< p>Tracking objects in video images has attracted much attention by machine vision and image processing researchers in recent years. Due to the importance of the subject, this paper presents a method for improving object tracking tasks with partial occlusion, which increases the efficiency of tracking. The proposed approach first performs a pre-processing and extracts the tracking targets from the image. Then the salient feature points are extracted from the targets that are moving objects. In the next step, the particle filter is used for tracking. The final steps are modifying points and updates. A new approach is used to determine the speed of the feature points because the speed of some points can be out of range and this causes errors in tracking especially when there is occlusion. The location of the new points is corrected and updated using the threshold values in modifying the process as needed. The experiments performed on the video sequence of PETS2000 database show that the precision and recall of the proposed approach are higher than other compared approaches. Manuscript profile

Nano-scale technology has brought more susceptibility to soft errors for the generation of complicated and state of the art devices. Soft errors are the impacts of radiation of the particles like a neutron, alpha, and ions on the surface of the circuits. To tackle the system malfunctions and provide a reliable device, studying the transient fault effects on the logic circuits can be a more significant issue. This paper presents a new approach based on Recurrent Neural Networks (RNNs) to estimate ICs' Soft Errors Rate (SER). As RNN can be deployed for signal processing and time series, we applied it to investigate transient fault effects while propagating through the combinational and sequential parts of a test chip and compute its SER by simulating and analyzing the circuit outputs. In this paper, the results of utilizing the proposed RNN model to estimate the SER of the ISCAS-85 benchmark circuits have been provided. Manuscript profile

Estimating the final price of products is of great importance. For manufacturing companies proposing a final price is only possible after the design process over. These companies propose an approximate initial price of the required products to the customers for which some of time and money is required. Here using the existing data of already designed transformers and utilizing the bayesian analysis of generalize poisson models and artificial neural networks, a shortcut method for estimating the material and final price of transformers is established. The proposed method being quite precise and fast, without any cost. Manuscript profile

In recent years, many researchers have been done in the area of wireless sensor networks that has led to the variety of algorithms and methods for the collection and transmission of environment information; but still many challenges faced by wireless sensor networks using methodologies are applied in various fields. Such as Media Access Control that due to the media being shared on these networks, there is a possibility of collision and data loss. Since the retransmission increases network latency and consequently reduces network energy, therefore various solutions have been proposed for media access control that their main purpose is media access control and prevention of collisions. Hence media access control protocols requirement, more and more felt. In this study, a free collision algorithm with the acceptable ability to media access channel is presented in which we have tried to reduce the number of time slots and increase the network throughput as much as possible. Manuscript profile