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The Blockchain for Healthcare 4.0 Apply in Standard Secure Medical Data Processing Architecture
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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.

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Health Situations Teaching Of Biology The Manner Teaching Its Relation To Ability Mind and Students Technical Medical Institute
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The Present study aims at answering the following questions:
1-What is the level of the teaching style of biology teachers who teach (human and his
health)

2-what is the level of healthy attitude to the teachers of biology who teach (human and his
health).
3- is there any relation between the teaching style of biology teachers who teach (human and
his health)and their student's Ability Mind.
4- is the any relation between the level of the healthy attitude to the teachers of biology who
teach (human and his health).
The researcher made the following for the purpose of answering the question of the study:
1-The card of observing the level of the teaching style (lecture style )to the teachers of
biology

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
The efficiency of cluster analysis to analyzing medical image of Covid-19 patient by using K-means algorithm
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Publication Date
Mon Jan 01 2024
Journal Name
Clinical Laboratory
Histopathological Tracing of HPV Genotypes 6 and 11 in Pediatric Patients in Medical City with Chronic Palatine and Pharyngeal Tonsillitis
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Publication Date
Fri May 30 2025
Journal Name
Iraqi Journal Of Science
A Novel Approach for Synthesizing the Pan-chromatic Band to (10 m) of Landsat 9 Based on Sentinel-2 Data to Improve Classification Performance
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This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Use The moment method to Estimate the Reliability Function Of The Data Of Truncated Skew Normal Distribution
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The Estimation Of The Reliability Function Depends On The Accuracy Of The Data Used To Estimate The Parameters Of The Probability distribution, and Because Some Data Suffer from a Skew in their Data to Estimate the Parameters and Calculate the Reliability Function in light of the Presence of Some Skew in the Data, there must be a Distribution that has flexibility in dealing with that Data. As in the data of Diyala Company for Electrical Industries, as it was observed that there was a positive twisting in the data collected from the Power and Machinery Department, which required distribution that deals with those data and searches for methods that accommodate this problem and lead to accurate estimates of the reliability function,

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Publication Date
Fri Mar 15 2019
Journal Name
Alustath Journal For Human And Social Sciences
A Developmental-Longitudinal Study of Request External Modifiers in Authentic and Elicited Data
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Publication Date
Mon May 15 2017
Journal Name
Journal Of Theoretical And Applied Information Technology
Anomaly detection in text data that represented as a graph using dbscan algorithm
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Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
A Security and Privacy Aware Computing Approach on Data Sharing in Cloud Environment
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Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Statistical Sciences
Use the robust RFCH method with a polychoric correlation matrix in structural equation modeling When you are ordinal data
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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Rock facies classification and its effect on the estimation of original oil in place based on petrophysical properties data
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The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

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