Search results for: EB thermal processing

Authors: Ahmed. S. Alasmari, M. S. Soliman, Magdy M. El-Rayes

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This study focuses on the effect of the addition of magnesium (Mg) and silver (Ag) on the mechanical properties of aluminum based alloys. The alloying elements will be added at different levels using the factorial design of experiments of 2²; the two factors are Mg and Ag at two levels of concentration. The superior mechanical properties of the produced Al-Cu-Mg-Ag alloys after aging will be resulted from a unique type of precipitation named as Ω-phase. The formed precipitate enhanced the tensile strength and thermal stability. This paper further investigated the microstructure and mechanical properties of as cast Al–Cu–Mg–Ag alloys after being complete homogenized treatment at 520 °C for 8 hours followed by isothermally age hardening process at 190 °C for different periods of time. The homogenization at 520 °C for 8 hours was selected based on homogenization study at various temperatures and times. The alloys’ microstructures were studied by using optical microscopy (OM). In addition to that, the fracture surface investigation was performed using a scanning electronic microscope (SEM). Studying the microstructure of aged Al-Cu-Mg-Ag alloys reveal that the grains are equiaxed with an average grain size of about 50 µm. A detailed fractography study for fractured surface of the aged alloys exhibited a mixed fracture whereby the random fracture suggested crack propagation along the grain boundaries while the dimples indicated that the fracture was ductile. The present result has shown that alloy 5 has the highest hardness values and the best mechanical behaviors.

Keywords: precipitation hardening, aluminum alloys, aging, design of experiments, analysis of variance, heat treatments

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Kai Liua, Hongbo Sua, Weimin Wangb, Hong Liangb

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Urban heat island (UHI) has attracted attention around the world since they profoundly affect human life and climatological. Better understanding the effects of landscape pattern on UHI is crucial for improving the ecological security and sustainability of cities. This study aims to investigate how landscape composition and configuration would affect UHI in Shenzhen, China, based on the analysis of land surface temperature (LST) in relation landscape metrics, mainly with the aid of three new satellite sensors launched by China. HJ-1B satellite system was utilized to estimate surface temperature and comprehensively explore the urban thermal spatial pattern. The landscape metrics of the high spatial resolution remote sensing satellites (GF-1 and ZY-3) were compared and analyzed to validate the performance of the new launched satellite sensors. Results show that the mean LST is correlated with main landscape metrics involving class-based metrics and landscape-based metrics, suggesting that the landscape composition and the spatial configuration both influence UHI. These relationships also reveal that urban green has a significant effect in mitigating UHI in Shenzhen due to its homogeneous spatial distribution and large spatial extent. Overall, our study not only confirm the applicability and effectiveness of the HJ-1B, GF-1 and ZY-3 satellite system for studying UHI but also reveal the impacts of the urban spatial structure on UHI, which is meaningful for the planning and management of the urban environment.

Keywords: urban heat island, Shenzhen, new remote sensing sensor, remote sensing satellites

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Authors: M. Javahar, H. B. Dong

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Single crystal components manufactured using Ni-base Superalloys are routinely used in the hot sections of aero engines and industrial gas turbines due to their outstanding high temperature strength, toughness and resistance to degradation in corrosive and oxidative environments. To control the quality of the single crystal turbine blades, particular attention has been paid to grain selection, which is used to obtain the single crystal morphology from a plethora of columnar grains. For this purpose, different designs of grain selectors are employed and the most common type is the spiral grain selector. A typical spiral grain selector includes a starter block and a spiral (helix) located above. It has been found that the grains with orientation well aligned to the thermal gradient survive in the starter block by competitive grain growth while the selection of the single crystal grain occurs in the spiral part. In the present study, 2D spiral selectors with different geometries were designed and produced using a state-of-the-art Bridgeman Directional Solidification casting furnace to investigate the competitive growth during grain selection in 2d grain selectors. The principal advantage of using a 2-D selector is to facilitate the wax injection process in investment casting by enabling significant degree of automation. The automation within the process can be derived by producing 2D grain selector wax patterns parts using a split die (metal mold model) coupled with wax injection stage. This will not only produce the part with high accuracy but also at an acceptable production rate.

