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

        The current research aims to investigate the skills of the intended meaning beyond the context when reading poetry among fifth literary students. To achieve the aim of the research, the researcher has followed the descriptive approach and used two tools: an open questionnaire that includes an inquiry about the skills of the intended meaning beyond the poetic context, and a closed questionnaire that were examined by the juries, and modified accordingly. Besides, its validity and stability were examined by applying the study on an exploratory sample of (15) teachers to reach its final version and determine the time required to answer it. Then, the researcher applied it on the research sample of (9

The research dealt with the risks of reinsurance and its impact on the financial performance of the National Insurance Company by focusing on reinsurance in the marine insurance branch. Negative impact on the financial performance of the NICs and the Marine Insurance Branch. The research sample resulted in a main hypothesis that reflects this relationship. Lee in the analysis of financial information reports National Insurance Company of the branch of marine insurance for the period of 2010 until 2017, and the use of (retention) for measuring the re-insurance operations index, and (insurance financial surplus rate) to measure financial performance. For the purpose of obtaining the results, a number of statistical methods were used accord

The research examines the mechanism of application of )ISO 21001: 2018( in the Energy Branch- Electromechanical Engineering at the University of Technology to achieve the quality of the educational service to prepare the branch to obtain the certificate of conformity with the requirements of) ISO 21001: 2018(, the necessary data were collected Depending on the (CHEKLIST) of (ISO 21001: 2018), field interviews and records of the concerned department, The researchers reached a number of results, the most prominent of which was the adoption of high quality leadership leaders and their willingness to implement the standard requirements, The university has a basic structure that qualifies it to implement the international standard, as

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

The research dealt with the impact of reinsurance on the financial surplus of the National Insurance Company by focusing on reinsurance in the marine insurance / merchandise branch. The aim of this research was to show the impact of reinsurance indicators (reinsurance ratios, retention ratios, commission rates earned) on reinsurance operations Data on the research variables were collected based on the inductive and deductive approach in the analysis of information for the financial reports of the National Insurance Company of the Marine Insurance Branch and the insurance portfolio (goods) for the period from 2010 to 2017, and for the purpose of obtaining results was used M a number of statistical methods commensurate with the nature of t

Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,