As a result of recent developments in highway research as well as the increased use of vehicles, there has been a significant interest paid to the most current, effective, and precise Intelligent Transportation System (ITS). In the field of computer vision or digital image processing, the identification of specific objects in an image plays a crucial role in the creation of a comprehensive image. There is a challenge associated with Vehicle License Plate Recognition (VLPR) because of the variation in viewpoints, multiple formats, and non-uniform lighting conditions at the time of acquisition of the image, shape, and color, in addition, the difficulties like poor image resolution, blurry image, poor lighting, and low contrast, these

Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual info

      Recognizing facial expressions and emotions is a basic skill that is learned at an early age and it is important for human social interaction. Facial expressions are one of the most powerful natural and immediate means that humans use to express their feelings and intentions. Therefore, automatic emotion recognition based on facial expressions become an interesting area in research, which had been introduced and applied in many areas such as security, safety health, and human machine interface (HMI). Facial expression recognition transition from controlled environmental conditions and their improvement and succession of recent deep learning approaches from different areas made facial expression representation mostly based on u

With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review

The purpose of this paper is to introduce and prove some coupled coincidence fixed point theorems for self mappings satisfying -contractive condition with rational expressions on complete partially ordered metric spaces involving altering distance functions with mixed monotone property of the mapping. Our results improve and unify a multitude of coupled fixed point theorems and generalize some recent results in partially ordered metric space. An example is given to show the validity of our main result. 

New complexes of M(II) with mixed ligand of 5-Chlorosalicylic acid (CSA) C7H5ClO3 as primary ligand and L- Valine (L-Val) C5H11NO2 as a secondary ligand were prepared and characterized by elemental analysis (C.H.N), UV., FT-IR, magnetic susceptibility, µeff (B.M) as well as the conductivity measurements (Λm ). In the complexes, the 5-chlorosalicylic acid is bidentate in all complexes coordinating through –OH- and –COO- groups; also L-Valine behaves as a bidentate ligand in all complexes through –NH2 and –COO- groups. These five mixed ligand complexes formulated as Na3[M(CSA)2(L-Val)]. The proposed molecular structure for all complexes is octahedral geometries. The synthesis complexes were tested in vitro for against four bacteria

New complexes of M(II) with mixed ligand of 5-Chlorosalicylic acid (CSA) C7H5ClO3 as primary ligand and L- Valine (L-Val) C5H11NO2 as a secondary ligand were prepared and characterized by elemental analysis (C.H.N), UV., FT-IR, magnetic susceptibility, μeff (B.M) as well as the conductivity measurements (Λm ). In the complexes, the 5-chlorosalicylic acid is bidentate in all complexes coordinating through –OH- and –COO- groups; also L-Valine behaves as a bidentate ligand in all complexes through –NH2 and –COO- groups. These five mixed ligand complexes formulated as Na3[M(CSA)2(L-Val)]. The proposed molecular structure for all complexes is octahedral geometries. The synthesis complexes were tested in vitro for against four bacteria

Market share is a major indication of business success. Understanding the impact of numerous economic factors on market share is critical to a company’s success. In this study, we examine the market shares of two manufacturers in a duopoly economy and present an optimal pricing approach for increasing a company’s market share. We create two numerical models based on ordinary differential equations to investigate market success. The first model takes into account quantity demand and investment in R&D, whereas the second model investigates a more realistic relationship between quantity demand and pricing.

Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The