Keywords: grain selector, single crystal, directional solidification, CMSX-4 superalloys, investment casting

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Authors: Sanjeev Kumar Sharma, Arnab Mondal, Ranjit Kumar Upadhyay

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Excitable cells often produce different oscillatory activities that help us to understand the transmitting and processing of signals in the neural system. We consider a FitzHugh-Rinzel (FH-R) model and studied the different dynamics of the model by considering the parameter c as the predominant parameter. The model exhibits different types of neuronal responses such as regular spiking, mixed-mode bursting oscillations (MMBOs), elliptic bursting, etc. Based on the bifurcation diagram, we consider the three regimes (MMBOs, elliptic bursting, and quiescent state). An analytical treatment for the occurrence of the supercritical Hopf bifurcation is studied. Further, we extend our study to a network of a hundred neurons by considering the bi-directional synaptic coupling between them. In this article, we investigate the alternation of spiking propagation and bursting phenomena of an uncoupled and coupled FH-R neurons. We explore that the complete graph of heterogenous desynchronized neurons can exhibit different types of bursting oscillations for certain coupling strength. For higher coupling strength, all the neurons in the network show complete synchronization.

Keywords: excitable neuron model, spiking-bursting, stability and bifurcation, synchronization networks

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Authors: Adrian Keith Caamino, Sina Shakibania, Lena Sunqvist-Öqvist, Jan Rosenkranz, Yousef Ghorbani

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Feldspar minerals are one of the main components of the earth’s crust. They are tectosilicate, meaning that they mainly contain aluminum and silicon. Besides aluminum and silicon, they contain either potassium, sodium, or calcium. Accordingly, feldspar minerals are categorized into three main groups: K-feldspar, Na-feldspar, and Ca-feldspar. In recent years, the trend to use K-feldspar has grown tremendously, considering its potential to produce potash and alumina. However, the feldspar minerals, in general, are difficult to decompose for the dissolution of their metallic components. Several methods, including intensive milling, leaching under elevated pressure and temperature, thermal pretreatment, and the use of corrosive leaching reagents, have been proposed to improve its low dissolving efficiency. In this study, as part of the POTASSIAL EU project, to overcome the low dissolution efficiency of the K-feldspar components, mechanical activation using intensive milling followed by leaching using hydrochloric acid (HCl) was practiced. Grinding operational parameters, namely time, rotational speed, and ball-to-sample weight ratio, were studied using the Taguchi optimization method. Then, the mineralogy of the grinded samples was analyzed using a scanning electron microscope (SEM) equipped with automated quantitative mineralogy. After grinding, the prepared samples were subjected to HCl leaching. In the end, the dissolution efficiency of the main elements and impurities of different samples were correlated to the mineralogical characterization results. K-feldspar component dissolution is correlated with ore mineralogy, which provides insight into how to best optimize leaching conditions for selective dissolution. Further, it will have an effect on purifying steps taken afterward and the final value recovery procedures

Keywords: K-feldspar, grinding, automated mineralogy, impurity, leaching

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Authors: Kemal Polat

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In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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Authors: Kanit Aroonrat, Somchai Wongwises

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A heat exchanger is one of the vital parts in a wide variety of applications. The tube with surface modification is generally referred to as an enhanced tube. With this, the thermal performance of the heat exchanger is improved. A dimpled tube is one of many kinds of enhanced tube. The heat transfer and pressure drop of two-phase flow inside dimpled tubes have received little attention in the literature, despite of having an important role in the development of refrigeration and air conditioning systems. As a result, the main aim of this study is to investigate the condensation heat transfer and pressure drop of refrigerant-134a flowing inside dimpled tubes. The test section is a counter-flow double-tube heat exchanger, which the refrigerant flows in the inner tube and water flows in the annulus. The inner tubes are one smooth tube and three dimpled tubes with different helical pitches. All test tubes are made from copper with an inside diameter of 8.1 mm and length of 1500 mm. The experiments are conducted over mass fluxes ranging from 300 to 500 kg/m²s, heat flux ranging from 10 to 20 kW/m², and condensing temperature ranging from 40 to 50 ˚C. The results show that all dimpled tubes provide higher heat transfer coefficient and frictional pressure drop compared to the smooth tube. In addition, the heat transfer coefficient and frictional pressure drop increase with decreasing of helical pitch. It can be observed that the dimpled tube with lowest helical pitch yields the heat transfer enhancement in the range of 60-89% with the frictional pressure drop increase of 289-674% in comparison to the smooth tube.

