EETP-MAC: energy efficient traffic prioritization for medium access control in wireless body area networks

Wireless body area network (WBAN) has witnessed significant attentions in the healthcare domain using biomedical sensor-based monitoring of heterogeneous nature of vital signs of a patient’s body. The design of frequency band, MAC superframe structure, and slots allocation to the heterogeneous nature of the patient’s packets have become the challenging problems in WBAN due to the diverse QoS requirements. In this context, this paper proposes an Energy Efficient Traffic Prioritization for Medium Access Control (EETP-MAC) protocol, which provides sufficient slots with higher bandwidth and guard bands to avoid channels interference causing longer delay. Specifically, the design of EETP-MAC is broadly divided in to four folds. Firstly, patient data traffic prioritization is presented with broad categorization including Non-Constrained Data (NCD), Delay-Constrained Data (DCD), Reliability-Constrained Data (RCD) and Critical Data (CD). Secondly, a modified superframe structure design is proposed for effectively handling the traffic prioritization. Thirdly, threshold based slot allocation technique is developed to reduce contention by effectively quantifying criticality on patient data. Forth, an energy efficient frame design is presented focusing on beacon interval, superframe duration, and packet size and inactive period. Simulations are performed to comparatively evaluate the performance of the proposed EETP-MAC with the state-of-the-art MAC protocols. The comparative evaluation attests the benefit of EETP-MAC in terms of efficient slot allocation resulting in lower delay and energy consumption.

     

A simple approach to solving the kinematics of the 4-UPS/PS (3R1T) parallel manipulator

Journal of Mechanical Science and Technology - This work reports on the position, velocity and acceleration analyses of a four-degrees-of-freedom parallel manipulator, 4-DoF-PM for brevity, which...     

Comparison of Peleg and Azuara et al. models in the modeling mass transfer during pile salting of goat sheets

Application of the Peleg and Azuara et al. models for describing mass transfer during pile salting of goat sheets using different mixtures of NaCl, KCl, CaCl₂ and MgCl₂ was investigated The high coefficient of determination (R² > 0.97 and R² > 0.95 for Peleg and Azuara et al. models, respectively) and the modulus of mean relative errors (MRE < 10% for both models) indicated the acceptability of both Peleg and Azuara et al. models for predicting both moisture loss and salt uptake. The equilibrium moisture and salt contents were estimated using Peleg rate constants and Azuara et al. model parameters. Equilibrium moisture (x_w) and salt contents (x_s) varied from 0.522 to 0.860 g water/g db and from 0.311 to 0.352 g NaCl/g db respectively. Multiple comparison of means showed that x_w and x_s predicted by the Peleg model were lower than those estimated by the Azuara et al. model. The values differed by 1.86–13.6% for x_w and by 1.13–10.57% for x_s.     

Occupational therapy for people with physical disability using interactive environments

Universal Access in the Information Society - This paper preconizes the use of interactive environments as an accessible and inexpensive solution that allows supporting the recovery process of...     

Part-by-part dimensional error compensation in compliant sheet metal assembly processes

Dimensional variation in assembly processes is one of the most important issues that affect quality. Although robust design and statistical process quality control help to reduce this problem, they cannot be used for instant variation reduction during assembly operations, especially during process ramp-up. This paper introduces a complete methodology for dimensional-related error compensation in compliant sheet metal assembly processes. The proposed methodology is divided into two steps: (1) an off-line error control-learning module using virtual assembly models to determine necessary adjustments; and (2) an in-line control implementation using a feed-forward control strategy based on the learned adjustments. The off-line learning step focuses on determining control actions or corrections to compensate for the negative effects incoming part errors have on Key Product Characteristics. Specifically, it utilizes a newly developed iterative sampling method based on Kriging fitting to efficiently determine optimal control actions. The in-line feed-forward control identifies appropriate part-by-part adjustments using these learned control actions and incoming assembly component measurements. In this paper, two case studies are presented. First, a mathematical case study presents an empirical proof for the feasibility of the Iterative Sampling and Fitting Algorithm. Second, a simulation-based case study illustrates the effectiveness of the proposed methodology to improve dimensional quality in assembly operations for compliant sheet metal parts.     

Modeling offenses among motorcyclists involved in crashes in Spain

In relative terms, Spanish motorcyclists are more likely to be involved in crashes than other drivers and this tendency is constantly increasing. The objective of this study is to identify the factors that are related to being an offender in motorcycle accidents. A binary logit model is used to differentiate between offender and non-offender motorcyclists. A motorcyclist was considered to be offender when s/he had committed at least one traffic offense at the moment previous to the crash. The analysis is based on the official accident database of the Spanish general directorate of traffic (DGT) for the 2003–2008 time period. A number of explanatory variables including motorcyclist characteristics and environmental factors have been evaluated. The results suggest that inexperienced, older females, not using helmets, absent-minded and non-fatigued riders are more likely to be offenders. Moreover, riding during the night, on weekends, for leisure purposes and along roads in perfect condition, mainly on curves, predict offenses among motorcyclists. The findings of this study are expected to be useful in developing traffic policy decisions in order to improve motorcyclist safety.