In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and introduced. Optimal results showed that the optimum viscosity and thermal conductivity occurs at maximum temperature.
Thermal evaporation method has used for depositing CdTe films
on corning glass slides under vacuum of about 10-5mbar. The
thicknesses of the prepared films are400 and 1000 nm. The prepared
films annealed at 573 K. The structural of CdTe powder and prepared
films investigated. The hopping and thermal energies of as deposited
and annealed CdTe films studied as a function of thickness. A
polycrystalline structure observed for CdTe powder and prepared
films. All prepared films are p-type semiconductor. The hopping
energy decreased as thickness increased, while thermal energy
increased.
A chemical optical fiber sensor based on surface plasmon resonance (SPR) was developed and implemented using multimode plastic optical fiber. The sensor is used to detect and measure the refractive index and concentration of various chemical materials (Urea, Ammonia, Formaldehyde and Sulfuric acid) as well as to evaluate the performance parameters such as sensitivity, signal to noise ratio, resolution and figure of merit. It was noticed that the value of the sensitivity of the optical fiber-based SPR sensor, with 60nm and 10 mm long, Aluminum(Al) and Gold (Au) metals film exposed sensing region, was 4.4 μm, while the SNR was 0.20, figure of merit was 20 and resolution 0.00045. In this work a multimode
... Show MoreDuring the last few decades, many academic and professional groups gave attention to adopting the multi-criteria decision-making methods in a variety of contexts for decision-making that are given to the diversity and sophistication of their selections. Five different classification methods are tested and assessed in this paper. Each has its own set of five attribute selection approaches. By using the multi-criteria decision-making procedures, these data can be used to rate options. Technique for order of preference by similarity to ideal solution (TOPSIS) is designed utilizing a modified fuzzy analytic hierarchy process (MFAHP) to compute the weight alternatives for TOPSIS in order to obtain the confidence value of each class
... Show MoreObjectives:
To evaluate mothers’ attitudes toward readiness for discharge care at home for a premature baby in Intensive Care Unit at teaching hospitals in Medical City Complex and to find out the relationship between mothers’ attitudes and their socio-demographic characteristics.
Methodology: A quasi-experimental study design was carried out through the period of 6th January 2020 to 2021 to 11th March 2021, to evaluate mother’s attitude toward discharge care plan for premature babies. The study carried out in Welfare Teaching Hospital, Nursing Home Hospital and Baghdad Teaching Hospital at Medical City Complex in Baghdad City on 30 mother of premature babies in neonatal intensive care units using the nonprobability sampling
The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).
Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method.
Background: With the increasing demands for adult orthodontics, a growing need arises to bond attachments to porcelain surfaces. Optimal adhesion to porcelain surface should allow orthodontic treatment without bond failure but not jeopardize porcelain integrity after debonding.The present study was carried out to compare the shear bond strength of metal bracket bonded to porcelain surface prepared by two mechanical treatments and by using different etching systems (Hydrofluoric acid 9% and acidulated phosphate fluoride 1.23%). Materials and Methods: The samples were comprised of 60 models (28mm *15mm*28mm) of metal fused to porcelain (feldspathic porcelain). They were divided as the following: group I (control): the porcelain surface left u
... Show MoreThe existence of the Internet, networking, and cloud computing support a wide range of new technologies. Blockchain is one of these technologies; this increases the interest of researchers who are concerned with providing a safe environment for the circulation of important information via the Internet. Maintaining solidity and integrity of a blockchain’s transactions is an important issue, which must always be borne in mind. Transactions in blockchain are based on use of public and private keys asymmetric cryptography. This work proposes usage of users’ DNA as a supporting technology for storing and recovering their keys in case those keys are lost — as an effective bio-cryptographic recovery method. The RSA private key is
... Show MoreFinding similarities in texts is important in many areas such as information retrieval, automated article scoring, and short answer categorization. Evaluating short answers is not an easy task due to differences in natural language. Methods for calculating the similarity between texts depend on semantic or grammatical aspects. This paper discusses a method for evaluating short answers using semantic networks to represent the typical (correct) answer and students' answers. The semantic network of nodes and relationships represents the text (answers). Moreover, grammatical aspects are found by measuring the similarity of parts of speech between the answers. In addition, finding hierarchical relationships between nodes in netwo
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