lar water heating systems with heat pipes of three diameter groups of 16, 22 and 28.5 mm. The first and third groups had evaporator lengths of 1150, 1300 and 1550 mm. The second group had an additional length of 1800 mm. all heat pipes were of fixed condenser length of 200 mm. Ethanol at 50% fill charge ratio of the evaporator volume was used as the heat pipes working fluid. Each heat pipe condenser section was inserted in a storage tank and the evaporator section inserted into an evacuated glass tube of the Owens- Illinois type. The combined heat pipe and evacuated glass tube form an active solar collector of a unique design.
The resulting ten solar water heating systems were tested outdoors under the meteorological conditions of Bag

Increasing the power conversion efficiency (PCE) of silicon solar cells by improving their junction properties or minimizing light reflection losses remains a major challenge. Extensive studies were carried out in order to develop an effective antireflection coating for monocrystalline solar cells. Here we report on the preparation of a nanostructured cerium oxide thin film by pulsed laser deposition (PLD) as an antireflection coating for silicon solar cell. The structural, optical, and electrical properties of a cerium oxide nanostructure film are investigated as a function of the number of laser pulses. The X-ray diffraction results reveal that the deposited cerium oxide films are crystalline in nature and have a cubic fluorite. The field

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi

This paper examines the decolonizing methods used by Leslie Marmon Silko in her novel Ceremony (1977) to heal the indigenous people from the patriarchal traditions of the white hegemony. This study aims to emphasize the vulnerable responses of the Pueblo people to the memories of the clan and to highlight Silko’s methods to sustain the history and lifestyle of the indigenous people. Therefore, Silko’s novel can be situated historically and culturally within memory-studies. To analyze the contrasting behaviors of characters, this paper projects the relationship between the collective patriarchal doctrines and that of the individual within the framework of memory studies. Theories of Jan and Aleida Assmann are used here to explore the

The focus of this research revolves around the importance level of sialic acid in the reasoning of cases, including tumors and then evaluate the patient's response to treatment and its impact on the immune response there are a lot of evidence showing that parts Alkrbu ???????? in peptides sugary and glycoproteins play an important role in Alfalitin life and responsiveness

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

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