In this paper we present an operational computer vision system for real-time motion detection and recording that can be used in surveillance system. The system captures a video of a scene and identifies the frames that contains motion and record them in such a way that only the frames that is important to us is recorded and a report is made in the form of a movie is made and can be displayed. All parts that are captured by the camera are recorded to compare both movies. This serves as both a proof-of- concept and a verification of other existing algorithms for motion detection. Motion frames are detected using frame differencing. The results of the experiments with the system indicate the ability to minimize some of the problems false detection and missed detections (like in a sudden change of light in the scene). The software part is written in Matlab language as an M-file and using the Simulink library, the hardware part we used a Pentium 4 computer with a web camera or a laptop integrated camera.
Fetal growth restriction is a significant contributor to fetal morbidity and mortality. In addition, there are heightened maternal risks associated with surgical operations and their accompanying dangers. Monitoring fetal development is a crucial objective of prenatal care and effective methods for early diagnosis of Fetal growth restriction, allowing prompt management and timely intervention to improve the outcomes. Screening for Fetal growth restriction can be achieved via many modalities; it can be medical, biochemical, or radiological. Some recommended combining more than one for better outcomes. Currently, there is inconsistency about the best method of Fetal growth restriction screening. In this review, a comprehensive
... Show MoreDue to the intensity of competition between economic units that run the trade in durable goods had to pay a lot of these companies to follow the new selling methods aimed at attracting customers to be able to increase its sales and thereby increase their profits , these methods are installment sales, which had been in great demand by the customers with limited income, who provides them with the possibility of possession and use of such goods and to postpone the full amount of the payment to the seller, This transaction sales have grown even became installment sales system at the present time of the common types of sales transactions and deployed a lot in our environment and in many sectors of the market, and in some cases m
... Show MoreElectronic Health Record (EHR) systems are used as an efficient and effective method of exchanging patients’ health information with doctors and other key stakeholders in the health sector to obtain improved patient treatment decisions and diagnoses. As a result, questions regarding the security of sensitive user data are highlighted. To encourage people to move their sensitive health records to cloud networks, a secure authentication and access control mechanism that protects users’ data should be established. Furthermore, authentication and access control schemes are essential in the protection of health data, as numerous responsibilities exist to ensure security and privacy in a network. So, the main goal of our s
... Show MoreComputer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
... Show MoreThe rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
... Show MoreThis study examined >140 relevant publications from the last few years (2018–2021). In this study, classification was reviewed depending on the operation's progress. Electrocoagulation (EC), electrooxidation (EO), electroflotation (EF), electrodialysis (ED), and electro-Fenton (EFN) processes have received considerable attention. The type of action (individual or hybrid) for each electrochemical procedure was evaluated, and statistical analysis was performed to compare them as a new manner of reviewing cited papers providing a massive amount of information efficiently to the readers. Individual or hybrid operation progress of the electrochemical techniques is critical issues. Their design, operation, and maintenance costs vary depending o
... Show MorePath planning in autonomous robotic systems (ARS) is challenging, especially in dynamic or uncertain environments. Many classical methods are computationally expensive and lack adaptability to real-world scenarios. In order to improve the overall path-planning capabilities of robots; this paper introduces a new smart robotic navigation system which uses Software Defined Network (SDN) and Multi-Spike Elman Neural Network (MS-ENN). The introduced system includes an innovative way to encode temporal information using multiple spikes which can capture much greater amounts of detail about changing environmental characteristics than conventional artificial neural networks. Additionally, it includes a spiking wave-front planner (SWP) to pr
... Show MoreThis paper considers the nonlinear homogeneous fractional Burger's equation as a type of nonlinear fractional partial differential equations (FPDE). Our goal in this paper is to show that an initial value problem (IVP) can be modified with a second initial condition when (α ∈ ( 1,2 ]) as the velocity of the movement, and the obtained solution agrees with the nature of the wave with space and time for the problem. The Caputo fractional derivative is used in all the fractional derivatives. Also, the algorithm of the Laplace transform decomposition method (LTDM) for fractional PDEs is presented. The approximate solution converges to the exact solution in Theorem 1. Also, a numerical simulation is made to confirm the theoretical resu
... Show MoreAs a result of the development and global openness and the possibility of companies providing their services outside their spatial boundaries that were determined by them, and the transformation of the world due to the development of the means of communication into a large global market that accommodates all products from different regions and of the same type and production field, competition resulted between companies, and the race to obtain the largest market share It ensures the largest amount of profits, and it is natural for the advertising promotion by companies for their product to shift from an advertisement for one product to a competitive advertisement that calls on the recipient to leave the competing product and switch to it
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