No abstract
Quantitative imaging biomarkers are of particular interest in drug development for their potential to accelerate the drug development pipeline. The lack of consensus methods and carefully characterized performance hampers the widespread availability of these quantitative measures. A framework to support collaborative work on quantitative imaging biomarkers would entail advanced statistical techniques, the development of controlled vocabularies, and a service-oriented architecture for processing large image archives. Until now, this framework has not been developed. With the availability of tools for automatic ontology-based annotation of datasets, coupled with image archives, and a means for batch selection and processing of image and clinical data, imaging will go through a similar increase in capability analogous to what advanced genetic profiling techniques have brought to molecular biology. We report on our current progress on developing an informatics infrastructure to store, query, and retrieve imaging biomarker data across a wide range of resources in a semantically meaningful way that facilitates the collaborative development and validation of potential imaging biomarkers by many stakeholders. Specifically, we describe the semantic components of our system, QI-Bench, that are used to specify and support experimental activities for statistical validation in quantitative imaging
List of Figures and Tables Figures Page 2-1 Progression in manufacturing line efficiency increases in 1998 and 1999. 2-2 Histogram of a single lot of >250 cells averaging 14.7%. 2-3 Plot of the increases in electrical yield over the 3 years of the program. 2-4 Contour plots of cell efficiency (%) as a function of the index of refraction, n R , thickness for a silicon nitride antireflection coating. 2-5 Contour plot of Fill Factor vs diffused-layer sheet resistivity and metalization 8 firing temperature 2-6 Improvements in cell fabrication mechanical yield over the three years of PVMaT 5A2. 2-7 Normalized wafer yield from 12/00 to 12/01. 2-8 Line scans of the f-harmonic along wafer diagonal (courtesy of S. Ostapenko, USF) 2-9 Acoustic amplitude at corners for high and low stress EFG wafers) courtesy of S. Ostapenko, USF). 2-10 Stress distribution in two EFG wafers (courtesy of S, Ostapenko, USF). 2-11 Capacitance sensor measurement of position of the surface of a growing experimental octagon tube. 2-12 Fast Fourier Transform (FFT) spectrum of buckle pattern in Fig. 2-11. 2-13 View of Tru-Si Atmospheric Downstream Plasma TM equipment. 2-14 Plasma flame configuration for the ADP TM process. 2-15 Example of submenu options available for statistical data analysis. 17 2-16 Pareto chart showing major contributing factors to Laser Cutting downtime. 2-17 Summary of ISO 9001 certification work. 3-1 Bulk lifetime improvement due to P, Al gettering and SiN hydrogenation. 3-2 50 cm diameter EFG cylinder. 4-1 Main menu from server data base querying user interface. 4-2 Results of a query in the server data base for Flatness Losses vs Tube Number for an experimental growth run of 57 octagon tubes. 4-3 View of module broken due to impact from wind-borne crushed roofing pieces. Arrow shows one of several impact points. 4-4 (a) Disconnected cable in junction box due to poor soldering. (b) Partially wetted solder joint in cable box. 4-5 Layering schematic for lamination structure for new ASE Americas module design. Tables 3-1 Comparison of standard ASE Americas cell process and proposed modifications using RTP methods. 3-2 Cell test parameters for cylindrical EFG multicrystalline Si solar cells. 26
Task 1-Manufacturing Systems 2.2 Task 2-Low Cost Processes 2.3 Task 3-Flexible Manufacturing 3.0 Highlights of the Year 1 Program 4.0 Future Work List of Figures Figure Page 1. a) Histogram of cell efficiency results for production lots. 4 b) Histogram of individual cells for the highest lot. 2. Summary of ISO 9000 certification work. 6 3. Photograph of new R&D laser cutting station. 9 4. Comparison of bulk lifetimes before and after processing for various sequences 12 5. Large diameter EFG tube in the process of growing. 13 6. View of 50 cm diameter EFG cylinder after completion of growth. 13 The section shown is 33 cm tall; full tubes are as long as 120 cm. 7. Temperature distribution in the crystal cylinder along growth direction (x) 14 used in the stress analysis. 8. Effective shear stress as a function of distance from the growth interface (x=0). 14 9. Dislocation density as a function of distance from the growth interface (x=0). 15 10. Transmission data for the new encapsulant after 4 months Arizona equivalent 18 accelerated UV exposure.
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