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A vehicular ad hoc network (VANET) is designed to enable efficient and authentic node/infrastructure communication. The primary role of VANETs is to distribute time-sensitive safety messages (sm) regularly, which causes packet congestion and broadcast failure due to the network's limited spectrum. For efficient and reliable delivery, the proposed paper uses a spatial hybrid division multiple access (SDMA) and time division multiple access (TDMA) over the control channel interval and hence termed a spatially distributed multichannel MAC (SDM-MAC) protocol. The frequency reuse approach is used to transfer data while efficiently utilising bandwidth, and throughput is considerably enhanced with carrier sense multiple access with collision avoidance (CSMA/CA) and with the help of TDMA. Moreover, an adaptive algorithm is proposed for an intelligent channel frame structure using this protocol to manage the highly dynamic scenario. The Markov chain defines the protocol, and the network simulator (NS2) analyses several performance metrics. Comparing the response with two existing MAC protocols, the proposed protocol reduces average latency compared to current MAC methods and improves the packet delivery ratio and throughput by an average of 26% and 28%, respectively. [ABSTRACT FROM AUTHOR]

Vehicular communication is gaining huge attention among researchers and industrialists due to its enormous capability in traffic management and infotainment solutions. IEEE 802.11p standard is established to achieve the objectives of vehicular communication by providing vehicle-to-vehicle and vehicle-to-infrastructure communication. Precise channel estimation is challenging in vehicular scenario, which impacts the robust execution of the vehicular communication. In the previous work for spectral temporal averaging (STA) channel estimation, fixed values of averaging parameters (α and β) have been chosen with acceptable loss. To resolve this issue, a curve fitting based optimisation technique has been implemented in this work. Curve fitting determines the suitable value of the parameters from the set of given values for respective channel conditions. The simulation results demonstrate that the propounded method is more superior to the earlier channel estimation schemes where fixed values of averaging parameters have been chosen in each channel scenarios. This is due to the curve fitting optimisation, which enhances the dependency of α and β values on packet error rate (PER) equation and eventually on the channel conditions. The proposed method is examined deeply in multiple scenarios with different sets of parameters to test the strength and robustness of the suggested work. [ABSTRACT FROM AUTHOR]

Background and Objective: With the advent of the COVID-19 pandemic, face-to-face training was suspended considering social-distancing norms. The training needs of the healthcare workers (HCWs) were being met by the online mode. Initially, the use of the online mode was limited but was eventually popularized with increased use. This would have led to a change in the perception toward the online mode. However, the use of online learning has financial and temporal obstacles. With this objective, a study was conducted among the HCWs to assess the perception, satisfaction, and preference associated with the modes of learning. Methods: A cross-sectional study was conducted from February to April 2021 among the HCWs. An online link to the survey was circulated among the HCWs who attended online or/and offline training. The questionnaire had 38 questions assessing the sociodemographic details, perception, satisfaction level, and preferences of the participants. Univariable and multivariate logistic regression were performed using SPSS v-22. Results: A total of 1,113 responses were received with the mean age of 33.17 ± 8.13 years and approximately 63% of the participants were females. Approximately 54% perceived the online mode of learning as a better mode of learning. Also, 67% preferred and 80.5% recommended the online mode whereas mean satisfaction was found to be more for the offline mode as compared to the online mode. Interpretation and Conclusions: The study concludes that the online mode of learning is the most preferred and recommended mode among the HCWs, whereas there is more dissatisfaction with respect to the online mode. The study also emphasizes that the instructors need to improve the practical knowledge of the learners by integrating technical modalities. [ABSTRACT FROM AUTHOR]

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1468-5957.2009.02134.x Byline: Edward R. Lawrence (1), John Geppert (1), Arun J. Prakash (1) Keywords: Campbell Cochrane habit utility model; Hansen Jagannathan bounds; Burnside test; stochastic discount factor; external habit utility Abstract: Abstract: This paper tests whether the Campbell and Cochrane (1999) habit utility model generates a valid stochastic discount factor for the 25 Fama-French size/book-to-market and size/momentum sorted portfolios. Campbell and Cochrane (1999) derive a consumption based habit utility asset pricing model and calibrate it to aggregate US stock market data. However, they do not test whether their model is consistent with a larger cross section of asset returns. We test their model using the methodology of Hansen and Jagannathan (1991) and Burnside (1994). In contrast to previous studies, we find that for reasonable parameter values, the model's stochastic discount factor is inside the Hansen-Jagannathan bounds and therefore satisfies the necessary conditions for a valid stochastic discount factor. We trace the difference between our results and previous studies to the method used to estimate the model's parameters and the parameter values themselves. Author Affiliation: (1)The first and third authors are from Florida International University, Miami. The second author is from the University of Nebraska-Lincoln, NE. They would like to thank Martin Walker (editor) and an anonymous referee for their useful comments and suggestions. Article History: (Paper received May 2007, revised version accepted January 2009) Article note: (*) Address for correspondence: Arun J. Prakash, RB 206A, Department of Finance, College of Business Administration, Florida International University, Miami FL 33199, USA., e-mail: prakasha@fiu.edu

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1475-6803.2007.00219.x Byline: Duong Nguyen (1), Suchismita Mishra (2), Arun Prakash (2), Dilip K. Ghosh (3) Keywords: G12 Abstract: Abstract We examine whether the use of the three-moment capital asset pricing model can account for liquidity risk. We also make a comparative analysis of a four-factor model based on Fama-French and Pastor-Stambaugh factors versus a model based solely on stock characteristics. Our findings suggest that neither of the models captures the liquidity premium nor do stock characteristics serve as proxies for liquidity. We also find that sensitivities of stock return to fluctuations in market liquidity do not subsume the effect of characteristic liquidity. Furthermore, our empirical findings are robust to differences in market microstructure or trading protocols between NYSE/AMEX and NASDAQ. Author Affiliation: (1)University of Massachusetts, Dartmouth (2)Florida International University (3)Institute of Policy Analysis