Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates

Optical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and tota

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

In this work, a novel design for the NiO/TiO2 heterojunction solar cells is presented. Highly-pure nanopowders prepared by dc reactive magnetron sputtering technique were used to form the heterojunctions. The electrical characteristics of the proposed design were compared to those of a conventional thin film heterojunction design prepared by the same technique. A higher efficiency of 300% was achieved by the proposed design. This attempt can be considered as the first to fabricate solar cells from highly-pure nanopowders of two different semiconductors.

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

Background: Joubert syndrome (JS) is a very rare autosomal recessive disorder characterized by agenesis of cerebellar vermis, abnormal eye movements, respiratory irregularities, and delayed generalized motor development. Retinal dystrophy and cystic kidneys may also be associated with this clinical syndrome. The importance of recognizing JS is related to the outcome and its potential complications. This syndrome is difficult to diagnose clinically because of its variable phenotype. Its neuroimaging hallmarks include the characteristic molar tooth sign and bat wing-shaped fourth ventricle

Objectives: To compare early pregnancy outcomes, including miscarriage, ectopic pregnancy, multiple pregnancy, and congenital anomalies, among women who conceived following ovulation induction with letrozole or clomiphene citrate. Methods: A prospective comparative observational study was conducted at Al-Elwiya Maternity Teaching Hospital and a private clinic in Baghdad, Iraq, from March 2023 to December 2024. One hundred infertile women aged 21–35 years who conceived after ovulation induction with either letrozole (5 mg/day) or clomiphene citrate (100 mg/day) for five days (cycle days 3–7) were enrolled. Participants were followed through early pregnancy with serial sonography at 6, 8–11, and 18–20 weeks of gestation. Data

Purpose: To validate a UV-visible spectrophotometric technique for evaluating niclosamide (NIC) concentration in different media across various values of pH. Methods: NIC was investigated using a UV-visible spectrophotometer in acidic buffer solution (ABS) of pH 1.2, deionized water (DW), and phosphate buffer solution (PBS), pH 7.4. The characterization of NIC was done with differential scanning calorimeter (DSC), powder X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The UV analysis was validated for accuracy, precision, linearity, and robustness. Results: The DSC spectra showed a single endothermic peak at 228.43 °C (corresponding to the melting point of NIC), while XRD and FTIR analysis confirmed the identit