PowerForecaster: Predicting power impact of mobile sensing applications at pre-installation time

This article presents a hierarchical context monitoring and composition framework that effectively supports next-generation context-aware services. The upcoming ubiquitous space will be covered with innumerable sensors and tiny devices, which ceaselessly pump out a huge volume of data. This data gives us an opportunity for numerous proactive and intelligent services. The services require extensive understanding of rich and comprehensive contexts in real time. The framework provides three hierarchical abstractions: PocketMon (personal), HiperMon (regional), and EGI (global). The framework provides effective approaches to combining context from each level, thereby allowing us to create a rich set of applications, not possible otherwise. It deals with an extensively broad spectrum of contexts, from personal to worldwide in terms of scale, and from crude to highly processed in terms of complexity. It also facilitates efficient context monitoring and addresses the performance issues, achieving a high level of scalability. We have prototyped the proposed framework and several applications running on top of it in order to demonstrate its effectiveness.11Nothe

Sandra Helps You Learn: The More You Walk, The More Battery Your Phone Drains

Emerging continuous sensing apps introduce new major factors governing phones' overall battery consumption behaviors: (1) added nontrivial persistent battery drain, and more importantly (2) different battery drain rate depending on the user's different mobility condition. In this paper, we address the new battery impacting factors significant enough to outdate users' existing battery model in real life. We explore an initial approach to help users understand the cause and effect between their physical activity and phones' battery life. To this end, we present Sandra, a novel mobility-aware smartphone battery information advisor, and study its potential to help users redevelop their battery model. We perform an extensive explorative study and deployment for 30 days with 24 users. Our findings reveal what they essentially learned, and in which situations they found Sandra very helpful. We share the lessons learned to help in the design of future mobility-aware battery advisors.1

PowerForecaster: Predicting Smartphone Power Impact of Continuous Sensing Applications at Pre-installation Time

Today's smartphone application (hereinafter 'app') markets miss a key piece of information, power consumption of apps. This causes a severe problem for continuous sensing apps as they consume significant power without users' awareness. Users have no choice but to repeatedly install one app after another and experience their power use. To break such an exhaustive cycle, we propose PowerForecaster, a system that provides users with power use of sensing apps at pre-installation time. Such advanced power estimation is extremely challenging since the power cost of a sensing app largely varies with users' physical activities and phone use patterns. We observe that the time for active sensing and processing of an app can vary up to three times with 27 people's sensor traces collected over three weeks. PowerForecaster adopts a novel power emulator that emulates the power use of a sensing app while reproducing users' physical activities and phone use patterns, achieving accurate, personalized power estimation. Our experiments with three commercial apps and two research prototypes show that PowerForecaster achieves 93.4% accuracy under 20 use cases. Also, we optimize the system to accelerate emulation speed and reduce overheads, and show the effectiveness of such optimization techniques.

ExerLink: Enabling Pervasive Social Exergames with Heterogeneous Exercise Devices

We envision that diverse social exercising games, or exergames, will emerge, featuring much richer interactivity with immersive game play experiences. Further, the recent advances of mobile devices and wireless networking will make such social engagement more pervasive - people carry portable exergame devices (e.g., jump ropes) and interact with remote users anytime, anywhere. Towards this goal, we explore the potential of using heterogeneous exercise devices as game controllers for a multi-player social exergame; e.g., playing a boat paddling game with two remote exercisers (one with a jump rope, and the other with a treadmill). In this paper, we propose a novel platform called ExerLink that converts exercise intensity to game inputs and intelligently balances intensity/delay variations for fair game play experiences. We report the design considerations and guidelines obtained from the design and development processes of game controllers. We validate the efficacy of game controllers and demonstrate the feasibility of social exergames with heterogeneous exercise devices via extensive human subject studies.

Structural basis for arginine glycosylation of host substrates by bacterial effector proteins

The bacterial effector proteins SseK and NleB glycosylate host proteins on arginine residues, leading to reduced NF-κB-dependent responses to infection. Salmonella SseK1 and SseK2 are E. coli NleB1 orthologs that behave as NleB1-like GTs, although they differ in protein substrate specificity. Here we report that these enzymes are retaining glycosyltransferases composed of a helix-loop-helix (HLH) domain, a lid domain, and a catalytic domain. A conserved HEN motif (His-Glu-Asn) in the active site is important for enzyme catalysis and bacterial virulence. We observe differences between SseK1 and SseK2 in interactions with substrates and identify substrate residues that are critical for enzyme recognition. Long Molecular Dynamics simulations suggest that the HLH domain determines substrate specificity and the lid-domain regulates the opening of the active site. Overall, our data suggest a front-face SNi mechanism, explain differences in activities among these effectors, and have implications for future drug development against enteric pathogens

Towards Interpersonal Assistants: Next-Generation Conversational Agents Opportunities With Always-on Microstructural Conversation Intervention Assistants

We propose novel interpersonal assistants, a next-generation conversational agent which is always-on, unobtrusively serving natural human-to-human conversations. We deepen the motivation and design insights with real practices in language delays and parent-child conflicts. We then present a common platform initiative to effectively support rapid development of interpersonal assistant applications, with a highlight on the key functional element of turn isolations and technical insights on microstructural dynamics.N

Towards Interpersonal Assistants: Next-Generation Conversational Agents Opportunities With Always-on Microstructural Conversation Intervention Assistants

We propose novel interpersonal assistants, a next-generation conversational agent which is always-on, unobtrusively serving natural human-to-human conversations. We deepen the motivation and design insights with real practices in language delays and parent–child conflicts. We then present a common platform initiative to effectively support rapid development of interpersonal assistant applications, with a highlight on the key functional element of turn isolations and technical insights on microstructural dynamics.11Nsciescopu