Social and Behavioral Sciences Commons^™

Manifold Learning Based Spectral Unmixing Of Hyperspectral Remote Sensing Data, Jun-Hwa Chi

Open Access Dissertations

Nonlinear mixing effects inherent in hyperspectral data are not properly represented in linear spectral unmixing models. Although direct nonlinear unmixing models provide capability to capture nonlinear phenomena, they are difficult to formulate and the results are not always generalizable. Manifold learning based spectral unmixing accommodates nonlinearity in the data in the feature extraction stage followed by linear mixing, thereby incorporating some characteristics of nonlinearity while retaining advantages of linear unmixing approaches. Since endmember selection is critical to successful spectral unmixing, it is important to select proper endmembers from the manifold space. However, excessive computational burden hinders development of manifolds for …

Adaptive Targeting: Engaging Farmers To Assess Perceptions And Improve Watershed Modeling, Optimization, And Adoption Of Agricultural Conservation Practices, Margaret Mccahon Kalcic

Open Access Dissertations

Targeting agricultural conservation practices to farmland that has the greatest impact on surface water quality has received wide support from scientists and watershed managers. The targeting approach has, however, been politically contentious as many believe farmers will oppose the approach on grounds such as privacy invasion and unfair distribution of government incentives. Targeting conservation practices using complex optimization models has become common in the scientific community, and yet targeted results are underutilized in practice because of difficulties such as knowledge transfer and absence of a political framework for their use. For targeting to be successful, it must be politically supported …

Mispronunciation Detection For Language Learning And Speech Recognition Adaptation, Zhenhao Ge

Open Access Dissertations

The areas of "mispronunciation detection" (or "accent detection" more specifically) within the speech recognition community are receiving increased attention now. Two application areas, namely language learning and speech recognition adaptation, are largely driving this research interest and are the focal points of this work.

There are a number of Computer Aided Language Learning (CALL) systems with Computer Aided Pronunciation Training (CAPT) techniques that have been developed. In this thesis, a new HMM-based text-dependent mispronunciation system is introduced using text Adaptive Frequency Cepstral Coefficients (AFCCs). It is shown that this system outperforms the conventional HMM method based on Mel Frequency Cepstral …

Design, Development, And Testing Of A Conformal Power Control Interface For Thrust Vectoring Aircraft, David Rozovski

Open Access Dissertations

Over the last five years, a new power control inceptor for tiltrotor aircraft, known as the Rotational Throttle Interface (RTI) was designed and built. Prior to the RTI, no tiltrotor inceptor had been able to simultaneously indicate both the direction and magnitude of thrust conformally. The purpose of the RTI is to provide an interface that maps to the intended vehicle response throughout ALL ranges of operation. Doing so is expected to reduce confusion that may have contributed to several tiltrotor accidents

Two tests were conducted with the RTI, one at the NASA Vertical Motion Simulator, and one at Canada's …

Simulating Land Use Land Cover Change Using Data Mining And Machine Learning Algorithms, Amin Tayyebi

Open Access Dissertations

The objectives of this dissertation are to: (1) review the breadth and depth of land use land cover (LUCC) issues that are being addressed by the land change science community by discussing how an existing model, Purdue's Land Transformation Model (LTM), has been used to better understand these very important issues; (2) summarize the current state-of-the-art in LUCC modeling in an attempt to provide a context for the advances in LUCC modeling presented here; (3) use a variety of statistical, data mining and machine learning algorithms to model single LUCC transitions in diverse regions of the world (e.g. United States …