Search results for: random differential inclusion

Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

Procedia PDF Downloads 175

Authors: Maria Amodeo, Pasquale Arpaia, Marco Buzio, Vincenzo Di Capua, Francesco Donnarumma

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Different deep neural network architectures have been compared and tested to predict magnetic hysteresis in the context of pulsed electromagnets for experimental physics applications. Modelling quasi-static or dynamic major and especially minor hysteresis loops is one of the most challenging topics for computational magnetism. Recent attempts at mathematical prediction in this context using Preisach models could not attain better than percent-level accuracy. Hence, this work explores neural network approaches and shows that the architecture that best fits the measured magnetic field behaviour, including the effects of hysteresis and eddy currents, is the nonlinear autoregressive exogenous neural network (NARX) model. This architecture aims to achieve a relative RMSE of the order of a few 100 ppm for complex magnetic field cycling, including arbitrary sequences of pseudo-random high field and low field cycles. The NARX-based architecture is compared with the state-of-the-art, showing better performance than the classical operator-based and differential models, and is tested on a reference quadrupole magnetic lens used for CERN particle beams, chosen as a case study. The training and test datasets are a representative example of real-world magnet operation; this makes the good result obtained very promising for future applications in this context.

Keywords: deep neural network, magnetic modelling, measurement and empirical software engineering, NARX

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Authors: Noufe H. Aljahdaly

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The Laplace homotopy perturbation method (LHPM) is an approximate method that help to compute the approximate solution for partial differential equations. The method has been used for solving several problems in science. It requires the initial condition, so it solves the initial value problem. In physics, when some important terms are taken in account, we may obtain non-integrable partial differential equations that do not have analytical integrals. This type of PDEs do not have exact solution, therefore, we need to compute the solution without initial condition. In this work, we improved the LHPM to be able to solve non-integrable problem, especially the damped PDEs, which are the PDEs that include a damping term which makes the PDEs non-integrable. We improved the LHPM by setting a perturbation parameter and an embedding parameter as the damping parameter and using the initial condition for damped PDE as the initial condition for non-damped PDE.

Keywords: non-integrable PDEs, modified Kawahara equation;, laplace homotopy perturbation method, damping term

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Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.

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In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means

Procedia PDF Downloads 558

Authors: F. A. Hassona, M. D. Hashem, R. I. Melek, B. M. Hakeem

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A differential settlement at the end of a bridge near the interface between the abutment and the embankment is a persistent problem for highway agencies. The differential settlement produces the common ‘bump at the end of the bridge’. Reduction in steering response, distraction to the driver, added risk and expense to maintenance operation, and reduction in a transportation agency’s public image are all undesirable effects of these uneven and irregular transitions. This paper attempts to simulate the bump at the end of the bridge using PLAXIS finite element 2D program. PLAXIS was used to simulate a laboratory model called Bridge to Embankment Simulator of Transition (B.E.S.T.) device which was built by others to investigate this problem. A total of six numerical simulations were conducted using hardening- soil model with rational assumptions of missing soil parameters to estimate the bump at the end of the bridge. The results show good agreements between the numerical and the laboratory models. Important factors influencing bumps at bridge ends were also addressed in light of the model results.

Keywords: bridge approach slabs, bridge bump, hardening-soil, PLAXIS 2D, settlement

Procedia PDF Downloads 348

Authors: Dong-Cheol Jeong, Jookyung Lee, Yu Hyeon Ro, Changsik Song

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The design and synthesis of photo-active polymeric systems are important in regard to solar energy harvesting and utilization. In this study, we synthesized photo-active polymer, thin films, and polymer gel via iterative self-assembly using reversible metal-terpyridine (M-tpy) interactions. The photocurrent generated in the polymeric thin films with Zn(II) was much higher than those of other films. Apparent diffusion rate constant (kapp) was measured for the electron hopping process via potential-step chronoamperometry. As a result, the kapp for the polymeric thin films with Zn(II) was almost two times larger than those with other metal ions. We found that the anodic photocurrents increased with the inclusion of the multi-walled carbon nanotube (MWNT) layer. Inclusion of MWNTs can provide efficient electron transfer pathways. In addition, polymer gel based on interactions between terpyridine and metal ions was shown the photocatalytic activity. Interestingly, in the Mg-terpyridine gel, the reaction rate of benzylamine to imine photo-oxidative coupling was faster than Fe-terpyridine gel because the Mg-terpyridine gel has two steps electron transfer pathway but Fe-terpyridine gel has three steps electron transfer pathway.

