Search results for: linear differential equations

Authors: Jalal Karam

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The methods of Fourier, Laplace, and Wavelet Transforms provide transfer functions and relationships between the input and the output signals in linear time invariant systems. This paper shows the equivalence among these three methods and in each case presenting an application of the appropriate (Fourier, Laplace or Wavelet) to the convolution theorem. In addition, it is shown that the same holds for a direct integration method. The Biorthogonal wavelets Bior3.5 and Bior3.9 are examined and the zeros distribution of their polynomials associated filters are located. This paper also presents the significance of utilizing wavelets as effective tools in processing speech signals for common multimedia applications in general, and for recognition and compression in particular. Theoretically and practically, wavelets have proved to be effective and competitive. The practical use of the Continuous Wavelet Transform (CWT) in processing and analysis of speech is then presented along with explanations of how the human ear can be thought of as a natural wavelet transformer of speech. This generates a variety of approaches for applying the (CWT) to many paradigms analysing speech, sound and music. For perception, the flexibility of implementation of this transform allows the construction of numerous scales and we include two of them. Results for speech recognition and speech compression are then included.

Keywords: continuous wavelet transform, biorthogonal wavelets, speech perception, recognition and compression

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Authors: Ahmed Z. Mazen, Nejat Rahmanian, Iqbal Mujtaba, Ali Hassanpour

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In oil and gas well drilling, the drill bit is an important part of the Bottom Hole Assembly (BHA), which is installed and designed to drill and produce a hole by several mechanisms. The efficiency of the bit depends on many drilling parameters such as weight on bit, rotary speed, and mud properties. When the bit is pulled out of the hole, the evaluation of the bit damage must be recorded very carefully to guide engineers in order to select the bits for further planned wells. Having a worn bit for hole drilling may cause severe damage to bit leading to cutter or cone losses in the bottom of hole, where a fishing job will have to take place, and all of these will increase the operating cost. The main factor to reduce the cost of drilling operation is to maximize the rate of penetration by analyzing real-time data to predict the drill bit wear while drilling. There are numerous models in the literature for prediction of the rate of penetration based on drilling parameters, mostly based on empirical approaches. One of the most commonly used approaches is Bourgoyne and Young model, where the rate of penetration can be estimated by the drilling parameters as well as a wear index using an empirical correlation, provided all the constants and coefficients are accurately determined. This paper introduces a new methodology to estimate the eight coefficients for Bourgoyne and Young model using the gPROMS parameters estimation GPE (Version 4.2.0). Real data collected form similar formations (12 ¼’ sections) in two different fields in Libya are used to estimate the coefficients. The estimated coefficients are then used in the equations and applied to nearby wells in the same field to predict the bit wear.

Keywords: Bourgoyne and Young model, bit wear, gPROMS, rate of penetration

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Authors: Gao ya

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This present study aims to find the relationship between self-efficacy and life satisfaction and the effects of self-efficacy on life satisfaction among Chinese people whose age is from 27-32, born between 1990 and 1995. People who were born between 1990 and 1995 are worthy to receive more attention now because the 90s was always received a lot of focus and labeled negatively as soon as they were born. And a large number of researches study people in individualism society more. So we chose the specific population whose age is from 27 to 32 live in a collectivist society. Demographic information was collected, including age, gender, education level, marital status, income level, number of children. We used the general self-efficacy scale(GSC) and the satisfaction with Life Scale(SLS) to collect data. A total of 350 questionnaires were distributed in and collected from mainland China, then 261 valid questionnaires were returned in the end, making a response rate of 74.57 percent. Some statistics techniques were used, like regression, correlation, ANOVA, T-test and general linear model, to measure variables. The findings were that self-efficacy positively related to life satisfaction. And self-efficacy influences life satisfaction significantly. At the same time, the relationship between demographic information and life satisfaction was analyzed.

Keywords: marital status, life satisfaction, number of children, self-efficacy, income level

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Authors: A. Hayrapetyan, A. Simon, P. Marques, G. Renart

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Business survival is a question of greatest interest for any economy. Firm characteristics that can explain or predict performance and, ultimately, business survival become of the greatest significance, as the sustainable longevity of any business can mean health for the future of the country. Family Firms (FFs) are one of the most ubiquitous forms of business worldwide, as more than half of European firms (60%) are considered as family firms. Therefore, the inherent characteristics of FFs are one of the possible explanatory variables for firm survival because FFs have strategic goals that differentiate them from other types of businesses. Although there is literature on the performance of FFs across generations, there are fewer studies on the factors that impact the survival of family and non-family FFs, as there is a lack of data on failed firms. To address this gap, this paper explores the differential survival of family firms versus non-family firms with a representative sample of companies of the region of Catalonia (Northeast of Spain) that were adhoc classified as family or nonfamily firms, as well as classified as failed or surviving, since no census data for family firms or for failed firms is available in Spain. By using the COX regression model on a representative sample of 629 family and non-family firms, this study investigates to what extent financial ratios, such as Liquidity, Solvency Rate can impact business survival, taking into consideration the socioemotional side of family firms, as well as revealing the differences between family and non-family firms. The findings show that the liquidity rate is significant for non-family firm survival, whereas not for family firms. On the other hand, FFs can benefit while having a higher solvency rate. Ultimately, this paper discovers that FFs increase their chances of survival when they are small, as the growth in size starts negatively impacting the socioemotional objectives of the firm. This study proves the existence of significant differences between family and non-family firms’ survival during economic crises, suggesting that the prioritization of emotional wealth creates distinct conditions for both types of firms.

