Search results for: discrete breeding swarm

Authors: Behrang Ekrami, Amin Tamadon

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Persian fallow deer (Dama dama mesopotamica) is belonging to the family Cervidae and is only found in a few protected areas in the northwest, north, and southwest of Iran. The aims of this study were analysis of inbreeding and morphometric parameters of semen in male Persian fallow deer to investigate the cause of reduced fertility of this endangered species in Dasht-e-Naz National Refuge, Sari, Iran. The Persian fallow deer semen was collected from four adult bucks randomly during the breeding and non-breeding season from five dehorned and horned deer's BY an artificial vagina. Twelve blood samples was taken from Persian fallow deer and mitochondrial DNA was extracted, amplified, extracted, sequenced, and then were considered for genetic analysis. The Persian fallow deer semen, both with normal and abnormal spermatozoa, is similar to that of domestic ruminants but very smaller and difficult to observe at the primary observation. The post-mating season collected ejaculates contained abnormal spermatozoa, debris and secretion of accessory glands in horned bucks and accessory glands secretion free of any spermatozoa in dehorned or early velvet budding bucks. Microscopic evaluation in all four bucks during the mating season showed the mean concentration of 9×106 spermatozoa/ml. The mean ±SD of age, testes length and testes width was 4.60±1.52 years, 3.58±0.32 and 1.86±0.09 cm, respectively. The results identified 1120 loci (assuming each nucleotide as locus) in which 377 were polymorphic. In conclusion, reduced fertility of male Persian fallow deer may be caused by inbreeding of the protected herd in a limited area of Dasht-e-Naz National Refuge.

Keywords: Persian fallow deer, spermatozoa, reproductive characteristics, morphometric parameters

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Authors: M. M. Islam, S. Sharmin, M. Shah Newaz, N. S. Juyena, M. M. Rahman, P. K. Jha, F. Y. Bari

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The aim of the present study was to select the high quality ram by measuring the scrotal biometry which has an effect on semen parameters. Ten rams were selected in the present study. Eight ejaculates were collected from each ram using artificial vagina method. Scrotal circumference was measured before and after semen collection on weekly basis using the Scrotal tape. Bio-metries of scrotum (scrotal length and scrotal volume) were calculated. Semen was evaluated for macroscopic and microscopic characteristics. The average estimated scrotal circumference (cm) and scrotal volume (cm3) in 8 different age groups were 17.16±0.05 cm and 61.30±0.70 cm3, 17.17±0.62 cm and 63.67±4.49 cm3, 17.22±0.52 cm and 64.90±4.21 cm3, 17.72±0.37 cm and 67.10±4.20 cm3, 18.41±0.35cm and 69.52±4.12cm3, 18.45±0.36cm and 77.17±3.81 cm3, 18.55±0.41 cm and 78.72±4.90 cm3, 19.10±0.30 cm and 87.35±5.45 cm3 respectively. The body weight, scrotal circumference and scrotal volume increased with the progress of age (P < 0.05). Body weight of age group 381-410 days (13.62+1.48 kg) was significantly higher than group 169-200 days (10.17±0.05 kg) and 201-230 days (10.42±1.18 kg) (p < 0.05). Scrotal circumference (SC) of age group 381-410 days (19.10±0.30 cm) was significantly higher (p < 0.05) than other groups. In age group 381-410 days, scrotal volume (SCV) (87.35±5.45 cm3) was significantly higher than other first five groups (p < 0.05). Both scrotal circumference and scrotal volume development was positively correlated with the increasing of body weight (R2= 0.51). Semen volume increased accordingly with the increasing of ages, varied from 0.35±0.00 ml to 1.15+0.26 ml. Semen volume of age group 381-410 days (1.15±0.26 ml) was significantly higher than other age groups (p < 0.05) except age group 351-380 days (p > 0.05). Mass activity of different age groups varied from 2.75 (±0.35) to 4.25 (±0.29) ml in the scale of 1-5. Sperm concentration, progressive motility (%),progressively improved according to the increasing of ages, but significant changes in these parameters were seen when the animals reaches the age 291 days or more (p < 0.05). However, normal spermatozoa (%) improved significantly from the age of 261 days or more. Mass activity (mass) was positively correlated with sperm concentration (R2=0.568) and progressive motility (%) (R2=0.616). The relationships of semen volume with body weight and scrotal measurements and sperm concentration indicate that they are useful in evaluating rams for breeding soundness and genetic improvement for fertility in indigenous ram.