Keywords: terpyridine, photocatalyst, self-assebly, metal-ligand

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Authors: Shahul Hamid Khan, S. Santhosh, Abhinav Kumar Sharma

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Environmental performance along with social performance is becoming vital factors for industries to achieve global standards. With a good environmental policy global industries are differentiating them from their competitors. This paper concentrates on multi stage, multi product and multi period manufacturing network. Bi-objective mathematical models for total cost and total emission for the entire forward supply chain are considered. Here five different problems are considered by varying the number of suppliers, manufacturers, and environmental levels, for illustrating the taken mathematical model. GA, and Random search are used for finding the optimal solution. The input parameters of the optimal solution are used to find the tradeoff between the initial investment by the industry and the long term benefit of the environment.

Keywords: closed loop supply chain, genetic algorithm, random search, green supply chain

Procedia PDF Downloads 549

Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

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The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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Authors: Muhammet Baldan, Emel Timuçin

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Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.

Keywords: random forest, machine learning, comparison, feature extraction

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Authors: Laura Salvia Diaz Silvarrey, Anh Phan

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Municipal Plastic Waste (MPW) comprises a mixture of thermoplastics such as high and low density polyethylene (HDPE and LDPE), polypropylene (PP), polystyrene (PS) and polyethylene terephthalate (PET). Recycling rate of these plastics is low, e.g. only 27% in 2013. The remains were incinerated or disposed in landfills. As MPW generation increases approximately 5% per annum, MPW management technologies have to be developed to comply with legislation . Pyrolysis, thermochemical decomposition, provides an excellent alternative to convert MPW into valuable resources like fuels and chemicals. Most studies on waste plastic kinetics only focused on HDPE and LDPE with a simple assumption of first order decomposition, which is not the real reaction mechanism. The aim of this study was to develop a kinetic study for each of the polymers in the MPW mixture using thermogravimetric analysis (TGA) over a range of heating rates (5, 10, 20 and 40°C/min) in N2 atmosphere and sample size of 1 – 4mm. A model-free kinetic method was applied to quantify the activation energy at each level of conversion. Kissinger–Akahira–Sunose (KAS) and Flynn–Wall–Ozawa (FWO) equations jointly with Master Plots confirmed that the activation energy was not constant along all the reaction for all the five plastic studied, showing that MPW decomposed through a complex mechanism and not by first-order kinetics. Master plots confirmed that MPW decomposed following a random scission mechanism at conversions above 40%. According to the random scission mechanism, different radicals are formed along the backbone producing the cleavage of bonds by chain scission into molecules of different lengths. The cleavage of bonds during random scission follows first-order kinetics and it is related with the conversion. When a bond is broken one part of the initial molecule becomes an unsaturated one and the other a terminal free radical. The latter can react with hydrogen from and adjacent carbon releasing another free radical and a saturated molecule or reacting with another free radical and forming an alkane. Not every time a bonds is broken a molecule is evaporated. At early stages of the reaction (conversion and temperature below 40% and 300°C), most products are not short enough to evaporate. Only at higher degrees of conversion most of cleavage of bonds releases molecules small enough to evaporate.

Keywords: kinetic, municipal plastic waste, pyrolysis, random scission

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Authors: Bukunola K. Oguntade, Gareth M. Watkins