Keywords: condensation, dimpled tube, heat transfer, pressure drop

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Authors: Maryam Sadeghi, Claude Bazin, Daniel Hodouin, Laura Perez Barnuevo

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The performance of a separation process is usually evaluated using performance indices calculated from elemental assays readily available from the chemical analysis laboratory. However, the separation process performance is essentially related to the properties of the minerals that carry the elements and not those of the elements. Since elements or metals can be carried by valuable and gangue minerals in the ore and that each mineral responds differently to a mineral processing method, the use of only elemental assays could lead to erroneous or uncertain conclusions on the process performance. This paper discusses the advantages of using performance indices calculated from minerals content, such as minerals recovery, for process performance assessments. A method is presented that uses elemental assays to estimate the minerals content of the solids in various process streams. The method combines the stoichiometric composition of the minerals and constraints of mass conservation for the minerals through the concentration process to estimate the minerals content from elemental assays. The advantage of assessing a concentration process using mineral based performance indices is illustrated for an iron ore concentration circuit.

Keywords: data reconciliation, iron ore concentration, mineral composition, process performance assessment

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Authors: J. Kazior, A. Szewczyk-Nykiel, T. Pieczonka, M. Laska

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Aluminium alloys are an important class of engineering materials for structural applications. This is due to the fact that these alloys have many interesting properties, namely, low density, high ratio of strength to density, good thermal and electrical conductivity, good corrosion resistance as well as extensive capabilities for shaping processes. In case of classical PM technology a particular attention should be paid to the selection of appropriate parameters of compacting and sintering processes and to keeping them. The latter need arises from the high sensitivity of aluminium based alloy powders on any fluctuation of technological parameters, in particular those related to the temperature-time profile and gas flow. Only then the desired sintered compacts with residual porosity may be produced. Except high mechanical properties, the other profitable properties of almost fully dense sintered components could be expected. Among them is corrosion resistance, rarely investigated on PM aluminium alloys. Thus, in the current study the Alumix 431/D commercial, press-ready grade powder was used for this purpose. Sintered compacts made of it in different conditions (isothermal sintering temperature, gas flow rate) were subjected to corrosion experiments in 0,1 M and 0,5 M NaCl solutions. The potentiodynamic curves were used to establish parameters characterising the corrosion resistance of sintered Alumix 431/D powder, namely, the corrosion potential, the corrosion current density, the polarization resistance, the breakdown potential. The highest value of polarization resistance, the lowest value of corrosion current density and the most positive corrosion potential was obtained for Alumix431/D powder sintered at 600°C and for highest protective gas flow rate.

Keywords: aluminium alloys, sintering, corrosion resistance, industry

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Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud

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The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.

Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method

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Authors: Mohammed Adamu Musa, Shehu Saminu Babba

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The technological trend towards waste utilization and cost reduction in industrial processing has attracted use of Rice Husk as a value added material. Both rice husk (RH) and Rice Husk Ash (RHA) has been found suitable for wide range of domestic as well as industrial applications. Therefore, the purpose of this research is to produce high grade sodium silicate from rice husk ash by considering the effect of temperature and time of heating as the process variables. The experiment was performed by heating the rice husk at temperatures 500 °C, 600 °C, 700 °C and 800 °C and time 60min, 90min, 120min and 150min were used to obtain the ash. 1.0M of aqueous sodium hydroxide solution was used to dissolve the silicate from the ash, which contained crude sodium silicate. In addition, the ash was neutralized by adding 5M of HCL until the pH reached 3.5 to give silica gel. At 6000C and 120mins, 94.23% silica was obtained from the RHA. At higher temperatures (700 °C and 800 °C) the percentage yield of silica reduced due to surface melting and carbon fixation in the lattice caused by presence of potassium. For this research, 600 °C is considered to be the optimum temperature for silica production from RHA. Silica produced from RHA can generate aggregate value and can be used in areas such as pulp and paper, plastic and rubber reinforcement industries.

