Charm-System Tests of CPT with FOCUS

We discuss a search for CPT violation in neutral charm meson oscillations. The data come from the Fermilab fixed-target experiment FOCUS. While flavor mixing in the charm sector is predicted to be small by the standard model, it is still possible to investigate CPT violation through study of the proper time dependence of the asymmetry in right-sign decay rates for D0 and D0-bar. Using present limits for D0-D0-bar mixing we infer bounds on charm CPT violation using data from FOCUS.Comment: 8 pages, invited talk at the Second Meeting on CPT and Lorentz Symmetry, Indiana University, Bloomington, August 15-18, 200

Electromagnetic connector

Connector pair consists of two iron cores brought together a short distance from each other. Each core is wound with insulated wire. Ac signal is connected through the pair across the gap by magnetic induction. Device can be used underwater or in flammable atmosphere

A laboratory experiment in calculus for the high school

Thesis (M.A.)--Boston Universit

Energy efficient engine diffuser/combustor model technology

A full scale, full annular diffuser/combustor model test rig was tested to investigate how configurational changes affect pressure loss and flow separation characteristics. The rig was characterized by five major modules: inlet; prediffuser; strut; simulated combustor; and full combustor. The prediffuser featured a short, curved wall dump design. Performance goals included: (1) a separation-free prediffuser flow field; (2) total pressure loss limited to 3.0 percent in the prediffuser and shrouds; and (3) an overall section pressure loss of 5.5 percent P sub T3 at the design airflow distribution. The results indicated that the prediffuser configurations operate well within the program goals for pressure loss and demonstrate separation free operation over a wide range of inlet conditions

Energy efficient engine, high-pressure turbine cooling model technology report

Two dimensional flow visualization model tests were used to substantiate the flow stability benefits derived from the use of turning vanes in the root and tip turn flow areas. Results indicate the need for corner fillets and flow injection into the acute corner formed by the intersection of the rib and simulated airfoil suction surface in order to minimize recirculation (stagnation) of flow in that region. Three dimensional flow visualization model tests verified the actual blade coolant passage design

Novel convolution-based signal processing techniques for an artificial olfactory mucosa

As our understanding of the human olfactory system has grown, so has our ability to design artificial devices that mimic its functionality, so called electronic noses (e-noses). This has led to the development of a more sophisticated biomimetic system known as an artificial olfactory mucosa (e-mucosa) that comprises a large distributed sensor array and artificial mucous layer. In order to exploit fully this new architecture, new approaches are required to analyzing the rich data sets that it generates. In this paper, we propose a novel convolution based approach to processing signals from the e-mucosa. Computer simulations are performed to investigate the robustness of this approach when subjected to different real-world problems, such as sensor drift and noise. Our results demonstrate a promising ability to classify odors from poor sensor signals

Bacteria classification using Cyranose 320 electronic nose

Background An electronic nose (e-nose), the Cyrano Sciences' Cyranose 320, comprising an array of thirty-two polymer carbon black composite sensors has been used to identify six species of bacteria responsible for eye infections when present at a range of concentrations in saline solutions. Readings were taken from the headspace of the samples by manually introducing the portable e-nose system into a sterile glass containing a fixed volume of bacteria in suspension. Gathered data were a very complex mixture of different chemical compounds. Method Linear Principal Component Analysis (PCA) method was able to classify four classes of bacteria out of six classes though in reality other two classes were not better evident from PCA analysis and we got 74% classification accuracy from PCA. An innovative data clustering approach was investigated for these bacteria data by combining the 3-dimensional scatter plot, Fuzzy C Means (FCM) and Self Organizing Map (SOM) network. Using these three data clustering algorithms simultaneously better 'classification' of six eye bacteria classes were represented. Then three supervised classifiers, namely Multi Layer Perceptron (MLP), Probabilistic Neural network (PNN) and Radial basis function network (RBF), were used to classify the six bacteria classes. Results A [6 × 1] SOM network gave 96% accuracy for bacteria classification which was best accuracy. A comparative evaluation of the classifiers was conducted for this application. The best results suggest that we are able to predict six classes of bacteria with up to 98% accuracy with the application of the RBF network. Conclusion This type of bacteria data analysis and feature extraction is very difficult. But we can conclude that this combined use of three nonlinear methods can solve the feature extraction problem with very complex data and enhance the performance of Cyranose 320

Independent Orbiter Assessment (IOA): Assessment of instrumental subsystem FMEA/CIL

The McDonnell Douglas Astronautics Company (MDAC) was selected in June 1986 to perform an Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL). The IOA effort first completed an analysis of the Instrumentation hardware, generating draft failure modes and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The IOA results were then compared to the NASA FMEA/CIL baseline. A resolution of each discrepancy from the comparison is provided through additional analysis as required. The results of that comparison for the Orbiter Instrumentation hardware are documented. The IOA product for Instrumentation analysis consisted of 107 failure mode worksheets that resulted in 22 critical items being identified. Comparison was made to the Pre 51-L NASA baseline with 14 Post 51-L FMEAs added, which consists of 96 FMEAs and 18 CIL items. This comparison produced agreement on all but 25 FMEAs which caused differences in 5 CIL items

Combined electronic nose and tongue for a flavour sensing system

We present a novel, smart sensing system developed for the flavour analysis of liquids. The system comprises both a so-called "electronic tongue" based on shear horizontal surface acoustic wave (SH-SAW) sensors analysing the liquid phase and a so-called "electronic nose" based on chemFET sensors analysing the gaseous phase. Flavour is generally understood to be the overall experience from the combination of oral and nasal stimulation and is principally derived from a combination of the human senses of taste (gustation) and smell (olfaction). Thus, by combining two types of microsensors, an artificial flavour sensing system has been developed. Initial tests conducted with different liquid samples, i.e. water, orange juice and milk (of different fat content), resulted in 100% discrimination using principal components analysis; although it was found that there was little contribution from the electronic nose. Therefore further flavour experiments were designed to demonstrate the potential of the combined electronic nose/tongue flavour system. Consequently, experiments were conducted on low vapour pressure taste-biased solutions and high vapour pressure, smell-biased solutions. Only the combined flavour analysis system could achieve 100% discrimination between all the different liquids. We believe that this is the first report of a SAW-based analysis system that determines flavour through the combination of both liquid and headspace analysis