DSpace How-To Guide: Tips and tricks for managing common DSpace chores

PDF fileThis short booklet is intended to introduce the commonest non-obvious customization related tasks for newcomers to DSpace administration. It has been written against the current stable version 1.3.2 of DSpace. We have tried to include instructions for different operating systems as required; most customizations, however, work identically cross-platform

The roles of hypocrisy induction and self construal theory to stop illegal downloading

The purpose of the study is to reveal how hypocrisy induction and self-construal theory influence attitudes toward the public service announcement urging against illegal downloading and the willingness to stop illegal downloading. As time goes on, illegal downloading has been rampant due to the advancement of technology, which motivates the government agencies involved in protecting intellectual property to conduct various campaigns. However, despite of their constant efforts, the previous methods such as legal punishment or monetary penalties categorized as an external factor have been ineffective to prevent illegal downloading. Therefore, the current study suggested a new strategy using hypocrisy induction and self-construal theory considered as an internal factor which spontaneously enocourage people to stop illegal downloading. To test hypotheses, a 3 (types of hypocrisy: hypocrisy induction by independent means vs. hypocrisy induction by interdependent means vs. control) X 2 (types of message in public service announcements: a personal perspective vs. a social perspective) between-subjects design was employed. The results showed that hypocrisy induction significantly affected attitudes toward the public service announcements and the willingness to stop illegal downloading. In addition, the interaction effect between types of hypocrisy and types of message was significant. Therefore, the study concluded that hypocrisy induction and self-construal theory would play an important role in preventing illegal downloading.Advertisin

CheckMATE 2: From the model to the limit

We present the latest developments to the CheckMATE program that allows models of new physics to be easily tested against the recent LHC data. To achieve this goal, the core of CheckMATE now contains over 60 LHC analyses of which 12 are from the 13 TeV run. The main new feature is that CheckMATE 2 now integrates the Monte Carlo event generation via Madgraph and Pythia 8. This allows users to go directly from a SLHA file or UFO model to the result of whether a model is allowed or not. In addition, the integration of the event generation leads to a significant increase in the speed of the program. Many other improvements have also been made, including the possibility to now combine signal regions to give a total likelihood for a model.Comment: 53 pages, 6 figures; references updated, instructions slightly change

CalFUSE v3: A Data-Reduction Pipeline for the Far Ultraviolet Spectroscopic Explorer

Since its launch in 1999, the Far Ultraviolet Spectroscopic Explorer (FUSE) has made over 4600 observations of some 2500 individual targets. The data are reduced by the Principal Investigator team at the Johns Hopkins University and archived at the Multimission Archive at Space Telescope (MAST). The data-reduction software package, called CalFUSE, has evolved considerably over the lifetime of the mission. The entire FUSE data set has recently been reprocessed with CalFUSE v3.2, the latest version of this software. This paper describes CalFUSE v3.2, the instrument calibrations upon which it is based, and the format of the resulting calibrated data files.Comment: To appear in PASP; 29 pages, 13 figures, uses aastex, emulateap

Six Noise Type Military Sound Classifier

Blast noise from military installations often has a negative impact on the quality of life of residents living in nearby communities. This negatively impacts the military's testing \& training capabilities due to restrictions, curfews, or range closures enacted to address noise complaints. In order to more directly manage noise around military installations, accurate noise monitoring has become a necessity. Although most noise monitors are simple sound level meters, more recent ones are capable of discerning blasts from ambient noise with some success. Investigators at the University of Pittsburgh previously developed a more advanced noise classifier that can discern between wind, aircraft, and blast noise, while simultaneously lowering the measurement threshold. Recent work will be presented from the development of a more advanced classifier that identifies additional classes of noise such as machine gun fire, vehicles, and thunder. Additional signal metrics were explored given the increased complexity of the classifier. By broadening the types of noise the system can accurately classify and increasing the number of metrics, a new system was developed with increased blast noise accuracy, decreased number of missed events, and significantly fewer false positives