Farah Mohammadi

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.

ELECTROMAGNETIC MODEL FOR MICROWAVE COMPONENTS OF INTEGRATED CIRCUITS

This paper presents an accurate and robust time-domain electromagnetic model for microwave components of integrated circuits. The time-domain model has been validated on different structures such as metallic waveguides, planer lines and the transition of waveguide-microstrip line under harmonic oscillation excitation. The results obtained from simulation were compared to the experimental test results. The simulation results demonstrated that the approach is suitable to model microwave components of integrated circuits.

Temperature and power measurement of modern dual core processor by infrared thermography

An infrared (IR) thermography measurement setup to capture the temperature distribution and power dissipation of the device under test is proposed in this paper. The system is based on a transparent oil heatsink which captures the thermal profile and run-time power dissipation from the device under test with a very fine degree of granularity. The proposed setup is used to perform the thermal analysis and power dissipation measurement of an Intel Dual Core E2180 processor. In addition, a three-dimensional finite element thermal model of the processor is developed to simulate the thermal properties of the processor. The results obtained using simulation efforts are compared to the experimental results from IR thermography.

Tumor parameter estimation considering the body geometry by thermography

Implementation of non-invasive, non-contact, radiation-free thermal diagnostic tools requires an accurate correlation between surface temperature and interior physiology derived from living bio-heat phenomena. Such associations in the chest, forearm, and natural and deformed breasts have been investigated using finite element analysis (FEA), where the geometry and heterogeneity of an organ are accounted for by creating anatomically-accurate FEA models. The quantitative links are involved in the proposed evolutionary methodology for forecasting unknown Physio-thermo-biological parameters, including the depth, size and metabolic rate of the underlying nodule. A Custom Genetic Algorithm (GA) is tailored to parameterize a tumor by minimizing a fitness function. The study has employed the finite element method to develop simulated data sets and gradient matrix. Furthermore, simulated thermograms are obtained by enveloping the data sets with ±10% random noise.

Dynamic compact thermal model of a package

This paper presents the generation and verification of a dynamic compact thermal model of electronic packages. The method is demonstrated for ball grid array (BGA) package. The resulting RC network dynamic compact thermal model is optimized to diverse conditions typical to the application-specific environment. The accuracy of the model is found sufficient for thermal design purposes in terms of predicted junction temperature response and heat flux of the desired locations of the package.

Application of Advanced Metering Infrastructure 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 creating 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 focuses on AMI which as the foundation of SG is responsible for collecting all the data and information from loads and consumers. AMI is also responsible for implementing control signals and commands to perform necessary control actions as well as Demand Side Management (DSM). In this paper we introduce SG and its features, establish the relationship between smart grid and AMI, explain three main subsystems of AMI and discuss some issues related to design and deployment of AMI.

The application of supervised learning through feed-forward neural networks for ECG signal classification

This paper introduces the use of ECG signals from multiple leads to improve the accuracy of ECG signal classification with Artificial Neural Networks (ANN). The current methods commonly proposed rely on advanced signal processing or statistical analysis of the main lead II (MLII) in order to extract features that serve as a description of the signal. MLII, while being the most easily obtained ECG signal, does not contain a complete description of the electrical activity of the heart. Therefore, we propose to include a precordial lead, V1, from the Standard 12-Lead ECG system, to give the neural network a 2D view of the electrical patterns that arise during heart activation. This method was shown to be 99.5% accurate.

Thermogram Assessment for Tumor Parameter Estimation Considering Body Geometry

In this paper, an estimation methodology (inverse process) is presented to forecast unknown thermal and geometrical parameters of a tumor region using a temperature profile, which may be obtained by infrared thermography, on the skin surface of different organs. To solve the inverse problem, a bioheat transfer model with nonlinear boundary conditions was applied to rectangular, cylindrical, hemispherical, and deformed hemispherical body parts using finite-element analysis software. Then, the genetic algorithm (GA) was used to estimate the major parameters, such as depth, heat generation rate, and tumor size, by minimizing a fitness function involving the temperature profiles obtained from simulated or clinical data with those obtained from numerical simulation. The obtained results show consistency between the actual and forecasted parameters. It was determined that a GA-based methodology is well suited for the estimation problem, since the depth, heat generation rate, and size of the heat source have been accurately anticipated.

A new approach for electrothermal analysis of electronic circuits

In this paper a new methodology and implementation of an experimental infrared (IR) measurement technique for the thermal and electrothermal analysis of electronic circuits is presented. The electrothermal analysis is based on coupling a circuit simulator and IR thermography measurement through an application program interface that updates the temperature information in near-real time. This method is applied to study the performance of a power MOSFET circuit.

Optimal Placement of Heterogeneous Uncore Component in 3D Chip-Multiprocessors

In this article, we present a convex optimization model to design a stacked hybrid memory system contains eDRAM and STT-RAM banks with minimum write energy consumption of STT-RAM memory banks and minimum refresh energy of eDRAM banks with efficient number of TSVs in embedded CMP. Our convex model optimizes numbers and placement of memory banks from different technologies on the memory layer and finding optimal number and optimal placement of TSVs while satisfy maximum Load on TSVs. Experimental results on PARSEC benchmark show that the proposed Architecture improves energy-delay product (EDP) by 51% on average.