Sharif Digital Repository

In this paper, a new method for spatial concealment of missing areas in image and video signals transmitted over error prone infrastructures, is presented. The concealment process is performed in three steps. First, a novel technique is used to estimate the significant edges of missing areas after performing a directional edge analysis on the correctly received neighboring blocks of the missing areas. This technique uses the moments of the neighboring edge magnitudes to obtain an adaptive threshold for rejecting non-significant directions. Second, based on the predicted significant directions, an approximation is obtained for each missing pixel. Finally, for each pixel, we compute a weighted... 

In this paper, we introduce a novel method for human activity recognition that benefits from the structure and sequential properties of the test data as well as the training data. In the training phase, we obtain a fraction of data labels at constant time intervals and use them in a semi-supervised graph-based method for recognizing the user's activities. We use label propagation on a k-nearest neighbor graph to calculate the probability of association of the unlabeled data to each class in this phase. Then we use these probabilities to train an HMM in a way that each of its hidden states corresponds to one class of activity. These probabilities are used to learn the transition probabilities... 

We have developed a Gaussian Process Regression method with adaptive kernels for concealment of the missing macro-blocks of block-based video compression schemes in a packet video system. Despite promising results, the proposed algorithm introduces a solid framework for further improvements. In this paper, the problem of estimating lost macro-blocks will be solved by estimating the proper covariance function of the Gaussian process defined over a region around the missing macro-blocks (i.e. its kernel function). In order to preserve block edges, the kernel is constructed adaptively by using the local edge related information. Moreover, we can achieve more improvements by local estimation of... 

Discriminative approaches to human pose estimation have became popular in recent years. These approaches face a big challenge: Similar inputs might correspond to very dissimilar poses. This property misleads the mapping functions which rely on the Euclidean distances in the input space. In this paper, we use the distances between the labels of the training data to learn a metric and map the input data to a space where this problem is minimized. Our mapping is linear and hence preserves the manifold structure of the input data. We benefit from the unlabeled data to estimate this manifold in the new space as a nearest neighbor graph. We finally utilize Tikhonov regularization to find a smooth... 

In today's programmable blockchains, smart contracts are limited to being deterministic and non-probabilistic. This lack of randomness is a consequential limitation, given that a wide variety of real-world financial contracts, such as casino games and lotteries, depend entirely on randomness. As a result, several ad-hoc random number generation approaches have been developed to be used in smart contracts. These include ideas such as using an oracle or relying on the block hash. However, these approaches are manipulatable, i.e. Their output can be tampered with by parties who might not be neutral, such as the owner of the oracle or the miners.We propose a novel game-theoretic approach for... 

In this letter, we introduce a semi-supervised manifold regularization framework for human pose estimation. We utilize the unlabeled data to compensate for the complexities in the input space and model the underlying manifold by a nearest neighbor graph. We argue that the optimal graph is a subgraph of the k nearest neighbors (k-NN) graph. Then, we estimate distances in the output space to approximate this subgraph. In addition, we use the underlying manifold of the points in the output space to introduce a novel regularization term which captures the correlation among the output dimensions. The modified graph and the proposed regularization term are utilized for a smooth regression over... 

For the 4th IUPAP International Conference of Women in Physics, we report on activities in science and engineering in Iran, and conditions for women in physics, in the three years since the 3rd IUPAP International Conference of Women in Physics was held in 2008. Iran has made prominent advancements and astonishing progress in laser technology, biotechnology, nanotechnology, genetics, computer software and hardware, and robotics. Iranian scientists have been very productive in several experimental fields, such as pharmaceutical, organic, and polymer chemistry. Conditions for women in physics have improved greatly in recent years. A project to improve the environment for learning physics, and... 

The lead is a heavy metal with hazardous impacts on environment and human life. Lead-free perovskite solar cells have attracted much attention in recent years, due to eco-friendly characteristics. Meanwhile, Pb-containing cells showed the highest efficiencies among the various types of cells. Hence, designing novel Pb-free solar cells with comparable or better performance than the Pb-containing ones is highly required. In this work, a lead-free methyl-ammonium-germanium-iodide (MAGeI3)-based perovskite solar cell with ITO/TiO2/MAGeI3/Spiro-OMeTAD/Ag multilayer nanostructure has been proposed and its main characteristics including open-circuit voltage (VOC) and power conversion efficiency (η)... 

Core/shell structure of ZnO nanowires coated with a monolayer of TiO 2 is investigated using Density Functional Theory (DFT). The electronic states of the semiconductor is calculated and compared before and after coating of the TiO2 monolayer on a ZnO [101 0] surface. The effect of TiO2 coating induce surface states changes and shifts the conduction and valence band edges to higher energies. Our results, in qualitative agreement with the experimental work of Matt Law et al. (J. Phys. Chem. B, 110, 22652), show an increase in open circuit voltage and a decrease in short circuit current in ZnO/TiO2 core shell dye sensitized solar cells. Regarding the semiconductor density of states (DOS), TiO2... 

