This paper is concerned with introducing and studying the first new approximation operators using mixed degree system and second new approximation operators using mixed degree system which are the core concept in this paper. In addition, the approximations of graphs using the operators first lower and first upper are accurate then the approximations obtained by using the operators second lower and second upper sincefirst accuracy less then second accuracy. For this reason, we study in detail the properties of second lower and second upper in this paper. Furthermore, we summarize the results for the properties of approximation operators second lower and second upper when the graph G is arbitrary, serial 1, serial 2, reflexive, symmetric, transitive, tolerance, dominance and equivalence in table.
In all applications and specially in real time applications, image processing and compression plays in modern life a very important part in both storage and transmission over internet for example, but finding orthogonal matrices as a filter or transform in different sizes is very complex and importance to using in different applications like image processing and communications systems, at present, new method to find orthogonal matrices as transform filter then used for Mixed Transforms Generated by using a technique so-called Tensor Product based for Data Processing, these techniques are developed and utilized. Our aims at this paper are to evaluate and analyze this new mixed technique in Image Compression using the Discrete Wavelet Transfo
... Show MoreEnergy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit
... Show MoreI've been in this work to prepare some complexes containing mixed Kandat with some transitional elements which new complexes according to the best of our knowledge and to refer to the information from the Internet until I have been studying this diagnosis Aalmakdat
The research on coordination polymers chemistry based on organic-metal framework with bridging ligands has accelerated during the past two decades. It is an interested hot topic in the synthetic inorganic chemistry, which allowed the fabrication of a variety of interested materials. These materials have shown a range of applications including light harvesting and magnetic properties. The thesis is divided in three chapters. The first chapter gives a general introduction on the development of self-assembled polymeric species based on transition metal. It is also covered a summary of the literature review on the current state of the art on self-assembled coordination ploymers. Furthermore, it includes a description on various relevant topics
... Show MoreNumerical simulations are carried out to evaluate the coherence concept’s effect on the performance regarding the optical system, when observing and imaging the planet’s surface. In numerous optical approaches, the coherence qualities of light sources play an important role. This paper provides an overview about the mathematical formulation of temporal and spatial coherence and incoherence properties of light sources. The circular aperture was used to describe the optical system like a telescope. The simulation results show that diffraction-limited for incoherent imaging system certainly improves the image. Yet, the quality of the image is degraded by the light source's highly spatial and temporal coherence properties, resulting in a
... Show MoreGenerally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co
... Show MoreReduce the required time for measuring the permeability of clayey soils by using new manufactured cell
Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s
... Show MoreThis study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K
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