Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 6 of 6
Full-Text Articles in Engineering
M²Brtpc: A Novel Modified Multimodal Biometric Recognition For Toddlers And Pre-School Children Approach, Mahmoud Bahzad, Labib M. Labib, Mostafa Elhosseini, Mahmoud Badawy
M²Brtpc: A Novel Modified Multimodal Biometric Recognition For Toddlers And Pre-School Children Approach, Mahmoud Bahzad, Labib M. Labib, Mostafa Elhosseini, Mahmoud Badawy
Mansoura Engineering Journal
A biometric system based on the characteristics of adults recently achieved an outstanding result. Over the last few decades, many applications have been developed for adults, such as fingerprint, face, iris, and hand-vein. Infant identification suffers from many problems and does not enroll all possible ages. Identifying children using one or any biometric features is the first step in ensuring that they are recognized before the law and that their rights are guaranteed. From another perspective, this prevents baby swaps in hospitals, Identifying Missing Children, and Civil ID Programs. This paper introduces an approach for Multimodal Biometric Recognition for Toddlers …
Detection Optimization Of Rare Attacks In Software-Defined Network Using Ensemble Learning, Ahmed M. El-Shamy, Nawal A. El-Fishawy, Gamal M. Attiya, Mokhtar Ahmed
Detection Optimization Of Rare Attacks In Software-Defined Network Using Ensemble Learning, Ahmed M. El-Shamy, Nawal A. El-Fishawy, Gamal M. Attiya, Mokhtar Ahmed
Mansoura Engineering Journal
Software-defined networking (SDN) is a highly flexible architecture that automates and facilitates network configuration and management. Intrusion detection systems (IDS) are becoming essential components in the network to detect malicious attacks and suspicious activities by continuously monitoring network traffic. Integration between SDN and machine learning (ML) techniques is extensively used to build an effective IDS against all potential cyber-attacks that aim at breaking the network security policy and stealing valuable data. Implementing an IDS based on SDN and ML has the advantage of managing traffic dynamically and fully autonomously to provide high protection against security threats. The main objective of …
Proposed Mitigation Framework For The Internet Of Insecure Things, Mahmoud M. Elgindy, Sally M. Elghamrawy, Ali I. El-Desouky
Proposed Mitigation Framework For The Internet Of Insecure Things, Mahmoud M. Elgindy, Sally M. Elghamrawy, Ali I. El-Desouky
Mansoura Engineering Journal
Intrusion detection systems IDS are increasingly utilizing machine learning methods. IDSs are important tools for ensuring the security of network data and resources. The Internet of Things (IoT) is an expanding network of intelligent machines and sensors. However, they are vulnerable to attackers because of the ubiquitous and extensive IoT networks. Datasets from intrusion detection systems (IDS) have been analyzed deep learning methods such as Bidirectional long-short term memory (BiLSTM). This research presents an BiLSTM intrusion detection framework with Principal Component Analysis PCA (PCA-LSTM-IDS). The PCA-LSTM-IDS is comprised of two layers: extracting layer which using PCA, and the anomaly BiLSTM …
An Optimized Deep Learning-Based Framework For Predicting Diabetes Mellitus Using Ffnn, Norhan S. Elmongy, Sally M. Elghamrawy, Amr M. T. Ali-Eldin, Ali I. Eldesouky
An Optimized Deep Learning-Based Framework For Predicting Diabetes Mellitus Using Ffnn, Norhan S. Elmongy, Sally M. Elghamrawy, Amr M. T. Ali-Eldin, Ali I. Eldesouky
Mansoura Engineering Journal
Diabetes mellitus (DM) is a major public health problem in Egypt, and the illness is regarded as a contemporary epidemic across the world. Diabetes is becoming more common, which is a cause for serious concern. As a result, precise and timely identification of the illness is critical. Health and research institutions have also recently expressed a serious interest in developing and implementing cutting-edge healthcare systems. Therefore, it is necessary to accurately and quickly identify the condition. To solve this issue, scientific research has been carried out, but the outcomes have fallen short. Four layers make up the proposed Diabetes mellitus …
Optimized Deep Learning Audio Tagging Approach, Fatma S. El-Metwally, Ali I. Eldesouky, Sally M. Elghamrawy
Optimized Deep Learning Audio Tagging Approach, Fatma S. El-Metwally, Ali I. Eldesouky, Sally M. Elghamrawy
Mansoura Engineering Journal
Audio signal processing is a method for applying powerful algorithms and techniques to record, improve, save and transmit audio content signals. Audio Tagging (AT) is a challenge that requires predicting the tags of audio clips. Developments in deep learning and audio signal processing have resulted in a significant improvement in audio tagging. Many techniques have been used. Several studies have introduced different audio tagging techniques, but the performance of the results obtained from these studies is insufficient. This study proposes an Optimized Deep Learning Audio Tagging (ODLAT] approach to classify and analyze audio tagging. Each input signal is used to …
Enhanced Load Balancing Based On Hybrid Artificial Bee Colony With Enhanced Β-Hill Climbing In Cloud, Maha Zeedan, Gamal Attiya, Nawal El-Fishawy
Enhanced Load Balancing Based On Hybrid Artificial Bee Colony With Enhanced Β-Hill Climbing In Cloud, Maha Zeedan, Gamal Attiya, Nawal El-Fishawy
Mansoura Engineering Journal
This paper proposes enhanced load balancer based artificial bee colony and β-Hill climbing for improving the performance metrics such as response time, processing cost, and utilization to avoid overloaded or under loaded situations of virtual machines. In this study, the suggested load balancer is called enhanced load balancing based on hybrid artificial bee colony with enhanced β-Hill climbing (ELBABCEβHC) to improve the response time, processing cost and the resource utilization. Our proposed approach starts by ranking the task then the greedy randomized adaptive search procedure (GRASP) is used in initializing populations. Further, the binary artificial bee colony (BABC) enhanced with …