Search results for: Wave Vortex Parameters

Authors: [email protected]

Abstract:

Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data need a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM), ensemble learning with hyper parameters optimization, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: Machine learning, Deep learning, cancer prediction, breast cancer, LSTM, Score-Level Fusion.

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Authors: Ugur Akyol, Dinçer Akal, Ahmet Cihan, Kamil Kahveci

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This study is concerned with the investigation of the suitability of several empirical and semi-empirical drying models available in the literature to define drying behavior of viscose yarn bobbins. For this purpose, firstly, experimental drying behaviour of viscose bobbins was determined on an experimental dryer setup which was designed and manufactured based on hot-air bobbin dryers used in textile industry. Afterwards, drying models considered were fitted to the experimentally obtained moisture ratios. Drying parameters were drying temperature and bobbin diameter. The fit was performed by selecting the values for constants in the models in such a way that these values make the sum of the squared differences between the experimental and the model results for moisture ratio minimum. Suitability of fitting was specified as comparing the correlation coefficient, standard error and mean square deviation. The results show that the most appropriate model in describing the drying curves of viscose bobbins is the Page model.

Keywords: Drying, moisture ratio, Page model, viscose

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Authors: Neslihan Yuca, Nilgün Karatepe

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The aim of this study was to synthesize the single walled carbon nanotubes (SWCNTs) and determine their hydrogen storage capacities. SWCNTs were firstly synthesized by chemical vapor deposition (CVD) of acetylene (C2H2) on a magnesium oxide (MgO) powder impregnated with an iron nitrate (Fe(NO3)3·9H2O) solution. The synthesis parameters were selected as: the synthesis temperature of 800°C, the iron content in the precursor of 5% and the synthesis time of 30 min. Purification process of SWCNTs was fulfilled by microwave digestion at three different temperatures (120, 150 and 200 °C), three different acid concentrations (0.5, 1 and 1.5 M) and for three different time intervals (15, 30 and 60 min). Nitric acid (HNO3) was used in the removal of the metal catalysts. The hydrogen storage capacities of the purified materials were measured using volumetric method at the liquid nitrogen temperature and gas pressure up to 100 bar. The effects of the purification conditions such as temperature, time and acid concentration on hydrogen adsorption were investigated.

Keywords: Carbon nanotubes, purification, microwavedigestion, hydrogen storage

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Authors: S. Raja Balachandar, K.Kannan

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A new Meta heuristic approach called "Randomized gravitational emulation search algorithm (RGES)" for solving vertex covering problems has been designed. This algorithm is found upon introducing randomization concept along with the two of the four primary parameters -velocity- and -gravity- in physics. A new heuristic operator is introduced in the domain of RGES to maintain feasibility specifically for the vertex covering problem to yield best solutions. The performance of this algorithm has been evaluated on a large set of benchmark problems from OR-library. Computational results showed that the randomized gravitational emulation search algorithm - based heuristic is capable of producing high quality solutions. The performance of this heuristic when compared with other existing heuristic algorithms is found to be excellent in terms of solution quality.

Keywords: Vertex covering Problem, Velocity, Gravitational Force, Newton's Law, Meta Heuristic, Combinatorial optimization.

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Authors: Dinara F. Gaynutdinova, Vladimir Ya Modorsky, Nikolay A. Shevelev

