The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

In this work an experimental study is performed to evaluate the thermal performance
of locally made closed loop solar hot water system using a shell and helical coiled tube
heat exchanger as a storage tank. Several measurements are taken include inlet and outlet
temperatures of both collectors and supply water and temperature distribution within the
storage tank. This is beside the water flow rate in both collectors and load cycle. The
main parameters of the system are obtained.

Background: Otitis media with effusion is characterized by accumulation of fluid in the middle ear in absence of acute inflammation and  it is the most common cause of  acquired hearing loss in children, and may  negatively affect language development failure of medical treatment of middle ear effusion frequently require myringotomy and tympanostomy tube insertion.

Objectives: To determine tympanostomy tube complications of tube in children with chronic otitis media with effusion who were treated with Shah Grommet tube insertion.

Methods: The Medical records of 162 ears of 87 children (52 male and 35 female) were reviewed respectively, the patients ages wer

This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg

<span lang="EN-US">The use of bio-signals analysis in human-robot interaction is rapidly increasing. There is an urgent demand for it in various applications, including health care, rehabilitation, research, technology, and manufacturing. Despite several state-of-the-art bio-signals analyses in human-robot interaction (HRI) research, it is unclear which one is the best. In this paper, the following topics will be discussed: robotic systems should be given priority in the rehabilitation and aid of amputees and disabled people; second, domains of feature extraction approaches now in use, which are divided into three main sections (time, frequency, and time-frequency). The various domains will be discussed, then a discussion of e

&nbsp;&nbsp;&nbsp; Taurodontism is a rare developmental dental anomaly marked by apical displacement of the pulpal floor, enlarged pulp chambers, and root bifurcation or trifurcation near the apex. Its etiology involves genetic mutations, syndromic associations, or developmental disturbances of Hertwig’s epithelial root sheath. Diagnosis relies mainly on radiographic assessment, with CBCT offering superior accuracy, and indices such as Shaw’s and Shifman’s aiding classification. Clinically, taurodontism complicates endodontic, surgical, orthodontic, and restorative procedures and may indicate underlying systemic disorders. Early recognition and interdisciplinary planning are crucial to optimizing patient outcomes. DOI: ht

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

Clothes are considered a means of aesthetic and artistic expression that help to hide the flaws of the body and highlight its merits , it has importance in people's lives as it reflects the individual's idea of himself and his personality. Whereas  the appreciation  in clothing  is a reflection of a person's sense of artistic components and the application of this sense to the clothes of his choice. Regarding the differences in clothing tastes by the university students according to the following variables (gender, specialization, stage of study,  age, monthly income), the current research is considered quantitative descriptive research that is concerned with studying a phenomenon that exists in reality, measuring it

A simple technique is proposed in this paper for estimating the coefficient of permeability of an unsaturated soil based on physical properties of soils that include grain size analysis, degree of saturation or water content, and porosity of the soil. The proposed method requires the soil-water characteristic curve for the prediction of the coefficient of permeability as most of the conventional methods. A procedure is proposed to define the hydraulic conductivity function from the soil water characteristic curve which is measured by the filter paper method. Fitting methods are applied through the program (SoilVision), after indentifying the basic properties of the soil such as Attereberg limits, specific gravity, void ratio, porosity, d