In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

Background: Coronavirus, which causes respiratory illness, has been a public health issue in recent decades. Because the clinical symptoms of infection are not always specific, it is difficult to expose all suspects to qualitative testing in order to confirm or rule out infection as a test. Methods: According to the scientific studies and investigations, seventy-three results of scientific articles and research  were obtained using PubMed, Medline, Research gate and Google Scholar. The research keywords used were COVID-19, coronavirus, blood parameters, and saliva. Results: This review provides a report on the changes in the blood and saliva tests of those who are infected with the COVID-19.COVID-19 is a systemic infection that has

16S ribosomal RNA (16S rRNA) gene sequences used to study bacterial phylogeny and taxonomy have been by far the most common housekeeping genetic marker utilized for identification and ancestor determination. This study aimed to investigate, for the first time, the relationship between Klebsiella spp. isolated from clinical and environmental samples in Iraq.

Fifty Klebsiella spp. isolates were isolated from clinical and environmental sources. Twenty-five isolates were collected from a fresh vegetable (Apium graveolens) and 25 from clinical samples (sputum, wound swab, urine). Enteric bacteria were isolated on selective and differential media and identified by an automatic identification system, vitek-2.

The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

This paper presents a hybrid approach called Modified Full Bayesian Classifier (M-FBC) and Artificial Bee Colony (MFBC-ABC) for using it to medical diagnosis support system. The datasets are taken from Iraqi hospitals, these are for the heart diseases and the nervous system diseases. The M-FBC is depended on common structure known as naïve Bayes. The structure for network is represented by D-separated for structure's variables. Each variable has Condition Probability Tables (CPTs) and each table for disease has Probability. The ABC is easy technique for implementation, has fewer control parameters and it could be easier than other swarm optimization algorithms, so that hybrid with other algorithms to reach the optimal structure. In the

The most prevalent chronic complication of diabetes mellitus is diabetic neuropathy. The pathogenesis of diabetic neuropathy is exacerbated by hyperglycemia-induced oxidative stress, which causes nerves to deteriorate in a programmed manner. Many clinical trials depend on supplement in an attempt to improve neuropathy symptoms such as (pain & tingling) and patient quality of life, one of them is Coenzyme Q10 which is reported to have an anti-inflammatory and antioxidant effects, and was totally nontoxic and non-reported side effects. This study aimed to evaluate using a Coenzyme Q10 supplement as an adjuvant therapy to gabapentin to improve the clinical symptoms of diabetic neuropathy in relation to its anti-inflammatory and antioxid

This research presents a new algorithm for classification the
shadow and water bodies for high-resolution satellite images (4-
meter) of Baghdad city, have been modulated the equations of the
color space components C1-C2-C3. Have been using the color space
component C3 (blue) for discriminating the shadow, and has been
used C1 (red) to detect the water bodies (river). The new technique
was successfully tested on many images of the Google earth and
Ikonos. Experimental results show that this algorithm effective to
detect all the types of the shadows with color, and also detects the
water bodies in another color. The benefit of this new technique to
discriminate between the shadows and water in fast Matlab pro