Requirements for tracking radar for falling spheres

Error analysis on radar tracking of falling sphere

Spatial patterns in timing of the diurnal temperature cycle

This paper investigates the structural difference in timing of the diurnal temperature cycle (DTC) over land resulting from choice of measuring device or model framework. It is shown that the timing can be reliably estimated from temporally sparse observations acquired from a constellation of low Earth-orbiting satellites given record lengths of at least three months. Based on a year of data, the spatial patterns of mean DTC timing are compared between temperature estimates from microwave Ka-band, geostationary thermal infrared (TIR), and numerical weather prediction model output from the Global Modeling and Assimilation Office (GMAO). It is found that the spatial patterns can be explained by vegetation effects, sensing depth differences and more speculatively the orientation of orographic relief features. In absolute terms, the GMAO model puts the peak of the DTC on average at 12:50 local solar time, 23 min before TIR with a peak temperature at 13:13 (both averaged over Africa and Europe). Since TIR is the shallowest observation of the land surface, this small difference represents a structural error that possibly affects the model's ability to assimilate observations that are closely tied to the DTC. The equivalent average timing for Ka-band is 13:44, which is influenced by the effect of increased sensing depth in desert areas. For non-desert areas, the Ka-band observations lag the TIR observations by only 15 min, which is in agreement with their respective theoretical sensing depth. The results of this comparison provide insights into the structural differences between temperature measurements and models, and can be used as a first step to account for these differences in a coherent way

The Ursinus Weekly, December 6, 1954

West Chester choir sings at vespers • Does Ursinus have adequate parking facilities? • Candlelight Communion to be held Dec. 9 in Bomberger • Improper procedure key in MSGA trial • Rosicrucians add members at after-dinner dessert • Dr. Dugger speaks, shows slides to pre-medical group • Christmas to visit UC in many forms • Beta Sig presents Bill Haley on Jan. 7 • Charles Hudnut wins award in national poetry contest • Seniors hold prom; Elect lord and lady • 300 attend seventeenth annual Messiah performance • Chesterfield holds contest Home for the holidays • Dr. Oliver Gogarty discusses poets • Band practicing for May Day; Marches at basketball games • Editorials • Test of time • Matmen boast 7 lettermen; Two MAC champions return • Gridmen elect Neborak MVP, 1955 captain • Heller, Bauser All Philadelphia 3rd hockey team • Susquehanna, Nat. Aggies bow; Juniata mars record by 78-56 • Westerhoff\u27s proposed revisions passed by MSGAhttps://digitalcommons.ursinus.edu/weekly/1462/thumbnail.jp

The USFD Spoken Language Translation System for IWSLT 2014

The University of Sheffield (USFD) participated in the International Workshop for Spoken Language Translation (IWSLT) in 2014. In this paper, we will introduce the USFD SLT system for IWSLT. Automatic speech recognition (ASR) is achieved by two multi-pass deep neural network systems with adaptation and rescoring techniques. Machine translation (MT) is achieved by a phrase-based system. The USFD primary system incorporates state-of-the-art ASR and MT techniques and gives a BLEU score of 23.45 and 14.75 on the English-to-French and English-to-German speech-to-text translation task with the IWSLT 2014 data. The USFD contrastive systems explore the integration of ASR and MT by using a quality estimation system to rescore the ASR outputs, optimising towards better translation. This gives a further 0.54 and 0.26 BLEU improvement respectively on the IWSLT 2012 and 2014 evaluation data