With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

This article investigates how an appropriate chaotic map (Logistic, Tent, Henon, Sine...) should be selected taking into consideration its advantages and disadvantages in regard to a picture encipherment. Does the selection of an appropriate map depend on the image properties? The proposed system shows relevant properties of the image influence in the evaluation process of the selected chaotic map. The first chapter discusses the main principles of chaos theory, its applicability to image encryption including various sorts of chaotic maps and their math. Also this research explores the factors that determine security and efficiency of such a map. Hence the approach presents practical standpoint to the extent that certain chaos maps will bec

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

   This paper aims to prove an existence theorem for Voltera-type equation in a generalized G- metric space, called the -metric space, where the fixed-point theorem in - metric space is discussed and its application.  First, a new contraction of Hardy-Rogess type is presented and also then fixed point theorem is established for these contractions in the setup of -metric spaces. As application, an existence result for Voltera integral equation is obtained.  

Background: Metal ions can be released from metallic orthodontic appliances due to corrosion in the oral cavity; prophylactic mouthwashes may have an effect on ion release from orthodontic wires. Materials and Methods: Thirty six orthodontic sets of half maxillary fixed appliance with 2 types of arch wires SS and NiTi(Morelli) were constructed and immersed in 2 types of mouthwashes; Claradone (non-fluoridated) and Silver Care (fluoridated) for 28 days at 37°C, then the released Ni and Cr ionswere measured using atomic absorption spectrophotometer and compared statistically. Results: Ni ion release was higher from NiTi wire group than SS wire group for both mouthwashes and also was higher for Silver Care group than for Claradone group.

This work was conducted to determine the volumetric mass transfer coefficient (Ky.a) infixed bed adsorption using hexane-benzene mixture by adsorption onto a fixed bed of white silica gel. Benzene concentration was measured by gas chromatography. The effect of feed flow rate and initial concentration of benzene in hexane-benzene mixture on the volumetric mass transfer coefficient and on the adsorption capacity of silica gel was investigated.

In general, the volumetric mass transfer coefficient increases with increasing hexane flow rate, and with increasing initial concentration of benzene in the mixture. The ultimate value of (Ky.a) was at 53 ml/min of hexane flow rate with benzene initial concentration of (6.53 wt. %), and it wa

The main objective of this work is to introduce and investigate fixed point (F. p) theorems for maps that satisfy contractive conditions in weak partial metric spaces (W.P.M.S), and give some new generalization of the fixed point theorems of Mathews and Heckmann. Our results extend, and unify a multitude of (F. p) theorems and generalize some results in (W.P.M.S). An example is given as an illustration of our results.

Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models