2,345 research outputs found
The Time of Flight System of the AMS-02 Space Experiment
The Time-of-Flight (TOF) system of the AMS detector gives the fast trigger to
the read out electronics and measures velocity, direction and charge of the
crossing particles. The new version of the detector (called AMS-02) will be
installed on the International Space Station on March 2004. The fringing field
of the AMS-02 superconducting magnet is kG where the
photomultiplers (PM) are installed. In order to be able to operate with this
residual field, a new type of PM was chosen and the mechanical design was
constrained by requiring to minimize the angle between the magnetic field
vector and the PM axis. Due to strong field and to the curved light guides, the
time resolution will be ps, while the new electronics will allow
for a better charge measurement.Comment: 5 pages, 4 figures. Proc. of 7th Int. Conf. on Adv. Tech. and Part.
Phys., 15-19 October 2001,Como (Italy
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The CDF-II silicon tracking system
The CDFII silicon tracking system, SVX, for Run II of the Fermilab Tevatron has up to 8 cylindrical layers with average radii spanning from {approx} (1.5 to 28.7) cm, and lengths ranging from {approx} (90 to 200) cm for a total active-area of {approx} 6 m{sup 2} and {approx} 7.2 x 10{sup 5} readout channels. SVX will improve the CDFII acceptance and efficiency for both B and high-Pt physics dependent upon b-tagging. Along with the description of the SVX we report some alignment survey data from the SVX assembly phase and the actual status of the alignment as it results from the offline data analysis. The problems encountered are also reviewed
The AMS-02 Time of Flight System. Final Design
The AMS-02 detector is a superconducting magnetic spectrometer that will
operate on the International Space Station. The time of flight (TOF) system of
AMS-02 is composed by four scintillator planes with 8, 8, 10, 8 counters each,
read at both ends by a total of 144 phototubes. This paper describes the new
design, the expected performances, and shows preliminary results of the ion
beam test carried on at CERN on October 2002.Comment: 4 pages, 6 EPS figures. Proc. of the 28th ICRC (2003
UNIMIB@NEEL-IT: Named Entity Recognition and Linking of Italian Tweets
Questo articolo descrive il sistema proposto dal gruppo UNIMIB per il task di Named Entity Recognition and Linking applicato a tweet in lingua italiana (NEEL-IT). Il sistema, che rappresenta un approccio iniziale al problema, \ue8 costituito da tre passaggi fondamentali: (1) Named Entity Recognition tramite l\u2019utilizzo di Conditional Random Fields, (2) Named Entity Linking considerando sia approcci supervisionati sia modelli di linguaggio basati su reti neurali, e (3) NIL clustering tramite un approccio basato su grafi.This paper describes the framework proposed by the UNIMIB Team for the task of Named Entity Recognition and Linking of Italian Tweets (NEEL-IT). The proposed pipeline, which represents an entry level system, is composed of three main steps: (1) Named Entity Recognition using Conditional Random Fields, (2) Named Entity Linking by considering both Supervised and Neural-Network Language models, and (3) NIL clustering byusing a graph-based approach
The accuracy of NIRS in predicting chemical composition and fibre digestibility of hay-based total mixed rations
The aim of this study was to develop near-infrared spectroscopy (NIRS) prediction models for the estimation of chemical components and the fibre undegradable fractions (uNDF) of hay-based total mixed rations (TMR). A total of 205 TMR samples were used for the study. All the chemical components were measured using standard AOAC reference methods and expressed as percentages of dry matter (DM). Prediction models were developed using both cross- and independent validation and different mathematical treatments applied on spectral data. The best spectral treatment was chosen based on the method which simultaneously achieved the lowest root mean square error and the highest explained variance in cross-validation. The coefficient of determination in external validation (R2P) was the greatest for starch prediction model (R2P = 0.84), followed by acid detergent fibre (ADF; R2P = 0.79), and amylase-treated ash-corrected NDF with addition of sodium sulphite (aNDFom) and crude protein prediction models (CP; R2P = 0.73). The concordance correlation coefficient (CCC) in validation ranged from 0.66 (ash prediction model) to 0.92 (starch prediction model), indicating substantial to accurate models’ predictive ability. This study indicated that NIRS can be a screening method for the prediction of CP, Starch, aNDFom, ADF, acid detergent lignin (ADL), uNDF and Ash. The use of TMR utilised in various herds provided high variability for the NIRS calibration dataset, implying that the developed NIRS pre-diction models could be applicable to TMR collected from herds located in the Parmigiano Reggiano cheese production area.Highlights NIRS can be successfully employed to determine quickly and at cost-effective different compositional and digestibility traits in hay-based TMR. TMR analysis predicted by NIRS can support nutritionists in the formulation of diets containing a proper nutrient profile to sustain physiological, metabolic, and immunological processes. The use of NIR technology for TMR analysis can allow frequent monitoring of rations and increasingly timely corrections, maximising cows’ diet utilisation and conversion of the ingested feed
Towards a Semantic Document Management System for Public Administration
This work has two objectives: to summarize the experiences carried out over the past four years by the National Interuniversity Consortium for Informatics (CINI) in the Datalake project funded by the CRUI in collaboration with the Directorate General of Automated Information Systems (DGSIA) of the Ministry of Justice, in synergy with other related projects of the Ministry; and to demonstrate how the experiences, Proof of Concepts, and functional specifications produced can serve as a repository of functionalities for a “semantic document management system for PA,” which aims to evolve the information systems of PAs into platforms where unstructured data can be exploited and integrated with structured data to enhance and add value to the digital services provided by the PA, and where governance processes can be conducted using all
knowledge expressed in documents and other forms of unstructured data. The judicial organization, proceedings, processes, user needs, functional structure of the Datalake, and implementation architecture are described, aiming towards a design and production pathway directed at all PAs
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