Keywords: COX regression, economy crises, family firm, non-family firm, survival

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Authors: Golden J. Zhang, Dongbao Zhou

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Darcy’s law is the fundamental theory in fluid dynamics and engineering applications. Although Darcy linearity was found to be valid for slow, viscous flow, non-linear and non-Darcian flow has been well documented under both small and large velocity fluid flow. Various classical models were proposed and used widely to quantify non-Darcian flow, including the well-known Forchheimer, Izbash, and Swartzendruber models. Applications, however, revealed limitations of these models. Here we propose a general model built upon the Caputo fractional derivative to quantify non-Darcian flow for various flows (laminar to turbulence).Real-world applications and model comparisons showed that the new fractional-derivative model, which extends the fractional model proposed recently by Zhou and Yang (2018), can capture the non-Darcian flow in the relatively small velocity in low-permeability deposits and the relatively high velocity in high-permeability sand. A scale effect was also identified for non-Darcian flow in fractured rocks. Therefore, fractional calculus may provide an efficient tool to improve classical models to quantify fluid dynamics in aquatic environments.

Keywords: fractional derivative, darcy’s law, non-darcian flow, fluid dynamics

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Authors: Yasaswi Palagummi, Sareh Rowlands

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Generalised Zero-Shot Learning, often known as GZSL, is an advanced variant of zero-shot learning in which the samples in the unseen category may be either seen or unseen. GZSL methods typically have a bias towards the seen classes because they learn a model to perform recognition for both the seen and unseen classes using data samples from the seen classes. This frequently leads to the misclassification of data from the unseen classes into the seen classes, making the task of GZSL more challenging. In this work of ours, to solve the GZSL problem, we propose an approach leveraging the Shifted Window based Self-Attention in the Swin Transformer (Swin-GZSL) to work in the inductive GSZL problem setting. We run experiments on three popular benchmark datasets: CUB, SUN, and AWA2, which are specifically used for ZSL and its other variants. The results show that our model based on Swin Transformer has achieved state-of-the-art harmonic mean for two datasets -AWA2 and SUN and near-state-of-the-art for the other dataset - CUB. More importantly, this technique has a linear computational complexity, which reduces training time significantly. We have also observed less bias than most of the existing GZSL models.

Keywords: generalised, zero-shot learning, inductive learning, shifted-window attention, Swin transformer, vision transformer

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Authors: Ririh Rahma Ratinghayu, Jayu Pramudya, Nur Aini Masruroh, Shi-Woei Lin

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This research studies pricing strategy in cooperative setting of hotel duopoly selling perishable product under fixed capacity constraint by using the perspective of managers. In hotel revenue management, competitor’s average room rate and occupancy rate should be taken into manager’s consideration in determining pricing strategy to generate optimum revenue. This information is not provided by business intelligence or available in competitor’s website. Thus, Information Sharing (IS) among players might result in improved performance of pricing strategy. IS is widely adopted in the logistics industry, but IS within hospitality industry has not been well-studied. This research put IS as one of cooperative game schemes, besides Mutual Price Setting (MPS) scheme. In off-peak season, hotel manager arranges pricing strategy to offer promotion package and various kinds of discounts up to 60% of full-price to attract customers. Competitor selling homogenous product will react the same, then triggers a price war. Price war which generates lower revenue may be avoided by creating collaboration in pricing strategy to optimize payoff for both players. In MPS cooperative game, players collaborate to set a room rate applied for both players. Cooperative game may avoid unfavorable players’ payoff caused by price war. Researches on horizontal cooperative game in logistics show better performance and payoff for the players, however, horizontal cooperative game in hotel revenue management has not been demonstrated. This paper aims to develop hotel revenue management models under duopoly cooperative schemes (IS & MPS), which are compared to models under non-cooperative scheme too. Each scheme has five models, Capacity Allocation Model; Demand Model; Revenue Model; Optimal Price Model; and Equilibrium Price Model. Capacity Allocation Model and Demand Model employs self-hotel and competitor’s full and discount price as predictors under non-linear relation. Optimal price is obtained by assuming revenue maximization motive. Equilibrium price is observed by interacting self-hotel’s and competitor’s optimal price under reaction equation. Equilibrium is analyzed using game theory approach. The sequence applies for three schemes. MPS Scheme differently aims to optimize total players’ payoff. The case study in which theoretical models are applied observes two hotels offering homogenous product in Indonesia during a year. The Capacity Allocation, Demand, and Revenue Models are built using multiple regression and statistically tested for validation. Case study data confirms that price behaves within demand model in a non-linear manner. IS Models can represent the actual demand and revenue data better than Non-IS Models. Furthermore, IS enables hotels to earn significantly higher revenue. Thus, duopoly hotel players in general, might have reasonable incentives to share information horizontally. During off-peak season, MPS Models are able to predict the optimal equal price for both hotels. However, Nash equilibrium may not always exist depending on actual payoff of adhering or betraying mutual agreement. To optimize performance, horizontal cooperative game may be chosen over non-cooperative game. Mathematical models can be used to detect collusion among business players. Empirical testing can be used as policy input for market regulator in preventing unethical business practices potentially harming society welfare.

