Modeling Data-Plane Power Consumption of Future Internet Architectures

With current efforts to design Future Internet Architectures (FIAs), the evaluation and comparison of different proposals is an interesting research challenge. Previously, metrics such as bandwidth or latency have commonly been used to compare FIAs to IP networks. We suggest the use of power consumption as a metric to compare FIAs. While low power consumption is an important goal in its own right (as lower energy use translates to smaller environmental impact as well as lower operating costs), power consumption can also serve as a proxy for other metrics such as bandwidth and processor load. Lacking power consumption statistics about either commodity FIA routers or widely deployed FIA testbeds, we propose models for power consumption of FIA routers. Based on our models, we simulate scenarios for measuring power consumption of content delivery in different FIAs. Specifically, we address two questions: 1) which of the proposed FIA candidates achieves the lowest energy footprint; and 2) which set of design choices yields a power-efficient network architecture? Although the lack of real-world data makes numerous assumptions necessary for our analysis, we explore the uncertainty of our calculations through sensitivity analysis of input parameters

Tracking the affective state of unseen persons.

Emotion recognition is an essential human ability critical for social functioning. It is widely assumed that identifying facial expression is the key to this, and models of emotion recognition have mainly focused on facial and bodily features in static, unnatural conditions. We developed a method called affective tracking to reveal and quantify the enormous contribution of visual context to affect (valence and arousal) perception. When characters' faces and bodies were masked in silent videos, viewers inferred the affect of the invisible characters successfully and in high agreement based solely on visual context. We further show that the context is not only sufficient but also necessary to accurately perceive human affect over time, as it provides a substantial and unique contribution beyond the information available from face and body. Our method (which we have made publicly available) reveals that emotion recognition is, at its heart, an issue of context as much as it is about faces

Managing Wireless Networks in the Healthcare Sector: Emerging Experiences of Cultural Impacts

The existing body of knowledge has generally supported that organizational culture plays a significant role in shaping group identity, work pattern, communication schemes, and interpersonal relations; all of these cultural elements are important organizational factors that shape workplaces and operational routines. In the context of emerging information technology, it has also been suggested that organizational culture could affect IT implementation and management. However, little is known about how emerging information technology shapes organizational culture, which in turn helps reshape the organization as a whole. The purpose of this paper is thus to build empirical understanding of how IT in general and emerging wireless networks in particular reshapes organizational culture. Case studies conducted in two hospitals situated in southwest U.S.A. illustrated that the implementation of wireless networks indeed helped shape and/or reshape organizational culture in the healthcare sector and in turn enhance healthcare organizations’ competitiveness in the marketplace. For IT managers and practitioners in healthcare institutions, effective strategy to plan and manage emerging ITs such as wireless networks will thus have long-term implications on cultivating organizational culture that could eventually reshape workplace and competitiveness