Kaamran Raahemifar

An overview of design techniques for CMOS phase detectors

An overview of the recent developments in the design techniques of CMOS phase detectors and an in-depth examination of the advantages and limitations of these techniques are presented. Both linear and nonlinear phase detectors are examined. Critical design issues, such as, sampling mechanism, lock condition, sensitivity to input data pattern, and reliability are investigated in detail.

Content based audio classification and retrieval using joint time-frequency analysis

We present an audio classification and retrieval technique that exploits the non-stationary behavior of music signals and extracts features that characterize their spectral change over time. Audio classification provides a solution to incorrect and inefficient manual labelling of audio files on computers by allowing users to extract music files based on content similarity rather than labels. In our technique, classification is performed using time-frequency analysis and sounds are classified into 6 music groups consisting of rock, classical, folk, jazz and pop. For each 5 second music segment, the features that are extracted include entropy, centroid, centroid ratio, bandwidth, silence ratio, energy ratio, and location of minimum and maximum energy. Using a database of 143 signals, a set of 10 time-frequency features are extracted and an accuracy of classification of around 93% using regular linear discriminant analysis or 92.3% using the leave-one-out method is achieved.

A novel genetic algorithm in LEACH-C routing protocol for sensor networks

This paper presents a new approach to clustering wireless sensor networks and determining cluster heads. Here we apply evolutionary algorithms in centralized clustering. LEACH-C is one of the effective (basic) parameters in network life time based on energy consuming value protocol. In suggested evolutionary algorithm, through proper application of evolutionary operators, we search for efficient clustering based on each nodes energy. Innovation of our method is in proper representation of chromosomes and also in determining proper fitness function according to problem features based on energy measure. In this paper we propose two new fitness functions. The results of applying these functions on four different types of sensor networks are presented and compared with the results of the Simulated Annealing method.

Effect of tumor shape, size, and tissue transport properties on drug delivery to solid tumors.

BackgroundThe computational methods provide condition for investigation related to the process of drug delivery, such as convection and diffusion of drug in extracellular matrices, drug extravasation from microvessels or to lymphatic vessels. The information of this process clarifies the mechanisms of drug delivery from the injection site to absorption by a solid tumor. In this study, an advanced numerical method is used to solve fluid flow and solute transport equations simultaneously to investigate the effect of tumor shape and size on drug delivery to solid tumor.MethodsThe advanced mathematical model used in our previous work is further developed by adding solute transport equation to the governing equations. After applying appropriate boundary and initial conditions on tumor and surrounding tissue geometry, the element-based finite volume method is used for solving governing equations of drug delivery in solid tumor. Also, the effects of size and shape of tumor and some of tissue transport parameters such as effective pressure and hydraulic conductivity on interstitial fluid flow and drug delivery are investigated.ResultsSensitivity analysis shows that drug delivery in prolate shape is significantly better than other tumor shapes. Considering size effect, increasing tumor size decreases drug concentration in interstitial fluid. This study shows that dependency of drug concentration in interstitial fluid to osmotic and intravascular pressure is negligible.ConclusionsThis study shows that among diffusion and convection mechanisms of drug transport, diffusion is dominant in most different tumor shapes and sizes. In tumors in which the convection has considerable effect, the drug concentration is larger than that of other tumors at the same time post injection.

Suboptimal Rate Adaptive Resource Allocation for Downlink OFDMA Systems

This paper aims to study the performance of low complexity adaptive resource allocation in the downlink of OFDMA systems with fixed or variable rate requirements (with fairness consideration). Two suboptimal resource allocation algorithms are proposed using the simplifying assumption of transmit power over the entire bandwidth. The objective of the first algorithm is to maximize the total throughput while maintaining rate proportionality among the users. The proposed suboptimal algorithm prioritizes the user with the highest sensitivity to the subcarrier allocation, and the variance over the subchannel gains is used to define the sensitivity of each user. The second algorithm concerns rate adaptive resource allocation in multiuser systems with fixed rate constraints. We propose a suboptimal joint subchannel and power allocation algorithm which prioritizes the users with the highest required data rates. The main feature of this algorithm is its low complexity while achieving the rate requirements.

Numerical modeling of drug delivery in a dynamic solid tumor microvasculature.

