http://hdl.handle.net/1957/8163 Search the Channel search http://ir.library.oregonstate.edu/jspui/simple-search http://hdl.handle.net/1957/13071 Title: Design techniques for high efficiency LED drivers<br/><br/>Authors: Bang, Sarvesh Jagdish<br/><br/>Abstract: The increasing popularity of cellular phones with integrated cameras in therecent past has led to major improvements in its image quality. However, integration of new features, such as mobile email, video streaming, MP3 etc. tend to put the limitation on image quality as camera phone designers struggle to manage multiple features while maintaining healthy battery life time.In this research, a novel efficient power management scheme for cameraphones with flash for better image/video quality is discussed. A prototype power management circuit comprising of a 2 MHz Buck-and-Boost DC-DC converter driving up to 1.2A flash light emitting diode (LED) in 500nm CMOS process is implemented. The converter achieves high efficiency over the entire Li-On battery voltage range of 3.0V to 5.2V by operating in buck, buck-and-boost and boost mode based on the input/output voltage and load current requirements. The proposed pulse width modulator (PWM) controller operates continuously over the entire Li-On battery range while providing constant LED current. The converter shows peak efficiencies of 87% and 83% for LED current of 0.6A and 1.2A, respectively.<br/><br/>Description: Graduation date: 2010 Sun, 04 Oct 2009 22:58:59 GMT http://hdl.handle.net/1957/12844 Title: Directional 60 GHz communication networks<br/><br/>Authors: Yildirim, Ferhat (Ahmet Ferhat)<br/><br/>Abstract: It is well known that multipath effects cause inter-symbol interference (ISI) for high-speed signaling and ultimately limit the achievable data rate at any frequency band. In this thesis, we study several different methods to tackle this issue and provide solutions for establishing efficient wireless links that can provide several Gbps data rate. Specifically, we show that proper choice of polarization, when used with the proposed topology detection algorithm reduces the multipath in 60 GHz wireless channel and increases the error-performance of the network. We also develop a direction-detection algorithm for directional communications in 60 GHz, which is proven to be effective in reducing multipath and increasing spatial diversity. Finally, we propose a double directional channel model for 60 GHz channel as a modification to IEEE 802.15.3c channel model to include the effects of directional antennas both on the transmitter and the receiver side.<br/><br/>Description: Graduation date: 2010 Tue, 22 Sep 2009 22:58:59 GMT http://hdl.handle.net/1957/12873 Title: A high power emulation of a wind farm<br/><br/>Authors: Lalla, Chelsea<br/><br/>Abstract: As more wind farms are connected to the grid, the variable nature of wind energy begins to influence grid stability. Energy storage could help smooth the variable nature of wind energy. Laboratory demonstration and exploration of the interaction between different energy storage devices and wind energy could help improve and encourage wind energy integration. To this end, a wind energy and energy storage project will be implemented in WESRF?s lab comprising of a zinc bromine battery, supercaps, hydropower, and wind energy. In this thesis, a scale model of the wind farm component of the project is modeled and experimentally tested. The wind farm is physically modeled by a 120kVA three-phase controllable voltage source and controlled in the synchronous reference frame.<br/><br/>Description: Graduation date: 2010 Thu, 17 Sep 2009 22:58:59 GMT http://hdl.handle.net/1957/12549 Title: Applying machine learning for prediction, recommendation, and integration<br/><br/>Authors: Bao, Xinlong<br/><br/>Abstract: This dissertation explores the idea of applying machine learning technologies to help computer users find information and better organize electronic resources, by presenting the research work conducted in the following three applications: FolderPredictor, Stacking Recommendation Engines, and Integrating Learning and Reasoning.FolderPredictor is an intelligent desktop software tool that helps the user quickly locate files on the computer. It predicts the file folder that the user will access next by applying machine learning algorithms to the user's file access history. The predicted folders are presented in existing Windows GUIs, so that the user's cost for learning new interactions is minimized. Multiple prediction algorithms are introduced and their performance is examined in two user studies.Recommender systems are one of the most popular means of assisting internet users in finding useful online information. The second part of this dissertation presents a novel way of building hybrid recommender systems by applying the idea of Stacking from ensemble learning. Properties of the input users/items, called runtime metrics, are employed as additional meta features to improve performance. The resulting system, called STREAM, outperforms each component engine and a static linear hybrid system in a movie recommendation problem.Many desktop assistant systems help users better organize their electronic resources by incorporating machine learning components (e.g., classifiers) to make intelligent predictions. The last part of this dissertation addresses the problem of how to improve the performance of these learning components, by integrating learning and reasoning through Markov logic. Through an inference engine called the PCE, multiple classifiers are integrated via a process called relational co-training that improves the performance of each classifier based on information propagated from other classifiers.<br/><br/>Description: Graduation date: 2010 Sun, 23 Aug 2009 22:58:59 GMT