The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Circuit designers typically combat variations in hardware and workload by increasing conservative guardbanding that leads to operational inefficiency. Reducing this excessive guardband is highly desirable, but causes timing errors in synchronous circuits. We propose a methodology for supervised learning based models to predict timing errors at bit-level. We show that a logistic regression based model...
Technology products and software undergo large pre-release testing which is restricted to selected customers called a focus group. Acquiring feedback from these customers provides valuable information about the potential acceptance of the product in the market. Currently, these groups are formed either by manual or random selection or by out-sourcing, which incurs a substantial cost. However, automatic...
Estimating the wake losses in a wind farm is critical in the short term forecast of wind power, following the Numerical Weather Prediction (NWP) approach. Understanding the intensity of the wakes and the nature of its propagation within the wind farm still remains a challenge to scientist, engineers and utility operators. In this paper, five different machine learning methods are used to estimate...
A sizable fraction of expensive resources such as water, gas, and electricity are lost in the process of distribution due to leaks, theft, and inefficiencies like aging infrastructure. Utilities worldwide are looking for solutions to localise losses and improve the overall efficiency of their distribution systems. The introduction of new sensing, communication, and control infrastructure in the next...
As the output from the solar PV systems varies significantly with technologies, designs and prevailing weather parameters, their evaluation under actual field conditions is important in identifying their real performance characteristics. In this paper, comparative performances of six different PV systems connected to a 1.2 MWp grid integrated solar farm are presented. The solar technologies considered...
Time series and data mining techniques have recently become popular for smart grid planning and optimization problems, in applications such as demand forecasting and renewable energy availability prediction. In the future liberalized smart grid with distributed generation and time varying resource pricing and availability, optimizing and sizing centralized and distributed energy resources for profit...
Power utilities worldwide face two major challenges — peak demand and power (supply-demand) imbalance. In the midst of these difficulties faced by utilities, growing fuel costs, environmental awareness and government directives have increased the push to deploy Electric Vehicles (EVs). One single EV being charged at its peak rate imposes an instantaneous load equivalent to that of 10 average households...
Economic and environmental concerns have fostered interest in incorporating greater amounts of electricity from renewable energy sources into the grid. Unfortunately, the intermittent availability of renewable power has raised a barrier to the inclusion of these sources. Distributed storage is perceived as a means to extract value from the different resources. However, the large cost of storage requires...
Increased environmental and economic concerns have set the stage for an increase in the fraction of electricity supplied using renewable sources. Recent advances in wind prediction offer hope that reduction in the uncertainty of wind availability will lead to an increase in its value. Model based methods that predict future wind availability and then optimize local generation have been seen to be...
Growing environmental awareness and new government directives have set the stage for an increase in the fraction of energy supplied using renewable resources. The fast variation in renewable power, coupled with uncertainty in availability, emphasizes the need for algorithms for intelligent online generation scheduling. These algorithms should allow us to compensate for the renewable resource when...
In this paper we describe an ongoing project which develops an automated residential Demand Response (DR) system that attempts to manage residential loads in accordance with DR signals. In this early stage of the project, we propose an approach for identifying individual appliance consumption from the aggregate load and discuss the effectiveness of load disaggregation techniques when total load data...
In this paper, a novel iterative encoding scheme is proposed for memory systems suffering from stuck-at errors. The stuck-at errors can be efficiently managed by using side information about stuck-at memory cells during encoding, while encoding for unconstrained number of stuck-at errors is intractable due to its exponential complexity. The proposed coding scheme employs an iterative encoding algorithm...
Sparse measurement structures - in which each measurement only depends on a small number of the inputs-arise in models of many problems such as sensor networks, group testing and even lossless data compression. The most important question in these applications is `How many measurements are sufficient to reconstruct the input ?'. Regular structures, where each input is measured the same number of times,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.