to investigate the comparative effect of teaching NLP, critical thinking, and a combination of NLP and critical thinking on EFL learners' reading comprehension. To fulfill the purpose of this study, a group of 82 female and male intermediate EFL learners at a Language School in Iran took a piloted sample PET as a proficiency test and 63 of them were selected as homogenous learners and were randomly assigned to three experimental groups. Within a treatment process of 10 sessions the teacher/researcher provided the participants of each group with handouts, explanations, practices, homework, and questionnaires on techniques of NLP, critical thinking, and a combination of both. During these 10 sessions, 10 same reading comprehension texts extracted from the multi-skill course book suggested by the language school where thought to the participants of each experimental group using skills and strategies of NLP, critical thinking, and a combination of both. On the eleventh session, the participants sat for a reading posttest. The results of one-way ANOVA showed no significant difference among the three groups in terms of reading comprehension. Justifications and implications for the findings of the study and suggestions for further research are presented.

Keywords: neuro-linguistic programming (NLP), critical thinking, reading comprehension

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Authors: Ashok Kumar, Parveen Parveen

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India is bestowed with an extremely high population of plant species with medicinal value and even has two biodiversity hotspots. Indian systems of medicine including Ayurveda, Siddha and Unani have historically been serving humankind across the world since time immemorial. About 1500 plant species have well been documented in Ayurvedic Nighantus as official medicinal plants. Additionally, several hundred species of plants are being routinely used as medicines by local people especially tribes living in and around forests. The natural resources for medicinal plants have unscientifically been over-exploited forcing rapid depletion in their genetic diversity. Moreover, renewed global interest in herbal medicines may even lead to additional depletion of medicinal plant wealth of the country, as about 95% collection of medicinal plants for pharmaceutical preparation is being carried out from natural forests. On the other hand, huge export market of medicinal and aromatic plants needs to be seriously tapped for enhancing inflow of foreign currency. Asparagus racemosus Willd., a member of family Liliaceae, is one of thirty-two plant species that have been identified as priority species for cultivation and conservation by the National Medicinal Plant Board (NMPB), Government of India. Though attention is being focused on standardization of agro-techniques and extraction methods, little has been designed on genetic improvement and selection of desired types with higher root production and saponin content, a basic ingredient of medicinal value. The saponin not only improves defense mechanisms and controls diabetes but the roots of this species promote secretion of breast milk, improved lost body weight and considered as an aphrodisiac. There is ample scope for genetic improvement of this species for enhancing productivity substantially, qualitatively and quantitatively. It is emphasized to select desired genotypes with sufficient genetic diversity for important economic traits. Hybridization between two genetically divergent genotypes could result in the synthesis of new F1 hybrids consisting of useful traits of both the parents. The evaluation of twenty seed sources of Asparagus racemosus assembled different geographical locations of India revelled high degree of variability for traits of economic importance. The maximum genotypic and phenotypic variance was observed for shoot height among shoot related traits and for root length among root related traits. The shoot height, genotypic variance, phenotypic variance, genotypic coefficient of variance, the phenotypic coefficient of variance was recorded to be 231.80, 3924.80, 61.26 and 1037.32, respectively, where those of the root length were 9.55, 16.80, 23.46 and 41.27, respectively. The maximum genetic advance and genetic gain were obtained for shoot height among shoot-related traits and root length among root-related traits. Index values were developed for all seed sources based on the four most important traits, and Panthnagar (Uttrakhand), Jodhpur (Rajasthan), Dehradun (Uttarakhand), Chandigarh (Punjab), Jammu (Jammu & Kashmir) and Solan (Himachal Pradesh) were found to be promising seed sources.

Keywords: asparagus, genetic, genotypes, variance

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Authors: Stojan Kravanja, Andrej Ivanič, Tomaž Žula

Abstract:

