DC glow discharges were generated between a thin cylindrical anode and a flat cathode, streamers are thought to propagate by photo-ionization; the parameters of photo-ionization depend on the He: CO ratio. Therefore we study streamers in He ( 90%, 80% and 70% ) with (10%, 20% and 30%) CO respectively. The streamer diameter is essentially the change by increase for similar voltage and pressure in all He-CO mixtures.

       The article analyzes the neologisms that arose in the Iraqi dialect after the 2003 US-British invasion and the fall of Saddam Hussein's regime, according to the theory I advocate: "The Basic Outline of Reference," a developed theory of Arab legacy and cognitive theory, which came out in 1987 in America, so we have used the terminology of cognitive grammar. In this theory it is stated that the reference is the interaction between four components: perception, imagination, imaginative comprehension and the linguistic sign or symbolization (the neological word in this article), which are closely related, so that none of them can be lacking, because they constitute a holistic whole that belongs to a deeper level. Let us

Due to its safety, low cost, real-time nature, and widespread availability, ultrasound has been employed as a diagnostic technique for numerous intraocular disorders. Unfortunately, speckle artifact that depends on the tissue is seen in ultrasound imaging. In this study, we present a technique for lowering speckle noise and enhancing ultrasound images to enhance human diagnostic performance. This technique combines the undecimated wavelet transform (UDWT) with a wavelet coefficient mapping function, which was utilized to improve the contrast of the denoised images acquired from the first component after the noise was removed using the UDWT. This technique can be used to enhance the visual quality of medical photographs as well as to enha

     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings