Search results for: temperature models

Authors: Shidvash Vakilipour, Scott Ormiston, Masoud Mohammadi, Rouzbeh Riazi, Kimia Amiri, Sahar Barati

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Two-phase and multi-phase flows are common flow types in fluid mechanics engineering. Among the basic and applied problems of these flow types, two-phase parallel flow is the one that two immiscible fluids flow in the vicinity of each other. In this type of flow, fluid properties (e.g. density, viscosity, and temperature) are different at the two sides of the interface of the two fluids. The most challenging part of the numerical simulation of two-phase flow is to determine the location of interface accurately. In the present work, a coupled interface tracking algorithm is developed based on Arbitrary Lagrangian-Eulerian (ALE) approach using a cell-centered, pressure-based, coupled solver. To validate this algorithm, an analytical solution for fully developed two-phase flow in presence of gravity is derived, and then, the results of the numerical simulation of this flow are compared with analytical solution at various flow conditions. The results of the simulations show good accuracy of the algorithm despite using a nearly coarse and uniform grid. Temporal variations of interface profile toward the steady-state solution show that a greater difference between fluids properties (especially dynamic viscosity) will result in larger traveling waves. Gravity effect studies also show that favorable gravity will result in a reduction of heavier fluid thickness and adverse gravity leads to increasing it with respect to the zero gravity condition. However, the magnitude of variation in favorable gravity is much more than adverse gravity.

Keywords: Coupled solver, gravitational force, interface tracking, Reynolds number to Froude number, two-phase flow.

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Authors: O. Onoriode Emoyan, E. Eyitemi Akporhonor, Charles Otobrise

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Polycyclic Aromatic Hydrocarbons (PAHs) are formed mainly because of incomplete combustion of organic materials during industrial, domestic activities or natural occurrence. Their toxicity and contamination of terrestrial and aquatic ecosystem have been established. However, with limited validity index, previous research has focused on PAHs isomer pair ratios of variable physicochemical properties in source identification. The objective of this investigation was to determine the empirical validity of Pearson Correlation Coefficient (PCC) and Cluster Analysis (CA) in PAHs source identification along soil samples of different land uses. Therefore, 16 PAHs grouped, as Endocrine Disruption Substances (EDSs) were determined in 10 sample stations in top and sub soils seasonally. PAHs was determined the use of Varian 300 gas chromatograph interfaced with flame ionization detector. Instruments and reagents used are of standard and chromatographic grades respectively. PCC and CA results showed that the classification of PAHs along pyrolitic and petrogenic organics used in source signature is about the predominance PAHs in environmental matrix. Therefore, the distribution of PAHs in the studied stations revealed the presence of trace quantities of the vast majority of the sixteen PAHs, which may ultimately inhabit the actual source signature authentication. Therefore, factors to be considered when evaluating possible sources of PAHs could be; type and extent of bacterial metabolism, transformation products/substrates, and environmental factors such as salinity, pH, oxygen concentration, nutrients, light intensity, temperature, co-substrates, and environmental medium are hereby recommended as factors to be considered when evaluating possible sources of PAHs.

Keywords: Comparative correlation, kinetically, polynuclear aromatic hydrocarbons, thermodynamically- favored PAHs, sources evaluation.

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Authors: Alexander J. Severinsky, Allen L. Sessoms

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Atmospheric carbon dioxide (CO2) has dominated the discussion around the causes of climate change. This is a reflection of a 100-year time horizon for all greenhouse gases that became a norm.  The 100-year time horizon is much too long – and yet, almost all mitigation efforts, including those set in the near-term frame of within 30 years, are still geared toward it. In this paper, we show that for a 30-year time horizon, methane (CH4) is the greenhouse gas whose radiative forcing exceeds that of CO2. In our analysis, we use the radiative forcing of greenhouse gases in the atmosphere, because they directly affect the rise in temperature on Earth. We found that in 2019, the radiative forcing (RF) of methane was ~2.5 W/m2 and that of carbon dioxide was ~2.1 W/m2. Under a business-as-usual (BAU) scenario until 2050, such forcing would be ~2.8 W/m2 and ~3.1 W/m2 respectively. There is a substantial spread in the data for anthropogenic and natural methane (CH4) emissions, along with natural gas, (which is primarily CH4), leakages from industrial production to consumption. For this reason, we estimate the minimum and maximum effects of a reduction of these leakages, and assume an effective immediate reduction by 80%. Such action may serve to reduce the annual radiative forcing of all CH4 emissions by ~15% to ~30%. This translates into a reduction of RF by 2050 from ~2.8 W/m2 to ~2.5 W/m2 in the case of the minimum effect that can be expected, and to ~2.15 W/m2 in the case of the maximum effort to reduce methane leakages. Under the BAU, we find that the RF of CO2 will increase from ~2.1 W/m2 now to ~3.1 W/m2 by 2050. We assume a linear reduction of 50% in anthropogenic emission over the course of the next 30 years, which would reduce the radiative forcing of CO2 from ~3.1 W/m2 to ~2.9 W/m2. In the case of "net zero," the other 50% of only anthropogenic CO2 emissions reduction would be limited to being either from sources of emissions or directly from the atmosphere. In this instance, the total reduction would be from ~3.1 W/m2 to ~2.7 W/m2, or ~0.4 W/m2. To achieve the same radiative forcing as in the scenario of maximum reduction of methane leakages of ~2.15 W/m2, an additional reduction of radiative forcing of CO2 would be approximately 2.7 -2.15 = 0.55 W/m2. In total, one would need to remove ~660 GT of CO2 from the atmosphere in order to match the maximum reduction of current methane leakages, and ~270 GT of CO2 from emitting sources, to reach "negative emissions". This amounts to over 900 GT of CO2.

Keywords: Methane Leakages, Methane Radiative Forcing, Methane Mitigation, Methane Net Zero.

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Authors: M. Ferguson, T. Konkova, I. Violatos

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Microstructure analysis of additively manufactured (AM) materials is an important step in understanding the interrelationship between mechanical properties and materials performance. Literature on the effect of a laser-based AM process parameters on the microstructure in the substrate-deposit interface is limited. The interface region, the adjoining area of substrate and deposit, is characterized by the presence of the fusion zone (FZ) and heat affected zone (HAZ) experiencing rapid thermal gyrations resulting in thermal induced transformations. Inconel 718 was utilized as a work material for both the substrate and deposit. Three blocks of Inconel 718 material were deposited by Direct Energy Deposition (DED) using three different laser powers, 550W, 750W and 950W, respectively. A coupled thermo-mechanical transient approach was utilized to correlate temperature history to the evolution of microstructure. Thermal history of the deposition process was monitored with the thermocouples installed inside the substrate material. Interface region of the blocks were analysed with Optical Microscopy (OM) and Scanning Electron Microscopy (SEM) including electron back-scattered diffraction (EBSD) technique. Laser power was found to influence the dissolution of intermetallic precipitated phases in the substrate and grain growth in the interface region. Microstructure and thermal history data were utilized to draw conclusive comparisons between the investigated process parameters.

Keywords: Additive manufacturing, direct energy deposition, electron back-scatter diffraction, finite element analysis, Inconel 718, microstructure, optical microscopy, scanning electron microscopy, substrate-deposit interface region.

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Authors: N. Valderrama, W. Albarracín, N. Algecira

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The effect of the inclusion of thyme and rosemary essential oils into chitosan films, as well as the microbiological and physical properties when storing chitosan film with and without the mentioned inclusion was studied. The film forming solution was prepared by dissolving chitosan (2%, w/v), polysorbate 80 (4% w/w CH) and glycerol (16% w/w CH) in aqueous lactic acid solutions (control). The thyme (TEO) and rosemary (REO) essential oils (EOs) were included 1:1 w/w (EOs:CH) on their combination 50/50 (TEO:REO). The films were stored at temperatures of 5, 20, 33°C and a relative humidity of 75% during four weeks. The films with essential oil inclusion did not show an antimicrobial activity against strains. This behavior could be explained because the chitosan only inhibits the growth of microorganisms in direct contact with the active sites. However, the inhibition capacity of TEO was higher than the REO and a synergic effect between TEO:REO was found for S. enteritidis strains in the chitosan solution. Some physical properties were modified by the inclusion of essential oils. The addition of essential oils does not affect the mechanical properties (tensile strength, elongation at break, puncture deformation), the water solubility, the swelling index nor the DSC behavior. However, the essential oil inclusion can significantly decrease the thickness, the moisture content, and the L* value of films whereas the b* value increased due to molecular interactions between the polymeric matrix, the loosing of the structure, and the chemical modifications. On the other hand, the temperature and time of storage changed some physical properties on the chitosan films. This could have occurred because of chemical changes, such as swelling in the presence of high humidity air and the reacetylation of amino groups. In the majority of cases, properties such as moisture content, tensile strength, elongation at break, puncture deformation, a*, b*, chrome, 7E increased whereas water resistance, swelling index, L*, and hue angle decreased.

Keywords: Chitosan, food additives, modified films, polymers.

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Authors: W. Swiderski

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Composite materials are one answer to the growing demand for materials with better parameters of construction and exploitation. Composite materials also permit conscious shaping of desirable properties to increase the extent of reach in the case of metals, ceramics or polymers. In recent years, composite materials have been used widely in aerospace, energy, transportation, medicine, etc. Fiber-reinforced composites including carbon fiber, glass fiber and aramid fiber have become a major structural material. The typical defect during manufacture and operation is delamination damage of layered composites. When delamination damage of the composites spreads, it may lead to a composite fracture. One of the many methods used in non-destructive testing of composites is active infrared thermography. In active thermography, it is necessary to deliver energy to the examined sample in order to obtain significant temperature differences indicating the presence of subsurface anomalies. To detect possible defects in composite materials, different methods of thermal stimulation can be applied to the tested material, these include heating lamps, lasers, eddy currents, microwaves or ultrasounds. The use of a suitable source of thermal stimulation on the test material can have a decisive influence on the detection or failure to detect defects. Samples of multilayer structure carbon composites were prepared with deliberately introduced defects for comparative purposes. Very thin defects of different sizes and shapes made of Teflon or copper having a thickness of 0.1 mm were screened. Non-destructive testing was carried out using the following sources of thermal stimulation, heating lamp, flash lamp, ultrasound and eddy currents. The results are reported in the paper.

Keywords: Non-destructive testing, IR thermography, composite material, thermal stimulation.

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

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A crucial part of maintaining a customer-oriented business in the telecommunications industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years, which has made it more important to understand customers’ needs in this strong market. For those who are looking to turn over their service providers, understanding their needs is especially important. Predictive churn is now a mandatory requirement for retaining customers in the telecommunications industry. Machine learning can be used to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: Machine Learning, Gradient Boosting, Logistic Regression, Churn, Random Forest, Decision Tree, ROC, AUC, F1-score.

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Authors: Z. Gholamzadeh, A. Zali, S. A. H. Feghhi, C. Tenreiro, Y. Kadi, M. Rezazadeh, M. Aref

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Most HWRs currently use natural uranium fuel. Using enriched uranium fuel results in a significant improvement in fuel cycle costs and uranium utilization. On the other hand, reactivity changes of HWRs over the full range of operating conditions from cold shutdown to full power are small. This reduces the required reactivity worth of control devices and minimizes local flux distribution perturbations, minimizing potential problems due to transient local overheating of fuel. Analyzing heavy water effectiveness on neutronic parameters such as enrichment requirements, peaking factor and reactivity is important and should pay attention as primary concepts of a HWR core designing. Two nuclear nuclear reactors of CANDU-type and hexagonal-type reactor cores of 33 fuel assemblies and 19 assemblies in 1.04 P/D have been respectively simulated using MCNP-4C code. Using heavy water and light water as moderator have been compared for achieving less reactivity insertion and enrichment requirements. Two fuel matrixes of (232Th/235U)O2 and (238/235U)O2 have been compared to achieve more economical and safe design. Heavy water not only decreased enrichment needs, but it concluded in negative reactivity insertions during moderator density variations. Thorium oxide fuel assemblies of 2.3% enrichment loaded into the core of heavy water moderator resulted in 0.751 fission to absorption ratio and peaking factor of 1.7 using. Heavy water not only provides negative reactivity insertion during temperature raises which changes moderator density but concluded in 2 to 10 kg reduction of enrichment requirements, depend on geometry type.

Keywords: MCNP-4C, Reactor core, Multiplication factor, Reactivity, Peaking factor.

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Authors: Theerawat Songyot, Tham Manjing, Bunyarit Uyyanonvara, Chanjira Sinthanayothin

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Corner detection and optical flow are common techniques for feature-based video stabilization. However, these algorithms are computationally expensive and should be performed at a reasonable rate. This paper presents an algorithm for discarding irrelevant feature points and maintaining them for future use so as to improve the computational cost. The algorithm starts by initializing a maintained set. The feature points in the maintained set are examined against its accuracy for modeling. Corner detection is required only when the feature points are insufficiently accurate for future modeling. Then, optical flows are computed from the maintained feature points toward the consecutive frame. After that, a motion model is estimated based on the simplified affine motion model and least square method, with outliers belonging to moving objects presented. Studentized residuals are used to eliminate such outliers. The model estimation and elimination processes repeat until no more outliers are identified. Finally, the entire algorithm repeats along the video sequence with the points remaining from the previous iteration used as the maintained set. As a practical application, an efficient video stabilization can be achieved by exploiting the computed motion models. Our study shows that the number of times corner detection needs to perform is greatly reduced, thus significantly improving the computational cost. Moreover, optical flow vectors are computed for only the maintained feature points, not for outliers, thus also reducing the computational cost. In addition, the feature points after reduction can sufficiently be used for background objects tracking as demonstrated in the simple video stabilizer based on our proposed algorithm.

Keywords: background object tracking, feature point reduction, low cost tracking, video stabilization.

