Search results for: electron back scattered diffraction.

Authors: John Justo Ambuchi, Zhaohan Zhang, Yujie Feng

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Quick development and usage of nanotechnology have resulted to massive use of various nanoparticles, such as iron oxide nanoparticles (IONPs) and multi-wall carbon nanotubes (MWCNTs). Thus, this study investigated the role of IONPs and MWCNTs in enhancing bioenergy recovery. Results show that IONPs at a concentration of 750 mg/L and MWCNTs at a concentration of 1500 mg/L induced faster substrate utilization and biogas production rates than the control. IONPs exhibited higher carbon oxygen demand (COD) removal efficiency than MWCNTs while on the contrary, MWCNT performance on biogas generation was remarkable than IONPs. Furthermore, scanning electron microscopy (SEM) investigation revealed extracellular polymeric substances (EPS) excretion from AGS had an interaction with nanoparticles. This interaction created a protective barrier to microbial consortia hence reducing their cytotoxicity. Microbial community analyses revealed genus predominance of bacteria of Anaerolineaceae and Longilinea. Their role in biodegradation of the substrate could have highly been boosted by nanoparticles. The archaea predominance of the genus level of Methanosaeta and Methanobacterium enhanced methanation process. The presence of bacteria of genus Geobacter was also reported. Their presence might have significantly contributed to direct interspecies electron transfer in the system. Exposure of AGS to nanoparticles promoted direct interspecies electron transfer among the anaerobic fermenting bacteria and their counterpart methanogens during the anaerobic digestion process. This results provide useful insightful information in understanding the response of microorganisms to IONPs and MWCNTs in the complex natural environment.

Keywords: Anaerobic granular sludge, extracellular polymeric substances, iron oxide nanoparticles, multi-wall carbon nanotubes.

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Authors: Abdellatif Kasbi, Abderrafii Rahali

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During the recent years, much interest has been devoted to fractional order control that has appeared as a very eligible control approach for the systems experiencing parametric uncertainty and outer disturbances. The main purpose of this paper is to design and evaluate the performance of a fractional order proportional integral (FOPI) controller applied to control prototype variable speed wind generation system (WGS) that uses a doubly fed induction generator (DFIG). In this paper, the DFIG-machine is controlled according to the stator field-oriented control (FOC) strategy, which makes it possible to regulate separately the reactive and active powers exchanged between the WGS and the grid. The considered system is modeled and simulated using MATLAB-Simulink, and the performance of FOPI controller applied to the back-to-back power converter control of DFIG based grid connected variable speed wind turbine are evaluated and compared to the ones obtained with a conventional PI controller.

Keywords: Design, fractional order PI controller, wind generation system, doubly fed induction generator, wind turbine, field-oriented control.

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Authors: Binay K. Dutta, Tayseir M. Abd Ellateif, Saikat Maitra

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In the present work homogeneous silica film on silicon was fabricated by colloidal silica sol. The silica sol precursor with uniformly granular particle was derived by the alkaline hydrolysis of tetraethoxyorthosilicate (TEOS) in presence of glycerol template. The film was prepared by dip coating process. The templated hetero-structured silica film was annealed at elevated temperatures to generate nano- and meso porosity in the film. The film was subsequently annealed at different temperatures to make it defect free and abrasion resistant. The sol and the film were characterized by the measurement of particle size distribution, scanning electron microscopy, XRD, FTIR spectroscopy, transmission electron microscopy, atomic force microscopy, measurement of the refractive index, thermal conductivity and abrasion resistance. The porosity of the films decreased whereas refractive index and dielectric constant of it `increased with the increase in the annealing temperature. The thermal conductivity of the films increased with the increase in the film thickness. The developed porous silica film holds strong potential for use in different areas.

Keywords: Silica film, Nanoporous, Sol-gel, Templating, Dip coating.