Keywords: burning, rice husk, rice husk ash, silica, silica gel, temperature

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: Sadegh Sadeghi, Negar Shabani

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From a thermal point of view, zeotropic mixtures are likely to be more efficient than azeotropic fluids in low-temperature thermodynamic cycles due to their suitable boiling characteristics. In this study, performance of a low-temperature Kalina cycle with R717/water working fluid used in different existing power plants is mathematically investigated. To analyze the behavior of the cycle, mass conservation, energy conservation, and exergy balance equations are presented. With regard to the similarity in molar mass of R717 (17.03 gr/mol) and water (18.01 gr/mol), there is no need to alter the size of Kalina system components such as turbine and pump. To optimize the cycle energy and exergy efficiencies simultaneously, a constrained multi-objective optimization is carried out applying an Artificial Bee Colony algorithm. The main motivation behind using this algorithm lies on its robustness, reliability, remarkable precision and high–speed convergence rate in dealing with complicated constrained multi-objective problems. Convergence rates of the algorithm for calculating the optimal energy and exergy efficiencies are presented. Subsequently, due to the importance of exergy concept in Kalina cycles, exergy destructions occurring in the components are computed. Finally, the impacts of pressure, temperature, mass fraction and mass flow rate on the energy and exergy efficiencies are elaborately studied.

Keywords: artificial bee colony algorithm, binary zeotropic mixture, constrained multi-objective optimization, energy efficiency, exergy efficiency, Kalina cycle

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Authors: Senthil Rajan Dharmalingam, Shamala Nadaraju, Srinivasan Ramamurthy

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Doxorubicin is the most widely used anticancer drugs in chemotherapy treatment. However, problems related to the development of multidrug resistance (MDR) and acute cardiotoxicity have led researchers to investigate alternative forms of administering doxorubicin for cancer therapy. Several methods have been attempted to overcome MDR, including the co-administration of a chemosensitizer inhibiting the efflux caused by ATP binding cassette transporters with anticancer drugs, and the bypass of the efflux mechanism. Co encapsulation of doxorubicin (Dox) and cyclosporine A (CSA) into poly (DL-lactide-co-glycolide) nanoparticles was emulsification-solvent evaporation method using polyvinyl alcohol as emulsion stabilizers. The Dox-CSA loaded nanoparticles were evaluated for particle size, zeta potential and PDI by light scattering analysis and thermal characterizations by differential scanning calorimetry (DSC). Loading efficiency (LE %) and in-vitro dissolution samples were evaluated by developed and validated HPLC method. The optimum particle size obtained is 298.6.8±39.4 nm and polydispersity index (PDI) is 0.098±0.092. Zeta potential is found to be -29.9±4.23. Optimum pH to increase Dox LE% was found 7.1 which gave 42.5% and 58.9% increase of LE% for pH 6.6 and pH 8.6 compared respectively. LE% achieved for Dox is 0.07±0.01 % and CSA is 0.09±0.03%. Increased volume of PVA and weight of PLGA shows increase in size of nanoparticles. DSC thermograms showed shift in the melting peak for the nanoparticles compared to Dox and CSA indicating encapsulation of drugs. In conclusion, these preliminary studies showed the feasibility of PLGA nanoparticles to entrap Dox and CSA and require future in-vivo studies to be performed to establish its potential.

