Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce

The objective of this work is to investigate the performance of a conventional three phase induction motor supplied by unbalanced voltages. An effort to study the motor steady state performance under this disturbance is introduced. Using per phase equivalent circuit analysis with the concept of symmetrical components approach, the steady state performance is theoretically calculated. Also, a model for the induction motor with the MATLAB/Simulink SPS tools has been implemented and steady state results were obtained. Both results are compared and show good correlation as well. The simulation model is introduced to support and enhance electrical engineers with a complete understanding for the steady state performance of a fully loaded induc

Cardiovascular disease (CVD) remains the leading cause of mortality in women. Estimating cardiovascular risk using prediction models is essential for guiding preventive strategies. Despite progress, conventional risk models still omit critical women-specific factors, limiting their accuracy. Precision medicine, supported by artificial intelligence, provides a framework to integrate these overlooked determinants. This approach may help close existing gaps in cardiovascular risk prediction. Sex-specific biomarkers that contribute to overall cardiovascular risk can be incorporated into risk assessment tools to improve prevention strategies, early detection, and personalized intervention. The integration of imaging-derived variables enh

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

The research deals with a very important issue that affects women, an important segment of the society. This is because women are the basis of the family and the pillar of the society. Thus, the aim of the research is to examine the level and dimensions of the emotional and existential psychological crisis at the sample of the study. It further aims to investigate the statistical significant difference at the level of (0.05) regarding the feeling of the existential psychological crisis among battered and non-battered women. To reveal the objectives of the study, the researcher applied the existential psychological crisis scale to a sample of (72) women, divided into two groups: (35) battered women, who have been chosen purposefully. Thos

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

Background: The prevalence of obesity is continuously rising world-wide. Obesity is an important risk factor of cardiovascular disease (CVD), metabolic syndrome (MS), and type 2 diabetes (T2D).
Objective: To estimate the frequency of MS in obese versus non-obese subjects in Basrah, Iraq .
Methods: This is a prospective clinical study performed in Al-Sadr Teaching Hospital, Basrah, and included 86 obese subjects (with a BMI ≥ 30), 39 males and 47 females, and 132 non-obese subjects ( with a BMI < 30 ), 60 males and 73 females as a control group. Measurement of height, weight, waist circumference (WC), blood pressure ( BP ), fasting blood glucose ( FBG ), total cholesterol (TC), triglycerides (TG ) and high density lipoprotein-

      Numerical simulations have been investigated to study the external free convective heat transfer from a vertically rectangular interrupted fin arrays. The continuity, Naver-Stockes and energy equations have been solved for steady-state, incompressible, two dimensional, laminar with Boussiuesq approximation by Fluent 15 software. The performance of interrupted fins was evaluated to gain the optimum ratio of interrupted length to fin length (

This research set out to provide a faster, easier, and more efficient process for nanoparticle (NP) synthesis of aluminum oxide NPs preparation by microwave irradiation, using plant extracts separately and in the same way (tea, coffee, rosemary), which is an easy-to-use and inexpensive method. The structural properties were investigated by X-ray diffractometer analysis technique (XRD). The X-ray analysis shows the structure has a polycrystalline nature with a hexagonal phase. The optical properties were studied using ultraviolet visible (UV-Vis) spectrometer, where the energy gap was determined. The surface morphology properties of the prepared aluminum NPs were examined by atomic force microscope (AFM). The Fourier transform infra

In this study, the ability of pistachio shells, as an unconventional adsorbent, to recover thallium cations from contaminated aqueous solutions was investigated. To achieve the objective of the study, practical experiments were conducted using a batch-mode adsorption unit under various operating conditions. The results obtained showed that the pistachio shells have the ability to remove thallium cations with a high efficiency exceeding 86% at room temperature. The results indicated that the maximum treatment efficiency was achieved at values of 7, 350 rpm, 86 ppm, 5 g, 150 min of pH, agitation speed, initial concentration of thallium, dosage of pistachio shell used, and contact time, respectively. Morphological results confirmed tha