Novel approach for hybrid MAC scheme for balanced energy and transmission in sensor devices

<p><span>Hybrid medium access control (MAC) scheme is one of the prominent mechanisms to offer energy efficiency in wireless sensor network where the potential features for both contention-based and schedule-based approaches are mechanized. However, the review of existing hybrid MAC scheme shows many loopholes where mainly it is observed that there is too much inclusion of time-slotting or else there is an inclusion of sophisticated mechanism not meant for offering flexibility to sensor node towards extending its services for upcoming applications of it. Therefore, this manuscript introduces a novel hybrid MAC scheme which is meant for offering cost effective and simplified scheduling operation in order to balance the performance of energy efficiency along with data aggregation performance. The simulated outcome of the study shows that proposed system offers better energy consumption, better throughput, reduced memory consumption, and faster processing in contrast to existing hybrid MAC protocols.</span></p>

Ordered Weighted Averaging (OWA), Decision Making Under Uncertainty, and Deep Learning: How Is This All Related?

Among many research areas to which Ron Yager contributed are decision making under uncertainty (in particular, under interval and fuzzy uncertainty) and aggregation – where he proposed, analyzed, and utilized the use of Ordered Weighted Averaging (OWA). The OWA algorithm itself provides only a specific type of data aggregation. However, it turns out that if we allows several OWA stages one after another, we get a scheme with a universal approximation property – moreover, a scheme which is perfectly equivalent to deep neural networks. In this sense, Ron Yager can be viewed as a (grand)father of deep learning. We also show that the existing schemes for decision making under uncertainty are also naturally interpretable in OWA terms.

The Influence of Gender Equality on Volunteering Among European Senior Citizens

This research analyzes how gender equality influences the participation of European senior citizens in a range of volunteering activities (Social Awareness, Professional and Political, Education, and Religion). The main contribution is the simultaneous consideration of different levels of data aggregation: individual, national and welfare system. This allows conclusions to be drawn on the effects of variables linked to sociodemographic characteristics, gender equality and welfare systems. The empirical estimation utilised microdata from the World Values Survey (2005/09 and 2010/14) and the United Nations Development Programme. Results suggest that the European senior citizens appear to believe that they are more equal than the official statistics of their countries indicate. Men are more likely to participate in professional and education activities; women are more likely to be involved in religious organisations. Welfare systems influence volunteering behaviours. The promotion of macro-policies for gender equality could be important for increasing participation in non-profit organisations.