Keywords: breeding soundness, ram, semen quality, scrotal biometry

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Authors: Gail Schofield, Antoine M. Dujon, Nicole Esteban, Rebecca M. Lester, Graeme C. Hays

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Variation in diel movement patterns during migration provides information on the strategies used by animals to maximize energy efficiency and ensure the successful completion of migration. For instance, many flying and land-based terrestrial species stop to rest and refuel at regular intervals along the migratory route, or at transitory ‘stopover’ sites, depending on resource availability. However, in cases where stopping is not possible (such as over–or through deep–open oceans, or over deserts and mountains), non-stop travel is required, with animals needing to develop strategies to rest while actively traveling. Recent advances in biologging technologies have identified mid-flight micro sleeps by swifts in Africa during the 10-month non-breeding period, and the use of lateralized sleep behavior in orca and bottlenose dolphins during migration. Here, highly accurate locations obtained by Argos-linked Fastloc-GPS transmitters of adult green (n=8 turtles, 9487 locations) and loggerhead (n=46 turtles, 47,588 locations) sea turtles migrating around thousand kilometers (over several weeks) from breeding to foraging grounds across the Indian and Mediterranean oceans were used to identify potential resting strategies. Stopovers were only documented for seven turtles, lasting up to 6 days; thus, this strategy was not commonly used, possibly due to the lack of potential ‘shallow’ ( < 100 m seabed depth) sites along routes. However, observations of the day versus night speed of travel indicated that turtles might use other mechanisms to rest. For instance, turtles traveled an average 31% slower at night compared to day during oceanic crossings. Slower travel speeds at night might be explained by turtles swimming in a less direct line at night and/or deeper dives reducing their forward motion, as indicated through studies using Argos-linked transmitters and accelerometers. Furthermore, within the first 24 h of entering waters shallower than 100 m towards the end of migration (the depth at which sea turtles can swim and rest on the seabed), some individuals travelled 72% slower at night, repeating this behavior intermittently (each time for a one-night duration at 3–6-day intervals) until reaching the foraging grounds. If the turtles were, in fact, resting on the seabed at this point, they could be inactive for up to 8-hours, facilitating protracted periods of rest after several weeks of constant swimming. Turtles might not rest every night once within these shallower depths, due to the time constraints of reaching foraging grounds and restoring depleted energetic reserves (as sea turtles are capital breeders, they tend not to feed for several months during migration to and from the breeding grounds and while breeding). In conclusion, access to data-rich, highly accurate Argos-linked Fastloc-GPS provided information about differences in the day versus night activity at different stages of migration, allowing us, for the first time, to compare the strategies used by a marine vertebrate with terrestrial land-based and flying species. However, the question of what resting strategies are used by individuals that remain in oceanic waters to forage, with combinations of highly accurate Argos-linked Fastloc-GPS transmitters and accelerometry or time-depth recorders being required for sufficient numbers of individuals.

Keywords: argos-linked fastloc GPS, data loggers, migration, resting strategy, telemetry

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Authors: Ali Mohammadi Bolban Abad, Fariborz Ahmadi

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Optimization in manufacture is a method to use limited resources to obtain the best performance and reduce waste. In this paper a new algorithm based on eurygaster life is introduced to obtain a plane in which task order and completion time of resources are defined. Evaluation results show our approach has less make span when the resources are allocated with some products in comparison to genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, NP-Hard problems, production scheduling

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Authors: Ersilio Tushaj

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The efficient solution that satisfies the optimal condition is an important issue in the structural engineering design problem. The new codes of structural design consist in design methodology that looks after the exploitation of the total resources of the construction material. In recent years some non-deterministic or meta-heuristic structural optimization algorithms have been developed widely in the research community. These methods search the optimum condition starting from the simulation of a natural phenomenon, such as survival of the fittest, the immune system, swarm intelligence or the cooling process of molten metal through annealing. Among these techniques the most known are: the genetic algorithms, simulated annealing, evolution strategies, particle swarm optimization, tabu search, ant colony optimization, harmony search and big bang crunch optimization. In this study, five of these algorithms are applied for the optimum weight design of a steel truss structure with variable geometry but fixed topology. The design process selects optimum distances and size sections from a set of commercial steel profiles. In the formulation of the design problem are considered deflection limitations, buckling and allowable stress constraints. The approach is repeated starting from different initial populations. The design problem topology is taken from an existing steel structure. The optimization process helps the engineer to achieve good final solutions, avoiding the repetitive evaluation of alternative designs in a time consuming process. The algorithms used for the application, the results of the optimal solutions, the number of iterations and the minimal weight designs, will be reported in the paper. Based on these results, it would be estimated, the amount of the steel that could be saved by applying structural analysis combined with non-deterministic optimization methods.

