Sharif Digital Repository

Background: Small scale robotics have attracted growing attention for the prospect of targeting and accessing cell-sized sites, necessary for high precision biomedical applications and drug/gene delivery. The loss of controlled gene therapy, inducing systemic side effects and reduced therapeutic efficiency, can be settled utilizing these intelligent carriers. Methods: Newly proposed solutions for the main challenges of control, power supplying, gene release and final carrier extraction/degradation have shifted these smart miniature robots to the point of being employed for practical applications of transferring oligonucleotides (pDNA, siRNA, mRNA, etc.) in near future. Conclusion: In this... 

We consider magnetic actuation and control of a spherical neutrally buoyant magnetic microrobot via magnetic coil setups and seek to design an optimal controller to reduce the required energy and coils’ currents. We showed that in currently employed setups, where the actuation frequency is few tens of Hertz, the nonlinear dynamics of the system can be well approximated by a set of linear constrained ones. The approximated model is obtained by consciously overlooking the rotational dynamics and the inertia terms in translational dynamics. We acquired the linear quadratic regulation (LQR) controller for the approximated model which is a constrained time-varying system. Finally, 3D manipulation... 

A number of HZSM-5 catalysts modified with 5 wt% Mg, Na, Zr, and Al as well as others modified with 5-60 wt% Zn prepared by wet impregnation. These materials were characterized by the NH3-TPD, XRF, and XRD analyses and tested in a slurry reactor to determine their activities in dehydration of methanol solution in kerosene. Reactions were carried out at 230°C and 19 bar for 4 h of residence time in the reactor. Results showed that in the first series, the catalyst modified with Zr and in the second series, the one modified with 10 wt% Zn led to the highest methanol conversion. It was deduced that elimination of strong acid sites and partial replacement of active cations in the HZSM-5 zeolite... 

In this paper we analyses the energy consumption of well known family of asynchronous circuits and present a new methodology for energy estimation of these circuits at intermediate-level of abstraction. Energy estimation is performed by simulating the intermediate format of the design. The number of Read and Write accesses on the ports of the concurrent processes are counted by analyzing the conditional and computational portion during the simulation which is the base of our estimation methodology. Our proposed power estimation scheme is faster than usual post-synthesis power estimation by an order of 9, while the estimated power resides in a boundary of 11% total imprecision. © 2007 IEEE  

NoC is an efficient on-chip communication architecture for SoC architectures. It enables integration of a large number of computational and storage blocks on a single chip. NoCs have tackled the SoCs disadvantages and are scalable. In this paper, we compare two popular NoC topologies, i.e., mesh and torus, in terms of different figures of merit e.g., latency, power consumption, and power/throughput ratio under different routing algorithms and two common traffic models, uniform and hotspot. To the best of our knowledge, this is the first effort in comparing mesh and torus topologies under different routing algorithms and traffic models with respect to their performance and power consumption.... 

In this paper, we will investigate the efficacy of IMAT (Iterative Method of Adaptive Thresholding) in recovering the sparse signal (parameters) for linear models with random missing data. Sparse recovery rises in compressed sensing and machine learning problems and has various applications necessitating viable reconstruction methods specifically when we work with big data. This paper will mainly focus on comparing the power of Iterative Method of Adaptive Thresholding (IMAT) in reconstruction of the desired sparse signal with that of LASSO. Additionally, we will assume the model has random missing information. Missing data has been recently of interest in big data and machine learning... 

In this paper, we introduce a novel and robust approach to quantized matrix completion. First, we propose a rank minimization problem with constraints induced by quantization bounds. Next, we form an unconstrained optimization problem by regularizing the rank function with Huber loss. Huber loss is leveraged to control the violation from quantization bounds due to two properties: first, it is differentiable; and second, it is less sensitive to outliers than the quadratic loss. A smooth rank approximation is utilized to endorse lower rank on the genuine data matrix. Thus, an unconstrained optimization problem with differentiable objective function is obtained allowing us to advantage from... 

The ultra-supercritical once-through boiler (OTB) unit is an advanced power generation technology with high plant efficiency and low emissions. However, it is difficult to realize a coordinate control for the ultra-supercritical OTB unit to achieve the fast and stable dynamic response during the load tracking and grid frequency disturbances and in the presence of unavoidable uncertainties. In this paper, an accurate grey box multivariable coupled nonlinear model of an ultra-supercritical boiler-turbine unit is considered. Steam pressure at throttle valve, specific enthalpy in separator and active power are adjusted at desired values by manipulation of the fuel rate command, feedwater rate...