Search results for: learning effect

Authors: A. Khalique, T. Naseem, N. Haque, Z. Rasool

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The objective of current study was to investigate the effect of Bacillus subtilis PB6 (CloSTAT) as a probiotic in broilers. The corn-soybean based diet was divided into four treatment groups; T1 (basal diet with no probiotic and no Clostridium perfringens); T2 (basal diet challenged with C. perfringens without probiotic); T3 (basal diet challenged with C. perfringens having 0.05% probiotic); T4 (basal diet challenged with C. perfringens having 0.1% probiotic). Every treatment group had four replicates with 24 birds each. Body weight and feed intake were measured on weekly basis, while ileal bacterial count was recorded on day-28 following Clostridium perfringens challenge. The 0.1% probiotic treatment showed 7.2% increase in average feed intake (P=0.05) and 8% increase in body weight compared to T2. In 0.1% treatment body weight was 5% higher than T3 (P=0.02). It was also observed that 0.1% treatment had improved feed conversion ratio (1.77) on 6^th week. No effect of treatment was observed on mortality and ileal bacterial count. The current study indicated that 0.1% use of probiotic had positive response in C. perfringens challenged broilers.

Keywords: Bacillus subtilis PB6, antibiotic growth promoters, Clostridium perfringens, CloSTAT, broilers.

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Authors: R.Karami, B.Kamkari, K.Kashefi

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Applying corona wind as a novel technique can lead to a great level of heat and mass transfer augmentation by using very small amount of energy. Enhancement of forced flow evaporation rate by applying electric field (corona wind) has been experimentally evaluated in this study. Corona wind produced by a fine wire electrode which is charged with positive high DC voltage impinges to water surface and leads to evaporation enhancement by disturbing the saturated air layer over water surface. The study was focused on the effect of corona wind velocity, electrode spacing and air flow velocity on the level of evaporation enhancement. Two sets of experiments, i.e. with and without electric field, have been conducted. Data obtained from the first experiment were used as reference for evaluation of evaporation enhancement at the presence of electric field. Applied voltages ranged from corona threshold voltage to spark over voltage at 1 kV increments. The results showed that corona wind has great enhancement effect on water evaporation rate, but its effectiveness gradually diminishes by increasing air flow velocity. Maximum enhancements were 7.3 and 3.6 for air velocities of 0.125 and 1.75 m/s, respectively.

Keywords: Electrohydodynamics (EHD), corona wind, high electric field, Evaporation enhancement

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Authors: W.M.F. Wan Ishak, N. A. Rowson

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The aim of this study is to compare the effect of the ultrasonic pre treatment on the removal of heavy metals (Iron, Zinc and Copper) from Acid Mine Drainage (AMD) by Denver Cell flotation. Synthetic AMD and individual metal solutions are used in the initial experiments to optimise the process conditions for real AMD. Three different process methods, ultrasound treatment followed by Denver flotation cell, Denver flotation cell alone and ultrasonic treatments run simultaneously with the Denver flotation cell were tested for every sample. Precipitation of the metal solutions by using sodium hydroxide (NaOH) and application of the optimum frother dosage followed by flotation significantly reduced the metal content of the AMD.

Keywords: Ultrasound, Denver cell, Flotation, Heavy metals, AMD

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Authors: Mehani M., Segni L.

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The plant world is the source of many medicines. Recently, researchers have estimated that there are approximately 400,000 plant species worldwide, of which about a quarter or a third have been used by societies for medicinal purposes. The human uses of plants for thousands of years to treat various ailments, in many developing countries, much of the population trust in traditional doctors and their collections of medicinal plants to treat them. Essential oils have many therapeutic properties. In herbal medicine, they are used for their antiseptic properties against infectious diseases of fungal origin, against dermatophytes, those of bacterial origin. The aim of our study is to determine the antimicrobial effect of essential oils of the plant Trigonella focnum greacum on some pathogenic bacteria, it is a medicinal plant used in traditional therapy. The test adopted is based on the diffusion method on solid medium (Antibiogram), this method determines the sensitivity or resistance of a microorganism vis-à-vis the extract studied. Our study reveals that the essential oil of the plant Trigonella focnum greacum has a different effect on the resistance of germs. For staphiloccocus Pseudomonnas aeroginosa and Krebsilla, are moderately sensitive strains, also Escherichia coli and Candida albicans represents a high sensitivity. By against Proteus is a strain that represents a weak sensitivity.

