Magnetic moments of charged hyperons

Measurements of the magnetic moments of the Ξ−, Σ+ and Σ− baryons are presented. The values found are μΞ−=−.69±.04, μΣ+=2.31±.027 and μΣ−=−.89±.14, in units μN. The Ξ− and Σ− results are final, while the Σ+ value is based on a preliminary analysis of about 22% of the data sample.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87403/2/58_1.pd

Search for polarization in Ξ0 hyperons

Inclusive hyperon production by 400 GeV protons at Fermilab has shown that the hyperons are produced with significant polarization. However no polarization has been seen for Λ’s produced at these energies. In this paper we present the results of a searcch for Ξ0 polarization.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87405/2/126_1.pd

Polarization of inclusively produced hyperons

We report here polarization results from a series of Fermilab experiments from the years 1974 through 1980, with some preliminary data from a high pT polarization experiment completed in February 1982. The Λ polarization has a remarkably simple and interesting behavior when expressed as a function of xF and pT.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87407/2/83_1.pd

Electron identification using a synchrotron radiation detector

A xenon filled multiwire proportional chamber was used to detect synchrotron radiation from high energy electrons traversing the field of a standard spectrometer magnet. Signals from the chamber were used to achieve an electron trigger with a pion rejection of ~ 17 and an average electron detection efficiency of 81%. Off-line analysis of the chamber signals increased the pion rejection to 59 with an electron efficiency of 77%.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26136/3/0000212.pd

Sign Language Recognition

This chapter covers the key aspects of sign-language recognition (SLR), starting with a brief introduction to the motivations and requirements, followed by a précis of sign linguistics and their impact on the field. The types of data available and the relative merits are explored allowing examination of the features which can be extracted. Classifying the manual aspects of sign (similar to gestures) is then discussed from a tracking and non-tracking viewpoint before summarising some of the approaches to the non-manual aspects of sign languages. Methods for combining the sign classification results into full SLR are given showing the progression towards speech recognition techniques and the further adaptations required for the sign specific case. Finally the current frontiers are discussed and the recent research presented. This covers the task of continuous sign recognition, the work towards true signer independence, how to effectively combine the different modalities of sign, making use of the current linguistic research and adapting to larger more noisy data set