Search results for: data mining technique

Authors: Krishnaiah Arkanti, Ramulu Malothu

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The experiments have been conducted to study the mechanical properties of commercially pure copper processing at room temperature by severe plastic deformation using equal channel angular extrusion (ECAE) through a die of 90^oangle up to 3 passes by route B_C i.e. rotating the sample in the same direction by 90^o after each pass. ECAE is used to produce from existing coarse grains to ultra-fine, equiaxed grains structure with high angle grain boundaries in submicron level by introducing a large amount of shear strain in the presence of hydrostatic pressure into the material without changing billet shape or dimension. Mechanical testing plays an important role in evaluating fundamental properties of engineering materials as well as in developing new materials and in controlling the quality of materials for use in design and construction. Yield stress, ultimate tensile stress and ductility are structure sensitive properties and vary with the structure of the material. Microhardness and tensile tests were carried out to evaluate the hardness, strength and ductility of the ECAE processed materials. The results reveal that the strength and hardness of commercially pure copper samples improved significantly without losing much ductility after each pass.

Keywords: Equal Channel Angular Extrusion, Severe Plastic Deformation, Copper, Mechanical Properties.

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Authors: Mohamed Gouskir, Belaid Bouikhalene, Hicham Aissaoui, Benachir Elhadadi

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In this paper, we present an application of Riemannian geometry for processing non-Euclidean image data. We consider the image as residing in a Riemannian manifold, for developing a new method to brain edge detection and brain extraction. Automating this process is a challenge due to the high diversity in appearance brain tissue, among different patients and sequences. The main contribution, in this paper, is the use of an edge-based anisotropic diffusion tensor for the segmentation task by integrating both image edge geometry and Riemannian manifold (geodesic, metric tensor) to regularize the convergence contour and extract complex anatomical structures. We check the accuracy of the segmentation results on simulated brain MRI scans of single T1-weighted, T2-weighted and Proton Density sequences. We validate our approach using two different databases: BrainWeb database, and MRI Multiple sclerosis Database (MRI MS DB). We have compared, qualitatively and quantitatively, our approach with the well-known brain extraction algorithms. We show that using a Riemannian manifolds to medical image analysis improves the efficient results to brain extraction, in real time, outperforming the results of the standard techniques.

Keywords: Riemannian manifolds, Riemannian Tensor, Brain Segmentation, Non-Euclidean data, Brain Extraction.

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Authors: Edison Muzenda

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The aim of this study was to compare the solubility of selected volatile organic compounds in water and silicon oil using the simple static headspace method. The experimental design allowed equilibrium achievement within 30 – 60 minutes. Infinite dilution activity coefficients and Henry-s law constants for various organics representing esters, ketones, alkanes, aromatics, cycloalkanes and amines were measured at 303K. The measurements were reproducible with a relative standard deviation and coefficient of variation of 1.3x10-3 and 1.3 respectively. The static determined activity coefficients using shaker flasks were reasonably comparable to those obtained using the gas liquid - chromatographic technique and those predicted using the group contribution methods mainly the UNIFAC. Silicon oil chemically known as polydimethysiloxane was found to be better absorbent for VOCs than water which quickly becomes saturated. For example the infinite dilution mole fraction based activity coefficients of hexane is 0.503 and 277 000 in silicon oil and water respectively. Thus silicon oil gives a superior factor of 550 696. Henry-s law constants and activity coefficients at infinite dilution play a significant role in the design of scrubbers for abatement of volatile organic compounds from contaminated air streams. This paper presents the phase equilibrium of volatile organic compounds in very dilute aqueous and polymeric solutions indicating the movement and fate of chemical in air and solvent. The successful comparison of the results obtained here and those obtained using other methods by the same authors and in literature, means that the results obtained here are reliable.

Keywords: Abatement, absorbent, activity coefficients, equilibrium, Henry's law constant.

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Authors: Wannakarn Likitrattanaporn

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The ultimate purpose of this investigation was to determine the teachers’ opinions as well as students’ opinions towards the Adapted English Lessons. The subjects of the study were 5 Thai teachers, who teach English, and 85 Grade 10 mixed-ability students at Triamudom Suksa Pattanakarn Ratchada School, Bangkok, Thailand. The research instruments included questionnaires and the informal interview. The data from the research instruments was collected and analyzed concerning linguistic principles of minimal pair and articulatory phonetics as well as teaching techniques of mimicry-memorization; vocabulary substitution drills, language pattern drills, reading comprehension exercise, practicing listening, speaking and writing skill and communicative activities; informal talk and free writing. The data was statistically compiled according to an arithmetic percentage. The results showed that the teachers and students have very highly positive opinions towards adapting linguistic principles for teaching and learning phonological accuracy. Teaching techniques provided in the Adapted English Lessons can be used efficiently in the classroom. The teachers and students have positive opinions towards them too.

Keywords: Applying linguistic principles and teaching techniques, teachers’ and students’ opinions, teaching English, the Adapted English Lessons.

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Authors: Mohammed A. Al-Manie, Mohammed I. Alkanhal

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In this paper, acoustic techniques are used to detect hidden insect infestations of date palm tress (Phoenix dactylifera L.). In particular, we use an acoustic instrument for early discovery of the presence of a destructive insect pest commonly known as the Red Date Palm Weevil (RDPW) and scientifically as Rhynchophorus ferrugineus (Olivier). This type of insect attacks date palm tress and causes irreversible damages at late stages. As a result, the infected trees must be destroyed. Therefore, early presence detection is a major part in controlling the spread and economic damage caused by this type of infestation. Furthermore monitoring and early detection of the disease can asses in taking appropriate measures such as isolating or treating the infected trees. The acoustic system is evaluated in terms of its ability for early discovery of hidden bests inside the tested tree. When signal acquisitions is completed for a number of date palms, a signal processing technique known as time-frequency analysis is evaluated in terms of providing an estimate that can be visually used to recognize the acoustic signature of the RDPW. The testing instrument was tested in the laboratory first then; it was used on suspected or infested tress in the field. The final results indicate that the acoustic monitoring approach along with signal processing techniques are very promising for the early detection of presence of the larva as well as the adult pest in the date palms.

Keywords: Acoustic emissions, acoustic sensors, nondestructivetests, Red Date Palm Weevil, signal processing..

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Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

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In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: Equivalent Martingale Measure, European Put Option, Girsanov Theorem, Martingales, Monte Carlo method, option price valuation, option price valuation formula.

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Authors: Mohammad Rohani, Gholamali Shafabakhsh, Abdolhosein Haddad, Ehsan Asnaashari

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Visual simulation has emerged as a key planning tool in built environment because it enables architects, engineers and project managers to visualize construction process evolution before the project actual commences. This provides an efficient technology for reducing time and cost through planning and controlling resources, machines and materials. With the development of infrastructure projects and the massive civil constructions such as bridges, urban tunnels and highways as well as sensitivity of their construction operations, it is very necessary to apply proper planning methods. Implementation of visual techniques into management of construction projects can provide a fundamental foundation for projects with massive activities and duplicate items. So, the purpose of this paper is to develop visual simulation management techniques for infrastructure projects such as highways bridges by the use of Four-Dimensional Computer-Aided design Models. This project simulates operational assembly-line for Box-Girder Concrete Bridges which it would be able to optimize the sequence and interaction of project activities and on the other hand, it would minimize any unintended conflicts prior to project start. In this paper, after introducing the various planning methods by building information model and concrete bridges in highways, an executive case study is demonstrated and then a visual technique (4D CAD) will be applied for the case. In the final step, the user feedback for interacting by this system evaluated according to six criteria.

Keywords: 4D application area, Box-Girder concrete bridges, CAD model, visual planning.

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Authors: S. Karabulut, A. Güllü, A. Güldas, R. Gürbüz

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This study investigates the effects of the lead angle and chip thickness variation on surface roughness during the machining of compacted graphite iron using ceramic cutting tools under dry cutting conditions. Analytical models were developed for predicting the surface roughness values of the specimens after the face milling process. Experimental data was collected and imported to the artificial neural network model. A multilayer perceptron model was used with the back propagation algorithm employing the input parameters of lead angle, cutting speed and feed rate in connection with chip thickness. Furthermore, analysis of variance was employed to determine the effects of the cutting parameters on surface roughness. Artificial neural network and regression analysis were used to predict surface roughness. The values thus predicted were compared with the collected experimental data, and the corresponding percentage error was computed. Analysis results revealed that the lead angle is the dominant factor affecting surface roughness. Experimental results indicated an improvement in the surface roughness value with decreasing lead angle value from 88° to 45°.