Keywords: essential oil, microorganisme, antibiogram

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Authors: Jalal Karam, Raed Saad

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This paper studies the effect of different compression constraints and schemes presented in a new and flexible paradigm to achieve high compression ratios and acceptable signal to noise ratios of Arabic speech signals. Compression parameters are computed for variable frame sizes of a level 5 to 7 Discrete Wavelet Transform (DWT) representation of the signals for different analyzing mother wavelet functions. Results are obtained and compared for Global threshold and level dependent threshold techniques. The results obtained also include comparisons with Signal to Noise Ratios, Peak Signal to Noise Ratios and Normalized Root Mean Square Error.

Keywords: Speech Compression, Wavelets.

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Authors: H. Mirzabozorg, M. Varmazyari

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In the present article, effect of non-uniform excitation of reservoir bottom on nonlinear response of concrete gravity dams is considered. Anisotropic damage mechanics approach is used to model nonlinear behavior of mass concrete in 2D space. The tallest monolith of Pine Flat dam is selected as a case study. The horizontal and vertical components of 1967 Koyna earthquake is used to excite the system. It is found that crest response and stresses within the dam body decrease significantly when the reservoir is excited nonuniformly. In addition, the crack profiles within the dam body and in vicinity of the neck decreases.

Keywords: Concrete gravity dam, dam-reservoir-foundation interaction, traveling wave, damage mechanics.

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Authors: A. Srion, W. Thepsuwan, N. Monmaturapoj

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Two Lithium Disilicate (LD) glass ceramics based on SiO2-Li2O-K2O-Al2O3 system were prepared through a glass melting method. The glass rods were then fabricated into dental crowns via a hot pressing at 900˚C and 850˚C in order to study the effect of the pressing temperatures on the phase formation and microstructure of the glasses. Different samples of as cast glass and heat treated samples (600˚C and 700˚C) were used to press for investigating the effect of an initial microstructure on the hot pressing technique. Xray diffraction (XRD) and scanning electron microscopy (SEM) were performed to determine the phase formation and microstructure of the samples, respectively. XRD results show that the main crystalline structure was Li2Si2O5 by having Li3PO4, Li0.6Al0.6Si2O6, Li2SiO3, Ca5 (PO4)3F and SiO2 as minor phases. Glass compositions with different heat treatment temperatures exhibited a difference phase formations but have less effect during pressing. SEM micrographs showed the microstructure of Li2Si2O5 as lath-like shape in all glasses. With increasing the initial heat treatment temperature, the longer the lath-like crystals of lithium disilicate were increased especially when using glass heat treatment at 700˚C followed by pressing at 900˚C. This could be suggested that LD1 heat treatment at 700˚C which pressing at 900˚C presented the best formation by the hot pressing and compiled microstructure.

Keywords: Lithium disilicate, Hot pressing, Dental crown, Microstructure.

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Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Efficient matrix-vector multiplication with diagonal sparse matrices is pivotal in a multitude of computational domains, ranging from scientific simulations to machine learning workloads. When encoded in the conventional Diagonal (DIA) format, these matrices often induce computational overheads due to extensive zero-padding and non-linear memory accesses, which can hamper the computational throughput, and elevate the usage of precious compute and memory resources beyond necessity. The ’DIA-Adaptive’ approach, a methodological enhancement introduced in this paper, confronts these challenges head-on by leveraging the advanced parallel instruction sets embedded within Machine Learning Units (MLUs). This research presents a thorough analysis of the DIA-Adaptive scheme’s efficacy in optimizing Sparse Matrix-Vector Multiplication (SpMV) operations. The scope of the evaluation extends to a variety of hardware architectures, examining the repercussions of distinct thread allocation strategies and cluster configurations across multiple storage formats. A dedicated computational kernel, intrinsic to the DIA-Adaptive approach, has been meticulously developed to synchronize with the nuanced performance characteristics of MLUs. Empirical results, derived from rigorous experimentation, reveal that the DIA-Adaptive methodology not only diminishes the performance bottlenecks associated with the DIA format but also exhibits pronounced enhancements in execution speed and resource utilization. The analysis delineates a marked improvement in parallelism, showcasing the DIA-Adaptive scheme’s ability to adeptly manage the interplay between storage formats, hardware capabilities, and algorithmic design. The findings suggest that this approach could set a precedent for accelerating SpMV tasks, thereby contributing significantly to the broader domain of high-performance computing and data-intensive applications.

