Individuals with limited motor control are often unable to interact with their environment. Recently, near-infrared spectroscopy (NIRS) systems have been investigated as potential brain-computer interfaces (BCI). Previous studies examined data offline, preventing users from understanding how their thoughts triggered the NIRS system. This thesis focused on understanding the short-term effects of feedback on user’s ability to learn how to control BCIs. Data were collected from control and experimental groups over seven sessions, as they performed fast singing imagery or mental arithmetic. Significant differences were observed between the control group’s results in non-feedback sessions and the experimental group’s results in feedback sessions. Qualitative results from 3 of the 10 participants suggested they had control of the feedback system. They performed the task with online accuracies of 61% - 88% in the final 2 sessions with feedback. These results suggest that continued investigation of NIRS feedback systems is warranted.

As variation in pork tenderness has increased, identification of tenderness has become an industry need. This study consisted of 1208 pork loins randomly selected to test the efficacy of four automated grading techniques. Visible and near-infrared spectroscopy (VVNIR) (350-1830 nm wavelengths), bioelectrical impedance (EI) (resistance, reactance, phase angle, and partial capacitance), pH, and CIE L*, a* and b* color space values were used to predict chemical moisture and lipid, pH, Warner-Bratzler shear force (WBSF), and Slice shear force (SSF) on 13 d aged pork loins. The means and standard deviations for WBSF were (22.95 and 5.16) and SSF were (165.49 and 58.15). Prediction was based on stepwise linear regression and partial least squares regression. VNIR, pH, and color, when in combination, had the highest R^2 (0.19 and 0.21) for the prediction of WBSF and SSF, respectively. Partial least squares regression (PLSR) was used to remove autocorrelation between VNIR values. By using PLSR, with an R ^2 value of 0.49, 100 percent of the "tender" chops were correctly classified, 93 percent of the "intermediate" chops were correctly classified, and 92 percent of the "tough" chops were correctly classified into its category for WBSF. However, SSF was much lower (R^2 = 0.24) with only correctly placing 62 percent of the "tender" chops and only 48 percent of the "intermediate" and "tough" chops. Electrical impedance, alone or in combination with other technologies, either did not improve predictability of linear regression equations (increase R^2) or of PLSR models (increase R^2). Equations and models that included EI values had low R^2. When adding EI to the regression equation involving all variables, R^2 increased slightly from 0.19 to 0.21 in predicting WBSF, and from 0.21 to 0.25 for SSF. When pH or CIE L* color space values were included in linear regression or PLSR models to predict WBSF and SSF, R^2 values increased from 0.14 to 0.19 for WBSF, and 0.14 to 0.21 for SSF. pH played a large role in predicting WBSF and SSF, along with CIE L*. Thus, for an on-line situation, use of VNIR, pH, and color could be used to predict tenderness. Utilization of VNIR alone could be effective in predicting pork tenderness (WBSF). Using EI alone, or in combination with VNIR, would not provide acceptable prediction of WBSF or SSF. Use of VNIR with pH and color would improve the ability to predict tender and intermediate pork WBSF and SSF, but the additional improvement in accuracy may not be warranted based on the cost and additional time needed when using more than one technology.

Thesis (M.S.)--University of Hawaii at Manoa, 2005. / Includes bibliographical references (leaves 48-50). Also available via World Wide Web.

Thesis (Ph.D.) -- University of Texas at Arlington, 2007.

No description available.

The application of visible/near-infrared hyper-spectral analysis to monitor the quality of frying oil and fried breaded chicken nuggets was investigated. / Partial least squares (PLS) calibration models were developed to predict the acid value, total polar components and viscosity of heated oils with different ratios of hydrogenation. Coefficient of determination (R2) and root mean square error (RMSE) were calculated to assess the performance of each model. Results of the study demonstrated good prediction ability of the calibration models for the quality parameters with R2 values of over 0.92. / The second study was based on developing calibration models for prediction of moisture and fat contents of fried breaded chicken nuggets with different levels of moisture and fat contents. Performing the same procedure for evaluation of the PLS calibration models, results of the study demonstrated that moisture and fat contents of fried breaded chicken nuggets could be predicted with R2 values of 0.92.

