A Self-Learning MAC Protocol for Energy Harvesting and Spectrum Access in Cognitive Radio Sensor Networks

The fusion of Wireless Sensor Networks (WSNs) and Cognitive Radio Networks (CRNs) into Cognitive Radio Sensor Networks (CRSNs) is quite an attractive proposal, because it allows a distributed set of low-powered sensor nodes to opportunistically access spectrum bands that are underutilized by their licensed owners (called primary users (PUs)). In addition, when the PUs are actively transmitting in their own bands, sensor nodes can switch to energy harvesting mode to obtain their energy needs (for free), to achieve almost perpetual life. In this work, we present a novel and fully distributed MAC protocol, called S-LEARN, that allows sensor nodes in a CRSN to entwine their RF energy harvesting and data transmission activities, while intelligently addressing the issue of disproportionate difference between the high power necessary for the node to transmit data packets and the small amount of power it can harvest wirelessly from the environment. The presented MAC protocol can improve both the network throughput and total harvested energy, while being robust to changes in the network configuration. Moreover, S-LEARN can keep the cost of the system low, and it avoids the pitfalls from which centralized systems suffer

Transition Economies in the Middle East: the Syrian Experience

There have been no in depth studies of post Socialist transition in the Middle East. Syria’s experience is a useful one to explore given its historically important role in the region and its distinctive characteristics. The Syrian economic transition, from the early 1990s to 2011, was in two phases: an incremental liberalisation phase and a transition to Social Market Economy phase. During both phases, Syrian policy makers showed a preference for a gradualist approach to economic transition, rather than a big-bang approach. This was facilitated by oil revenues and subsidies from the Gulf States. The Syrian experience therefore has its own distinct characteristics, as well as elements in common with the transitions in other post Socialist economies

Examining Contextual Factors and Individual Value Dimensions of Healthcare Providers Intention to Adopt Electronic Health Technologies in Developing Countries

Part 5: Research in ProgressInternational audienceDespite substantial research on electronic health (e-Health) adoption, there still exist vast differences between resource-rich and resource-poor populations regarding Information Technology adoption. To help bridge the technological gulf between developed and developing countries, this research-in-progress paper examines healthcare providers’ intention to adopt e-health technologies from two perspectives 1) contextual factors (i.e. specific to developing world settings) and 2) individual value dimensions (i.e. cultural, utilitarian, social and personal). The primary output of this paper is a theoretical model merging both the contextual factors and value dimensions; this forms a strong baseline to examine and help ensure the successful adoption of e-Health technologies within developing countries. Future research will be performed to validate the model developed in this paper, with a specific focus on mobile Health in Malawi, Africa

A Self-Learning MAC Protocol for Energy Harvesting and Spectrum Access in Cognitive Radio Sensor Networks

The fusion of Wireless Sensor Networks (WSNs) and Cognitive Radio Networks (CRNs) into Cognitive Radio Sensor Networks (CRSNs) is quite an attractive proposal, because it allows a distributed set of low-powered sensor nodes to opportunistically access spectrum bands that are underutilized by their licensed owners (called primary users (PUs)). In addition, when the PUs are actively transmitting in their own bands, sensor nodes can switch to energy harvesting mode to obtain their energy needs (for free), to achieve almost perpetual life. In this work, we present a novel and fully distributed MAC protocol, called S-LEARN, that allows sensor nodes in a CRSN to entwine their RF energy harvesting and data transmission activities, while intelligently addressing the issue of disproportionate difference between the high power necessary for the node to transmit data packets and the small amount of power it can harvest wirelessly from the environment. The presented MAC protocol can improve both the network throughput and total harvested energy, while being robust to changes in the network configuration. Moreover, S-LEARN can keep the cost of the system low, and it avoids the pitfalls from which centralized systems suffer

Intrathecal pethidine: an alternative anaesthetic for transsurethral research of prostate?

We aimed to determine the usefulness of intrathecal pethidine as the sole anaesthetic for transurethral resection of prostate (TURP) while comparing the incidence of hypotension with intrathecal bupivacaine. A double-blinded randomized prospective trial was conducted involving 40 patients for TURP. The patients were divided equally into two groups; Group A received 2ml 0.5% bupivaccine intrathecally and group B received 40mg pethidine intrathecally. Changes in blood pressure and heart rate were measured over the first 30 minutes. The highest sensory block and the time to reach it were documented. The degree of motor blockade was also recorded. There was no significant difference in the incidence of hypotension. The pethidine group had significantly greater reduction in heart rate, a lower degree of motor block, shorter period before requests for postoperative analgesia but a higher incidence of sedation, nausea and vomiting. Intrathecal pethidine did not offer any advantage over intrathecal bupivaccine for TURP. Keywords: intrathecal pethidine, transurethral resection, prostate Mary Slessor Journal of Medicine Vol. 5 (1), 2005: 61-6

Symmetry of gamma distribution data about the mean after processing with EWMA function

Abstract Statistical Process Control (SPC) plays a vital role in maintaining quality and reducing variability in manufacturing processes. Among SPC techniques, the Exponentially Weighted Moving Average (EWMA) stands out for its ability to detect small process shifts quickly, making it a valuable tool in ensuring product consistency and preventing quality issues. EWMA constructs control charts to monitor process mean shifts, tracks product/service quality by identifying variations, and monitors manufacturing process parameters for early detection of deviations and necessary adjustments. EWMA control chart has been proposed as an alternative to the Shewhart control chart. Sequential measurements are processed using the EWMA function before being placed on the control chart. One of the crucial concerns about the EWMA control chart is the asymmetry of the data around the mean. Although processing with the EWMA function reduces data skewness, the problem of asymmetric data may not be solved. The control chart is designed to leave in front of the upper control limit (UCL) α/2 of the data and behind the lower control limit (LCL) another α/2 of the data, and this does not occur in the case of symmetric data. α/2 represents the significance level for each tail in a two-tailed hypothesis test, indicating the probability of incorrectly rejecting the null hypothesis for each side of the distribution. Since many of the distributions in real life can be approximated by the Gamma distribution, the Gamma distribution was adopted in this study. The Monte Carlo simulation methodology was implemented to generate Gamma distributed data, process it with EWMA function and assess the skewness and kurtosis. The purpose of this paper is to evaluate the effect of EWMA parameters on the performance of the EWMA control chart. Moreover, it focuses on skewness and kurtosis reduction after data processing using the EWMA function. The findings help researchers and practitioners to select the best parameters. Further, the research investigates the effect of EWMA parameter on the shape of distribution