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The problem under research is that of unpredictable modes occurring in two-stage centrifugal hydraulic pump as a result of hydraulic processes caused by vibrations of structural components. Numerical, analytical and experimental approaches are considered. A hypothesis was developed that the problem of unpredictable pressure decrease at the second stage of centrifugal pumps is caused by cavitation effects occurring upon vibration. The problem has been studied experimentally and theoretically as of today. The theoretical study was conducted numerically and analytically. Hydroelastic processes in dynamic “liquid – deformed structure” system were numerically modelled and analysed. Using ANSYS CFX program engineering analysis complex and computing capacity of a supercomputer the cavitation parameters were established to depend on vibration parameters. An influence domain of amplitudes and vibration frequencies on concentration of cavitation bubbles was formulated. The obtained numerical solution was verified using CFM program package developed in PNRPU. The package is based on a differential equation system in hyperbolic and elliptic partial derivatives. The system is solved by using one of finite-difference method options – the particle-in-cell method. The method defines the problem solution algorithm. The obtained numerical solution was verified analytically by model problem calculations with the use of known analytical solutions of in-pipe piston movement and cantilever rod end face impact. An infrastructure consisting of an experimental fast hydro-dynamic processes research installation and a supercomputer connected by a high-speed network, was created to verify the obtained numerical solutions. Physical experiments included measurement, record, processing and analysis of data for fast processes research by using National Instrument signals measurement system and Lab View software. The model chamber end face oscillated during physical experiments and, thus, loaded the hydraulic volume. The loading frequency varied from 0 to 5 kHz. The length of the operating chamber varied from 0.4 to 1.0 m. Additional loads weighed from 2 to 10 kg. The liquid column varied from 0.4 to 1 m high. Liquid pressure history was registered. The experiment showed dependence of forced system oscillation amplitude on loading frequency at various values: operating chamber geometrical dimensions, liquid column height and structure weight. Maximum pressure oscillation (in the basic variant) amplitudes were discovered at loading frequencies of approximately 1,5 kHz. These results match the analytical and numerical solutions in ANSYS and CFM.

Keywords: Computing experiment, hydroelasticity, physical experiment, vibration.

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Authors: C. Ramsauer, J. Karandikar, D. Leitner, T. Schmitz, F. Bleicher

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Machining instability, or chatter, can impose an important limitation to discrete part machining. In this work, a networked implementation of milling stability optimization with Bayesian learning is presented. The milling process was monitored with a wireless sensory tool holder instrumented with an accelerometer at the TU Wien, Vienna, Austria. The recorded data from a milling test cut were used to classify the cut as stable or unstable based on a frequency analysis. The test cut result was used in a Bayesian stability learning algorithm at the University of Tennessee, Knoxville, Tennessee, USA. The algorithm calculated the probability of stability as a function of axial depth of cut and spindle speed based on the test result and recommended parameters for the next test cut. The iterative process between two transatlantic locations was repeated until convergence to a stable optimal process parameter set was achieved.

Keywords: Bayesian learning, instrumented tool holder, machining stability, optimization strategy.

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Authors: Marios M. Hadjiandreou, Raul Conejeros, Ian Wilson

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This study presents a mathematical modeling approach to the planning of HIV therapies on an individual basis. The model replicates clinical data from typical-progressors to AIDS for all stages of the disease with good agreement. Clinical data from rapid-progressors and long-term non-progressors is also matched by estimation of immune system parameters only. The ability of the model to reproduce these phenomena validates the formulation, a fact which is exploited in the investigation of effective therapies. The therapy investigation suggests that, unlike continuous therapy, structured treatment interruptions (STIs) are able to control the increase in both the drug-sensitive and drug-resistant virus population and, hence, prevent the ultimate progression from HIV to AIDS. The optimization results further suggest that even patients characterised by the same progression type can respond very differently to the same treatment and that the latter should be designed on a case-by-case basis. Such a methodology is presented here.

Keywords: AIDS, chemotherapy, mathematical modeling, optimal control, progression.

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Authors: Orkide Donma, Mustafa M. Donma