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The synthesis and characterization of metal-organic frameworks (MOFs) is an area of coordination chemistry which has grown rapidly in recent years. Worldwide there has been growing concerns about future energy supplies, and its environmental impacts. A good number of MOFs have been tested for the adsorption of small molecules in the vapour phase. An important issue for potential applications of MOFs for gas adsorption and storage materials is the stability of their structure upon sorption. Therefore, study on the thermal stability of MOFs upon adsorption is important. The incorporation of two or more transition metals in a coordination polymer is a current challenge for designed synthesis. This work focused on the synthesis, characterization and small molecule adsorption properties of three microporous (one zinc monometal and two bimetallics) complexes involving Cu(II), Zn(II) and 1,2,4,5-benzenetetracarboxylic acid using the ambient precipitation and solvothermal method. The complexes were characterized by elemental analysis, Infrared spectroscopy, Scanning Electron microscopy, Thermogravimetry analysis and X-ray Powder diffraction. The N2-adsorption Isotherm showed the complexes to be of TYPE III in reference to IUPAC classification, with very small pores only capable for small molecule sorption. All the synthesized compounds were observed to contain water as guest. Investigations of their inclusion properties for small molecules in the vapour phase showed water and methanol as the only possible inclusion candidates with 10.25H2O in the monometal complex [Zn4(H2B4C)2.5(OH)3(H2O)]·10H2O but not reusable after a complete structural collapse. The ambient precipitation bimetallic; [(CuZnB4C(H2O)2]·5H2O, was found to be reusable and recoverable from structure collapse after adsorption of 5.75H2O. In addition, Solvo-[CuZnB4C(H2O)2.5]·2H2O obtained from solvothermal method show two cycles of rehydration with 1.75H2O and 0.75MeOH inclusion while structure remains unaltered upon dehydration and adsorption.

Keywords: adsorption, characterization, copper, metal -organic frameworks, zinc

Procedia PDF Downloads 133

Authors: Amey Kulkarni, Paavan Shetty, Amol Patil, B. Rajiv

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Fuel Efficiency plays a very important role in overall performance of an automobile. In this paper study of fuel efficiency of heavy construction, compaction machine is done. The fuel Consumption trials are performed in order to obtain the consumption of fuel in performing certain set of actions by the compactor. Usually, Heavy Construction machines are put to work in locations where refilling the fuel tank is not an easy task and also the fuel is consumed at a greater rate than a passenger automobile. So it becomes important to have a fuel efficient machine for long working hours. The fuel efficiency is the most important point in determining the future scope of the product. A heavy construction compaction machine operates in five major roles. These five roles are traveling, Static working, High-frequency Low amplitude compaction, Low-frequency High amplitude compaction, low idle. Fuel consumption readings for 1950 rpm, 2000 rpm & 2350 rpm of the engine are taken by using differential fuel flow meter and are analyzed. And the optimum RPM setting which fulfills the fuel efficiency, as well as engine performance criteria, is considered. Also, other factors such as rear end gears, Intake and exhaust restriction for an engine, vehicle operating techniques, air drag, Tribological aspects, Tires are considered for increasing the fuel efficiency of the compactor. The fuel efficiency of compactor can be precisely calculated by using Differential Fuel Flow Meter. By testing the compactor at different combinations of Engine RPM and also considering other factors such as rear end gears, Intake and exhaust restriction of an engine, vehicle operating techniques, air drag, Tribological aspects, The optimum solution was obtained which lead to significant improvement in fuel efficiency of the compactor.

Keywords: differential fuel flow meter, engine RPM, fuel efficiency, heavy construction compaction machine

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Authors: Seyfullah Madakbas, Hatice Birtane, Memet Vezir Kahraman

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In this study, we aimed to synthesize and characterize polyhedral oligomeric silsesquioxanes containing polyimide nanocomposite. Polyimide nanocomposites widely have been used in membranes in fuel cell, solar cell, gas filtration, sensors, aerospace components, printed circuit boards. Firstly, polyamic acid was synthesized and characterized by Fourier Transform Infrared. Then, polyhedral oligomeric silsesquioxanes containing polyimide nanocomposite was prepared with thermal imidization method. The obtained polyimide nanocomposite was characterized by Fourier Transform Infrared, Scanning Electron Microscope, Thermal Gravimetric Analysis and Differential Scanning Calorimetry. Thermal stability of polyimide nanocomposite was evaluated by thermal gravimetric analysis and differential scanning calorimetry. Surface morphology of composite samples was investigated by scanning electron microscope. The obtained results prove that successfully prepared polyhedral oligomeric silsesquioxanes are containing polyimide nanocomposite. The obtained nanocomposite can be used in many industries such as electronics, automotive, aerospace, etc.

