Physical Sciences and Engineering

The purpose of this study was to investigate the influence of imagery, concentration, level of experience and playing position on penalty kick performance success among the players of the University of Cape Coast (UCC) Youngsters Football Club (FC). Thirty registered players of UCC Youngsters FC for the 2022/2023 season participated in the study. The players were subjected to the taking of kicks from the penalty spot after imagery and concentration intervention programs.

Ransomware attacks have emerged as a major cybersecurity threat in terms of the massive financial and data losses it has inflicted across the globe. Such attacks cannot easily be detected by traditional detection techniques, including signature-based and rule-based detection, because these are issues that rely heavily on predefined characteristics and static rules for their identification purposes.

Dermatological disorders, and especially skin cancer, are a worldwide health issue. Precise and early diagnosis is critical in order to pursue efficient treatment, and machine learning, in this case Convolutional Neural Networks (CNNs), has tremendous potential in computerizing the diagnostic process. This research suggests a Visual Geometry Group Network (VGGNet) model for dermatological disorder diagnosis, specifically for skin disorders like melanoma, psoriasis, and eczema.

Financial fraud activities are a serious threat to the security and integrity of online banking systems. Traditional fraud detection approaches, such as rule-based and simple machine learning models, are not effective in detecting changing patterns of fraud and suffer from high false positive rates and scalability. To overcome these drawbacks, this research introduces BankSafeNet, a Dual-Autoencoder and Transformer-Based Anomaly Detection System for detecting financial fraud.

Maintenance of performance, reliability, and efficiency of any system within distributed computing environments is central to QoS. Conventional QoS optimization methods confront challenges regarding dynamic resource allocation, failure, and adaptation of systems. To overcome these limitations, a hybrid artificial neural network and Ant Colony Optimization model are proposed to provide an efficient QoS optimization strategy.

Internet of Things networks are proliferating rapidly, and securing document sharing over the cloud presents a significant challenge. Traditional encryption techniques cannot create a compromise between security, efficiency, and scalability. The known encryption techniques such as AES, RSA, and ABE have high computational overheads and their inefficient key management render them unsuitable for larger-scale IoT environments.

This research article explores the development and impact of a gamified platform aimed at increasing legal literacy and awareness about children’s rights among children. Despite significant legal frameworks established to protect and promote children’s rights, awareness and understanding of these rights among children still need to be improved. The gamified platform seeks to bridge this gap by making legal education accessible, engaging, and age-appropriate through interactive games and storytelling.

Sugarcane pest and disease detection consider techniques in precision agriculture that would not only be expected to maintain the crops' health but even improve their yields. This research proposes assessing the various detection algorithms for their efficiency in detecting and classifying sugarcane diseases, including Deep Learning (CNN, ResNet, YOLO), Machine Learning (SVM, Random Forest, K-NN), Image Processing, and Hybrid Approaches.

Foot-related ailments, such as microbial infections and discomfort due to prolonged use of footwear, have necessitated the development of functional insoles with therapeutic properties. This study focuses on the development of a medicated bamboo insole infused with Ipomoea staphylina extract, known for its potent antimicrobial and anti-inflammatory properties. Bamboo fiber was selected as the base material due to its breathability, moisture-wicking ability, and eco-friendliness.

The whole world was taken in by surprise with the Covid 19 pandemic, Iraq and its educational institutions are no exception. During that period most institutions closed and tried to implement some kind of Distant Learning, Online Learning or Blended Learning to avoid the spread of the pandemic. This study tries to explore the impact online teaching had on the learners’ outcome by comparing the overall results of students in the first official exam (Intermediate) before Online Learning and after online learning during the pandemic.