Automatic recognition of individuals is very important in modern eras. Biometric techniques have emerged as an answer to the matter of automatic individual recognition. This paper tends to give a technique to detect pupil which is a mixture of easy morphological operations and Hough Transform (HT) is presented in this paper. The circular area of the eye and pupil is divided by the morphological filter as well as the Hough Transform (HT) where the local Iris area has been converted into a rectangular block for the purpose of calculating inconsistencies in the image. This method is implemented and tested on the Chinese Academy of Sciences (CASIA V4) iris image database 249 person and the IIT Delhi (IITD) iris database v1 using MATLAB 2017a. This method has high accuracy in the center and radius finding reaches 97% for 2268 iris on CASIA V4 image and 99.77% for 2240 iris images on IITD, the speed is acceptable compared to the real-time detection speed and stable performance.
The lethality of inorganic arsenic (As) and the threat it poses have made the development of efficient As detection systems a vital necessity. This research work demonstrates a sensing layer made of hydrous ferric oxide (Fe2H2O4) to detect As(III) and As(V) ions in a surface plasmon resonance system. The sensor conceptualizes on the strength of Fe2H2O4 to absorb As ions and the interaction of plasmon resonance towards the changes occurring on the sensing layer. Detection sensitivity values for As(III) and As(V) were 1.083 °·ppb−1 and 0.922 °·ppb
Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
The support qualitative information regards as an additional step in the process of decision-making where the method following by companies to provide information help in the creation of value because it is very important to deliver information to investors about their stratigies and what happen truly inside the companies i.e. every case relating with the expectations of stockhotslder and the prices of markets depending on those expectation ,and if the matter isn’t that there will be lack of confidence thate couldn’t be backed again. The decisions of the investors effected by security ,economic ,political, psychological, emotional ,and financial factors .
... Show MoreThe Islamic Bank of Al-Nahrain offers a formula for financing the purchase of real estate through a deferred sale contract, through Murabaha to the order to buy, and the payment of the price is in the form of instalments that include (the purchase price of the profit and the mutual agreement on the real estate). This research aims to show the reflection of real estate murabaha on the bank's investments, by measuring the effect of real estate murabaha on the profits achieved by the Islamic Bank of Al-Nahrain Bank. The growth of 'real estate murabaha' realized from the 'amounts granted by Bank X, in addition to analyzing the financial ratios of profitability indicators, including (return on deposits Y2) and for the years (2016 - 20
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The paper is concerned with, the behavior of the hydrostatic thrust bearings lubricated with liquid-solid lubricants using Einstein viscosity formula, and taking into account the centrifugal force resulting from high speed. Also studied is the effect of the bearing dimensions on the pressure, flow rate, load capacity, shear stress, power consumption and stiffness.
The theoretical results show an increase in load capacity by (8.3%) in the presence of solid graphite particles with concentration of (16%) by weight as compared with pure oil, with increasing shear stress. .
In general the performance of hydrostatic thrust bearings improve for load carrying capacity, volume flow rate,
... Show MoreIn this paper, a miniaturized 2 × 2 electro-optic plasmonic Mach– Zehnder switch (MZS) based on metal–polymer–silicon hybrid waveguide is presented. Adiabatic tapers are designed to couple the light between the plasmonic phase shifter, implemented in each of the MZS arms, and the 3-dB input/output directional couplers. For 6 µm-long hybrid plasmonic waveguide supported by JRD1 polymer (r33= 390 pm/V), a π-phase shift voltage of 2 V is obtained. The switch is designed for 1550 nm operation wavelength using COMSOL software and characterizes by 2.3 dB insertion loss, 9.9 fJ/bit power consumption, and 640 GHz operation bandwidth
Background: Odontogenic tumors are a diverse group of lesions with a variety of clinical behavior and histopathologic subtypes, from hamartomatous and benign to malignant. The study aimed to examine the clinical and pathological features of odontogenic tumors in Baghdad over the last 11 years (2011–2021). Materials and Methods: The present retrospective study analyzed all formalin-fixed, paraffin-embedded tissue blocks of patients diagnosed with an odontogenic tumor that were retrieved from archives at a teaching hospital/College of Dentistry in Baghdad University, Iraq, between 2011 and 2021. The diagnosis of each case was confirmed by examining the hematoxylin and eosin stained sections by two expert pathologists. Data from pati
... Show MoreA three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
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