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Obesity is a low-grade inflammatory disease and may lead to health problems such as hypertension, dyslipidemia, diabetes. It is also associated with important risk factors for cardiovascular diseases. This requires the detailed evaluation of obesity, particularly in children. The aim of this study is to enlighten the potential associations between lipid ratios and obesity indices and to introduce those with discriminating features among children with obesity and metabolic syndrome (MetS). A total of 408 children (aged between six and eighteen years) participated in the scope of the study. Informed consent forms were taken from the participants and their parents. Ethical Committee approval was obtained. Anthropometric measurements such as weight, height as well as waist, hip, head, neck circumferences and body fat mass were taken. Systolic and diastolic blood pressure values were recorded. Body mass index (BMI), diagnostic obesity notation model assessment index-II (D2 index), waist-to-hip, head-to-neck ratios were calculated. Total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDLChol), low-density lipoprotein cholesterol (LDLChol) analyses were performed in blood samples drawn from 110 children with normal body weight, 164 morbid obese (MO) children and 134 children with MetS. Age- and sex-adjusted BMI percentiles tabulated by World Health Organization were used to classify groups; normal body weight, MO and MetS. 15^th-to-85^th percentiles were used to define normal body weight children. Children, whose values were above the 99th percentile, were described as MO. MetS criteria were defined. Data were evaluated statistically by SPSS Version 20. The degree of statistical significance was accepted as p≤0.05. Mean±standard deviation values of BMI for normal body weight children, MO children and those with MetS were 15.7±1.1, 27.1±3.8 and 29.1±5.3 kg/m², respectively. Corresponding values for the D2 index were calculated as 3.4±0.9, 14.3±4.9 and 16.4±6.7. Both BMI and D2 index were capable of discriminating the groups from one another (p≤0.01). As far as other obesity indices were considered, waist-to hip and head-to-neck ratios did not exhibit any statistically significant difference between MO and MetS groups (p≥0.05). Diagnostic obesity notation model assessment index-II was correlated with the triglycerides-to-HDL-C ratio in normal body weight and MO (r=0.413, p≤0.01 and r=0.261, (p≤0.05, respectively). Total cholesterol-to-HDL-C and LDL-C-to-HDL-C showed statistically significant differences between normal body weight and MO as well as MO and MetS (p≤0.05). The only group in which these two ratios were significantly correlated with waist-to-hip ratio was MetS group (r=0.332 and r=0.334, p≤0.01, respectively). Lack of correlation between the D2 index and the triglycerides-to-HDL-C ratio was another important finding in MetS group. In this study, parameters and ratios, whose associations were defined previously with increased cardiovascular risk or cardiac death have been evaluated along with obesity indices in children with morbid obesity and MetS. Their profiles during childhood have been investigated. Aside from the nature of the correlation between the D2 index and triglycerides-to-HDL-C ratio, total cholesterol-to-HDL-C as well as LDL-C-to- HDL-C ratios along with their correlations with waist-to-hip ratio showed that the combination of obesity-related parameters predicts better than one parameter and appears to be helpful for discriminating MO children from MetS group.

Keywords: Children, lipid ratios, metabolic syndrome, obesity indices.

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Authors: V. G. Rifert, V. V. Gorin, V. V. Sereda, V. V. Treputnev

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The analysis of heat transfer design methods in condensing inside plain tubes under existing influence of shear stress is presented in this paper. The existing discrepancy in more than 30-50% between rating heat transfer coefficients and experimental data has been noted. The analysis of existing theoretical and semi-empirical methods of heat transfer prediction is given. The influence of a precise definition concerning boundaries of phase flow (it is especially important in condensing inside horizontal tubes), shear stress (friction coefficient) and heat flux on design of heat transfer is shown. The substantiation of boundary conditions of the values of parameters, influencing accuracy of rated relationships, is given. More correct relationships for heat transfer prediction, which showed good convergence with experiments made by different authors, are substantiated in this work.

Keywords: Film condensation, heat transfer, plain tube, shear stress.

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of features selection methods to reduce the dimensionality of the document-representation vector. Four feature selection methods are evaluated: Random Selection, Information Gain (IG), Support Vector Machine (called SVM_FS) and Genetic Algorithm with SVM (GA_FS). We showed that the best results were obtained with SVM_FS and GA_FS methods for a relatively small dimension of the features vector comparative with the IG method that involves longer vectors, for quite similar classification accuracies. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Features selection, learning with kernels, support vector machine, genetic algorithms and classification.

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Authors: Yun Won Chung

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The energy consumption of home femto base stations (BSs) can be reduced, by turning off the Wi-Fi radio interface when there is no mobile station (MS) under the coverage of the BSs or MSs do not transmit or receive data packet for long time, especially in late night. In the energy-efficient home femto BSs, if MSs have any data packet to transmit and the Wi-Fi radio interface in off state, MSs wake up the Wi-Fi radio interface of home femto BSs by using additional low power radio interface. In this paper, the performance of the energy-efficient home femto BSs from the aspect of energy consumption and cumulative average delay, and show the effect of various parameters on energy consumption and cumulative average delay. From the results, the tradeoff relationship between energy consumption and cumulative average delay is shown and thus, appropriate operation should be needed to balance the tradeoff.

Keywords: energy consumption, power saving, femto base station.

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: Landslide, limit analysis, ANN, soil properties.

