The State of Anti-Phishing Platforms: A Survey
The insidious nature of phishing attacks remains a significant and costly challenge for digital systems. These attacks exploit both human vulnerabilities and technical errors, resulting in substantial financial losses, data breaches, and reputational damage for individuals and organizations across the globe. Recognizing this increasing threat has led to the emergence of a diverse market of […]
A High-Performance DNA Multiple Pattern Matching Algorithm Based on Index Binding and ASCII Hashing
Beyond health, the exponential trend in the volume of genomic data, combined with broad access to personal genome sequencing, has generated a pressing demand for fast and scalable algorithms to explore patterns in DNA sequences. Rapid and specific identification of DNA sub-sequences is of critical importance in various applications, such as personalized medicine, evolutionary biology, […]
Evaluating AI Performance in Academic Settings: A Comparative Study of ChatGPT-4 and Gemini
This study conducts a systematic comparison of ChatGPT-4 and Gemini in addressing academic queries across four disciplines: Python programming, financial accounting, business administration, and medical sciences. Through a mixed-methods analysis of 40 standardized questions (balanced between numerical and narrative formats), we evaluate the models’ accuracy, reasoning capabilities, and limitations. Results reveal ChatGPT-4’s superior performance with […]
Predicting employee retention using artificial intelligence and survival analysis approaches
Background: Employee retention is a critical concern for organizations seeking to maintain a stable and productive workforce. Understanding the factors driving turnover is essential for designing effective HR interventions. Methods: This study applies advanced survival analysis techniques, including the Kaplan–Meier estimator, Cox proportional hazards model, and Random Survival Forests (RSF), to predict employee retention and […]
A predictive model for climate change using advanced machine learning algorithms in Egypt
This study evaluates advanced machine learning (ML) models for forecasting daily average temperatures in Egypt, using a dataset from one of the world’s most climate databases, the GHCN-D of the NCEI under NOAA (United States). The dataset spans nine years (January 1, 2015 – December 31, 2023) and consists of 73,562 daily records from 23 […]
A novel integrated model for investigation into employee compliance with information security policies
A key component of a company’s integrity, both financially and in terms of reputation, is information security. When given the right direction, employees can play a significant role in strengthening information security, despite the fact that they are frequently seen as the weakest link in the chain. Businesses are doing this by implementing information security […]
A review of artificial intelligence based control techniques for power electronics
The integration of Artificial Intelligence (AI) into power electronics marks a major advancement in control techniques, providing increased efficiency, adaptability, and reliability across various industrial and commercial applications. This research paper aims to present and review the fields of AI in control systems, focusing on key AI-based techniques such as neural networks, fuzzy logic, genetic […]
Automatic term extraction for Arabic text: Approaches, techniques, and challenges
Automatic Term Extraction (ATE) is an essential task in Natural Language Processing (NLP) that aims to identify domain-specific terms from large corpora. In the context of Arabic, ATE plays an essential role in applications such as ontology construction, dictionary development, information retrieval, and text mining. However, the rich morphological structure, and orthographic ambiguities of Arabic […]
The feature-value paradox: Unsupervised discovery of strategic archetypes in the smartphone market using machine learning
This study employs unsupervised machine learning, a core branch of Artificial Intelligence (AI), and feature importance analysis to identify strategic archetypes in the smartphone market based solely on technical specifications. Moving be- yond traditional price prediction models, we analyze a comprehensive dataset to discover latent product strategies. Using K-Means clustering, we identify five distinct strategic […]
Automated COVID-19 detection from chest X-rays using HOG features
The COVID-19 pandemic has necessitated the development of rapid and accurate diagnostic tools to assist healthcare professionals in disease detection and management [1]. This study presents a different machine learning framework for COVID-19 classification using chest X-ray images, employing Histogram of Oriented Gradients (HOG) feature extraction combined with Principal Component Analysis (PCA) for dimensionality reduction […]