Sharif Digital Repository

Exact recovery of a sparse solution for an underdetermined system of linear equations implies full search among all possible subsets of the dictionary, which is computationally intractable, while ℓ1 minimization will do the job when a Restricted Isometry Property holds for the dictionary. Yet, practical sparse recovery algorithms may fail to recover the vector of coefficients even when the dictionary deviates from the RIP only slightly. To enjoy ℓ1 minimization guarantees in a wider sense, a method based on a combination of full-search and ℓ1 minimization is presented. The idea is based on partitioning the dictionary into atoms which are in some sense... 

Linear sampling of sparse vectors via sensing matrices has been a much investigated problem in the past decade. The nonlinear sampling methods, such as quadratic forms are also studied marginally to include undesired effects in data acquisition devices (e.g., Taylor series expansion up to two terms). In this paper, we introduce customized nonlinear sampling techniques that provide possibility of sparse signal recovery. The main advantage of the nonlinear method over the conventional linear schemes is the reduction in the number of required samples to 2k for recovery of k-sparse signals. We also introduce a low-complexity reconstruction method similar to the annihilating filter in the... 

QBism is one of the main candidates for an epistemic interpretation of quantum mechanics. According to QBism, the quantum state or the wavefunction represents the subjective degrees of belief of the agent assigning the state. But, although the quantum state is not part of the furniture of the world, quantum mechanics grasps the real via the Born rule which is a consistency condition for the probability assignments of the agent. In this paper, we evaluate the plausibility of recent criticism of QBism. We focus on the consequences of the subjective character of the quantum state, the issue of realism and the problem of the evolution of the quantum state in QBism. In particular, drawing upon... 

To investigate the biomarker detection capability of the 2D MoSe2 monolayer as the lung cancer detection sensor, the interaction between the biomarker molecules and the surface of the sensor has been studied by first-principles calculations in three scenarios namely i) pristine MoSe2, ii) Nb-doped MoSe2, iii) Nb-decorated MoSe2 monolayers. In this study, it is proposed that Nb-decorated MoSe2 is a promising biosensor for detecting the two most prominent lung cancer biomarkers in the breath namely 2-butanone (C4H8O) and 1-propanol (C3H8O). The adsorption energy, charge transfer, and the equivalent sensitivity for C3H8O adsorption on Nb-decorated MoSe2 were calculated as −1.907 eV, 0.026e, and... 

An analysis is presented of the effective electromagnetic parameters of high-permittivity, anisotropic artificial dielectrics which are built by stacking arrays of metallic elements and conventional dielectric films, with adjacent arrays shifted with respect to each other. The effective parameters of the artificial dielectric are extracted from the scattering coefficients of plane electromagnetic waves which are normally or obliquely incident on a slab of the artificial material with finite thickness. These coefficients are derived from the generalised scattering matrix of a single layer of metallic elements which is computed using the integral equation technique. Both two-dimensional and... 

Semiconductor gas sensors have been developed so far on empirical bases, but now recent innovative materials for advancing gas sensor technology have been made available for further developments. Two-dimensional (2D) materials have gained immense attention since the advent of graphene. This attention inspired researchers to explore a new family of potential 2D materials. The superior structural, mechanical, optical and electrical properties of 2D materials made them attractive for next-generation smart device applications. There are considerable improvements and research studies on graphene, molybdenum disulfide (MoS2), tungsten disulfide (WS2), tin sulfide (SnS2), black phosphorus and other... 

In order to plan precise treatment or accurate tumor removal surgery, brain tumor segmentation is critical for detecting all parts of tumor and its surrounding tissues. To visualize brain anatomy and detect its abnormalities, we use multi-modal Magnetic Resonance Imaging (MRI) as input. This paper introduces an efficient and automated algorithm based on the 3D bit-plane neighborhood concept for Brain Tumor segmentation using a rule-based learning algorithm. In the proposed approach, in addition to using intensity values in each slice, we consider sets of three consecutive slices to extract information from 3D neighborhood. We construct a Rule base using sequential covering algorithm. Through... 

