An Improved Vanet Clustering and Channel Quality using Movc and Weighted Probability

VANET offers a vast range of application which will make travel experience safe. The concept behind VANET is quite simple which incorporates wireless communication and capable of sharing data; the vehicles are turned for offering network to provide services which can be used in the home or office networks. VANET network nodes are move in-network with higher velocity in the network. This higher mobility of vehicles causes increased resource and energy utilization which causes failure of nodes. Resource and energy consumption is higher for inefficient constructed clustering for VANET. Also, vehicle mobility causes several obstacles in data transmission this causes degraded channel quality. data transmission this causes degraded channel quality. In this paper concentrated on improving channel quality and energy efficiency in the network. Initially, performed efficient clustering through middle-order based cluster head (CH) election (MOVC) mechanism. Through effective CH election resource and energy utilization is limited. In the next stage, channel quality is improved by the proposed weighted probability approach for effective data transmission between vehicles in the VANET network. The weighted probability approach estimates the path for data transmission to destination vehicle. Through the selection of CHs using the middle-order approach, the network exhibits an effective maintenance phase here, the weighted probability is applied for the estimation of the path for effective data transmission in the VANET. The comparative analysis of the proposed approach exhibits significant performance rather than conventional technique. The estimated residual energy of the proposed approach is almost 20% higher than ACO, PSO, and KH. The packet delivery rate is observed around 80% and delay is minimal as of 2.5sec.

A Procustes's Procedure for Obtaining Divergences

Divergences have become a very useful tool for measuring similarity (or dissimilarity) between probability distributions. Depending on the field of application a more appropriate measure may be necessary. In this paper we introduce a family of divergences we call gamma-divergences. They are based on the convexity property of the functions that generate them. We demonstrate that these divergences verify all the usually required properties, and we extend them to weighted probability distribution. We investigate their properties in the context of kernel theory. Finally, we apply our findings to the analysis of simulated and real time series.

500 30-DAY SURVIVAL AND RECOVERY AFTER HIP FRACTURE BY MOBILISATION TIMING AND DEMENTIA: A UK DATABASE STUDY

Introduction To compare 30-day survival and recovery of prefracture ambulation between patients mobilised early (on the day of or day after surgery) and patients mobilised late (2 days of more after surgery) in England and Wales. To determine whether the presence of dementia influences the association between mobilisation timing and 30-day survival and recovery. Methods Secondary analysis of the UK National Hip Fracture Database linked to hospitalisation records for 126,897 patients 60 years or older who underwent surgery for nonpathological first hip fracture in England or Wales between 2014 and 2016. We used logistic regression to regress survival and ambulation recovery at 30-days with respect to mobilisation timing, overall and by dementia, with adjustment for confounding using a propensity score for mobilisation treatment with respect to confounders. Results Overall, 99,667 (79%) patients mobilised early. Among those who mobilised early compared to those who mobilised late, the weighted odds ratio of survival was 1.92 (95% CI 1.80–2.05), of recovering outdoor ambulation was 1.25 (95% CI 1.03–1.51), and of recovering indoor ambulation was 1.53 (95% CI 1.32–1.78) by 30 days. Early compared with late mobilisation led to a 3.8% increase in the weighted probability of survival, 22.8% increase in weighted probability of recovering outdoor ambulation and 10.0% increase in the weighted probability of recovering indoor ambulation, by 30-days. Patients with dementia were less likely to mobilise early but increases in survival and ambulation recovery were observed both for those with and without dementia. Conclusion Early mobilisation led to increase probability of survival and recovery for patients (with and without dementia) after hip fracture. Early mobilisation should be incorporated as a measured indicator of quality internationally. Reasons for failure to mobilise early should also be captured to inform quality improvement initiatives.

A Road Environment Prediction System for Intelligent Vehicle

The road environment prediction is an essential task for intelligent vehicle. In this study, we provide a flexible system that focuses on freespace detection and road environment prediction to host vehicle. The hardware of this system includes two parts: a binocular camera and a low-power mobile platform, which is flexible and portable for a variety of intelligent vehicle. We put forward a multiscale stereo matching algorithm to reduce the computing cost of the hardware unit. Based on disparity space and points cloud, we propose a weighted probability grid map to detect freespace region and a state model to describe the road environment. The experiments show that the proposed system is accurate and robust, which indicates that this technique is fully competent for road environment prediction for intelligent vehicle.

HASH Algorithm of Weighted Probability Model

<p>In this paper, a brand-new hash algorithm is provided. The length of the hash value can be customized. It is theoretically proved that the hash collision limit can be reached. The algorithm can be applied flexibly, and it can be applied to digital signatures, document verification and other fields in the future.</p>

HASH Algorithm of Weighted Probability Model

<p>In this paper, a brand-new hash algorithm is provided. The length of the hash value can be customized. It is theoretically proved that the hash collision limit can be reached. The algorithm can be applied flexibly, and it can be applied to digital signatures, document verification and other fields in the future.</p>

Channel Coding of Weighted Probabilistic Model

<p>In this paper a brand new channel error detection and correction method is provided. Artificially adding symbols to the source binary sequence makes the binary sequence present a regularity. The receiver can use this rule to implement error detection and correction. Since many redundant symbols are added, a weighted probability model lossless coding method is proposed in this paper to remove redundant information, and the reasons why Markov chains and conditional probabilities are not feasible are given. It is proven that the method in this paper can reach the channel capacity when the code length approaches infinity. It is shown experimentally that when the code rate is 1/2 in the BIAWGN channel, the method in this paper is superior to the polar code and LDPC code.</p>