Keywords: CGI, milling, surface roughness, ANN, regression, modeling, analysis.

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Authors: S. Matour, M. Mahdavinejad, R. Fayaz

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Daylight utilization is a key factor in achieving visual and thermal comfort, and energy savings in integrated building design. However, lack of measured data related to this topic has become a major challenge with the increasing need for integrating lighting concepts and simulations in the early stages of design procedures. The current paper deals with the values of daylight illuminance on horizontal and south facing vertical surfaces; the data are estimated using IESNA model and measured values of the horizontal and vertical illuminance, and a regression model with an acceptable linear correlation is obtained. The resultant illuminance frequency curves are useful for estimating daylight availability on south facing surfaces in Tehran. In addition, the relationship between indirect vertical illuminance and the corresponding global horizontal illuminance is analyzed. A simple parametric equation is proposed in order to predict the vertical illumination on a shaded south facing surface. The equation correlates the ratio between the vertical and horizontal illuminance to the solar altitude and is used with another relationship for prediction of the vertical illuminance. Both equations show good agreement, which allows for calculation of indirect vertical illuminance on a south facing surface at any time throughout the year.

Keywords: Tehran daylight availability, horizontal illuminance, vertical illuminance, diffuse illuminance.

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Authors: Fatema-Tuz-Zahura, Raquib Ahsan

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Punching shear failure is usually the governing failure mode of flat plate structures. Punching failure is brittle in nature which induces more vulnerability to this type of structure. In the present study, a 3D finite element model of a flat plate with low reinforcement ratio and without any transverse reinforcement has been developed. Punching shear stress and the deflection data were obtained on the surface of the flat plate as well as through the thickness of the model from numerical simulations. The obtained data were compared with the experimental results. Variation of punching stress with respect to deflection as obtained from numerical results is found to be in good agreement with the experimental results; the range of variation of punching stress is within 5%. The numerical simulation shows an early and gradual onset of nonlinearity, whereas the same is late and abrupt as observed in the experimental results. The range of variation of punching stress for different slab thicknesses between experimental and numerical results is less than 15%. The developed numerical model is useful to complement available punching test series performed in the past. The results obtained from the numerical model will be helpful for designing retrofitting schemes of flat plates.

Keywords: Flat plate, finite element model, punching shear, reinforcement ratio.

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Authors: Simon B. N. Thompson

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Cortisol is essential to the regulation of the immune system and yawning is a pathological symptom of multiple sclerosis (MS). Electromyography activity (EMG) in the jaw muscles typically rises when the muscles are moved and with yawning is highly correlated with cortisol levels in healthy people. Saliva samples from 59 participants were collected at the start and after yawning, or at the end of the presentation of yawning-provoking stimuli, in the absence of a yawn, together with EMG data and questionnaire data: Hospital Anxiety and Depression Scale, Yawning Susceptibility Scale, General Health Questionnaire, demographic, health details. Exclusion criteria: chronic fatigue, diabetes, fibromyalgia, heart condition, high blood pressure, hormone replacement therapy, multiple sclerosis, stroke. Significant differences were found between the saliva cortisol samples for the yawners, t (23) = -4.263, p = 0.000, as compared with the non-yawners between rest and post-stimuli, which was nonsignificant. Significant evidence was found to support the Thompson Cortisol Hypothesis suggesting that rises in cortisol levels are associated with yawning. Further research is exploring the use of cortisol as an early diagnostic tool for MS. Ethics approval granted and professional code of conduct, confidentiality, and safety issues are approved therein.

Keywords: Cortisol, Multiple Sclerosis, Yawning, Thompson’s Cortisol Hypothesis.

