Sharif Digital Repository

Water-quality modeling and prediction is a complicated task because of inherent randomness and uncertainties associated with various processes and variables throughout the stream environment and the lack of appropriate data. Hence, the results of mathematical models are always approximate, lying within an uncertainty. This paper describes and demonstrates the application of the U.S. Environmental Protection Agency's water-quality model, QUAL2E-UNCAS, to the Zayandeh-Rood River in Iran. First-order reliability analysis is used to examine the variability of predicted water-quality parameters of total dissolved solids, dissolved oxygen, and biochemical oxygen demand. This analysis also... 

Asphaltene deposition is a problematic challenge for oil production. Changes in key parameters like pressure and fluid composition during natural depletion and different gas injection scenarios may result in asphaltene precipitation and deposition. In this work, a model is developed by application of mass balance equations, momentum equation, asphaltene deposition and permeability reduction models. An algorithm is developed to perform iterative procedure to solve the numerical equations that contains highly coupled variables. Indeed, an equation is introduced to calculate the saturation of the precipitated asphaltene phase. Model parameters were determined by genetic algorithm which is a... 

Commute mode choice and number of non-work stops during the commute are joint decisions interacting with each other. If an individual chooses a vehicle for the commute, regarding vehicle's restrictions, there could be some stops. On the other hand, if an individual needs to have some stops, a vehicle can be selected for the commute regarding the number of stops. In this study, to consider the interaction between these decisions, we employed a copula-based joint modeling framework. The data used in this study are drawn from origin-destination travels data of Shiraz-Iran conducted in 1997. The commuting mode choice modeling is undertaken using a multinomial logit model, and the number of... 

Due to flexibility of thin plates, high-amplitude vibrations are observed when they are subjected to severe dynamic loads. Because of the extensive application of circular plates in industry, attenuating the undesired vibrations is of foremost importance. In this paper, Adaptable Vibration Suppressors (AVSs) as a semi-active control approach were utilized to suppress the vibrations in a free circular plate under the concentrative harmonic excitation. Using mode summation method, the mathematical model of the hybrid system including the plate and an arbitrary number of vibration suppressors was analyzed. By developing a complex multiple-loop algorithm, optimum values for the parameters of... 

Due to flexibility of thin plates, high-amplitude vibrations are observed when they are subjected to severe dynamic loads. Because of the extensive application of circular plates in industry, attenuating the undesired vibrations is of foremost importance. In this paper, Adaptable Vibration Suppressors (AVSs) as a semi-active control approach were utilized to suppress the vibrations in a free circular plate under the concentrative harmonic excitation. Using mode summation method, the mathematical model of the hybrid system including the plate and an arbitrary number of vibration suppressors was analyzed. By developing a complex multiple-loop algorithm, optimum values for the parameters of... 

In this paper, a computational counterpart of the experimental investigation is presented based on a nonlocal computational homogenization technique for extracting damage model parameters in quasi-brittle materials with softening behavior. The technique is illustrated by introducing the macroscopic nonlocal strain to eliminate the mesh sensitivity in the macroscale level as well as the size dependence of the representative volume element (RVE) in the first-order continuous homogenization. The macroscopic nonlocal strains are computed at each direction, and both the local and nonlocal strains are transferred to the microscale level. Two RVEs with similar geometries and material properties are... 

An extension to the classical mass-spring model for more realistic simulation of soft tissues for surgery simulation was proposed. The conventional equations of mass-spring model were generalized for non-linear springs, and model parameters were tuned using experimental data. Results show that the proposed model is fast and interactive, and also demonstrate the typical nonlinear and visco-elastic behaviors of soft tissues well. © 2008 The authors. All rights reserved  

The flight of unmanned aerial vehicles is often associated with model uncertainties, measurement noises, and environmental disturbances such as wind gust. To mitigate these challenges, the accurate estimation of states is vital. Moreover, the wind model and its parameters should also be estimated and compensated during the flight. In this paper, a multiple model filter is implemented for this purpose. To investigate the performance of the multiple model filter, three different models including constant wind, '1-cosine' model and wind shear model are considered. The multiple model filter utilizes three extended Kalman filter to simultaneously estimate the model of wind, the parameters of the... 

A statistical algorithm is introduced to improve the false inference of active loci, in the population in which members are admixture. The algorithm uses an advanced clustering algorithm based on a Bayesian approach. The proposed algorithm simultaneously infers the hidden structure of the population. In this regard, the Monte Carlo Markov Chain (MCMC) algorithm has been used to evaluate the posterior probability distribution of the model parameters. The proposed algorithm is implemented in a bundle, and then its performance is widely evaluated in a number of artificial databases. The accuracy of the clustering algorithm is compared with the STRUCTURE method based on certain criterion. © 2019... 

Bacterial populations are promising candidates for the development of the receiver and transmitter nanomachines for molecular communication (MC). A bacterial receiver is required to uptake the information molecules and produce the detectable molecules following a regulation mechanism. We have constructed a novel bacterial MC receiver using an inducible bacterial L-rhamnose-regulating operon. The proposed bacterial receiver produces green fluorescent protein (GFP) in response to the L-rhamnose information molecules following a quite fast regulation mechanism. To fabricate the receiver, the bacterial population has been transformed using a plasmid harboring L-rhamnose operon genes and gene... 