Keywords: Adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication.

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Authors: M. Olmedilla, M. R. Martinez-Torres, S. L. Toral

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Electronic Word-Of-Mouth (eWOM) communities represent today an important source of information in which more and more customers base their purchasing decisions. They include thousands of reviews concerning very different products and services posted by many individuals geographically distributed all over the world. Due to their massive audience, eWOM communities can help users to find the product they are looking for even if they are less popular or rare. This is known as the long tail effect, which leads to a larger number of lower-selling niche products. This paper analyzes the long tail effect in a well-known eWOM community and defines a tool for finding niche products unavailable through conventional channels.

Keywords: eWOM, Online user reviews, Long tail theory, Product categorization, Social Network Analysis.

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Authors: G. Bhushan

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Multilobe bearings are found to be more stable than circular bearings. A three lobe bearing also possesses good stability characteristics. Sometimes the line of action of the load does not pass through the axis of a bearing and is shifted on either side by a few degrees. Load orientation is one of the factors that affect the stability of a three lobe bearing. The effect of load orientation on the stability of a three-lobe has been discussed in this paper. The results show that stability of a three-lobe bearing supporting either rigid or flexible rotor is increased for the positive values of load orientation i.e. when the load line is shifted in the opposite direction of rotation.

Keywords: Thee-lobe bearing, load orientation, finite element method.

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: Big data, k-NN, machine learning, traffic speed prediction.

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Authors: Rizwan Nasir, Hilmi Mukhtar, Zakaria Man, Dzeti Farhah Mohshim

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Carbon dioxide has been well associated with greenhouse effect, and due to its corrosive nature it is an undesirable compound. A variety of physical-chemical processes are available for the removal of carbon dioxide. Previous attempts in this field have established alkanolamine group has the capability to remove carbon dioxide. So, this study combined the polymeric membrane and alkanolamine solutions to fabricate the amine polymeric membrane (APM) to remove carbon dioxide (CO₂). This study entails the effect of three types of amines, monoethanolamine (MEA), diethanolamine (DEA), and methyldiethanolamine (MDEA). The effect of each alkanolamine group on the morphology and performance of polyether sulfone (PES) polymeric membranes was studied. Flat sheet membranes were fabricated by solvent evaporation method by adding polymer and different alkanolamine solutions in the N-Methyl-2-pyrrolidone (NMP) solvent. The final membranes were characterized by using Field Emission Electron Microscope (FESEM), Fourier Transform Infrared (FTIR), and Thermo-Gravimetric Analysis (TGA). The membrane separation performance was studied. The PES-DEA and PES-MDEA membrane has good ability to remove carbon dioxide. 

Keywords: Amine Polymeric membrane, Alkanolamine solution, CO2 Removal, Characterization.

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Authors: A. Kamath, Z. X. Chen, C. J. Gu, F. Zheng, X. P. Wang, N. Singh, G-Q. Lo

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In this paper we use low frequency noise analysis to understand and map the current conduction path in a multi gate junctionless FinFET.  The device used in this study behaves as a gated resistor and shows excellent short channel effect suppression due to its multi gate structure. Generally for a bulk conduction device like the junctionless device studied in this work, the low frequency noise can be modelled using the mobility fluctuation model; however for this device we can also see the effect of carrier fluctuations on the LFN characteristic. The noise characteristic at different gate bias and also the possible location of the traps is explained.

Keywords: LFN analysis, junctionless, Current conduction path, FinFET.

