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Fast optical signal detected in the prefrontal lobe with near-infrared spectroscopy during sleepZhao, Jun, January 2005 (has links)
Thesis (M.S.)--University of Missouri-Columbia, 2005. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (January 11, 2007) Includes bibliographical references.
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The near-infrared properties of compact binary systems /Froning, Cynthia Suzanne, January 1999 (has links)
Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 178-184). Available also in a digital version from Dissertation Abstracts.
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An investigation into the introduction of process analytical technology, using near infrared analysis, to selected pharmaceutical processesNaicker, Krishnaveni January 2007 (has links)
Introduction: Process analytical technologies are systems for the analysis and control of manufacturing processes to assure acceptable end-product quality. This is achieved by timely measurements of critical parameters and performance attributes of raw material and in-process material and processes. The introduction of process analytical technology using near infrared analysis was investigated in three areas, namely incoming raw material analysis, blend uniformity analysis and moisture determination in the fluid bed dryer. Methodology: Incoming raw material identification - The FOSS XDS rapid content analyzer was used for the development of a NIR method for the identification and material qualification of starch maize and lactose monohydrate. Blend uniformity analysis – The SP15 Laboratory Blender fitted with near infrared probe was utilized for the study. Two types of blend experiments were designed to monitor the distribution of magnesium stearate (lubricant) in the blend, namely, a powder blend utilizing lactose monohydrate and a granule blend utilizing Ridaq® granule. Software methods were developed to monitor the standard deviation of the absorbance at the wavelengths that were specific for lactose monohydrate, Ridaq® granule and magnesium stearate. To confirm the prediction of end-point using near infrared, results were verified using an atomic absorption method for magnesium stearate. The blends were sampled at the selected time intervals corresponding to three states of the blend, namely, before end-point, at end-point and after end-point using a sampling plan. An additional six blends were conducted for the granule blend and sampled when the standard deviation had reached a value below 3 x 10-6 at the magnesium stearate wavelength at four consecutive data points (standard deviation value extrapolated from blends carried out to predetermined time intervals). Moisture determination in the fluid bed dryer – Moisture values for two products (Product A and Product B) were retrospectively collected from past production batches. A process capability study was conducted on the moisture values to determine if the current process was in a state of control. Results and Discussion: Incoming raw material identification – The algorithms used for the spectral library were able to distinguish between the raw materials selected. The spectral library positively identified the starch maize and lactose monohydrate samples that were not present in the library. The negative challenge with pregelatinised starch and tablettose demonstrated that the spectral library was able to differentiate between closely related compounds. Blend uniformity analysis – Blends sampled at the predetermined time intervals demonstrated a homogeneous state when the standard deviation of the absorbance was low and a non-homogeneous state when the standard deviation of the absorbance was high, thus near infrared prediction on the state of the blend was confirmed by the standard analytical methods. The series of Ridaq® granule and magnesium stearate blends sampled when the standard deviation was below 3 x 10-6 were homogeneous with the exception of one blend that was marginally out of specification. Blend durations were significantly lower than the standard blend durations used in the facility and ranged from 112 to 198 seconds. Moisture determination in the fluid bed dryer – From the process capability study of the two products it was noted that Product A is stable but can still be optimized while Product B is at a desirable state. The statistical evaluation of the moisture values for Product A and Product B demonstrated that the use of the product temperature to monitor the moisture gave consistent results. The current process is stable and capable of producing repeatable results although near infrared provides a means for continuously monitoring the product moisture and allows one to take action to prevent over-drying or under-drying. Conclusion: From the investigations conducted, it can be seen that there is definitely a niche for process analytical technology at this pharmaceutical company. The implementation is a gradual process of change, which may take time, probably several years (Heinze & Hansen 2005).