Nowadays, Autonomous Underwater Vehicles (AUV) are used in environmental studies, ocean floor mapping, and measuring water properties. Navigation of these vehicles is one of the most challenging issues due to the unavailability of global positioning system (GPS) signal underwater. Inertial navigation is a method commonly used for underwater navigation. If a low-cost Inertial Measurement Unit (IMU) is used, navigation quality will decline rapidly due to sensor inherent error. Although using a Doppler Velocity Log (DVL) speedometer sensor helps limit this error to some extent, it does not yield acceptable accuracy in low-cost IMUs. Filtering the gyro based on the AUV rotational dynamics model... 

Short-term interaction between heart rate (HR) and physiological measures like blood pressure and respiration reveals relevant information about autonomic nervous system (ANS) function. Complex mathematical models for describing their couplings have been proposed in the literature. However, an accurate estimation of their parameters in an inverse modeling problem is crucial to extract reliable ANS related indices. This study considers a physiologically-based model of the cardiovascular-respiratory system and ANS control that presents the neural and mechanical effects of respiration separately. The estimation method is evaluated on synthetic signals. An accurate estimation of the... 

Convolution Neural Networks (CNNs), despite being one of the most successful image classification methods, are not robust to most geometric transformations (rotation, isotropic scaling) because of their structural constraints. Recently, scale steerable filters have been proposed to allow scale invariance in CNNs. Although these filters enhance the network performance in scaled image classification tasks, they cannot maintain the scale information across the network. In this paper, this problem is addressed. First, a CNN is built with the usage of scale steerable filters. Then, a scale equivariat network is acquired by adding a feature map to each layer so that the scale-related features are... 

In this paper, a model-based dynamics equation for the needle movement through the soft tissue is developed. A model-based control scheme which uses the force estimation calculated through the simulated tissue deformation data and the dynamic finite element as the tissue model is proposed. To compare the performance of the proposed controller, a PD controller is also used for the proposed needle dynamics equation. It is shown that even with uncertainty in model parameters; the mode-based controller outperforms the PD controller. Furthermore, although increasing the controller gain improves the performance of PD, but the model-based controller's performance is still superior  

In this study, the traffic parameters were collected from three work zones in Iran in order to evaluate the queue length in the work zones. The work zones were observed at peak and non-peak hours. The results showed that abrupt changes in Freeway Free Speed (FFS) and arrival flow rate caused shockwaves and created a bot-tleneck in that section of the freeway. In addition, accel-eration reduction, abrupt change in the shockwave speed, abrupt change in the arrival flow rate and increase in the percentage of heavy vehicles have led to extreme queue lengths and delay. It has been found that using daily traffic data for scheduling the maintenance and rehabilita-tion projects could diminish the... 

The aim of this study is to develop a new fuzzy optimization model to find the optimal factor weights of modified DRASTIC index for groundwater vulnerability mapping an urban aquifer to nitrate contamination. Eight factors including water table depth, recharge, aquifer media, soil media, topography, impact of vadose zone, hydraulic conductivity, and land use are considered and rated. A fuzzy linear regression is formulated between the values of eight factors and corresponding nitrate concentration in groundwater. An optimization model based on real code genetic algorithm with objective of minimizing the sum of the fuzzy spread of the regression coefficients is implemented. Aquifer of Mashhad... 

A new composite adaptive control strategy is developed for both of the reduction of cancer tumor volume and the online identification of tumor parameters during the drug delivery process in chemotherapy. This control strategy is developed for three different nonlinear mathematical cell-kill models of the cancer tumor including the log-kill hypothesis, Norton-Simon hypothesis and Emax hypothesis. All of these models are considered to have fully parametric uncertainties. The stability, tracking convergence and parameters identification convergence during the chemotherapy process are proved using the Lyapunov method. For the first time, the parameters identification of the uncertain... 

This paper numerically studies the interaction of a flowing granular material with an entrainable granular bed, while materials are mixed at the interface of two materials. The rheological behavior of this granular mixture is characterized by a generalized viscoplastic model that includes local volume fraction of materials as well as their physical properties, i.e. size, density, and friction angle. Additionally, the effect of the dynamics of entrained bed-type particles on the rheology of the granular mixture is considered. The governing equations of the flow are discretized using the Incompressible Smoothed Particle Hydrodynamics (SPH) method in which mixing of particles can be... 

In this communication, a hybrid model based on Least Square Support Vector Machine (LSSVM) was constructed to predict CO2 corrosion rate. The input parameters of the model are temperature, CO2 partial pressure, flow velocity and pH. The data used for training and testing of the developed model are 612 and 109 data, respectively. In order to benefit LSSVM from Kernel learning, we compared three kernel functions to select the most efficient one. Furthermore, Coupled Simulated Annealing (CSA) optimization technique was adapted to choose the best optimal values of the model parameters. The results elucidate that Gaussian Kernel functions is the desired function which can afford high accuracy for... 

Despite advancements in developing physics-based formulations to estimate the sheet-flow travel time (tSHF), the quantification of the relative impacts of influential parameters on tSHF has not previously been considered. In this study, a brief review of the physics-based formulations to estimate tSHF including kinematic wave (K-W) theory in combination with Manning's roughness (K-M) and with Darcy-Weisbach friction formula (K-D) over single and multiple planes is provided. Then, the relative significance of input parameters to the developed approaches is quantified by a density-based global sensitivity analysis (GSA). The performance of K-M considering zero-upstream and uniform flow depth...