PDE-constrained LDDMM via geodesic shooting and inexact Gauss-Newton-Krylov optimization using the incremental adjoint Jacobi equations

The class of non-rigid registration methods proposed in the framework of PDE-constrained Large Deformation Diffeomorphic Metric Mapping is a particularly interesting family of physically meaningful diffeomorphic registration methods. Inexact Newton-Krylov optimization has shown an excellent numerical accuracy and an extraordinarily fast convergence rate in this framework. However, the Galerkin representation of the non-stationary velocity fields does not provide proper geodesic paths. In this work, we propose a method for PDE-constrained LDDMM parameterized in the space of initial velocity fields under the EPDiff equation. The derivation of the gradient and the Hessian-vector products are performed on the final velocity field and transported backward using the adjoint and the incremental adjoint Jacobi equations. This way, we avoid the complex dependence on the initial velocity field in the derivations and the computation of the adjoint equation and its incremental counterpart. The proposed method provides geodesics in the framework of PDE-constrained LDDMM, and it shows performance competitive to benchmark PDE-constrained LDDMM and EPDiff-LDDMM methods

The Welfare Cost of Means-Testing: Pensioner Participation in Income Support

We estimate parametric and semi-parametric binary choice models of benefit take-up by British pensioners and develop methods, based on the compensating variation, of inferring the cash-equivalent value of disutility arising from stigma or complexity of the claims process, taking account of the self-selection induced by take-up. We extend this to incorporate the claim costs borne by welfare-recipients into the measurement of pensioner poverty. We find that allowing for implicit claim costs in this way has a non-negligible impact on poverty measurement.benefit take-up; program participation; pensions; welfare; poverty

Combining edge and cloud computing for mobility analytics

Mobility analytics using data generated from the Internet of Mobile Things (IoMT) is facing many challenges which range from the ingestion of data streams coming from a vast number of fog nodes and IoMT devices to avoiding overflowing the cloud with useless massive data streams that can trigger bottlenecks [1]. Managing data flow is becoming an important part of the IoMT because it will dictate in which platform analytical tasks should run in the future. Data flows are usually a sequence of out-of-order tuples with a high data input rate, and mobility analytics requires a real-time flow of data in both directions, from the edge to the cloud, and vice-versa. Before pulling the data streams to the cloud, edge data stream processing is needed for detecting missing, broken, and duplicated tuples in addition to recognize tuples whose arrival time is out of order. Analytical tasks such as data filtering, data cleaning and low-level data contextualization can be executed at the edge of a network. In contrast, more complex analytical tasks such as graph processing can be deployed in the cloud, and the results of ad-hoc queries and streaming graph analytics can be pushed to the edge as needed by a user application. Graphs are efficient representations used in mobility analytics because they unify knowledge about connectivity, proximity and interaction among moving things. This poster describes the preliminary results from our experimental prototype developed for supporting transit systems, in which edge and cloud computing are combined to process transit data streams forwarded from fog nodes into a cloud. The motivation of this research is to understand how to perform meaningfulness mobility analytics on transit feeds by combining cloud and fog computing architectures in order to improve fleet management, mass transit and remote asset monitoringComment: Edge Computing, Cloud Computing, Mobility Analytics, Internet of Mobile Things, Edge Fog Fabri

Equalizing Community Voice in an International Service-Learning Project: A Narrative Inquiry of a Social Entrepreneurial Peruvian Women\u27s Group