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Authors: S. Sarumathi, P. Ranjetha, C. Saraswathy, M. Vaishnavi, S. Geetha

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Clustering is an unsupervised learning technique for aggregating data objects into meaningful classes so that intra cluster similarity is maximized and inter cluster similarity is minimized in data mining. However, no single clustering algorithm proves to be the most effective in producing the best result. As a result, a new challenging technique known as the cluster ensemble approach has blossomed in order to determine the solution to this problem. For the cluster analysis issue, this new technique is a successful approach. The cluster ensemble's main goal is to combine similar clustering solutions in a way that achieves the precision while also improving the quality of individual data clustering. Because of the massive and rapid creation of new approaches in the field of data mining, the ongoing interest in inventing novel algorithms necessitates a thorough examination of current techniques and future innovation. This paper presents a comparative analysis of various cluster ensemble approaches, including their methodologies, formal working process, and standard accuracy and error rates. As a result, the society of clustering practitioners will benefit from this exploratory and clear research, which will aid in determining the most appropriate solution to the problem at hand.

Keywords: Clustering, cluster ensemble methods, consensus function, data mining, unsupervised learning.

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Authors: A. Hani

Abstract:

In recent decades with the development of technology and lack of food sources, sewage sludge in production of human foods is inevitable. Various sources of municipal and industrial sewage sludge that is produced can provide the requirement of plant nutrients. Soils in arid, semi-arid climate of central Iran that most affected by water drainage, iron and zinc deficiencies, using of sewage sludge is helpful. Therefore, the aim of this study is investigation of sewage sludge and manure application on Ni, Pb and Cd uptake by Savory. An experiment in a randomized complete block design with three replications was performed. Sewage sludge treatments consisted of four levels, control, 15, 30, 80 tons per hectares; the manure was used in four levels of control, 20, 40 and 80 tons per hectare. Results showed that the wet and dry weights was not affected by sewage sludge using, while, manure has significant effect on them. The effect of sewage sludge on the cadmium and lead concentrations were significant. Interactions of sewage sludge and manure on dry weight values were not significant. Compare mean analysis showed that increasing the amount of sewage sludge had no significant effect on cadmium concentration and it reduced when sewage sludge usage increased. This is probably due to increased plant growth and reduced concentrations of these elements in the plant.

Keywords: Savory, lead, cadmium, sewage sludge, manure.

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Authors: M. Zerikat, S. Chekroun

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This paper proposes an effective adaptation learning algorithm based on artificial neural networks for speed control of an induction motor assumed to operate in a high-performance drives environment. The structure scheme consists of a neural network controller and an algorithm for changing the NN weights in order that the motor speed can accurately track of the reference command. This paper also makes uses a very realistic and practical scheme to estimate and adaptively learn the noise content in the speed load torque characteristic of the motor. The availability of the proposed controller is verified by through a laboratory implementation and under computation simulations with Matlab-software. The process is also tested for the tracking property using different types of reference signals. The performance and robustness of the proposed control scheme have evaluated under a variety of operating conditions of the induction motor drives. The obtained results demonstrate the effectiveness of the proposed control scheme system performances, both in steady state error in speed and dynamic conditions, was found to be excellent and those is not overshoot.

Keywords: Electric drive, Induction motor, speed control, Adaptive control, neural network, High Performance.

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Authors: N. Khleifia, A. Hannachi, N. Abbes

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In the present paper, an experimental investigation was conducted to study the thermodynamic of uranium extraction from Tunisian wet phosphoric acid using the synergistic solvent mixture of di-2-ethylhexyl phosphoric acid (DEHPA) and trioctyl phosphine oxid (TOPO) diluted in kerosene. The effect of different factors affecting the extraction process (temperature, TOPO and DEHPA concentrations) has been investigated. The obtained data of temperature effect on the extraction showed that the enthalpy change is -35.8 kJ.mol^-1. The slope analysis method was used for determining the stoichiometry of the extracted species.

Keywords: DEHPA-TOPO, extraction, phosphoric acid, stoichiometry, uranium.

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Authors: S. Odeh, E. Abdelghani

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Collaborative working environments for distance education can be considered as a more generic form of contemporary remote labs. At present, the majority of existing real laboratories are not constructed to allow the involved participants to collaborate in real time. To make this revolutionary learning environment possible we must allow the different users to carry out an experiment simultaneously. In recent times, multi-user environments are successfully applied in many applications such as air traffic control systems, team-oriented military systems, chat-text tools, multi-player games etc. Thus, understanding the ideas and techniques behind these systems could be of great importance in the contribution of ideas to our e-learning environment for collaborative working. In this investigation, collaborative working environments from theoretical and practical perspectives are considered in order to build an effective collaborative real laboratory, which allows two students or more to conduct remote experiments at the same time as a team. In order to achieve this goal, we have implemented distributed system architecture, enabling students to obtain an automated help by either a human tutor or a rule-based e-tutor.