Keywords: horizontal cooperative game theory, hotel revenue management, information sharing, mutual price setting

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Authors: Dmitry Dikarev, Ajit Nimbalker, Alexei Davydov

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Polar coding is a novel example of error correcting codes, which can achieve Shannon limit at block length N→∞ with log-linear complexity. Active research is being carried to adopt this theoretical concept for using in practical applications such as 5th generation wireless communication systems. Cyclic redundancy check (CRC) error detection code is broadly used in conjunction with successive cancellation list (SCL) decoding algorithm to improve finite-length polar code performance. However, there are two issues: increase of code block payload overhead by CRC bits and decrease of CRC error-detection capability. This paper proposes a method to control CRC overhead and false alarm rate of polar decoding. As shown in the computer simulations results, the proposed method provides the ability to use any set of CRC polynomials with any list size while maintaining the desired level of false alarm rate. This level of flexibility allows using polar codes in 5G New Radio standard.

Keywords: 5G New Radio, channel coding, cyclic redundancy check, list decoding, polar codes

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Authors: Shaghayegh Shajari, Mehdi Mahmoodi, Mahmood Rajabian, Uttandaraman Sundararaj, Les J. Sudak

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Although several strain sensors based on carbon nanotubes (CNTs) have been reported, the stretchability and sensitivity of these sensors have remained as a challenge. Highly stretchable and sensitive strain sensors are in great demand for human motion monitoring and human-machine interface. This paper reports the fabrication and characterization of a new type of strain sensors based on a stretchable fluoropolymer / CNT nanocomposite system made via melt-mixing technique. Electrical and mechanical characterizations were obtained. The results showed that this nanocomposite sensor has high stretchability up to 280% of strain at an optimum level of filler concentration. The piezoresistive properties and the strain sensing mechanism of the strain sensor were investigated using Electrochemical Impedance Spectroscopy (EIS). High sensitivity was obtained (gauge factor as large as 12000 under 120% applied strain) in particular at the concentrations above the percolation threshold. Due to the tunneling effect, a non- linear piezoresistivity was observed at high concentrations of CNT loading. The nanocomposites with good conductivity and lightweight could be a promising candidate for strain sensing applications.

Keywords: carbon nanotubes, fluoropolymer, piezoresistive, strain sensor

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Authors: Olanrewaju Rotimi Bodede, Akinlabi Oyetunji

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Modeling the dry compressive strength of sodium silicate bonded kaolin refractory bricks was studied. The materials used for this research work included refractory clay obtained from Ijero-Ekiti kaolin deposit on coordinates 7º 49´N and 5º 5´E, sodium silicate obtained from the open market in Lagos on coordinates 6°27′11″N 3°23′45″E all in the South Western part of Nigeria. The mineralogical composition of the kaolin clay was determined using the Energy Dispersive X-Ray Fluorescence Spectrometer (ED-XRF). The clay samples were crushed and sieved using the laboratory pulveriser, ball mill and sieve shaker respectively to obtain 100 μm diameter particles. Manual pipe extruder of dimension 30 mm diameter by 43.30 mm height was used to prepare the samples with varying percentage volume of sodium silicate 5 %, 7.5 % 10 %, 12.5 %, 15 %, 17.5 %, 20% and 22.5 % while kaolin and water were kept at 50 % and 5 % respectively for the comprehensive test. The samples were left to dry in the open laboratory atmosphere for 24 hours to remove moisture. The samples were then were fired in an electrically powered muffle furnace. Firing was done at the following temperatures; 700ºC, 750ºC, 800ºC, 850ºC, 900ºC, 950ºC, 1000ºC and 1100ºC. Compressive strength test was carried out on the dried samples using a Testometric Universal Testing Machine (TUTM) equipped with a computer and printer, optimum compression of 4.41 kN/mm2 was obtained at 12.5 % sodium silicate; the experimental results were modeled with MATLAB and Origin packages using polynomial regression equations that predicted the estimated values for dry compressive strength and later validated with Pearson’s rank correlation coefficient, thereby obtaining a very high positive correlation value of 0.97.