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Authors: Alpha Agape Gopalai, S. M. N. Arosha Senanayake

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This paper explores the opportunity of using tri-axial wireless accelerometers for supervised monitoring of sports movements. A motion analysis system for the upper extremities of lawn bowlers in particular is developed. Accelerometers are placed on parts of human body such as the chest to represent the shoulder movements, the back to capture the trunk motion, back of the hand, the wrist and one above the elbow, to capture arm movements. These sensors placement are carefully designed in order to avoid restricting bowler-s movements. Data is acquired from these sensors in soft-real time using virtual instrumentation; the acquired data is then conditioned and converted into required parameters for motion regeneration. A user interface was also created to facilitate in the acquisition of data, and broadcasting of commands to the wireless accelerometers. All motion regeneration in this paper deals with the motion of the human body segment in the X and Y direction, looking into the motion of the anterior/ posterior and lateral directions respectively.

Keywords: Motion Regeneration, Virtual Instrumentation, Wireless Accelerometers.

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Authors: L.A.Kumaraswamidhas, P.Velmurugan, K.Sankaranarayanasamy

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This work has been conducted to study on comfort level of drivers of suspended cabin tractor semitrailer. Some drivers suffer from low back pain caused by vibration. The practical significance of applying suspended cabin type of tractor semi trailer was tested at different road conditions, different speed as well as different load conditions for comfortable driver seat interface (x, y, z ) and the process parameters have been prioritized using Taguchi-s L27 orthogonal array. Genetic Algorithm (GA) is used to optimize the human comfort vibration of suspended cabin tractor semitrailer drivers. The practical significance of applying GA to human comfort to reaction of suspended cabin tractor semitrailer has been validated by means of computing the deviation between predicted and experimentally obtained human comfort to vibration. The optimized acceleration data indicate a little uncomfortable ride for suspended cabin tractor semitrailer.

Keywords: Genetic Algorithm, Ride Comfort, Taguchi Method, Tractor Semitrailer

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Authors: H. R. Khodaei, M. Moradi, A. H. Tajik

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The type of foundation commonly used today for berthing dolphins is a set of tubular steel piles with large diameters, which are known as monopiles. The design of these monopiles is based on the theories related with laterally loaded piles. One of the most common methods to analyze and design the piles subjected to lateral loads is the p-y curves. In the present study, centrifuge tests are conducted in order to obtain the p-y curves. Series of tests were designed in order to investigate the scaling laws in the centrifuge for monotonic loading. Also, two important parameters, the embedded depth L of the pile in the soil and free length e of the pile, as well as their ratios were studied via five experimental tests. Finally, the p-y curves of API are presented to be compared with the curves obtained from the tests so that the differences could be demonstrated. The results show that the p-y curves proposed by API highly overestimate the lateral load bearing capacity. It suggests that these curves need correction and modification for each site as the soil conditions change.

Keywords: Centrifuge modeling, monopile, lateral loading, p-y curves.

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Authors: Josip Vasilj, Petar Sarajcev, Damir Jakus

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One of the major difficulties introduced with wind power penetration is the inherent uncertainty in production originating from uncertain wind conditions. This uncertainty impacts many different aspects of power system operation, especially the balancing power requirements. For this reason, in power system development planing, it is necessary to evaluate the potential uncertainty in future wind power generation. For this purpose, simulation models are required, reproducing the performance of wind power forecasts. This paper presents a wind power forecast error simulation models which are based on the stochastic process simulation. Proposed models capture the most important statistical parameters recognized in wind power forecast error time series. Furthermore, two distinct models are presented based on data availability. First model uses wind speed measurements on potential or existing wind power plant locations, while the seconds model uses statistical distribution of wind speeds.

Keywords: Wind power, Uncertainty, Stochastic process, Monte Carlo simulation.

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Authors: H. M. Farghally, N. M. Ahmed, H. T. El-Madany, D. M. Atia, F. H. Fahmy

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Energy is required in almost every aspect of human activities and development of any nation in the world. Increasing fossil fuel price, energy security and climate change have important bearings on sustainable development of any nation. The renewable energy technology is considered one of the drastic approaches which taken over the world to reduce the energy problem. The preservation of vegetables by freezing is one of the most important methods of retaining quality in agricultural products over long-term storage periods. Freezing factories show high demand of energy for both heat and electricity; the hybrid Photovoltaic/Thermal (PV/T) systems could be used in order to meet this requirement. This paper presents PV/T system design for freezing factory. Also, the complete mathematical modeling and MATLAB SIMULINK of PV/T collector is introduced. The sensitivity analysis for the manufacturing parameters of PV/T collector is carried out to study their effect on both thermal and electrical efficiency.