Keywords: structural optimization, non-deterministic methods, truss structures, steel truss

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Authors: E. Feizi Ashtiani, S. Jamshidi, M.H Niksokhan, A. Feizi Ashtiani

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Waste load allocation (WLA) policies may use multi-objective optimization methods to find the most appropriate and sustainable solutions. These usually intend to simultaneously minimize two criteria, total abatement costs (TC) and environmental violations (EV). If other criteria, such as inequity, need for minimization as well, it requires introducing more binary optimizations through different scenarios. In order to reduce the calculation steps, this study presents value index as an innovative decision making approach. Since the value index contains both the environmental violation and treatment costs, it can be maximized simultaneously with the equity index. It implies that the definition of different scenarios for environmental violations is no longer required. Furthermore, the solution is not necessarily the point with minimized total costs or environmental violations. This idea is testified for Haraz River, in north of Iran. Here, the dissolved oxygen (DO) level of river is simulated by Streeter-Phelps equation in MATLAB software. The WLA is determined for fish farms using multi-objective particle swarm optimization (MOPSO) in two scenarios. At first, the trade-off curves of TC-EV and TC-Inequity are plotted separately as the conventional approach. In the second, the Value-Equity curve is derived. The comparative results show that the solutions are in a similar range of inequity with lower total costs. This is due to the freedom of environmental violation attained in value index. As a result, the conventional approach can well be replaced by the value index particularly for problems optimizing these objectives. This reduces the process to achieve the best solutions and may find better classification for scenario definition. It is also concluded that decision makers are better to focus on value index and weighting its contents to find the most sustainable alternatives based on their requirements.

Keywords: waste load allocation (WLA), value index, multi objective particle swarm optimization (MOPSO), Haraz River, equity

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Authors: Annet Namusoke, Annet Namayanja, Peter Wasswa, Shakirah Nampijja

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Common bean cultivar G2333 which offers broad resistance for anthracnose has been widely used as a source of resistance in breeding for anthracnose resistance. The cultivar is pyramided with three genes namely CO-4, CO-5 and CO-7 and of these three genes, the CO-4 gene has been found to offer the broadest resistance. The main aim of this work was to identify and validate easily assayable PCR based co-dominant molecular markers for selection of the CO-4 gene in segregating populations derived from crosses of G2333 with RWR 1946 and RWR 2075, two commercial Andean cultivars highly susceptible to anthracnose. Marker sequences for the study were obtained by blasting the sequence of the COK-4 gene in the Phaseolus gene database. Primer sequence pairs that were not provided from the Phaseolus gene database were designed by the use of Primer3 software. PCR conditions were optimized and the PCR products were run on 6% HPAGE gel. Results of the polymorphism test indicated that out of 18 identified markers, only two markers namely BM588 and BM211 behaved co-dominantly. Phenotypic evaluation for reaction to anthracnose disease was done by inoculating 21days old seedlings of three parents, F1 and F2 populations with race 7 of Colletotrichum lindemuthianum in the humid chamber. DNA testing of the BM588 marker onto the F2 segregating population of the crosses RWR 1946 x G 2333 and RWR 2075 x G2333 further revealed that the marker BM588 co-segregated with disease resistance with co-dominance of two alleles of 200bp and 400bp, fitting the expected segregation ratio of 1:2:1. The BM588 marker was significantly associated with disease resistance and gave promising results for marker assisted selection of the CO-4 gene in the breeding lines. Activities to validate the BM211 marker are also underway.

Keywords: codominant, Colletotrichum lindemuthianum, MAS, Phaseolus vulgaris

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Authors: Khin Aye Myint, Mohd Rafii Yusop, Mohd Yusoff Abd Samad, Shairul Izan Ramlee, Mohd Din Amiruddin, Zulkifli Yaakub