Keywords: dry compressive strength, kaolin, modeling, sodium silicate

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Authors: Giriprasath Ramanathan, Sivakumar Singaravelu, M. D. Raja, Uma Tirichurapalli Sivagnanam

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Collagen is the abundant protein found in the skin of the animal body that has been designed to provide adequate structural support for the adhesion of cells. The dressing material widely used for tissue engineering and biomedical application has to posses good swelling and biological property for the absorption of exudates and cell proliferation. Acid solubilised collagen from the fish skin of the Arothron stellatus was extracted. The collagen with hydroxypropyl and carboxy methyl cellulose has the better biological property to enhance the healing efficiency. The inter property of collagen with interesting perspectives in the tissue engineering process leads to the development of biomaterial with natural polymer with biologically derived collagen. Keeping this as an objective, the composite biomaterial was fabricated to improve the wound healing and biological properties. In this study the collagen from Arothron stellatus fish skin (ACO) was uniformly blended separately with hydroxypropyl methyl cellulose (HPMC) and carboxyl methyl cellulose (CMC) as biosheets. The casted biosheets were impregnated with mupirocin to get rid of infection from the microbes. Further, the results obtained from differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), tensile studies and biocompatibility of the biosheets were assessed. The swelling, porosity and degradation of the casted biosheets were studied to make the biosheets as a suitable wound dressing material. ACO-HPMC and ACO-CMC biosheets both showed good results, but ACO-HPMC biosheet showed better results than ACO-CMC and hence it can be used as a potential dermal substitute in skin tissue engineering.

Keywords: arothron stellatus, biocompatibility, collagen, tensile strenght

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Authors: Yakin Hajlaoui, Richard Labib, Jean-François Plante, Michel Gamache

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This study introduces the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs' processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW's ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. it employ gradient descent and backpropagation to train ML-IDW, comparing its performance against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. the results highlight the efficacy of ML-IDW, particularly in handling complex spatial datasets, exhibiting lower mean square error in regression and higher F1 score in classification.

Keywords: deep learning, multi-layer neural networks, gradient descent, spatial interpolation, inverse distance weighting

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Authors: Andre F. A. Cyrino

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Knowing that the technological advance is the focus on the efficient extraction of energy from wind, and therefore in the design of wind turbine structures, this work aims the study of the fluid-structure interaction of an idealized wind turbine. The blade was studied as a beam attached to a cylindrical Hub with rotation axis pointing the air flow that passes through the rotor. Using the calculus of variations and the finite difference method the blade will be simulated by a discrete number of nodes and the aerodynamic forces were evaluated. The study presented here was written on Matlab and performs a numeric simulation of a simplified model of windmill containing a Hub and three blades modeled as Euler-Bernoulli beams for small strains and under the constant and uniform wind. The mathematical approach is done by Hamilton’s Extended Principle with the aerodynamic loads applied on the nodes considering the local relative wind speed, angle of attack and aerodynamic lift and drag coefficients. Due to the wide range of angles of attack, a wind turbine blade operates, the airfoil used on the model was NREL SERI S809 which allowed obtaining equations for Cl and Cd as functions of the angle of attack, based on a NASA study. Tridimensional flow effects were no taken in part, as well as torsion of the beam, which only bends. The results showed the dynamic response of the system in terms of displacement and rotational speed as the turbine reached the final speed. Although the results were not compared to real windmills or more complete models, the resulting values were consistent with the size of the system and wind speed.

Keywords: blade aerodynamics, fluid–structure interaction, wind turbine aerodynamics, wind turbine blade

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Authors: Gwenyth C. Eichfeld

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Variation in global COVID-19 spread is partly explained by social and behavioral factors. Many of these behaviors are linked to genetics. The short polymorphism of the 5-HTTLPR promoter region of the SLC6A4 gene is linked to collectivism. The seven-repeat polymorphism of the DRD4 gene is linked to risk-taking, migration, sensation-seeking, and impulsivity. Fewer CAG repeats in the androgen receptor gene are linked to impulsivity. This study investigates an association between the country-level frequency of these variants and early Covid-19 spread. Results of regression analysis indicate a significant association between increased country-wide prevalence of the short allele of the SLC6A4 gene and decreased COVID-19 spread when other factors that have been linked to COVID-19 are controlled for. Additionally, results show that the short allele of the SLC6A4 gene is associated with COVID-19 spread through GDP and percent urbanization rather than collectivism. Results showed no significant association between the frequency of the DRD4 polymorphism nor the androgen receptor polymorphism with early COVID-19 spread.

