In this paper, the complexes of Shiff base of Methyl -6-[2-(diphenylmethylene)amino)-2-(4-hydroxyphenyl)acetamido]-2,2-dimethyl-5-oxo-1-thia-4-azabicyclo[3.2.0]heptane-3-carboxylate (L) with Cobalt(II), Nickel(II), Cupper(II) and Zinc(II) have been prepared. The compounds have been characterized by different means such as FT-IR, UV-Vis, magnetic moment, elemental microanalyses (C.H.N), atomic absorption, and molar conductance. It is obvious when looking at the spectral study that the overall complexes obtained as monomeric structure as well as the metals center moieties are two-coordinated with octahedral geometry excepting Co complexes that existed as a tetrahedral geometry. Hyper Chem-8.0.7

The dependence of the energy losses or the stopping power for the ion contribution in D- T hot plasma fuels upon the corresponding energies and the related penetrating factorare arrive by using by a theoretical approximation models. In this work we reach a compatible agreement between our results and the corresponding experimental results.

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

The research stems from its goal of identifying the impact of visual management on the strategic acceleration of business organizations and the state of this effect through the knowledge embedding in the Iraqi oil companies. The oil sector was tested, represented by (3) oil companies, and a sample of (151) individuals who participated in activating the visual management, distributed in higher management levels. The research relied on the descriptiveanalytical approach and the questionnaire was a main tool for collecting data and information. The results showed that visual management positively affects strategic acceleration. Moreover, This effect is amplified by the mediating role played by Embedding Knowledge.

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho