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

  In the present paper, Arabic Character Recognition  Edge detection method based on contour and connected components  is proposed. First stage contour extraction feature is introduced to tackle the Arabic characters edge detection problem, where the aim is to extract the edge information presented in the Arabic characters, since it is crucial to understand the character content.         The second stage connected components appling for the same characters to find edge detection. The proposed approach exploits a number of connected components, which move on the character by character intensity values, to establish matrix, which represents the edge information at each pixel location .

An experimental investigation of natural convection heat transfer from an isothermal horizontal,vertical and inclined heated square flat plates with and without circular hole, were carried out in two cases, perforated plates without an impermeable adiabatic hole "open core" and perforated plates with an impermeable adiabatic hole "closed core" by adiabatic plug. The experiments covered the laminar region with a range of Rayleih number of (1.11x106 ≤RaLo≤4.39x106 ), at Prandtle number (Pr=0.7). Practical experiments have been done with variable inclination angles from horizon (Ф=0o ,45o,90o,135oand 180o),facing upward (0o≤Ф<90o), and downward (90o
≤Ф<180o). The results showed that the temperature gradient increases whi

There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

The social tolerance is one of the important variables in personality; it helps growth and development of individual's personality. Theories and the students affirmed that social Tolerance affects the society growth and development as well.
The presents study aims:
1. Estimating the social Tolerance for Baghdad College students.
2. Realizing how College students vary in social Tolerance according to:
Sex, (Male, Female) ٍSpecialization (Scientific, Humanity).
3. Realizing the nature of relationship between social Tolerance of College students and father and mother styles. To achieve this research goals the researcher established parameter (scale) for social Tolerance applied to sample of (500) students male and female. Th

Identification by biological features gets tremendous importance with the increasing of security systems in society. Various types of biometrics like face, finger, iris, retina, voice, palm print, ear and hand geometry, in all these characteristics, iris recognition gaining attention because iris of every person is unique, it never changes during human lifetime and highly protected against damage. This unique feature shows that iris can be good security measure. Iris recognition system listed as a high confidence biometric identification system; mostly it is divide into four steps: Acquisition, localization, segmentation and normalization. This work will review various Iris Recognition systems used by different researchers for each recognit

Iraqi oil crudes have some of the physical and chemical characteristics that distinguish it from other types of oil crudes in the world. Some of these features such us molecular composition, rheological, viscosity and emulsions are studied carefully by researchers. In this work, a comparative study of the linear and the non-linear optical properties for typical heavy and light crude oils of Iraqi origin was studied utilizing Z-scan technique. The He -Ne laser of wavelength 632.8 nm had been used for this purpose. These samples were collected from Basra and Kut oil fields. The values of the non-linear refractive index (n₂), non-linear absorption coefficient (β), and third-order electrical susceptibility (χ³) were e

The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a s

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.