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Authors: Saliha Gachi, Mouloud Aissani, Fouad Boubenider

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Friction Stir Welding (FSW) is a solid-state welding technique that can join material without melting the plates to be welded. In this work, we are interested to demonstrate the potentiality of FSW for joining the heat-treatable aluminum alloy 2024-T3 which is reputed as difficult to be welded by fusion techniques. Thereafter, the FSW joint is compared with another one obtained from a conventional fusion process Tungsten Inert Gas (TIG). FSW welds are made up using an FSW tool mounted on a milling machine. Single pass welding was applied to fabricated TIG joint. The comparison between the two processes has been made on the temperature evolution, mechanical and microstructure behavior. The microstructural examination revealed that FSW weld is composed of four zones: Base metal (BM), Heat affected zone (HAZ), Thermo-mechanical affected zone (THAZ) and the nugget zone (NZ). The NZ exhibits a recrystallized equiaxed refined grains that induce better mechanical properties and good ductility compared to TIG joint where the grains have a larger size in the welded region compared with the BM due to the elevated heat input. The microhardness results show that, in FSW weld, the THAZ contains the lowest microhardness values and increase in the NZ; however, in TIG process, the lowest values are localized on the NZ.

Keywords: Friction stir welding, tungsten inert gaz, aluminum, microstructure.

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Authors: R. Kamalakannan, N. Ravi Kumar

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The global energy consumption is increasing persistently and need for distributed power generation through renewable energy is essential. To meet the power requirements for consumers without any voltage fluctuations and losses, modeling and design of multilevel inverter with Flexible AC Transmission System (FACTS) capability is presented. The presented inverter is provided with 13-level cascaded H-bridge topology of Insulated Gate Bipolar Transistor (IGBTs) connected along with inbuilt Distributed Static Synchronous Compensators (DSTATCOM). The DSTATCOM device provides control of power factor stability at local feeder lines and the inverter eliminates Total Harmonic Distortion (THD). The 13-level inverter utilizes 52 switches of each H-bridge is fed with single DC sources separately and the Pulse Width Modulation (PWM) technique is used for switching IGBTs. The control strategy implemented for inverter transmits active power to grid as well as it maintains power factor to be stable with achievement of steady state power transmission. Significant outcome of this project is improvement of output voltage quality with steady state power transmission with low THD. Simulation of inverter with DSTATCOM is performed using MATLAB/Simulink environment. The scaled prototype model of proposed inverter is built and its results were validated with simulated results.

Keywords: FACTS devices, distributed-Static synchronous compensators, DSTATCOM, total harmonics elimination, modular multilevel converter.

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Authors: H. Mansor, S. B. Mohd Noor

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This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. Nevertheless, usually there are large peaks in the deadbeat response. By integrating QFT specifications into deadbeat algorithm, the large peaks could be tolerated. On the other hand, emerging QFT with adaptive element will produce a robust controller with wider coverage of uncertainty. By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called selftuning QFT-based deadbeat controller could be achieved. The output response that is fast, robust and adaptive is expected. Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. Grain drying process is very complex with highly nonlinear behaviour, long delay, affected by environmental changes and affected by disturbances. Performance comparisons have been performed between the proposed self-tuning QFT-based deadbeat, standard QFT and standard dead-beat controllers. The efficiency of the self-tuning QFTbased dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant.

Keywords: Deadbeat control, quantitative feedback theory (QFT), robust control, self-tuning control.

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Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, S. Harapanahalli, J. Walsh

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The objective of this study was to determine the effects of environmental stressors on the performance of lactating dairy cows and discuss some future trends. There exists a relationship between the meteorological data and milk yield prediction accuracy in pasture-based dairy systems. New precision technologies are available and are being developed to improve the sustainability of the dairy industry. Some of these technologies focus on welfare of individual animals on dairy farms. These technologies allow the automatic identification of animal behaviour and health events, greatly increasing overall herd health and yield while reducing animal health inspection demands and long-term animal healthcare costs. The data set consisted of records from 489 dairy cows at two dairy farms and temperature measured from the nearest meteorological weather station in 2018. The effects of temperature on milk production and behaviour of animals were analyzed. The statistical results indicate different effects of temperature on milk yield and behaviour. The “comfort zone” for animals is in the range 10 °C to 20 °C. Dairy cows out of this zone had to decrease or increase their metabolic heat production, and it affected their milk production and behaviour.

Keywords: Behaviour, milk yield, temperature, precision technologies.

