Sharif Digital Repository

This research presents a probabilistic framework for risk analysis under the dual hazards of flood and earthquake using reliability methods. In this research the term “risk” refers to the exceedance probability of the maximum loss resulting from the flood and earthquake hazards over a given time period. This methodology is implemented for the multi-hazard risk analysis of the buildings of a virtual city. The Monte Carlo sampling method is used to propagate uncertainties and compute the probability distribution of the maximum loss under each hazard. Subsequently, the load combination theory is applied to integrate the loss exceedance probabilities under the flood and earthquake hazards.... 

Vertical turbulent mixing in lakes plays a critical role in the distribution and transfer of nutrients, oxygen, and heat, significantly impacting lake productivity and the growth of algae and aquatic plants. During summer, the persistent and intense solar radiation creates a thermal stratification in lakes, which inhibits deep vertical mixing. In stratified lakes and oceans, small-scale mixing processes are key drivers of vertical fluxes that transport particles and substances, including nutrients, pollutants, and microorganisms. Despite the significant influence of small-scale turbulent mixing, numerical models of stratified lakes often neglect these effects due to the challenges associated... 

The purpose of this research is to investigate the capability of process-oriented modeling and deep learning for monitoring and forecasting the water quality of stratified lakes and to provide a unified framework integrating these two models to improve the monitoring and prediction of water quality. In this thesis, the process-oriented General Ocean Turbulence Model (GOTM) has been developed to simulate the hydrodynamic and thermodynamic processes of Gull Lake from 2008 to 2017. Subsequently, the MLP deep learning model has been employed to study the lake's key water quality indicators during this period. Meteorological data serves as input for the GOTM. Calibration and validation of the... 

Due to anthropogenic activities and climate change, Lake Urmia, one of the largest hypersaline lakes, is exposed to desiccating. The increase in salinity in this lake up to more than 400 p.s.u has endangered the ecology of this lake. In this study, a three-dimensional, unstructured grid and finite volume model FVCOM has been developed to investigate Lake Urmia's hydrodynamics, salinity, and water temperature over the year 2016. Some of the model inputs were lake bathymetry, meteorological data (including air temperature and pressure, wind speed and direction, short-wave and longwave radiation), precipitation, evaporation, river flux, salinity, and temperature. The model was calibrated... 

Wetlands are valuable ecosystems that have a wide variety of functions to protect biodiversity, natural, economic and social values. Hydrological changes and nutrient enrichment, resulting from population growth, economic development and climate change are threatening the wetlands. Recently, assessing spatial and temporal variations of water quality has become an important aspect of the physical and chemical characterization of aquatic environments. Anzali wetland is one of the international wetlands in Iran, located in the southern part of the Caspian Sea in Gilan province. This wetland has been exposed to many pollution sources including agricultural, industrial, and municipal wastewater... 

Water resources globally are facing significant stress due to overexploitation. In recent decades, the balance between the available water resources and the amount of water consumption in the catchment area of Lake Urmia due to human factors and natural phenomena like climate change has been severely disrupted. In the last 20 years, the cumulative impact of these factors has led to a dramatic reduction in Lake Urmia’s water level by over 8 meters, with a concomitant rise in water salinity. To address the hydrodynamic challenges of Lake Urmia, it is crucial to understand the upstream watersheds. Thirteen perennial rivers, primarily the Zarinehroud and Simineroud, fulfill the water rights... 

Considering the significant impact of salinity and temperature on the life of aquatic ecosystems, the growth of plants and animals, and the health of people; it is necessary to predict the spatiotemporal distribution of these qualitative characteristics in aquatic environments by using precise algorithms through hydrodynamic models. This research presents an improved algorithm for calculating qualitative characteristics of aquatic environments, such as salinity, during the wet/drying processes. The developed algorithm in this study has been incorporated into FVCOM which is a three-dimensional hydrodynamic model. The current algorithm governing the FVCOM model is not capable of accurately... 

Entanglement spectrum is the set of eigenvalues of reduced density matrix for a definite state. It contains more information than the entanglement entropy. This spectrum can show entanglement measure, quantum phase transition and topological order in a system. In recent years, the entanglement spectrum for several models has been studied. The entanglement spectrum shows a correspondence to the energy spectrum within some specific regions, which are related to the edge state of the system; It has been verified for the Heisenberg ladder [1] and fractional quantum Hall effect [3]. Moreover, the topological order can be seen in the entanglement spectrum. There exists an acceptable adaption... 

Gesture and motion evaluation are needed for a variety of applications. The use of human hand motions as a natural interface tool has motivated researchers to conduct research in the modeling, analysis and evaluation of various hand movements. In particular, human-computer intelligent interaction has been a focus of research in vision-based gesture recognition. In this work, we introduce a 3-D hand model evaluation method that offers flexible and elaborate representation of hand motion. We used landmarked points on tips and joints of the fingers and calculated the 3-D coordinates of these points through a stereo vision system followed by an HMM (Hidden Markov Model) to recognize hand... 

International Data Company (IDC) has reported, at the end of 2020, the total amount of digital data stored in the entire world will reach 40 thousand Exabytes. The idea of accessing this volume of data, anywhere at any time by exploiting commodity hardware, led into the introduction of cloud storage. The abounded rate and variety of failures in the equipment used in cloud storage systems, placed fault tolerance, at top of the challenges in these systems. HDFS layer in Hadoop has provided cloud with reliable storage. Replication is the conventional method to protect data against failures in HDFS. But the storage overhead is a big deal and therefore designers are tending towards erasure codes.... 

Internet of Things (IoT) is a communicative infrastructure, which establishes IP-based connections between many smart devices with limited energy supplies. The gathering of such an enormous number of connected devices would impose many challenges, with routing the most important issue. Standardization of the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) was a major step towards fulfilling the IoT routing requirements. The key element in determining the routing policies and creation of the topology in RPL is the objective function. According to our studies, more than 97% of the consumed energy of a node in wireless networks is due to transceiver activities. On the other hand,... 

The objective of this research is to enhance the accuracy of temperature and pressure variables derived from global meteorological models such as ERA5 using machine learning and deep learning (ML-DL) techniques. Since variables like temperature and pressure are critical metrics for various processes and decision-making in fields such as agriculture and limnology, and they serve as input variables in most hydrological, hydrodynamic, and meteorological models, accessing high-precision time series with appropriate temporal resolution is of great importance. Currently, global meteorological models like ERA5 provide relatively long time series of these variables on a grid with spatial resolutions...