Keywords: Collaboration environment, e-tutor, multi-user environments, socio-technical system.

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Authors: Hasan Furkan Kurt, Tugba Nur Atabey, Onat Cavit Dereli, Ahmad Salmanogli, H. Selcuk Gecim

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In the article, the main goal is to study the effect of the plasmonic properties on the photocurrent generated by a photodetector. Fundamentally, a typical photodetector is designed and simulated using the finite element methods. To utilize the plasmonic effect, gold nanoparticles with different shape, size and morphology are buried into the intrinsic region. Plasmonic effect is arisen through the interaction of the incoming light with nanoparticles by which electrical properties of the photodetector are manipulated. In fact, using plasmonic nanoparticles not only increases the absorption bandwidth of the incoming light, but also generates a high intensity near-field close to the plasmonic nanoparticles. Those properties strongly affect the generated photocurrent. The simulation results show that using plasmonic nanoparticles significantly enhances the electrical properties of the photodetectors. More importantly, one can easily manipulate the plasmonic properties of the gold nanoparticles through engineering the nanoparticles' size, shape and morphology. Another important phenomenon is plasmon-plasmon interaction inside the photodetector. It is shown that plasmon-plasmon interaction improves the electron-hole generation rate by which the rate of the current generation is severely enhanced. This is the key factor that we want to focus on, to improve the photodetector electrical properties.

Keywords: Nanoparticles, plasmonic, plasmon-plasmon interaction, plasmonic photodetector.

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Authors: Abdul Hafeez, Shahid Adeel, Ayesha Hussain

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There are number of plants species in the universe which give the protections from different diseases and give colour for the foods and textiles. The environmental condition of the universe suggested toward the ecofriendly textiles. The aim of the paper is to analyze the influence of pre & post mordanting of alum on radiated cotton fabric with Gamma Radiation of different doses by using Ipomoea indica leaves extract. Alum used as mordant with the concentration of 2, 4, 6, 8 and 10% as pre and post mordanting to observe the effect of light and colour fastness of radiated cotton. 6% of alum concentration in pre mordanting gave good colour strength 117.82 with darker in shade toward the greenish tone and in post mordanting 6% concentration gave good colour strength 102.19. The lab values show that the colour is darker in tone and gave bluish effect. Further results showed that alum gave good light and rubbing fastness on gamma radiated cotton fabric.

Keywords: Ipomoea indica, gamma radiation, alum, light fastness.

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Authors: Mohamed A. G. H. Abdalsadig, Amir Nourian, G. G. Nasr, M. Babaie

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Gas lift is one of the most common forms of artificial lift, particularly for offshore wells because of its relative down hole simplicity, flexibility, reliability, and ability to operate over a large range of rates and occupy very little space at the well head. Presently, petroleum industry is investing in exploration and development fields in offshore locations where oil and gas wells are being drilled thousands of feet below the ocean in high pressure and temperature conditions. Therefore, gas-lifted oil wells are capable of failure through gas lift valves which are considered as the heart of the gas lift system for controlling the amount of the gas inside the tubing string. The gas injection rate through gas lift valve must be controlled to be sufficient to obtain and maintain critical flow, also, gas lift valves must be designed not only to allow gas passage through it and prevent oil passage, but also for gas injection into wells to be started and stopped when needed. In this paper, smart gas lift valve has been used to investigate the effect of the valve port size, depth of injection and vertical lift performance on well productivity; all these aspects have been investigated using PROSPER simulator program coupled with experimental data. The results show that by using smart gas lift valve, the gas injection rate can be controlled which leads to improved flow performance.

Keywords: Effect of gas lift valve port size, effect water cut, and vertical flow performance.

