Dependency Management in Distributed Settings (Poster Abstract)

Ubiquitous-computing environments are heterogeneous and volatile in nature. Systems that support ubicomp applications must be self-managed, to reduce human intervention. In this paper, we present a general service that helps distributed software components to manage their dependencies. Our service proactively monitors the liveness of components and recovers them according to supplied policies. Our service also tracks the state of components, on behalf of their dependents, and may automatically select components for the dependent to use based on evaluations of customized functions. We believe that our approach is flexible and abstracts away many of the complexities encountered in ubicomp environments. In particular, we show how we applied the service to manage dependencies of context-fusion operators and present some experimental results

Solar: An Open Platform for Context-Aware Mobile Applications

Emerging pervasive computing technologies transform the way we live and work by embedding computation in our surrounding environment. To avoid increasing complexity, and allow the user to concentrate on her tasks, applications in a pervasive computing environment must automatically adapt to their changing \em context, including the user state and the physical and computational environment in which they run. Solar is a middleware platform to help these “context-aware” applications aggregate desired context from heterogeneous sources and to locate environmental services depending on the current context. By moving most of the context computation into the infrastructure, Solar allows applications to run on thin mobile clients more effectively. By providing an open framework to enable dynamic injection of context processing modules, Solar shares these modules across many applications, reducing application development cost and network traffic. By distributing these modules across network nodes and reconfiguring the distribution at runtime, Solar achieves parallelism and online load balancing

Mining Frequent and Periodic Association Patterns

Profiling the clients\u27 movement behaviors is useful for mobility modeling, anomaly detection, and location prediction. In this paper, we study clients\u27 frequent and periodic movement patterns in a campus wireless network. We use offline data-mining algorithms to discover patterns from clients\u27 association history, and analyze the reported patterns using statistical methods. Many of our results reflect the common characteristics of a typical academic campus, though we also observed some unusual association patterns. There are two challenges: one is to remove noise from data for efficient pattern discovery, and the other is to interpret discovered patterns. We address the first challenge using a heuristic-based approach applying domain knowledge. The second issue is harder to address because we do not have the knowledge of people\u27s activities, but nonetheless we could make reasonable interpretation of the common patterns

MPCS: Mobile-based Patient Compliance System for Chronic Illness Care

More than 100 million Americans are currently living with at least one chronic health condition and expenditures on chronic diseases account for more than 75 percent of the $2.3 trillion cost of our healthcare system. To improve chronic illness care, patients must be empowered and engaged in health self-management. However, only half of all patients with chronic illness comply with treatment regimen. The self-regulation model, while seemingly valuable, needs practical tools to help patients adopt this self-centered approach for long-term care. \par In this position paper, we propose Mobile-phone based Patient Compliance System (MPCS) that can reduce the time-consuming and error-prone processes of existing self-regulation practice to facilitate self-reporting, non-compliance detection, and compliance reminders. The novelty of this work is to apply social-behavior theories to engineer the MPCS to positively influence patients\u27 compliance behaviors, including mobile-delivered contextual reminders based on association theory; mobile-triggered questionnaires based on self-perception theory; and mobile-enabled social interactions based on social-construction theory. We discuss the architecture and the research challenges to realize the proposed MPCS

MPCS: Mobile-based Patient Compliance System for Chronic Illness Care

More than 100 million Americans are currently living with at least one chronic health condition and expenditures on chronic diseases account for more than 75 percent of the $2.3 trillion cost of our healthcare system. To improve chronic illness care, patients must be empowered and engaged in health self-management. However, only half of all patients with chronic illness comply with treatment regimen. The self-regulation model, while seemingly valuable, needs practical tools to help patients adopt this self-centered approach for long-term care. \par In this position paper, we propose Mobile-phone based Patient Compliance System (MPCS) that can reduce the time-consuming and error-prone processes of existing self-regulation practice to facilitate self-reporting, non-compliance detection, and compliance reminders. The novelty of this work is to apply social-behavior theories to engineer the MPCS to positively influence patients\u27 compliance behaviors, including mobile-delivered contextual reminders based on association theory; mobile-triggered questionnaires based on self-perception theory; and mobile-enabled social interactions based on social-construction theory. We discuss the architecture and the research challenges to realize the proposed MPCS

