Izzat Alsmadi
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View article: Enhanced obstacle detection using bilateral vision-aided transformer neural network for visually impaired persons
Enhanced obstacle detection using bilateral vision-aided transformer neural network for visually impaired persons Open
Obstacle detection remains vital in autonomous navigation and assistive technologies, especially for visually impaired individuals. This work introduces an enhanced obstacle detection framework based on a Bilateral Vision Transformer and C…
View article: HeSRN: Representation Learning On Heterogeneous Graphs via Slot-Aware Retentive Network
HeSRN: Representation Learning On Heterogeneous Graphs via Slot-Aware Retentive Network Open
Graph Transformers have recently achieved remarkable progress in graph representation learning by capturing long-range dependencies through self-attention. However, their quadratic computational complexity and inability to effectively mode…
View article: Enhanced Obstacle Detection Using Bilateral Vision-Aided Transformer Neural Network for Visually Impaired Persons
Enhanced Obstacle Detection Using Bilateral Vision-Aided Transformer Neural Network for Visually Impaired Persons Open
Obstacle detection remains vital in autonomous navigation and assistive technologies, especially for visually impaired individuals. This work introduces an enhanced obstacle detection framework based on a Bilateral Vision Transformer and C…
View article: Cybersecurity Intelligence Through Textual Data Analysis: A Framework Using Machine Learning and Terrorism Datasets
Cybersecurity Intelligence Through Textual Data Analysis: A Framework Using Machine Learning and Terrorism Datasets Open
This study examines multi-lexical data sources, utilizing an extracted dataset from an open-source corpus and the Global Terrorism Datasets (GTDs), to predict lexical patterns that are directly linked to terrorism. This is essential as spe…
View article: Exploring the Potential of Large Language Models in Public Transportation: San Antonio Case Study
Exploring the Potential of Large Language Models in Public Transportation: San Antonio Case Study Open
The integration of large language models (LLMs) into public transit systems presents a transformative opportunity to enhance urban mobility. This study explores the potential of LLMs to revolutionize public transportation management within…
View article: Researching public health datasets in the era of deep learning: a systematic literature review
Researching public health datasets in the era of deep learning: a systematic literature review Open
Objective: Explore deep learning applications in predictive analytics for public health data, identify challenges and trends, and then understand the current landscape. Materials and Methods: A systematic literature review was conducted in…
View article: Stance Detection in the Context of Fake News—A New Approach
Stance Detection in the Context of Fake News—A New Approach Open
Online social networks (OSNs) are inundated with an enormous daily influx of news shared by users worldwide. Information can originate from any OSN user and quickly spread, making the task of fact-checking news both time-consuming and reso…
View article: Using Large Language Models in Public Transit Systems, San Antonio as a case study
Using Large Language Models in Public Transit Systems, San Antonio as a case study Open
The integration of large language models into public transit systems represents a significant advancement in urban transportation management and passenger experience. This study examines the impact of LLMs within San Antonio's public trans…
View article: Transforming Computer Security and Public Trust Through the Exploration of Fine-Tuning Large Language Models
Transforming Computer Security and Public Trust Through the Exploration of Fine-Tuning Large Language Models Open
Large language models (LLMs) have revolutionized how we interact with machines. However, this technological advancement has been paralleled by the emergence of "Mallas," malicious services operating underground that exploit LLMs for nefari…
View article: An Innovative Method of Malicious Code Injection Attacks on Websites
An Innovative Method of Malicious Code Injection Attacks on Websites Open
This paper provides a model to identify website vulnerability to Code Injection Attacks (CIAs). The proposed model identifies vulnerabilities to CIA of various websites, to check vulnerable to CIAs. The lack of existing models in providing…
View article: Predicting Question Quality on StackOverflow with Neural Networks
Predicting Question Quality on StackOverflow with Neural Networks Open
The wealth of information available through the Internet and social media is unprecedented. Within computing fields, websites such as Stack Overflow are considered important sources for users seeking solutions to their computing and progra…
View article: A Review on Searchable Encryption Functionality and the Evaluation of Homomorphic Encryption
A Review on Searchable Encryption Functionality and the Evaluation of Homomorphic Encryption Open
