Owing to the booming development of the WWW, it creates many new challenges for information filtering. Information Filtering (IF) is an area of research that develops tools for discriminating between relevant and irrelevant information. IF can find good matches between the web pages and the users' information needs. Users first give descriptions about what they need, i.e., user profiles, to start the services. A profile index is built on these profiles. A series of incoming web pages will be put into the matching process. Each incoming web page is represented in the same form of the user profile. In this way, the users who are interested in an incoming web page can be identified by comparing the descriptions of the web page with each user profile. At last, the web page will be recommended to the users whose profiles belong to the filtered results. Therefore, a critical issue of the information filtering service is how to index the user profiles for an efficient matching process. When we index the user profile, we can reduce the costs of storage space and the processing time for modifying the user profiles. In this thesis, first, we propose a count-based tree method, which takes the count of each keyword into consideration, to reduce the large storage spaces as needed by the tree method. Next, three large-itemset-based methods are proposed to reduce the storage space, which are called the count-major large itemset method, the weighted large itemset method and the hybrid method. In these three large-itemset-based methods, we first cluster profiles with similar interests into the same group. Next, for each cluster, we apply the mining association rules techniques to help us to construct the index strategies. We design three methods by using the idea of the Apriori algorithm which is one of well-known approaches in mining association rules. But, we modify the minimum support and the goal in the Apriori algorithm. We may not always output the large itemset Lk. That is, we may only use Lw, where w < k. In summary, the cost of storage spaces of our four methods are less than that of the tree method proposed by Yan and Garcia-Molina. According to our simulation results, each of our four methods may provide the best result when different input data sets. Next, we propose a large-itemset-based approach to the incremental update of the index structure for storing keywords to reduce the update cost. When someone's interests are often changed, we must care about the way how to provide the low update cost of the index structure. We take the weight of each keyword into consideration. That is, each keyword can be distinguished the long-term interest which has weight above the threshold from the short-term interest which has weight below the threshold. Owing to that the probability of modifying the short-term interests is higher than that of modifying the long-term interests, we can update the short-term interests locally. According to our simulation results, our method really can reduce the update cost as needed by Wu and Chen' methods.

To reduce large motion responses of moored platforms in a harsh environment in deep waters, a thruster-assisted position mooring system can be applied. By applying the system, global dynamic responses can be improved in terms of the mooring line/riser top tensions, operational radii, and the top and bottom angle of the production risers. Kalman filtering as an optimum observer and estimator for stochastic disturbances is implemented in the developed control algorithm to filter out wave frequency responses. Investigation of the performance of thruster-assisted moored offshore platforms was conducted in terms of six-degree-of-freedom motions and mooring line/riser top tensions by means of a fully coupled hull/mooring/riser dynamic analysis program in the time domain and a spectral analysis. The two cases, motion analyses of a platform with thrusters and without thrusters, are extensively compared. The numerical examples illustrate that for deepwater position-keeping of platforms a thruster-assisted moored platform can be an effective solution compared to a conventionally moored platform.

Propulsion systems like Turboprop engines are generally designed to operate at a narrow range of optimum steady state performance conditions. However, these conditions are likely to vary in an unpredictable manner according to factors such as components aging, structural damages or even the operating environment. Over time, inefficiencies could add up and can lead to expensive fuel consumption or faster component aging. This thesis presents a self-optimizing control scheme, referred as Peak-seeking control, applied to propulsion systems similar to Turboprop engines. Using an extended Kalman filter, the Peak-seeking method is able drive the system to an optimal condition based only on measurements. No prior knowledge of the engine dynamics is required which make the Peak-seeking technique easy to implement and also allow for modularity in the engine design. This study is performed on both a turboprop and a DC motor driving a variable pitch propeller and considers several performance functions to optimize.

Thesis (M.S.)--California Polytechnic State University, 2009. / Mode of access: Internet. Title from PDF title page; viewed on Jan. 19, 2010. Major professor: John Saghri, Associate Professor. "Presented to the faculty of California Polytechnic State University, San Luis Obispo." "In partial fulfillment of the requirements for the degree [of] Master of Science in Electrical Engineering." "December 2009." Includes bibliographical references (p. 67-68).

Thesis--Auburn University, 2009. / Abstract. Vita. Includes bibliographic references.

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ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA / Network loads close to Ethernet wire speed and latency sensitive data in a Flight Test Instrumentation (FTI) system, represent challenging requirements for FTI network equipment. Loss of data due to network congestion, overflow on the end nodes, as well as packet latency above a few hundred microseconds, can be critical during a flight test. To avoid these problems, several advanced packet filtering and network optimization functions are required in order to achieve best possible performance and thus avoid loss of data. This paper gives insight into how to properly engineer an Ethernet based FTI network and how to use advanced Ethernet switch techniques such as Quality of Service (QoS) and rate shaping.

Smoothing and noise reduction of images is often an important first step in image processing applications. Simple image smoothing algorithms like the Gaussian filter have the unfortunate side effect of blurring the image which could obfuscate important information and have a negative impact on the following applications. The bilateral filter is a well-used non-linear smoothing algorithm that seeks to preserve edges and contours while removing noise. The bilateral filter comes at a heavy cost in computational speed, especially when used on larger images, since the algorithm does a greater amount of work for each pixel in the image than some simpler smoothing algorithms. In applications where timing is important, this may be enough to encourage certain developers to choose a simpler filter, at the cost of quality. However, the time cost of the bilateral filter can be greatly reduced through parallelization, as the work for each pixel can theoretically be done simultaneously. This work uses Nvidia’s Compute Unified Device Architecture (CUDA) to implement and evaluate some of the most common and effective methods for parallelizing the bilateral filter on a Graphics processing unit (GPU). This includes use of the constant and shared memories, and a technique called 1 x N tiling. These techniques are evaluated on newer hardware and the results are compared to a sequential version, and a naive parallel version not using advanced techniques. This report also intends to give a detailed and comprehensible explanation to these techniques in the hopes that the reader may be able to use the information put forth to implement them on their own. The greatest speedup is achieved in the initial parallelizing step, where the algorithm is simply converted to run in parallel on a GPU. Storing some data in the constant memory provides a slight but reliable speedup for a small amount of work. Additional time can be gained by using shared memory. However, memory transactions did not account for as much of the execution time as was expected, and therefore the memory optimizations only yielded small improvements. Test results showed 1 x N tiling to be mostly non-beneficial for the hardware that was used in this work, but there might have been problems with the implementation.

The kingdom Fungi is taxonomically and ecologically diverse, containing an estimated 1.5 million species. Fungi include decomposers, pathogens, and plant and animal mutualists. Many fungi are microorganisms, and the processes shaping microbial diversity may be fundamentally different from those that shape plants and animals. However, ecologists do not yet fully understand how fungal species are distributed over space and time. Using fungi that inhabit the water of Sarracenia carnivorous pitchers, I describe inter and intraspecific fungal diversity and investigate the processes that shape fungal diversity. I introduce these concepts in Chapter 1. In Chapter 2, I describe changes in fungal species diversity over space and time. I enumerated fungal species in five Sarracenia populations across the United States and Canada, and show that thousands, but not hundreds of kilometers separate distinct fungal communities. I also sampled a single Sarracenia population over a Sarracenia growing season, and found that young fungal communities are significantly different from older fungal communities. Observed patterns correlate with environmental factors including temperature and pitcher pH, and with the presence or population structure of pitcher inhabiting arthropods. In Chapter 3, I describe dispersal of and competition among three common pitcher fungi. I tracked Candida glaebosa, Rhodotorula glutinis, and Pseudozyma aphidis appearances in pitchers in a single Sarracenia population, and show that different appearances reflect different dispersal times. I also describe interactions between dispersal and competition in microcosms: high numbers of propagules introduced into a microcosm give a competitive advantage to investigated fungi. In Chapter 4, I describe changes in genotype composition of a population of Candida glaebosa, which is widespread and abundant in pitchers, and disperses early in the season. I observed three C. glaebosa populations in five locations; C. glaebosa population structure does not reflect broader community structure as described in Chapter 2. Population structure instead correlates with host taxonomy, and I contrast inter and intraspecific diversity patterns and the processes that potentially cause such patterns.