Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Recently, numerous the generalizations of Hurwitz-Lerch zeta functions are investigated and introduced. In this paper, by using the extended generalized Hurwitz-Lerch zeta function, a new Salagean’s differential operator is studied. Based on this new operator, a new geometric class and yielded coefficient bounds, growth and distortion result, radii of convexity, star-likeness, close-to-convexity, as well as extreme points are discussed.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita

The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop

Background: Autism spectrum disorder (ASD) is characterized by impairments in social interaction and communication, restricted patterns of behavior, and unusual sensory sensitivities. Saliva may provide an easily accessible sample for analysis. Some salivary constituents levels altered in adolescents with ASD including antioxidants . This study aimed to investigate salivary physicochemical characteristic in relation to oral health status among adolescent with ASD. Materials and methods: Two groups were included in this study: forty institutionalized autistic adolescents and forty apparently healthy school adolescents with age range (12-15 years old, only males) selected randomly from Baghdad. Each group subdivided into two groups according

Salivary peroxidases have biological functions of particular importance to oral health. The aim of this paper is to shed the light on saliva and serum total peroxidases activity as well as the activity of each of salivary peroxidase (SPO) and myeloperoxidase (MPO) in patients with oral tumors. The studied participants were divided into two groups: the first group included 18 oral squamous cell carcinoma patients and 20 age and gender-matched healthy controls while the second group consisted of 20 oral ossifying fibroma patients and 23 age and gender-matched healthy controls. Total peroxidases activity was determined, and its specific activity was calculated in serum and whole mixed saliva as well as in the supernatant and pellet fractions

Background and objectives: Whether to use a cold scalpel or laser surgery to remove a lesion in the skin of the craniofacial area is the main question the surgeon asks him- or herself to do. The study tried to extend the literature with data that may help the surgeons to choose the right method. Methods: Thirty patients with intra- and extraoral craniofacial skin lesions managed by Carbone dioxide (CO2) laser surgery. Results: The most common type of lesion treated was melanocytic nevi (15 patients; 50%). Conclusion: The main complication of CO2 laser surgery is the remaining permanent hypopigmentation of the treated area; however, the CO2 laser has many advantages (especially at the time of surgery) making it a good choice for the manageme

Background: Major depressive disorder (MDD) is mental disorder characterized by an all-encompassing low mood accompanied by low self-esteem, and by loss of interest or pleasure in normally enjoyable activities. The aims of the study: were to determine the prevalence of oral manifestation among patients with major depressive disorder receiving antidepressant drugs, and detect alkaline phosphatase (ALP), Total Salivary proteins (TSP), and Interleukin-6 (IL-6) in relation to MDD patients under treatment and to compare with healthy controls. Materials and method: (50) MDD patients; between the ages of 20 years and 60 years.The depression patients are divided into (25) patients under treatment with fluoxetine (Prozac), and (25) patients under tr