Power constrained test scheduling using power profile manipulation

This paper presents a novel power profile manipulation technique which reduces the testing time of the recently proposed power constrained test scheduling algorithms. The power profile manipulation technique consists of reordering and rotating test sequences and a new power approximation model. It is shown when the proposed power profile manipulation is integrated in power conscious test scheduling, savings up to 25% in testing time are achieved using benchmark circuits synthesized in AMS 0.35µm technology

Designing Coalition-Proof Reverse Auctions over Continuous Goods

This paper investigates reverse auctions that involve continuous values of different types of goods, general nonconvex constraints, and second stage costs. We seek to design the payment rules and conditions under which coalitions of participants cannot influence the auction outcome in order to obtain higher collective utility. Under the incentive-compatible Vickrey-Clarke-Groves mechanism, we show that coalition-proof outcomes are achieved if the submitted bids are convex and the constraint sets are of a polymatroid-type. These conditions, however, do not capture the complexity of the general class of reverse auctions under consideration. By relaxing the property of incentive-compatibility, we investigate further payment rules that are coalition-proof without any extra conditions on the submitted bids and the constraint sets. Since calculating the payments directly for these mechanisms is computationally difficult for auctions involving many participants, we present two computationally efficient methods. Our results are verified with several case studies based on electricity market data

Flight experience with advanced controls and displays during piloted curved decelerating approaches in a powered-lift STOL aircraft

The control, display, and procedural features are described for a flight experiment conducted to assess the feasibility of piloted STOL approaches along predefined, steep, curved, and decelerating approach profiles. It was found to be particularly important to assist the pilot through use of the flight director computing capability with the lower frequency control-related tasks, such as those associated with monitoring and adjusting configuration trim as influenced by atmospheric effects, and preventing the system from exceeding powerplant and SAS authority limitations. Many of the technical and pilot related issues identified in the course of this flight investigation are representative of similarly demanding operational tasks that are thought to be possible only through the use of sophisticated control and display systems

Genetic algorithms for scheduling generation and maintenance in power systems

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A Survey of Prediction and Classification Techniques in Multicore Processor Systems

In multicore processor systems, being able to accurately predict the future provides new optimization opportunities, which otherwise could not be exploited. For example, an oracle able to predict a certain application\u27s behavior running on a smart phone could direct the power manager to switch to appropriate dynamic voltage and frequency scaling modes that would guarantee minimum levels of desired performance while saving energy consumption and thereby prolonging battery life. Using predictions enables systems to become proactive rather than continue to operate in a reactive manner. This prediction-based proactive approach has become increasingly popular in the design and optimization of integrated circuits and of multicore processor systems. Prediction transforms from simple forecasting to sophisticated machine learning based prediction and classification that learns from existing data, employs data mining, and predicts future behavior. This can be exploited by novel optimization techniques that can span across all layers of the computing stack. In this survey paper, we present a discussion of the most popular techniques on prediction and classification in the general context of computing systems with emphasis on multicore processors. The paper is far from comprehensive, but, it will help the reader interested in employing prediction in optimization of multicore processor systems