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Authors: Miyako Oulevey, Kaori Tsutsui, David Lavallee, Naohiko Kohtake

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The Japan Sports Agency has made efforts to unify several career support programs for Olympic athletes prior to the 2020 Tokyo Olympics. One of the programs, the Japan Olympic Committee Career Academy (JCA) was established in 2008 for Olympic athletes at their retirement. Research focusing on the service content of sport career support programs can help athletes experience a more positive transition. This study was designed to investigate the service content of the JCA program in relation to athletes’ career transition needs, including any differences of the reasons for retirement between Summer/Winter and Male/Female Olympic athletes, and to suggest the directions of how to unify the career support programs in Japan after hosting the Olympic Games using sport career transition models. Semi-structured interviews were conducted and analyzed the JCA director who started and managed the program since its inception, and a total of 15 conceptual categories were generated by the analysis. Four conceptual categories were in the result of “JCA situation”, 4 conceptual categories were in the result of “Athletes using JCA”, and 7 conceptual categories were in the result of “JCA current difficulties”. Through the analysis it was revealed that: the JCA had occupational supports for both current and retired Olympic athletes; other supports such as psychological support were unclear due to the lack of psychological professionals in JCA and the difficulties collaborating with other sports organizations; and there are differences in tendencies of visiting JCA, financial situations, and career choices depending on Summer/Winter and Male/Female athletes.

Keywords: Career support programs, causes of career termination, Olympic athlete, Olympic committee.

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Authors: B. L. Ho, L. Shi, D. F. Wang, V. C. T. Mok

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The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.

Keywords: Functional magnetic resonance imaging, multivariate regression, network hubs, resting state functional connectivity.

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Authors: B. Nassar, W. Hussein, M. Mokhtar

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The critical concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission, but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the problem above coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions, and the results show that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Keywords: Space telemetry monitoring, multivariate analysis, PCA algorithm, space operations.

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: Short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, Gain.

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Authors: O. D. Adegbehingbe, S. D. Eyono Obono

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The education sector is constantly faced with rapid changes in technologies in terms of ensuring that the curriculum is up to date and in terms of making sure that students are aware of these technological changes. This challenge can be seen as the motivation for this study, which is to examine the factors affecting computing students’ awareness of the latest Information Technologies (ICTs). The aim of this study is divided into two sub-objectives which are: the selection of relevant theories and the design of a conceptual model to support it as well as the empirical testing of the designed model. The first objective is achieved by a review of existing literature on technology adoption theories and models. The second objective is achieved using a survey of computing students in the four universities of the KwaZulu-Natal province of South Africa. Data collected from this survey is analyzed using Statistical package for the Social Science (SPSS) using descriptive statistics, ANOVA and Pearson correlations. The main hypothesis of this study is that there is a relationship between the demographics and the prior conditions of the computing students and their awareness of general ICT trends and of Digital Switch Over (DSO) a new technology which involves the change from analog to digital television broadcasting in order to achieve improved spectrum efficiency. The prior conditions of the computing students that were considered in this study are students’ perceived exposure to career guidance and students’ perceived curriculum currency. The results of this study confirm that gender, ethnicity, and high school computing course affect students’ perceived curriculum currency while high school location affects students’ awareness of DSO. The results of this study also confirm that there is a relationship between students prior conditions and their awareness of general ICT trends and DSO in particular.

Keywords: Education, Information Technologies, IDT, awareness.

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Authors: O. Abramova, L. Abukova, A. Goreva, G. Isaeva

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The present work was made for the purpose of evaluating the interstitial water’s role in the mobilization of metal elements of clay deposits and occurrences in sedimentary formation in the hydro-geological basins. The experiments were performed by using a special facility, which allows adjusting the pressure, temperature, and the frequency of the acoustic vibrations. The dates for study were samples of the oil shales (Baltic career, O₂kk) and clay rocks, mainly montmorillonite composition (Borehole SG-12000, the depth of selection 1000–3600 m, the Azov-Kuban trough, N₁). After interstitial water squeezing from the rock samples, decrease in the original content of the rock forming components including trace metals V, Cr, Co, Ni, Cu, Zn, Zr, Mo, Pb, W, Ti, and others was recorded. The experiments made it possible to evaluate the ore elements output and organic matters with the interstitial waters. Calculations have shown that, in standard conditions, from each ton of the oil shales, 5-6 kg of ore elements and 9-10 kg of organic matter can be escaped. A quantity of matter, migrating from clays in the process of solidification, is changed depending on the lithogenesis stage: more recent unrealized deposits lose more ore and organic materials than the clay rocks, selected from depth over 3000 m. Each ton of clays in the depth interval 1000-1500 m is able to generate 3-5 kg of the ore elements and 6-8 kg of the organic matters. The interstitial waters are a freight forwarder over transferring these matters in the reservoir beds. It was concluded that the interstitial waters which escaped from the study samples are solutions with abnormal high concentrations of the metals and organic matters. In the discharge zones of the sediment basins, such fluids can create paragenetic associations of the sedimentary-catagenetic ore and hydrocarbon mineral resources accumulations.

Keywords: Hydrocarbons, ore genesis, paragenesis, interstitial waters.