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Authors: Keshav Pujeri, Pranesh Jain, Krutibas Panda

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Significant changes in oil and gas drilling have emphasized the need to verify the integrity and reliability of drill stem components. Defects are inevitable in cast components, regardless of application; but if these defects go undetected, any severe defect could cause down-hole failure. One such defect is shrinkage porosity. Castings with lower level shrinkage porosity (CB levels 1 and 2) have scattered pores and do not occupy large volumes; so pressure testing and helium leak testing (HLT) are sufficient for qualifying the castings. However, castings with shrinkage porosity of CB level 3 and higher, behave erratically under pressure testing and HLT making these techniques insufficient for evaluating the castings- integrity. This paper presents a case study to highlight how the radiography technique is much more effective than pressure testing and HLT.

Keywords: Casting Defects, Interconnects, Leak Check, Pressure Test, Radiography.

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Authors: Muhibul Haque Bhuyan, Quazi D. M. Khosru

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Carrier scatterings in the inversion channel of MOSFET dominates the carrier mobility and hence drain current. This paper presents an analytical model of the subthreshold drain current incorporating the effective electron mobility model of the pocket implanted nano scale n-MOSFET. The model is developed by assuming two linear pocket profiles at the source and drain edges at the surface and by using the conventional drift-diffusion equation. Effective electron mobility model includes three scattering mechanisms, such as, Coulomb, phonon and surface roughness scatterings as well as ballistic phenomena in the pocket implanted n-MOSFET. The model is simulated for various pocket profile and device parameters as well as for various bias conditions. Simulation results show that the subthreshold drain current data matches the experimental data already published in the literature.

Keywords: Linear Pocket Profile, Pocket Implanted n-MOSFET, Subthreshold Drain Current and Effective Mobility Model.

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Authors: Guohua Cao, Xu Dong

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X-ray Fluorescence Molecular Imaging (XFMI) holds great promise as a low-cost molecular imaging modality for biomedical applications with high chemical sensitivity. However, for in vivo biomedical applications, a key technical bottleneck is the relatively low chemical sensitivity of XFMI, especially at a reasonably low radiation dose. In laboratory x-ray source based XFMI, one of the main factors that limits the chemical sensitivity of XFMI is the scattered x-rays. We will present our latest findings on improving the chemical sensitivity of XFMI using excitation beam spectrum optimization. XFMI imaging experiments on two mouse-sized phantoms were conducted at three different excitation beam spectra. Our results show that the minimum detectable concentration (MDC) of iodine can be readily increased by five times via excitation spectrum optimization. Findings from this investigation could find use for in vivo pre-clinical small-animal XFMI in the future.

Keywords: Molecular imaging, X-ray fluorescence, chemical sensitivity, X-ray scattering.

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Authors: Martin Henkel

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Different forms of interaction are an integral part of modern courses. Traditional courses held on-campus might focus on teacher-student interaction, or student-student interaction, or both. However when these traditional on-campus courses are to be held as distance courses there is a risk that these well-designed interactions will be difficult or impossible to uphold. For example, studentstudent interaction in traditional project assignments might not work well if the students are scattered across the world. Thus, even a welldesigned traditional on-site course cannot without modification be turned into a distance course. Traditional on-site courses simply have to be redesigned to become true distance courses. This paper describes a structured approach which facilitates the redesign of a traditional course into a distance course. The approach is based on that the desired forms of course flexibility are identified, and thereafter that the course activities are redesigned to facilitate interaction in a distance course. The approach is making use of known patterns of pedagogic interaction and existing guidelines for distance education design. The approach is illustrated with an example course in the field of information systems design.

Keywords: Distance education, interaction in education, course design.

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Authors: Thamo Sutharssan, Diogo Montalvao, Yong Chen, Wen-Chung Wang, Claudia Pisac

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A combined heat and power (CHP) system is an efficient and clean way to generate power (electricity). Heat produced by the CHP system can be used for water and space heating. The CHP system which uses hydrogen as fuel produces zero carbon emission. Its’ efficiency can reach more than 80% whereas that of a traditional power station can only reach up to 50% because much of the thermal energy is wasted. The other advantages of CHP systems include that they can decentralize energy generation, improve energy security and sustainability, and significantly reduce the energy cost to the users. This paper presents the economic benefits of using a CHP system in the domestic environment. For this analysis, natural gas is considered as potential fuel as the hydrogen fuel cell based CHP systems are rarely used. UK government incentives for CHP systems are also considered as the added benefit. Results show that CHP requires a significant initial investment in returns it can reduce the annual energy bill significantly. Results show that an investment may be paid back in 7 years. After the back period, CHP can run for about 3 years as most of the CHP manufacturers provide 10 year warranty.

