Machine Learning Model for Measuring Cyclomatic Complexity of Source Code
Published in: International Conference On Intelligent Computing, Communications, Networking And Services (ICCNS2023)
Jun 20, 2023
Software developers strive to build high-performance and quality software with a very high degree of coherence among its components, simplified structure, and reduced complexity. A cyclomatic complexity measure is used to identify areas of code that are difficult to maintain or debug by determining how many independent paths, conditional and iteration statements there are through the source code. Using AI, it is possible to estimate and measure the cyclomatic complexity of source code by analyz...
Using natural language processing for programming language code classification with Multinomial Naive Bayes
Published in: Revue d'Intelligence Artificielle
Jun 01, 2023
Ayman Odeh
Munther Odeh
Hussein Odeh
Nada Odeh
Classifying Programming Languages scripts is very important task for several reasons such as: automated analysis, code maintenance, code search, quality assurance, and code understanding; this process is similar to processing natural languages, especially high-level languages like Python, Java, C#, C, C++, PHP, JavaScript, and others. Leveraging natural language processing concepts, this research explores the application of the Multinomial Naïve Bayes (MNB) algorithm to identify and classify pr...
ANN-based critical review of the effective moment of inertia of RC beams
Published in: Emergent Materials
Jun 01, 2023
This paper presents an artificial neural network (ANN)–based critical review of the ACI 318 Code formula for calculating the effective moment of inertia (Ie) of reinforced concrete (RC) beams. The value of Ie varies along the span length from a gross cross-sectional moment of inertia (Ig) for uncracked sections to a cracked cross-sectional moment of inertia (Icr) for cracked sections. Branson’s expression for Ie was adopted by the ACI 318 Code until 2019 when a new equation for Ie was introduce...
Utilizing Artificial Bee Colony Algorithm as Feature Selection Method in Arabic Text Classification
Published in: The International Arab Journal of Information Technology
May 10, 2023
Uni-temporal Sentinel-2 imagery for wildfire detection using deep learning semantic segmentation models
Published in: Geomatics, Natural Hazards and Risk
Apr 05, 2023
Wildfires are common disasters that have long-lasting climate effects and serious ecological, social, and economic effects due to climate change. Since Earth observation (EO) satellites were launched into space, remote sensing (RS) has become a more efficient technique that can be used in agriculture, environmental protection, geological exploration, and wildfires. The increasing number of EO satellites orbiting the earth provides huge amounts of data, such as Sentinel-2 with its Multi Spectral...
Metamaterial inspired electromagnetic bandgap filter for ultra-wide stopband screening devices of electromagnetic interference
Published in: Scientific Reports
Jan 10, 2023
Presented here is a reactively loaded microstrip transmission line that exhibit an ultra-wide bandgap. The reactive loading is periodically distributed along the transmission line, which is electromagnetically coupled. The reactive load consists of a circular shaped patch which is converted to a metamaterial structure by embedded on it two concentric slit-rings. The patch is connected to the ground plane with a via-hole. The resulting structure exhibits electromagnetic bandgap (EBG) properties....