Sharif Digital Repository

With the advent of new positioning services, one can reach more satellites these days to find his position. Using a combination of satellites which belong to different constellations needs some considerations like addressing biases between their time references. Each constellation has progressed to the point that they have enough satellites to provide accurate position separately. According to this fact, we propose to find the position in each constellation and fusion their results in a way that final position has the minimum possible variance instead of combining the constellations in a satellite level and dealing with inter system biases. Experimental studies are conducted based on IGS... 

Least squares estimation is a widely-used technique for range-based source localization, which obtains the most probable position of mobile station. These methods cannot provide desirable accuracy in the case with a non line of sight (NLOS) path between mobile station and base stations. To circumvent this drawback, many algorithms have been proposed to identify and mitigate this error; however, they have a large run-time overhead. On the other hand, new positioning systems utilize a large set of base stations, and a practical algorithm should be fast enough to deal with them. In this paper, we propose a novel algorithm based on subspace method to identify and eliminate the NLOS error.... 

Controlling nonlinear systems have always been a challenging problem. Complexity is mostly the result of nonlinear systems behavior dependence on initial conditions and input. Linearization techniques are such kinds of nonlinear systems analysis tools, which can give suitable results in neighborhood of equilibrium points. In addition, phase portraits are very efficient for visualizing the behavior of system in equilibrium points' neighborhood. In this paper, designing a controller for a low order dynamic system with multiple equilibrium points in presence of a sinusoidal disturbance with unknown amplitude and unknown bounded frequency is investigated. The proposed controller is based on a... 

Active learning method (ALM) is a powerful fuzzy-based soft computing methodology suitable for various applications such as function modeling, control systems, clustering and classification. Despite considerable advantages, the main computational engine of ALM, ink drop spread (IDS), is memory-intensive, which imposes significant area overheads in the hardware realization of the ALM for real-time applications. In this paper, we propose a compressed model for ALM which greatly alleviates the storage limitations. The proposed approach employs a distinct inference algorithm, enabling a significant reduction in memory utilization from O(N2) to O(2N) for a multi-input single-output (MISO) system.... 

The current coronavirus disease 2019 (COVID-19) outbreak spread rapidly worldwide. Yet, there is no identifiable antiviral treatment, so an effective drug is urgently needed. Preventive strategies and oxygen therapy are the main practical approaches to prevent and treat COVID-19. Clinical trials are in progress for the antiviral and immunomodulation agents that eventually are being developed for COVID-19 treatment. Pharmacological, immunotherapies, natural-based supplements, biologics, and combination therapies interventions have been established. The concept of drug repurposing was re-visited, and many conventional antivirals or immunosuppresses were evaluated for Efficacy against COVID-19...