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The narrow base of genetic is the main obstacle of breeding and genetic improvement in oil palm industry. In order to broaden the genetic bases, the Malaysian Palm Oil Board has been extensively collected wild germplasm from its original area of 11 African countries which are Nigeria, Senegal, Gambia, Guinea, Sierra Leone, Ghana, Cameroon, Zaire, Angola, Madagascar, and Tanzania. The germplasm collections were established and maintained as a field gene bank in Malaysian Palm Oil Board (MPOB) Research Station in Kluang, Johor, Malaysia to conserve a wide range of oil palm genetic resources for genetic improvement of Malaysian oil palm industry. Therefore, assessing the performance and genetic diversity of the wild materials is very important for understanding the genetic structure of natural oil palm population and to explore genetic resources. Principal component analysis (PCA) and Cluster analysis are very efficient multivariate tools in the evaluation of genetic variation of germplasm and have been applied in many crops. In this study, eight populations of MPOB-Senegal oil palm germplasm were studied to explore the genetic variation pattern using PCA and cluster analysis. A total of 20 yield and yield component traits were used to analyze PCA and Ward’s clustering using SAS 9.4 version software. The first four principal components which have eigenvalue >1 accounted for 93% of total variation with the value of 44%, 19%, 18% and 12% respectively for each principal component. PC1 showed highest positive correlation with fresh fruit bunch (0.315), bunch number (0.321), oil yield (0.317), kernel yield (0.326), total economic product (0.324), and total oil (0.324) while PC 2 has the largest positive association with oil to wet mesocarp (0.397) and oil to fruit (0.458). The oil palm population were grouped into four distinct clusters based on 20 evaluated traits, this imply that high genetic variation existed in among the germplasm. Cluster 1 contains two populations which are SEN 12 and SEN 10, while cluster 2 has only one population of SEN 3. Cluster 3 consists of three populations which are SEN 4, SEN 6, and SEN 7 while SEN 2 and SEN 5 were grouped in cluster 4. Cluster 4 showed the highest mean value of fresh fruit bunch, bunch number, oil yield, kernel yield, total economic product, and total oil and Cluster 1 was characterized by high oil to wet mesocarp, and oil to fruit. The desired traits that have the largest positive correlation on extracted PCs could be utilized for the improvement of oil palm breeding program. The populations from different clusters with the highest cluster means could be used for hybridization. The information from this study can be utilized for effective conservation and selection of the MPOB-Senegal oil palm germplasm for the future breeding program.

Keywords: cluster analysis, genetic variability, germplasm, oil palm, principal component analysis

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Authors: Saeed Sayyad Hagh Shomar

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Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using the users’ stated preference in questionnaire models users’ departure time choice affected by congestion pricing schemes in high traffic suburban entrance roads of Tehran. The results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: congestion pricing, departure time, modeling, travel timing, time of the day, transportation planning

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Authors: Leonardo A. Ambrosio, Carlos. H. Silva Santos, Ivan E. L. Rodrigues, Ayumi K. de Campos, Leandro A. Machado

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In this work, we propose an algorithm developed under Python language for the modeling of ordinary scalar Bessel beams and their discrete superpositions and subsequent calculation of optical forces exerted over dielectric spherical particles. The mathematical formalism, based on the generalized Lorenz-Mie theory, is implemented in Python for its large number of free mathematical (as SciPy and NumPy), data visualization (Matplotlib and PyJamas) and multiprocessing libraries. We also propose an approach, provided by a synchronized Software as Service (SaaS) in cloud computing, to develop a user interface embedded on a mobile application, thus providing users with the necessary means to easily introduce desired unknowns and parameters and see the graphical outcomes of the simulations right at their mobile devices. Initially proposed as a free Android-based application, such an App enables data post-processing in cloud-based architectures and visualization of results, figures and numerical tables.

Keywords: Bessel Beams and Frozen Waves, Generalized Lorenz-Mie Theory, Numerical Methods, optical forces

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Authors: S. Saju, G. Thirugnanam

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In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet

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Authors: Jaehyug Lee, Tae-Ho Song

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Vacuum insulation panel (VIP) can achieve very low thermal conductivity by evacuating its inner space. Heat transfer in the core materials of highly-evacuated VIP occurs by conduction through the solid structure and radiation through the pore. The effect of various scattering modes in combined conduction-radiation in VIP is investigated through numerical analysis. The discrete ordinates interpolation method (DOIM) incorporated with the commercial code FLUENT® is employed. It is found that backward scattering is more effective in reducing the total heat transfer while isotropic scattering is almost identical with pure absorbing/emitting case of the same optical thickness. For a purely scattering medium, the results agree well with additive solution with diffusion approximation, while a modified term is added in the effect of optical thickness to backward scattering is employed. For other scattering phase functions, it is also confirmed that backwardly scattering phase function gives a lower effective thermal conductivity. Thus, the materials with backward scattering properties, with radiation shields are desirable to lower the thermal conductivity of VIPs.

