In this study, an efficient photocatalyst for water splitting was developed. The Cr₂O₃ and TiO₂ nanoparticles (Cr₂O₃-TNPs) nanocomposite with (Chitosan extract) was created using ecologically friendly methods, such as the impregnation technique as TiO₂ exhibits nano spherical (TNPs) shape structure. According to the researchers, this nanocomposite material enhanced its ability to absorb ultraviolet light while also speeding up the recombination of photogenerated electrons and holes. The TNPs and prepared Cr₂O₃-TNPs were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy dispersive x-ray sp

In this experimental study, which was carried out in photonics laboratory at Strathclyde University, UK, dynamics of a multi-Quantum well semiconductor active medium laser, was studied. This is in order to study its emission stability and pulse shape development under the influence of strong optical feedback level with different deriving currents, in the free space transmission medium. An external stable resonator was constructed by inserting high reflectivity dielectric mirror outside the laser output, 20 cm apart from it, which is an extralarge external cavity. Controlling the reflected back optical power was done by using a nonpolarized (50:50) beam splitter. The external resonator supported by focusing (plano-convex) lens in order to

Background: Microscopic examination of parotid gland reveals hypertrophy of the aciner cells sometimes two to three times greater than normal size of PG, in cases associated with longstanding diabetes. This study was designed to determine the effects of duration, fasting plasma glucose and glycosylated hemoglobin on parotid gland enlargement among poorly controlled type 2 diabetes mellitus. Subjects, Materials, and Method: This study was conducted on 36 parotid glands of 18 with type 2 DM , at age range ( 40-60) years, all of them were selected from subjects attending (Endocrine clinic for diabetic patients) in Baghdad Teaching Hospital. , pg was measured with ultrasonography in both longitudinal and horizontal plane. Results: the rate of e

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

The researcher studied transportation problem because it's great importance in the country's economy. This paper which ware studied several ways to find a solution closely to the optimization, has applied these methods to the practical reality by taking one oil derivatives which is benzene product, where the first purpose of this study is, how we can reduce the total costs of transportation for product of petrol from warehouses in the province of Baghdad, to some stations in the Karsh district and Rusafa in the same province. Secondly, how can we address the Domandes of each station by required quantity which is depending on absorptive capacity of the warehouses (quantities supply), And through r

In this paper, we describe a new method for image denoising. We analyze properties of the Multiwavelet coefficients of natural images. Also it suggests a method for computing the Multiwavelet transform using the 1st order approximation. This paper describes a simple and effective model for noise removal through suggesting a new technique for retrieving the image by allowing us to estimate it from the noisy image. The proposed algorithm depends on mixing both soft-thresholds with Mean filter and applying concurrently on noisy image by dividing into blocks of equal size (for concurrent processed to increase the performance of the enhancement process and to decease the time that is needed for implementation by applying the proposed algorith

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to