Sharif Digital Repository

The use of external fields such as magnet and ultrasound to enhance the targeted drug delivery (TDD) by nano-microcarriers could be a potential method. In this research, the drug delivery of magnetic nanoparticles (NPs) coated nanoliposomes and microbubbles (MBs) to the atherosclerosis plaque was investigated under magnetic and ultrasound fields in terms of their adhesion to the plaque through ligand–receptor binding. The Halbach arrangement enhanced the surface density of nanoliposomes and MBs adhered to the plaque by ∼ (Formula presented.) and ∼ (Formula presented.), respectively. A focused transducer at the power of (Formula presented.) led to better drug delivery performance and caused ∼... 

The use of external fields such as magnet and ultrasound to enhance the targeted drug delivery (TDD) by nano-microcarriers could be a potential method. In this research, the drug delivery of magnetic nanoparticles (NPs) coated nanoliposomes and microbubbles (MBs) to the atherosclerosis plaque was investigated under magnetic and ultrasound fields in terms of their adhesion to the plaque through ligand–receptor binding. The Halbach arrangement enhanced the surface density of nanoliposomes and MBs adhered to the plaque by ∼ (Formula presented.) and ∼ (Formula presented.), respectively. A focused transducer at the power of (Formula presented.) led to better drug delivery performance and caused ∼... 

Ideally the processing gain in passive radar is PG=BT. Where B is the bandwidth and T is the integration time. So by increasing T the target detectability will also increase. But practically, when we deal with moving targets, increasing T will result in a problem: target migration from its range cell that in turn results in decreased processing gain. In this paper we have suggested a method, by which we can compensate target's migration, while keeping the computational load low  

Targeted delivery by either passive or active targeting of therapeutics to the bone is an attractive treatment for various bone related diseases such as osteoporosis, osteosarcoma, multiple myeloma, and metastatic bone tumors. Engineering novel drug delivery carriers can increase therapeutic efficacy and minimize the risk of side effects. Developmnet of nanocarrier delivery systems is an interesting field of ongoing studies with opportunities to provide more effective therapies. In addition, preclinical nanomedicine research can open new opportunities for preclinical bone-targeted drug delivery; nevertheless, further research is needed to progress these therapies towards clinical... 

An optical guiding system is modeled and the signal processing and its operation are studied. Our model is based on the principle that two moving objects are considered, in which one is the moving robot, and the other one is the sought object. The reported system is capable of detecting and measuring the relative motion of the target, and, in response generating electrical signal capable of directing and guiding the vehicle on the shop floor. In this way, the respected robot or vehicle using such a device can maintain its aim on the related target scene at all times. The proposed system offers a higher degree of accuracy and reliability since it considers the state-of-art electronic and... 

In this paper the accuracy of measurement with respect to some parameters like baseline variance and DOA estimation and bistatic RCS is considered. The Radar designer can find the appropriate parameters to having the minimum error in target localization and maximum coverage range. © 2006 IEEE  

In this paper the problem of cooperative tracking of multiple targets for multi-agent systems is investigated. Defining problem of target tracking as gathering maximum rewards associated with the targets, an optimization-based algorithm is presented. A cooperative receding horizon controller for reaching moving targets is proposed. Agents are controlled by adjusting their headings toward the moving targets. A notable advantage of the proposed approach is the estimations of target's motion and planning the agent's heading based on them. Simulation results are provided to verify the efficiency of the proposed method  

In this paper, we consider the problem of transmit code design to optimize the detection probability of an extended target embedded in Gaussian signal-dependent interference. We model the target with a priori known target impulse response (TIR) structure along with an unknown reflection factor. As is known, the performance of the generalized likelihood ratio test (GLRT) detector, for the case at hand, monotonically increases with the signal-to-interference-plus-noise ratio (SINR). Hence, we deal with the code design problem via maximizing the SINR. We also enforce a peak-to-average power ratio (PAR) constraint on the sought code. We devise a cyclic method to tackle the highly non-convex... 

A new hybrid fuzzy adaptive algorithm for tracking maneuvering targets is proposed in this paper. The algorithm is implemented with fuzzy inference system (FIS) and current statistical model and adaptive Altering (CSMAF). The CSMAF algorithm is one of most effective methods for tracking the maneuvering targets. It has a higher precision in tracking the maneuvering targets with larger accelerations while it has a lower precision in tracking the maneuvering targets with smaller acceleration. In the proposed algorithm, to overcome the disadvantage of the CSMAF algorithm, the covariance of process noise CSMAF is adjusted adaptively by the output of a FIS. The input of the FIS is discrepancy of... 