Keywords: combined conduction and radiation, discrete ordinates interpolation method, scattering phase function, vacuum insulation panel

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Authors: Amber Jamal, Imran Siddiqui, Syed Tanveer Iqbal

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This review is aimed to shed some light on problems constructing a theory of spacetime and geometry in terms of all quantum degrees of freedom called ‘Quantum Gravity’. Such a theory, which is effective at all scales of distances and energies, describes the enigma of the beginning of the Universe, its possible end, and reducing to general relativity at large distances but in a semi-classical approximation. Furthermore, the theory of quantum gravity also describes the Universe as a whole and provides a description of most fundamental questions that have puzzled scientists for decades, such as: what is space, what is time, and what is the fundamental structure of the Universe, is the spacetime discrete, if it is, where does the continuum of spacetime come from at low energies and macroscopic scales and where does it emerge from its fundamentally discrete building blocks? Quantum Field Theory (QFT) is a framework which describes the microscopic properties and dynamics of the basic building blocks of any condensed matter system. In QFT, atoms are quanta of continuous fields. At smaller scales or higher energies, the continuum description of spacetime fails. Therefore, a new description is required in terms of microscopic constituents (atoms or molecules). The objective of this scientific endeavor is to discuss the above-mentioned problems rigorously and to discuss possible way-out of the problems.

Keywords: QFT, quantum degrees of freedom, quantum gravity, semi-classical approximation

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Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

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Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Olena Grygorieva

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Nowadays mechanisms of thymocytes emigration from the thymus to the periphery are investigated actively. We have proposed a hypothesis of thymocytes’ migration from the thymus through lymphatic vessels during periodical short-term local edema. By morphological, hystochemical methods we have examined quantity of lymphocytes, epitelioreticulocytes, mast cells, blood and lymphatic vessels in morpho-functional areas of rats’ thymuses during the first week after birth in 4 hours interval. In newborn and beginning from 8 hour after birth every 12 hours specific density of the thymus, absolute quantity of microcirculatory vessels, especially of lymphatic ones, lymphcyte-epithelial index, quantity of mast cells and their degranulative forms increase. Structure of extracellular matrix, intrathymical microenvironment and lymphocytes’ adhesive properties change. Absolute quantity of small lymphocytes in thymic cortex changes wavy. All these changes are straightly expressed from 0 till 2, from 12 till 16, from 108 till 120 hours of postnatal life. During this periods paravasal lymphatic vessels are stuffed with lymphocytes, i.e. discrete migration of lymphocytes from the thymus occurs. After rapid edema reduction, quantity of lymphatic vessels decrease, they become empty. Therefore, in the thymus of newborn periodical short-term local edema is observed, on its top discrete migration of lymphocytes from the thymus occurs.

Keywords: lymphocytes, lymphatic vessels, mast cells, thymus

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Paolo Sassi, Jorge Freiria, Gabriel Usera

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In this work, a finite volume fluid flow solver is coupled with a discrete element method module for the simulation of the dynamics of free and elastic bodies in interaction with the fluid and between themselves. The open source fluid flow solver, caffa3d.MBRi, includes the capability to work with nested overlapping grids in order to easily refine the grid in the region where the bodies are moving. To do so, it is necessary to implement a recognition function able to identify the specific mesh block in which the device is moving in. The set of overlapping finer grids might be displaced along with the set of bodies being simulated. The interaction between the bodies and the fluid is computed through a two-way coupling. The velocity field of the fluid is first interpolated to determine the drag force on each object. After solving the objects displacements, subject to the elastic bonding among them, the force is applied back onto the fluid through a Gaussian smoothing considering the cells near the position of each object. The fishnet is represented as lumped masses connected by elastic lines. The internal forces are derived from the elasticity of these lines, and the external forces are due to drag, gravity, buoyancy and the load acting on each element of the system. When solving the ordinary differential equations system, that represents the motion of the elastic and flexible bodies, it was found that the Runge Kutta solver of fourth order is the best tool in terms of performance, but requires a finer grid than the fluid solver to make the system converge, which demands greater computing power. The coupled solver is demonstrated by simulating the interaction between the fluid, an elastic fishnet and a set of free bodies being captured by the net as they are dragged by the fluid. The deformation of the net, as well as the wake produced in the fluid stream are well captured by the method, without requiring the fluid solver mesh to adapt for the evolving geometry. Application of the same strategy to the simulation of elastic structures subject to the action of wind is also possible with the method presented, and one such application is currently under development.

Keywords: computational fluid dynamics, discrete element method, fishnets, nested overlapping grids

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Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

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In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

