Measurement of Bc Mass and Lifetime at LHCb

The $B_c^\pm$ mass and lifetime measurements using the decay $B_c^\pm \to J/\psi \pi^\pm$ at the LHCb experiment were studied. About 310 signal events are expected for a data set which corresponds to an integrated luminosity of 1 fb$^{-1}$, with a $B/S$ ratio equal to 2. Based on these data, the $B_c^\pm$ mass and lifetime can be measured with expected statistical errors below 2 MeV/$c^2$ and 30 fs, respectively.Comment: 5 pages, 2 figures, Proceedings of the XVII International Workshop on Deep-Inelastic Scattering and Related Topics, April 26-30, 2009 Madrid, Spai

Computer Program, System, and Method for Observation and Communication for Mobile Settings, Mobile Applications, and Wearable Mobile Devices

A system including at least first and second wearable mobile devices and optionally one or more smartphones or other computing devices for allowing a wearable mobile device wearer, an on-site observer, and a remote observer to research and test usability of products in mobile settings, mobile applications, mobile devices, and wearable mobile devices, desktop usability settings, and other settings and devices. The devices nm a software application for generating first-person video and third-person video, transmitting the video to the other devices, marking the videos with time stamps, and allowing the remote observer to send messages and other information to the other devices

Non-leptonic charmless Bc decays and their search at LHCb

We discuss the decay of Bc mesons into two light mesons (pi, K^(*), eta', rho, omega, phi). All these decay channels come from a single type of diagram, namely tree annihilation. This allows us to derive extremely simple SU(3) relations among these processes. The size of annihilation contributions is an important issue in B physics, and we provide two different estimates in the case of non-leptonic charmless Bc decays, either a comparison with annihilation decays of heavy-light mesons or a perturbative model inspired by QCD factorisation. We finally discuss a possible search for these channels at LHCb.Comment: 22 pages, 1 figur

Vehicle Detection Using Android Smartphones

Rear-end collisions are the most common traffic accidents. Technologies, such as collision warning systems, are developed to reduce the risks of rear-end collisions. This study presents a mobile technology using smartphones to detect the leading vehicle, allowing the possibility to make collision warning systems more affordable and portable. This technology uses the rear camera of an Android smartphone to capture images of driving scenes, and then uses advanced computer vision algorithms to detect and track the leading vehicle. This study may have important applications to improve driving safety

Lane keeping under cognitive distractions: performance and mechanisms

Cognitive distractions while driving often reduce the variability of lane position. However, data do not make clear whether smaller lane variability should be interpreted as a performance loss, indicating rigidified or unresponsive steering response to external stimuli, or a performance improvement in lane-keeping, indicating better lateral control. Four hypotheses, rigidified steering, visual enhancement, lateral prioritization, and automatic steering, debated on the performance implications and mechanisms of smaller lane variability under cognitive distractions. This dissertation project compares these hypotheses, and explores two important questions: first, whether the smaller lane variability under cognitive distraction indicates a performance loss or a performance gain in lane-keeping; second, what is the underlying cognitive mechanisms of lane variability reduction. Three studies have been carried out to assess drivers’ responsiveness to heavy lateral winds under varying levels of cognitive load. Data showed that cognitive load reduced the variability of lane position but increased the variability of vehicle speed, engendering more frequent steering activity but less frequent speed manipulation. Cognitive load also increased the coherence, or coupling between steering wheel position and lateral wind strength. More interestingly, distracted drivers produced quicker steering response time to the sudden onset of lateral wind. Results thus suggest that smaller lane variability under cognitive distractions is an indicator of better lane-keeping performance, and distracted drivers achieved better lane-keeping performance by actively prioritizing lateral control. Findings carry practical applications for mitigating driving risks and theoretical implications on the relationship between attention allocation and driving performance

Towards a Practical Pedestrian Distraction Detection Framework using Wearables

Pedestrian safety continues to be a significant concern in urban communities and pedestrian distraction is emerging as one of the main causes of grave and fatal accidents involving pedestrians. The advent of sophisticated mobile and wearable devices, equipped with high-precision on-board sensors capable of measuring fine-grained user movements and context, provides a tremendous opportunity for designing effective pedestrian safety systems and applications. Accurate and efficient recognition of pedestrian distractions in real-time given the memory, computation and communication limitations of these devices, however, remains the key technical challenge in the design of such systems. Earlier research efforts in pedestrian distraction detection using data available from mobile and wearable devices have primarily focused only on achieving high detection accuracy, resulting in designs that are either resource intensive and unsuitable for implementation on mainstream mobile devices, or computationally slow and not useful for real-time pedestrian safety applications, or require specialized hardware and less likely to be adopted by most users. In the quest for a pedestrian safety system that achieves a favorable balance between computational efficiency, detection accuracy, and energy consumption, this paper makes the following main contributions: (i) design of a novel complex activity recognition framework which employs motion data available from users' mobile and wearable devices and a lightweight frequency matching approach to accurately and efficiently recognize complex distraction related activities, and (ii) a comprehensive comparative evaluation of the proposed framework with well-known complex activity recognition techniques in the literature with the help of data collected from human subject pedestrians and prototype implementations on commercially-available mobile and wearable devices

Investigating charmonium production at LHC with the p pbar final state

We propose to investigate various charmonium states using their common decay channel to p pbar at LHC. Having the branching ratios for charmonium decaying into the p pbar final state measured or calculated, we propose to measure the charmonium production rate for both hadroproduction including soft-diffraction and inclusive production from b-hadron decays. We discuss the theoretical impacts in QCD of measuring different charmonium production rates and also the experimental prospects at LHCb, in particular, those for yet unmeasured eta_c and h_c.Comment: 5 pages, no figur

Driving While Reading Using Google Glass Versus Using a Smartphone: Which is More Distracting to Driving Performance?

Using a phone while driving leads to distraction and impaired driving performance. When reading text on a phone, the act of looking away from the road could cause driving impairment. Wearable displays like Google Glass might reduce the visual impairment caused by looking away, even if they do not overcome other factors contributing to impaired driving. However, such devices could also increase impairment by giving drivers the mistaken impression that they can pay attention to both the display and the road simultaneously or impair visual processing by superimposing visual information in the driving scenes. We compared driving performance in a simulated naturalistic driving task while drivers read text on Google Glass or on a smartphone. As expected, reading on Google Glass and the smartphone both impaired driving performance by increasing lane variations, but drivers using Google Glass showed less lane variation compared to smartphone users. To the extent that these metrics reflect better driving performance, Google Glass might somewhat reduce the costs of reading text while driving. Keywords: Driver distraction; Tactical vehicle control; Google Glass; Cellphon