Sharif Digital Repository

The achievement of our previously proposed space-time coding algorithm entitled full-rate linear-receiver space-time block code (FRLR STBC) has motivated us to propose, in this paper, a new class of high-rate space-time-frequency block codes (STFBCs) over frequency-selective Rayleigh fading channels. We have called these codes FRLR STFBCs with interleaving (FRLR STFBCs-I). FRLR STFBCs-I could achieve a full-diversity property over quasi-static channels. Simulation results also verify that the proposed schemes exhibit proper performances in comparison with the recently proposed STFBCs. The most outstanding characteristic of the newly introduced high-rate codes is the linear complexity of the... 

In this study, the authors show that the coding advantage (CA) of quasi-orthogonal space-frequency block codes (QOSFBCs) could be decomposed into two parts, namely intrinsic CA (ICA) and extrinsic CA (ECA). Then, by using the ICA, the authors demonstrate that the optimum precoder of the QOSFBCs could be analytically derived without any requirement of the exhaustive search. Then, by improving the ECA, the authors enhance performances of the QOSFBCs efficiently - up to 4dB. Finally, the authors show that a very fast optimisation process for the QOSFBCs is viable over any arbitrary frequency-selective channel  

Analysis of gamma-ray spectra is an important step for identification and quantification of radionuclides in a sample. In this paper a new gamma-ray spectra analysis algorithm based on Particle Swarm Optimization (PSO) is developed to identify different isotopes of a mixed gamma-ray source and determine their fractional abundances. PSO is an iterative algorithm that imitates the social behaviors observed in nature to solve complex optimization problems. The PSO method is used for complex fitting to the response of a 3 [Formula presented] 3 inch NaI (Tl) scintillation detector and the fitting process is controlled by a test for significance of abundance and computation of Theil coefficient.... 

A novel approach for analyzing complex gamma-ray spectra using a sequential algorithm is introduced. The developed Sequential Gamma-ray Spectrum Deconvolution (SGSD)algorithm produces a sequence of spectra converging to the best estimation of output spectrum of a gamma-ray detector. In each point of sequence, an isotope of unknown gamma-ray source is identified and the respective response of the detector to unknown source is reconstructed. Effectiveness of the developed algorithm is demonstrated by two empirical and simulation studies. In the case of empirical study, a number of recorded gamma-ray spectra related to a mixed gamma-ray source including different combinations of 5 isotopes... 

A novel neutron Spectrum Deconvolution using Particle Swarm Optimization (SDPSO) code has been developed to unfold the neutron spectrum from a pulse height distribution and a response matrix. The Particle Swarm Optimization (PSO) imitates the bird flocks social behavior to solve complex optimization problems. The results of the SDPSO code have been compared with those of the standard spectra and recently published Two-steps Genetic Algorithm Spectrum Unfolding (TGASU) code. The TGASU code have been previously compared with the other codes such as MAXED, GRAVEL, FERDOR and GAMCD and shown to be more accurate than the previous codes. The results of the SDPSO code have been demonstrated to... 

Online elemental analysis of irradiated tissues is an important challenge in proton therapy for estimating the depth of the Bragg peak and monitoring the healing process. In the present study, the prompt gamma (PG) spectra of the most abundant elements of human tissues were obtained for two different incident protons of 30 MeV and 120 MeV using the Geant4 toolkit. Train phantoms were defined to study the elemental analysis of the tissue from PG spectra. It was found that the intensities of 7.12 and 3.91 MeV PG depend on the mass of 16O and 20Ca elements for both proton energies, respectively. Furthermore, multi-variable linear functions were presented for overlapping peaks like 4.44 and 2.31... 

Modeling of High Purity Germanium (HPGe) detector on a wide energy range is important in gamma-ray spectroscopy. The precisely modeled detector can be used for proton-induced prompt gamma-ray spectroscopy. In this work, we used both the gamma-rays of calibration sources and prompt gamma-rays emitted in proton capture reactions to model a coaxial p-type HPGe detector using Geant4 Monte Carlo simulation for the gamma-ray energy range of 59–10764 keV. The calibration sources were 137Cs, 241Am, 60Co, 152Eu, and 133Ba, while the prompt gamma-rays were due to the gamma-ray cascades following the 27Al(p,γ)28Si reaction capture at the resonant energies of 992, 1317 and 2483 keV, as well as the... 

Motivated by the statistical correspondence between phases of the transmitted and received vectors, we present a fast decoding method for quasi-orthogonal space-time block codes (QOSTBCs) in this paper. The proposed decoder selects proper candidates from precomputed and sorted sets by focusing on the phase of a specific entry of the combined and decoupled vector. The ML metric of the most probable candidates is first evaluated, and then, the remaining candidates are assessed based on the similarity between the phases. The new algorithm can work with any type of constellation such as QAM and PSK and supports generalized block-diagonal QOSTBCs. Theoretical results backed by simulation tests... 

One of the well-known online monitoring techniques used for quality control of bulk samples is Prompt Gamma Neutron Activation Analysis (PGNAA). PGNAA suffers from the so-called matrix effect problems such as density, thickness and moisture content of the sample under study. In this work, an Artificial Neural Network (ANN) model is introduced to deal with these effects. The required spectra for training and testing the proposed ANN model are obtained by Monte Carlo simulation of the gamma-ray spectra recorded in a PGNAA online analyzer system used in cement factories. The gamma-ray spectra related to given set of density, thickness and moisture content are corrected channel-to-channel using... 