Both behavioral and neurophysiological data indicate that many factors contribute to how infants tune to their native language(s) in early infancy. However, substantial debate remains regarding the neural mechanisms that underlie this tuning process. This study was designed to determine whether the behavioral changes in infants' processing of native and non-native speech during the second half of the first year correspond to qualitative neural processing changes that can be measured using near-infrared spectroscopy (NIRS). Specifically, we used NIRS to examine changes in hemodynamic activity in monolingually-exposed infants between the ages of 3 and 14 months while they were exposed to native (English) and non-native (Spanish) speech. In all infants, measurements were taken from the bilateral temporal regions of the cerebral cortex. Three age groups were tested: pre-tuned infants, who should show no sensitivity to phonological differences between the native and non-native speech samples (3-to-6-month-olds), actively tuning infants, who should be beginning to differentiate between the phonology of the native and non-native speech samples (7-to-10-month-olds), and tuned infants, who should readily distinguish between the phonologies of the native and non-native speech samples (11-to-14-month-olds). Results demonstrated significant differences in hemodynamic activity during the processing of native speech compared to non-native speech in each of the three age groups, with qualitatively different patterns of hemispheric lateralization emerging in response to the two types of speech in each of the three groups. These findings point to a potential neural marker of infants' sensitivity to the phonology of their native language as it emerges with increasing age that will be useful in future research.

Gamification is an emerging phenomenon that has been advocated for its potential to improve organisational outcomes. The present study aimed to examine the effect of gamification in a perceptual diagnosis task. Forty participants completed a 22-minute visual search task. To investigate the role of game mechanics participants were divided into four conditions resulting from the factorial combination of the narrative mechanic (narrative and control condition) and the points mechanic (Points and no-points control condition). Attention effort, motivation, and work engagement were measured through performance metrics, functional near-infrared spectroscopy (fNIRS), and self-report questionnaires. The results revealed points significantly increased task performance while narrative significantly increased intrinsic motivation and prefrontal oxygenation. These findings may provide much needed contributions to the literature surrounding gamification. It was also revealed that fNIRS measures of frontal activation may be a reasonable objective indicator of initial cognitive effort. This presents significant real world applications for objectively measuring motivation.

The agriculture industry experiences severe economic losses each year when wheat crops become infected with Fusarium and the mycotoxin Deoxynivalenol (DON). This research investigated the feasibility of using near infrared hyperspectral imaging to detect Fusarium damage and DON in Canadian Western Red Spring wheat. Four samples were selected from each grain grade resulting in 16 samples and 240 hyperspectral data cubes. The data cubes were calibrated to the system, the consistent spectra was found and then a 1- nearest neighbour classifier was generated. Grade percentages were computed and used to generate two 3- nearest neighbour classifiers, one for identifying Fusarium damage and the other for identifying DON content. The Fusarium damage classifier had an accuracy of 85% and the DON content classifier had an accuracy of 80%. While a single sample image classification will not replace manual testing, the use of multiple samples from one harvest could reduce manual inspections.

The application of hyperspectral imaging technique in the wavelength range of 400-1000 nm to estimate some of the maturity parameters of mangoes was investigated. Mangoes with different quality levels were grouped using principle component analysis (PCA). Feature wavelengths were identified to predict total soluble solids content, water content and firmness using simple correlation, first derivative, partial least square (PLS) regression analysis and measured values. Calibration models were developed using the selected wavelengths from correlation coefficients, first derivative, partial least square (PLS) regression analysis and corresponding maturity parameters employing artificial neural network model to predict total soluble solids content, water content and firmness of the fruit. Performance of the models was compared using the correlation coefficient (r) values. Fruit firmness was predicted with high correlation coefficient (r=0.88) followed by water content (r=0.81) and total soluble solids (r=0.78) using wavelengths selected from simple correlation of first derivative data with the parameters and ANN model. The results of the study demonstrated the scope for further research on maturity and quality evaluation of fruits using hyperspectral imaging technique.