Keywords: Combined Heat and Power, Clean Energy, Hydrogen Fuel Cell, Economic Analysis of CHP, Zero Emission.

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Authors: B. Gopal, Pannala Krishna Murthy, G. N. Sreenivas

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The increasing demand of electric power is giving an emphasis on the need for the maximum utilization of renewable energy sources. On the other hand maintaining power quality to satisfaction of utility is an essential requirement. In this paper the design aspects of a Unified Power Quality Conditioner integrated with photovoltaic system in a distributed generation is presented. The proposed system consist of series inverter, shunt inverter are connected back to back on the dc side and share a common dc-link capacitor with Distributed Generation through a boost converter. The primary task of UPQC is to minimize grid voltage and load current disturbances along with reactive and harmonic power compensation. In addition to primary tasks of UPQC, other functionalities such as compensation of voltage interruption and active power transfer to the load and grid in both islanding and interconnected mode have been addressed. The simulation model is design in MATLAB/ Simulation environment and the results are in good agreement with the published work.

Keywords: Distributed Generation(DG), Interconnected mode, Islanding mode, Maximum power point tracking (MPPT), Power Quality (PQ), Unified power quality conditioner (UPQC), Photovoltaic array (PV).

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Authors: Ahmed M. Hemeida, Wael A. Farag, Osama A. Mahgoub

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This paper focuses on developing an integrated reliable and sophisticated model for ultra large wind turbines And to study the performance and analysis of vector control on large wind turbines. With the advance of power electronics technology, direct driven multi-pole radial flux PMSG (Permanent Magnet Synchronous Generator) has proven to be a good choice for wind turbines manufacturers. To study the wind energy conversion systems, it is important to develop a wind turbine simulator that is able to produce realistic and validated conditions that occur in real ultra MW wind turbines. Three different packages are used to simulate this model, namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind simulator developed by National Renewable Energy Laboratory (NREL). The wind turbine mechanical parts are modeled by FAST (Fatigue, Aerodynamics, Structures and Turbulence) code which is also developed by NREL. Simulink is used to model the PMSG, full scale back to back IGBT converters, and the grid.

Keywords: FAST, Permanent Magnet Synchronous Generator(PMSG), TurbSim, Vector Control and Pitch Control

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Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy

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A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.

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Authors: S. Aisyah Azizan, M. Syafiq Azmi, Yuki Harada, Yoshinobu Maeda, Takaomi Matsutani

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We introduced an all-optical multicasting characteristics with wavelength conversion based on a novel all-optical triode using negative feedback semiconductor optical amplifier. This study was demonstrated with a transfer speed of 10 Gb/s to a non-return zero 231-1 pseudorandom bit sequence system. This multi-wavelength converter device can simultaneously provide three channels of output signal with the support of non-inverted and inverted conversion. We studied that an all-optical multicasting and wavelength conversion accomplishing cross gain modulation is effective in a semiconductor optical amplifier which is effective to provide an inverted conversion thus negative feedback. The relationship of received power of back to back signal and output signals with wavelength 1535 nm, 1540 nm, 1545 nm, 1550 nm, and 1555 nm with bit error rate was investigated. It was reported that the output signal wavelengths were successfully converted and modulated with a power penalty of less than 8.7 dB, which the highest is 8.6 dB while the lowest is 4.4 dB. It was proved that all-optical multicasting and wavelength conversion using an optical triode with a negative feedback by three channels at the same time at a speed of 10 Gb/s is a promising device for the new wavelength conversion technology.

Keywords: Cross gain modulation, multicasting, negative feedback optical amplifier, semiconductor optical amplifier.

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Authors: M. Govindarajan, R. M. Chandrasekaran

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Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.

Keywords: Back propagation, classification accuracy, textmining, time complexity.