Keywords: polyimide, nanocomposite, polyhedral oligomeric silsesquioxanes

Procedia PDF Downloads 178

Authors: Norazuwin Najihah Mat Tahir, Fuziyah Ishak, Seripah Awang Kechil

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The onset of the convective instability in the horizontal through flow of a power-law nanofluid saturated by porous layer heated from below under the influences of magnetic field are investigated in this study. The linear stability theory is used for the transformation of the partial differential equations to system of ordinary differential equations through infinitesimal perturbations, scaling, linearization and method of normal modes with two-dimensional periodic waves. The system is solved analytically for the closed form solution of the Rayleigh number by using the Galerkin-type weighted residuals method to investigate the onset of both traveling wave and oscillatory convection. The effects of the power-law index, Lewis number and Peclet number on the stability of the system were investigated. The Lewis number stabilizes while the power-law index and Peclet number destabilize the nanofluid system. The system in the presence of magnetic field is more stable than the system in the absence of magnetic field.

Keywords: convection, instability, magnetic field, nanofluid, power-law

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Authors: Marcel Meinhardt, Manfred Keuser, Thomas Braml

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Cracking of reinforced concrete is a complex phenomenon induced by direct loads or restraints affecting reinforced concrete structures as soon as the tensile strength of the concrete is exceeded. Hence it is important to predict where cracks will be located and how they will propagate. The bond theory and the crack formulas in the actual design codes, for example, DIN EN 1992-1-1, are all based on the assumption that the reinforcement bars are embedded in homogeneous concrete without taking into account the influence of transverse reinforcement and the real stress situation. However, it can often be observed that real structures such as walls, slabs or beams show a crack spacing that is orientated to the transverse reinforcement bars or to the stirrups. In most Finite Element Analysis studies, the smeared crack approach is used for crack prediction. The disadvantage of this model is that the typical strain localization of a crack on element level can’t be seen. The crack propagation in concrete is a discontinuous process characterized by different factors such as the initial random distribution of defects or the scatter of material properties. Such behavior presupposes the elaboration of adequate models and methods of simulation because traditional mechanical approaches deal mainly with average material parameters. This paper concerned with the modelling of the initiation and the propagation of cracks in reinforced concrete structures considering the influence of transverse reinforcement and the real stress distribution in reinforced concrete (R/C) beams/plates in bending action. Therefore, a parameter study was carried out to investigate: (I) the influence of the transversal reinforcement to the stress distribution in concrete in bending mode and (II) the crack initiation in dependence of the diameter and distance of the transversal reinforcement to each other. The numerical investigations on the crack initiation and propagation were carried out with a 2D reinforced concrete structure subjected to quasi static loading and given boundary conditions. To model the uncertainty in the tensile strength of concrete in the Finite Element Analysis correlated normally and lognormally distributed random filed with different correlation lengths were generated. The paper also presents and discuss different methods to generate random fields, e.g. the Covariance Matrix Decomposition Method. For all computations, a plastic constitutive law with softening was used to model the crack initiation and the damage of the concrete in tension. It was found that the distributions of crack spacing and crack widths are highly dependent of the used random field. These distributions are validated to experimental studies on R/C panels which were carried out at the Laboratory for Structural Engineering at the University of the German Armed Forces in Munich. Also, a recommendation for parameters of the random field for realistic modelling the uncertainty of the tensile strength is given. The aim of this research was to show a method in which the localization of strains and cracks as well as the influence of transverse reinforcement on the crack initiation and propagation in Finite Element Analysis can be seen.

Keywords: crack initiation, crack modelling, crack propagation, cracks, numerical simulation, random fields, reinforced concrete, stochastic

