970 resultados para Blind cord safety


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Vehicular ad hoc network (VANET) applications are principally categorized into safety and commercial applications. Efficient traffic management for routing an emergency vehicle is of paramount importance in safety applications of VANETs. In the first case, a typical example of a high dense urban scenario is considered to demonstrate the role of penetration ratio for achieving reduced travel time between source and destination points. The major requirement for testing these VANET applications is a realistic simulation approach which would justify the results prior to actual deployment. A Traffic Simulator coupled with a Network Simulator using a feedback loop feature is apt for realistic simulation of VANETs. Thus, in this paper, we develop the safety application using traffic control interface (TraCI), which couples SUMO (traffic simulator) and NS2 (network simulator). Likewise, the mean throughput is one of the necessary performance measures for commercial applications of VANETs. In the next case, commercial applications have been considered wherein the data is transferred amongst vehicles (V2V) and between roadside infrastructure and vehicles (I2V), for which the throughput is assessed.

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Avoidance of collision between moving objects in a 3-D environment is fundamental to the problem of planning safe trajectories in dynamic environments. This problem appears in several diverse fields including robotics, air vehicles, underwater vehicles and computer animation. Most of the existing literature on collision prediction assumes objects to be modelled as spheres. While the conservative spherical bounding box is valid in many cases, in many other cases, where objects operate in close proximity, a less conservative approach, that allows objects to be modelled using analytic surfaces that closely mimic the shape of the object, is more desirable. In this paper, a collision cone approach (previously developed only for objects moving on a plane) is used to determine collision between objects, moving in 3-D space, whose shapes can be modelled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained and used to derive dynamic inversion based avoidance strategies.

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The safety of an in-service brick arch railway bridge is assessed through field testing and finite-element analysis. Different loading test train configurations have been used in the field testing. The response of the bridge in terms of displacements, strains, and accelerations is measured under the ambient and design train traffic loading conditions. Nonlinear fracture mechanics-based finite-element analyses are performed to assess the margin of safety. A parametric study is done to study the effects of tensile strength on the progress of cracking in the arch. Furthermore, a stability analysis to assess collapse of the arch caused by lateral movement at the springing of one of the abutments that is elastically supported is carried out. The margin of safety with respect to cracking and stability failure is computed. Conclusions are drawn with some remarks on the state of the bridge within the framework of the information available and inferred information. DOI: 10.1061/(ASCE)BE.1943-5592.0000338. (C) 2013 American Society of Civil Engineers.

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One of the challenges for accurately estimating Worst Case Execu-tion Time(WCET) of executables is to accurately predict their cache behaviour. Various techniques have been developed to predict the cache contents at different program points to estimate the execution time of memory-accessing instructions. One of the most widely used techniques is Abstract Interpretation based Must Analysis, which de-termines the cache blocks guaranteed to be present in the cache, and hence provides safe estimation of cache hits and misses. However,Must Analysis is highly imprecise, and platforms using Must Analysis have been known to produce blown-up WCET estimates. In our work, we propose to use May Analysis to assist the Must Analysis cache up-date and make it more precise. We prove the safety of our approach as well as provide examples where our Improved Must Analysis provides better precision. Further, we also detect a serious flaw in the original Persistence Analysis, and use Must and May Analysis to assist the Persistence Analysis cache update, to make it safe and more precise than the known solutions to the problem.

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Any waterway with one end closed and the other open is generally called a blind channel. The main flow tends to expand, separate, and cause circulation at the mouth of blind channels. The main flow continuously transfers momentum and sediment into the circulation region through the turbulent mixing region (TMR) between them, thus leading to a large amount of sediment deposition in the blind channels. This paper experimentally investigated the properties of the water flow and sediment diffusion in TMR, demonstrating that both water flow and sediment motion in TMR approximately coincide with a similar structure as in the free mixing layer induced by a jet. The similarity functions of flow velocity and sediment concentration are then assumed, based on observation, and the resulting calculation of these functions is substantially facilitated. For the kind of low velocity flow system of blind channels with a finite width, a simple formula for the sediment deposition rate in blind channels is established by analyzing the gradient of crosswise velocity and sediment concentration in TMR.

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We consider the problem of blind multiuser detection. We adopt a Bayesian approach where unknown parameters are considered random and integrated out. Computing the maximum a posteriori estimate of the input data sequence requires solving a combinatorial optimization problem. We propose here to apply the Cross-Entropy method recently introduced by Rubinstein. The performance of cross-entropy is compared to Markov chain Monte Carlo. For similar Bit Error Rate performance, we demonstrate that Cross-Entropy outperforms a generic Markov chain Monte Carlo method in terms of operation time.

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We present methods for fixed-lag smoothing using Sequential Importance sampling (SIS) on a discrete non-linear, non-Gaussian state space system with unknown parameters. Our particular application is in the field of digital communication systems. Each input data point is taken from a finite set of symbols. We represent transmission media as a fixed filter with a finite impulse response (FIR), hence a discrete state-space system is formed. Conventional Markov chain Monte Carlo (MCMC) techniques such as the Gibbs sampler are unsuitable for this task because they can only perform processing on a batch of data. Data arrives sequentially, so it would seem sensible to process it in this way. In addition, many communication systems are interactive, so there is a maximum level of latency that can be tolerated before a symbol is decoded. We will demonstrate this method by simulation and compare its performance to existing techniques.