The identification of the physical parameters (mass, stiffness, and damping) of structural, mechanical, and biomechanical systems is a major challenge in many applications, especially when dealing with old systems and biological systems with heavy damping and where environmental noises are presented. This work presents a novel methodology called eigenvector phase correction (EVPHC) to solve for the physical parameters of structural and biomechanical systems even with the existence of a significant amount of noise. The method was first tested on structural/mechanical systems and showed superior results when compared with an iterative method from the literature. EVPHC was then developed and used to identify the physical parameters of supine humans under vertical whole-body vibration. Modal parameters of fifteen human subjects, in the supine position, were first identified in this work using experimentation under vertical whole-body vibration. EVPHC was then used to solve an inverse modal problem for the identification of the stiffness and damping parameters at the cervical and lumbar areas of supine humans. The results showed that the resulting physical parameters were realistically close to those presented in the literature. The proposed human model was able to predict the time histories of the acceleration at the head, chest, pelvis, and legs very closely to those of the experimental measured values. A scaling methodology is also presented in this work, where an average human model was scaled to an individual subject using the body mass properties.

Three experiments investigated the ability and means by which Florida manatees determine sound source directionality. An eight-choice discrimination paradigm determined the sound localization abilities of two manatees within a 360° array of speakers. Five conditions were tested including a 3,000 and 200 ms, 95 dB, 0.2-24 kHz signal, a 3,000 ms, 80 dB, 18-24 kHz signal, a 3000 ms, 110 dB, 0.2-1.5 kHz signal and a 200 ms, 101 dB, 4 kHz tonal signal. A sixth condition attenuated the level of the 3,000 ms, 95 dB, 0.2-24 kHz signal in 3 dB increments until accuracy reached 75%. Subjects performed above the 12.5% chance level for all broadband frequencies and were able to localize over a large level range. Errors were typically located to either side of the signal source location when presented in the front 180° but were more dispersed when presented from the 135°, 180° and 225° locations. Front-to-back confusions were few and accuracy was greater when signals originated from the front 180°. Head/body related transfer functions determined how different frequencies were filtered by the manatees' head/torso to create frequency-specific interaural level differences (ILDs). Hydrophones were suspended next to each manatee ear and Fast Fourier transform (FFT) ratios compared received signals with and without the subject's presence. ILD magnitudes were derived for all frequencies, as well as specific 0.2-1.5, 0.2-5, and 18-30 kHz bands of frequencies. ILDs were found for all frequencies as a function of source location, although they were largest with frequencies above 18 kHz and when signals originated at 90° and 270°. Larger ILDs were found when the signals originated behind the subjects as compared to in front of them. Auditory evoked potential (AEP) techniques were used to map manatee sound conduction pathways in-water and in-air using 15 and 24 kHz carriers. All subjects produced AEPs at each position the transducer was placed, however specific sound conduction pathway(s) were not identified. AEP amplitudes were usually greater with the 24 kHz carrier, however patterns between carriers at identical body positions were highly variable between subjects.

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This thesis investigates the design and the analysis of acoustic signal processing algorithms in reverberant rooms. Reverberation poses a major challenge to acoustic signal processing problems. It degrades speech intelligibility and causes many acoustic algorithms that process sound to perform poorly. Current solutions to the reverberation problem frequently only work in lightly reverberant environments. There is need to improve the reverberant performance of acoustic algorithms.¶ The approach of this thesis is to explore how the intrinsic properties of reverberation can be exploited to improve acoustic signal processing algorithms. A general approach to soundfield modelling using statistical room acoustics is applied to analyze the reverberant performance of several acoustic algorithms. A model of the underlying structure of reverberation is incorporated to create a new method of soundfield reproduction.¶ Several outcomes resulting from this approach are: (i) a study of how more sound capture with directional microphones and beamformers can improve the robustness of acoustic equalization, (ii) an assessment of the extent to which source tracking can improve accuracy of source localization, (iii) a new method of soundfield reproduction for reverberant rooms, based upon a parametrization of the acoustic transfer function and (iv) a study of beamforming to directional sources, specifically exploiting the directionality of human speech.¶ The approach to soundfield modelling has permitted a study of algorithm performance on important parameters of the room acoustics and the algorithm design. The performance of acoustic equalization and source tracking have been found to depend not only on the levels of reverberation but also on the correlation of pressure between points in reverberant soundfields. This correlation can be increased by sound capture with directional capture devices. Work on soundfield reproduction has shown that, though reverberation significantly degrades the performance of conventional techniques, by accounting for the reverberation it is possible to design reproduction methods that function well in reverberant environments.