Procedia PDF Downloads 157

Authors: M. Seguini, D. Nedjar

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An accuracy nonlinear analysis of a deep beam resting on elastic perfectly plastic soil is carried out in this study. In fact, a nonlinear finite element modeling for large deflection and moderate rotation of Euler-Bernoulli beam resting on linear and nonlinear random soil is investigated. The geometric nonlinear analysis of the beam is based on the theory of von Kàrmàn, where the Newton-Raphson incremental iteration method is implemented in a Matlab code to solve the nonlinear equation of the soil-beam interaction system. However, two analyses (deterministic and probabilistic) are proposed to verify the accuracy and the efficiency of the proposed model where the theory of the local average based on the Monte Carlo approach is used to analyze the effect of the spatial variability of the soil properties on the nonlinear beam response. The effect of six main parameters are investigated: the external load, the length of a beam, the coefficient of subgrade reaction of the soil, the Young’s modulus of the beam, the coefficient of variation and the correlation length of the soil’s coefficient of subgrade reaction. A comparison between the beam resting on linear and nonlinear soil models is presented for different beam’s length and external load. Numerical results have been obtained for the combination of the geometric nonlinearity of beam and material nonlinearity of random soil. This comparison highlighted the need of including the material nonlinearity and spatial variability of the soil in the geometric nonlinear analysis, when the beam undergoes large deflections.

Keywords: finite element method, geometric nonlinearity, material nonlinearity, soil-structure interaction, spatial variability

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Authors: Wen-Lih Chen, Chao-Kuang Chen, Mao-Ju Fang, Hsiang-Cheng Hsu

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In this study, we conducted CFD simulation to study the gas cycle of a medium-temperature-differential (MTD) γ-type Stirling engine. Mesh compression and expansion as well as overset mesh techniques are employed to simulate the moving parts of the engine. Shear-Stress Transport (SST) k-ω turbulence model has been adopted because the model is not prone to generate excessive turbulence upon impingement regions. Hence, wall heat transfer rates at the hot and cold ends will not be overestimated. The effects of several different displacer-cylinder-wall temperature setups, including smooth and finned walls, on engine performance are investigated. The results include temperature contours, pressure versus volume diagrams, and variations of heat transfer rates, indicated power, and efficiency. It is found that displacer-wall heat transfer is one of the most important factors on engine performance, and some wall-temperature setups produce better results than others.

Keywords: CFD, finned wall, MTD Stirling engine, heat transfer

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Authors: Kailash C. Madan

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We study four models of a three server queueing system with Bernoulli schedule optional server vacations. Customers arriving at the system one by one in a Poisson process are provided identical exponential service by three parallel servers according to a first-come, first served queue discipline. In model A, all three servers may be allowed a vacation at one time, in Model B at the most two of the three servers may be allowed a vacation at one time, in model C at the most one server is allowed a vacation, and in model D no server is allowed a vacation. We study steady the state behavior of the four models and obtain steady state probability generating functions for the queue size at a random point of time for all states of the system. In model D, a known result for a three server queueing system without server vacations is derived.

Keywords: a three server queue, Bernoulli schedule server vacations, queue size distribution at a random epoch, steady state

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Authors: Boadi Agyekum

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In this study, a social location perspective is used to explore the challenges of creating opportunities that will foster lifelong education, inclusion, and equity for residents of rural communities in Ghana. The differentiated experiences of rural adults are under-researched and often unacknowledged in lifelong education literature and distance education policy. There is a need to examine carefully the structural inequalities that create disadvantages for residents of rural communities and women in pursuing distance education in designated cities in Ghana. The paper uses in-depth interviews to explore participants’ experiences of learning at a distance and to scrutinise the narratives of lifelong education. The paper reflects on the implications of the framework employed for educators and social justice in lifelong education. It further recommends the need to provide IT laboratories and fully online programs that would require stable and regular internet and access to ICT equipment for potential learning in rural communities. The social location approach presented a number of axes of diversity as comparatively more important than others; these included gender, age, education, work commitment, geography, and degree of social connectedness. This can inform lifelong education policy and programs to sustain quality education.

Keywords: equity, distance education, lifelong learning, social location, intersectionality, rural communities

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Authors: Fouzi Aboura

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The fractional order proportional-integral-derivative (FOPID) controller or fractional order (PIλDµ) is a proportional-integral-derivative (PID) controller where integral order (λ) and derivative order (µ) are fractional, one of the important application of classical PID is the Automatic Voltage Regulator (AVR).The FOPID controller needs five parameters optimization while the design of conventional PID controller needs only three parameters to be optimized. In our paper we have proposed a comparison between algorithms Differential Evolution (DE) and Hybrid Genetic Algorithm Particle Swarm Optimization (HGAPSO) ,we have studied theirs characteristics and performance analysis to find an optimum parameters of the FOPID controller, a new objective function is also proposed to take into account the relation between the performance criteria’s.