Procedia PDF Downloads 291

Authors: B. Karabuluter, O. Karaduman

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Traffic management and traffic planning are important issues, especially in big cities. Due to the increase of personal vehicles and the physical constraints of urban roads, the problem of transportation especially in crowded cities over time is revealed. This situation reduces the living standards, and it can put human life at risk because the vehicles such as ambulance, fire department are prevented from reaching their targets. Even if the city planners take these problems into account, emergency planning and traffic management are needed to avoid cases such as traffic congestion, intersections, traffic jams caused by traffic accidents or roadworks. In this study, in smart traffic management issues, proposed solutions using intelligent vehicles acting in cooperation with urban roads are examined. Traffic management is becoming more difficult due to factors such as fatigue, carelessness, sleeplessness, social behavior patterns, and lack of education. However, autonomous vehicles, which remove the problems caused by human weaknesses by providing driving control, are increasing the success of practicing the algorithms developed in city traffic management. Such intelligent vehicles have become an important solution in urban life by using 'swarm intelligence' algorithms and cooperative driving methods to provide traffic flow, prevent traffic accidents, and increase living standards. In this study, studies conducted in this area have been dealt with in terms of traffic jam, intersections, regulation of traffic flow, signaling, prevention of traffic accidents, cooperation and communication techniques of vehicles, fleet management, transportation of emergency vehicles. From these concepts, some taxonomies were made out of the way. This work helps to develop new solutions and algorithms for cities where intelligent vehicles that can perform cooperative driving can take place, and at the same time emphasize the trend in this area.

Keywords: intelligent traffic management, cooperative driving, smart driving, urban road, swarm intelligence, connected vehicles

Procedia PDF Downloads 332

Authors: Ceren Kaya, Okan Erkaymaz, Orhan Ayar, Mahmut Özer

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Diabetes Mellitus (Diabetes) is a disease based on insulin hormone disorders and causes high blood glucose. Clinical findings determine that diabetes can be diagnosed by electrophysiological signals obtained from the vital organs. 'Diabetic Retinopathy' is one of the most common eye diseases resulting on diabetes and it is the leading cause of vision loss due to structural alteration of the retinal layer vessels. In this study, features of horizontal and vertical Video-Oculography (VOG) signals have been used to classify non-proliferative and proliferative diabetic retinopathy disease. Twenty-five features are acquired by using discrete wavelet transform with VOG signals which are taken from 21 subjects. Two models, based on multi-layer perceptron and radial basis function, are recommended in the diagnosis of Diabetic Retinopathy. The proposed models also can detect level of the disease. We show comparative classification performance of the proposed models. Our results show that proposed the RBF model (100%) results in better classification performance than the MLP model (94%).

Keywords: diabetic retinopathy, discrete wavelet transform, multi-layer perceptron, radial basis function, video-oculography (VOG)

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Authors: Maurizio E. Picarella, Ludovica Fumelli, Francesca Siligato, Andrea Mazzucato

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Studies on reproductive dynamics in crops subjected to heat stress are crucial to breed more tolerant cultivars. In tomato, cultivars, breeding lines, and wild species have been thoroughly evaluated for the response to heat stress in several studies. Here, we address the reaction to temperature stress in a panel of selected landraces representing genotypes cultivated before the advent of professional varieties that usually show high adaptation to local environments. We adopted an experimental design with two open field trials, where transplanting was spaced by one month. In the second field, plants were thus subjected to mild stress with natural temperature fluctuations. The genotypes showed wide variation for both vegetative (plant height) and reproductive (stigma exsertion, pollen viability, number of flowers per inflorescence, and fruit set) traits. On average, all traits were affected by heat conditions; except for the number of flowers per inflorescence, the “G*E” interaction was always significant. In agreement with studies based on different materials, estimated broad sense heritability was high for plant height, stigma exsertion, and pollen viability and low for the number of flowers per inflorescence and fruit set. Despite the interaction, traits recorded in control and in heat conditions were positively correlated. The first two principal components estimated by multivariate analysis explained more than 50% of the total variability. The study indicated that landraces present a wide variability for the response of reproductive traits to temperature stress and that such variability could be very informative to dissect the traits with higher heritability and identify new QTL useful for breeding more resilient varieties.

Keywords: fruit set, heat stress, solanum lycopersicum L., style exsertion, tomato

Procedia PDF Downloads 129

Authors: P. L. D. N. M. de Silva, S. G. Edirisinghe, R. Weerasuriya

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High peak-to-average power ratio (PAPR) is a concern of orthogonal frequency division multiplexing (OFDM) based visible light communication (VLC) systems. Discrete Fourier Transform spread (DFT-s) OFDM is an alternative single carrier modulation scheme which would address this concern. Employing channel coding techniques is another mechanism to reduce the PAPR. Previous research has been conducted to study the impact of these techniques separately. However, to the best of the knowledge of the authors, no study has been done so far to identify the improvement which can be harnessed by hybridizing these two techniques for VLC systems. Therefore, this is a novel study area under this research. In addition, channel coding techniques such as Polar codes and Turbo codes have been tested in the VLC domain. However, other efficient techniques such as Hamming coding and Convolutional coding have not been studied too. Therefore, the authors present the impact of the hybrid of DFT-s OFDM and Channel coding (Hamming coding and Convolutional coding) on PAPR in VLC systems using Matlab simulations.