In order to plan precise treatment or accurate tumor removal surgery, brain tumor segmentation is critical for detecting all parts of tumor and its surrounding tissues. To visualize brain anatomy and detect its abnormalities, we use multi-modal Magnetic Resonance Imaging (MRI) as input. This paper introduces an efficient and automated algorithm based on the 3D bit-plane neighborhood concept for Brain Tumor segmentation using a rule-based learning algorithm. In the proposed approach, in addition to using intensity values in each slice, we consider sets of three consecutive slices to extract information from 3D neighborhood. We construct a Rule base using sequential covering algorithm. Through... 

Glioma is one of the most frequent primary brain tumors in adults that arise from glial cells. Automatic and accurate segmentation of glioma is critical for detecting all parts of tumor and its surrounding tissues in cancer detection and surgical planning. In this paper, we present a reliable classification framework for detection and segmentation of abnormal tissues including brain glioma tumor portions such as edemas and tumor core. This framework learns weighted features extracted from the 3D cubic neighborhoods regarding to gray-level differences that indicate the spatial relationships among voxels. In addition to intensity values in each slice, we consider sets of three consecutive... 

Space environments have a significant influence on advanced composite structures and adhesive joints. Degradation in the mechanical properties of aerospace materials changes the dynamic behavior of the structures and adhesive joints. In this paper, a typical tubular adhesive joint with material degradation due to geostationary orbit (GEO) thermal cycles has been studied numerically with Python scripts. Adhesive joint geometry and boundary conditions are the main parametric study parameters. The results show that the first non–zero natural frequencies of the clamped-free tubular adhesive joint decreased due to mechanical property degradation. A dynamic behavior comparison of the degradation... 

Glioma is a common type of tumor that develops in the brain. Due to many differences in the shape and appearance, accurate segmentation of glioma for identifying all parts of the tumor and its surrounding tissues in cancer detection is a challenging task in cancer detection. In recent researches, the combination of atlas-based segmentation and machine learning methods have presented superior performance over other automatic brain MRI segmentation algorithms. To overcome the side effects of limited existing information on atlas-based segmentation, and the long training and the time consuming phase of learning methods, we proposed a semi-supervised learning framework by introducing a... 

This paper presents a novel Cyber-Physical System (CPS) equipped with an advanced Distributed Model Predictive Control (DMPC) method with reduced order computational complexity, zero steady-state error, reduced start-up energy consumption and improved transient response for the optimal heating-cooling of buildings. The satisfactory application of this method for the optimal heating-cooling of a large-scale (6-story) building with 40 rooms is illustrated. Smart Industrial Internet of Things (IIoT) -based thermostats, a gateway and a general Quadratic Programming (QP) solver are developed. Using this hardware set-up, the simulation results for the 6-story building are verified in a small scale... 

Purpose. Drug release from nanosystems at the sites of either absorption or effect biophase is a major determinant of its biological action. Thus, in vitro drug release is of paramount importance in gaining insight for the systems performance in vivo. Methods. A novel in vitro in vivo correlation, IVIVC, model denoted as double reciprocal area method was presented and applied to 19 drugs from 55 nano formulations with total 336 data, gathered from literature. Results. The proposed model correlated the in vitro with in vivo parameters with overall error of 12.4 ± 3.9%. Also the trained version of the model predicted the test formulations with overall error of 15.8 ± 3.7% indicating the... 

High-quality guided wave devices are key components in integrated millimeter-wave circuits. In this paper, we propose mm-wave planar dielectric waveguides based on thin, anisotropic artificial dielectric layers with very high in-plane permittivity. Waves propagating on such films are surface waves whose field exponentially decays outside the film in the vertical direction, similar to waveguides commonly used in integrated optics. The very high in-plane permittivity of the artificial dielectric layers leads to strong field confinement, and allows the implementation of relatively thin waveguides. This fact, together with the planar structure of these devices, make them highly suitable for...