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Authors: Shima Soleimani, Steven Eckels

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One area of special importance for the surface-level study of heat exchangers is tubes with internal micro-fins (< 0.5 mm tall). Micro-finned surfaces are a kind of extended solid surface in which energy is exchanged with water that acts as the source or sink of energy. Significant performance gains are possible for either shell, tube, or double pipe heat exchangers if the best surfaces are identified. The parametric studies of micro-finned tubes that have appeared in the literature left some key parameters unexplored. Specifically, they ignored three-dimensional (3D) micro-fin configurations, conduction heat transfer in the fins, and conduction in the solid surface below the micro-fins. Thus, this study aimed at implementing a parametric study of 3D micro-finned tubes that considered micro-fine height and discontinuity features. A 3D conductive and convective heat-transfer simulation through coupled solid and periodic fluid domains is applied in a commercial package, ANSYS Fluent 19.1. The simulation is steady-state with turbulent water flow cooling the inner wall of a tube with micro-fins. The simulation utilizes a constant and uniform temperature on the tube outer wall. Performance is mapped for 18 different simulation cases, including a smooth tube using a realizable k-ε turbulence model at a Reynolds number of 48,928. Results compared the performance of 3D tubes with results for the similar two-dimensional (2D) one. Results showed that the micro-fine height has a greater impact on performance factors than discontinuity features in 3D micro-fin tubes. A transformed 3D micro-fin tube can enhance heat transfer, and pressure drops up to 21% and 56% compared to a 2D one, respectfully.

Keywords: Three-dimensional micro-fin tube, heat transfer, friction factor, heat exchanger.

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Authors: T. C. Manjunath, B. Bandyopadhyay

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Active vibration control is an important problem in structures. The objective of active vibration control is to reduce the vibrations of a system by automatic modification of the system-s structural response. In this paper, the modeling and design of a fast output sampling feedback controller for a smart flexible beam system embedded with shear sensors and actuators for SISO system using Timoshenko beam theory is proposed. FEM theory, Timoshenko beam theory and the state space techniques are used to model the aluminum cantilever beam. For the SISO case, the beam is divided into 5 finite elements and the control actuator is placed at finite element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. Controllers are designed using FOS method and the performance of the designed FOS controller is evaluated for vibration control for 4 SISO models of the same plant. The effect of placing the sensor at different locations on the beam is observed and the performance of the controller is evaluated for vibration control. Some of the limitations of the Euler-Bernoulli theory such as the neglection of shear and axial displacement are being considered here, thus giving rise to an accurate beam model. Embedded shear sensors and actuators have been considered in this paper instead of the surface mounted sensors and actuators for vibration suppression because of lot of advantages. In controlling the vibration modes, the first three dominant modes of vibration of the system are considered.

Keywords: Smart structure, Timoshenko beam theory, Fast output sampling feedback control, Finite Element Method, State space model, SISO, Vibration control, LMI

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Authors: Ismail Bile Hassan, Masrah Azrifah Azmi Murad

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This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards health information application in Smart National Identity Card. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the factors of trust, perceived risk, Privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory up to now. This research identifies factors affecting the citizens’ behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens’ new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. Empirical study may be conducted in the future to provide proof and empirically validate this I-P framework.

Keywords: Unified Theory of Acceptance and Use of Technology (UTAUT) model, UTAUT2 model, Smart National Identity Card (SNIC), Health information application, Privacy Calculus Model (PCM).

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Authors: Maria L. McLeod

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This study examines the ways in which cancer patient narratives are portrayed and framed on the websites of three leading U.S. cancer care centers – The University of Texas MD Anderson Cancer Center in Houston, Memorial Sloan Kettering Cancer Center in New York, and Seattle Cancer Care Alliance. Thirty patient stories, 10 from each cancer center website blog, were analyzed using qualitative and quantitative textual analysis of unstructured data, documenting common themes and other elements of story structure and content. Patient narratives were coded using grounded theory as the basis for conducting emergent qualitative research. As part of a systematic, inductive approach to collecting and analyzing data, recurrent and unique themes were examined and compared in terms of positive and negative framing, patient agency, and institutional praise. All three of these cancer care centers are teaching hospitals, with university affiliations, that emphasize an evidence-based scientific approach to treatment that utilizes the latest research and cutting-edge techniques and technology. The featured cancer stories suggest positive outcomes based on anecdotal narratives as opposed to the science-based treatment models employed by the cancer centers. An analysis of 30 sample stories found skewed representation of the “cancer experience” that emphasizes positive outcomes while minimizing or excluding more negative realities of cancer diagnosis and treatment. The stories also deemphasize patient agency, instead focusing on deference and gratitude toward the cancer care centers, which are cast in the role of savior.  

Keywords: Cancer framing, cancer narratives, survivor stories, patient narratives.