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Authors: Kalyan Kr. Mandal, Suresh Thokchom, Mithun Roy

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The present paper reports results of an experimental program conducted to study performance of fly ash based geopolymer pastes at elevated temperature. Three series of geopolymer pastes differing in Na2O content (8.5%, 10% and 11.5%) were manufactured by activating low calcium fly ash with a mixture of sodium hydroxide and sodium silicate solution. The paste specimens were subjected to temperatures as high as 900oC and the behaviour at elevated temperatures were investigated on the basis of physical appearance, weight losses, residual strength, shrinkage measurements and sorptivity tests at different temperatures. Scanning electron microscopy along with EDX and XRD tests were also conducted to examine microstructure and mineralogical changes during the thermal exposure. Specimens which were initially grey turned reddish accompanied by appearance of small cracks as the temperature increased to 900oC. Loss of weight was more in specimens manufactured with highest Na2O content. Geopolymer paste specimen containing minimum Na2O performed better than those with higher Na2O content in terms of residual compressive strength.

Keywords: Compressive strength, EDX, Elevated temperature, Fly ash, Geopolymer, Scanning electron microscopy, XRD

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Authors: N. B. Fedosenko, A.A Iatcenko, S.A. Levanov

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The paper shows some ability to manage two-phase flows arising from the use of unsteady effects. In one case, we consider the condition of fragmentation of the interface between the two components leads to the intensification of mixing. The problem is solved when the temporal and linear scale are small for the appearance of the developed mixing layer. Showing that exist such conditions for unsteady flow velocity at the surface of the channel, which will lead to the creation and fragmentation of vortices at Re numbers of order unity. Also showing that the Re is not a criterion of similarity for this type of flows, but we can introduce a criterion that depends on both the Re, and the frequency splitting of the vortices. It turned out that feature of this situation is that streamlines behave stable, and if we analyze the behavior of the interface between the components it satisfies all the properties of unstable flows. The other problem we consider the behavior of solid impurities in the extensive system of channels. Simulated unsteady periodic flow modeled breaths. Consider the behavior of the particles along the trajectories. It is shown that, depending on the mass and diameter of the particles, they can be collected in a caustic on the channel walls, stop in a certain place or fly back. Of interest is the distribution of particle velocity in frequency. It turned out that by choosing a behavior of the velocity field of the carrier gas can affect the trajectory of individual particles including force them to fly back.

Keywords: Two-phase, mixing, separating, flow control

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Authors: Jiayue Zhao, Hongjuan Wu, Guiwen Liu

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Old neighborhoods with a large elderly population depend on community-based elderly care facilities (community-based ECFs) for aging-in-place. Yet, due to scarce and scattered land, the facilities face inequitable distribution. This research uses spatial equity theory for measuring the spatial equity of community-based ECFs in old neighborhoods. Field surveys gather granular data and methods including coverage rate, Gini coefficient, Lorenz curve and G2SFCA. The findings showed that coverage is substantial but does not indicate supply is matching to demand, nor does it imply superior accessibility. The key contributions are that structuring spatial equity framework considering elderly residents’ travel behavior. This study dedicated to the international literature on spatial equity from the perspective of travel behavior and could provide valuable suggestions for the urban planning of old neighborhoods.

Keywords: Community-based ECFs, elderly residents’ travel behavior, old neighborhoods, spatial equity.

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Authors: Jahan Zeb, Muhammad Younus Javed, Usman Qayyum

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This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.

Keywords: Average filtering, Bicubic Interpolation, Neurons, vectorization.

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Authors: Narayanan Sambu Potty , Mohammad Kabir B. Mohd Akram

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Structural Integrity Management (SIM) is important for the protection of offshore crew, environment, business assets and company and industry reputation. API RP 2A contained guidelines for assessment of existing platforms mostly for the Gulf of Mexico (GOM). ISO 19902 SIM framework also does not specifically cater for Malaysia. There are about 200 platforms in Malaysia with 90 exceeding their design life. The Petronas Carigali Sdn Bhd (PCSB) uses the Asset Integrity Management System and the very subjective Risk based Inspection Program for these platforms. Petronas currently doesn-t have a standalone Petronas Technical Standard PTS-SIM. This study proposes a recommended practice for the SIM process for offshore structures in Malaysia, including studies by API and ISO and local elements such as the number of platforms, types of facilities, age and risk ranking. Case study on SMG-A platform in Sabah shows missing or scattered platform data and a gap in inspection history. It is to undergo a level 3 underwater inspection in year 2015.