Keywords: convolutional coding, discrete Fourier transform spread orthogonal frequency division multiplexing, hamming coding, peak-to-average power ratio, visible light communications

Procedia PDF Downloads 154

Authors: Saif Ullah

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Survey of avian fauna of Bara Gali Summer Campus, University of Peshawar in the Hazara District was conducted from April to October, 2013. A total of 21 species belonging to 5 orders and 15 families were recorded. Out of these 6 were resident, 12 were summer visitor and 3 were rare. Order Passeriformes was represented by 16 species which are Certhia himalayana, Megalaima virens, Phylloscopus trochiloides, Garrulax lineatus, Passer rutilans, Corvus macrorhynchos, Hypsipetes leucocephalus, Acridotheres tristis, Delichon dasypus cashmeriensis, Hirundo rustica, Muscicapa thalassina, Saxicola ferrea, Myiophoneus caeruleus, Parus melonolophus, Parus rufonuchalis, Parus monticolus, belonging to 11 families. Two species Dendrocopos himalayansis and Picus squamatus belongs to only 1 family of order Piciformes. Only one species from the remaining 3 orders were recorded i.e. Accipiter virgatus belongs to order Accipitriformes, Upupa epops from order Coraciformes, while order Psittaciformes represented by Psittacula himalayana .The distribution and abundance varied with season and maximum number of species was found during the monsoon season when most of the birds migrate for breeding. Some habits and behaviors like nesting, feeding, breeding and vocalizations were also studied which are very unique from other birds. Among bird species adapted to diverse habitat in the field, Himalayan Jungle Crow, Common Mynas, Bulbuls, Barn Swallows, barbets were prominent. Interesting feature of the avian fauna is familiarity with flora was greatly observed. Human related impacts such as grazing by livestock, removal of shrub cover, disturbance of habitat etc. were also studied.

Keywords: birds, summer visitor, Phylloscopus trochiloides, Parus monticolus

Procedia PDF Downloads 306

Authors: Anton James

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This study explored the contribution of parenting styles in the Maternal Perception of Compliance Model (MPCM). This model explores maternal expectations to illustrate the formation of maternal perception of severity of noncompliance in adolescent children. The methodology consisted of three stages: In the first stage, a focus group was held, and the data was analysed to fine-tune the interview schedule. In the second stage, a single interview was held, and the interview schedule was further modified. The third and the final stage consisted of interviewing six mothers who had adolescent children. They were chosen with ‘maximum variation’ approach to represent three tiered socioeconomic statuses, and Asian, white and black ethnicities. The data was thematically analysed in a hybrid fashion: inductive coding and deductive assignment of codes into discrete parenting styles. The study found: a) parenting styles are not always discrete and sometimes it can be mixed. b) The parenting styles are influenced by culture, socioeconomic status, transgenerational knowledge, academic knowledge, observational knowledge, self-reflective knowledge, and parental anxiety. c) The parenting style functioned a mediating mechanism where it attempted to converge discrepancies between parental expectations of compliance with maternal perception of severity of noncompliance. The findings of parenting styles were discussed in relation to MPCM.

Keywords: compliance, expectation, parenting styles, perception

Procedia PDF Downloads 781

Authors: Sally Ibrahim, Mohamed Hedia, Mohamed Taqi, Mohamed Derbala, Karima Mahmoud, Youssef Ahmed, Sayed Ismail, Mohamed El-Belely

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The identification and quantification of serum microRNA (miRNA) from mares with endometritis might serve as useful and implementable clinical biomarkers for the early diagnosis of endometiritis. Aims of the current study were (I) to study the expression pattern of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205, and (II) to determine the levels of interleukin 6 (IL-6), prostaglandins (PGF₂α and PGE₂), in the serum of Arabian mares with healthy and abnormal uterine status (endometritis). This study was conducted on 80 Arabian mares (4-14 years old). Mares were divided into 48 sub-fertile mares suspected of endometritis and 32 fertile at stud farms. The criteria for mares to be enrolled in the endometritis group were that they had been bred three or more times unsuccessfully in the breeding season or had a history of more than one year of reproductive failure. In addition, two or more of the following criteria on a checklist were present: abnormal clinical findings, transrectal ultrasonographic uterine examination showed abnormal fluid in the uterus (echogenic or ≥2 cm in diameter), positive endometrial cytology; and bacterial and/or fungal growth. Serum samples were collected for measuring IL-6, PGF₂α, and PGE₂ concentrations, as well as serum miRNA isolation and quantitative real-time PCR. Serum concentrations of IL-6, PGE₂, and PGF₂α were higher (P ≤ 0.001) in mares with endometritis compared to the control healthy ones. The expression profile of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205 increased (P≤0.001) in mares with endometritis compared to the control ones. To the best of our knowledge, this is the first study that revealed that serum miRNA and serum inflammatory mediators (IL-6, PGE₂, and PGF₂α) could be used as non-invasive gold standard biomarkers, and therefore might be served as an important additional diagnostic tool for endometritis in Arabian mares. Moreover, estimation of the serum concentrations of serum miRNA, IL-6, PGE₂, and PGF₂α is a promising recommended tool during the breeding soundness examination in mares.