This contribution focuses on structural optimization in civil engineering using mixed integer non-linear programming (MINLP). MINLP is characterized as a versatile method that can handle both continuous and discrete optimization variables simultaneously. Continuous variables are used to optimize parameters such as dimensions, stresses, masses, or costs, while discrete variables represent binary decisions to determine the presence or absence of structural elements within a structure while also calculating discrete materials and standard sections. The optimization process is divided into three main steps. First, a mechanical superstructure with a variety of different topology-, material- and dimensional alternatives. Next, a MINLP model is formulated to encapsulate the optimization problem. Finally, an optimal solution is searched in the direction of the defined objective function while respecting the structural constraints. The economic or mass objective function of the material and labor costs of a structure is subjected to the constraints known from structural analysis. These constraints include equations for the calculation of internal forces and deflections, as well as equations for the dimensioning of structural components (in accordance with the Eurocode standards). Given the complex, non-convex and highly non-linear nature of optimization problems in civil engineering, the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm is applied. This algorithm alternately solves subproblems of non-linear programming (NLP) and main problems of mixed-integer linear programming (MILP), in this way gradually refines the solution space up to the optimal solution. The NLP corresponds to the continuous optimization of parameters (with fixed topology, discrete materials and standard dimensions, all determined in the previous MILP), while the MILP involves a global approximation to the superstructure of alternatives, where a new topology, materials, standard dimensions are determined. The optimization of a convex problem is stopped when the MILP solution becomes better than the best NLP solution. Otherwise, it is terminated when the NLP solution can no longer be improved. While the OA/ER algorithm, like all other algorithms, does not guarantee global optimality due to the presence of non-convex functions, various modifications, including convexity tests, are implemented in OA/ER to mitigate these difficulties. The effectiveness of the proposed MINLP approach is demonstrated by its application to various structural optimization tasks, such as mass optimization of steel buildings, cost optimization of timber halls, composite floor systems, etc. Special optimization models have been developed for the optimization of these structures. The MINLP optimizations, facilitated by the user-friendly software package MIPSYN, provide insights into a mass or cost-optimal solutions, optimal structural topologies, optimal material and standard cross-section choices, confirming MINLP as a valuable method for the optimization of structures in civil engineering.

Keywords: MINLP, mixed-integer non-linear programming, optimization, structures

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Authors: Mária Csernoch, Piroska Biró

Abstract:

The legends about “user-friendly” and “easy-to-use” birotical tools (computer-related office tools) have been spreading and misleading end-users. This approach has led us to the extremely high number of incorrect documents, causing serious financial losses in the creating, modifying, and retrieving processes. Our research proved that there are at least two sources of this underachievement: (1) The lack of the definition of the correctly edited, formatted documents. Consequently, end-users do not know whether their methods and results are correct or not. They are not aware of their ignorance. They are so ignorant that their ignorance does not allow them to realize their lack of knowledge. (2) The end-users’ problem-solving methods. We have found that in non-traditional programming environments end-users apply, almost exclusively, surface approach metacognitive methods to carry out their computer related activities, which are proved less effective than deep approach methods. Based on these findings we have developed deep approach methods which are based on and adapted from traditional programming languages. In this study, we focus on the most popular type of birotical documents, the text-based documents. We have provided the definition of the correctly edited text, and based on this definition, adapted the debugging method known in programming. According to the method, before the realization of text editing, a thorough debugging of already existing texts and the categorization of errors are carried out. With this method in advance to real text editing users learn the requirements of text-based documents and also of the correctly formatted text. The method has been proved much more effective than the previously applied surface approach methods. The advantages of the method are that the real text handling requires much less human and computer sources than clicking aimlessly in the GUI (Graphical User Interface), and the data retrieval is much more effective than from error-prone documents.

Keywords: deep approach metacognitive methods, error-prone birotical documents, financial losses, human and computer resources

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Authors: A. Boursali, A. Guen-Bouazza

Abstract:

We present a simulation of a HEMT (high electron mobility transistor) structure with and without a field plate. We extract the device characteristics through the analysis of DC, AC and high frequency regimes, as shown in this paper. This work demonstrates the optimal device with a gate length of 15 nm, InAlN/GaN heterostructure and field plate structure, making it superior to modern HEMTs when compared with otherwise equivalent devices. This improves the ability to bear the burden of the current density passes in the channel. We have demonstrated an excellent current density, as high as 2.05 A/m, a peak extrinsic transconductance of 0.59S/m at VDS=2 V, and cutting frequency cutoffs of 638 GHz in the first HEMT and 463 GHz for Field plate HEMT., maximum frequency of 1.7 THz, maximum efficiency of 73%, maximum breakdown voltage of 400 V, leakage current density IFuite=1 x 10-26 A, DIBL=33.52 mV/V and an ON/OFF current density ratio higher than 1 x 1010. These values were determined through the simulation by deriving genetic and Monte Carlo algorithms that optimize the design and the future of this technology.

Keywords: HEMT, silvaco, field plate, genetic algorithm, quantum

Procedia PDF Downloads 337