Keywords: doxorubicin, cyclosporine, PLGA, nanoparticles

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Authors: Sitthichai Laisema, Panita Wannapiroon

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This study is a research and development which is intended to: 1) design ubiquitous collaborative learning activities with virtual teams using CPS processes to develop creative thinking and collaboration skills, and 2) assess the suitability of the ubiquitous collaborative learning activities. Its methods are divided into 2 phases. Phase 1 is the design of ubiquitous collaborative learning activities with virtual teams using CPS processes, phase 2 is the assessment of the suitability of the learning activities. The samples used in this study are 5 professionals in the field of learning activity design, ubiquitous learning, information technology, creative thinking, and collaboration skills. The results showed that ubiquitous collaborative learning activities with virtual teams using CPS processes to develop creative thinking and collaboration skills consist of 3 main steps which are: 1) preparation before learning, 2) learning activities processing and 3) performance appraisal. The result of the learning activities suitability assessment from the professionals is in the highest level.

Keywords: ubiquitous learning, collaborative learning, virtual team, creative problem solving

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Authors: Kazuaki Shiraishi, Narumitsu Asai, Tsukasa Kitahara, Sosuke Mieno, Takaharu Kameoka

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The purpose of this research is to facilitate productivity advances in agriculture. To accomplish this, we developed an automatic three-dimensional (3D) recording system for growth of field crops that consists of a number of inexpensive modules: a very low-cost stereo camera, a couple of ZigBee wireless modules, a Raspberry Pi single-board computer, and a third generation (3G) wireless communication module. Our system uses an inexpensive Web stereo camera in order to keep total costs low. However, inexpensive video cameras record low-resolution images that are very noisy. Accordingly, in order to resolve these problems, we adopted a deep learning method. Based on the results of extended period of time operation test conducted without the use of an external power supply, we found that by using Super-Resolution Convolutional Neural Network method, our system could achieve a balance between the competing goals of low-cost and superior performance. Our experimental results showed the effectiveness of our system.

Keywords: 3D plant data, automatic recording, stereo camera, deep learning, image processing

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Authors: Khan Farhan Rafat, M. Junaid Hussain

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Seamless modification of an entity for the purpose of hiding a message of significance inside its substance in a manner that the embedding remains oblivious to an observer is known as steganography. Together with today's pervasive registering frameworks, steganography has developed into a science that offers an assortment of strategies for stealth correspondence over the globe that must, however, need a critical appraisal from security breach standpoint. Microsoft Word is amongst the preferably used word processing software, which comes as a part of the Microsoft Office suite. With a user-friendly graphical interface, the richness of text editing, and formatting topographies, the documents produced through this software are also most suitable for stealth communication. This research aimed not only to epitomize the fundamental concepts of steganography but also to expound on the utilization of Microsoft Word document as a carrier for furtive message exchange. The exertion is to examine contemporary message hiding schemes from security aspect so as to present the explorative discoveries and suggest enhancements which may serve a wellspring of information to encourage such futuristic research endeavors.

Keywords: hiding information in plain sight, stealth communication, oblivious information exchange, conceal, steganography

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Authors: F. Uriel, M. M. Fernandez Liporace