Keywords: platform, assessment, integrity, risk based inspection.

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Authors: Dharmendra Chourishi “Maitraya”, Sridevi Seshadri

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Bluetooth is a personal wireless communication technology and is being applied in many scenarios. It is an emerging standard for short range, low cost, low power wireless access technology. Current existing MAC (Medium Access Control) scheduling schemes only provide best-effort service for all masterslave connections. It is very challenging to provide QoS (Quality of Service) support for different connections due to the feature of Master Driven TDD (Time Division Duplex). However, there is no solution available to support both delay and bandwidth guarantees required by real time applications. This paper addresses the issue of how to enhance QoS support in a Bluetooth piconet. The Bluetooth specification proposes a Round Robin scheduler as possible solution for scheduling the transmissions in a Bluetooth Piconet. We propose an algorithm which will reduce the bandwidth waste and enhance the efficiency of network. We define token counters to estimate traffic of real-time slaves. To increase bandwidth utilization, a back-off mechanism is then presented for best-effort slaves to decrease the frequency of polling idle slaves. Simulation results demonstrate that our scheme achieves better performance over the Round Robin scheduling.

Keywords: Piconet, Medium Access Control, Polling algorithm, Scheduling, QoS, Time Division Duplex (TDD).

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Authors: M. Farahnakian, M.R. Razfar, S. Elhami-Joosheghan

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This paper presents an approach for the determination of the optimal cutting parameters (spindle speed, feed rate, depth of cut and engagement) leading to minimum surface roughness in face milling of high silicon stainless steel by coupling neural network (NN) and Electromagnetism-like Algorithm (EM). In this regard, the advantages of statistical experimental design technique, experimental measurements, artificial neural network, and Electromagnetism-like optimization method are exploited in an integrated manner. To this end, numerous experiments on this stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness is created by using a back propogation neural network, then the optimization problem was solved by using EM optimization. Additional experiments were performed to validate optimum surface roughness value predicted by EM algorithm. It is clearly seen that a good agreement is observed between the predicted values by EM coupled with feed forward neural network and experimental measurements. The obtained results show that the EM algorithm coupled with back propogation neural network is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.

Keywords: cutting parameters, face milling, surface roughness, artificial neural network, Electromagnetism-like algorithm,

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Authors: I. Miličević, M. Hadzima Nyarko, R. Bušić, J. Simonović Radosavljević, M. Prokopijević, K. Vojisavljević

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This paper investigates the effects of different treatment methods of rubber aggregates for self-compacting concrete (SCC) on compressive strength and modulus of elasticity. SCC mixtures with 10% replacement of fine aggregate with crumb rubber by total aggregate volume and with different aggregate treatment methods were investigated. The rubber aggregate was treated in three different methods: dry process, water-soaking, and NaOH treatment plus water soaking. Properties of SCC in a fresh and hardened state were tested and evaluated. Scanning electron microscope (SEM) analysis of three different SCC patches were made and discussed. It was observed that applying the proposed NaOH plus water soaking method resulted in the improvement of fresh and hardened concrete properties. It resulted in a more uniform distribution of rubber particles in the cement matrix, a better bond between rubber particles and the cement matrix, and higher compressive strength of SCC rubberized concrete.

Keywords: Compressive strength, modulus of elasticity, NaOH treatment, rubber aggregate, self-compacting rubberized concrete, scanning electron microscope analysis.