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Authors: S. H. Mohades Kasaei, S. M. Mohades Kasaei, S. A. Mohades Kasaei, M. Taheri, M. Rahimi, H. Vahiddastgerdi, M. Saeidinezhad

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Omni directional mobile robots have been popularly employed in several applications especially in soccer player robots considered in Robocup competitions. However, Omni directional navigation system, Omni-vision system and solenoid kicking mechanism in such mobile robots have not ever been combined. This situation brings the idea of a robot with no head direction into existence, a comprehensive Omni directional mobile robot. Such a robot can respond more quickly and it would be capable for more sophisticated behaviors with multi-sensor data fusion algorithm for global localization base on the data fusion. This paper has tried to focus on the research improvements in the mechanical, electrical and software design of the robots of team ADRO Iran. The main improvements are the world model, the new strategy framework, mechanical structure, Omni-vision sensor for object detection, robot path planning, active ball handling mechanism and the new kicker design, , and other subjects related to mobile robot

Keywords: Mobile robot, Machine vision, Omni directional movement, Autonomous Systems, Robot path planning, Object Localization.

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Authors: Jamal R. Elbergali

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Multiple Input Multiple Output (MIMO) systems are wireless systems with multiple antenna elements at both ends of the link. Wireless communication systems demand high data rate and spectral efficiency with increased reliability. MIMO systems have been popular techniques to achieve these goals because increased data rate is possible through spatial multiplexing scheme and diversity. Spatial Multiplexing (SM) is used to achieve higher possible throughput than diversity. In this paper, we propose a Zero- Forcing (ZF) detection using a combination of Ordered Successive Interference Cancellation (OSIC) and Zero Forcing using Interference Cancellation (ZF-IC). The proposed method used an OSIC based on Signal to Noise Ratio (SNR) ordering to get the estimation of last symbol, then the estimated last symbol is considered to be an input to the ZF-IC. We analyze the Bit Error Rate (BER) performance of the proposed MIMO system over Rayleigh Fading Channel, using Binary Phase Shift Keying (BPSK) modulation scheme. The results show better performance than the previous methods.

Keywords: SNR, BER, BPSK, MIMO, Modulation, Zero forcing (ZF), OSIC, ZF-IC, Spatial Multiplexing (SM).

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Authors: Aleksandrs Kovalcuks, Mara Duma

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Egg yolk oil is a concentrated source of egg bioactive compounds, such as fat-soluble vitamins, phospholipids, cholesterol, carotenoids and others. To extract lipids and other fat-soluble nutrients from liquid egg yolk, a two-step extraction process involving polar (ethanol) and non-polar (hexane) solvents were used. This extraction technique was based on egg yolk bioactive compounds polarities, where non-polar compound was extracted into non-polar hexane, but polar in to polar alcohol/water phase. But many egg yolk bioactive compounds are not strongly polar or non-polar. Egg yolk phospholipids, cholesterol and pigments are amphipatic (have both polar and non-polar regions) and their behavior in ethanol/hexane solvent system is not clear. The aim of this study was to clarify the behavior of phospholipids, cholesterol and carotenoids during extraction of egg yolk oil with ethanol and hexane and determine the loss of these compounds in egg yolk oil. Egg yolks and egg yolk oil were analyzed for phospholipids (phosphatidylcholine (PC) and phosphatidylethanolamine (PE)), cholesterol and carotenoids (lutein, zeaxanthin, canthaxanthin and β-carotene) content using GC-FID and HPLC methods. PC and PE are polar lipids and were extracted into polar ethanol phase. Concentration of PC in ethanol was 97.89% and PE 99.81% from total egg yolk phospholipids. Due to cholesterol’s partial extraction into ethanol, cholesterol content in egg yolk oil was reduced in comparison to its total content presented in egg yolk lipids. The highest amount of lutein and zeaxanthin was concentrated in ethanol extract. The opposite situation was observed with canthaxanthin and β-carotene, which became the main pigments of egg yolk oil.

Keywords: Cholesterol, egg yolk oil, lutein, phospholipids, solvent extraction.