Keywords: Arabian Mares, endometritis, inflammatory mediators, serum miRNA

Procedia PDF Downloads 180

Authors: Hesham A. Khalek, Shafik S. Khoury, Remon F. Aziz, Mohamed A. Hakam

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Slipforming operation’s linearity is a source of planning complications, and operation is usually subjected to bottlenecks at any point, so careful planning is required in order to achieve success. On the other hand, Discrete-event simulation concepts can be applied to simulate and analyze construction operations and to efficiently support construction scheduling. Nevertheless, preparation of input data for construction simulation is very challenging, time-consuming and human prone-error source. Therefore, to enhance the benefits of using DES in construction scheduling, this study proposes an integrated module to establish a framework for automating the generation of time schedules and decision support for Slipform construction projects, particularly through the project feasibility study phase by using data exchange between project data stored in an Intermediate database, DES and Scheduling software. Using the stored information, proposed system creates construction tasks attribute [e.g. activities durations, material quantities and resources amount], then DES uses all the given information to create a proposal for the construction schedule automatically. This research is considered a demonstration of a flexible Slipform project modeling, rapid scenario-based planning and schedule generation approach that may be of interest to both practitioners and researchers.

Keywords: discrete-event simulation, modeling, construction planning, data exchange, scheduling generation, EZstrobe

Procedia PDF Downloads 376

Authors: Kushaal Selvarajah, Geetha Annavi, Mohd Noor Hisham Mohd Nadzir

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Sambar deer (Rusa unicolor) was uplisted from Least Concern to Vulnerable by the International Union for Conservation of Nature Red list in 2015 due to drastic population decline in the wild throughout its geographical range. Sambar deer is a valued prey for the highly endangered species such as the Malayan tiger. Ex-situ conservation efforts, i.e., captive breeding, initiated by local government to boost sambar deer numbers in captivity and to reintroduce into the wild to support a higher number of tigers, consistent with the goal of our National Tiger Conservation Action Plan. The reproductive success of sambar deer and their welfare management practices in captivity are important components for effective captive breeding programs. However, there is a lack of study carried out on sambar deer in recent years and their behavior in captivity. Three captive sites (Zoo Negara, Zoo Taiping, and Sungkai Conservation Centre) were selected and observed for an average of 40 days each site (6 hours/day). A Generalized Linear Model (GLM) was used to determine the correlation between social behavior and extrinsic parameters. A comparison between all three captive sites showed the strongest correlation in behavioral variability, followed by a time of observation. This proves that there is a difference between in behavioral consistency and frequency between herds across captive sites rising to the possibility of external factors that are influential. Time of day of observation also had significant influence on certain extrinsic parameters being skewed to morning observations and this could be due to an adaptive behavior to the feeding time in the captive sites being in the morning which caused the deer to be resting towards the afternoon. Extensive study need to be done on sambar deer to pinpoint the specifics and better understanding of these possible influential factors in their behavior.

Keywords: behaviour ecology, captivity, ex-situ conservation, husbandry

Procedia PDF Downloads 158

Authors: James Adewale, Joshua Sunday

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In this paper, we developed a linear multistep method, which is implemented in predictor corrector-method. The corrector is developed by method of collocation and interpretation of power series approximate solutions at some selected grid points, to give a continuous linear multistep method, which is evaluated at some selected grid points to give a discrete linear multistep method. The predictors were also developed by method of collocation and interpolation of power series approximate solution, to give a continuous linear multistep method. The continuous linear multistep method is then solved for the independent solution to give a continuous block formula, which is evaluated at some selected grid point to give discrete block method. Basic properties of the corrector were investigated and found to be zero stable, consistent and convergent. The efficiency of the method was tested on some linear, non-learn, oscillatory and stiff problems of first order, initial value problems of ordinary differential equations. The results were found to be better in terms of computer time and error bound when compared with the existing methods.

Keywords: predictor, corrector, collocation, interpolation, approximate solution, independent solution, zero stable, consistent, convergent

Procedia PDF Downloads 501