The complicated capillary network induced by angiogenesis is one of the main reasons of unsuccessful cancer therapy. A multi-scale mathematical method which simulates drug transport to a solid tumor is used in this study to investigate how capillary network structure affects drug delivery. The mathematical method involves processes such as blood flow through vessels, solute and fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. The effect of heterogeneous dynamic network on interstitial fluid flow and drug delivery is investigated by this multi-scale method. The sprouting angiogenesis model is used for generating capillary network and then fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network and fluid flow in normal and tumor tissues. Finally, convection-diffusion equation is used to simulate drug delivery. Three approaches are used to simulate drug transport based on the developed mathematical method: without a vascular network, using a static vascular network, and a dynamic vascular network. The avascular approach predicts more uniform and higher drug concentration than vascular approaches since the simplified assumptions are implemented in this method. The dynamic network which uses more realistic assumptions predicts more irregular blood vessels, high interstitial pressure, and more heterogeneity in drug distribution than other two approaches.

Optic Disc and Optic Cup Segmentation Methodologies for Glaucoma Image Detection: A Survey

Glaucoma is the second leading cause of loss of vision in the world. Examining the head of optic nerve (cup-to-disc ratio) is very important for diagnosing glaucoma and for patient monitoring after diagnosis. Images of optic disc and optic cup are acquired by fundus camera as well as Optical Coherence Tomography. The optic disc and optic cup segmentation techniques are used to isolate the relevant parts of the retinal image and to calculate the cup-to-disc ratio. The main objective of this paper is to review segmentation methodologies and techniques for the disc and cup boundaries which are utilized to calculate the disc and cup geometrical parameters automatically and accurately to help the professionals in the glaucoma to have a wide view and more details about the optic nerve head structure using retinal fundus images. We provide a brief description of each technique, highlighting its classification and performance metrics. The current and future research directions are summarized and discussed.

Optimal PID controller design for AVR system using particle swarm optimization algorithm

A proportional-integral-derivative (PID) controller is a generic feedback controller widely used in industrial control systems, process control, motor drive, and instrumentation. Despite the popularity, the tuning aspect of PID coefficients is a challenge for researchers and plant operators. In this paper Particle Swarm Optimization Algorithm is used to design the optimum PID controller parameters for a high order automatic voltage regulator (AVR). The proposed approach with new defined time-domain cost function, has a very easy implementation, stable convergence characteristic and ability of fast tuning of optimum PID controller parameters that requires fewer number of iterations. In order to evaluate the performance of the PSO-PID controller, the results are compared with the genetic algorithm (GA). The comparison shows the PSO-PID algorithm has more efficiency and robustness in improving the step response of an AVR system.

A Novel Subcarrier Allocation Algorithm for Multiuser OFDM System With Fairness: User's Perspective

In wireless multiuser OFDM systems, dynamic resource allocation has been shown to improve the performance by exploiting the multiuser diversity. In this paper we propose a subcarrier allocation algorithm to increase the total data rate for the downlink of a variable bit rate multiuser OFDM system with proportional rate constraints subject to bit error rate and total transmit power. We assume that the channel is quasi-static where the channel status does not vary within each transmission block and the base station has perfect knowledge of subchannel gains. The proposed algorithm is based on prioritizing the critical (most sensitive) user in the system and the variance of the subchannel gains for each user is used to define the sensitivity of the user to the subcarrier allocation. Simulation results show that this algorithm achieves higher capacity with acceptable proportional fairness compared to the previous suboptimal solutions proposed by Rhee et al. in [9] and Shen et al. in [12].

A Survey on Advanced Metering Infrastructure and its Application in Smart Grids

This survey paper is an excerpt of a more comprehensive study on Smart Grid (SG) and the role of Advanced Metering Infrastructure (AMI) in SG. The survey was carried out as part of a feasibility study for the creation of a Net-Zero community in a city in Ontario, Canada. SG is not a single technology; rather it is a combination of different areas of engineering, communication and management. This paper intends to focus on AMI, which is responsible for collecting all the data and information from loads and consumers, as the foundation for SG. AMI is also responsible for implementing control signals and commands to perform necessary control actions, including Demand Side Management (DSM). In this paper we introduce SG and its features, establish the relation between SG and AMI, explain three main subsystems of AMI and discuss related security issues.