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All Journal Civil Engineering Journal Mathematics Research and Education Journal
Ghani, Usman
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Civil Engineering, Building, Construction & Architecture Education Mathematics Other

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Road Traffic Accident Analysis and Identification of Black Spot Locations on Highway Iqbal, Asad; Rehman, Zia ur; Ali, Shahid; Ullah, Kaleem; Ghani, Usman
Civil Engineering Journal Vol 6, No 12 (2020): December
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/cej-2020-03091629

Abstract

Road safety is the main problem in developing countries. Every year, millions of people die in road traffic accidents, resulting in huge losses of humankind and the economy. This study focuses on the road traffic accident analysis and identification of black spots on the Lahore-Islamabad Highway M-2. Official data of road traffic accidents were collected from National Highway and Highway Police (NH & MP) Pakistan. The data was digitized on MS Excel and Origin Pro. The accident Point weightage (APW) method was employed to identify the black spots and rank of the top ten black spots. The analysis shows that the trend of road traffic accidents on M-2 was characterized by a high rate of fatal accidents of 35.3%. Human errors account for 66.8% as the major contributing factors in road traffic accidents, while vehicle errors (25.6%) and environmental factors (7.6%) were secondary and tertiary contributing factors. The main causes of road traffic accidents were the dozing on the wheel (27.9%), the careless driving (24.6%), tyre burst (11.7%), and the brakes failure (7.4%). Kallar Kahar (Salt Range) was identified as a black spot (223 km, 224 km, 225 km, 229 km, and 234 km) due to vehicle brake failure. The human error was a major contributory factor in road traffic accidents, therefore public awareness campaign on road safety is inevitable and use of the dozen alarm to overcome dozing on the wheel. Doi: 10.28991/cej-2020-03091629 Full Text: PDF
Challenges for Security in IoT: A Comprehensive Approach with Mathematical Modeling, Zero Trust, and Solutions Ghani, Usman
Mathematics Research and Education Journal Vol. 10 No. 1 (2026): April
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/mrej.2026.vol10(1).22109

Abstract

The Internet of Things (IoT) has transformed modern digital infrastructure by enabling intelligent connectivity among billions of devices across industries, healthcare, transportation, and smart homes. However, the rapid expansion of IoT networks has introduced serious security challenges, including weak authentication, unauthorized access, data interception, and limited device resources. This study proposes a comprehensive IoT security framework that integrates mathematical modeling, lightweight encryption, artificial intelligence, and Zero Trust Architecture (ZTA). Graph theory is applied to analyze trust propagation and identify vulnerable nodes within IoT networks, while dynamic trust scores are used to improve authentication and anomaly detection. Simulation results from a 25-node IoT environment demonstrate that the proposed integrated model achieves higher trust accuracy and detection rates with low computational overhead compared to traditional security approaches. The findings indicate that combining mathematical optimization with Zero Trust principles provides an adaptive, scalable, and efficient solution for strengthening IoT cybersecurity in modern interconnected systems
Co-Authors Ali, Shahid Iqbal, Asad Rehman, Zia ur Ullah, Kaleem