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Rapid Non-Destructive Assessment of Southern Yellow Pine Lumber Properties by Near Infrared SpectroscopyDiaz, Ignacio 15 December 2012 (has links)
Over the last several years questions about the strength of structural lumber have been raised. The purpose of this study was to examine the relationship between physically measured wood properties using Near Infrared spectroscopy. Physical properties were determined from (2 x 4 x 2 in.) cut samples. Destructive mechanical testing was performed on 744; 8 feet long, No.2 grade 2x4’s. Diffuse reflectance NIR spectra was collected from the cross-sectional face of each block using FOSS NIR Systems Inc. Model 5000 scanning spectrometer. Calibrations were then created between measured properties and NIR estimates. Density, specific gravity, latewood percentage, MOE and MOR had coefficient of determinations of 0.78, 0.56, 0.02, 0.56, and 0.48 respectively. The low correlation is likely caused by the grade of lumber. Because No.2 lumber has considerable knots, they were the determining factor in strength and stiffness; these results would likely not be similar in a higher grade lumber.
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Visible and near-infrared spectroscopic analysis of potatoesSingh, Baljinder January 2005 (has links)
No description available.
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The validity and reliability of Near-infrared interactance in the measurement of body fatShek, Kwai-kuen, Leon., 石桂娟. January 2003 (has links)
published_or_final_version / Sports Science / Master / Master of Science in Sports Science
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Application of near infrared spectroscopy in meat quality assessment丁海標, Ding, Haibiao. January 1999 (has links)
published_or_final_version / Zoology / Doctoral / Doctor of Philosophy
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NEW BIOINFORMATIC TECHNIQUES FOR THE ANALYSIS OF LARGE DATASETSHarris, Justin Clay 01 January 2007 (has links)
A new era of chemical analysis is upon us. In the past, a small number of samples were selected from a population for use as a statistical representation of the entire population. More recently, advancements in data collection rate, computer memory, and processing speed have allowed entire populations to be sampled and analyzed. The result is massive amounts of data that convey relatively little information, even though they may contain a lot of information. These large quantities of data have already begun to cause bottlenecks in areas such as genetics, drug development, and chemical imaging. The problem is straightforward: condense a large quantity of data into only the useful portions without ignoring or discarding anything important. Performing the condensation in the hardware of the instrument, before the data ever reach a computer is even better. The research proposed tests the hypothesis that clusters of data may be rapidly identified by linear fitting of quantile-quantile plots produced from each principal component of principal component analysis. Integrated Sensing and Processing (ISP) is tested as a means of generating clusters of principal component scores from samples in a hyperspectral near-field scanning optical microscope. Distances from the centers of these multidimensional cluster centers to all other points in hyperspace can be calculated. The result is a novel digital staining technique for identifying anomalies in hyperspectral microscopic and nanoscopic imaging of human atherosclerotic tissue. This general method can be applied to other analytical problems as well.
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Complex sensor data analysis through data augmentationConlin, Adrian Keith January 1996 (has links)
No description available.
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Library search techniques for the identification of Chinese herbal drugs using infrared spectroscopy.January 2002 (has links)
Tsai Sam-Hip. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 56-60). / Abstracts in English and Chinese. / Acknowledgements --- p.i / Abstract --- p.ii / Contents --- p.iv / Chapter Chapter 1 --- Introduction / Chapter 1.1 --- Basic theory of infrared spectroscopy --- p.1 / Chapter 1.2 --- History Chinese herbal drugs --- p.4 / Chapter 1.3 --- Identification of Chinese herbal drugs using traditional methods --- p.6 / Chapter 1.4 --- Identification of Chinese herbal drugs by spectral fingerprinting method --- p.8 / Chapter 1.5 --- Objectives of this research --- p.10 / Chapter Chapter 2 --- "Extraction and identification of Chinese herbal drugs using the ""Effective Peaks Matching"" method" / Chapter 2.1 --- Experimental --- p.12 / Chapter 2.2 --- Results and Discussions --- p.21 / Chapter Chapter 3 --- Identification of Chinese herbal drugs using point-to-point spectral comparison method / Chapter 3.1 --- Experimental --- p.28 / Chapter 3.2 --- Results and Discussions --- p.34 / Conclusion --- p.55 / References --- p.56 / Appendices / Chapter A1 --- "VBA programs for the ""Effective Peaks Matching"" method" --- p.61 / Chapter A2 --- "VBA programs for ""point-to-point"" comparison method" --- p.74 / Chapter A3 --- Original spectra for database building --- p.79
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