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In the last decade, academic achievement in higher education has become a topic of agenda in Argentina, regarding the high figures of adjustment problems, academic failure and dropout, and the low graduation rates in the context of massive classes and traditional teaching methods. Psychological variables, such as perceived social support, academic motivation and learning styles and strategies have much to offer since their measurement by tests allows a proper diagnose of their influence on academic achievement. Framed in a major research, several studies analysed multiple samples, totalizing 5135 students attending Argentinean public universities. The first goal was aimed at the identification of statistically significant differences in psychological variables -perceived social support, learning styles, learning strategies, and academic motivation- by age, gender, and degree of academic advance (freshmen versus sophomores). Thus, an inferential group differences study for each psychological dependent variable was developed by means of student’s T tests, given the features of data distribution. The second goal, aimed at examining associations between the four psychological variables on the one hand, and academic achievement on the other, was responded by correlational studies, calculating Pearson’s coefficients, employing grades as the quantitative indicator of academic achievement. The positive and significant results that were obtained led to the formulation of different predictive models of academic achievement which had to be tested in terms of adjustment and predictive power. These models took the four psychological variables above mentioned as predictors, using regression equations, examining predictors individually, in groups of two, and together, analysing indirect effects as well, and adding the degree of academic advance and gender, which had shown their importance within the first goal’s findings. The most relevant results were: first, gender showed no influence on any dependent variable. Second, only good achievers perceived high social support from teachers, and male students were prone to perceive less social support. Third, freshmen exhibited a pragmatic learning style, preferring unstructured environments, the use of examples and simultaneous-visual processing in learning, whereas sophomores manifest an assimilative learning style, choosing sequential and analytic processing modes. Despite these features, freshmen have to deal with abstract contents and sophomores, with practical learning situations due to study programs in force. Fifth, no differences in academic motivation were found between freshmen and sophomores. However, the latter employ a higher number of more efficient learning strategies. Sixth, freshmen low achievers lack intrinsic motivation. Seventh, models testing showed that social support, learning styles and academic motivation influence learning strategies, which affect academic achievement in freshmen, particularly males; only learning styles influence achievement in sophomores of both genders with direct effects. These findings led to conclude that educational psychologists, education specialists, teachers, and universities must plan urgent and major changes. These must be applied in renewed and better study programs, syllabi and classes, as well as tutoring and training systems. Such developments should be targeted to the support and empowerment of students in their academic pathways, and therefore to the upgrade of learning quality, especially in the case of freshmen, male freshmen, and low achievers.

Keywords: academic achievement, academic motivation, coping, learning strategies, learning styles, perceived social support

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Authors: Awatef Hicheur Cairns, Billel Gueni, Hind Hafdi, Christian Joubert, Nasser Khelifa

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Given the ever changing needs of the job markets, education and training centers are increasingly held accountable for student success. Therefore, education and training centers have to focus on ways to streamline their offers and educational processes in order to achieve the highest level of quality in curriculum contents and managerial decisions. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to discover, analyze and provide a visual representation of complete educational processes. In this paper, we present our distributed computation platform which allows different education centers and institutions to load their data and access to advanced data mining and process mining services. To achieve this, we present also a comparative study of the different clustering techniques developed in the context of process mining to partition efficiently educational traces. Our goal is to find the best strategy for distributing heavy analysis computations on many processing nodes of our platform.

Keywords: educational process mining, distributed process mining, clustering, distributed platform, educational data mining, ProM

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Authors: Anurag Jain, Rajneesh Kumar

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Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, join idle queue, join shortest queue, load balancing, task scheduling

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Authors: Fares Khalfallah, Zakaria Boumerzoug, Selvarajan Rajakumar, Elhadj Raouache

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The ceramic-aluminum bond is strongly present in industrial tools, due to the need to combine the properties of metals, such as ductility, thermal and electrical conductivity, with ceramic properties like high hardness, corrosion and wear resistance. In recent years, some joining techniques have been developed to achieve a good bonding between these materials such as brazing, diffusion bonding, ultrasonic joining and friction welding. In this work, AA1100 aluminum alloy rods were welded with Alumina 99.9 wt% ceramic rods, by friction welding. The effect of friction pressure on mechanical and structural properties of welded joints was studied. The welding was performed by direct friction welding machine. The welding samples were rotated at a constant rotational speed of 900 rpm, friction time of 4 sec, forging strength of 18 MPa, and forging time of 3 sec. Three different friction pressures were applied to 20, 34 and 45 MPa. The three-point bending test and Vickers microhardness measurements were used to evaluate the strength of the joints and investigate the mechanical properties of the welding area. The microstructure of joints was examined by optical microscopy (OM), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The results show that bending strength increased, and then decreased after reaching a maximum value, with increasing friction pressure. The SEM observation shows that the increase in friction pressure led to the appearance of cracks in the microstructure of the interface area, which is decreasing the bending strength of joints.

