485 research outputs found
Lane Line Detection and Object Scene Segmentation Using Otsu Thresholding and the Fast Hough Transform for Intelligent Vehicles in Complex Road Conditions
No full textAn Otsu-threshold- and Canny-edge-detection-based fast Hough transform (FHT) approach to lane detection was proposed to improve the accuracy of lane detection for autonomous vehicle driving. During the last two decades, autonomous vehicles have become very popular, and it is constructive to avoid traffic accidents due to human mistakes. The new generation needs automatic vehicle intelligence. One of the essential functions of a cutting-edge automobile system is lane detection. This study recommended the idea of lane detection through improved (extended) Canny edge detection using a fast Hough transform. The Gaussian blur filter was used to smooth out the image and reduce noise, which could help to improve the edge detection accuracy. An edge detection operator known as the Sobel operator calculated the gradient of the image intensity to identify edges in an image using a convolutional kernel. These techniques were applied in the initial lane detection module to enhance the characteristics of the road lanes, making it easier to detect them in the image. The Hough transform was then used to identify the routes based on the mathematical relationship between the lanes and the vehicle. It did this by converting the image into a polar coordinate system and looking for lines within a specific range of contrasting points. This allowed the algorithm to distinguish between the lanes and other features in the image. After this, the Hough transform was used for lane detection, making it possible to distinguish between left and right lane marking detection extraction; the region of interest (ROI) must be extracted for traditional approaches to work effectively and easily. The proposed methodology was tested on several image sequences. The least-squares fitting in this region was then used to track the lane. The proposed system demonstrated high lane detection in experiments, demonstrating that the identification method performed well regarding reasoning speed and identification accuracy, which considered both accuracy and real-time processing and could satisfy the requirements of lane recognition for lightweight automatic driving systems
Wild Plant Habitat Characterization in the Last Two Decades in the Nile Delta Coastal Region of Egypt
No full textEnvironmental and land-use changes put severe pressure on wild plant habitats. The present study aims to assess the biodiversity of wild plant habitats and the associated spatiotemporal environmental changes in the coastal region of Dakahlia Governorate following an integrated approach of remote sensing, GIS, and samples analysis. Thirty-seven stands were spatially identified and studied to represent the different habitats of wild plants in the Deltaic Mediterranean coastline region. Physical and chemical characteristics of soil samples were examined, while TWINSPAN classification was used to identify plant communities. Two free Landsat images (TM and OLI) acquired in 1999 and 2019 were processed to assess changes via the production of land use and cover maps (LULC). Moreover, NDSI, NDMI, and NDSI indices were used to identify wild plant habitats. The floristic composition indicated the existence of 57 species, belonging to 51 genera of 20 families. The largest families were Asteraceae, Poaceae, and Chenopodiaceae. The classification of vegetation led to the identification of four groups. Canonical Correspondence Analysis (CCA) revealed that electrical conductivity, cations, organic carbon, porosity, chlorides, and bicarbonates are the most effective soil variables influencing vegetation. The results of the spectral analysis indicated an annual coverage of bare lands (3.56 km2), which is strongly related to the annual increase in vegetation (1.91 km2), water bodies (1.22 km2), and urban areas (0.43 km2). The expansion of urban and agricultural regions subsequently increased water bodies and caused occupancy of bare land, resulting in the development of wild plant habitats, which are mostly represented by the sparse vegetation class as evaluated by NDVI. The increase in mean moisture values (NDMI) from 0.03 in 1999 to 0.15 in 2019 might be explained by the increase in total areas of wild plant habitats throughout the study period (1999–2019). This may improve the adequacy of environments for wild habitats, causing natural plant proliferation
Artificial neural network scheme to solve the hepatitis B virus model
No full textThis article aims to describe the simulation studies of the hepatitis B virus non-linear system using supervised neural networks procedures supported by Levenberg-Marquardt back propagation methodology. The proposed strategy has five distinct quantities: susceptible X(t), symptomatic infections Y(t), chronic infections W(t), recovered population R(t), and a population that has received vaccinations Z(t). The reference data set for all three distinct cases has been obtained utilizing the ND-Solver and Adams method in Mathematica software. The outcomes have been validated with performance plots for all cases. To check the accuracy and effectiveness of proposed methodology mean square error has are presented. State transition, and regression plots are illustrated to elaborated the testing, training, and validation methodology. Additionally, absolute errors for different components of hepatitis B virus model are demonstrated to depict the error occurring during distinct cases. Whereas the data assigned to training is 81%, and 9% for each testing and validation. The mean square error for all three cases is 10−12 this show the accuracy and correctness of proposed methodology
Application of Ternary Nanoparticles in the Heat Transfer of an MHD Non-Newtonian Fluid Flow
No full textThis paper introduces a novel theoretical model of ternary nanoparticles for the improvement of heat transmission. Ternary nanoparticles in a heat conductor are shown in this model. Ternary nanoparticles consist of three types of nanoparticles with different physical properties, and they are suspended in a base fluid. Analytical solutions for the temperature and velocity fields are found by using the Laplace transform approach and are modeled by using a novel fractional operator. As a result, the ternary nanoparticles are identified, and an improved heat transfer feature is observed. Further experimental research on ternary nanoparticles is being carried out in anticipation of a faster rate of heat transmission. According to the graphed data, ternary nanoparticles have greater thermal conductivity than that of hybrid nanoparticles. Moreover, the fractional approach based on the Fourier law is a more reliable and efficient way of modeling the heat transfer problem than the artificial approach. The researchers were driven to create a concept of existing nanoparticles in order to boost heat transfer, since there is a strong demand in the industry for a cooling agent with improved heat transfer capabilities
