In this research we present a model for medication adherence from information systems and technologies (IS/IT) perspective. Information technology applications for healthcare have the potential to improve cost-effectiveness, quality and accessibility of healthcare. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. IS/IT perspective helps in leveraging the technology advancements to develop a health IT system for effectively measuring medication adherence and administering interventions. Majority of medication adherence studies have focused on average medication adherence. Average medication adherence is the ratio of the number of doses consumed and the number of doses prescribed. It does not matter in which order or pattern patients consume the dose. Patients with enormously diverse dosing behavior can achieve the same average levels of medication adher­ence. The same outcomes with different levels of ad­herence raise the possibility that patterns of adherence affect the effectiveness of medication adherence. We propose that medication adherence research should utilize effective medication adherence (EMA), derived by including both the pattern and average medication adherence for a patient. Using design science research (DSR) approach we have developed a model as an artifact for smart interventions. We have leveraged behavior change techniques (BCTs) based on the behavior change theories to design smart intervention. Because of the need for real time requirements for the system, we are also focusing on hierarchical control system theory and reference model architecture (RMA). The benefit of using this design is to enable an intervention to be administered dynamically on a need basis. A key distinction from existing systems is that the developed model leverages probabilistic measure instead of static schedule. We have evaluated and validated the model using formal proofs and by domain experts. The research adds to the IS knowledge base by providing the theory based smart interventions leveraging BCTs and RMA for improving the medication adherence. It introduces EMA as a measurement of medication adherence to healthcare systems. Smart interventions based on EMA will further lead to reducing the healthcare cost by improving prescription outcomes.

Software-intensive systems are increasingly expected to operate under changing and uncertain conditions, including not only varying user needs and workloads, but also fluctuating resource capacity. Self-adaptation is an approach that aims to address this problem, giving systems the ability to change their behavior and structure to adapt to changes in themselves and their operating environment without human intervention. Self-adaptive systems tend to be reactive and myopic, adapting in response to changes without anticipating what the subsequent adaptation needs will be. Adapting reactively can result in inefficiencies due to the system performing a suboptimal sequence of adaptations. Furthermore, some adaptation tactics—atomic adaptation actions that leave the system in a consistent state—have latency and take some time to produce their effect. In that case, reactive adaptation causes the system to lag behind environment changes. What is worse, a long running adaptation action may prevent the system from performing other adaptations until it completes, further limiting its ability to effectively deal with the environment changes. To address these limitations and improve the effectiveness of self-adaptation, we present proactive latency-aware adaptation, an approach that considers the timing of adaptation (i) leveraging predictions of the near future state of the environment to adapt proactively; (ii) considering the latency of adaptation tactics when deciding how to adapt; and (iii) executing tactics concurrently. We have developed three different solution approaches embodying these principles. One is based on probabilistic model checking, making it inherently able to deal with the stochastic behavior of the environment, and guaranteeing optimal adaptation choices over a finite decision horizon. The second approach uses stochastic dynamic programming to make adaptation decisions, and thanks to performing part of the computations required to make those decisions off-line, it achieves a speedup of an order of magnitude over the first solution approach without compromising optimality. A third solution approach makes adaptation decisions based on repertoires of adaptation strategies— predefined compositions of adaptation tactics. This approach is more scalable than the other two because the solution space is smaller, allowing an adaptive system to reap some of the benefits of proactive latency-aware adaptation even if the number of ways in which it could adapt is too large for the other approaches to consider all these possibilities. We evaluate the approach using two different classes of systems with different adaptation goals, and different repertoires of adaptation strategies. One of them is a web system, with the adaptation goal of utility maximization. The other is a cyberphysical system operating in a hostile environment. In that system, self-adaptation must not only maximize the reward gained, but also keep the probability of surviving a mission above a threshold. In both cases, our results show that proactive latency-aware adaptation improves the effectiveness of self-adaptation with respect to reactive time-agnostic adaptation.