Keywords: FOPID controller, fractional order, AVR system, objective function, optimization, GA, PSO, HGAPSO

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Authors: Anit S. Malhotra, Ajay Duseja, Neelam Chadha

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Endothelial dysfunction is a precursor to atherosclerosis, and flow-mediated dilatation (FMD) in the brachial artery is the commonest method to evaluate endothelial function in humans. Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver disorders encountered in clinical practice. An earlier meta-analysis had quantitatively assessed the degree of endothelial dysfunction using FMD. However, the largest study investigating the relation of FMD with NAFLD was published after that meta-analysis. In addition, that meta-analysis did not include some studies, including one from our centre. Therefore, an updating the previous meta-analysis was considered important. We searched PubMed, Cochrane Library, Embase, Scopus, SCI, Google Scholar, conference proceedings, and references of included studies till June 2017 to identify observational studies evaluating endothelial function using FMD in patients with non-alcoholic fatty liver disease. Data was analyzed using MedCalc. Fourteen studies were found eligible for inclusion in the meta-analysis. Patients with NAFLD had lower brachial artery FMD as compared to controls, standardized mean difference (random effects model) being –1.279%; 95% confidence interval (CI), –1.478 to –0.914. The effect size became smaller after addition of the recent study with the largest sample size was included compared with the earlier meta-analysis. In conclusion, patients with NAFLD had low FMD values indicating that they are at a higher risk of cardiovascular disease although our results suggest the effect size is not as large as reported previously.

Keywords: endothelial dysfunction, flow-mediated dilatation, meta-analysis, non-alcoholic fatty liver disease

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Authors: Nisha Sharma, Mili Kaur, Ashutosh Halder, Seema Kaushal, Manoj Kumar, Manish Jain

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Purpose: To investigate microRNAs (miRNA) as an epigenomic etiological factor in idiopathic non-obstructive azoospermia (NOA). In order to achieve the same, an association was seen between occupational exposure to radiation, thermal, and chemical factors and idiopathic cases of non-obstructive azoospermia, and later, testicular differential miRNA expression profiling was done in exposure group NOA cases. Method: It is a prospective study in which 200 apparent idiopathic male factor infertility cases, who have been advised to undergo testicular fine needle aspiration (FNA) evaluation, are recruited. A detailed occupational history was taken to understand the possible type of exposure due to the nature and duration of work. A total of 26 patients were excluded upon XY-FISH and Yq microdeletion tests due to the presence of genetic causes of infertility, 6 hypospermatogeneis (HS), six Sertoli cell-only syndrome (SCOS), and six normospermatogeneis patients testicular FNA samples were used for RNA isolation followed by small RNA sequencing and nCounter miRNA expression analysis. Differential miRNA expression profile of HS and SCOS patients was done. A web-based tool, miRNet, was used to predict the interacting compounds or chemicals using the shortlisted miRNAs with high fold change. The major limitation encountered in this study was the insufficient quantity of testicular FNA sample used for total RNA isolation, which resulted in a low yield and RNA integrity number (RIN) value. Therefore, the number of RNA samples admissible for differential miRNA expression analysis was very small in comparison to the total number of patients recruited. Results: Differential expression analysis revealed 69 down-regulated and 40 up-regulated miRNAs in HS and 66 down-regulated and 33 up-regulated miRNAs in SCOS in comparison to normospermatogenesis controls. The miRNA interaction analysis using the miRNet tool showed that the differential expression profiles of HS and SCOS patients were associated with arsenic trioxide, bisphenol-A, calcium sulphate, lithium, and cadmium. These compounds are reproductive toxins and might be responsible for miRNA-mediated epigenetic deregulation leading to NOA. The association between occupational risk factor exposure and the non-exposure group of NOA patients was not statistically significant, with ꭓ2 (3, N= 178) = 6.70, p= 0.082. The association between individual exposure groups (radiation, thermal, and chemical) and various sub-types of NOA is also not significant, with ꭓ2 (9, N= 178) = 15.06, p= 0.089. Functional analysis of HS and SCOS patients' miRNA profiles revealed some important miR-family members in terms of male fertility. The miR-181 family plays a role in the differentiation of spermatogonia and spermatocytes, as well as the transcriptional regulation of haploid germ cells. The miR-34 family is expressed in spermatocytes and round spermatids and is involved in the regulation of SSCs differentiation. Conclusion: The reproductive toxins might adopt the miRNA-mediated mechanism of disease development in idiopathic cases of NOA. Chemical compound induced; miRNA-mediated epigenetic deregulation can give a future perspective on the etiopathogenesis of the disease.