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Authors: H. Ferfera-Harrar, T. Benhalima, D. Lerari

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Contamination of water, due to the discharge of untreated industrial wastewaters into the ecosystem, has become a serious problem for many countries. In this study, bioadsorbents based on chitosan-g-poly(acrylamide) and montmorillonite (MMt) clay (CTS-g-PAAm/MMt) hydrogel nanocomposites were prepared via free‐radical grafting copolymerization and crosslinking of acrylamide monomer (AAm) onto natural polysaccharide chitosan (CTS) as backbone, in presence of various contents of MMt clay as nanofiller. Then, they were hydrolyzed to obtain highly functionalized pH‐sensitive nanomaterials with uppermost swelling properties. Their structure characterization was conducted by X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) analyses. The adsorption performances of the developed nanohybrids were examined for removal of methylene blue (MB) cationic dye from aqueous solutions. The factors affecting the removal of MB, such as clay content, pH medium, adsorbent dose, initial dye concentration and temperature were explored. The adsorption process was found to be highly pH dependent. From adsorption kinetic results, the prepared adsorbents showed remarkable adsorption capacity and fast adsorption rate, mainly more than 88% of MB removal efficiency was reached after 50 min in 200 mg L^-1 of dye solution. In addition, the incorporating of various content of clay has enhanced adsorption capacity of CTS-g-PAAm matrix from 1685 to a highest value of 1749 mg g^-1 for the optimized nanocomposite containing 2 wt.% of MMt. The experimental kinetic data were well described by the pseudo-second-order model, while the equilibrium data were represented perfectly by Langmuir isotherm model. The maximum Langmuir equilibrium adsorption capacity (q_m) was found to increase from 2173 mg g⁻¹ until 2221 mg g⁻¹ by adding 2 wt.% of clay nanofiller. Thermodynamic parameters revealed the spontaneous and endothermic nature of the process. In addition, the reusability study revealed that these bioadsorbents could be well regenerated with desorption efficiency overhead 87% and without any obvious decrease of removal efficiency as compared to starting ones even after four consecutive adsorption/desorption cycles, which exceeded 64%. These results suggest that the optimized nanocomposites are promising as low cost bioadsorbents.

Keywords: Chitosan, clay, dye adsorption, hydrogels nanocomposites.

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Authors: Vinay Chandwani, Vinay Agrawal, Ravindra Nagar

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Artificial Neural Networks (ANN) trained using backpropagation (BP) algorithm are commonly used for modeling material behavior associated with non-linear, complex or unknown interactions among the material constituents. Despite multidisciplinary applications of back-propagation neural networks (BPNN), the BP algorithm possesses the inherent drawback of getting trapped in local minima and slowly converging to a global optimum. The paper present a hybrid artificial neural networks and genetic algorithm approach for modeling slump of ready mix concrete based on its design mix constituents. Genetic algorithms (GA) global search is employed for evolving the initial weights and biases for training of neural networks, which are further fine tuned using the BP algorithm. The study showed that, hybrid ANN-GA model provided consistent predictions in comparison to commonly used BPNN model. In comparison to BPNN model, the hybrid ANNGA model was able to reach the desired performance goal quickly. Apart from the modeling slump of ready mix concrete, the synaptic weights of neural networks were harnessed for analyzing the relative importance of concrete design mix constituents on the slump value. The sand and water constituents of the concrete design mix were found to exhibit maximum importance on the concrete slump value.

Keywords: Artificial neural networks, Genetic algorithms, Back-propagation algorithm, Ready Mix Concrete, Slump value.

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Authors: M. M. Hasan, A. S. M. A. Haseeb, R. Saidur, H. H. Masjuki

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In this investigation, anatase TiO2 thin films were grown by radio frequency magnetron sputtering on glass substrates at a high sputtering pressure and room temperature. The anatase films were then annealed at 300-600 °C in air for a period of 1 hour. To examine the structure and morphology of the films, X-ray diffraction (XRD) and atomic force microscopy (AFM) methods were used respectively. From X-ray diffraction patterns of the TiO2 films, it was found that the as-deposited film showed some differences compared with the annealed films and the intensities of the peaks of the crystalline phase increased with the increase of annealing temperature. From AFM images, the distinct variations in the morphology of the thin films were also observed. The optical constants were characterized using the transmission spectra of the films obtained by UV-VIS-IR spectrophotometer. Besides, optical thickness of the film deposited at room temperature was calculated and cross-checked by taking a cross-sectional image through SEM. The optical band gaps were evaluated through Tauc model. It was observed that TiO2 films produced at room temperatures exhibited high visible transmittance and transmittance decreased slightly with the increase of annealing temperatures. The films were found to be crystalline having anatase phase. The refractive index of the films was found from 2.31-2.35 in the visible range. The extinction coefficient was nearly zero in the visible range and was found to increase with annealing temperature. The allowed indirect optical band gap of the films was estimated to be in the range from 3.39 to 3.42 eV which showed a small variation. The allowed direct band gap was found to increase from 3.67 to 3.72 eV. The porosity was also found to decrease at a higher annealing temperature making the film compact and dense.

