Algorithms for determining planar area properties from peripheral points

The determination of planar properties—cross sectional areas, centroids, moments of inertia, and so forth—plays a central role in the solution of many diverse engineering problems. Despite the increasing availability of computational power to engineers and students alike in recent years with the advent of small desktop computers, however, the traditionally laborious and error-prone methods of making these determinations, involving area decomposition or strip integration, are still being taught to the present generation of engineering students, mostly due to a lack of suitable alternative techniques. These classical methods are found to be particularly difficult to adapt to general computational algorithms. This work presents a novel approach, requiring only the peripheral points of any planar area as inputs, and is ideally suited for numerical methods. It is shown that all planar properties of technical interest can be generated, once and for all, with straightforward algorithms that are readily programmed in any scientific computing language, or adapted to typical spreadsheet formats. These algorithms are fully general and require no decision-making on the part of the user. Various worked examples are presented.     

Airborne scatterometers: investigating ocean backscatter under low and high-wind conditions

Attempting to understand and predict weather on a local and global basis has challenged both the scientific and engineering communities. One key parameter in understanding the weather is the ocean surface wind vector because of its role in the energy exchange at the air-sea surface. scatterometers, radars that measure the reflectivity of a target offer a tool with which to remotely monitor these winds from tower-, aircraft-, and satellite-based platforms. This paper introduces three current airborne scatterometer systems, and presents data collected by these instruments under low-, moderate-, and high-wind conditions. The paper focuses on airborne scatterometers because of their ability to resolve submesoscale variations in wind fields. Discrepancies between existing theory and the observations are noted and the concerns in measuring low-wind speeds discussed. Finally, the application of using this technology for estimating the surface-wind vector during a hurricane is demonstrated     

Construction experiences with SSC collider dipole magnets atFermilab

Full length and short model SSC (Superconducting Super Collider) 50 mm bore dipoles are being built and tested at Fermilab. The mechanical design of these magnets has been determined from experience with the construction of previous superconducting magnets. Construction experience includes coil fabrication, ground insulation, instrumentation, collaring, and yoke assembly. Fabrication techniques are explained, and construction problems and their solutions are reviewed. The relationship of short to long model construction is discussed     

A Realistic Computer-Simulated Brain Phantom for Evaluation of PET Charactenstics

To evaluate accurately the imaging characteristics of positron emission tomography (PET), a realistic computer-simulated brain phantom was developed. A cross-sectional slice from a human cadaver brain was chosen for its combination of gray matter, white matter, and cerebrospinal fluid (CSF) regions. The slice was photographed and digitized into a gray-level image with a video digitizer, boundary edges were located around cerebral structures in the digitized image, and each structural region was assigned a uniform pixel value dependent on both the cerebral parameter (e.g., blood flow, oxygen uptake, metabolic rate) under investigation and the type of structure (gray matter, white matter, CSF). Line integrals through the regions were generated at various angular and transverse positions according to specific physical characteristics (such as detector line-spread function) of a tomographic scanner configuration to create a set of simulated but realistic projection measurements. The set of projection measurements can be processed with any standard reconstruction program to create a tomographic image to reveal the effects of various PET characteristics. Investigations with this computer-simulated brain phantom have demonstrated its usefulness for examining the interrelations among neuroanatomical structure volume, tomographic spatial resolution, partial volume effect, and nonlinear parameter estimation. Transportability of the simulated phantom and the procedure to other medical imaging environments is described, and limitations of this simulation procedure are discussed.     

Protein crystal growth in microgravity-temperature induced large scale crystallization of insulin

One of the major stumbling blocks that prevents rapid structure determination using x-ray crystallography is macromolecular crystal growth. There are many examples where crystallization takes longer than structure determination. In some cases, it is impossible to grow useful crystals on earth. Recent experiments conducted in conjunction with NASA on various Space Shuttle missions have demonstrated that protein crystals often grow larger and display better internal molecular order than their earth-grown counterparts. This paper reports results from three Shuttle flights using the Protein Crystallization Facility (PCF). The PCF hardware produced large, high-quality insulin crystals by using a temperature change as the sole means to affect protein solubility and thus, crystallization. The facility consists of cylinders/containers with volumes of 500, 200, 100, and 50 ml. Data from the three Shuttle flights demonstrated that larger, higher resolution crystals (as evidenced by x-ray diffraction data) were obtained from the microgravity experiments when compared to earth-grown crystals.     

Use of fuzzy-logic-inspired features to improve bacterialrecognition through classifier fusion

Escherichia coli O157:H7 has been found to cause serious health problems. Traditional methods to identify the organism are quite slow, pulsed-held gel electrophoresis (PFGE) images contain "banding pattern" information which can be used to recognize the bacteria. A fuzzy logic rule-based system is used as a guide to find a good feature set for the recognition of E. coli O157:H7. While the fuzzy rule-based system achieved good recognition, the human inspired features used in the rules were incorporated into a multiple neural network fusion approach which gave excellent separation of the target bacteria. The fuzzy integral was utilized in the fusion of neural networks trained with different feature sets to reach an almost perfect classification rate of E. coli O157:H7 PFGE patterns made available for the experiments.