Keywords: microRNA, non-obstructive azoospermia (NOA), occupational exposure, hypospermatogenesis (HS), Sertoli cell only syndrome (SCOS)

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Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

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Authors: Tasawar Hayat, Madiha Rashid, Maria Imtiaz, Ahmed Alsaedi

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This problem is about the study of flow of viscous fluid due to rotating disk in nanofluid. Effects of magnetic field, slip boundary conditions and thermal radiations are encountered. An incompressible fluid soaked the porous medium. In this model, nanoparticles of Cu is considered with water as the base fluid. For Copper-water nanofluid, graphical results are presented to describe the influences of nanoparticles volume fraction (φ) on velocity and temperature fields for the slip boundary conditions. The governing differential equations are transformed to a system of nonlinear ordinary differential equations by suitable transformations. Convergent solution of the nonlinear system is developed. The obtained results are analyzed through graphical illustrations for different parameters. Moreover, the features of the flow and heat transfer characteristics are analyzed. It is found that the skin friction coefficient and heat transfer rate at the surface are highest in copper-water nanofluid.

Keywords: MHD nanofluid, porous medium, rotating disk, slip effect

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Authors: Omid Azimaraghi, Noushin Khazaei

Abstract:

Background: Fluid therapy is an important aspect of the perioperative period and a major challenge for anesthesiologists. To authors best knowledge, there is a lack of strong guidance and evidence regarding the optimal approach to fluid therapy. Therefore a variety of medical devices have been introduced to help physicians. In this study, we aimed to evaluate the effectiveness of pleth variability index in guiding fluid therapy in different patient positions. Materials and Methods: Inclusion criteria consisted of patients aged 18-50 years old and classified as American Society of Anesthesiologists physical status I and II, who were candidates for elective thyroidectomy surgery. In total, 36 patients meeting the inclusion criteria were enrolled in the study. After induction of anesthesia and start of mechanical ventilation Pleth variability index was measured in the supine position, then patients were placed in Trendelenburg and reverse Trendelenburg position (30 degrees, 5 minutes); Pleth Variability Index has measured again in the mentioned positions. Results: Mean PVI (Pleth Variability Index) in the supine position was 14.3 ± 3.7 in comparison to 21.5 ± 4.3 in the reverse Trendelenburg position. The mean PVI in Trendelenburg position was 9.1 ± 2.0 in Trendelenburg position (p < 0.05). Conclusion: In conclusion, we found that Pleth Variability Index varies with patient position and this should be taken into account when using this index during fluid therapy.

Keywords: fluid therapy, Pleth Variability Index, position, surgery

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Authors: Eugene Stepanov, Arkadi Ponossov

Abstract:

Many mathematical models used in biological and other applications are ill-posed. The reason for that is the nature of differential equations, where the nonlinearities are assumed to be step functions, which is done to simplify the analysis. Prominent examples are switched systems arising from gene regulatory networks and neural field equations. This simplification leads, however, to theoretical and numerical complications. In the presentation, it is proposed to apply the theory of hybrid feedback controls to regularize the problem. Roughly speaking, one attaches a finite state control (‘automaton’), which follows the trajectories of the original system and governs its dynamics at the points of ill-posedness. The construction of the automaton is based on the classification of the attractors of the specially designed adjoint dynamical system. This ‘hybridization’ is shown to regularize the original switched system and gives rise to efficient hybrid numerical schemes. Several examples are provided in the presentation, which supports the suggested analysis. The method can be of interest in other applied fields, where differential equations contain step-like nonlinearities.