Elemental analysis can be performed using obtained gamma-ray spectrum of the sample under study. In this work, simple Multi-Layer Perceptron (MLP) neural network models are proposed for analyzing a gamma-ray emitting sample using whole information of its obtained gamma-ray spectrum. Elemental analysis is performed in two fields of study using 3 × 3 inch NaI(Tl) detectors: Radio-Isotope Identification (RIID) and Prompt Gamma Neutron Activation Analysis (PGNAA). The gamma-ray point sources are used for an empirical study in RIID field, while a Monte Carlo simulation study is considered for determining chlorine and water content of crude oil using combination of PGNAA technique and a MLP model.... 

A new neutron spectrum unfolding code TGASU (Two-steps Genetic Algorithm Spectrum Unfolding) has been developed to unfold the neutron spectrum from a pulse height distribution which was calculated using the MCNPX-ESUT computational Monte Carlo code. To perform the unfolding process, the response matrices were generated using the MCNPX-ESUT computational code. Both one step (common GA) and two steps GAs have been implemented to unfold the neutron spectra. According to the obtained results, the new two steps GA code results has shown closer match in all energy regions and particularly in the high energy regions. The results of the TGASU code have been compared with those of the standard... 

In this paper, by applying a new permutation to the full-diversity block circular delay diversity (BCDD) space-frequency codes (SFCs), we show that their performance could be enhanced. Furthermore, we propose a new method for performing the permutation in the absence of partial channel state information at the transmitter. This new permutation, which is done based on artificial delay and power profiles (ADPPs), could improve the performance of the BCDD SFCs more than 3 dB as simulation results demonstrate  

Four 5-, 10-, 20- and 30-story moment frames, representing low-, mid-, and two high-rise structures, were subjected to a great number of idealized directivity pulses. The amplitudes and periods of pulses vary from 0.02 g to 1.0 g and 0.5 to 12 sec, respectively. Over 1400 nonlinear dynamic analyses of low- to high-rise moment frames were performed which were feasible through using modified fish-bone model. The distribution of interstory drift along the height was studied and two applied contours were proposed: (i) the maximum interstory drift contour, and (ii) the critical story contour. These contours were demonstrated versus the ratio of natural period of the structure to the pulse period... 

In this article singular points of a parallel manipulator are obtained based on a novel geometrical method. Here we introduce the constrained plain method (CPM) and some of its application in parallel mechanism. Given the definition of constraint plane (CP) and infinite constraint plane (ICP) the dependency conditions of constraints is achieved with the use of a new theorem based on the Ceva geometrical theorem. The direction of angular velocity of a body is achieved by having three ICPs with the use of another theorem. Finally, with the use of the above two novel theorems singularities of the 3UPF_PU mechanism are obtained. It should be emphasized that this method is completely geometrical,... 

An analytical model is proposed to study the effect of particle size on melting enthalpy and entropy of metallic nanoparticles (NPs). The Mott's and Regel's equations for melting entropy in the combination of core average coordination number (CAC) and surface average coordination number (SAC) of freestanding NPs are considered. Clusters of icosahedral (IC), body centered cubic (BCC), and body centered tetragonal (BCT) structure without any vacancies and defects are modeled. Using the variable coordination number made this model to be in good agreement with experimental and molecular dynamic (MD) results of different crystal structures. The model predicts melting entropy and enthalpy of... 

Grinding is widely used for manufacturing of components that require fine surface finish and good dimensional accuracy. In this study a thermo-mechanical finite element analysis is conducted to find out how grinding parameters can affect temperature and residual stress distribution in the workpiece. Results of parametric study presented in this work indicate, by carefully selecting the grinding parameters, minimum thermal and mechanical damage can be achieved. Higher workpiece velocities produce higher surface residual stress. By increasing depths of cut, depth of tensile residual stresses increases. Convection heat coefficient does not have any considerable effect on surface residual stress... 

Adaptive Noise Cancellation (ANC) is a well-known technique for background noise reduction in automobile and vehicular environments. The noise fields in automobile and other vehicle interior obey the diffuse noise field model closely. On the other hand, the ANC does not provide sufficient noise reduction in the diffuse noise fields. In this paper, a new multistage post-filter is designed for ANC as a solution to diffuse noise conditions. The designed post-filter is a single channel Linear Prediction (LP) based speech enhancement system. The LP is performed by an adaptive lattice filter and attempts to extract speech components by using intermediate ANC signals. The post-filter has no... 

Self-Compacting Concrete (SCC) is a unique type of concrete that can flow and fill spaces without the need for vibrating compaction, resulting in a dense and uniform material. This article focuses on estimating the compressive strength of SCC utilizing Artificial Neural Networks. Specifically, the study employs multilayer perceptrons with back-propagation learning algorithms, which are commonly used in various problem-solving scenarios. The study covers essential components such as structure, algorithm, data preprocessing, over-fitting prevention, and sensitivity analysis in MLPs. The input variables considered in the research include water, fine aggregate, super-plasticizer, fly ash, coarse... 

Seismic retrofits can significantly reduce the vulnerability of masonry buildings. Multiple seismic retrofit alternatives are often available for a given building. Estimating the cost of each candidate action is essential to selecting and implementing the appropriate seismic retrofit initiatives. This research harnesses the capabilities of various regression models for cost estimation. A dataset from 167 retrofit projects for masonry school buildings was used to develop models. Three main retrofit actions were taken into consideration: shotcrete, steel belt and fiber-reinforced polymer. Various regression methods, including multiple linear regression, ridge regression, lasso regression, and...