Mobile Ad-Hoc Network (MANET) facilitates the creation of dynamic reconfigurable networks, without centralized infrastructure. MANET routing protocols have to face high challenges like link instability, node mobility, frequently changing topologies and energy consumption of node, due to these challenges routing becomes one of the core issues in MANETs. This Thesis mainly focuses on the reactive routing protocol such as Ad-Hoc On-Demand Distance Vector (AODV) routing protocol. Reliable and Efficient Reactive Routing Protocol (RERRP) for MANET has been proposed to reduce the link breakages between the moving nodes. This scheme selects a reliable route using Reliability Factor (RF); the RF considers Route Expiration Time and Hop Count to select a routing path with high reliability and have less number of hops. The simulation result shows that RERRP outperforms AODV and enhance the packet delivery fraction (PDF) by around 6% and reduces the network routing load (NRL) by around 30%. Broadcasting in MANET could cause serious redundancy, contention, and collision of the packets. A scheme, Effective Broadcast Control Routing Protocol (EBCRP) has been proposed for the controlling of broadcast storm problem in a MANET. The EBCRP is mainly selects the reliable node while controlling the redundant re-broadcast of the route request packet. The proposed algorithm EBCRP is an on-demand routing protocol, therefore AODV route discovery mechanism was selected as the base of this scheme. The analysis of the performance of EBCRP has revealed that the EBCRP have controlled the routing overhead significantly, reduces it around 70% and enhance the packet delivery by 13% as compared to AODV. An Energy Sensible and Route Stability Based Routing Protocol (ESRSBR) have also been proposed that mainly focuses on increasing the network lifetime with better packet delivery. The ESRSBR supports those nodes to participate in the data transfer that have more residual energy related to their neighbour nodes. The proposed protocol also keeps track of the stability of the links between the nodes. Finally, the ESRSBR selects those routes which consist of nodes that have more residual energy and have stable links. The comparative analysis of ESRSBR with AODV and recently proposed routing protocol called Link Stability and Energy Aware (LSEA) routing protocol revealed that the proposed protocol ESRSBR has a significantly affect the network lifetime, increases it around 10% and 13% as compared to LSEA and AODV protocols respectively. The ESRSBR also decreases the routing overhead by 22% over LSEA and by 38% over AODV.

Context-aware computing utilizes information about users and/or their environments in order to provide relevant information and services. To date, however, most context-aware applications only take advantage of contexts that can either be produced on the device they are running on, or on external devices that are known beforehand. While there are many application domains where sharing context is useful and/or necessary, creating these applications is currently difficult because there is no easy way for devices to share information without 1) explicitly directing them to do so, or 2) through some form of advanced user coordination (e.g., sharing credentials and/or IP addresses, installing and running the same software). This makes these techniques useful when the need to share context is known a priori, but impractical for the one time, opportunistic encounters which make up the majority of users’ lives. To address this problem, this thesis presents the Group Context Framework (GCF), a software framework that allows devices to form groups and share context with minimal prior coordination. GCF lets devices openly discover and request context from each other. The framework then lets devices intelligently and autonomously forms opportunistic groups and work together without requiring either the application developer or the user to know of these devices beforehand. GCF supports use cases where devices only need to share information once or spontaneously. Additionally, the framework provides standardized mechanisms for applications to collect, store, and share context. This lets devices form groups and work together, even when they are performing logically separate tasks (i.e., running different applications). Through the development of GCF, this thesis identifies the conceptual and software abstractions needed to support opportunistic groups in context-aware applications. As part of our design process, we looked at current contextsharing applications, systems, and frameworks, and developed a conceptual model that identifies the most common conditions that cause users/devices to form a group. We then created a framework that supports grouping across this entire model. Through the creation of four prototype systems, we show how the ability to form opportunistic groups of devices can increase users and devices’ access to timely information and services. Finally, we had 20 developers evaluate GCF, and verified that the framework supports a wide range of existing and novel use cases. Collectively, this thesis demonstrates the utility of opportunistic groups in context-aware computing, and highlights the critical challenges that need to be addressed to make opportunistic context sharing both practical and usable in real-world settings. The contributions of this thesis are: 1. A conceptual model, based on an analysis of prior literature, which describes the conditions under which users and/or devices form and work in groups. 2. An implementation of the Group Context Framework, which highlights the software abstractions and architecture needed to support all of the group types identified in our conceptual model. 3. A demonstration of the value of opportunistic groups in context aware computing, through the creation of four major systems and numerous smaller applications. 4. A validation of GCF’s robustness, through an examination of 65 ideas submitted by 20 developers. 5. An examination of the challenges associated with utilizing opportunistic groups in context-aware applications, based on our own experiences using GCF, as well as from issues raised by developers from academia and industry.