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Authors: Ö.F. Ursavas, H. Karal

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In this study it is aimed to determine the level of preservice teachers- computer phobia. Whether or not computer phobia meaningfully varies statistically according to gender and computer experience has been tested in the study. The study was performed on 430 pre-service teachers at the Education Faculty in Rize/Turkey. Data in the study were collected through the Computer Phobia Scale consisting of the “Personal Knowledge Questionnaire", “Computer Anxiety Rating Scale", and “Computer Thought Survey". In this study, data were analyzed with statistical processes such as t test, and correlation analysis. According to results of statistical analyses, computer phobia of male pre-service teachers does not statistically vary depending on their gender. Although male preservice teachers have higher computer anxiety scores, they have lower computer thought scores. It was also observed that there is a negative and intensive relation between computer experience and computer anxiety. Meanwhile it was found out that pre-service teachers using computer regularly indicated lower computer anxiety. Obtained results were tried to be discussed in terms of the number of computer classes in the Education Faculty curriculum, hours of computer class and the computer availability of student teachers.

Keywords: Computer phobia, computer anxiety, computer thought, pre-service teachers.

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Authors: Mokhtar Djeddou, Amine Mehel, Georges Fokoua, Anne Tanière, Patrick Chevrier

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Commuters’ exposure to air pollution, particularly to particle matter inside vehicles, is a significant health issue. Assessing particle concentrations and characterizing their distribution is an important first step in understanding and proposing solutions to improve car cabin air quality. It is known that particle dynamics is intimately driven by particle-turbulence interactions. In order to analyze and model pollutants distribution inside car cabins, it is crucial to examine first the single-phase flow topology and its associated turbulence characteristics. Within this context, Computational Fluid Dynamics (CFD) simulations were conducted to model airflow inside a full-scale car cabin using Reynolds Averaged Navier-Stokes (RANS) approach combined with the first order Realizable k-ε model to close the RANS equations. To assess the numerical model, a campaign of velocity field measurements at different locations in the front and back of the car cabin has been carried out using hot-wire anemometry technique. Comparison between numerical and experimental results shows a good agreement of velocity profiles. Additionally, visualization of streamlines shows the formation of jet flow developing out of the dashboard air vents and the formation of large vortex structures, particularly between the front and back-seat compartments. These vortical structures could play a key role in the accumulation and clustering of particles in a turbulent flow.

Keywords: Car cabin, CFD, hot-wire anemometry, vortical flow.

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Authors: Monoranjan Maibam, Arundhati Maibam, Bojen Akoijam

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Myths may be understood as a special kind of literature though not found in written form. Through myths, anthropologists make attempts to describe a world which members of a literate society can barely imagine. Mythical stories about origin of numerous ethnic and tribal communities have helped in tracing their route of migration and the long journey undertaken before arriving at their present places of settlement. This study intends to highlight the myths associated with the origin of the Thangal tribe of Manipur from an anthropological perspective and interpret the stories in the context of evolution, migration and relationship with other neighbouring groups. Fieldwork was conducted using an interview guide to collect primary data and published literatures were consulted for secondary data. The result show two popular versions of origin myths are found among the Thangal- first is origin from a cave at Makhel located in the Maram area and second is the belief that the Thangal, the Tangkhul and the Meitei are brothers who emerged out of a cave long ago. In conclusion, the origin myths of the Thangal may be confirmed and established through archaeological findings in the form of artefacts. Mention of erection of memorial stones in the second version is a good clue to start an archaeological survey of the sites which are believed to have been once occupied by the people.

Keywords: Anthropology, migration, myth, Thangal.

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Authors: Rallapalli Revanth, Shivakumar Bhavi, Vijay Kumar Turaga

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Dispensing powders manually can be difficult as it requires to gradually pour and check the amount on the scale to be dispensed. Current systems are manual and non-continuous in nature and is user dependent and it is also difficult to control powder dispensation. Recurrent dosing of powdered medicines in precise amounts quickly and accurately has been an all-time challenge. Various powder dispensing mechanisms are being designed to overcome these challenges. Battery operated screw conveyor mechanism is being innovated to overcome above problems faced. These inventions are numerically evaluated at concept development level by employing Computational Fluid Dynamics (CFD) of gas-solids multiphase flow systems. CFD has been very helpful in the development of such devices, saving time and money by reducing the number of prototypes and testing. In this study, powder dispensation from the trocar's end is simulated by using the Dense Discrete Phase Model technique along with Kinetic Theory of Granular Flow. The powder is viewed as a secondary flow in air (DDPM-KTGF). By considering the volume fraction of powder as 50%, the transportation side is done by rotation of the screw conveyor. The performance is calculated for 1 sec time frame in an unsteady computation manner. This methodology will help designers in developing design concepts to improve the dispensation and the effective area within a quick turnaround time frame.

