Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the use of Gray Level Co-occurrence Matrix (GLCM) features and DBN classifier provides 98.26% accuracy with the two specific classes were tested. Improvements/Applications: AD is a neurological condition affecting the brain and causing dementia that may affect the mind and memory. The disease indirectly impacts more than 15 million relatives, companions and guardians. The results of the present research are expected to help the specialist in decision making process.
The existence of the Internet, networking, and cloud computing support a wide range of new technologies. Blockchain is one of these technologies; this increases the interest of researchers who are concerned with providing a safe environment for the circulation of important information via the Internet. Maintaining solidity and integrity of a blockchain’s transactions is an important issue, which must always be borne in mind. Transactions in blockchain are based on use of public and private keys asymmetric cryptography. This work proposes usage of users’ DNA as a supporting technology for storing and recovering their keys in case those keys are lost — as an effective bio-cryptographic recovery method. The RSA private key is
... Show MoreThe laser micro-cutting process is the most widely commonly applied machining process which can be applied to practically all metallic and non-metallic materials. While this had challenges in cutting quality criteria such as geometrical precision, surface quality and numerous others. This article investigates the laser micro-cutting of PEEK composite material using nano-fiber laser, due to their significant importunity and efficiency of laser in various manufacturing processes. Design of experiential tool based on Response Surface Methodology (RSM)-Central Composite Design (CCD) used to generate the statistical model. This method was employed to analysis the influence of parameters including laser speed,
... Show MoreFaces blurring is one of the important complex processes that is considered one of the advanced computer vision fields. The face blurring processes generally have two main steps to be done. The first step has detected the faces that appear in the frames while the second step is tracking the detected faces which based on the information extracted during the detection step. In the proposed method, an image is captured by the camera in real time, then the Viola Jones algorithm used for the purpose of detecting multiple faces in the captured image and for the purpose of reducing the time consumed to handle the entire captured image, the image background is removed and only the motion areas are processe
... Show MoreAccuracy in multiple objects segmentation using geometric deformable models sometimes is not achieved for reasons relating to a number of parameters. In this research, we will study the effect of changing the parameters values on the work of the geometric deformable model and define their efficient values, as well as finding out the relations that link these parameters with each other, by depending on different case studies including multiple objects different in spacing, colors, and illumination. For specific ranges of parameters values the segmentation results are found good, where the success of the work of geometric deformable models has been limited within certain limits to the values of these parameters.
In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe
... Show MoreHuman posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre
... Show MoreBackground: Gastroesophageal reflux disease can lead to esophageal complications, including esophagitis, ulceration, stricture, hemorrhage, and Barrett’s esophagus. However, the spectrum of problems associated with GERD has expanded to extra esophageal sites. Chronic cough and asthma are two clinical problems caused or triggered by GERD. Spirometric changes among GERD associated cough and asthma still a topic of ongoing research.
Objectives: This study was designated to evaluate the spirometric picture of GERD associated cough and asthma subjects in relation to different clinical aspects of the disease including body mass index (BMI), disease duration, presence or absence of symptoms as well as endoscop
Background: the most common underlying cause of left ventricular (LV) diastolic dysfunction is myocardial ischemia. Diastolic dysfunction has been reported in up to 90% of patients with coronary artery disease.
The influence of Toxoplasma gondii in the pathogenesis of hepatic disease has lately had considerable attention. The objective of this study is to assess the seroprevalence of T. gondii infection in patients with chronic liver disease from Baghdad-Iraq. All patients have attended Gastroenterology and Hepatology Teaching Hospital, Medical city in Baghdad, Iraq An analytical case–control study was achieved from September to November 2018. Seventy male patients with chronic liver disease (CLD) and 70 control males (free of chronic liver diseases) participated in this study, their ages were between (18-80) years old. Serum samples were taken from all subjects and were analysed with enzyme-linked imm
... Show MoreThis search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com
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