Keywords: Titanium dioxide, RF reactive sputtering, Structuralproperties, Surface morphology, Optical properties.

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Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

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DNA Barcode provides good sources of needed information to classify living species. The classification problem has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use the similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. However, all the used methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. In fact, our method permits to avoid the complex problem of form and structure in different classes of organisms. The empirical data and their classification performances are compared with other methods. Evenly, in this study, we present our system which is consisted of three phases. The first one, is called transformation, is composed of three sub steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. Moreover, the second phase step is an approximation; it is empowered by the use of Multi Library Wavelet Neural Networks (MLWNN). Finally, the third one, is called the classification of DNA Barcodes, is realized by applying the algorithm of hierarchical classification.

Keywords: DNA Barcode, Electron-Ion Interaction Pseudopotential, Multi Library Wavelet Neural Networks.

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Authors: Maryam Vafadar, Alireza Behrad, Saeed Akbari

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Nowadays, with the emerging of the new applications like robot control in image processing, artificial vision for visual servoing is a rapidly growing discipline and Human-machine interaction plays a significant role for controlling the robot. This paper presents a new algorithm based on spatio-temporal volumes for visual servoing aims to control robots. In this algorithm, after applying necessary pre-processing on video frames, a spatio-temporal volume is constructed for each gesture and feature vector is extracted. These volumes are then analyzed for matching in two consecutive stages. For hand gesture recognition and classification we tested different classifiers including k-Nearest neighbor, learning vector quantization and back propagation neural networks. We tested the proposed algorithm with the collected data set and results showed the correct gesture recognition rate of 99.58 percent. We also tested the algorithm with noisy images and algorithm showed the correct recognition rate of 97.92 percent in noisy images.

Keywords: Back propagation neural network, Feature vector, Hand gesture recognition, k-Nearest Neighbor, Learning vector quantization neural network, Robot control, Spatio-temporal volume, Visual servoing

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Authors: Puntani Pongsumpun, I-Ming Tang

Abstract:

The most Malaria cases are occur along Thai-Mynmar border. Mathematical model for the transmission of Plasmodium falciparum and Plasmodium vivax malaria in a mixed population of Thais and migrant Burmese living along the Thai-Myanmar Border is studied. The population is separated into two groups, Thai and Burmese. Each population is divided into susceptible, infected, dormant and recovered subclasses. The loss of immunity by individuals in the infected class causes them to move back into the susceptible class. The person who is infected with Plasmodium vivax and is a member of the dormant class can relapse back into the infected class. A standard dynamical method is used to analyze the behaviors of the model. Two stable equilibrium states, a disease-free state and an epidemic state, are found to be possible in each population. A disease-free equilibrium state in the Thai population occurs when there are no infected Burmese entering the community. When infected Burmese enter the Thai community, an epidemic state can occur. It is found that the disease-free state is stable when the threshold number is less than one. The epidemic state is stable when a second threshold number is greater than one. Numerical simulations are used to confirm the results of our model.

Keywords: Basic reproduction number, Burmese, local stability, Plasmodium Vivax malaria.

