Higher College of Technology

About: Higher College of Technology is a based out in . It is known for research contribution in the topics: Higher education & Tourism. The organization has 369 authors who have published 379 publications receiving 729 citations.

Mixed convection flows of tangent hyperbolic fluid past an isothermal wedge with entropy: A mathematical study

Abstract: The non-linear, steady, mixed convective boundary layer flow and heat transfer of an incompressible tangent hyperbolic non-Newtonian fluid from an isothermal wedge in the presence of magnetic field is analyzed numerically using the Keller Box implicit finite difference technique. The entropy analysis due to MHD flow of tangent hyperbolic fluid past an isothermal wedge and viscous dissipation is also included. The numerical code is validated with previous Newtonian studies available in the literature. Graphical and tabulated results are analyzed to study the behavior of fluid velocity, temperature, concentration, shear stress, heat transfer rate, entropy generation number and Bejan number for various emerging thermo physical parameters, namely, Weissenberg number ( We), power Jaw index ( n), mixed convection parameter (,l), pressure gradient parameter ( m), Prandtl number (Pr), Biot number (y), Hartmann number (Ha ), Brinkmann number (Br), Reynolds number (Re ) and temperature gradient ( lI). It is observed that velocity, entropy, Bejan number and surface heat transfer rate are reduced with increasing Weissenberg number, but temperature and local skin friction are increased. Increasing pressure gradient enhances velocity, entropy, local skin friction and surface heat transfer rate but reduces temperature and Bejan number. An increase in an isothermal power law index (n) is observed to increase velocity, Bejan number and surface heat transfer rate but decreases temperature, entropy and local skin friction. Increasing magnetic parameter (Ha) is found to decrease temperature, entropy, surface heat transfer rate and local skin friction and increases velocity and Bejan number. The research is applicable for coating materials in chemical engineering for instance, robust paints, production of aerosol deposition and water soluble solution thermal treatment.

A Comparative Study on Crack-Healing Ability of Al2O3/SiC Structural Ceramic Composites Synthesized by Microwave Sintering and Conventional Electrical Sintering

Abstract: This study was conducted to assess and compare the crack-healing ability of conventional electrical sintered and microwave sintered Al2O3/x wt. % SiC (x = 5, 10, 15, and 20) structural ceramic composites. The crack-healing ability of both conventional electrical sintered and microwave sintered specimens was studied by introducing a crack of ∼100 µm length by Vickers’s indentation and conducting a heat treatment at 1200°C for dwell time of 1 h in air. The flexural or bending strength of sintered, cracked, and crack-healed specimens was determined by three-point bending test, and the phase variations by X-ray diffraction and SEM micrographs before and after crack-healing of both the sintering methods were studied and compared. The results show that almost all the specimens recovered their strength after crack-healing, but the strength of microwave sintered Al2O3/SiC structural ceramic composites has been shown to be better than that of conventional electrical sintered Al2O3/SiC structural ceramic composites. The microwave sintered crack-healed Al2O3/10 wt. % SiC specimen shows higher flexural strength of 794 MPa, which was 105% when compared with conventional electrical sintered Al2O3/10 wt. % SiC and crack-healed Al2O3/10 wt. % SiC specimen. It was found by X-ray diffractogram that before crack-healing, all the conventional electrical sintered samples have SiO2 phase which reduce the crack-healing ability and microwave sintered samples with 15 and 20 wt. % SiC show lesser SiO2 phase and 5 and 10 wt. % SiC samples have no SiO2 phase before crack-healing. However, after crack-healing treatment, all the samples have distinct SiO2 phase along with Al2O3 and SiC phases. Microwave sintered Al2O3/10 wt. % SiC specimen cracks were fully healed which was evident in SEM micrographs.

Real-Time Face Mask Detection in Deep Learning using Convolution Neural Network

Abstract: COVID -19 Pandemic has affected human being without distinguishing the region and religion around the world. Even though vaccine is available now, we should still be use precautionary steps to avoid being affected by this virus. Use of face mask will help to stop the spread of the virus. COVID - 19 face mask detector will help in detecting whether a person is wearing mask or not by the use of its on face mask net with deep learning techniques. With suggested technique of deep learning get an accuracy of 98 percent. Our suggested technique also works with still pictures and give effective results with live video stream captured using the CCTV cameras and able to identify whether person is using face mask or not. It is very useful at the place of the mass gathering and screening like shopping mall and railway station and shopping streets and colleges. By using this tool for the face mask will help in regulating the use of it and if person found not using it will be easily warned by the regulator.

Comprehensive Analysis on Security Threats Prevalent in IoT-Based Smart Farming Systems

Abstract: Smart farming is a vital notion for the development of agriculture and food processing industries globally. Industrial revolution in computing and digital network turned agriculture industry to a digitalized and automated technology. Manual and mechanical tools are replaced by tools that are controlled by mobile phones, drones and Web-based applications. IoT is the major applicant in smart farming that controls sensors in devices and data analysis by remote servers. Security is deployed as built-in mechanisms in the devices or as software tools implemented in the mobile devices, sensor systems and machines that are remotely controlled. Protocol-based security is provided to data that are collected from the fields and to the data that are transmitted to remote servers for processing. However, in recent years vulnerabilities in smart farming applications are demoralized which ensued smart farming systems being victimized to cyber-attacks. This research work provides insight analysis on several security threats that are being subjugating smart farming devices and processes. This paper will provide intrigue on vulnerabilities existing in smart farming systems and the threats that exploit them.