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Authors: Smaali Assia, Outemzabet Ratiba, Media El Mahdi, Kadi Mohamed

Abstract:

Films of pure tin oxide SnO2 and in presence of antimony atoms (SnO2-Sb) deposited onto glass substrates have shown a sufficiently high energy gap to be transparent in the visible region, a high electrical mobility and a carrier concentration which displays a good electrical conductivity [1]. In this work, the effects of polycrystalline silicon substrate on the optical properties of pure and Sb doped tin oxide is investigated. We used the APCVD (atmospheric pressure chemical vapour deposition) technique, which is a low-cost and simple technique, under nitrogen ambient, for growing this material. A series of SnO2 and SnO2-Sb have been deposited onto polycrystalline silicon substrates with different contents of antimony atoms at the same conditions of deposition (substrate temperature, flow oxygen, duration and nitrogen atmosphere of the reactor). The effect of the substrate in terms of morphology and nonlinear optical properties, mainly the reflectance, was studied. The reflectance intensity of the device, compared to the reflectance of tin oxide films deposited directly on glass substrate, is clearly reduced on the overall wavelength range. It is obvious that the roughness of the poly-c silicon plays an important role by improving the reflectance and hence the optical parameters. A clear shift in the minimum of the reflectance upon doping level is observed. This minimum corresponds to strong free carrier absorption, resulting in different plasma frequency. This effect is followed by an increase in the reflectance depending of the antimony doping. Applying the extended Drude theory to the combining optical and electrical obtained results these effects are discussed.

Keywords: Doping, oxide, reflectance.

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Authors: Kirti Tewari, Rahul Dev

Abstract:

Solar water heating is a thermodynamic process of heating water using sunlight with the help of solar water heater. Thus, solar water heater is a device used to harness solar energy. In this paper, a modified solar water heating system (MSWHS) has been proposed over flat plate collector (FPC) and Evacuated tube collector (ETC). The modifications include selection of materials other than glass, and glass wool which are conventionally used for fabricating FPC and ETC. Some modifications in design have also been proposed. Its collector is made of double layer of semi-cylindrical acrylic tubes and fibre reinforced plastic (FRP) insulation base. Water tank is made of double layer of acrylic sheet except base and north wall. FRP is used in base and north wall of the water tank. A concept of equivalent thickness has been utilised for calculating the dimensions of collector plate, acrylic tube and tank. A thermal model for the proposed design of MSWHS is developed and simulation is carried out on MATLAB for the capacity of 200L MSWHS having collector area of 1.6 m2, length of acrylic tubes of 2m at an inclination angle 25° which is taken nearly equal to the latitude of the given location. Latitude of Allahabad is 24.45° N. The results show that the maximum temperature of water in tank and tube has been found to be 71.2°C and 73.3°C at 17:00hr and 16:00hr respectively in March for the climatic data of Allahabad. Theoretical performance analysis has been carried out by varying number of tubes of collector, the tank capacity and climatic data for given months of winter and summer.

Keywords: Acrylic, Fibre reinforced plastic, Solar water Heating, Thermal model, Conventional water heaters.

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Authors: Redouane Tlemsani, Abdelkader Benyettou

Abstract:

Work is in on line Arabic character recognition and the principal motivation is to study the Arab manuscript with on line technology.

This system is a Markovian system, which one can see as like a Dynamic Bayesian Network (DBN). One of the major interests of these systems resides in the complete models training (topology and parameters) starting from training data.

Our approach is based on the dynamic Bayesian Networks formalism. The DBNs theory is a Bayesians networks generalization to the dynamic processes. Among our objective, amounts finding better parameters, which represent the links (dependences) between dynamic network variables.

In applications in pattern recognition, one will carry out the fixing of the structure, which obliges us to admit some strong assumptions (for example independence between some variables). Our application will relate to the Arabic isolated characters on line recognition using our laboratory database: NOUN. A neural tester proposed for DBN external optimization.

The DBN scores and DBN mixed are respectively 70.24% and 62.50%, which lets predict their further development; other approaches taking account time were considered and implemented until obtaining a significant recognition rate 94.79%.

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition.

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Authors: Zachariah Sinkala

Abstract:

A systems approach model for prostate cancer in prostate duct, as a sub-system of the organism is developed. It is accomplished in two steps. First this research work starts with a nonlinear system of coupled Fokker-Plank equations which models continuous process of the system like motion of cells. Then extended to PDEs that include discontinuous processes like cell mutations, proliferation and deaths. The discontinuous processes is modeled by using intensity poisson processes. The model incorporates the features of the prostate duct. The system of PDEs spatial coordinate is along the proximal distal axis. Its parameters depend on features of the prostate duct. The movement of cells is biased towards distal region and mutations of prostate cancer cells is localized in the proximal region. Numerical solutions of the full system of equations are provided, and are exhibit traveling wave fronts phenomena. This motivates the use of the standard transformation to derive a canonically related system of ODEs for traveling wave solutions. The results obtained show persistence of prostate cancer by showing that the non-negative cone for the traveling wave system is time invariant. The traveling waves have a unique global attractor is proved also. Biologically, the global attractor verifies that evolution of prostate cancer stem cells exhibit the avascular tumor growth. These numerical solutions show that altering prostate stem cell movement or mutation of prostate cancer cells lead to avascular tumor. Conclusion with comments on clinical implications of the model is discussed.

Keywords: Fokker-Plank equations, global attractor, stem cell.

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Authors: Daehwan Kim, Jaemin Kim, Seongwon Cho, Yongsuk Jang, Sun-Tae Chung, Boo-Gyoun Kim

Abstract:

AAM has been successfully applied to face alignment, but its performance is very sensitive to initial values. In case the initial values are a little far distant from the global optimum values, there exists a pretty good possibility that AAM-based face alignment may converge to a local minimum. In this paper, we propose a progressive AAM-based face alignment algorithm which first finds the feature parameter vector fitting the inner facial feature points of the face and later localize the feature points of the whole face using the first information. The proposed progressive AAM-based face alignment algorithm utilizes the fact that the feature points of the inner part of the face are less variant and less affected by the background surrounding the face than those of the outer part (like the chin contour). The proposed algorithm consists of two stages: modeling and relation derivation stage and fitting stage. Modeling and relation derivation stage first needs to construct two AAM models: the inner face AAM model and the whole face AAM model and then derive relation matrix between the inner face AAM parameter vector and the whole face AAM model parameter vector. In the fitting stage, the proposed algorithm aligns face progressively through two phases. In the first phase, the proposed algorithm will find the feature parameter vector fitting the inner facial AAM model into a new input face image, and then in the second phase it localizes the whole facial feature points of the new input face image based on the whole face AAM model using the initial parameter vector estimated from using the inner feature parameter vector obtained in the first phase and the relation matrix obtained in the first stage. Through experiments, it is verified that the proposed progressive AAM-based face alignment algorithm is more robust with respect to pose, illumination, and face background than the conventional basic AAM-based face alignment algorithm.

Keywords: Face Alignment, AAM, facial feature detection, model matching.

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Authors: Nkem Angela Udeani

Abstract:

Despite the wide spread use of synthetic dyes, natural dyes are still exploited and used to enhance its inherent aesthetic qualities as a major material for beautification of the body. Centuries before the discovery of synthetic dyes, natural dyes were the only source of dye open to mankind. Dyes are extracted from plant - leaves, roots and barks, insect secretions, and minerals. However, research findings have made it clear that of all, plants- leaves, roots, barks or flowers are the most explored and exploited in which henna (Lawsonia innermis L.) is one of those plants. Experiment has also shown that henna is used in body painting in conjunction with an alkaline (Ammonium Sulphate) as a fixing agent. This of course gives a clue that if colour derived from henna is properly investigated, it may not only be used for body decoration but possibly, may have affinity to fiber substrate. This paper investigates the dyeing potentials – dye ability and fastness qualities of henna dye extracts on cotton and linen fibers using mordants like ammonium sulphate and other alkalis (hydrosulphate and caustic soda, potash, common salt, potassium alum). Hot and cold water and ethanol solvent were used in the extraction of the dye to investigate the most effective method, dye ability, and fastness qualities of these extracts under room temperature. The results of the experiment show that cotton have a high rate of dye intake than other fiber. On a similar note, the colours obtained depend most on the solvent used. In conclusion, hot water extraction appears more effective. While the colours obtained from ethanol and both cold hot methods of extraction range from light to dark yellow, light green to army green and to some extent shades of brown hues.

Keywords: Dye, fabrics, henna leaves, potential.

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: Spatial Information Network, Traffic prediction, Wavelet decomposition, Time series model.

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Authors: Naeem Ahmed

Abstract:

Social work is a professional activity based on the approach of “helping people to help themselves” (Stroup). Social work education and practice both are based on humanitarian philosophy in which social workers try to increase the happiness of the society and to reduce the problems of society. Labour welfare is a specialised field of social work which especially focuses on welfare of organised and unorganised labour. In India labour is facing numerous problems in both organised and unorganised sectors because of ignorance, illiteracy, high rate of unemployment etc. In most of the Indian social work institutions we have this specialization with different names like Human Resource Management or Industrial Relation and Personnel Management or Industrial Relations and Labour Welfare or Industrial Social Work etc. Field work practice is integrated part of social work education curriculum in all specialised field. In India we have different field work practice models being followed in different institutions. The main objective of this paper is to prepare a universal field work practicum model in the field of labour welfare. This paper is exploratory in nature, researcher used personal experience and secondary data (model of field work practice in different institutions like Aligarh Muslim University, Pondicherry University, Central University of Karnataka, University of Lucknow, MJP Rohilkhand University Bareilly etc.) Researcher found that there is an immediate need to upgrade the curriculum or field work practice in this particular field, as more than 40 percent of total population engaged in either unorganised or organised sector (NSSO 2011-12) and they are not aware about their rights. In this way a social worker can play an important role in existing labour welfare facilities by making them aware.

Keywords: Fieldwork, labour welfare, organised labour, social work practice, unorganised labour.

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Authors: J. P. Chica Cano, G. Cabot, S. de Persis, F. Foucher

Abstract:

Among all possibilities to combat global warming, CO₂ capture and sequestration (CCS) is presented as a great alternative to reduce greenhouse gas (GHG) emission. Several strategies for CCS from industrial and power plants are being considered. The concept of combined oxy-fuel combustion has been the most alternative solution. Nevertheless, due to the high cost of pure O₂ production, additional ways recently emerged. In this paper, an innovative combustion process for a gas turbine cycle was studied: it was composed of methane combustion with oxygen enhanced air (OEA), exhaust gas recirculation (EGR) and H₂O issuing from STIG (Steam Injection Gas Turbine), and the CO₂ capture was realized by membrane separator. The effect on this combustion process was emphasized, and it was shown that a study of the influence of H₂O dilution on the combustion parameters by experimental and numerical approaches had to be carried out. As a consequence, the laminar burning velocities measurements were performed in a stainless steel spherical combustion from atmospheric pressure to high pressure (up to 0.5 MPa), at 473 K for an equivalence ratio at 1. These experimental results were satisfactorily compared with Chemical Workbench v.4.1 package in conjunction with GRIMech 3.0 reaction mechanism. The good correlations so obtained between experimental and calculated flame speed velocities showed the validity of the GRIMech 3.0 mechanism in this domain of combustion: high H₂O dilution, low N₂, medium pressure. Finally, good estimations of flame speed and pollutant emissions were determined in other conditions compatible with real gas turbine. In particular, mixtures (composed of CH₄/O₂/N₂/H₂O/ or CO₂) leading to the same adiabatic temperature were investigated. Influences of oxygen enrichment and H₂O dilution (compared to CO₂) were disused.

Keywords: CO2 capture, oxygen enrichment, water dilution, laminar burning velocity, pollutants emissions.

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Authors: T.C. Manjunath, B. Bandyopadhyay

Abstract:

This paper features the modeling and design of a Robust Decentralized Fast Output Sampling (RDFOS) Feedback control technique for the active vibration control of a smart flexible multimodel Euler-Bernoulli cantilever beams for a multivariable (MIMO) case by retaining the first 6 vibratory modes. The beam structure is modeled in state space form using the concept of piezoelectric theory, the Euler-Bernoulli beam theory and the Finite Element Method (FEM) technique by dividing the beam into 4 finite elements and placing the piezoelectric sensor / actuator at two finite element locations (positions 2 and 4) as collocated pairs, i.e., as surface mounted sensor / actuator, thus giving rise to a multivariable model of the smart structure plant with two inputs and two outputs. Five such multivariable models are obtained by varying the dimensions (aspect ratios) of the aluminium beam. Using model order reduction technique, the reduced order model of the higher order system is obtained based on dominant Eigen value retention and the Davison technique. RDFOS feedback controllers are designed for the above 5 multivariable-multimodel plant. The closed loop responses with the RDFOS feedback gain and the magnitudes of the control input are obtained and the performance of the proposed multimodel smart structure system is evaluated for vibration control.

Keywords: Smart structure, Euler-Bernoulli beam theory, Fastoutput sampling feedback control, Finite Element Method, Statespace model, Vibration control, LMI, Model order Reduction.

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Authors: Amit Kumar Bhandary, Prithviraj Gupta, Siddhartha Mukherjee, Mahua Ghosh Chaudhuri, Rajib Dey

Abstract:

Chromite ores are primarily used for extraction of chromium, which is an expensive metal. For low grade chromite ores (containing less than 40% Cr₂O₃), the chromium extraction is not usually economically viable. India possesses huge quantities of low grade chromite reserves. This deposit can be utilized after proper physical beneficiation. Magnetic separation techniques may be useful after reduction for the beneficiation of low grade chromite ore. The sample collected from the sukinda mines is characterized by XRD which shows predominant phases like maghemite, chromite, silica, magnesia and alumina. The raw ore is crushed and ground to below 75 micrometer size. The microstructure of the ore shows that the chromite grains surrounded by a silicate matrix and porosity observed the exposed side of the chromite ore. However, this ore may be utilized in refractory applications. Chromite ores contain Cr₂O₃, FeO, Al₂O₃ and other oxides like Fe-Cr, Mg-Cr have a high tendency to form spinel compounds, which usually show high refractoriness. Initially, the low grade chromite ore (containing 34.8% Cr₂O₃) was reduced at 1200 ⁰C for 80 minutes with 30% coke fines by weight, before being subjected to magnetic separation. The reduction by coke leads to conversion of higher state of iron oxides converted to lower state of iron oxides. The pre-reduced samples are then characterized by XRD. The magnetically inert mass was then reacted with 20% MgO by weight at 1450 ⁰C for 2 hours. The resultant product was then tested for various refractoriness parameters like apparent porosity, slag resistance etc. The results were satisfactory, indicating that the resultant spinel compounds are suitable for refractory applications for elevated temperature processes.

Keywords: Apparent porosity, beneficiation, low grade chromite, refractory, spinel compounds, slag resistance.

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