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Full-Text Articles in Architecture
Anti-Phishing Approach For Iot System In Fog Networks Based On Machine Learning Algorithms, Mahmoud Gad Awwad, Mohamed M. Ashour, El Said A. Marzouk, Eman Abdelhalim
Anti-Phishing Approach For Iot System In Fog Networks Based On Machine Learning Algorithms, Mahmoud Gad Awwad, Mohamed M. Ashour, El Said A. Marzouk, Eman Abdelhalim
Mansoura Engineering Journal
As the Internet of Things (IoT) continues to expand, ensuring the security and privacyِ of IoT systems becomes increasingly critical. Phishing attacks pose a significant threat to IoT devices and can lead to unauthorized access, data breaches, and compromised functionality. In this paper, we propose an anti-phishing approach for IoT systems in fog networks that leverages machine learning algorithms, including a .fusion with deep learning techniques We explore the effectiveness of eleven traditional machine learning algorithms combined with deep learning in detecting and preventing phishing attacks in IoT systems. By utilizing a diverse range of algorithms, we aim to enhance …
Deep Learning Based Classification Of Focal Liver Lesions With 3 And 4 Phase Contrast-Enhanced Ct Protocols, Ahmed El-Emam, Hossam El-Din Moustafa, Mohamed Moawad, Mohamed Aouf
Deep Learning Based Classification Of Focal Liver Lesions With 3 And 4 Phase Contrast-Enhanced Ct Protocols, Ahmed El-Emam, Hossam El-Din Moustafa, Mohamed Moawad, Mohamed Aouf
Mansoura Engineering Journal
It had been noticed that 3-phase and 4-phase computed tomography protocols with contrast serve as standard examinations for diagnosing liver tumors. Additionally, many patients require periodic follow-up, which entails significant radiation exposure for them. Advancements in image processing facilitate automated liver lesion segmentation. However, the challenge remains in classifying these small lesions by doctors, especially when the liver has different types of lesions with very little intensity difference. Therefore, deep learning can be utilized for the classification of liver lesions. The present work introduces a CNN-based module for the classification of liver lesions. The module consists of four stages: data …
Revolutionary Artificial Intelligence Architectural Design Solutions; Is It An Opportunity Or A Threat?, Mahmoud Desouki, T. A. El-Haddad, Bahaa El-Boshey
Revolutionary Artificial Intelligence Architectural Design Solutions; Is It An Opportunity Or A Threat?, Mahmoud Desouki, T. A. El-Haddad, Bahaa El-Boshey
Mansoura Engineering Journal
Architectural design is uniquely complex, time-consuming work, so AI promises major benefits but also risks. Architectural design software programs have recently made an impressive development, especially those that use artificial intelligence. AI could transform design and construction with tools enabling generative design, parametric modeling, simulation, and optimization. However, AI’s impact remains unclear. Adoption depends on architects leveraging AI to augment judgment rather than replace it. Factors limiting AI include limited education/experience, threats to creative skills architects value, and unreliable AI design tools. While many see AI as an opportunity, not an endangerment, optimism and uncertainty prevail. AI may ultimately enhance …
Ehf-Fndm: An Efficient Hybrid Features Fake News Detection Methodology On Social Media, Haidy Samir Fahim, Asmaa Mohamed Al-Saied, Ahmed Shaban Samra, Abeer Twakol Khalil
Ehf-Fndm: An Efficient Hybrid Features Fake News Detection Methodology On Social Media, Haidy Samir Fahim, Asmaa Mohamed Al-Saied, Ahmed Shaban Samra, Abeer Twakol Khalil
Mansoura Engineering Journal
People are increasingly using social media to consume and share news. The inherent benefits of social media over traditional news media include its low cost and ease of access. In addition, publishing a news article requires less content censorship on social media. The rapid spread of "fake news" on social media, that is, news that contains intentionally false information, has a significant negative impact on society. For instance, false information about the coronavirus disease "2019" has spread around the world like a virus. Therefore, developing effective methods to detect fake news early has great importance. In this paper, the (Efficient …
Computer Vision Aided Hotspot Creation In Virtual Environments, Lama A. Affara, Bilal E. Nakhal
Computer Vision Aided Hotspot Creation In Virtual Environments, Lama A. Affara, Bilal E. Nakhal
Architecture and Planning Journal (APJ)
Hotspot creation is one of the most important modules within virtual environments which helps show the navigators of these environments some information about semantic elements within it and facilitate the navigation between the virtual spaces. In this paper, a system for automatic hotspot proposals and creation in virtual environments is proposed. The system uses computer vision modules to automatically propose hotspot locations in addition to identifying and creating these hotspots with candidate labels. Two main modules used in the system are object detection and scene segmentation. The scene segmentation helps give candidate hotspot areas and provides an overall understanding of …
Using Deep Learning To Generate Front And Backyards In Landscape Architecture, Mehmet O. Senem, Mustafa Koç, Hayriye E. Tunçay, İmdat As
Using Deep Learning To Generate Front And Backyards In Landscape Architecture, Mehmet O. Senem, Mustafa Koç, Hayriye E. Tunçay, İmdat As
Architecture and Planning Journal (APJ)
The use of artificial intelligence (AI) engines in the design disciplines is a nascent field of research, which became very popular over the last decade. In particular, deep learning (DL) and related generative adversarial networks (GANs) proved to be very promising. While there are many research projects exploring AI in architecture and urban planning, e.g., in order to generate optimal floor layouts, massing models, evaluate image quality, etc., there are not many research projects in the area of landscape architecture - in particular the design of two-dimensional garden layouts. In this paper, we present our work using GANs to generate …