Numerical analysis of Magnetohydrodynamic convection heat flow in an enclosure
No full textThis article investigates the modeling and numerical simulation of Magnetohydrodynamic (MHD) buoyancy-driven convection flow in a differentially heated, square enclosure. Left vertical side is given a high temperature and the right vertical side is sustained at a low temperature. Horizontal sides of the enclosure are insulated. A constant magnetic field is presumed horizontally. Findings of the governing differential equations are explored numerically considering the impact of Magneto-hydrodynamic (MHD). Problem is deciphered by Galerkin finite element approach in COMSOL Multiphysics. Numerical solutions are computed for different values of Rayleigh number ranging 103≤Ra≤107 and Hartmann number ranging 0≤Ha≤40. Rate of heat that passes from the heated side is affected by increasing Rayleigh and Hartmann numbers. Comportment of MHD free convection heat flow from transient to steady state is numerically examined for a period of 0 to 1 s. The numerical solutions are discussed in respect of streamlines, iso-contours, and isotherms. In addition, physical quantities such as velocity and Nusselt number are studied. It is seen that with increasing values of Rayleigh number there is increase in local Nusselt number distribution on heated side of the cavity. Velocity distribution in the flow domain decreases in variations with increasing Hartmann number
Recovery and Amino Acid Composition of Protein Precipitates Isolated from Rice Starch Processing Liquors
No full textBehavior of stiffened concrete-filled steel tube columns infilled with nanomaterial-based concrete subjected to axial compression
No full textThe use of nanotechnology in the field of construction emerged as the utilization of nanomaterials to improve the mechanical properties of concrete. In this study, a novel form of stiffening scheme was suggested, named a catty-cornered propped concrete-filled steel tube (CFST) column. The performance of the suggested stiffened CFST column was analyzed under axial compression. The steel tube of CFST specimens was filled with normal and nanomaterial-based concrete. The three kinds of nanomaterials were utilized viz., nano-silica (NS), carbon nanotubes (CNT), and nano-titanium dioxide (NT). The results of the investigation were collected in terms of ultimate capacity, load vs strain behavior, and load vs deformation response. The ductility index (DI), secant stiffness, composite interaction, and confining effect variation were also discussed further. It was observed that the suggested stiffening scheme was able to increase the ultimate capacity of unstiffened CFST by approximately 14%. The use of nanomaterials in CFST infill concrete also resulted in an approximately 7% increase in load capacity. Further increasing the number of stiffening bars improved the ductility and stiffness of the column section. On the other hand, the inclusion of nanomaterials resulted in a decrease in the ductility index and improved the stiffness of the section. The proposed stiffening scheme resulted in better composite interaction and increased confinement. It was also concluded that the utilization of nanomaterial-based concrete as an infill in the stiffened CFST column could enhance its performance under axial compression loading
Transmission dynamics of a novel HIV/AIDS model through a higher-order Galerkin time discretization scheme
No full textAbstract There are numerous contagious diseases caused by pathogenic microorganisms, including bacteria, viruses, fungi, and parasites, that have the propensity to culminate in fatal consequences. A communicable disease is an illness caused by a contagion agent or its toxins and spread directly or indirectly to a susceptible animal or human host by an infected person, animal, vector, or immaterial environment. Human immunodeficiency virus (HIV) infection, hepatitis A, B, and C, and measles are all examples of communicable diseases. Acquired immunodeficiency syndrome (AIDS) is a communicable disease caused by HIV infection that has become the most severe issue facing humanity. The research work in this paper is to numerically explore a mathematical model and demonstrate the dynamics of HIV/AIDS disease transmission using a continuous Galerkin–Petrov time discretization of a higher-order scheme, specifically the cGP(2)-scheme. Depict a graphical and tabular comparison between the outcomes of the mentioned scheme and those obtained through other classical schemes that exist in the literature. Further, a comparison is performed relative to the well-known fourth-order Ruge–Kutta (RK4) method with different step sizes. By contrast, the suggested approach provided more accurate results with a larger step size than RK4 with a smaller step size. After validation and confirmation of the suggested scheme and code, we implement the method to the extended model by introducing a treatment rate and show the impact of various non-linear source terms for the generation of new cells. We also determined the basic reproduction number and use the Routh-Hurwitz criterion to assess the stability of disease-free and unique endemic equilibrium states of the HIV model
Novel decision aid model for green supplier selection based on extended EDAS approach under pythagorean fuzzy Z-numbers
No full textThe main objective of this study is to identify the green suppliers that would most effectively assist manufacturing producers in implementing green manufacturing production while including uncertainty and reliability in their decision-making. For this firstly, we justify and manifest the idea of Pythagorean Fuzzy Z-numbers (PyFZNs). It has significant implications for improving the effectiveness of decision-making processes in several theories of uncertainty. It can more flexibly explain real-world data and human cognition due to its capacity to express imprecise and reliable information. Thus it is a more accurate mathematical tool for addressing accuracy and uncertainty. Secondly, we defined the Pythagorean fuzzy Z-number arithmetic aggregation operators and geometric aggregation operators. Thirdly, based on the proposed operators and EDAS (Evaluation based on distance from average solution) approach, a fast decision model is designed to deal with the issue of multi-criteria decision-making. Finally, using PyFZN data we also provide a numerical example to demonstrate the usability of the created multicriteria decision-making (MDM) approach. Moreover, a case study also proves its efficacy
Amino Acid Pattern and Nutritional Evaluation of Precipitates from Aqueous By‐Products of Starch Industry
No full text- …