Keywords: welding of ceramic to aluminum, friction welding, alumina, AA1100 aluminum alloy

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Authors: Leonardo E. Pacheco, Carlos A. Díaz

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An alternative way of addressing the difficult to recover the useless heat is through an ejector refrigeration cycle for vehicles applications. A group of thermo-compressor supply the mechanical compressor function at conventional refrigeration compression system. The thermo-compressor group recovers the thermal energy from waste streams (exhaust gases product in internal combustion motors, gases burned in wellhead among others) to eliminate the power consumption of the mechanical compressor. These types of alternative cooling system (air-conditioners) present a kind of advantages in both the increase in energy efficiency and the improvement of the COP of the system being studied from their its mechanical simplicity (decrease of moving parts). An ejector refrigeration cycle represents a significant step forward in the optimization of the efficient use of energy in the process of air conditioning and an alternative to reduce the environmental impacts. On one side, with the energy recycling decreases the temperature of the gases thrown into the atmosphere, which contributes to the principal beneficiaries of the average temperature of the planet. In parallel, mitigating the environmental impact caused by the production and handling of conventional cooling fluids commonly available in the market, causing the destruction of the ozone layer. This work had studied the operation of the multiejector cooling system for a truck with a 420 HP engine at different rotation speed. The operation condition limits and the COP of multi-ejector cooling systems applied in a truck are analyzed for a variable rpm range from to 800–1800 rpm.

Keywords: ejector system, exhaust gas, multiejector cooling system, recovery energy

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Authors: Alireza Abbassi Monjezi, Mohammad Hasan Shaheed

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Flood, caused by excessive rainfall, monsoon, cyclone and tsunami is a common disaster in many countries of the world especially sea connected low-lying countries. A stand-alone self-powered water filtration module for decontamination of floodwater has been designed and modeled. A combination forward osmosis – low pressure reverse osmosis (FO-LPRO) system powered by solar photovoltaic-thermal (PVT) energy is investigated which could overcome the main barriers to water supply for remote areas and ensure off-grid filtration. The proposed system is designed to be small scale and portable to provide on-site potable water to communities that are no longer themselves mobile nor can be reached quickly by the aid agencies. FO is an osmotically driven process that uses osmotic pressure gradients to drive water across a controlled pore membrane from a feed solution (low osmotic pressure) to a draw solution (high osmotic pressure). This drops the demand for high hydraulic pressures and therefore the energy demand. There is also a tendency for lower fouling, easier fouling layer removal and higher water recovery. In addition, the efficiency of the PVT unit will be maximized through freshwater cooling which is integrated into the system. A filtration module with the capacity of 5 m3/day is modeled to treat floodwater and provide drinking water. The module can be used as a tool for disaster relief, particularly in the aftermath of flood and tsunami events.

Keywords: flood resilience, membrane desalination, portable water treatment, solar energy

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Authors: Kelly Danielly Da Silva Alcantara, Daniel Fernando Molina Junqueira, Graziella Colato Antonio

Abstract:

The Law No. 12,305/10, established by the National Solid Waste Policy (PNRS), provides major changes in the management and managing scenario of solid waste in Brazil. The PNRS established since changes from population behavior as environmental and the consciousness and commitment of the companies with the waste produced. The objective of this project is to conduct a benchmarking study of the management models of Waste Management Municipal Solid (MSW) in national and international levels emphasizing especially in the European Union (Portugal, France and Germany), which are reference countries in energy development, sustainability and consequently recovery of waste generated. The management that encompasses all stages that are included in this sector will be analyzed by benchmarking, as the collection, transportation, processing/treatment and final disposal of waste. Considering the needs to produce clean energy in Brazil, this study will allow the determination to the best treatment of the waste in order to reduce the amount of waste and increase the lifetime of the landfill. Finally, it intends to identify the energy recovery potential through a study analysis of economic viability, energy and sustainable based on a holistic approach.