Keywords: neuroscience, genetics, population sciences, Covid-19

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Authors: Ali Mahmoud, Shadi Najjar, Mounir Mabsout, Kassim Tarhini

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Empirical expressions for estimating the wheel load distribution and live-load bending moment are typically specified in highway bridge codes such as the AASHTO procedures. The purpose of this paper is to analyze the reliability levels that are inherent in reinforced concrete slab bridges that are designed based on the simplified empirical live load equations in the AASHTO LRFD procedures. To achieve this objective, bridges with multi-lanes (three and four lanes) and different spans are modeled using finite-element analysis (FEA) subjected to HS20 truck loading, tandem loading, and standard lane loading per AASHTO LRFD procedures. The FEA results are compared with the AASHTO LRFD moments in order to quantify the biases that might result from the simplifying assumptions adopted in AASHTO. A reliability analysis is conducted to quantify the reliability index for bridges designed using AASHTO procedures. To reach a consistent level of safety for three- and four-lane bridges, following a previous study restricted to one- and two-lane bridges, the live load factor in the design equation proposed by AASHTO LRFD will be assessed and revised if needed by alternating the live load factor for these lanes. The results will provide structural engineers with more consistent provisions to design concrete slab bridges or evaluate the load-carrying capacity of existing bridges.

Keywords: reliability analysis of concrete bridges, finite element modeling, reliability analysis, reinforced concrete bridge design, load carrying capacity

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Authors: Lewis Wallace, William Dempster, David Nash, Alexandros Boukis, Craig Maclean

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This paper, through traditional test methods and close adherence to international standards, presents a characterization study of a woven Polyethylene Terephthalate (PET). Testing is undergone in the axial, shear, and out-of-plane (bend) directions, and the results are fitted to the *FABRIC material model with ABAQUS FEA. The non-linear behaviors of the fabric in the axial and shear directions and behaviors on the macro scale are explored at the meso scale level. The medical grade bio-fabric is tested in untreated and heat-treated forms, and deviations are closely analyzed at the micro, meso, and macro scales to determine the effects of the process. The heat-treatment process was found to increase the stiffness of the fabric during axial and bending stiffness testing but had a negligible effect on the shear response. The ability of *FABRIC to capture behaviors unique to fabric deformation is discussed, whereby the unique phenomenological input can accurately represent the experimentally derived inputs.

Keywords: experimental techniques, FEA modelling, materials characterization, post-processing techniques

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Authors: Shivani Saini

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The effect of vertical throughflow on the onset of convection in Rivlin-Ericksen Elastico-Viscous nanofluid with convective boundary condition is investigated. The flow is stimulated with modified Darcy model under the assumption that the nanoparticle volume fraction is not actively managed on the boundaries. The heat conservation equation is formulated by introducing the convective term of nanoparticle flux. A linear stability analysis based upon normal mode is performed, and an approximate solution of eigenvalue problems is obtained using the Galerkin weighted residual method. Investigation of the dependence of the Rayleigh number on various viscous and nanofluid parameter is performed. It is found that through flow and nanofluid parameters hasten the convection while capacity ratio, kinematics viscoelasticity, and Vadasz number do not govern the stationary convection. Using the convective component of nanoparticle flux, critical wave number is the function of nanofluid parameters as well as the throughflow parameter. The obtained solution provides important physical insight into the behavior of this model.

Keywords: Darcy model, nanofluid, porous layer, throughflow

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Authors: Alessandro Poma, Kal Karim, Sergey Piletsky, Giuseppe Battaglia

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The recent increasing emergency threat to public health of infectious influenza diseases has prompted interest in the detection of avian influenza virus (AIV) H5N1 in humans as well as animals. A variety of technologies for diagnosing AIV infection have been developed. However, various disadvantages (costs, lengthy analyses, and need for high-containment facilities) make these methods less than ideal in their practical application. Molecularly Imprinted Polymeric Nanoparticles (MIP NPs) are suitable to overcome these limitations by having high affinity, selectivity, versatility, scalability and cost-effectiveness with the versatility of post-modification (labeling – fluorescent, magnetic, optical) opening the way to the potential introduction of improved diagnostic tests capable of providing rapid differential diagnosis. Here we present our first results in the production and testing of MIP NPs for the detection of AIV H5N1. Recent developments in the solid-phase synthesis of MIP NPs mean that for the first time a reliable supply of ‘soluble’ synthetic antibodies can be made available for testing as potential biological or diagnostic active molecules. The MIP NPs have the potential to detect viruses that are widely circulating in farm animals and indeed humans. Early and accurate identification of the infectious agent will expedite appropriate control measures. Thus, diagnosis at an early stage of infection of a herd or flock or individual maximizes the efficiency with which containment, prevention and possibly treatment strategies can be implemented. More importantly, substantiating the practicability’s of these novel reagents should lead to an initial reduction and eventually to a potential total replacement of animals, both large and small, to raise such specific serological materials.

