Sharif Digital Repository

Traffic accidents are one of the leading causes of death in the world. During the last decade driver distraction played a significant role in occurrence of road crashes. Since the issue is becoming a widespread concern in many countries, the main objective of the present study was to investigate the influence of driver distraction on the various aspects of traffic accidents. In this regard, the data source of reported crashes of the United States of America in year 2010 is used. Three main property of crashes including severity, type, and avoidance maneuver are studied. Analysis of accidents severity by generalized ordered logit model indicated that phone usage and in-vehicle distraction... 

In the literature on transportation demand analysis, there is an ongoing debate among researchers regarding the causality of the relationship between the built environment and travel behavior. The central issue in this context is residential self-selection, which refers to individuals' tendency to choose their residential location based on their travel abilities, needs, and preferences. Ignoring this phenomenon leads to an overestimation of the true impact of built environment characteristics on travel behavior, resulting in inefficient policy-making based on such estimates. The objective of this research is to examine the effect of residential self-selection on travel mode choice,... 

A new phase of matter which is known as quark-gluon plasma is created after ultrarelativistic nucleus-nucleus collisions. Experimental data imply that hydrodynamic equations can explain this new phase of matter. On the other hand, observations show that the geometry of initial energy distribution fluctuates event-by-event, even in a given centrality class. Also, the geometry of initial state distribution reflects itself as different samples of final particle spectrum results by the hydrodynamic evolution. The particle momentum distribution can be expanded by Fourier series which its coefficients called harmonic flows. We can only study the effects of hydrodynamics on initial fireball by flow... 

Vibration signals have been used for fault diagnosis frequently. These signals are captured using sensors, which are mounted on different locations of the equipment. Using data captured from different locations of the equipment, will result in roubustness of the fault diagnosis model. But sometimes the predictions of sensors mounted on different locations, happen to conflict. These conflicts among sources of information, make it hard to decide about the overal health state of the equipment. In fact, these conflicts causes a kind of uncertainty called epistemic uncertainty. A powerful mathematical framework for managing epistemic uncertainties, is Dempster-Shafer theory of evidence. An... 

Since seepage-related problems account for the cause of more than forty percent of dam failure seepage analysis serves as one of the most significant stage in the design process of an embankment dam. Currently a steady seepage analysis in a typical or maximum cross section of the dam is formed instead of transient seepage analysis for simplicity. In this way, for the change of condition (unsaturated to saturated) in the first filling of dams and it’s effects on behavior and reaction of dams until the steady seepage condition established; the results of steady seepage analysis cannot be satisfactory. In this thesis, based on finite element method and with assumption of saturated-unsaturated... 

Over the past several decades, human activities have resulted in a significant increase in surface and ground water pollution. Human activities have caused significant pollution of surface and groundwater, with pollutants like nitrates, phosphorus, heavy metals, toxins, and chemical fertilizers degrading water quality. In order to control pollution and reduce the concentration of pollutants in water, it is necessary to use appropriate numerical criteria to evaluate and manage the quality of water resources. The water quality index, as a scoring method for investigating the combined effects of independent parameters on overall water quality, is a widely-used metric for measuring the quality... 

It is inevitable to simulate the phenomena that govern nature to make decisions and policies on water and environmental issues. Therefore, researchers have tried to make a good prediction of water's quantitative and qualitative status by using modeling and computer processing power. One of the primary and essential issues in modeling is using sensitivity analysis techniques. Using this knowledge, much information will be obtained on how to influence the model's output regarding various factors such as parameters, input data, and initial and boundary conditions. Global sensitivity analysis based on variance as one of the most well-known and, at the same time, the most widely used sensitivity... 

Water quality is a fundamental pillar of public health, sustainable development, and food security, and monitoring pollutants such as total phosphorus (TP) plays a crucial role in the effective management of surface water resources. Phosphorus is an essential element for agricultural production; however, its loss from soil to aquatic systems can lead to environmental issues such as eutrophication, biodiversity loss, and degradation of water quality. Although monitoring TP concentrations is vital for effective water quality management, many countries face a lack of sufficient and consistent data. Numerical models, particularly data-driven approaches based on machine learning, can help bridge... 

In recent decades, the unprecedented decline of water resources has turned Lake Urmia into one of Iran’s most critical environmental hotspots. The expansion of the lake’s dried bed has intensified the occurrence of salt dust storms, leading to serious consequences for public health, agriculture, the local economy, and ecological sustainability across the region. The main objective of this study was to develop a data-driven model to predict PM₁₀ concentrations over the Lake Urmia watershed using advanced machine learning algorithms. To achieve this, a comprehensive dataset was compiled, including meteorological variables, land cover types, remote sensing indices such as Aerosol Optical Depth...