Illinois Institute of Technology

About: Illinois Institute of Technology is a education organization based out in Chicago, Illinois, United States. It is known for research contribution in the topics: Electric power system & Wireless network. The organization has 10188 authors who have published 21062 publications receiving 554178 citations. The organization is also known as: IIT & Illinois Tech.

Humidity sensing properties of Nation and sol-gel derived SiO2/Nafion composite thin films

Abstract: Nafion, sol-gel derived SiO2 and SiO2/Nafion composite films were prepared through casting and dip-coating methods. Impedance response of the films to relative humidity and the stability of the response against different aging environments were examined. The response to relative humidity of each film was analyzed with their complex impedance spectra at different humidities.

Robust Constrained Operation of Integrated Electricity-Natural Gas System Considering Distributed Natural Gas Storage

Abstract: A robust security-constrained unit commitment (robust SCUC) model is proposed in this paper to enhance the operational reliability of integrated electricity-natural gas system (IEGS) against possible transmission line outages. In this work, adjustable capability of natural gas contract is considered to avoid dramatic changes in real-time gas demand. Distributed natural gas storage is also included to smooth out power system demand curve and further improve operational efficiency at normal state and during contingencies. Nonlinear and nonconvex natural gas flow functions are relaxed into second-order cone (SOC) constraints, then the SOC-based column and constraint generation method is adopted to solve the proposed two-stage robust convex optimization problem. In this iterative method, the security-check subproblem feeds back worst case constraints to the first-stage master problem, until no violated scenarios can be detected. Simulations tested on 6-bus-6-node and 118-bus-10-node IEGS with natural gas storage show that the proposed storage model is effective in the robust SCUC solution for IEGS considering possible N − k contingencies with limited natural gas adjustments.

A Hybrid Model for Day-Ahead Price Forecasting

Abstract: This paper presents a hybrid time-series and adaptive wavelet neural network (AWNN) model for the day-ahead electricity market clearing price forecast. Instead of using price series, one-period continuously compounded return series is used to achieve more attractive statistical properties. The autoregressive moving average with exogenous variables (ARMAX) model is used to catch the linear relationship between price return series and explanatory variable load series, the generalized autoregressive conditional heteroscedastic (GARCH) model is used to unveil the heteroscedastic character of residuals, and AWNN is used to present the nonlinear, nonstationary impact of load series on electricity prices. The Monte Carlo method is adopted to generate more evenly distributed random numbers used for time series and AWNN models to accelerate the convergence. Several criteria such as average mean absolute percentage error (AMAPE) and the variance of forecast errors are used to assess the model and measure the forecasting accuracy. Illustrative price forecasting examples of the PJM market are presented to show the efficiency of the proposed method.

On greedy construction of connected dominating sets in wireless networks

Abstract: Summary Since no fixed infrastructure and no centralized management present in wireless networks, a connected dominating set (CDS) of the graph representing the network is widely used as a virtual backbone. Constructing a minimum CDS is NP-hard. In this paper, we propose a new greedy algorithm, called S-MIS, with the help of Steiner tree that can construct a CDS within a factor of 4:8 þ ln5 from the optimal solution. We also introduce the distributed version of this algorithm. We prove that the proposed algorithm is better than the current best performance ratio which is 6.8. A simulation is conducted to compare S-MIS with its variation which is rS-MIS. The simulation shows that the sizes of the CDSs generated by S-MIS and rS-MIS are almost the same. Copyright # 2005 John Wiley & Sons, Ltd.

Postprandial metabolic events and fruit-derived phenolics: a review of the science

Abstract: There is increasing evidence that the postprandial state is an important contributing factor to chronic disease. The role of fruit phenolic compounds to protect health and lower disease risk through their actions in mitigating fed-state metabolic and oxidative stressors is of interest and the topic of the present paper. Two main questions are posed: first, what is the role of plant foods, specifically fruits rich in complex and simple phenolic compounds in postprandial metabolic management; and second, does the evidence support consuming these fruits with meals as a practical strategy to preserve health and lower risk for disease? This review provides an overview of the postprandial literature, specifically on the effect of fruits and their inherent phenolic compounds in human subjects on postprandial lipaemia, glycaemia/insulinaemia and associated events, such as oxidative stress and inflammation. Among the identified well-controlled human trials using a postprandial paradigm, >50 % of the trials used wine or wine components and the remaining used various berries. Notwithstanding the need for more research, the collected data suggest that consuming phenolic-rich fruits increases the antioxidant capacity of the blood, and when they are consumed with high fat and carbohydrate 'pro-oxidant and pro-inflammatory' meals, they may counterbalance their negative effects. Given the content and availability of fat and carbohydrate in the Western diet, regular consumption of phenolic-rich foods, particularly in conjunction with meals, appears to be a prudent strategy to maintain oxidative balance and health.