Cloud Service Providers, exemplified by industry leaders like Google Cloud Platform, Microsoft Azure, and Amazon Web Services, deliver a dynamic array of cloud services in an ever-evolving landscape. This sector is witnessing substantial g…
View article: Predictive analytics-based evaluation of performance of public bus transportation San Antonio, Texas as a case study
Predictive analytics-based evaluation of performance of public bus transportation San Antonio, Texas as a case study Open
Citizens in large cities utilize public transportation as an alternative to self-driving for several reasons, such as avoiding traffic congestion and parking costs and utilizing their time for other things (e.g. reading a book or respondin…
View article: A Review on Searchable Encryption Functionality and the Evaluation of Homomorphic Encryption
A Review on Searchable Encryption Functionality and the Evaluation of Homomorphic Encryption Open
Cloud Service Providers, such as Google Cloud Platform, Microsoft Azure, or Amazon Web Services, offer continuously evolving cloud services. It is a growing industry. Businesses, such as Netflix and PayPal, rely on the Cloud for data stora…
View article: Recognition of Arabic Air-Written Letters: Machine Learning, Convolutional Neural Networks, and Optical Character Recognition (OCR) Techniques
Recognition of Arabic Air-Written Letters: Machine Learning, Convolutional Neural Networks, and Optical Character Recognition (OCR) Techniques Open
Air writing is one of the essential fields that the world is turning to, which can benefit from the world of the metaverse, as well as the ease of communication between humans and machines. The research literature on air writing and its ap…
View article: U2-Net: A Very-Deep Convolutional Neural Network for Detecting Distracted Drivers
U2-Net: A Very-Deep Convolutional Neural Network for Detecting Distracted Drivers Open
In recent years, the number of deaths and injuries resulting from traffic accidents has been increasing dramatically all over the world due to distracted drivers. Thus, a key element in developing intelligent vehicles and safe roads is mon…
View article: Recognition of Arabic Air-Written Letters: Machine Learning, Convolutional Neural Networks, and Optical Character Recognition (OCR) Techniques
Recognition of Arabic Air-Written Letters: Machine Learning, Convolutional Neural Networks, and Optical Character Recognition (OCR) Techniques Open
It is a challenging problem that air-written Arabic letters has received a lot of attention in the past decades when compared to commonly spoken languages like English languages. To fill this gap, we propose a strong model that brings toge…
View article: Indexing of Arabic documents automatically based on lexical analysis
Indexing of Arabic documents automatically based on lexical analysis Open
The continuous information explosion through the Internet and all information sources makes it necessary to perform all information processing activities automatically in quick and reliable manners. In this paper, we proposed and implement…
View article: IMPROVING COVERAGE AND NOVELTY OF ABSTRACTIVE TEXT SUMMARIZATION USING TRANSFER LEARNING AND DIVIDE AND CONQUER APPROACHES
IMPROVING COVERAGE AND NOVELTY OF ABSTRACTIVE TEXT SUMMARIZATION USING TRANSFER LEARNING AND DIVIDE AND CONQUER APPROACHES Open
Automatic Text Summarization (ATS) models yield outcomes with insufficient coverage of crucial details and poor degrees of novelty. The first issue resulted from the lengthy input, while the second problem resulted from the characteristics…
View article: Enhancing Neural Text Detector Robustness with μAttacking and RR-Training
Enhancing Neural Text Detector Robustness with μAttacking and RR-Training Open
With advanced neural network techniques, language models can generate content that looks genuinely created by humans. Such advanced progress benefits society in numerous ways. However, it may also bring us threats that we have not seen bef…
View article: Mutation-Based Adversarial Attacks on Neural Text Detectors
Mutation-Based Adversarial Attacks on Neural Text Detectors Open
Neural text detectors aim to decide the characteristics that distinguish neural (machine-generated) from human texts. To challenge such detectors, adversarial attacks can alter the statistical characteristics of the generated text, making …
View article: Resource Allocation Methods in Vanets:a Systematic Literature Review
Resource Allocation Methods in Vanets:a Systematic Literature Review Open
Autonomous vehicles take on a more prominent part of our every day life activities. As the number of vehicles grows so does the need for resources to ensure safe and consistent operations of these vehicles. Today's networks and power grid …
View article: Warm-Starting for Improving the Novelty of Abstractive Summarization
Warm-Starting for Improving the Novelty of Abstractive Summarization Open
ive summarization is distinguished by using novel phrases that are not found in the source text. However, most previous research ignores this feature in favour of enhancing syntactical similarity with the reference. To improve novelty aspe…