Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

Background: As a multifactorial disorder, temporomandibular joint (TMD) is difficult to diagnose, and multiple factors affect the joint and cause the temporomandibular disorder. Standardization of clinical diagnosis of TMD should be used to reach a definite clinical diagnosis; the condylar bone may degenerate in accordance with these disorders. Aims: Evaluate the correlation between the clinical diagnosis and degenerative condylar change (flattening, sclerosis, erosion, and osteophyte). Materials and Methods: A prospective study with a study group of 97 TMD patients (total of 194 joints) aged 20 to 50. Patients were sent to cone beam computed tomography (CBCT) to assess the degenerative condylar change. Results: No association was found bet

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

The azo Schiff base [Reaction of 4-aminoanypyrine and P-hydroxy acetophenone] and O-Phenylene diamine have been prepared. One azo Schiff base chelate of Co(Il), Ni(II), Cu(II) and Zn(II)ion was also prepared. The chemical frameworks of the azo Schiff base and like elemental analyses (CHN), determinations of molar conductance, 1 H &13C NMR, IR mass and electronic spectroscopy .The elemental analyses exhibited the combination of [L: M] 1:1 ratio. Established on the values IR spectral, it is showed that the azo Schiff base compound acts as neutral hexadentate ligand bonded with the metal ion from two hydroxyl, two azomethine and two azo groups of the azo Schiff base compound in chelation was confirmed by IR , 1Hand 13CNMR spectral outco

In this study, an efficient compression system is introduced, it is based on using wavelet transform and two types of 3Dimension (3D) surface representations (i.e., Cubic Bezier Interpolation (CBI)) and 1 st order polynomial approximation. Each one is applied on different scales of the image; CBI is applied on the wide area of the image in order to prune the image components that show large scale variation, while the 1 st order polynomial is applied on the small area of residue component (i.e., after subtracting the cubic Bezier from the image) in order to prune the local smoothing components and getting better compression gain. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, t