In many applications, e.g. urban traffic monitoring, stock trading, and industrial sensor data monitoring, clustering algorithms are applied on data streams in real-time to find current patterns. Here, sliding windows are commonly used as they capture concept drift. Real-time clustering over sliding windows is early detection of continuously evolving clusters as soon as they occur in the stream, which requires efficient maintenance of cluster memberships that change as windows slide. Data stream management systems (DSMSs) provide high-level query languages for searching and analyzing streaming data. In this thesis we extend a DSMS with a real-time data stream clustering framework called Generic 2-phase Continuous Summarization framework (G2CS).  G2CS modularizes data stream clustering by taking as input clustering algorithms which are expressed in terms of a number of functions and indexing structures. G2CS supports real-time clustering by efficient window sliding mechanism and algorithm transparent indexing. A particular challenge for real-time detection of a high number of rapidly evolving clusters is efficiency of window slides for clustering algorithms where deletion of expired data is not supported, e.g. BIRCH. To that end, G2CS includes a novel window maintenance mechanism called Sliding Binary Merge (SBM). To further improve real-time sliding performance, G2CS uses generation-based multi-dimensional indexing where indexing structures suitable for the clustering algorithms can be plugged-in.

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Precision surface finishes are used in a wide variety of applications. From bearing races and rolling elements to parallel slide ways, the frictional characteristics of these surfaces are critical to the performance of the products. Experimental trial and error has shown that certain surfaces outperform others in certain applications, but the specific surface characteristics that make this true have yet to be fully understood. The research goal was to develop an apparatus that can test the coefficient of rolling/sliding friction of different precision machined surfaces and to combine this data with topographic analysis of the surfaces to correlate specific 3-D parameters with the frictional performance of a surface. The sample treatments consisted of four different surface textures (hard-turned, ground, honed and isotropic finish) and four different relative surface speeds. By monitoring the torque in the sample-mounting shaft under lubricated conditions the coefficient of rolling/sliding friction of each surface was found. Utilizing white light interferometry measurement of the surfaces, a highly detailed map of each surface was obtained. Using different characteristic values of each machined surface (RMS roughness, asperity density, lay direction, etc.), the frictional behavior of the surfaces were compared to the surface characteristics yielding insight into the relationship between surface finish and friction in rolling/sliding contact. Friction coefficient was found to correlate most strongly with RMS roughness (Sq) and density of surface summits (Sds). These parameters govern mechanical interference of asperities and surface adhesion respectively. These findings suggest that friction coefficients of surfaces could be optimized through manipulation of three-dimensional surface parameters.

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No description available.

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaves 76-77).

Dissertation (Ph. D. in Mechanical Engineering) Naval Postgraduate School, September 1996. / Dissertation supervisor(s): Anthony Healey. "September 1996." Includes bibliographical references (p. 341-345). Also available online.

No description available.

We study the computational complexity of collecting items inside a grid map with obstacles, using an agent that always slides to the maximal extend, until it is stopped by an obstacle. An agent could be, for example, a robot or a vehicle, while obstacles could be walls or other immovable objects, and items could be packages that need to be picked up. This problem has very natural applications in robotics. The restricted type of motion of the agent naturally models movement on a frictionless surface, and movement of a robot with limited sensing capabilities and thus limited localization. For example, if a robot cannot determine the distance traveled once it starts moving, then it makes sense to keep moving until an obstacle is reached, even if the robot has a map of the environment. With today’s technology it is possible to create sophisticated robots but, since the complexity and the costs of such robots are high, it is sometimes better to use simple inexpensive robots that can still solve relatively complex tasks. In fact, simple robots are quite common and usually built using simple sensors that have limited capabilities, but that are easy to use and are considerably cheaper than more sophisticated ones. The computational complexity of numerous problems with movable objects has been extensively studied before. However, only a few of them have maximal sliding agents, and they usually do not have the goal of collecting items. We show that the problem of deciding if all the items can be collected by a maximal sliding agent can be solved efficiently when the agent is the only moving object in the map. However, we show that optimization problems such as determining the minimum number of moves required to collect all the items, and also variants in more complex environments are computationally intractable. Hence, for those problems it is better to focus on using heuristics than on finding optimal solutions.

The development, implementation, and testing of a leader-follower based robust nonlinear formation controller is discussed in this thesis. This controller uses sliding mode control on the length and angle between the leader and follower vessels to produce the desired formation. A boat model, assuming planar motion (three degrees of freedom), is used as the bases for the controller. Open loop testing is performed to determine parameter values to match the simulation model to the physical one and, upon tuning of the controller to match, closed loop testing of the controller with a virtual leader is also performed. From these tests it is found that the controller is unstable, thus improvements to the controller, through changes made to the model and to the parameter identification process, are undertaken. Simulations comparing the initial and updated models of the vehicle to open loop data show an improvement in the new model.