Keywords: Multiphase flow, screw conveyor, transient, DDPM - KTGF.

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Authors: Oluwagbenga B. Fatile, Felix U. Idu, Olajide T. Sanya

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This paper reports the viability of developing Zn-27Al alloy matrix hybrid composites reinforced with alumina, graphite and fly ash (solid waste bye product of coal in thermal power plants). This research work was aimed at developing low cost-high performance Zn-27Al matrix composite with low density. Alumina particulates (Al2O3), graphite added with 0, 2, 3, 4 and 5 wt% fly ash were utilized to prepare 10wt% reinforcing phase with Zn-27Al alloy as matrix using two-step stir casting method. Density measurement, estimated percentage porosity, tensile testing, micro hardness measurement and optical microscopy were used to assess the performance of the composites produced. The results show that the hardness, ultimate tensile strength, and percent elongation of the hybrid composites decrease with increase in fly ash content. The maximum decrease in hardness and ultimate tensile strength of 13.72% and 15.25% respectively were observed for composite grade containing 5wt% fly ash. The percentage elongation of composite sample without fly ash is 8.9% which is comparable with that of the sample containing 2wt% fly ash with percentage elongation of 8.8%. The fracture toughness of the fly ash containing composites was however superior to those of composites without fly ash with 5wt% fly ash containing composite exhibiting the highest fracture toughness. The results show that fly ash can be utilized as complementary reinforcement in ZA-27 alloy matrix composite to reduce cost.

Keywords: Fly ash, hybrid composite, mechanical behaviour, stir-cast.

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Authors: R. Prakash, B. Meenakshipriya, R. Kumaravelan

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Fresh water is one of the resources which is getting depleted day by day. A wise method to address this issue is by the application of renewable energy-sun irradiation and by means of decentralized, cheap, energetically self-sufficient, robust and simple to operate plants, distillates can be obtained from sea, river or even sewage. Solar desalination is a technique used to desalinate water using solar energy. The present work deals with the comprehensive design and simulation of solar tracking system using LabVIEW, temperature and mass flow rate control of the solar desalination plant using LabVIEW and also analysis of single phase inverter circuit with LC filters for solar pumping system in MATLAB. The main objective of this work is to improve the performance of solar desalination system using automatic tracking system, output control using temperature and mass flow rate control system and also to reduce the harmonic distortion in the solar pumping system by means of LC filters. The simulation of single phase inverter was carried out using MATLAB and the output waveforms were analyzed. Simulations were performed for optimum output temperature control, which in turn controls the mass flow rate of water in the thermal collectors. Solar tracking system was accomplished using LABVIEW and was tested successfully. The thermal collectors are tracked in accordance with the sun’s irradiance levels, thereby increasing the efficiency of the thermal collectors.

Keywords: Desalination, Electro dialysis, LabVIEW, MATLAB, PWM inverter, Reverse osmosis.

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The modern Artificial Narrow Intelligence (ANI) models cannot: a) independently, situationally, and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, and cognize under uncertainty and changing of the environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU). This system uses a neural network as its computational memory, and activates functions of the perception, identification of real objects, fuzzy situational control, and forming images of these objects. These images and objects are used for modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision Making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, and Wisdom. In doing so are performed analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge of the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of situational control, fuzzy logic, psycholinguistics, informatics, and modern possibilities of data science were applied. The proposed self-controlled system of brain and mind is oriented on use as a plug-in in multilingual subject applications.

Keywords: Computational psycholinguistic cognitive brain and mind system, situational fuzzy control, uncertainty, AI.

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Authors: Sima Ziaee, Khosro Jafarpur

Abstract:

Among all mechanical joining processes, welding has been employed for its advantage in design flexibility, cost saving, reduced overall weight and enhanced structural performance. However, for structures made of relatively thin components, welding can introduce significant buckling distortion which causes loss of dimensional control, structural integrity and increased fabrication costs. Different parameters can affect buckling behavior of welded thin structures such as, heat input, welding sequence, dimension of structure. In this work, a 3-D thermo elastic-viscoplastic finite element analysis technique is applied to evaluate the effect of shell dimensions on buckling behavior and entropy generation of welded thin shells. Also, in the present work, the approximated longitudinal transient stresses which produced in each time step, is applied to the 3D-eigenvalue analysis to ratify predicted buckling time and corresponding eigenmode. Besides, the possibility of buckling prediction by entropy generation at each time is investigated and it is found that one can predict time of buckling with drawing entropy generation versus out of plane deformation. The results of finite element analysis show that the length, span and thickness of welded thin shells affect the number of local buckling, mode shape of global buckling and post-buckling behavior of welded thin shells.