Traditionally, international service-learning (ISL) programs are created and led by host groups, which frequently overlook the international communities’ learning process and perspectives and the long-term impact of service missions on the community. Fundamentally, ISL is meant to address community needs. With the principal focus being on enriching students’ learning, community voice is often eclipsed. The research aim was to investigate the empowerment and efficacy of an ISL project to strengthen relationships between engaged scholars and international communities and improve future service-learning trips. Using a qualitive narrative research design, I investigated a 2021-2022 ISL Based Photovoice Project applying Kolb’s Experiential Learning (EL) Cycle and Dr. Dorothy Ettling’s Process of Empowerment Model as my principal frameworks. Photovoice (Wang & Burris, 1997) is a participatory research method designed to allow often marginalized groups to document their realities, create a narrative, and heighten public awareness on a social concern. According to Buck et al. (2019), Ettling’s model was used to create capacity in disadvantaged communities globally and at UIW, to align professors’ and students’ talents and abilities with the challenges of those vulnerable communities. This study’s sample consisted of a Chimbote-native RA and six Peruvian women, ages 55 to 75, who are all members of the same social entrepreneurship organization. Data collected for the study included seven individual, semi-structured interviews, photographs, and research journal/notes. In vivo and holistic coding were used to extract codes from the data for analysis, and Braun and Clarke’s (2006) six-step approach assisted in the identification of themes. To document and construct a narrative of my study participants’ journeys through the course of the project, Dan Harmon’s Story Circle was used. Six members of the Peruvian social entrepreneurial group, Pushaq Warmi, led workshops in three surrounding communities of Chimbote, Peru, including rural areas, providing education and awareness on coping and management of mental health issues brought on or exacerbated by the COVID pandemic in addition to domestic abuse in the home, demonstrating ways to motivate and inspire their female workshop participants. Pushaq Warmi used the Photovoice method to document their workshop experiences. A public exhibition of their work in Nuevo Chimbote raised awareness of leading mental health concerns women face in Peru and reinforced their group’s mission, as stated by one Pushaq Warmi member, “to bring development and well-being to women through training to strengthen organizational and leadership capacities” (personal communication, March 8, 2020). The findings explored the transformative experiences of the participants in an ISL project. The study revealed that Ettling’s Process of Empowerment together with Kolb’s theory of EL could be integrated effectively into community directed ISL projects. The study’s qualitative methodology shows how Dan Harmon’s Story Circle may be applied to document and analyze individual and collective growth. In this ISL Photovoice project, study participants underwent a transformative change fostered by the development of five components that promote individual and group empowerment: 1. Capacity building based on professional goals and community motives; 2. Purpose through motivation, inspiration, and knowledge-sharing; 3. Self-development and awareness through exposure to service oriented projects; 4. Collaboration stemming from group work; and 5. Building self-esteem and reinvigorating a commitment to social advocacy by community impact through service work. The study demonstrated the potential of international communities as co-developers of service-learning initiatives. As co-collaborators, students and faculty of ISL projects can empower international communities by providing them with knowledge and skills on self-directed participatory methods, with the understanding that the communities may employ these techniques in a manner that makes sense to them. This was Dr. Dorothy Ettling’s true vision. My work with the study participants in an ISL project underscored their ownership and control allowing community voice to flourish. The project introduced the group to a participatory method the women then tailored to their motives/agenda. Additionally, the project’s focus on the women’s capacity development demonstrated its sustainability potential. The instruction on Photovoice will continue to be drawn from and adapted by the women of Pushaq Warmi to educate and train different communities. The women they train will then be able to train other women. It is recommended that the traditional approach of student-centered learning in ISL projects shift to one of community-based learning. Faculty should also invest in establishing long-term relationships with groups, organizations, or members of the community at service sites. New projects must also involve local authorities, community agents, leaders of social organizations, and the general population. The results of this study will assist in the development of a UIW faculty service-learning handbook, which will focus on ISL projects based on long-term relationships/partnerships, community needs, a reflective process, and sustainability potential

Towards Smarter Electric Vehicle Charging with Low Carbon Smart Grids: Pricing and Control.

