The superiority of multiple-input multiple-output (MIMO) radars over conventional radars has been recently shown in many aspects. These radars consist of many transmitters and receivers located far from each other. In this scenario, the MIMO radar is able to observe the targets from different directions. One of the advantages of these radars is exploitation of Doppler frequencies from different transmitter-target-receiver paths. The extracted Doppler frequencies can be used for estimation of target velocity Vector so that, the radar can be able to track the targets by use of its velocity Vector with reasonable accuracy. In this paper, two different processing systems are considered for MIMO radars. First one is the pulse Doppler system, and the second one is continuous wave (CW) system without range processing. The measurement of the velocity Vector of the target and its counterpart errors are taken into account. Also, the extended Kalman target Tracking by using its velocity Vector is considered. Besides, its performance is compared with those of MIMO target Tracking without using the velocity Vector and conventional radars. The simulation results show that the MIMO radars using velocity Vector have superior performance over other above-mentioned radars in fast maneuvering target Tracking. Since the range processing is ignored in CW MIMO radar systems, the complexity of this system is much lower than that of Pulse Doppler MIMO radar system, but has lower performance in Tracking fast maneuvering target.

"In this paper, a new method for Vector Tracking of GPS satellite signals in weak signal circumstances is presented. Extended Kalman Filter (EKF) is usually used in Vector Tracking. As divergence is one of the main problems in common Kalman filters, Adaptive Kalman filters are used to avoid divergence. Common adaptive Kalman filter in Vector Tracking is implemented using a window with limited length, which cannot be greater than a specified amount and so after a short while Kalman filter will become divergent again. Window length is specified empirically and in accordance to statistical characteristics which may lead to an ideal solution for one specific amount, but not the other. Therefore adaptive Strong Tracking Kalman Filter (STKF) is used in this paper. Simulation results show that adaptive STKF has high accuracy in rela-tion to adaptive EKF, and in case of correctly arranged STKF parameters computing complexity of the pro-posed Vector Tracking will be less than the traditional method. Results show that in comparison to tradition-al Vector Tracking, methods based on adaptive STKF have significantly reduced errors in measuring carrier frequency, position and of course velocity.

In high dynamic conditions, using Vector Tracking loops instead of scalar Tracking loops in GPS receivers is proved as an efficient method to compensate the performance. The Minimum Mean Squared Error detector as a multiuser detector is applied in the Vector Tracking loop for more reliability and efficiency. The Kalman filter does the two tasks of Tracking and extracting the navigation data after applying the multiuser detection on the correlator outputs. The covariance analysis is performed to study the effect of applying a multiuser detector along with a Vector Tracking loop against the conventional one. The covariance analysis is performed and the variance in the pseudorange-rate estimates produced by the two architectures of conventional Vector Tracking and the one with multiuser detector are used as the performance criteria. The steady state, state covariance of the Kalman filter of Vector Tracking loop is calculated. Comparing the psuedorange rate variances obtained from covariance analysis of each method shows improved performance of the new joint receiver of Vector and multiuser detector.

Target Tracking is estimating the state of moving targets using noisy measurements obtained at a single observation point or node. Particle filters or sequential Monte Carlo methods use a set of weighted state samples, called particles, to approximate the posterior probability distribution in a Bayesian setup. During the past few years, Particle Filters have become very popular because of their ability to process observations represented by nonlinear state-space models where the noise of the model can be non-Gaussian. There are many Particle Filter methods, and almost all of them are based on three operations: particle propagation, weight computation, and resampling. One of the main limitations of the previously proposed schemes is that their implementation in a wireless sensor network demands prohibitive communication capability since they assume that all the sensor observations are available to every processing node in the weight update step. In this paper, we use a machine learning technique called support Vector machine to overcome this drawback and improve the energy consumption of sensors. Support Vector Machine (SVM) is a classifier which attempts to find a hyperplane that divides two classes with the largest margin. Given labeled training data, SVM outputs an optimal hyperplane which categorizes new examples. The training examples that are closest to the hyperplane are called support Vectors. Using our approach, we could compress sensor observations and only support Vectors will be communicated between neighbor sensors which lead to cost reduction in communication. We use LIBSVM library in our work and use MATLAB software to plot the results and compare the proposed protocol with CPF and DPF algorithms. Simulation results show significant reduction in the amount of data transmission over the network.

It is well-known that the stator Inter-Turn Short Circuit (ITSC) fault detection in Vector-controlled Induction Motor (IM) is a very difficult task so far. This is due to the various problems encountered in diagnostic processes resulting from the speed variation and its influence on electrical signals. As a solution, this paper proposes an approach based on the Vold-Kalman Filter Order Tracking (VKF-OT) technique. To this end, stator phase current, quadrature current and rotational speed were monitored at various speeds with and without fault (i. e. healthy and with the ITSC fault) in the Field oriented control (FOC) IM drive. The VKF-OT technique was applied to the monitored currents in order to track the related harmonic components fault, the results are compared to the classical Fourier analysis (FFT). The obtained results proved that the presented approach is more efficient than the FFT technique, especially when the IM is operating under non-stationary speed conditions.

Aims and Background: Nowadays, monoclonal antibodies (mAbs) became powerful therapeutic and diagnostic tools. Due to showing minimum immunogenic reaction and their properties, human mAbs are important. The purpose of this study was to construct an immune antibody library from a vaccinated donor against tetanus toxin.Materials and Methods: A whole blood sample was taken from the donor who was vaccinated against tetanus toxoid. PBMC were isolated by using ficol. After RNA extraction, all variation of VH and VL regions by RT-PCR reactions were amplified and linked as a ScFv antibody. The amplicons were inserted in T-Vector and transformed to E. coli DH5α strain, followed by an ELISA test. Plasmids were also extracted and sequenced.Results: cDNA quality was confirmed by using HPRT primers. To confirm PCR, insertion and transformation, gel electrophoresis and restriction enzymes digestion were applied. Positive clones were selected based on growth on LB agar which is the blue/white selection method. After plasmid extraction and DNA sequencing, the sequences were aligned using igBLAST at NCBI. The result was shown to have admissible similarity among antibody gene library nucleotide sequences and the antibody genes were deposited in this database. ELISA confirmed this data too.Conclusion: In this study, the immune human antibody library was constructed and confirmed using DNA sequencing and sequences alignment in NCBI database. ELISA test confirms antibody specifically. The next step is to screen the library to find an antibody specifically for tetanus toxin.

In today's world, we are witnessing the launch, maintenance, control and exploitation of various projects. Projects that have high costs and optimal use of this capital in the current economy of the country are highly regarded by managers. On the other hand, each project is expected to achieve its predetermined goals at a specified time. Today, the necessity of rapid construction of subway lines in Tehran's metropolitan area, which is involved in severe traffic jams, is not covered by anyone. Despite the understanding of this issue by the authorities and the good actions taken so far in this direction. However, more effort and a greater determination to reach the acceptable speed in the construction and completion of metro lines is necessary. Quick implementation of projects is based on the principles of concurrent engineering, called fast Tracking, in construction projects. In the fast delivery method, solutions such as resource enhancement, synchronous engineering, overlapping phases, value engineering, teamwork by the multi-functional team, improving communication and information transfer, and accelerating decision making, using efficient contractual methods (transferring risks as Effective way, which by using the correct methods, accelerates the implementation of the project. Therefore, in this article, management strategies for implementing fast Tracking projects in the development projects of the country have been investigated.