Showing for: Sustainable Cities and Communities
View All ResearchUsing a neural network model to assess the effect of antistripping agents on the performance of moisture-conditioned asphalt
Moisture damage in asphalt is one of the prime concerns for flexible pavements degradation worldwide. Many of the pavement distresses are the direct and indirect outcomes of the moisture intrusion in asphalt pavement. This study focuses on developing a neural network (NN) to determine the effect of types and percentages [...]
Characterization of crash-prone drivers in Saudi Arabia – A multivariate analysis
This study conducted a survey of traffic crashes with the data collected from police stations in the three cities of Saudi Arabia involving different features related to crashes, drivers, vehicles, and understanding of traffic signs. Among the chauffeurs, drivers at fault and not at fault were separated and investigated through [...]
Radiological impact of NORM generated by oil and gas industries in the kingdom of Bahrain
A study of the external background radiation in areas affected by NORM generated by oil and gas industrial activities has been performed in the Kingdom of Bahrain. In this framework, two experimental residential areas, Awali and Riffa Views, were selected due to the presence of extensive oil and gas exploration [...]
Towards statistical significance of configurational models: New evidence of variance and bootstrapping
Configurational modelling involves simple but powerful methodologies that seamlessly integrate the design process and has high adherence by professionals. However, a traditionally intuitive approach, rather than a statistically informed one, occasionally compromises such models. As a consequence, the models often do not reach statistical significance and therefore are of limited [...]
Assessment of spatial variations of particulate matter (PM10 and PM2.5) in Bahrain identified by air quality index (AQI)
The rapid urbanization, industrialization, modernization, and the frequent Middle Eastern dust storms have negatively impacted the ambient air quality in Bahrain. The objective of this study is to identify the most critical atmospheric air pollutants with emphasis on their potential risk to health based on calculated AQI (air quality index) [...]
Linkage between company scores and stock returns
Previous studies on company scores conducted at firm-level, generally concluded that there exists a positive relation between company scores and stock returns. Motivated by these studies, this study examines the relationship between company scores (Corporate Governance Score, Economic Score, Environmental Score, and Social Score) and stock returns, both at portfolio-level [...]
The syntactic signature of starbucks’ locations Towards a machine-learning approach to location decision-making
The space syntax Theory of Natural Movement postulates that everything else being equal, land use selects their location based on the asymmetry of accessibility created by the configuration of the street network. In this article, I test the hypothesis whether configurational (syntactic) properties of an urban street network are relevant [...]
Moisture damage evaluation in SBS and lime modified asphalt using AFM and artificial intelligence
Damage due to moisture in polymer modified asphalt pavements has been investigated for several decades; yet, the exact and mathematical causes of moisture are not precisely known. Nanoscale experiment has been conducted in this study with an atomic force microscopy (AFM) to determine these effects in terms of adhesive and [...]
Gardens on the Arid Climate
Bahrain is located in the climate of the arid zone which rainfall is low and irregular. This paper discusses the approaches which response to the local context that has been implemented by the government of Bahrain to sustain the quality of the public garden in the arid climate, turning to [...]
Predicting compressive strength of blended cement concrete with ANNs
Predicting the compressive strength of concrete is important to assess the load-carrying capacity of a structure. However, the use of blended cements to accrue the technical, economic and environmental benefits has increased the complexity of prediction models. Artificial Neural Networks (ANNs) have been used for predicting the compressive strength of [...]