Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of Alzheimer's disease. The system employs MRI and feature extraction methods to categorize images. This paper adopts the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset includes functional MRI and Positron-Version Tomography scans for Alzheimer's patient identification, which were produced for people with Alzheimer's as well as typical individuals. The proposed technique uses MRI brain scans to discover and categorize traits utilizing the Histogram Features Extraction (HFE) technique to be combined with the Canny edge to representing the input image of the Convolutional Neural Networks (CNN) classification. This strategy keeps track of their instances of gradient orientation in an image. The experimental result provided an accuracy of 97.7% for classifying ADNI images.
This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul
... Show MoreIn recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS. This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GP
... Show MoreHepatocellular carcinoma (HCC) is the third most common cause of cancer-related death. Therefore, it is critical for researchers to understand molecular biology in greater depth. In several diseases including cancer, abnormal miRNA expression has been linked to apoptosis, proliferation, differentiation, and metastasis. Many miRNAs have been studied in relation to cancer, including miR-122, miR-223, and others. Hepatitis B and C viruses are the most important global risk factors for HCC. This study is intended to test whether serum miRNAs serve as a potential biomarker for both HCC and viral infections HBV and C. The expression of miRNA in 64 serum samples was analyzed by RT-qPCR. Compared to healthy volunteers, HCC patients' sera expre
... Show MoreAerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A
... Show MoreEight patients (3 male and 5 female) were treated in this study by Endovenous Laser Ablation (EVLA); Mathematical models are proposed to estimate the applied laser power and to assess the recovery period. The estimations of the applied laser power and recovery period in these models will be depended mainly on the diameter of the incompetent vein. In addition, Excel Program was utilized to find the proposed models. A 1470 nm diode laser up to 15W continuous power (CW) was used in the treatment of venous ulcers by EVLA procedure. Following up by duplex ultrasound was started in the 1st week after the first session until the vein is completely closed. The present study concluded that the relationship both between
... Show MoreThe objective of this study is to evaluate the level of cytokines IL-1?, IL-10 and IL-17A in the serum of patients with Alzheimer's disease (AD), vascular dementia (VD) and down syndrome (DS). The results showed that Serum level of IL-1? was significantly increased in AD patients (3.79 ± 0.26 pg/ml) as compared with DS patients (2.78 ± 0.39 pg/ml) or controls (2.78 ± 0.22 pg/ml), while no significant difference was observed between AD and VD (3.25 ± 0.20 pg/ml) patients or between VD patients, DS patients and controls. The serum level of IL-10 was approximated in VD and DS patients and controls (3.39 ± 0.24, 2.77 ± 0.39 and 3.41 ± 0.35 pg/ml, respectively), but was significantly (P ? 0.05) increased in AD patients (5.73 ± 0.55 pg/ml
... Show MoreAudio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to
... Show MoreThe diabetic foot is considered one of the long term diabetes complications caused by a defect in blood vessel and nerve system. This requires dealing with diabetic foot with professional medical care, so as to prevent its development in advanced stages which could end to gangrene and amputation of the foot. This study has been initiated through follow-up of twelve patients with diabetes and the presence various occlusions in lower limb artery. One patient from them was chosen for investigation, this patient has stenosis in popliteal artery and presence multiple stenosis in superficial femoral artery. This study based on analysis present case of patient and prediction for progress stenosis in superficial femoral artery till arrive semi t
... Show MoreMobile Wireless sensor networks have acquired a great interest recently due to their capability to provide good solutions and low-priced in multiple fields. Internet of Things (IoT) connects different technologies such as sensing, communication, networking, and cloud computing. It can be used in monitoring, health care and smart cities. The most suitable infrastructure for IoT application is wireless sensor networks. One of the main defiance of WSNs is the power limitation of the sensor node. Clustering model is an actual way to eliminate the inspired power during the transmission of the sensed data to a central point called a Base Station (BS). In this paper, efficient clustering protocols are offered to prolong network lifetime. A kern
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Objective(s): To assess the job satisfaction during of covid-19 among the nurses in respiratory isolation units of coronavirus disease.
Methodology: A descriptive cross-sectional design was carried out in four hospitals at isolation units of coronavirus disease from the period (21th December, 2021 to 27th January, 2022). A non-probability (convenience) sampling method consists of (300) nurse was selected convenience based on the study criteria. The tool used to measure the job satisfaction is Job satisfaction scale for clinical nursing (JSS-CN). This tool consists of two parts, the first part is for demographic information and consists of 8 items, and the second
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