Keywords: Renewable energy, Hybrid PV/T system, Sensitivity analysis.

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Authors: Md. Z. Alam, Devi R. Asih, Md. N. Salleh

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Immobilization of lipase enzyme produced from palm oil mill effluent (POME) by the activated carbon (AC) among the low cost support materials was optimized. The results indicated that immobilization of 94% was achieved by AC as the most suitable support material. A sequential optimization strategy based on a statistical experimental design, including one-factor-at-a-time (OFAT) method was used to determine the equilibrium time. Three components influencing lipase immobilization were optimized by the response surface methodology (RSM) based on the face-centered central composite design (FCCCD). On the statistical analysis of the results, the optimum enzyme concentration loading, agitation rate and carbon active dosage were found to be 30 U/ml, 300 rpm and 8 g/L respectively, with a maximum immobilization activity of 3732.9 U/g-AC after 2 hrs of immobilization. Analysis of variance (ANOVA) showed a high regression coefficient (R²) of 0.999, which indicated a satisfactory fit of the model with the experimental data. The parameters were statistically significant at p<0.05.

Keywords: Activated carbon, adsorption, immobilization, POME based lipase.

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Authors: S. Gao, S. Srirattayawong

Abstract:

In this study, a computational fluid dynamics (CFD) model has been developed for studying the effect of surface roughness profile on the EHL problem. The cylinders contact geometry, meshing and calculation of the conservation of mass and momentum equations are carried out using the commercial software packages ICEMCFD and ANSYS Fluent. The user defined functions (UDFs) for density, viscosity and elastic deformation of the cylinders as the functions of pressure and temperature are defined for the CFD model. Three different surface roughness profiles are created and incorporated into the CFD model. It is found that the developed CFD model can predict the characteristics of fluid flow and heat transfer in the EHL problem, including the main parameters such as pressure distribution, minimal film thickness, viscosity, and density changes. The results obtained show that the pressure profile at the center of the contact area directly relates to the roughness amplitude. A rough surface with kurtosis value of more than 3 has greater influence over the fluctuated shape of pressure distribution than in other cases.

Keywords: CFD, EHL, Kurtosis, Surface roughness.

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Authors: M. Norouzi, M. H. Kayhani, M. R. H. Nobari, M. Karimi Demneh

Abstract:

In this paper, fully developed flow and heat transfer of viscoelastic materials in curved ducts with square cross section under constant heat flux have been investigated. Here, staggered mesh is used as computational grids and flow and heat transfer parameters have been allocated in this mesh with marker and cell method. Numerical solution of governing equations has being performed with FTCS finite difference method. Furthermore, Criminale-Eriksen- Filbey (CEF) constitutive equation has being used as viscoelastic model. CEF constitutive equation is a suitable model for studying steady shear flow of viscoelastic materials which is able to model both effects of the first and second normal stress differences. Here, it is shown that the first and second normal stresses differences have noticeable and inverse effect on secondary flows intensity and mean Nusselt number which is the main novelty of current research.

Keywords: Viscoelastic, fluid flow, heat convection, CEF model, curved duct, square cross section.

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Authors: J. P. Makwana, A. K. Joshi, Rajesh N. Patel, Darshil Patel

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Recently, fluidized bed gasification becomes an attractive technology for power generation due to its higher efficiency. The main objective pursued in this work is to investigate the producer gas production potential from sized biomass (sawdust and pigeon pea) by applying the air gasification technique. The size of the biomass selected for the study was in the range of 0.40-0.84 mm. An experimental study was conducted using a fluidized bed gasifier with 210 mm diameter and 1600 mm height. During the experiments, the fuel properties and the effects of operating parameters such as gasification temperatures 700 to 900 °C, equivalence ratio 0.16 to 0.46 were studied. It was concluded that substantial amounts of producer gas (up to 1110 kcal/m3) could be produced utilizing biomass such as sawdust and pigeon pea by applying this fluidization technique. For both samples, the rise of temperature till 900 °C and equivalence ratio of 0.4 favored further gasification reactions and resulted into producer gas with calorific value 1110 kcal/m3.

Keywords: Sized biomass, fluidized bed gasifier, equivalence ratio, temperature profile, gas composition.

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Authors: D. S. Vardar, A. S. Kipcak, F. T. Senberber, E. M. Derun, N. Tugrul, S. Piskin

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Zinc borate is an important inorganic hydrate borate material, which can be used as a flame retardant agent and corrosion resistance material. This compound can loss its structural water content at higher than 290°C. Due to thermal stability; Zinc Borate can be used as flame retardant at high temperature process of plastic and gum. In this study, the ultrasonic reaction of zinc borates were studied using hydrozincite (Zn5(CO3)2·(OH)6) and boric acid (H3BO3) raw materials. Before the synthesis raw materials were characterized by X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR). Ultrasonic method is a new application on the zinc borate synthesis. The synthesis parameters were set to 90°C reaction temperature and 55 minutes of reaction time, with 1:1, 1:2, 1:3, 1:4 and 1:5 molar ratio of starting materials (Zn5(CO3)2·(OH)6 : H3BO3). After the zinc borate synthesis, the products were analyzed by XRD and FT-IR. As a result, optimum molar ratio of 1:5 is determined for the synthesis of zinc borates with ultrasonic method.

Keywords: Borate, ultrasonic method, zinc borate, zinc borate synthesis.

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Authors: G. Trigui, B. Laroche, M. Miquel, B. Dubreucq, A. Trubuil

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The subcellular organelles called oil bodies (OBs) are lipid-filled quasi-spherical droplets produced from the endoplasmic reticulum (ER) and then released into the cytoplasm during seed development. It is believed that an OB grows by coalescence with other OBs and that its stability depends on the composition of oleosins, major proteins inserted in the hemi membrane that covers OBs. In this study, we measured the OB-volume distribution from different genotypes of A. thaliana after 7, 8, 9, 10 and 11 days of seed development. In order to test the hypothesis of OBs dynamics, we developed a simple mathematical model using non-linear differential equations inspired from the theory of coagulation. The model describes the evolution of OB-volume distribution during the first steps of seed development by taking into consideration the production of OBs, the increase of triacylglycerol volume to be stored, and the growth by coalescence of OBs. Fitted parameters values show an increase in the OB production and coalescence rates in A. thaliana oleosin mutants compared to wild type.

Keywords: Biogenesis, coalescence, oil body, oleosin, population dynamics.

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Authors: A. Seleem, M. Mortada, M. El Morsi, M. Younan

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Diffusion stills have been effective in water desalination. The present work represents a model of the distillation process by using vertical single-effect diffusion stills. A semianalytical model has been developed to model the process. A software computer code using Engineering Equation Solver EES software has been developed to solve the equations of the developed model. An experimental setup has been constructed, and used for the validation of the model. The model is also validated against former literature results. The results obtained from the present experimental test rig, and the data from the literature, have been compared with the results of the code to find its best range of validity. In addition, a parametric analysis of the system has been developed using the model to determine the effect of operating conditions on the system's performance. The dominant parameters that affect the productivity of the still are the hot plate temperature that ranges from (55- 90°C) and feed flow rate in range of (0.00694-0.0211 kg/m2-s).

Keywords: Analytical Model, Solar Distillation, Sustainable Water Systems, Vertical Diffusion Still.

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Authors: T. C. B. N. Assunção, J. L. Silvino, P. Resende

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The winding hot-spot temperature is one of the most critical parameters that affect the useful life of the power transformers. The winding hot-spot temperature can be calculated as function of the top-oil temperature that can estimated by using the ambient temperature and transformer loading measured data. This paper proposes the estimation of the top-oil temperature by using a method based on Least Squares Support Vector Machines approach. The estimated top-oil temperature is compared with measured data of a power transformer in operation. The results are also compared with methods based on the IEEE Standard C57.91-1995/2000 and Artificial Neural Networks. It is shown that the Least Squares Support Vector Machines approach presents better performance than the methods based in the IEEE Standard C57.91-1995/2000 and artificial neural networks.

Keywords: Artificial Neural Networks, Hot-spot Temperature, Least Squares Support Vector, Top-oil Temperature.

