34,629 research outputs found
Possibly New Charmed Baryon States from Decay
We examine the invariant mass spectrum of in decay measured by BABAR and find that through the 2-step processes of
, where denotes a
charmed baryon state, some of the peaks can be identified with the established
, and . Moreover, in
order to account for the measured spectrum, it is necessary to introduce a new
charmed baryon resonance with MeV.Comment: 8 pages, 1 figure, title changed and discussions updated, version
accepted for publication in Phys. Rev.
Caching and Auditing in the RPPM Model
Crampton and Sellwood recently introduced a variant of relationship-based
access control based on the concepts of relationships, paths and principal
matching, to which we will refer as the RPPM model. In this paper, we show that
the RPPM model can be extended to provide support for caching of authorization
decisions and enforcement of separation of duty policies. We show that these
extensions are natural and powerful. Indeed, caching provides far greater
advantages in RPPM than it does in most other access control models and we are
able to support a wide range of separation of duty policies.Comment: Accepted for publication at STM 2014 (without proofs, which are
included in this longer version
Seeing Is Believing: Analysts' Corporate Site Visits
This study examines the impact of corporate site visits on analysts’ forecast accuracy based on a sample of such visits to Chinese listed firms during 2009–2012. We find that analysts who conduct visits (“visiting analysts”) have a greater increase in forecast accuracy than other analysts. Consistent with the notion that site visits facilitate analysts’ information acquisition through observing firms’ operations, we find that the results are stronger for manufacturing firms, firms with more tangible assets, and firms with more concentrated business lines. Moreover, we find that the effect of a site visit is greater when the site visit is an analyst-only visit, when the current visit is preceded by fewer visits, and when visiting analysts are based far from the visited firms. Furthermore, we find that site visits partially mitigate nonlocal analysts’ information disadvantage. Collectively, these results indicate that site visits are an important information acquisition activity for analysts.postprin
Feasibility Study of Tractor-Test Vehicle Technique for Practical Structural Condition Assessment of Beam-Like Bridge Deck
The tractor-test vehicle technique of non-destructive testing for indirect measurement of the modal properties of a bridge deck is revisited in this paper with several improvements for possible practical application to the structural condition assessment of a beam-like bridge deck. The effect of damping of the vehicle-bridge system is considered and the modal properties from only the first vibration mode of the structure will be used for a quick and simple assessment. The two test vehicles are designed to have the same modal frequency and damping ratio but with parameters in the follower No.2 test vehicle proportional to those in the follower No.1 test vehicle. This effectively removes the effect of road surface roughness in the response of an equivalent vehicle such that the error in the subsequent condition assessment is reduced. Through data collected on-site transmitted to the remote computer platform, a simple technique based on the moment-curvature relationship acceptable to practical engineers is adopted for the condition assessment with improvements in the estimation of the element bending stiffness of the deck. Scenarios with different damping, vehicle speed, road surface roughness, and local damages in the bridge structure are studied with or without temperature effect in the measurement. Through numerical simulations and field tests, the tractor-test vehicle technique of non-destructive testing with the proposed modifications and improvements has been demonstrated to give consistently accurate estimates of the element bending stiffness of the bridge deck but with a small error close to the end of the deck
Learning Points and Routes to Recommend Trajectories
The problem of recommending tours to travellers is an important and broadly
studied area. Suggested solutions include various approaches of
points-of-interest (POI) recommendation and route planning. We consider the
task of recommending a sequence of POIs, that simultaneously uses information
about POIs and routes. Our approach unifies the treatment of various sources of
information by representing them as features in machine learning algorithms,
enabling us to learn from past behaviour. Information about POIs are used to
learn a POI ranking model that accounts for the start and end points of tours.
Data about previous trajectories are used for learning transition patterns
between POIs that enable us to recommend probable routes. In addition, a
probabilistic model is proposed to combine the results of POI ranking and the
POI to POI transitions. We propose a new F score on pairs of POIs that
capture the order of visits. Empirical results show that our approach improves
on recent methods, and demonstrate that combining points and routes enables
better trajectory recommendations
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