Keywords: influenza virus, molecular imprinting, nanoparticles, polymers

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Authors: K. Bhojnadh, M. Fiddler, D. Cheshire

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An investigation into the Kutta effect on the trailing edge of a subsonic aerofoil was conducted which led to an analysis using Ansys Fluent to determine the effect of flow separation over a NACA 0012 aerofoil. This aerofoil was subjected to oscillations to create an unsteady flow over the aerofoil, therefore, creating turbulence, with unsteady aerodynamics playing a key role to determine the flow regimes when the aerofoil is subjected to different angles of attack along with varying Reynolds numbers. Many theories were evolved to determine the flow parameters of a 2-D aerofoil in these unsteady conditions because they behave unpredictably at the trailing edge when subjected to a different angle of attack. The shear area observed in the boundary layer at the trailing edge tends towards an unsteady turbulent flow even at small angles of attack, creating drag as the flow separates, reducing the aerodynamic performance of aerofoil. In this paper, research was conducted to determine the effect of Kutta circulation over the aerofoil and the effect of that circulation in reducing the effect of pressure and boundary layer distribution over the aerofoil. The effect of circulation is observed by using Ansys Fluent by using varying flow parameters and differential schemes to observe the flow behaviour on the aerofoil. Initially, steady flow analysis was conducted on the aerofoil to determine the effect of circulation, and it was noticed that the effect of circulation could only be properly observed when the aerofoil is subjected to oscillations. Therefore, that was modelled by using Ansys user-defined functions, which define the motion of the aerofoil by creating a dynamic mesh on the aerofoil. Initial results were observed, and further development of the dynamic mesh functions in Ansys is taking place. This research will determine the overall basic principles of unsteady flow aerodynamics applied to the investigation of Kutta related circulation, and gives an indication regarding the generation of vortices which is discussed further in this paper.

Keywords: circulation, flow seperation, turbulence modelling, vortices

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Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

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The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

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Authors: Chunhua Ma

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Background: There is a relationship between cultural identity and psychological health. Resilience is an important factor of psychological health, and cultural identity will protect the resilience. The research showed that the cultural identity, resilience, and self-concordance of students from different cultures. It should be a theoretical basis to improve mental health of different nationalities students. And the role of resilience factors for adults’ cultural identity and self-concordance was deserve studied. Aims: The current study aimed to examine the relationship between cultural identity and self-concordance among Chinese academician from 3 minorities, postulating mediating by resilience. Methods: This study used cross-sectional and correlational design. Participants were 328 Chinese aged between 18 and 25 years. Data was collected via self-reports including both closed and opened questions. Results: Linear regression analysis controlling for age, gender, the result showed that: (a) Cultural identity was related to self-concordance, resilience was related to self-concordance and cultural identity was related to resilience, (b) Resilience mediated the link between cultural identity and self-concordance, respectively. Discussion: Our findings suggested that resilience and cultural identity are important factors in self-concordance. If minority college students realized the heterogeneous culture, it would alleviate their psychological conflict, stimulate their strength potential and improve their self-concordance.

Keywords: cultural identity, resilience, self-concordance, mediating effect

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Authors: Arooba Azam Khan

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The present study aims to focus on the relationship between smartphone addiction and academic performance of students along with social networking sites, overuse of smartphone, GPA’s and time management skills as their sub-variables. In this world of technology, the smartphone becomes a vital part of everyone’s life. The addiction of smartphones has both negative and positive impact on young people (students). Students keep themselves busy with smartphones without noticing that smartphone addiction is creating a negative impact on their social, academic, and personal lives. A quantitative approach was used to collect data through questionnaire from 360 students of two private universities in Pakistan in summer 2017. The target age group was 19-24 studying in Bachelors programmes. Data were analyzed by using SPSS (version 20), linear correlation and regression tests were applied. Results reveal that there is a negative relationship between smartphone addiction and academic performance. Moreover, it has been proved that students with good time management skills achieve high grades/GPA’s than those who have poor time management skills. From the findings, the researcher suggests that students should spend their time wisely and use their smartphones for educational purpose. However, students need training and close monitoring to get benefits out of smartphones use.

Keywords: smartphone addiction, academic performance, time management skills, quantitative research

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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An estimating equation technique is an alternative method of the widely used maximum likelihood methods, which enables us to ease some complexity due to the complex characteristics of time-varying covariates. In the situations, when both the time-varying covariates and left-truncation are considered in the model, the maximum likelihood estimation procedures become much more burdensome and complex. To ease the complexity, in this study, the modified estimating equations those have been given high attention and considerations in many researchers under semiparametric transformation model was proposed. The purpose of this article was to develop the modified estimating equation under flexible and general class of semiparametric transformation models for left-truncated and right censored survival data with time-varying covariates. Besides the commonly applied Cox proportional hazards model, such kind of problems can be also analyzed with a general class of semiparametric transformation models to estimate the effect of treatment given possibly time-varying covariates on the survival time. The consistency and asymptotic properties of the estimators were intuitively derived via the expectation-maximization (EM) algorithm. The characteristics of the estimators in the finite sample performance for the proposed model were illustrated via simulation studies and Stanford heart transplant real data examples. To sum up the study, the bias for covariates has been adjusted by estimating density function for the truncation time variable. Then the effect of possibly time-varying covariates was evaluated in some special semiparametric transformation models.

