Mahboobeh Ghorbani | University of Southern California (original) (raw)

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Papers by Mahboobeh Ghorbani

With discovery of the insulin, Type-1 diabetes converted from a fatal and acute to a chronic dise... more With discovery of the insulin, Type-1 diabetes converted from a fatal and acute to a chronic disease which includes micro-vascular complications which range from Kidney disease to stroke and micro-vascular complications such as retinopathy, nephropathy and neuropathy. Artificial pancreas is a solution to improve the quality of life for people with this very fast growing disease in the world and to reduce the costs. Despite technological advances e.g., in subcutaneous sensors and actuators for insulin injection, modeling of blood glucose dynamics and control algorithms still need significant improvement. In this paper, we investigate challenges and opportunities for development of efficient algorithm for designing robust artificial pancreas. We discuss the state of the art and summarize clinical and in silico assessment results. We contrast conventional integer order system approach with a newly proposed fractal control and summarize its benefits.

Frontiers in physiology, 2018

Gene expression is a vital process through which cells react to the environment and express funct... more Gene expression is a vital process through which cells react to the environment and express functional behavior. Understanding the dynamics of gene expression could prove crucial in unraveling the physical complexities involved in this process. Specifically, understanding the coherent complex structure of transcriptional dynamics is the goal of numerous computational studies aiming to study and finally control cellular processes. Here, we report the scaling properties of gene expression time series in and . Unlike previous studies, which report the fractal and long-range dependency of DNA structure, we investigate the individual gene expression dynamics as well as the cross-dependency between them in the context of gene regulatory network. Our results demonstrate that the gene expression time series display fractal and long-range dependence characteristics. In addition, the dynamics between genes and linked transcription factors in gene regulatory networks are also fractal and long-...

Proceedings of the 2014 International Conference on Hardware/Software Codesign and System Synthesis, 2014

Cloud Computing is a promising approach to handle the growing needs for computation and storage i... more Cloud Computing is a promising approach to handle the growing needs for computation and storage in an efficient and cost-effective manner. Towards this end, characterizing workloads in the cloud infrastructure (e.g., a data center) is essential for performing cloud optimizations such as resource provisioning and energy minimization. However, there is a huge gap between the characteristics of actual workloads (e.g., they tend to be bursty and exhibit fractal behavior) and existing cloud optimization algorithms, which tend to rely on simplistic assumptions about the workloads. To close this gap, based on fractional calculus concepts, we present a fractal model to account for the complex dynamics of cloud computing workloads (i.e., the number of request arrivals or CPU/memory usage during each time interval). More precisely, we introduce a fractal operator to account for the time-varying fractal properties of the cloud workloads. In addition, we present an efficient (online) parameter estimation algorithm, an accurate forecasting strategy, and a novel fractal-based model predictive control approach for optimizing the CPU utilization, and hence, the overall energy consumption in the system while satisfying networked architecture performance constraints like queue capacities. We demonstrate advantages of our fractal model in forecasting the complex cloud computing dynamics over conventional (non-fractal) models by using real-world cloud (Google) traces. Unlike non-fractal models, which have very poor prediction capabilities under bursty workload conditions, our fractal model can accurately predict bursty request processes, which is crucial for cloud computing workload forecasting. Finally, experimental results demonstrate that the fractal model based optimization outperforms the non-fractal based ones in terms of minimizing the resource utilization by an average of 30%.

EURASIP Journal on Advances in Signal Processing, 2012

In this article, we present a new iterative algorithm aimed at improving the performance of the s... more In this article, we present a new iterative algorithm aimed at improving the performance of the sigma-delta analog to digital (A/D) converter. We subject the existing sigma-delta modulator, without changing the configuration, to an iterative procedure to increase the signal-to-noise ratio of the reconstructed signal. In other words, we demonstrate that sigma-delta modulated signals can be decoded using the iterative algorithm. Simulation results confirm that the proposed method works very well, even when less complex filters are used. The simple and regular structure of this new A/D converter, not only makes realization of the hardware as ASIC or on FPGA boards easy, but also allows it to operate at high frequency levels with optimized power consumption and small chip area. Implementation of the design with an FPGA shows that experimental results are in agreement with the simulation results.

2013 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), 2013

Healthcare costs in the US are among the highest in the world. Widespread chronic diseases such a... more Healthcare costs in the US are among the highest in the world. Widespread chronic diseases such as diabetes constitute a significant cause of rising healthcare costs. Despite the increased need for smart healthcare systems that monitor patients' body balance, there is no coherent theory that facilitates the design and optimization of efficient and robust cyber physical systems. In this paper, we propose a mathematical model for capturing the dynamics of blood glucose characteristics (e.g., time dependent fractal behavior) observed in real world measurements via fractional calculus concepts. Building on our time dependent fractal model, we propose a novel mathematical model as well as hardware architecture for an artificial pancreas that relies on solving a constrained multi-fractal optimal control problem for regulating insulin injection. We verify the accuracy of our mathematical model by comparing it to conventional nonfractal models using real world measurements and showing that the nonlinear optimal controller based on fractal calculus concepts is superior to nonfractal controllers. We also verified the feasibility of in silico realization of the proposed optimal control algorithm by prototyping on FPGA platform.

2014 IEEE International Congress on Big Data, 2014

$Research paper thumbnail of Reducing risk of closed loop control of blood glucose in artificial pancreas using fractional calculus$

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014

Healthcare costs in the US are among the highest in the world. Chronic diseases such as diabetes ... more Healthcare costs in the US are among the highest in the world. Chronic diseases such as diabetes significantly contribute to these extensive costs. Despite technological advances to improve sensing and actuation devices, we still lack a coherent theory that facilitates the design and optimization of efficient and robust medical cyber-physical systems for managing chronic diseases. In this paper, we propose a mathematical model for capturing the complex dynamics of blood glucose time series (e.g., time dependent and fractal behavior) observed in real world measurements via fractional calculus concepts. Building upon our time dependent fractal model, we propose a novel model predictive controller for an artificial pancreas that regulates insulin injection. We verify the accuracy of our controller by comparing it to conventional non-fractal models using real world measurements and show how the nonlinear optimal controller based on fractal calculus concepts is superior to non-fractal co...

$Research paper thumbnail of Prediction and control of bursty cloud workloads: A fractal framework$

In nanometer-scale process technologies, the effects of process variations are observed in Multip... more In nanometer-scale process technologies, the effects of process variations are observed in Multiprocessor System-on-Chips (MPSoC) in terms of variations in frequencies and leakage powers among the processors on the same chip as well as across different chips of the same design. Traditional approaches try to improve the worst-case value for energy of a system whereas statistical optimizations are more recently

Abstract In nanometer-scale process technologies, the effects of process variations are observed ... more Abstract In nanometer-scale process technologies, the effects of process variations are observed in Multiprocessor System-on-Chips (MPSoC) in terms of variations in frequencies and leakage powers among the processors on the same chip as well as across different ...