Background. The use of mobile technology has become more prevalent within the delivery of healthcare (m-health) within the developing world. Its use is considered convenient and innovative, but little is known about its effectiveness. Although promising, there is a lack of literature pertaining to its overall effectiveness. Purpose. This study takes the perspectives of threes groups of key stakeholders to describe the m-health service and the perceived benefits of using the mobile health technology implemented by BRAC in the urban slums of Korail, within the capital city: Dhaka, Bangladesh. Methods. The study uses an exploratory descriptive case study design. The methodology includes demographic questionnaires, and semi-structured interviews. The sample included three groups: the BRAC developers, the community health workers (CHWs) and the villagers. Conclusion. This study described the perspectives of those involved with the service, defining the m-health service as well as highlighting four major themes: strengths and benefits, knowledge and awareness, challenges and barriers and areas of improvement. The emerging themes found in the study provide paradigms of what to expect when implementing pilot m-health innovation and suggests direction for growth and sustainability. / Thesis / Master of Science (MSc) / The purpose of the study is to understand the new mobile health (m-health) service started by BRAC in the urban slums of Dhaka Bangladesh. This is carried out by asking questions to the people who use the service the most: the BRAC developers, the community health workers (CHWs) and the villagers.

Mobile edge computing (MEC) has recently been introduced as a key technology, emerging in response to the increased focus on the emergence of new heterogeneous computing applications, resource-constrained mobile devices, and the long delay of traditional cloud data centers. Although many researchers have studied how the heterogeneous latency-critical application requirements can interact with the MEC system, very few have addressed how to deploy a flexible and scalable MEC infrastructure at the mobile operator for the expected heterogeneous mobile traffic. The proposed system model in this research project relies on the Network Function Virtualization (NFV) concept to virtualize the MEC infrastructure and provide scalable and flexible infrastructure regardless of the underlying physical hardware. In NFV-enabled networks, the received mobile workload is often deployed as Service Function Chains (SFCs), responsible for accomplishing users' service requests by steering traffic through different VNF types and virtual links. Thus, efficient VNF placement and orchestration mechanisms are required to address the challenges of the heterogenous users' requests, various Quality of Service (QoS) requirements, and network traffic dynamicity. This research project addresses the scalable design and dimensioning of an agile NFV-enabled MEC infrastructure problem from a dual perspective. First, a neural network model (i.e., a subset of machine learning) helps proactively auto-scale the various virtual service instances by predicting the number of SFCs required for a time-varying mobile traffic load. Second, the Mixed-Integer Linear Program (MILP) is used to create a physical MEC system infrastructure by mapping the predicted virtual SFC networks to the MEC nodes while minimizing deployment costs. Numerical results show that the machine learning (ML) model achieves a high prediction accuracy of 95.6%, which demonstrates the added value of using the ML technique at the edge network in reducing deployment costs while ensuring delay requirements for different latency-critical applications with high acceptance rates. Due to the exponential nature of this MILP formulation, we also propose a scalable bender decomposition approach with near-optimal results at a significantly reduced design and dimensioning cost. Numerical results show the viability of the bender decomposition approach in its proximity to the optimal dimensioning cost and in its reasonable solution time.

The current study was conducted with foreign language students enrolled in the summer course at Middlebury Institute of International Studies (MIIS), an intense foreign language program. The study measured and analyzed students' preferences toward mobile applications for learning a foreign language. Survey questionnaires were used to collect data on students' preferences of mobile delivery modes for learning a foreign language. The research design deployed was single-case design at two points-in-time, called repeated measures design in the t-test statistics, where effects-over-time of treatment (i.e., using a technological device) were tracked. The effects-over-time of using a mobile device for learning foreign language skills were significant and the magnitude of differences in students' attitudes between Weeks 2 and 8 was also significant. Students must have felt that their performance had changed at Week 8 and that using a smartphone could have been the difference. The structure and the research methodology of having null hypotheses that are tested statistically are both clear enough to provide a template for a replication of the study with a different sample. The statistical tests used by this study can be replicated with different research problems or a different audience.

Yes / This paper is concerned with the effects on the network performance of moving parts of what is considered traditionally to belong to the ground segment to on board the satellite. Initially, an overview of geostationary satellite communication systems and payload technology is presented, followed by a description of the network architecture and protocols that are the basis of the simulation models. The results obtained from this testbed are presented before concluding with a discussion of the results obtained.

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Sleep concerns are prevalent and can have a detrimental impact on the overall functioning of an individual. Nightmares, specifically, have been tied to a myriad of adverse mental health outcomes and are known to exacerbate other medical/mental health symptoms. Further, nightmares appear to persist after treatment of other concerns such as posttraumatic stress, depression, and anxiety. Although many treatments exist for nightmare disorder and posttraumatic nightmares, only Imagery Rehearsal Therapy has continuously been cited as first line treatment (Morgenthaler et al., 2018). Mobile health (mHealth) technology has emerged as a viable avenue for exploration in the mental health field as technological advances are becoming commonplace in integration of clinical practice to increase accessibility. Research suggests that using mobile modalities may be a feasible way to provide sleep interventions; however, research has yet to fully explore this possibility. This project assessed a mobile application called Dream EZ released by the National Center for Telehealth and Technology, which is based on Imagery Rehearsal Therapy, but has yet to conduct research on its effectiveness. The primary purposes of this project were to (1) explore the effectiveness of smartphone-based mHealth application treatment (Dream EZ) in reduction of psychological symptoms as compared to waitlist control and (2) evaluate adherence and acceptability of treatment via smartphone application. Findings from the study support use of mHealth nightmare treatment for nightmares distress reduction (main effect: p =.010, d = .53; interaction: p =.145, d = .30). Results regarding effectiveness of mHealth treatment were inconclusive as analyses were underpowered in relation to reduction of PTSD symptoms (main effect: p =.415, d = .17; interaction: p = .262, d = .23) and suicidality (main effect: p =.007, d = .57; interaction: p =.758, d = .07). Treatment adherence and acceptability were not significantly associated with nightmare symptom reduction. Although some hypotheses were underpowered, the strength of this study laid in its use of a randomized control trial hybrid-2 study design and its timely look at viability of technology use in clinical treatment. Future directions include replication within a clinical population and in various settings such as primary care clinics.

The rapid growth in the use of wireless communication and portable devices in recent years has created a great potential for a variety of mobile work technology support. However, we still lack the theories to explore the nature of mobile work, examine the needs for mobile work support, and identify the appropriate mobile technologies for various kinds of mobile work. This study is an attempt to meet the challenge. A mobile task model is proposed in this study which includes four dimensions: task complexity, task interdependence, time criticality, and location sensitivity. New instruments are developed to measure the constructs of time criticality and location sensitivity. Six typical mobile work support functions are examined: mobile communication, mobile information searching, mobile transaction processing, location related service, mobile job dispatching and mobile office. In light of contingency theory and attitude/behavioral theory, a research model is proposed to identify the ideal fit between task characteristics and typical mobile work support functions. Based on empirical data from real mobile workers, the nature of mobile work and the differences in mobile work between mobile knowledge workers and field workers are analysed. New instruments for the time and location related constructs are validated through the empirical data. The differences in perceived usefulness of the typical mobile work support functions between mobile knowledge workers and field workers are presented, as well as those of the current usage and intention to use. Finally, the ideal fit is identified on the basis of the empirical data. This study contributes both to theory and practice. The establishment of a mobile task model, including the development of new instruments for time and location constructs, provides a foundation for future mobile business research. The identification of the ideal fit between task characteristics and mobile technology functions, based on contingency theory and attitude/behavioral theory, extends and enriches mobile business research. The results of the study can provide guidance and recommendations on how to strategically plan and implement suitable mobile applications, and to identify opportunities for the development of appropriate technological solutions for mobile work support. / Thesis / Doctor of Philosophy (PhD)

No / Mobile language learning games usually only focus on spelling or out of context meaning for the entire dictionary, ignoring the role of an authentic environment. ‘Detective Alavi’ is an educational mobile game that provides a shared space for students to work collaboratively towards language learning in a narrative rich environment. This game motivates and preserves a conversation between learners and their teachers, and also between learners and learners, whilst being immersed in the story of the game. A seamless self-assessment scoring system in the game structure provides a less dominating environment for students to expose their weaknesses, and at the same time assists students to judge what skills they have learned and how much. This game has produced improvement in different cognitive processes and a deeper level of learning during the collaborative game play.