The two-dimensional transient heat conduction through a thermal insulation of temperature dependent thermal properties is investigated numerically using the FVM. It is assumed that this insulating material is initially at a uniform temperature. Then, it is suddenly subjected at its inner surface with a step change in temperature and subjected at its outer surface with a natural convection boundary condition associated with a periodic change in ambient temperature and heat flux of solar radiation. Two thermal insulation materials were selected. The fully implicit time scheme is selected to represent the time discretization. The arithmetic mean thermal conductivity is chosen to be the value of the approximated thermal conductivity at the i

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

The smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterogenous data from various resources, including unmanned aerial vehicles, surveillance cameras, and low-earth-orbit satellites. One of the core challenges in exploitation of such high temporal data streams, specifically videos, is the trade-off between the quality of video streaming and limited transmission bandwidth. An optimal compromise is needed between video quality and subsequently, rec

This article introduces a numerical study on heat exchange and corrosion coefficients of Zinc–water nanofluid stream in a circular tube fitted with swirl generator utilizing CFD emulation. Different  forms of swirl generator which have the following properties of plain twisted tape (PTT) and baffle wings twisted tape (BTT) embeds with various ratio of twisting (y = 2.93, 3.91 and 4.89), baffle inclination angles (β = 0°, - 30° and 30) joined with 1%, 1.5% and 2% volume fraction of ZnO nanofluid were utilized for simulation. The results demonstrated that the heat and friction coefficients conducted by these two forms of vortex generator raised with Reynolds number, twist ratio and baffle inclination angles decreases. Likewise, t

This paper reports an experimental study regarding the influence of vertical oscillations on the natural convection heat transfer from a vertical channel. An experimental set-up was constructed and calibrated; the vertical channel was tested in atmosphere at 25o
C. The channel-to-ambient temperature difference was varied with the power supply to the electrical heater ranging between
15W to 70W divided into five levels. Data sets were measured under different operating condition from a test rig under six vibrating velocities (VVs) levels ranging from (5-30 m/s) in addition to the stationary state. The results show that the maximum heat transfer enhancement factor (E) occurs at Rayleigh number (Ra=2.328×103 ) and vibrational Reynol

Mechanical degradation hampers the practical usage of polymers for turbulent drag reduction
application. Mechanical degradation refers to the chemical process in which the activation energy of
polymer chain scission is exceeded by mechanical action on the polymer chain, and bond rupture
occurs. When a water-soluble polymer and surfactant are mixed in water solution, the specific structures
(aggregates) are formed, in which polymer film is formed around micelle. In this work, Xanthan gum (XG) –
Sodium lauryl ether sulfate (SELS) complex formation and its effect on percentage viscosity reduction
(%VR) was studied. It was found that SELS surfactant reduced the mechanical degradation of XG much
more efficiently than th

The mediation system is based on settling the dispute amicably through the intervention of a third party by bringing views closer away from the judiciary, which is an amicable way to settle disputes, which disputants resort to voluntarily, but some Western legislation has begun to impose resorting to mediation to settle disputes compulsorily, to take advantage of its advantages, get rid of the disadvantages of resorting to the judiciary in some disputes, and relieve pressure on the courts.

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d