Cloud-based Electronic Health Records (EHRs) have seen a substantial increase in usage in recent years, especially for remote patient monitoring. Researchers are interested in investigating the use of Healthcare 4.0 in smart cities. This involves using Internet of Things (IoT) devices and cloud computing to remotely access medical processes. Healthcare 4.0 focuses on the systematic gathering, merging, transmission, sharing, and retention of medical information at regular intervals. Protecting the confidential and private information of patients presents several challenges in terms of thwarting illegal intrusion by hackers. Therefore, it is essential to prioritize the protection of patient medical data that is stored, accessed, and shared on the cloud to avoid unauthorized access or compromise by the authorized components of E-healthcare systems. A multitude of cryptographic methodologies have been devised to offer safe storage, exchange, and access to medical data in cloud service provider (CSP) environments. Traditional methods have not been effective in providing a harmonious integration of the essential components for EHR security solutions, such as efficient computing, verification on the service side, verification on the user side, independence from a trusted third party, and strong security. Recently, there has been a lot of interest in security solutions that are based on blockchain technology. These solutions are highly effective in safeguarding data storage and exchange while using little computational resources. The researchers focused their efforts exclusively on blockchain technology, namely on Bitcoin. The present emphasis has been on the secure management of healthcare records through the utilization of blockchain technology. This study offers a thorough examination of modern blockchain-based methods for protecting medical data, regardless of whether cloud computing is utilized or not. This study utilizes and evaluates several strategies that make use of blockchain. The study presents a comprehensive analysis of research gaps, issues, and a future roadmap that contributes to the progress of new Healthcare 4.0 technologies, as demonstrated by research investigations.
This study aimed to investigate the role of Big Data in forecasting corporate bankruptcy and that is through a field analysis in the Saudi business environment, to test that relationship. The study found: that Big Data is a recently used variable in the business context and has multiple accounting effects and benefits. Among the benefits is forecasting and disclosing corporate financial failures and bankruptcies, which is based on three main elements for reporting and disclosing that, these elements are the firms’ internal control system, the external auditing, and financial analysts' forecasts. The study recommends: Since the greatest risk of Big Data is the slow adaptation of accountants and auditors to these technologies, wh
... Show MoreObjective: The study aimed to 1) measure the prevalence of depression and anxiety among Iraqi pharmacy and medical students at a number of universities in Baghdad using Hospital Anxiety and Depression Scale (HADS) and 2) investigate the association between various sociodemographic factors and students’ HADS scores. Methods: This study was based on a cross-sectional descriptive design in four universities in Baghdad, Iraq. Depression and anxiety were screened using an Arabic version of the HADS. An online survey was administered via Qualtrics to convenience samples of students at four colleges of pharmacy and a college of medicine between March and June 2018. Multiple linear regression was used to identify factors associated
... Show MoreABSTRACT University college libraries are one of the most important information institutions for all researchers during their research and study life, they seeks to provide information sources such as; books, periodicals, theses, databases, Inquiry service and answering questions services in various disciplines to achieve its goals. In 2020, college libraries of all types stepped up to meet the needs of their users' as they responded to the impacts of COVID-19, also extended necessary lifelines to community members facing job losses, healthcare crises, and remote work and learning during an unprecedented and uncertain time. The research aim to identifying the services provided to the postgraduate students users at University of Baghdad coll
... Show MoreThe present research is descriptive and analytical by nature; it practically presents the method of implementing the standard pattern in an unconventional way using the bias-cut line. The study aims at investigating the variables of bias-cut and their suitability for fitting large-shaped Iraqi ladies. It also aims at exploring the artistic and innovative features of the bias-cut. Therefore, one needs to understand the rules and basics of clothing and the nature of the body to reach the maximum degree of control.Consequently, the study is to answer the following questions: What is the effectiveness of tailoring on the bias-cut in fitting a standard template of a large-shaped Iraqi ladies? Is it possible to obtain from the offered possibil
... Show MoreBackground: Assessment is an important part of the learning cascade in education. Students realize it as an influential motivator to direct and guide their learning. The method of assessment determines the way the students reach high levels of learning. It has been documented that one of factor affecting students’ choice of learning approach is the way how assessment is being performed. Many methods of assessment namely multiple choice questions, essay questions and others are mainly used to assess basic science knowledge in undergraduate education. Objectives: The aim of this study is to compare multiple choice questions (MCQ) and essay questions (EQ) (record the success and failure rate of multiple choice questions (MCQ) and essay quest
... Show MoreThese days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that. The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce
... Show MoreIn this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method
Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
... Show MoreMachine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To
... Show MoreAn analytical approach based on field data was used to determine the strength capacity of large diameter bored type piles. Also the deformations and settlements were evaluated for both vertical and lateral loadings. The analytical predictions are compared to field data obtained from a proto-type test pile used at Tharthar –Tigris canal Bridge. They were found to be with acceptable agreement of 12% deviation.
Following ASTM standards D1143M-07e1,2010, a test schedule of five loading cycles were proposed for vertical loads and series of cyclic loads to simulate horizontal loading .The load test results and analytical data of 1.95
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