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Authors: Ifeyinwa E. Achumba, Djamel Azzi, Rinat Khusainov

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There are three approaches to complete Bayesian Network (BN) model construction: total expert-centred, total datacentred, and semi data-centred. These three approaches constitute the basis of the empirical investigation undertaken and reported in this paper. The objective is to determine, amongst these three approaches, which is the optimal approach for the construction of a BN-based model for the performance assessment of students- laboratory work in a virtual electronic laboratory environment. BN models were constructed using all three approaches, with respect to the focus domain, and compared using a set of optimality criteria. In addition, the impact of the size and source of the training, on the performance of total data-centred and semi data-centred models was investigated. The results of the investigation provide additional insight for BN model constructors and contribute to literature providing supportive evidence for the conceptual feasibility and efficiency of structure and parameter learning from data. In addition, the results highlight other interesting themes.

Keywords: Bayesian networks, model construction, parameterlearning, structure learning, performance index, model comparison.

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Authors: A. Chellil, I. Gahlouz, S. Lecheb, A. Nour, S. Chellil, H. Mechakra, H. Kebir

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In this paper, the experimental study for the instability of a separator rotor is presented, under dynamic loading response in the harmonic analysis condition. The global measurement and analysis of vibration on the cement separator RC500 is carried, the points of measurement used are radial dots, vertical, horizontal and oblique. The measures of trends and spectral analysis for reconnaissance of the main anomalies, the main defects in the separator and manifestation, the results prove that the defects effect has a negative effect on the stability of the rotor. Experimentally the study of the rotor in transient system allowed to determine the vibratory responses due to the unbalances and various excitations.

Keywords: Rotor, experimental, defect, frequency, specter.

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Authors: Rohan Putatunda, Aryya Gangopadhyay

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Acoustic sensors, if embedded in smart street lights, can help in capturing the activities (car honking, sirens, events, traffic, etc.) in cities. Needless to say, the acoustic data from such scenarios are complex due to multiple audio streams originating from different events, and when decomposed to independent signals, the amount of retrieved data volume is small in quantity which is inadequate to train deep neural networks. So, in this paper, we address the two challenges: a) separating the mixed signals, and b) developing an efficient acoustic classifier under data paucity. So, to address these challenges, we propose an architecture with supervised deep learning, where the initial captured mixed acoustics data are analyzed with Fast Fourier Transformation (FFT), followed by filtering the noise from the signal, and then decomposed to independent signals by fast independent component analysis (Fast ICA). To address the challenge of data paucity, we propose a multi feature-based deep neural network with high performance that is reflected in our experiments when compared to the conventional convolutional neural network (CNN) and multi-layer perceptron (MLP).

Keywords: FFT, ICA, vehicle classification, multi-feature DNN, CNN, MLP.

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Authors: M. Azadbakht, E. Ghajarjazi, E. Amiri, F. Abdigaol

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In this research the effect of moisture at three levels (47, 57, and 67 w.b.%) on the physical properties of the Pofaki pea variety including, dimensions, geometric mean diameter, volume, sphericity index and the surface area was determined. The influence of different moisture levels (47, 57 and 67 w.b.%), in two loading orientation (longitudinal and transverse) and three loading speed (4,6 and 8 mm min-1) on the mechanical properties of pea such as maximum deformation, rupture force, rupture energy, toughness and the power to break the pea was investigated. It was observed in the physical properties that moisture changes were affective at 1% on, dimensions, geometric mean diameter, volume, sphericity index and the surface area. It was observed in the mechanical properties that moisture changes were effective at 1% on, maximum deformation, rupture force, rupture energy, toughness and the power to break. Loading speed was effective on maximum deformation, rupture force, rupture energy at 1% and it was effective on toughness at 5%. Loading orientation was effective on maximum deformation, rupture force, rupture energy, toughness at 1% and it was effective on power at 5%. The mutual effect of speed and orientation were effective on rupture energy at 1% and were effective on toughness at 5% probability. The mutual effect of moisture and speed were effective on rupture force and rupture energy at 1% and were effective on toughness 5% probability. The mutual effect of orientation and moisture on rupture energy and toughness were effective at 1%.

Keywords: Mechanical properties, Pea, Physical properties.

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Authors: J. P. Dubois, O. M. Abdul-Latif

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Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of medical ultrasound images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to clinical ultrasound images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected ultrasound images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (detection hypotheses) in the original images.

