
Islam saeed FathiSuez Canal University · Department of Mathematics
Islam saeed Fathi
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Publications (13)
Brain tumors, marked by unchecked cell proliferation within the central nervous system, present substantial challenges for accurate diagnosis and effective treatment. Early and precise detection is crucial for successful intervention. This study presents an innovative framework aimed at enhancing the detection and classification of brain tumor char...
The increased utilization of digital instruments like smartphones, Internet of Things (IoT) sensors, cameras, and microphones has resulted in extensive amounts of big data. Inherent challenges associated with big data include significant data dimensionality, redundancy, and irrelevant information. The main objective of feature selection is eliminat...
This paper presents an online educational platform that leverages facial expression recognition technology to monitor students' progress within the classroom. Periodically, a camera captures images of students in the classroom, processes these images, and extracts facial data through detection methods. Subsequently , students' learning statuses are...
Orthogonal generalized Laguerre moments of fractional orders (FrGLMs) are signal and image descriptors. The utilization of the FrGLMs in the analysis of big-size signals encounters three
challenges. First, calculating the high-order moments is a time-consuming process. Second, accumulating numerical errors leads to numerical instability and degrade...
The development of Internet of Healthcare Things (IoHT) technology leads to high upgrades in monitor signal systems concerning healthcare. Battery life-saving is one of the biggest issues facing healthcare monitoring signal systems. The most important approach to achieve this goal is to decrease the signal size (i.e., data or signal compression); t...
Remote Healthcare Monitoring Systems (RHMs) that employ fetal phonocardiography (fPCG) signals are highly efficient technologies for monitoring continuous and long-term fetal heart rate. Wearable devices used in RHMs still face a challenge that decreases their efficacy in terms of energy consumption because these devices have limited storage and ar...
Bio-signals are extensively used in diagnosing many diseases in wearable devices. In signal processing, signal reconstruction is one of the essential applications. Discrete orthogonal moments (DOMs) are effective analysis tools for signals that can extract digital information without redundancy. The propagation of numerical errors is a significant...
Bio-signals are extensively used in diagnosing many diseases in wearable devices. In signal processing, signal reconstruction is one of the essential applications. Discrete Orthogonal Moments (DOMs) are effective analysis tools for signals that can extract digital information without redundancy. The propagation of numerical errors is a significant...
Remote Healthcare Monitoring Systems (RHMs) that use ECG signals are very effective tools for the early diagnosis of various heart conditions. However, these systems are still confronted with a problem that reduces their efficiency, such as energy consumption in wearable devices because they are battery-powered and have limited storage. This paper...
In this paper, we have presented a hybrid algorithm for solving some constrained optimization problems. The constraint optimization problems can be solved by handling the constraints. To handle these constrains, we have used penalty functions method. Ant Lion Optimizer (ALO) is one of the recent meta-heuristic algorithms. It inspired by the hunting...
In order to solve constraint optimization problems, constraints should be handled. The most common technique is penalty functions. Ant lion optimizer (ALO) is one of meta-heuristic algorithms which used to solve optimization problems. In this paper, the performance of ALO using different penalty-based methods (static penalty, dynamic penalty, and a...