Keywords: EM algorithm, estimating equation, semiparametric transformation models, time-to-event outcomes, time varying covariate

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Authors: Rojin Bana Derakhshan, Abbas Toloie

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For the purpose of optimizing and developing energy efficiency in building, it is required to recognize key elements of success in optimization of energy consumption before performing any actions. Surveying Principal Components is one of the most valuable result of Linear Algebra because the simple and non-parametric methods are become confusing. So that energy management system implemented according to energy management system international standard ISO50001:2011 and all energy parameters in building to be measured through performing energy auditing. In this essay by simulating used of data mining, the key impressive elements on energy saving in buildings to be determined. This approach is based on data mining statistical techniques using feature selection method and fuzzy logic and convert data from massive to compressed type and used to increase the selected feature. On the other side, influence portion and amount of each energy consumption elements in energy dissipation in percent are recognized as separated norm while using obtained results from energy auditing and after measurement of all energy consuming parameters and identified variables. Accordingly, energy saving solution divided into 3 categories, low, medium and high expense solutions.

Keywords: energy saving, key elements of success, optimization of energy consumption, data mining

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Authors: F. S. Alavi

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In this study, MATLAB engineering software was used in order to model an industrial Ambient Air Vaporizer (AAV), considering combined convection and conduction heat transfers from the fins and the tube. The developed theoretical model was then used to investigate the effects of various design factors such as gas flow rate, ambient air temperature, fin thickness and etc. on total vaporizer ‘s length required. Cryogenic liquid nitrogen was selected as an input fluid, in all cases. According to the results, increasing the inlet fluid flow rate has direct linear effect on the total required length of vaporizer. Vaporizer’s required length decreases by increasing the size of fin radius or size of fin thickness. The dependency of vaporizer’s length on fin thickness’ size reduces at higher values of thickness and gradually converge to zero. For low flow rates, internal convection heat transfer coefficient depends directly on gas flow rate but it becomes constant, independent on flow rate after a specific value. As the ambient air temperature increases, the external heat transfer coefficient also increases and the total required length of vaporizer decreases.

Keywords: heat exchanger, modeling, heat transfer, design

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Authors: Anukriti Verma, Bhawna Rathi, Shivani Sharda

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Reactive Arthritis (ReA) is a disorder that causes inflammation in joints due to certain infections at distant sites in the body. ReA begins with stiffness, pain, and inflammation in these areas especially the ankles, knees, and hips. It gradually causes several complications such as conjunctivitis in the eyes, skin lesions in hand, feet and nails and ulcers in the mouth. Nowadays the diagnosis of ReA is based upon a differential diagnosis pattern. The parameters for differentiating ReA from other similar disorders include physical examination, history of the patient and a high index of suspicion. There are no standard lab tests or markers available for ReA hence the early diagnosis of ReA becomes difficult and the chronicity of disease increases with time. It is reported that enteric disorders such as Inflammatory Bowel Disease (IBD) that is inflammation in gastrointestinal tract namely Crohn’s Disease (CD) and Ulcerative Colitis (UC) are reported to be linked with ReA. Several microorganisms are found such as Campylobacter, Salmonella, Shigella and Yersinia causing IBD leading to ReA. The aim of our study was to perform the in-silico analysis in order to find interactions between microorganisms and human host causing IBD leading to ReA. A systems biology approach for metabolic network reconstruction and simulation was used to find the essential genes of the reported microorganisms. Interactomics study was used to find the interactions between the pathogen genes and human host. Genes such as nhaA (pathogen), dpyD (human), nagK (human) and kynU (human) were obtained that were analysed further using the functional, pathway and network analysis. These genes can be used as putative drug targets and biomarkers in future for early diagnosis, prevention, and treatment of IBD leading to ReA.

Keywords: drug targets, inflammatory bowel disease, reactive arthritis, systems biology

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Authors: Nusrat T. Chowdhury

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Green Supply Chain Management (GSCM) is becoming a key to success for profitable businesses. The various activities contributing to carbon emissions in a supply chain are transportation, ordering and holding of inventory. This research work develops a mixed-integer nonlinear programming (MINLP) model that considers the scenario of a supply chain with multiple periods, multiple products and multiple suppliers. The model assumes that the demand is deterministic, the buyer has a limited storage space in each period, the buyer is responsible for the transportation cost, a supplier-dependent ordering cost applies for each period in which an order is placed on a supplier and inventory shortage is permissible. The model provides an optimal decision regarding what products to order, in what quantities, with which suppliers, and in which periods in order to maximize the profit. For the purpose of evaluating the carbon emissions, three different carbon regulating policies i.e., carbon cap-and-trade, the strict cap on carbon emission and carbon tax on emissions, have been considered. The proposed MINLP has been validated using a randomly generated data set.