School climate and left-behind children’s achievement motivation: The mediating role of learning adaptability and the moderating role of teacher support

School climate has been reported to have an important impact on children’s achievement motivation, but the mechanism for the impact of school climate on left-behind children has not been fully explored. The purpose of this study is to investigate the roles of left-behind children’s learning adaptability and teacher support in mediating and moderating the relationship between school climate and achievement motivation. In this study, 1,417 left-behind children were surveyed. The results showed that: (1) after controlling for gender and age, the school climate still had a positive effect on the achievement motivation of left-behind children (c′ = 0.177, p < 0.001). (2) School climate perceived by left-behind children directly predicted their achievement motivation, and indirectly through their learning adaptability (a1 = 0.338, p < 0.001; b = 0.341, p < 0.001). In other words, left-behind children’s learning adaptability may play an intermediary role between school climate and achievement motivation. (3) The indirect effect of school climate on achievement motivation through learning adaptability was moderated by teacher support (a2 = 0.153, p < 0.001), and this indirect effect was more significant for left-behind children who perceived high teacher support. The research reveals the importance of school climate and teacher support to the growth and development of left-behind children, thus holding theoretical significance for improving the achievement motivation of left-behind children

Immune Events Associated with High Level Protection against Schistosoma japonicum Infection in Pigs Immunized with UV-Attenuated Cercariae

BACKGROUND: The vaccination of radiation-attenuated Schistosoma japonicum cercariae can induce effective protection in artiodactyl, but the immune events related to protective immunity are not fully understood. To provide a paradigm for a human recombinant antigen vaccine, we have undertaken a vaccination and challenge experiment in pigs, which was recognized as an appropriate animal model in this type of study because of their similarity to human in immunology, and investigated the relative immune events induced by the radiation-attenuated S. japonicum cercariae. METHODS AND FINDINGS: We found that pigs immunized once with 400 µw UV-irradiated cercariae exhibited 63.84% and 71.82% reductions in worm burden and hepatic eggs respectively. Protective immunity in vaccinated pigs was associated with high level productions of IgM, total IgG, IgG1 and IgG2; IgG2 was significantly increased in the acute infection. IFN-γ levels could be elicited by immunization. At week 6 post-infection, IFN-γ, IL-4 and IL-10 levels also showed a dramatic rise synchronously in vaccinated pigs. Moreover, the granzyme b, nk-lysin, ifnγ, il4 and il10 mRNA levels in early skin-draining lymph nodes of immunized pigs were higher than those in pigs with non-irradiated cercariae infection. In addition, cytotoxicity-related genes in the mesenteric lymph nodes were significantly upregulated in vaccinated pigs in the acute infection. CONCLUSION/SIGNIFICANCE: Our results demonstrated that IFN-γ and IgG2 antibody production, as well as genes related to cytotoxicity are associated with the high level protection induced by UV-irradiated Schistosoma japonicum vaccine. These findings indicated that optimal vaccination against S. japonicum required the induction of IFN-γ, IgG2 antibody related to Th1 responses and cytotoxicity effect

Solar: Building A Context Fusion Network for Pervasive Computing

The complexity of developing context-aware pervasive-computing applications calls for distributed software infrastructures that assist applications to collect, aggregate, and disseminate contextual data. In this dissertation, we present a Context Fusion Network (CFN), called Solar, which is built with a scalable and self-organized service overlay. Solar is flexible and allows applications to select distributed data sources and compose them with customized data-fusion operators into a directed acyclic information flow graph. Such a graph represents how an application computes high-level understandings of its execution context from low-level sensory data. To manage application-specified operators on a set of overlay nodes called Planets, Solar provides several unique services such as application-level multicast with policy-driven data reduction to handle buffer overflow, context-sensitive resource discovery to handle environment dynamics, and proactive monitoring and recovery to handle common failures. Experimental results show that these services perform well on a typical DHT-based peer-to-peer routing substrate. In this dissertation, we also discuss experience, insights, and lessons learned from our quantitative analysis of the input sensors, a detailed case study of a Solar application, and development of other applications in different domains