Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

The study aims to indicate the role of the agricultural initiative in building agricultural development, mediated by activation of the role of internal and external audit on agricultural initiative projects, for the purpose of meeting the challenges of abuses on agricultural land and lack of water used in agriculture and proportions of high poverty, which led to the rural people of the migration to the city and leave agriculture and livestock, and that of the main conclusions reached by the researcher. When comparing the work of the external auditing agencies (the Federal Office of Financial Supervision) on the initiative of agricultural projects with internal audit services in the Directorate of Agriculture and branches of the Agricultu

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Objective: Assessment of health problems and identify demographical information to elderly. Methodology:
it is a descriptive study, data were collected by the researchers depended on the direct interview with the
elderly by using the study instrument (questionnaire) as well as review the records of the geriatric.
Results: The majority of study sample (66%) were males and (24.3%) were within age group (70-74) years,
(44.7%) were widows, and (41.7%) did not read and write. This study applied the international classification
of diseases(short-table) in (11) items, which stated that most of the elderly were complaining from
health problems: debility of hearing (80.65%), eczema or allergies (69.35%), debility of vision (66.9

This research aims to identify the role that forensic accounting plays on the transparency and quality of the financial statements in trade bank of Iraq and the Gulf Commercial Bank in Babylon. This research came to address the problem that most financial institutions suffer from, which is represented by the lack of transparency and the quality of the financial statements issued in a manner. Annual also the manipulation and fraud in the financial data, which causes a big gap between that institutions and organizational stakeholders. According to the implementation of the research hypothesis and the objectives of the research, a questionnaire was prepared consisting of three axes, the first axis dealing with the demographic distri

Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu