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

   Undoped and Al-doped CdO thin films have been prepared by vacuum thermal evaporation  on  glass  substrate  at  room  temperature  for  various  Al  doping ratios (0.5, 1 and 2)wt.% . The films are characterized by XRD and AFM surface morphology properties. XRD analysis showed that CdO:Al films are highly polycrystalline and exhibit cubic crystal structure of lattice constant averaged to 0.4696 nm with (111) preferred orientation. However, intensity of all peaks rapidly decreases which indicates that the crystallinity decreases with the increase of Al dopant. The grain size decreases with Al content (from 60.81 to 48.03 nm). SEM and AFM were applied to study the morphology an

The present work involves studying the effect of electrolyte composition [@1= 0.5 wt.%  NH₄F / 5% H₂O / 5% Glycerol (GLY)/ 90%  Ethylene Glycol (EG)] and [ @2= 0.5 wt. % NH₄F / 5% H₂O / 95%  Ethylene Glycol (EG)]  on the structural and photoelectrochemical properties of titania nanotubes arrays (TNTAs). TNTAs substrates were successfully carried out via anodization technique and were carried out in 40 V for one hour in different electrolytes (@1, and @2). The properties of physicochemical of TNTAs were distinguished via an X-ray Diffractometer (XRD), Field Emission Scanning Electron Microscope (FESEM), an Energy Dispersive X-ray (EDX), and UV–visible diffuse reflectance. T

The present work involves studying the effect of electrolyte composition [@1= 0.5 wt.%  NH4F / 5% H2O / 5% Glycerol (GLY)/ 90%  Ethylene Glycol (EG)] and [ @2= 0.5 wt. % NH4F / 5% H2O / 95%  Ethylene Glycol (EG)]  on the structural and photoelectrochemical properties of titania nanotubes arrays (TNTAs). TNTAs substrates were successfully carried out via anodization technique and were carried out in 40 V for one hour in different electrolytes (@1, and @2). The properties of physicochemical of TNTAs were distinguished via an X-ray Diffractometer (XRD), Field Emission Scanning Electron Microscope (FESEM), an Energy Dispersive X-ray (EDX), and UV–visible diffuse reflectance. The photoelectrochemical response of TNTAs was evaluated

Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this