Keywords: benchmarking, energy recovery, landfill, municipal solid waste

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Authors: Julien Romieux, Fabio Verdicchio

Abstract:

Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: cooperative signal processing, signal representation and approximation, power management, wireless sensor networks

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Authors: Jean-Philippe Gagnon, Benjamin Saute, Stéphane Boubanga-Tombet

Abstract:

Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. However, it is well known that most combustion gases such as carbon dioxide (CO₂), water vapor (H₂O), and carbon monoxide (CO) selectively absorb/emit infrared radiation at discrete energies, i.e., over a very narrow spectral range. Therefore, temperature profiles of most combustion processes derived from conventional broadband imaging are inaccurate without prior knowledge or assumptions about the spectral emissivity properties of the combustion gases. Using spectral filters allows estimating these critical emissivity parameters in addition to providing selectivity regarding the chemical nature of the combustion gases. However, due to the turbulent nature of most flames, it is crucial that such information be obtained without sacrificing temporal resolution. For this reason, Telops has developed a time-resolved multispectral imaging system which combines a high-performance broadband camera synchronized with a rotating spectral filter wheel. In order to illustrate the benefits of using this system to characterize combustion experiments, measurements were carried out using a Telops MS-IR MW on a very simple combustion system: a wood fire. The temperature profiles calculated using the spectral information from the different channels were compared with corresponding temperature profiles obtained with conventional broadband imaging. The results illustrate the benefits of the Telops MS-IR cameras for the characterization of laminar and turbulent combustion systems at a high temporal resolution.

Keywords: infrared, multispectral, fire, broadband, gas temperature, IR camera

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

Abstract:

Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: M. A. Ferhat, M. N. Boukhatem, F. Chemat

Abstract:

Microwave Clevenger or microwave accelerated distillation (MAD) is a combination of microwave heating and distillation, performed at atmospheric pressure without added any solvent or water. Isolation and concentration of volatile compounds are performed by a single stage. MAD extraction of orange essential oil was studied using fresh orange peel from Valencia late cultivar oranges as the raw material. MAD has been compared with a conventional technique, which used a Clevenger apparatus with hydro-distillation (HD). MAD and HD were compared in term of extraction time, yields, chemical composition and quality of the essential oil, efficiency and costs of the process. Extraction of essential oils from orange peels with MAD was better in terms of energy saving, extraction time (30 min versus 3 h), oxygenated fraction (11.7% versus 7.9%), product yield (0.42% versus 0.39%) and product quality. Orange peels treated by MAD and HD were observed by scanning electronic microscopy (SEM). Micrographs provide evidence of more rapid opening of essential oil glands treated by MAD, in contrast to conventional hydro-distillation.

Keywords: clevenger, microwave, extraction; hydro-distillation, essential oil, orange peel

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Authors: J. O. Akinyele, R. W. Salim, K. O. Oikelome, O. T. Olateju

Abstract:

Rice Husk (RH) is the major byproduct in the processing of paddy rice. The management of this waste has become a big challenge to some of the rice producers, some of these wastes are left in open dumps while some are burn in the open space, and these two actions have been contributing to environmental pollution. This study evaluates an alternative waste management of this agricultural product for use as a civil engineering material. The RH was burn in a controlled environment to form Rice Husk Ash (RHA). The RHA was mix with lateritic clay at 0, 2, 4, 6, 8, and 10% proportion by weight. Chemical test was conducted on the open burn and controlled burn RHA with the lateritic clay. Physical test such as particle size distribution, Atterberg limits test, and density test were carried out on the mix material. The chemical composition obtained for the RHA showed that the total percentage compositions of Fe2O3, SiO2 and Al2O3 were found to be above 70% (class “F” pozzolan) which qualifies it as a very good pozzolan. The coefficient of uniformity (Cu) was 8 and coefficient of curvature (Cc) was 2 for the soil sample. The Plasticity Index (PI) for the 0, 2, 4, 6, 8. 10% was 21.0, 18.8, 16.7, 14.4, 12.4 and 10.7 respectively. The work concluded that RHA can be effectively used in hydraulic barriers and as a stabilizing agent in soil stabilization.

Keywords: rice husk ash, pozzolans, paddy rice, lateritic clay

Procedia PDF Downloads 321