Computer
Safa S. Abdul-Jabbar; Alaa K. Farhan; Rana F. Ghani
Abstract
Blockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships ...
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Blockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships between data points to draw meaningful conclusions. The field of data analytics in Blockchain is relatively new, and few studies have been conducted to examine the challenges involved in Blockchain data analytics. This article presents a systematic analysis of how data analytics affects Blockchain performance, with the aim of investigating the current state of Blockchain-based data analytics techniques in research fields and exploring how specific features of this new technology may transform traditional business methods. The primary objectives of this study are to summarize the significant Blockchain techniques used thus far, identify current challenges and barriers in this field, determine the limitations of each paper that could be used for future development, and assess the extent to which Blockchain and data analytics have been effectively used to evaluate performance objectively. Moreover, we aim to identify potential future research paths and suggest new criteria in this burgeoning discipline through our review.
Computer
Maryam Raad Shihab; Rana Fareed Ghani; Athraa Jasim Mohammed
Abstract
The traffic surveillance system is a type of intelligent system of traffic control. Traffic control provides solutions to most problems faced by people. It helps to monitor, detect traffic congestion and traffic accidents. As science evolved, it became possible to control traffic using video surveillance. ...
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The traffic surveillance system is a type of intelligent system of traffic control. Traffic control provides solutions to most problems faced by people. It helps to monitor, detect traffic congestion and traffic accidents. As science evolved, it became possible to control traffic using video surveillance. Video surveillance is the most economical option that does not involve high costs or changes in infrastructure. Vehicle detection is one of the main parts of the traffic surveillance system. In this paper, vehicles will be detected using two different artificial intelligence methods (the YOLO method and the HAAR cascade classifier method). The first one is smarter than the second method, and both of them contain machine learning. The first processing step will read the video. Then vehicle detection algorithms are applied using two different ways. The comparison between them depends on the results to find the most effective and applicable vehicle detection method. After implementing the two methods, results were obtained using YOLO, that the accuracy is 91.31% and the error rate is 8.69%, in time 10 sec. As for using the XML (HAAR cascade classifier method) method, the accuracy is 86.9%, the quality is 86.9%, completeness is 90.9%, and the error rate is 13%, in time 17 sec. Thus, we conclude that the YOLO method has better results than the second method.
Computer
Rasha Ismail Ahmed; Rasha Mohammed Mohsin Mohammed Mohsin; Rana Fareed Ghani
Abstract
The rapid growth of the human population and the spread of many bad habits affect the health of human beings, this leads to many health problems, such as heart disease, blood pressure, and diabetes. Some of these diseases require earlier detection and fast treatment, to avoid major risks, such as permanent ...
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The rapid growth of the human population and the spread of many bad habits affect the health of human beings, this leads to many health problems, such as heart disease, blood pressure, and diabetes. Some of these diseases require earlier detection and fast treatment, to avoid major risks, such as permanent damage or even life loss. The fast evolution of communications and nanotechnology nowadays is being facilitated to help with saving lives before great damage happens. This paper suggests a special architecture through which to monitor patients remotely using an Internet of Things (IoT)architecture for the purpose of notifying the paramedics and health care centers to rescue the life of cardiovascular patients. The experiments, after attempts with several types of classification algorithms, showed that The result shows that The decision tree has high accuracy for predicting the new heart attack and saving lives before happening of great damage .the result reached between( 83 to 87) percentage, which is a good percentage to avoid the risk of heart attacks and thus reducing death rates.
Communication
Abdulqader Falhi Jabbar; Rana Fareed Ghani; Asia Ali Salman
Abstract
Road traffic accidents are one of the leading causes of mortality globally. Reducing the number of traffic-related incidents has become a serious socio-economic and public health problem, given the ever-increasing number of cars on the road. As a result, this paper proposes an intelligent vehicle prediction ...
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Road traffic accidents are one of the leading causes of mortality globally. Reducing the number of traffic-related incidents has become a serious socio-economic and public health problem, given the ever-increasing number of cars on the road. As a result, this paper proposes an intelligent vehicle prediction communication mechanism that alerts drivers to any autos that may be overtaking or bypassing the targeted vehicle. The primary goal of this paper is to leverage modern Internet of Things (IoT) and wireless sensor technologies to predict any potential accident that may occur as a result of car accidents. This paper proposes the Collision Prediction of a Moving Vehicle (CPMV) system. The information acquired by CPMV will alert the driver to divert the vehicle in a reasonable amount of time before any harm occurs. It redirects the inbound object that emitted the Ultrasound signal which was received by the vehicle, to a safe location. The proposed system predicts collision between vehicles through Wi-Fi and Bluetooth, using a set of sensors with a precision of 360 degrees and a distance of collision prediction of one meter and at a speed of 200-300 revolutions per minute. The python programming language was utilized to code the programs that control the vehicle during the implementation of this project. The Raspberry Pi 4 is utilized as the controller to examine the vehicle’s spatial data. The test results showed that using this application to deal with an approaching object can be a successful strategy in the three proposed scenarios at different angles and directions.
Computer
Roaa E. Alhassany; Rana F. Ghani
Abstract
In recent years, especially with COVID-19, video conference applications have become very important. Millions of peoples around the world have become to communicate with each other through using video conference applications. The most critical factor in the performance success of video conference applications ...
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In recent years, especially with COVID-19, video conference applications have become very important. Millions of peoples around the world have become to communicate with each other through using video conference applications. The most critical factor in the performance success of video conference applications is the user's perception of the quality of the experience. In this work, an Extreme Learning Machine (ELM) model was proposed for predicting video quality of experience. The proposed system extracts several features from videos that have a significant impact on the quality of the experience. The model performance was validated with unseen data. Spearman’s Rank Correlation Coefficient (SRCC), Root Mean Square Error (RMSE), Pearson’s Linear Correlation Coefficient (PLCC) metrics have been used to measure the accuracy of the model and correlation. The results demonstrate that the proposed model had better performance than models used by the previous researchers that were used for predicting video QoE in terms of precision, correlation, and running time.
Iman Mohammed Hasan; Rana Fareed Ghani
Abstract
Today's insurance industry plays a significant role in a variety of fields, particularly in health insurance. As IoT technology advances, health insurers in IoT networks can obtain real-time medical data for individuals and issue individual insurance policies based on a person's lifestyle. However, sharing ...
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Today's insurance industry plays a significant role in a variety of fields, particularly in health insurance. As IoT technology advances, health insurers in IoT networks can obtain real-time medical data for individuals and issue individual insurance policies based on a person's lifestyle. However, sharing personal data requires a guarantee of privacy and security. This paper suggests a Blockchain technology to solve this problem. The work presents a novel framework that integrates health insurers, IoT-based networks, and Blockchain technology to implement access control protocol using a smart contract for sharing the financial premium of insureds with the stakeholders as non-participants/authorized parties. The evaluation of the proposal results in authorized access within less time compared to traditional data-sharing systems, and the security analysis shows that proposal can protect data from potential threats.