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Authors: Pramod Jagtap, Kisan Jadhav, Neha Dand

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Risperidone (RISP) is an antipsychotic agent and has low water solubility and nontargeted delivery results in numerous side effects. Hence, an attempt was made to develop SLNs hydrogel for intranasal delivery of RISP to achieve maximum bioavailability and reduction of side effects. RISP loaded SLNs composed of 1.65% (w/v) lipid mass were produced by high shear homogenization (HSH) coupled ultrasound (US) method using glycerylmonostearate (GMS) or Imwitor 900K (solid lipid). The particles were loaded with 0.2% (w/v) of the RISP & surface-tailored with a 2.02% (w/v) non-ionic surfactant Tween® 80. Optimization was done using 32 factorial design using Design Expert® software. The prepared SLNs dispersion incorporated into Polycarbophil AA1 hydrogel (0.5% w/v). The final gel formulation was evaluated for entrapment efficiency, particle size, rheological properties, X ray diffraction, in vitro diffusion, ex vivo permeation using sheep nasal mucosa and histopathological studies for nasocilliary toxicity. The entrapment efficiency of optimized SLNs was found to be 76 ± 2%, polydispersity index <0.3., particle size 278 ± 5 nm. This optimized batch was incorporated into hydrogel. The pH was found to be 6.4 ± 0.14. The rheological behaviour of hydrogel formulation revealed no thixotropic behaviour. In histopathology study, there was no nasocilliary toxicity observed in nasal mucosa after ex vivo permeation. X-ray diffraction data shows drug was in amorphous form. Ex vivo permeation study shows controlled release profile of drug.

Keywords: Ex vivo, particle size, risperidone, solid lipid nanoparticles.

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Authors: Jonmichael A. Weaver, David A. Miller

Abstract:

Ultra High Molecular Weight Polyethylene (UHMWPE) presents several distinct advantages as a material with a high strength to weight ratio, durability, and neutron stability. Understanding the change in the mechanical performance of UHMWPE due to environmental exposure is key to safety for future applications. Dyneema® HB-210, a 15 µm diameter UHMWPE multi-filament fiber laid up in a polyurethane matrix in [0/ 90]2, with a thickness of 0.17 mm is compared to the same fiber and orientation system, HB-212, with a rubber-based matrix under UV aging conditions. UV aging tests according to ASTM-G154 were performed on both HB-210 and HB-212 to interrogate the change in mechanical properties, as measured through dynamic mechanical analysis and imaged using a scanning electron microscope. These results showed a decrease in both the storage modulus and loss modulus of the aged material compared to the unaged, even though the tan δ slightly increased. Material degradation occurred at a higher rate in Dyneema® HB-212 compared to HB-210. The HB-210 was characterized for the effects of 100 hours of UV aging via dynamic mechanical analysis. Scanning electron microscope images were taken of the HB-210 and HB-212 to identify the primary damage mechanisms in the matrix. Embrittlement and matrix spall were the products of prolonged UV exposure and erosion, resulting in decreased mechanical properties.

Keywords: Composite materials, material characterization, UV aging, UHMWPE.

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Authors: Alireza Sadrmomtaz

Abstract:

Positron emission particle tracking (PEPT) is a technique in which a single radioactive tracer particle can be accurately tracked as it moves. A limitation of PET is that in order to reconstruct a tomographic image it is necessary to acquire a large volume of data (millions of events), so it is difficult to study rapidly changing systems. By considering this fact, PEPT is a very fast process compared with PET. In PEPT detecting both photons defines a line and the annihilation is assumed to have occurred somewhere along this line. The location of the tracer can be determined to within a few mm from coincident detection of a small number of pairs of back-to-back gamma rays and using triangulation. This can be achieved many times per second and the track of a moving particle can be reliably followed. This technique was invented at the University of Birmingham [1]. The attempt in PEPT is not to form an image of the tracer particle but simply to determine its location with time. If this tracer is followed for a long enough period within a closed, circulating system it explores all possible types of motion. The application of PEPT to industrial process systems carried out at the University of Birmingham is categorized in two subjects: the behaviour of granular materials and viscous fluids. Granular materials are processed in industry for example in the manufacture of pharmaceuticals, ceramics, food, polymers and PEPT has been used in a number of ways to study the behaviour of these systems [2]. PEPT allows the possibility of tracking a single particle within the bed [3]. Also PEPT has been used for studying systems such as: fluid flow, viscous fluids in mixers [4], using a neutrally-buoyant tracer particle [5].

Keywords: PET, BGO, Particle Tracking, ECAT 931, List mode, PEPT.

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