Environmental and political directions indicate transition to a decarbonized transportation system is necessary as it is one of the most pollutant sectors regarding greenhouse gas emissions. Research in Demand Side Management suggests that its tools are the most cost-effective option for improving the performance of the grid without incurring into high infrastructure investments, hence reducing the payback for start-ups in the sector. This Thesis proposes solutions to tackle 5 objectives around this area of research: 1-2 are related to developing a demand response pricing and EV smart charging strategies, 3-4 are related to developing a multi-objective charging scheme in order to ensure fairness and reduction of CO2eq emissions, and 5 is related to testing parameters of EV charging to understand future improvements and limitations in the proposed models. Chapter 3, that tackles objectives 1-2, proposes a data-driven optimisation algorithm with pricing and control modules that communicate with each other to achieve a successful integration with the grid by charging at the right price and expected time. The results show customers can be positively engaged with pricing signals while providing support to the grid. Chapter 4, which tackles objectives 3-4, proposes a multi-objective EV charging formulation that include perspectives of EV users, a carbon regulator and a charging station operator. The multi-objective formulation is solved with a genetic algorithm in order to find the fairest and the greenest solution. Results which are evaluated using different scenarios show different weights to each objective function can differ based on the charging location and EV charging availability. Finally, Chapter 5 which tackles objective 5, shows a sensitivity analysis where improvements in revenues, reduction of carbon emissions and bidding capacity depend on the evaluation of EV users’ parameters, and the charging station control and sizing

Bilingual consumer memory in the advergaming context: A cross-script comparison

Written language is the core of culture and central to marketing communications. The differences in language processing exhibited by Eastern/Western bilingual consumers are of great concern for global and multinational companies wishing to effectively promote their products through the Internet. Advergaming is a promotional method consisting of the delivery of advertising messages through electronic games. Despite recent scholarly interest, no previous research has compared brand memory across groups of bilinguals of different writing systems or scripts in the advergaming context. The dissertation investigated differences in brand memory of bilinguals of languages based on different scripts. Specifically, a logographic-based language (Chinese), a biscriptal language (Korean), and alphabetic-based languages (English and Spanish) were investigated. The purpose was to compare differences in brand recall and recognition across groups of bilinguals from China, Mexico, South Korea and the United States. Since high arousal levels might negatively influence cognitive capacity as generated by emotional intensity, the effect of arousal was also examined. The data collection procedure involved a series of international experiments. The experimental stimuli consisted of designated exposure to selected advergames. Following the gameplay in experiment 1, data was collected through translated surveys. In experiment 2, data was collected during the gameplay with aid of an electrocardiogram machine, and after the gameplay via self-reported measures of arousal. Four hundred subjects participated in experiment 1. Contrary to expectations, results indicated that alphabetic and biscriptal participants outperformed logographic participants. The main finding confirmed that second language proficiency is a key concept that should be included when comparing East/West bilingual consumers\u27 memory. Familiarity with brands was also a factor affecting both recall and recognition scores, indicated by significant differences among groups. Thirty additional subjects representing the script groups of interest participated in experiment 2. Triangulation of measures indicated that the physiological (heart rate) measures impact was the most salient. The most robust finding was the negative effect of physiological measures on recall scores. In sum, the effect of script, second language proficiency, prior brand familiarity and arousal in short-term brand memory was uncovered, in order to provide guidelines for an effective use of brand placements in advergames

The Social Media Grasp: Understanding Its Mediating Relationship to Social Media Use

Social media anxiety has become a focal point explaining continued use of social media despite aggressive social content. Using structural equation modeling, we examine a conceptual model explaining social media use that includes the constructs of social interactive anxiety, social media anxiety, and antisocial online behavior, which is divided into aggressive and non-aggressive antisocial cyber content. Our sample includes respondents of multiple age-groups that is representative of the actual social media population. We have surveyed users of six popular social media platforms including Facebook, Twitter, Instagram, Snapchat, Linked-In, and Pinterest. Results show that social anxious individuals participate more actively in social media when social media anxiety is present. Thus, despite increased social media anxiety, social anxious individuals remain online using social media platforms. We also see evidence that exposure to nonaggressive antisocial content leads to exposure to aggressive antisocial content. This aggressive antisocial content increases social media anxiety