Recent technological advances have witnessed the rapid encroachment of computing systems into our social spaces. Their acceptance in these social spaces by other occupants, however, might be mostly contingent on their social appropriateness. Notions of social appropriateness might seem vague but even people who don’t act on this commonsense knowledge, and accord to social norms, can sometimes find themselves ostracized from society. It is reflected in behavior that supports a sense of successful engagement and connection. Such behavior communicates a desire to be accepted and a willingness to engage, as opposed to inappropriateness that conveys indifference, rejection or even danger. As social actors, how can systems improve their interactions with us in order to better succeed at their tasks? Perhaps, more interestingly, how might they even improve our communications with each other? In this thesis we describe a framework to identify opportunities to design systems that can begin to act appropriately in social settings, which we call Considerate Systems. It includes a design process and guidelines, which allows an interaction to be viewed from the perspectives of the user, system and task. It also includes an architecture that guides the addition of productive social responses to interactive systems. We demonstrate the utility of this framework by exploring two types of scenarios that impact social interactions in contrasting ways. Remote interactions (such as on a conference call) suffer from an impinging of social cues that people rely on while communicating. On the other hand, situated multitasking interactions (such as texting while driving) can easily overwhelm users and detract from their performance. The framework is applied towards the design of autonomous agents tackling problems endemic to such scenarios. We evaluate their success with respect to specific scenario goals. We conclude by noting that while the challenges of instilling computing systems with a sense of appropriateness seem daunting, our productive use of systems can be enhanced with them.

Master of Science / Department of Electrical and Computer Engineering / Balasubramaniam Natarajan / Space-time coding (STC) schemes for Multiple Input Multiple Output (MIMO) systems have been an area of active research in the past decade. In this thesis, we propose a novel design of Space-Time Block Codes (STBCs) using Redundant Residue Number System (RRNS) codes, which are ideal for high data rate communication systems. Application of RRNS as a concatenated STC scheme to a MIMO wireless communication system is the main motivation for this work. We have optimized the link between residues and complex constellations by incorporating the “Direct Mapping” scheme, where residues are mapped directly to Gray coded constellations. Knowledge of apriori probabilities of residues is utilized to implement a probability based “Distance-Aware Direct Mapping” (DA) scheme, which uses a set-partitioning approach to map the most probable residues such that they are separated by the maximum possible distance. We have proposed an “Indirect Mapping” scheme, where we convert the residues back to bits before mapping them. We have also proposed an adaptive demapping scheme which utilizes the RRNS code structure to reduce the ML decoding complexity and improve the error performance. We quantify the upper bounds on codeword and bit error probabilities of both Systematic and Non-systematic RRNS-STBC and characterize the achievable coding and diversity gains assuming maximum likelihood decoding (MLD). Simulation results demonstrate that the DA Mapping scheme provides performance gain relative to a Gray coded direct mapping scheme. We show that Systematic RRNS-STBC codes provide superior performance compared to Nonsystematic RRNS-STBC, for the same code parameters, owing to more efficient binary to residue mapping. When compared to other concatenated STBC and Orthogonal STBC (OSTBC) schemes, the proposed system gives better performance at low SNRs.

A Computação Ubíqua está revolucionando a interação do ser-humano com os dispositivos computacionais ao disponibilizar tecnologias pouco intrusivas ao cotidiano das pessoas. A Computação Ciente de Contexto, um dos temas de pesquisa em Computação Ubíqua, tem contribuído para a construção de aplicações capazes de customizar-se e adaptar-se às necessidades do usuário sem a intervenção explícita deste. Suportar o desenvolvimento de aplicações Cientes de Contexto é um dos desafios da Computação Ubíqua. Desenvolvido no mesmo grupo de pesquisa que este trabalho está inserido, o Serviço Web Context Kernel, gerencia informações de contexto e explora as especificações e tecnologias da Web como plataforma de intercâmbio para a informação contextual. O trabalho aqui reportado teve como objetivo investigar a utilização de Serviços Web por meio do emprego da infra-estrutura Context Kernel na integração de aplicações em cenários de trabalho colaborativo e de aprendizado eletrônico. Como resultado, foi elaborado um conjunto de lições aprendidas provenientes do estudo e do emprego das especificações para Serviços Web. Outros resultados foram: as especificações de informações de contexto de grupo e de metadados educacionais em dimensões de contexto e exemplos de utilização do Context Kernel para tornar aplicações cientes de contexto. / Ubiquitous computing has became a revolution in terms of the user-computer interaction by providing technologies that seamlessly integrate themselves to people?s everyday life. Context-aware computing, which is an important research theme in ubiquitous computing, has been contributing for the building of applications that are capable both to customize and adapt themselves aiming to support a user without disturb him. A great challenge in ubiquitous computing has been the support to build context-aware aplications. For that reason, the it has been developed the Context Kernel Web Service, which is a service infrastructure that makes use of Web-based specifications and technologies in order to promote the management and the interchange of context information. In this work the usage of Web Services was analyzed by using the Context Kernel to integrate applications in scenarios of cooperative work and e-learning. As a result, a list of lessons learned was ellaborated with respect to the use and the study of Web Services specifications for context-aware computing. Other results include a context information specifications for metadata about group and educational resources as well as examples of how to use the Context Kernel to leverage applications context-aware.