Characterization and determination of a complex mixture of fatty acid methyl esters was performed for commercial fish oil using two-dimensional GC-MS data coupled with resolution techniques. Various principle component analysis methods such as significant factor analysis and fixed size moving window evolving factor analysis were used for the number of factors, zero concentration and selective regions. Then, the convoluted chromatograms were resolved into pure chromatograms and mass spectra using heuristic evolving latent projections (HELP) method. Fatty acids of C16:1ω7, C18:4ω3, C18:1ω11, C18:1ω9, C18:0, C20:2ω6, C20:1ω9, C 22:1ω11, C22:1ω9 and C24:1ω9 were resolved and identified by using... 

We present a new method for the robust estimation of a two-dimensional conducting target orientation using measured radar cross-section data. The method is based on a Generalized Regression Neural Network (GRNN) scheme, which belongs to the family of radial basis neural networks  

A new method for the robust estimation of target orientation using measured radar cross section is proposed. The method is based on a Generalized Regression Neural Network (GRNN) scheme. The network is trained by the FFT modulus of bistatic radar cross section data sampled at the receiver positions. The target value to be trained is the angle between a defined target orientation and the incident wave. Results based on actual measurements are presented  

To produce emotional artificial systems in AI domain, usually a subset of human emotional states are imported to the target domain and the major differences between natural and artificial domains are often ignored. In this paper we will discuss about why such an approach is not useful for all possible applications of emotions and we will show how it is necessary and possible to produce artificial emotion systems based on the target systems goals, abilities and needs  

In this paper a novel algorithm for detection, parameter estimation, and image formation of a moving target in ground-based circular strip-map synthetic aperture radar (GBCSAR) is proposed. Because multiple similar scans of the scene with short revisit time are possible, moving target detection is performed by clutter cancellation. Despite of the frequency-domain or multi-antenna clutter cancellation methods, this system has the capability of removing the clutter completely regardless of the target speed or the signal to clutter ratio (SCR). Estimation of target parameters and range-cell migration correction (RCMC) is based on comparing two consecutive target images. Finally the azimuth... 

The Gaussian mixture probability hypothesis density (GM-PHD) filter is a closed form approximation of the multi-target Bayes filter which can overcome most multitarget tracking problems. Limited field of view, decreasing cost of cameras, and advances of using multi-camera induce us to use large-scale camera networks. In this paper, a multihuman tracking framework using the PHD filter in a distributed camera network is proposed. Each camera tracks objects locally with PHD filter and a track-after-detect scheme and its estimates of targets are sent to neighboring nodes. Then each camera fuses its local estimates with it's neighbors. The proposed method is evaluated on the public PETS2009... 

An algorithm, by cooperation of multiple flying vehicles, is developed to localize a moving target in the presence of measurement noise and mis-modeling. It works based on jointly sharing information and data fusion by using a recursive Bayesian estimator and a searching guidance law to direct each flying vehicle to a position where the probability of target detection is maximum. To evaluate this algorithm, a high fidelity simulation program with six degrees of freedom dynamics is also developed  

In this paper, an iterative method for block-sparse recovery is suggested for target parameters estimation in a distributed MIMO radar system. The random sampling has been used as the sensing scheme in the receivers. The simulation results prove that the proposed method is superior to the other state-of-the-art techniques in the accuracy of the target estimation task. © 2016 IEEE  

While visual target tracking is one of the noteworthy and the most active research areas in computer vision and machine learning, many challenges are still unresolved. In this paper, an adaptive generic target tracker is proposed that includes the adaptive determination of learning parameters from spatio-temporal context model, analysis of prior targets and confidence map for accurate target localization, and modified scale estimation scheme based on confidence map. According to spatio-temporal context model, the learning parameters are adaptively determined for achieving confidence map and target scale robustly. Moreover, analysis of the confidence map helps our tracker to change context... 

Several target position finding methods are proposed in various papers mainly regarding sensor networks. However, the problem of position finding in passive radar systems is somewhat different from the general case of sensor networks. Generally, in a passive radar system, there are few receivers located at short distances when compared with the it distance from the target. In this case, a problem known as geometric dilution of precision (GDP) occurs, which considerably increases the error of many proposed methods. This phenomenon can even make the position finding equations non-solvable. Regarding this fact, we have developed a least mean square error (LMSE) based method, which uses both the... 

One of the agents of error in angle of arrival estimation of signal is the response of the ground to the reflected waves from the target. In low-height target situations this phenomenon can be so tormenting that may cause much more error than thermal noise. In this article two methods of Fixed Beam and Double Null are used as preliminary techniques to overcome the problem of low-altitude targets angle estimation and the optimum weights for beam-forming array radar are proposed. The beam-forming methods enable the radar to estimate the target angle precisely while it is robust against diffuse and specular ground reflection components and the exact knowledge of surface slope is not required