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Authors: Yogesh Aggarwal

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The paper discusses the results obtained to predict reinforcement in singly reinforced beam using Neural Net (NN), Support Vector Machines (SVM-s) and Tree Based Models. Major advantage of SVM-s over NN is of minimizing a bound on the generalization error of model rather than minimizing a bound on mean square error over the data set as done in NN. Tree Based approach divides the problem into a small number of sub problems to reach at a conclusion. Number of data was created for different parameters of beam to calculate the reinforcement using limit state method for creation of models and validation. The results from this study suggest a remarkably good performance of tree based and SVM-s models. Further, this study found that these two techniques work well and even better than Neural Network methods. A comparison of predicted values with actual values suggests a very good correlation coefficient with all four techniques.

Keywords: Linear Regression, M5 Model Tree, Neural Network, Support Vector Machines.

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Authors: Sidhartha Panda, N. P. Padhy

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The application of a Static Synchronous Series Compensator (SSSC) controller to improve the transient stability performance of a power system is thoroughly investigated in this paper. The design problem of SSSC controller is formulated as an optimization problem and Particle Swarm Optimization (PSO) Technique is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor angle of the generator is involved; transient stability performance of the system is improved. The proposed controller is tested on a weakly connected power system subjected to different severe disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and its ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC controller improves greatly the voltage profile of the system under severe disturbances.

Keywords: Particle swarm optimization, transient stability, power system oscillations, SSSC.

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Authors: Jürgen Roßmann, Gerrit Alves

Abstract:

In today-s world, the efficient utilization of wood resources comes more and more to the mind of forest owners. It is a very complex challenge to ensure an efficient harvest of the wood resources. This is one of the scopes the project “Virtual Forest II" addresses. Its core is a database with data about forests containing approximately 260 million trees located in North Rhine-Westphalia (NRW). Based on this data, tree growth simulations and wood mobilization simulations can be conducted. This paper focuses on the latter. It describes a discrete-event-simulation with an attached 3-D real time visualization which simulates timber harvest using trees from the database with different crop resources. This simulation can be displayed in 3-D to show the progress of the wood crop. All the data gathered during the simulation is presented as a detailed summary afterwards. This summary includes cost-benefit calculations and can be compared to those of previous runs to optimize the financial outcome of the timber harvest by exchanging crop resources or modifying their parameters.

Keywords: Timber harvest, simulation, 3-D, optimization.

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Authors: Ratanaporn Leesing, Ratanaporn Baojungharn

Abstract:

Microbial oil was produced by soil isolated oleaginous yeast YU5/2 in flask-batch fermentation. The yeast was identified by molecular genetics technique based on sequence analysis of the variable D1/D2 domain of the large subunit (26S) ribosomal DNA and it was identified as Torulaspora globosa. T. globosa YU5/2 supported maximum values of 0.520 g/L/d, 0.472 g lipid/g cells, 4.16 g/L, and 0.156 g/L/d for volumetric lipid production rate, and specific yield of lipid, lipid concentration, and specific rate of lipid production respectively, when culture was performed in nitrogen-limiting medium supplemented with 80g/L glucose. Among the carbon sources tested, maximum cell yield coefficient (YX/S, g/L), maximum specific yield of lipid (YP/X, g lipid/g cells) and volumetric lipid production rate (QP, g/L/d) were found of 0.728, 0.237, and 0.619, respectively, using sweet potato tubers hydrolysates as carbon source.

Keywords: Microbial oil, oleaginous yeast, Torulasporaglobosa YU5/2, sweet potato tubers, kinetic parameters.

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Authors: Azhar Hussain, Kashif Shahzad, Chunming Tang

Abstract:

this paper gives a novel approach towards real-time speed estimation of multiple traffic vehicles using fuzzy logic and image processing techniques with proper arrangement of camera parameters. The described algorithm consists of several important steps. First, the background is estimated by computing median over time window of specific frames. Second, the foreground is extracted using fuzzy similarity approach (FSA) between estimated background pixels and the current frame pixels containing foreground and background. Third, the traffic lanes are divided into two parts for both direction vehicles for parallel processing. Finally, the speeds of vehicles are estimated by Maximum a Posterior Probability (MAP) estimator. True ground speed is determined by utilizing infrared sensors for three different vehicles and the results are compared to the proposed algorithm with an accuracy of ± 0.74 kmph.

Keywords: Defuzzification, Fuzzy similarity approach, lane cropping, Maximum a Posterior Probability (MAP) estimator, Speed estimation

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