Keywords: Buckling behavior, Elastic viscoplastic model, Entropy generation, Finite element method, Shell dimensions.

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Authors: Anjali Chatterjee, Nirmal Kumar Roy

Abstract:

Economically transformers constitute one of the largest investments in a Power system. For this reason, transformer condition assessment and management is a high priority task. If a transformer fails, it would have a significant negative impact on revenue and service reliability. Monitoring the state of health of power transformers has traditionally been carried out using laboratory Dissolved Gas Analysis (DGA) tests performed at periodic intervals on the oil sample, collected from the transformers. DGA of transformer oil is the single best indicator of a transformer-s overall condition and is a universal practice today, which started somewhere in the 1960s. Failure can occur in a transformer due to different reasons. Some failures can be limited or prevented by maintenance. Oil filtration is one of the methods to remove the dissolve gases and prevent the deterioration of the oil. In this paper we analysis the DGA data by regression method and predict the gas concentration in the oil in the future. We bring about a comparative study of different traditional methods of regression and the errors generated out of their predictions. With the help of these data we can deduce the health of the transformer by finding the type of fault if it has occurred or will occur in future. Additional in this paper effect of filtration on the transformer health is highlight by calculating the probability of failure of a transformer with and without oil filtrating.

Keywords: Power Transformers, Dissolve gas Analysis, Regression method, Filtration, oil.

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Authors: Gilbert Makanda, Roelf Sypkens

Abstract:

A mathematical model for knowledge acquisition in teaching and learning is proposed. In this study we adopt the mathematical model that is normally used for disease modelling into teaching and learning. We derive mathematical conditions which facilitate knowledge acquisition. This study compares the effects of dropping out of the course at early stages with later stages of learning. The study also investigates effect of individual interaction and learning from other sources to facilitate learning. The study fits actual data to a general mathematical model using Matlab ODE45 and lsqnonlin to obtain a unique mathematical model that can be used to predict knowledge acquisition. The data used in this study was obtained from the tutorial test results for mathematics 2 students from the Central University of Technology, Free State, South Africa in the department of Mathematical and Physical Sciences. The study confirms already known results that increasing dropout rates and forgetting taught concepts reduce the population of knowledgeable students. Increasing teaching contacts and access to other learning materials facilitate knowledge acquisition. The effect of increasing dropout rates is more enhanced in the later stages of learning than earlier stages. The study opens up a new direction in further investigations in teaching and learning using differential equations.

Keywords: Differential equations, knowledge acquisition, least squares nonlinear, dynamical systems.

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

Abstract:

The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: Yoichi Hikino, Mutsuto Kawahara

Abstract:

The purpose of this study is to derive optimal shapes of a body located in viscous flows by the finite element method using the acoustic velocity and the four-step explicit scheme. The formulation is based on an optimal control theory in which a performance function of the fluid force is introduced. The performance function should be minimized satisfying the state equation. This problem can be transformed into the minimization problem without constraint conditions by using the adjoint equation with adjoint variables corresponding to the state equation. The performance function is defined by the drag and lift forces acting on the body. The weighted gradient method is applied as a minimization technique, the Galerkin finite element method is used as a spatial discretization and the four-step explicit scheme is used as a temporal discretization to solve the state equation and the adjoint equation. As the interpolation, the orthogonal basis bubble function for velocity and the linear function for pressure are employed. In case that the orthogonal basis bubble function is used, the mass matrix can be diagonalized without any artificial centralization. The shape optimization is performed by the presented method.

Keywords: Shape Optimization, Optimal Control Theory, Finite Element Method, Weighted Gradient Method, Fluid Force, Orthogonal Basis Bubble Function, Four-step Explicit Scheme, Acoustic Velocity.

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