Keywords: hybrid feedback control, ill-posed problems, singular perturbation analysis, step-like nonlinearities

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Authors: Rovina Kobun, Shafiquzzaman Siddiquee

Abstract:

A novel and simple electrochemical sensor for the determination of melamine was developed based on modified gold electrode (AuE) with chitosan (CHIT) nanocomposite membrane, zinc oxide nanoparticles (ZnONPs) and ionic liquids ([EMIM][Otf]) to enhance the potential current response of melamine. Cyclic voltammetry and differential pulse voltammetry were used to investigate the electrochemical behaviour between melamine and modified AuE in the presence of methylene blue as a redox indicator. The experimental results indicated that the interaction of melamine with CHIT/ZnONPs/([EMIM][Otf])/AuE were based on the strong interaction of hydrogen bonds. The morphological characterization of modified AuE was observed under scanning electron microscope. Under optimal conditions, the current signal was directly proportional to the melamine concentration ranging from 9.6 x 10-5 to 9.6 x 10-11 M, with a correlation coefficient of 0.9656. The detection limit was 9.6 x 10-12 M. Finally, the proposed method was successfully applied and displayed an excellent sensitivity in the determination of melamine in milk samples.

Keywords: melamine, gold electrode, zinc oxide nanoparticles, cyclic voltammetries, differential pulse voltammetries

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Authors: Zayar Phyo, Ei Chaw Htoon

Abstract:

In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.

Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel

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Authors: Azad Hussain, Shoaib Ali, M. Y. Malik, Saba Nazir, Sarmad Jamal

Abstract:

This article reports a fundamental numerical investigation to analyze the impact of thermal radiations on MHD flow of differential type nanofluid past a porous plate. Here, viscosity is taken as function of temperature. Energy equation is deliberated in the existence of viscous dissipation. The mathematical terminologies of nano concentration, velocity and temperature are first cast into dimensionless expressions via suitable conversions and then solved by using Shooting technique to obtain the numerical solutions. Graphs has been plotted to check the convergence of constructed solutions. At the end, the influence of effective parameters on nanoparticle concentration, velocity and temperature fields are also deliberated in a comprehensive way. Moreover, the physical measures of engineering importance such as the Sherwood number, Skin friction and Nusselt number are also calculated. It is perceived that the thermal radiation enhances the temperature for both Vogel's and Reynolds' models but the normal stress parameter causes a reduction in temperature profile.

Keywords: MHD flow, differential type nanofluid, Porous medium, variable viscosity, thermal radiation

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Authors: Usharani Rathinam

Abstract:

Although policies directing inclusion of marginalized were in effect, majority of chronically impoverished in India belonged to schedule caste and schedule tribes. Also, taking into account that poverty is gendered; destitute women belonged to lower social order whose need is not largely highlighted at policy level. This paper discusses on social relations poverty which highlights on how social order that existed structurally in the society can perpetuate chronic poverty, followed by a critical review on social inclusion policies of India, its merits and demerits in addressing chronic poverty. Multiple case study design is utilized to address this concern in four districts of India; Jhansi, Tikamgarh, Cuddalore and Anantapur. These four districts were selected by purposive sampling based on the criteria; the district should either be categorized as a backward district or should have a history of high poverty rate. Qualitative methods including eighty in-depth interviews, six focus group discussions, six social mapping procedures and three key informant interviews were conducted in 2011, at each of the locations. Analysis of the data revealed that irrespective of gender, schedule castes and schedule tribe participants were found to be chronically poor in all districts. Caste based discrimination is exhibited at both micro and macro levels; village and institutional levels. At village level, lower caste respondents had lesser access to public resources. Also, within institutional settings, due to confiscation, unequal access to resources is noticed, especially in fund distribution. This study found that half of the budget intended for schedule caste and schedule tribes were confiscated by upper caste administrative staffs. This implies that power based on social hierarchy marginalize lower caste participants from accessing better economic, social, and political benefits, that had led them to suffer long term poverty. This study also explored the traditional ties between caste, social structure and bonded labour as a cause of long-term poverty. Though equal access is being emphasized in constitutional rights, issues at micro level have not been reflected in formulation of these rights. Therefore, it is significant for a policy to consider the structural complexity and then focus on issues such as equal distribution of assets and infrastructural facilities that will reduce exclusion and foster long-term security in areas such as employment, markets and public distribution.

Keywords: caste, inclusion policies, India, social order

Procedia PDF Downloads 206