本文主要是利用時間數列中的轉換函數模式對國內的成交量與成交價、美國道瓊工業平均指數與台灣發行量加權股價指數及NASDAQ 指數與台灣電子類股進行研究與預測，除了找出適當的預測模式外，同時可以看出世界的經貿大國－美國對台灣所造成的影響，也可以針對"量是否先價而行"的說法加以應証。 在研究期間裡，分析的結果顯示大盤的成交量平均領先成交價兩期，電子類股與熱門股則呈現價量同期的現象，而美國股價與NASDAQ股價分別平均領先台灣股價與電子類股一期，除了從大盤的資料來分析外，也可經由重要的類股來分析股價可能的走勢，另外短期預測也有不錯的結果，這說明了美國仍 然具有其影響力，也同時應証了"量是價的先行指標"的說法，另外此三種現象，都可做為預測台灣股價指數的參考指標。 / The article utilizes the transfer function model in time series to make prediction on closing volume with closing value of the stock market, the American Dow Jones average index with the index of Taiwan stock market index, NASDAQ index with Taiwan electronic stock. In additional to discovering the appropriate prediction model, we can simultaneously see the influence of America with great economic power on Taiwan and how the concept that the volume determines the value is verified. During the process of this research, the outcome of the analysis indicates the closing volume is two times ahead of the closing value while the volume and value of the electronic and glamour stocks are changing in the same time and the American stock value and NASDAQ index are one time ahead of Taiwan electronic stock value. Besides the analysis based on the whole data, we can predict the possible futuristic stock trend. On the other hand, we can get pretty good result based on this theory, which accounts for the fact that America has some influence on Taiwan stock market and verifies the concept that the volume determines the value.. In addition, these three phenomenon can serve as the references for the prediction on the Taiwan stock index.

經由研究一個輸入序列的轉換模式來關注結構性變化之偵測與處理。 / Time series data are often subject to uncontrolled or unexpected interventions, from which various types of outlying observations or structure changes are produced. In this article, we focus on detecting and treating structure change events in multiple time series by studying transfer function models with one input series. Monte Carlo simulations will be used to study the performance of the proposed procedures.

<p>Volume rendering (VRT) has been used with great success in studies of patients using computed tomography (CT), much because of the possibility of standardizing the rendering protocols. When using magnetic resonance imaging (MRI), this procedure is considerably more difficult, since the signal from a given tissue can vary dramatically, even for the same patient. This thesis work focuses on how to improve the presentation of MRI data by using VRT protocols including standardized transfer functions. The study is limited to exclusively examining data from patients with suspected renal artery stenosis. A total number of 11 patients are examined.</p><p>A statistical approach is used to standardize the volume rendering protocols. The histogram of the image volume is modeled as the sum of two gamma distributions, corresponding to vessel and background voxels. Parameters describing the gamma distributions are estimated with a Maximum-likelihood technique, so that expectation (E1 and E2) and standard deviation of the two voxel distributions can be calculated from the histogram. These values are used to generate the transfer function.</p><p>Different combinations of the values from the expectation and standard deviation were studied in a material of 11 MR angiography datasets, and the visual result was graded by a radiologist. By comparing the grades, it turned out that using only the expectation of the background distribution (E1) and vessel distribution (E2) gave the best result. The opacity is then defined with a value of 0 up to a signal threshold of E1, then increasing linearly up to 50 % at a second threshold E2, and after that a constant opacity of 50 %. The brightness curve follows the opacity curve to E2, after which it continues to increase linearly up to 100%.</p><p>A graphical user interface was created to facilitate the user-control of the volumes and transfer functions. The result from the statistical calculations is displayed in the interface and is used to view and manipulate the transfer function directly in the volume histogram.</p><p>A transfer function generated with the Maximum-likelihood VRT method (ML-VRT) gave a better visual result in 10 of the 11 cases than when using a transfer function not adapting to signal intensity variations.</p>

In the current study, sub-fossil Cladocera collected from the surface sediment of 44 shallow lakes spanning over five latitudes from north to south of Turkey using snap-shot methodology revealed strong impact of salinity on cladoceran community structure. To see the whole picture, sediment cores collected from six of the lakes and long-term monitoring data from two of the lakes were also investigated. Contemporary cladocerans and sub-fossil assemblages were compared to reveal that their responses to salinity changes were highly similar. This lead us to use sub-fossil cladocerans and salinity data from water column together while generating the calibration data set using ordination techniques. Salinity transfer function models were developed utilising weighted averaging techniques. The developed salinity transfer function was applied to cladocera assemblages from dated sediment cores. Hindcasting of the salinity inference model was performed using monitoring data and the reconstructed salinities from two central Anatolian lakes and reflected good linear correlation with the known lake salinity history. This thesis has confirmed that sub-fossil Cladocera is a valuable indicator of historical salinity change and marker for the monitoring of lakes. For the first time, the lake environmental variables and sub-fossil cladoceran species composition from the surface sediments of Turkish shallow lakes were studied and a salinity transfer function was developed to elucidate past salinity change. The approach of the current study has been proven to be reliable while interpreting past salinity conditions. Since monitoring programmes are scarce in Turkey, paleolimnological analyses would be beneficial especially when defining effective restoration strategies.

In optical imaging system, misfocus occurs because of a nonaccuate focal length. In recent years, the improvement for misfocus problem has caught much attention in researches. This thesis is aimed to explore the misfocus improvement and analysis. Lens plays an important role in optical image system. It can focus light at one point. The distance between the focal point and the lens is called focal length. Focal length is determined by the object distance and the image distance. As light is focused farther out of the focal point, the image will blur. It is called misfocus. The general method to improve misfocus image is done by post-processing. In 1995, wave-front coding was first proposed by Dowski and Cathey. They placed the phase mask in front of the lens, and then emphasized on the processing. In recent years, more and more researches work on this field. In this thesis, a one ring phase mask is designed by modulating the phase difference in the ring to make the improvement better. Research before wave-front coding in order to achieve a closed optical transfer function for different degrees of misfocus, but we hope the phase mask can provide immediate improvement. This idea can be applied to real-time video monitoring.