Sharif Digital Repository

The design of a fully-integrated ΔΣ -controlled fractional-N frequency synthesizer is described. Using a dual modulus 64/72 prescaler based on injection locking technique and a novel third order digital ΔΣ modulator, we achieved an extremely low power synthesizer in 2.5GHz band.. Total power dissipation of the frequency synthesizer is less than 6mW at a 1.5V supply. The loop bandwidth is optimized to achieve a -123dBc/Hz phase noise at 3MHz offset frequency. The locking time of the loop is less than 30μs  

Conventional wastewater treatment processes are not completely effective in removing vancomycin. In this study, affecting parameters on vancomycin degradation, such as pH, catalyst, initial vancomycin concentration, temperature, and reaction time were investigated simultaneously during a removal process based on titanium dioxide with ultraviolet irradiation in an aqueous solution. Titanium dioxide was synthesized and characterized using X-ray diffraction and scanning electron microscopy. The average size of the synthesized crystals was 4.7 (± 0.2) nm. Design of experiments was done by a central composite design based on the response surface methodology and multiple linear regression was... 

Investigations have shown the traces of antibiotics in surface water, groundwater, wastewater treatment plants, and drinking water. However, conventional wastewater treatment is not entirely effective for vancomycin degradation. Advanced oxidation is one of the most widespread methods of antibiotic degradation in aqueous media. Vancomycin was quantified by high-performance liquid chromatography. The Response Surface Methodology (RSM) based on Central Composite Design (CCD) was used to explore and optimise the effect of the independent variables on vancomycin degradation. Independent variables were as follows: pH (3–11), vancomycin concentration (15–75 mg/L), TiO2–clinoptilolite (25–125 mg in... 

Purpose – This paper aims to provide a criteria-based evaluation framework for assessing knowledgemanagement system (KMS) development methodologies. Design/methodology/approach – The evaluation criteria have been elicited based on the features expected from a successful KMS. Furthermore, a number of prominent KMS development methodologies have been scrutinized based on the proposed evaluation framework. Findings – It was demonstrated that the proposed evaluation framework is detailed and comprehensive enough to reveal the strengths and weaknesses of KMS development methodologies. It was also revealed that even though the evaluated methodologies possess certain strong features, they suffer... 

In this work, we use 13 microlensing candidates with dark lenses from OGLE III catalogue [L. Wyrzykowski et al., Mon. Not. R. Astron. Soc. 458 (2016) 3012.] and cross-match them with the GAIA catalogue. We identify the microlensing source stars in the GAIA catalogue by comparing the coordinate and the magnitude of stars and using the proper motion and the parallax parameters of the source stars. Combining with the microlensing light curves as well as the microlensing parallax effect, we determine the mass and the distance of lenses from Earth. We conclude that the lens for this set of microlensing events for the massive lenses are black hole and for the small lenses are neutron/white dwarf... 

The main issue in a surveillance environment is the target tracking. The most important concern in this problem is the association of the various measurements with the existing target tracks. The fuzzy c-means data association (FCMDA) algorithm, based on the fuzzy c-means (FCM) algorithm, is an efficient solution for the problem of measurement to track association in a multisensor multitarget environment. It has a high accuracy in measurement to track association when targets are far from each other. However, its accuracy remains low when targets are close to one another. The FCMDA algorithm performance is usually lost in this environment, especially when measurement noise is high. In the... 

The problem of fuzzy data association for target tracking in a cluttered environment is discussed in this paper. In data association filters based on fuzzy clustering, the association probabilities of tracking filters are reconstructed by utilizing the fuzzy membership degree of the measurement belonging to the target. Clearly in these filters, the fuzzy clustering method has an important role; better approach causes better precision in target tracking. Recently, by using the information theory, the maximum entropy fuzzy data association filter (MEF-DAF), as a fast and efficient algorithm, is introduced in literature. In this paper, by modification of a fuzzy clustering objective function,... 

In this paper, the main discharge region and the plasma on the pre-ionization section in a TEA-CO2 laser are simulated by a distributed RLC electric circuit. The transmission line method is applied to the nonlinear distributed circuit, and it is approximated by a lumped nonlinear RLC circuit. By this method the governing partial differential equations are reduced to a system of ordinary differential equations. The parameters of the plasma in this laser are obtained by using this model. The possible photoionization instability is presented. To discuss the instability of the plasma, the current density perpendicular to the applied electric field is obtained. Furthermore, the electron... 

We propose a modified structured secant relation to get a more accurate approximation of the second curvature of the least squares objective function. Then, using this relation and an approach introduced by Andrei, we propose three scaled nonlinear conjugate gradient methods for nonlinear least squares problems. An attractive feature of one of the proposed methods is satisfication of the sufficient descent condition regardless of the line search and the objective function convexity. We establish that the three proposed algorithms are globally convergent, under the assumption of the Jacobian matrix having full column rank on the level set for one, and without such assumption for the other... 

We propose a modified structured secant relation to get a more accurate approximation of the second curvature of the least squares objective function. Then, using this relation and an approach introduced by Andrei, we propose three scaled nonlinear conjugate gradient methods for nonlinear least squares problems. An attractive feature of one of the proposed methods is satisfication of the sufficient descent condition regardless of the line search and the objective function convexity. We establish that the three proposed algorithms are globally convergent, under the assumption of the Jacobian matrix having full column rank on the level set for one, and without such assumption for the other... 

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... 

The current statistical model and adaptive filtering (CSMAF) algorithm is one of the most effective methods for tracking the maneuvering targets. However, it is still worthy to investigate the characteristics of the CSMAF algorithm, which 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 this paper a novel adaptive tracking algorithm for maneuvering targets is proposed. To overcome the disadvantage of the CSMAF algorithm, a simple multi-layer feedforward neural network (NN) is used By introducing NN, two sources of information of the filter are fused while its... 

The track fusion combines individual tracks formed by different sensors. Tracks are usually obtained by Kalman Filter (KF), since it is suitable for real-time application. The KF is an optimal linear estimator when the measurement noise has a Gaussian distribution with known covariance. However, in practice, some of the sensors do not have these properties, and the traditional KF is not an optimal estimator. In this paper, a novel adaptive Kalman filter (NAKF) is proposed. In this approach, the measurement noise covariance is adjusted by using an introduced simple mathematical function of one variable, called the degree of matching (DoM), where it is defined on the basis of covariance...