A5028950807- Infrastructure Maintenance and Monitoring
- Groundwater and Watershed Analysis
- Traffic Prediction and Management Techniques
- Air Quality and Health Impacts
- Flood Risk Assessment and Management
- Urban Transport and Accessibility
- COVID-19 impact on air quality
- Transportation Planning and Optimization
- Automated Road and Building Extraction
- Hydrology and Watershed Management Studies
- Noise Effects and Management
- Impact of Light on Environment and Health
- Asphalt Pavement Performance Evaluation
- Land Use and Ecosystem Services
- Handwritten Text Recognition Techniques
- Remote-Sensing Image Classification
- Acoustic Wave Phenomena Research
- Traffic and Road Safety
- Vehicle Noise and Vibration Control
- Sustainable Building Design and Assessment
- Earthquake Detection and Analysis
- Remote Sensing and Land Use
- Neural Networks and Applications
- Marine and coastal ecosystems
- earthquake and tectonic studies
University of Sharjah
2017-2024
University of British Columbia
2022-2024
Okanagan University College
2023
University of British Columbia Hospital
2023
Institute of Engineering Science
2021
University of Detroit Mercy
2002
Meeting water demands is a critical pillar for sustaining normal human living standards, industry evolution and agricultural growth. The main obstacles developing countries in arid regions include unplanned urbanisation limited resources. Locating constructing dams strategic priority of to preserve store water. Recent advances remote sensing, geographic information system (GIS), machine learning (ML) techniques provide valuable tools producing dam site suitability map (DSSM). In this...
The increase in water demand and the scarcity of fresh arid regions have contributed to depletion groundwater. Artificial Groundwater Recharge (AGR) is an advanced strategy that contributes combating shortage issues. Limited efforts been exerted evaluate demarcate AGR potential zones United Arab Emirates (UAE). current study aims delineate zone mapping using traditional analytical hierarchy process (AHP) a hybrid deep learning model namely, Convolutional Neural Network-Xtreme Gradient...
Among all the natural hazards, earthquake prediction is an arduous task. Although many studies have been published on hazard assessment (EHA), very few use of artificial intelligence (AI) in spatial probability (SPA). There a great deal complexity observed SPA modeling process due to involvement seismological geophysical factors. Recent shown that insertion certain integrated factors such as ground shaking, seismic gap, and tectonic contacts AI model improves accuracy extent. Because...
This paper presents the development of a new model for predicting traffic incident duration using random forests (RFs), data-driven machine learning technique. Utilizing an extensive dataset with over 140,000 records and 52 variables, developed models were optimized by fine-tuning their parameters. The best-performing RF achieved mean absolute error (MAE) 36.652 min, which is acceptable given wide range considered (1–1,440 min). Another set was short 5- to 120-minute duration. performance...
Earthquakes are the most destructive natural hazards because of their adversely severe impacts on urban areas. affect people's lives and properties, thus captivating extensive attention seismologists. Carrying out probability hazard assessment for prevention, reduction mega-events recovery will be great significance in affected Given that limited studies have attempted to estimate earthquake Spatial Probability Assessment (SPA) Arabian Peninsula, this study aims evaluate SPA Earthquake...
The performance of asphalt pavement is highly affected by climate factors, such as temperature and precipitation. Different moisture conditions change the paving material properties, which consequently influence performance. Considerable research has been conducted to study effect factors on performance; however, there are no focused studies that have investigated pavements in cold regions. In this research, different design regions utilising data extracted from Long-Term Pavement...
This study presents an analysis of the impact COVID-19 lockdown on people’s mobility trends, air quality, and utility consumption in Sharjah, United Arab Emirates (UAE). Records subsequent easing measures, infection vaccination rates, community reports, remotely sensed ground-based quality data, (electricity, water, gas) data were collected analyzed study. The trends reflected stringency increasing residential sector but decreasing all other sectors. showed significant improvement...
Climate change is undoubtedly affecting the global weather of Earth. Rapid human civilization has mainly caused this in last few decades. This research examined spatial and temporal land surface temperature (LST) United Arab Emirates (UAE) coastal cities located an arid region that faced massive urbanization over 50 years. We estimated LST using by-products Landsat MODIS images covering 2000 until 2020. The assessment was performed two contexts, i.e., spatially temporally, daytime vs....
Urbanization is typically demonstrated by expansion of a city's infrastructure, mainly development its roads and buildings. In particular, transportation infrastructure key indicator growth in the city since backbone economic prosperity. Recent advances satellite imagery, terms improved spatial temporal resolutions, enable efficient identification change patterns prediction built-up areas. this study, two approaches were adopted to quantify assess pattern urbanization. The first approach...
Accurate prediction of roadway traffic noise remains challenging. Many researchers continue to improve the performance their models by either adding more variables or improving modeling algorithms. In this research, machine learning (ML) techniques were developed predict accurately. The ML applied were: regression decision trees, support vector machine, ensembles, and artificial neural network. parameters each these fine-tuned achieve best results. addition, a state-of-the-art hybrid...
The problem of estimating earthquake risk is one the primary themes for researchers and investigators in field geosciences. combined assessment spatial probability determination at large scales challenging. To best authors’ knowledge, there no updated earthquake-hazard-and-risk assessments Eurasia region have been published since 1999. Considering that characterized by a seismically active Alpine–Himalayan fault zone Pacific Ring Fire, which are frequently affected devastating events,...
The aim of this article is to develop an automatic algorithm for the classification non stationary signals. application context classify uterine electromyogram (EMG) events prevent onset preterm birth. idea discriminate between by allocating them physiological classes: contractions, foetus motions, Alvarez or Long Duration Low Frequency waves. Our method based on Wavelet Packet (WP) decomposition and choice a best basis purpose. Before classification, there need detect in recorded...