Due to the important role of commitment and trust in the relationship marketing, the factors which can directly result in a committed relationship along with the factors which can influence the commitment through influencing trust, according to the model of commitment and trust by (Morgan & Hunt, 1994) have been introduced and their level of importance has been investigated here. The article uses fuzzy cognitive maps (FCMs) in the proposed model to find the most important paths leading to relationship commitment. The FCM analyzes the responses of a group of 30 people including general practitioners in dentistry, managers of dental departments in some of the public clinics and hospitals who... 

Conventionally, a film of TiO2 particles of 300 nm size is employed in Dye-sensitized solar cells (DSCs) as the back reflector film to enhance the light harvesting. Perfect reflectance of silver in visible and near infrared motivates to investigate its potential as the material for the light back reflector film in DSCs. In this study, light back reflector films consisting of 300 nm-sized silver particles, as well as vacuum evaporated silver flat film, were fabricated and compared to 300 nm-sized rutile-type TiO2 particulate reflector film to study their optical aspects. Conventional TiO2 rutile-type particulate film demonstrates slightly lower performance... 

Monolithic dye-sensitized solar cells are conventionally fabricated using carbon composite layer as the counter electrode. In the current research, the brittle carbon composite layer is replaced with a metal foil, aiming to decrease the device series resistance and using less catalyst material in counter electrode. This metallic structure has also an advantage of mechanical strength and decreases the fabrication complexity. The counter electrode is prepared by electrodepositing Cr film followed by electrodepositing Pt nanoparticles on a metal foil. As the porous spacer layer, different composite layers of SiO2, TiO2, and Al2O3 are investigated and the best results are obtained for TiO2... 

Microbial fuel cells (MFCs) have been a potential green energy source for a long time but one of the problems is that either the technology must be used on a large scale or special equipment have been necessary to keep the fuel cells running such as syringe pumps. Paper-based microbial fuel cells do not need to have a syringe pump to run and can run entirely by themselves when placed in contact with the fluids that are necessary for it to run. Paper-based microbial fuel cells are also more compact than traditional MFCs since the device doesn't need any external equipment to run. The goal of this paper is to develop a microbial fuel cell that does not require a syringe pump to function. This... 

This paper proposes a novel decentralized control approach for islanded direct-current (DC) microgrids (MGs) based on model predictive control (MPC) to regulate the distributed generation unit (DGU) output voltages, i.e. the voltages of the point of common coupling (PCC). A local controller is designed for each DGU, in the presence of uncertainties, disturbances, and unmodeled dynamics. First, a discrete-time state-space model of an MG is derived. Afterward, an MPC algorithm is designed to perform the PCC voltage control. The proposed MPC scheme ensures that the PCC voltages remain within an acceptable range. Several simulation studies have been conducted to illustrate the effectiveness of... 

Sophisticated surgeons are widely indicating the use of surgical robots in order to reject human error, increase precision, and speed. Among well-known robotic mechanisms, parallel robots are broadly more investigated regarding their special characters as higher acceleration, speed, and accuracy, and less weight. Specific surgical procedures confine, and restrict their workspace, while controlling and validating the robots are complicated regarding to their complex dynamic. To this end, in this paper, a 6-DOF robot, with rotary manipulators, is designed and controlled. Addressing nonlinearity of parallel robots, an innovative methodology is formulated to robustly penalize the error of... 

Sophisticated surgeons are widely indicating the use of surgical robots in order to reject human error, increase precision, and speed. Among well-known robotic mechanisms, parallel robots are broadly more investigated regarding their special characters as higher acceleration, speed, and accuracy, and less weight. Specific surgical procedures confine and restrict their workspace, while controlling and validating the robots are complicated based on their complex dynamic. To this end, in this paper, a 6-DOF robot, with linear manipulators, is designed and controlled. Addressing the inherent nonlinearity of the robot mechanism, an adaptive PID manipulator is employed and validated with nonlinear... 

Although so many advances have been proposed in the field of artificial intelligence and superconductivity, there are few reports on their combination. On the other hand, because of the nonlinear and multivariable characteristics of the superconductive elements and capabilities of neural networks in this field, it seems useful to apply the neural networks to model and control the superconductive phenomena or devices. In this paper, a new constructive neural network (CNN) trained by two different optimization algorithms; back-propagation and genetic algorithm, is proposed which models the behavior of the superconductive fault current limiters (SFCLs). Simulation results show that the proposed... 

In this paper, a new control strategy for optimal attitude tracking control of a multivariable satellite system has been presented. The approach is based on a Multilayer Perceptron Neural Network (MLPNN) and a classical PD Controller for its initial stabilization. It is shown how the network can be employed as a multivariable self-organizing and self-learning controller in conjunction with a PD controller for attitude control of a satellite. By using three thrusters and quaternion for kinematics representation, the attitude dynamics of the satellite has been presented. In contrast to the previous classical approaches, it is shown how this controller can be carried out in an on-line manner... 

ADI have been used for a wide variety of application in automotive,rail,and heavy engineering industry because of its excellent mechanical properties such as high strength with good ductility,good wear resistance,and good fatigue properties. The properties of austempered ductile iron are dependent on both chemistry and heat treatment, which has lead to invention of MADI (machinable austempered ductile iron). MADI is a new class of ductile iron with superior mechanical property than regular ductile iron with the same machinability characteristic. In this study Different cycles of austempering process (austenitization and austempering cycle) applied Due to the effect of heat treatment cycle on...