Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi

One of the most popular and legally recognized behavioral biometrics is the individual's signature, which is used for verification and identification in many different industries, including business, law, and finance. The purpose of the signature verification method is to distinguish genuine from forged signatures, a task complicated by cultural and personal variances. Analysis, comparison, and evaluation of handwriting features are performed in forensic handwriting analysis to establish whether or not the writing was produced by a known writer. In contrast to other languages, Arabic makes use of diacritics, ligatures, and overlaps that are unique to it. Due to the absence of dynamic information in the writing of Arabic signatures,

Huge number of medical images are generated and needs for more storage capacity and bandwidth for transferring over the networks. Hybrid DWT-DCT compression algorithm is applied to compress the medical images by exploiting the features of both techniques. Discrete Wavelet Transform (DWT) coding is applied to image YCbCr color model which decompose image bands into four subbands (LL, HL, LH and HH). The LL subband is transformed into low and high frequency components using Discrete Cosine Transform (DCT) to be quantize by scalar quantization that was applied on all image bands, the quantization parameters where reduced by half for the luminance band while it is the same for the chrominance bands to preserve the image quality, the zig

We describe the synthesis and characterization of a novel 2D-MnOx material using a combination of HR-TEM, XAS, XRD, and reactivity measurements. The ease with which the 2D material can be made and the conditions under which it can be made implies that water oxidation catalysts previously described as “birnessite-like” (3D) may be better thought of as 2D materials with very limited layer stacking. The distinction between the materials as being “birnessite-like” and “2D” is important because it impacts on our understanding of the function of these materials in the environment and as catalysts. The 2D-MnOx material is noted to be a substantially stronger chemical oxidant than previously noted for other birnessite-like manganese oxi

Abstract:In this paper, some probability characteristics functions (moments, variances,convariance, and spectral density functions) are found depending upon the smallestvariance of the solution of some stochastic Fredholm integral equation contains as aknown function, the sine wave function

Most studies and research have tried to shed light on unemployment and employment in general, with less focus on the problems facing working women and the resulting social and economic consequences that threaten their human and professional lives. For women, working is one of the basic necessities for the sustainability of human life, and it constitutes an essential axis for both sexes and through it. It also gives a person the status and social status where the individual finds a ready opportunity to practice his intentions and desires, test his abilities and talents, and achieve his ambitions. The availability of full employment in general and the joining of women to the labor market is an important and fundamental factor in the sustai

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

In this work, the nuclear density distributions, size radii and elastic electron scattering form factors are calculated for proton-rich 8B, 17F, 17Ne, 23Al and 27P nuclei using the radial wave functions of Woods-Saxon potential. The parameters of such potential for nuclei under study are generated so as to reproduce the experimentally available size radii and binding energies of the last nucleons on the Fermi surface.