Keywords: green supply chain, carbon emission, mixed integer non-linear program, inventory shortage, carbon cap-and-trade

Procedia PDF Downloads 233

Authors: Muhammad Usman Akram

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This research work based on GNSS-Aided Photogrammetry for Digital Mapping. It focuses on topographic survey of an area or site which is to be used in future Planning & development (P&D) or can be used for further, examination, exploration, research and inspection. Survey and Mapping in hard-to-access and hazardous areas are very difficult by using traditional techniques and methodologies; as well it is time consuming, labor intensive and has less precision with limited data. In comparison with the advance techniques it is saving with less manpower and provides more precise output with a wide variety of multiple data sets. In this experimentation, Aerial Photogrammetry technique is used where an UAV flies over an area and captures geocoded images and makes a Three-Dimensional Model (3-D Model), UAV operates on a user specified path or area with various parameters; Flight altitude, Ground sampling distance (GSD), Image overlapping, Camera angle etc. For ground controlling, a network of points on the ground would be observed as a Ground Control point (GCP) using Differential Global Positioning System (DGPS) in PPK or RTK mode. Furthermore, that raw data collected by UAV and DGPS will be processed in various Digital image processing programs and Computer Aided Design software. From which as an output we obtain Points Dense Cloud, Digital Elevation Model (DEM) and Ortho-photo. The imagery is converted into geospatial data by digitizing over Ortho-photo, DEM is further converted into Digital Terrain Model (DTM) for contour generation or digital surface. As a result, we get Digital Map of area to be surveyed. In conclusion, we compared processed data with exact measurements taken on site. The error will be accepted if the amount of error is not breached from survey accuracy limits set by concerned institutions.

Keywords: photogrammetry, post processing kinematics, real time kinematics, manual data inquiry

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Authors: Hossein Ramezani Ali-Akbari

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This paper presents an innovative method to control the rotational speed of a satellite solar panel during its deployment phase. A brushed DC motor has been utilized in the passive spring driven deployment mechanism to reduce the deployment speed. In order to use the DC motor as a damper, its connector terminals have been connected with an external resistance in a closed circuit. It means that, in this approach, there is no external power supply in the circuit. The working principle of this method is based on the back electromotive force (or back EMF) of the DC motor when an external torque (here the torque produced by the torsional springs) is coupled to the DC motor’s shaft. In fact, the DC motor converts to an electric generator and the current flows into the circuit and then produces the back EMF. Based on Lenz’s law, the generated current produced a torque which acts opposite to the applied external torque, and as a result, the deployment speed of the solar panel decreases. The main advantage of this method is to set an intended damping coefficient to the system via changing the external resistance. To produce the sufficient current, a gearbox has been assembled to the DC motor which magnifies the number of turns experienced by the DC motor. The coupled electro-mechanical equations of the system have been derived and solved, then, the obtained results have been presented. A full-scale prototype of the deployment mechanism has been built and tested. The potential application of brushed DC motors as a rotational speed damper has been successfully demonstrated.

Keywords: back electromotive force, brushed DC motor, rotational speed damper, satellite solar panel deployment mechanism

Procedia PDF Downloads 320

Authors: Arsalan Ghaderi, Behzad Karami Matin, Abdolrahim Afkhamzadeh, Abouzar Keshavarzi, Parvin Nokhasi

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Background: Lack of individual health as one of the major health problems among the pilgrims can be followed by several complications. The main aim of this study was to determine factors predicting individual health among pilgrims of Kurdistan County; in the west of Iran and health belief model (HBM) was applied as theoretical framework. Methods: A cross-sectional study was conducted among 100 pilgrims who referred in the red crescent of Kurdistan County, the west of Iran which was randomly selected for participation in this study. A structured questionnaire was applied for collecting data and data were analyzed by SPSS version 21 using bivariate correlations and linear regression statistical tests. Results: The mean age of respondents was 59.45 years [SD: 11.56], ranged from 50 to 73 years. The HBM predictor variables accounted for 47% of the variation in the outcome measure of the individual health. The best predictors for individual health were perceived severity and cause to action. Conclusion: Based on our result, it seems that designing and implementation of educational programs to increase seriousness about complications of lack of individual health and increasing cause to action among the pilgrims may be useful in order to promote individual health among pilgrims.

Keywords: individual health, pilgrims, Iran, health belief model

Procedia PDF Downloads 523