Com os avanços dos processos da microeletrônica temos dispositivos menores e com maior poder de computação e comunicação. Um Ambiente Pervasivo contém diferentes dispositivos, tais como sensores, atuadores, eletroeletrônicos e dispositivos móveis que interagem com a pessoa de forma natural ao conhecer o contexto. A diversidade de dispositivos e informações do Ambiente Pervasivo introduz um problema de interoperabilidade. Um Ambiente Pervasivo é dinâmico devido à mobilidade do usuário, a variedade de dispositivos. Neste trabalho, é proposto um modelo semântico de contexto para permitir interoperabilidade e fornecer suporte ao dinamismo do Ambiente Pervasivo. O modelo proposto contém características da modelagem de contexto realizadas por trabalhos anteriores, assim como sua integração com a modelagem de preferências das pessoas, políticas de privacidade e serviços. Verificou-se que o modelo de contexto proposto é adequado mediante sua aplicação em um Estudo de Caso e mediante testes realizados. Mostra-se que a modelo de contexto utilizado ontologias e Serviços Web Semânticos permite tratar com informação incompleta e inconsistente, bem como fornece suporte na interoperabilidade e ao dinamismo do Ambiente Pervasivo. / Advances in microelectronic processes have allowed smaller devices with more computation and communication power. Pervasive environment contains different devices like electronic sensor, actuators and mobile devices which interact with the person naturally after the context is known. The device and information diversity introduce an interoperability problem. Pervasive environments are dynamics because of user\'s mobility and a variety of devices. In this work, we propose a context model to allow interoperability and to give support to pervasive environment dynamism. The proposed model contains features of context modeling developed in previous works, as well as, their integration with the modeling of the people\'s preferences, privacy policies and services. It was verified that the context model is appropriate by their application in a Case Study and by accomplished tests. It is shown that the model of context using ontologies and Semantic Web Services allow us to work with inconsistent and incomplete information, as well as gives support to interoperability and dynamism of the Pervasive Environment.

No description available.

"Due to the dramatic growth in the use of Wireless Sensor Network (WSN) applications - ranging from environment and habitat monitoring to tracking and surveillance, network research in WSN protocols has been very active in the last decade. With battery-powered sensors operating in unattended environments, energy conservation becomes the key technique for improving WSN lifetimes. WSN Medium Access Control (MAC) protocols address energy awareness and reduced duty cycles since the radio is the component that consumes most of the energy. This thesis investigates the performance of two recently published energy-aware MAC protocols, Crankshaft and SCP-MAC. Crankshaft has been shown to be one of the best protocols in terms of energy consumption in dense WSNs while SCP-MAC has a dedicated low duty cycle and low average latencies. The focus of this investigation is to discover techniques for reducing the latency of Crankshaft. Using OMNeT++, an open source and component-based simulation framework, this study investigates possible modifications to Crankshaft to improve its latency. The potential improvements considered include modifications to Crankshaft’s retransmission contention scheme (Sift), adjustments to its inherent settings, and investigating the impact of ACKs. Since OMNeT++ readily provided only a variant of SCP-MAC identified as SCP-MAC*, the simulations results presented involve comparing variants of both protocols (Crankshaft and SCP-MAC*). The performance of these protocols is also analyzed using distinct sensor node communication patterns. It was determined that Crankshaft’s latency depends on its ACK/Retransmission settings. Specifically, Crankshaft has the best latency with No ACKs, without much loss in energy consumption. But the latency can also be improved when ACKs are enabled by reducing the number of retries. Furthermore, the latency and delivery ratio are also directly governed by the WSN traffic pattern and the congestion in the network, as there was a noticeable improvement for both parameters in one-hop traffic, compared to multi-hop convergecast traffic to the sink. Finally, it was observed that Crankshaft’s broadcast performance in flooding traffic can be improved by increasing the number of broadcast slots used, though this is detrimental to its performance in unicast traffic."