Keywords: LS-SVM, medical ultrasound imaging, partially developed speckle, multi-look model.

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Authors: S. Santalunai, T. Thosdeekoraphat, C. Thongsopa

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This paper presents the effect of electric field distribution which is an electric field intensity analysis. Consideration of the dielectric heating of grains and insects, the rice and rice weevils are utilized for dielectric heating analysis. Furthermore, this analysis compares the effect of electric field distribution in rice and rice weevil. In this simulation, two copper plates are used to generate the electric field for dielectric heating system and put the rice materials between the copper plates. The simulation is classified in two cases, which are case I one rice weevil is placed in the rice and case II two rice weevils are placed at different position in the rice. Moreover, the probes are located in various different positions on plate. The power feeding on this plate is optimized by using CST EM studio program of 1000 watt electrical power at 39 MHz resonance frequency. The results of two cases are indicated that the most electric field distribution and intensity are occurred on the rice and rice weevils at the near point of the probes. Moreover, the heat is directed to the rice weevils more than the rice. When the temperature of rice and rice weevils are calculated and compared, the rice weevils has the temperature more than rice is about 41.62 Celsius degrees. These results can be applied for the dielectric heating applications to eliminate insect.

Keywords: Copper plates, Electric field distribution, Dielectric heating.

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Authors: E. Bárcena-Martín, S. Pérez-Moreno

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This paper explores the extent of the gap in poverty rates between immigrant and native households in Spanish regions and assess to what extent regional differences in individual and contextual characteristics can explain the divergences in such a gap. By using multilevel techniques and European Union Survey on Income and Living Conditions, we estimate immigrant households experiments an increase of 76 per cent in the odds of being poor compared with a native one when we control by individual variables. In relation to regional differences in the risk of poverty, regionallevel variables have higher effect in the reduction of these differences than individual variables.

Keywords: Immigration, Multilevel Analysis, Poverty, Spanish Regions

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Authors: Vladimir Simovic, Matija Varga, Tonco Marusic

Abstract:

This research paper shows matrix technology models and examples of information systems in education (in the Republic of Croatia and in the Germany) in support of business, education (when learning and teaching) and e-learning. Here we researched and described the aims and objectives of the main process in education and technology, with main matrix classes of data. In this paper, we have example of matrix technology with detailed description of processes related to specific data classes in the processes of education and an example module that is support for the process: ‘Filling in the directory and the diary of work’ and ‘evaluation’. Also, on the lower level of the processes, we researched and described all activities which take place within the lower process in education. We researched and described the characteristics and functioning of modules: ‘Fill the directory and the diary of work’ and ‘evaluation’. For the analysis of the affinity between the aforementioned processes and/or sub-process we used our application model created in Visual Basic, which was based on the algorithm for analyzing the affinity between the observed processes and/or sub-processes.

Keywords: Designing, education management, information systems, matrix technology, process affinity.

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Authors: Z. Didar, A. Pourfarzad, M. H. Haddad Khodaparast

Abstract:

Nowadays, consumption of whole flours and flours with high extraction rate is recommended, because of their high amount of fibers, vitamins and minerals. Despite nutritional benefits of whole flour, concentration of some undesirable components such as phytic acid is higher than white flour. In this study, effect of several lactic acid bacteria sourdough on Toast bread is investigated. Sourdough from lactic acid bacteria (Lb. plantarum, Lb. reuteri) with different dough yield (250 and 300) is made and incubated at 30°C for 20 hour, then added to dough in the ratio of 10, 20 and 30% replacement. Breads that supplemented with Lb. plantarum sourdough had lower phytic acid. Higher replacement of sourdough and higher DY cause higher decrease in phytic acid content. Sourdough from Lb. plantarum, DY = 300 and 30% replacement cause the highest decrease in phytic acid content (49.63 mg/100g). As indicated by panelists, Lb. reuteri sourdough can present the greatest effect on overall quality score of the breads. DY reduction cause a decrease in bread quality score. Sensory score of Toast bread is 81.71 in the samples that treated with Lb. reuteri sourdough with DY = 250 and 20% replacement.

Keywords: Phytic Acid, Sourdough, Toast Bread, Whole Wheat Flour, Lactic Acid Bacteria.

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