Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

The banking sector has a significant impact on the economic growth of the country, and the importance of this sector must assess its financial performance from time to time, to measure the situation related to money for each bank and how to put the supervision of the efficiency of the full. The research aims at evaluating the financial performance according to the elements of the CAMELS model, which including capital adequacy, asset quality, management efficiency, profitability, liquidity and market risk sensitivity. The research included the study of Al-Mansour Investment Bank during the period from 2014 to 2018. The base capital ratio was used to total assets to measure capital adequacy The proportion of investments to total assets to mea

Abstract: A novel design of Mach Zehnder Interferometer (MZI) in terms of using special type of optical fiber that has double clad with graded distribution of the refractive index that can be easily implemented practically was suggested and simulated in this work. The suggested design is compact, rapid, and is simple to be modified and tested. The simulated design contains a MZI of 1546.74 nm of central wavelength that is constructed using special type of double clad optical fiber that has two different numerical apertures. The first aperture will supply single mode propagation via its core, while the second numerical aperture supports a zigzag wave propagation (multimode) in the first clad region. The interferometer’s

The research aimed to statement, which impact that the development of Iraqi auditing standards in the fight against corruption and to fulfill the reform requirements by conducting a comparative study analysis with a framework proposal to amend the Iraqi Audit directory number statement (6) issued by the Accounting and Auditing Standards Board of the Republic of Iraq dated 08/24/2002 on audit planning and supervision on the basis of the latest versions of international auditing standards in this regard.

The researchers concluded that there is a need to update the standards (evidence) audit accredited in the Republic of Iraq in accordance with international auditing standards to meet the requirements of the report of the external a

Objective: The aims of research to identify sample of websites of Arabian medical periodicals and exam applying to
standards for publishing on the internet.
Methodology: A survey method is applied about nine medical periodicals websites and data are collected through
forms include five international standards to assessing websites.
Results: of data collected, the following findings are obtained:
1. Through examining website addresses, unsuitability was found in using Universal Resources Locater, because six of
periodicals use com. in URL. While, all of them not relevance commercial but scientific aim.
2. To measure Credibility Standard by adopting numbers values, the results found, four of periodicals obtained (level

Certainly there is a negative impact on development due to corruption in its corruption forms It is administrative and financial as well as direct impact on all sectors Including the health sector, which has seen in Iraq a marked setback in performance and services , The research aims at the possibility of demonstrating the negative effects of financial and administrative corruption on health institutions and Inability to meet health needs The extent to which Regulatory institutions and institutions manage to reduce financial and administrative corruption and ways of dealing with it The phenomenon of financial and administrative corruption is the most serious phenomenon because of its impact on economic growth, which in turn impedes the

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

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