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.
The increased applications of technology in the field of architecture, especially digital technology and aspects of automation, have made a major impact on various aspects of local architecture, especially the traditional ones. As these technologies have succeeded in integrating many technological applications in many traditional and heritage buildings and taking them to more complex uses. And included in it characteristics that were not contained, therefore the research problem was concentrated in the absence of a holistic view of the role of the aspects of automation as a technological and design effect and its mutual effects on traditional buildings (especially the traditional Bagh
This study aimed to investigate the feasibility of treatment actual potato chips processing wastewater in a continuously operated dual chambers microbial fuel cell (MFC) inoculated with anaerobic sludge. The results demonstrated significant removal of COD and suspended solids of more than 99% associated with relatively high generation of current and power densities of 612.5 mW/m3 and 1750 mA/m3, respectively at 100 Ω external resistance.
Arabic language processing with artificial intelligence has evolved significantly in the past decades, from traditional rule- and dictionary-based techniques, through statistical models to modern deep and transformer models. This review intends to present an overview of the most well-known Arabic models as well as datasets used for its training, and the main practical applications such as sentiment analysis, machine translation, speech recognition, and smart assistant. AI-based Arabic NLP has had good progress in the previous decades, from rule and dictionary-based approaches to statistical methods and deep transformative learning models nowadays. In addition to it, the most popular state-of-the-art models that are fine-tuned for the Arabi
... Show MoreThe Al-Kindy College Medical Journal (KCMJ) is an Iraqi scholarly journal published by the Al-Kindy College of Medicine, University of Baghdad. It was officially founded in 2004. It is a peer-reviewed journal, published in both online and printed forms. It has a mission to offer a publication platform that mirrors recent knowledge and findings in the field of medicine and medical sciences. It publishes various types of articles, including editorial, review article, research article, brief report, case report, and letter to editor. It accepts articles in the English language. It was biannually published till 2021 when it started to launch three issues per year. The journal is registered with numerous partners, including Iraqi Academi
... Show MoreObjective(s): To assess the burden of mothers` care for child with colostomy and find out relationships between child and mother socio-demographic data with mothers` burden. Methodology: a descriptive study was conducted from 1 August 2013 to 1 September 2014. The sample consisted of 100 children and their mothers at Baghdad Teaching hospital in Baghdad city. A questionnaire was prepared based on the previous literature review, meeting mothers of children with colostomy, and the Zarit Burden Interview scale. Data has collected through the application of questionnaire and interview techniques. Results: T
Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil
... Show MoreThe aim of the research is to identify the effectiveness of the educational pillars strategy based on Vygotsky's theory in mathematical achievement and information processing of first-grade intermediate students. In pursuit of the research objectives, the experimental method was used, and the quasi-experimental design was used for two equivalent groups, one control group taught traditionally and the other experi-mental taught according to the educational pillars strategy. The research sample consisted of (66) female students from the first intermediate grade, who were inten-tionally chosen after ensuring their equivalence, taking into account several factors, most notably chronological age and their level of mathematics, and they we
... Show MoreThe purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
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Abstract:
We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.
In this research, I estimate the reliability function of cluster function by using the seemingly unrelate
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