Emergent interfaces: vague, complex, bespoke and embodied interaction between humans and computers

Most human-computer interfaces are built on the paradigm of manipulating abstract representations. This can be limiting when computers are used in artistic performance or as mediators of social connection, where we rely on qualities of embodied thinking: intuition, context, resonance, ambiguity, fluidity. We explore an alternative approach to designing interaction that we call the emergent interface: interaction leveraging unsupervised machine learning to replace designed abstractions with contextually-derived emergent representations. The approach offers opportunities to create interfaces bespoke to a single individual, to continually evolve and adapt the interface in line with that individual’s needs and affordances, and to bridge more deeply with the complex and imprecise interaction that defines much of our non-digital communication. We explore this approach through artistic research rooted in music, dance and AI with the partially emergent system Sonified Body. The system maps the moving body into sound using an emergent representation of the body derived from a corpus of improvised movement from the first author. We explore this system in a residency with three dancers. We reflect on the broader implications and challenges of this alternative way of thinking about interaction, and how far it may help users avoid being limited by the assumptions of a system’s designer

A Peer-reviewed Newspaper About_ Research Values

An interrogation of value and values in contemporary media and digital culture. Publication resulting from research workshop at Brandenburg Center for Media Studies – ZeM, Potsdam, organised in collaboration with Brandenburg Center for Media Studies – ZeM, Potsdam, and transmediale festival for art and digital culture, Berlin

Study of Women, Infant feeding, and Type 2 diabetes mellitus after GDM pregnancy (SWIFT), a prospective cohort study: methodology and design

<p>Abstract</p> <p>Background</p> <p>Women with history of gestational diabetes mellitus (GDM) are at higher risk of developing type 2 diabetes within 5 years after delivery. Evidence that lactation duration influences incident type 2 diabetes after GDM pregnancy is based on one retrospective study reporting a null association. The Study of Women, Infant Feeding and Type 2 Diabetes after GDM pregnancy (SWIFT) is a prospective cohort study of postpartum women with recent GDM within the Kaiser Permanente Northern California (KPNC) integrated health care system. The primary goal of SWIFT is to assess whether prolonged, intensive lactation as compared to formula feeding reduces the 2-year incidence of type 2 diabetes mellitus among women with GDM. The study also examines whether lactation intensity and duration have persistent favorable effects on blood glucose, insulin resistance, and adiposity during the 2-year postpartum period. This report describes the design and methods implemented for this study to obtain the clinical, biochemical, anthropometric, and behavioral measurements during the recruitment and follow-up phases.</p> <p>Methods</p> <p>SWIFT is a prospective, observational cohort study enrolling and following over 1, 000 postpartum women diagnosed with GDM during pregnancy within KPNC. The study enrolled women at 6-9 weeks postpartum (baseline) who had been diagnosed by standard GDM criteria, aged 20-45 years, delivered a singleton, term (greater than or equal to 35 weeks gestation) live birth, were not using medications affecting glucose tolerance, and not planning another pregnancy or moving out of the area within the next 2 years. Participants who are free of type 2 diabetes and other serious medical conditions at baseline are screened for type 2 diabetes annually within the first 2 years after delivery. Recruitment began in September 2008 and ends in December 2011. Data are being collected through pregnancy and early postpartum telephone interviews, self-administered monthly mailed questionnaires (3-11 months postpartum), a telephone interview at 6 months, and annual in-person examinations at which a 75 g 2-hour OGTT is conducted, anthropometric measurements are obtained, and self- and interviewer-administered questionnaires are completed.</p> <p>Discussion</p> <p>This is the first, large prospective, community-based study involving a racially and ethnically diverse cohort of women with recent GDM that rigorously assesses lactation intensity and duration and examines their relationship to incident type 2 diabetes while accounting for numerous potential confounders not assessed previously.</p

Level of student and teacher classroom interaction, school level and gender differences as predictors of self-regulated learning

The study explores student and teacher interaction, gender and school level as significant predictors of self regulated learning. The present research utilized a sequential explanatory mixed method research design to explore self-regulation among Filipino students in different school levels (N=300). Stepwise multiple regression analysis was utilized to determine strategy instruction, student-centered learning and gender as significant predictors of self-regulated learning. Also, in-depth interviews were conducted to explore further students\u27 different self-regulated learning strategies and teachers\u27 teaching strategies, and how these two variables are related

Global geomagnetic perturbation forecasting using deep learning

Geomagnetically Induced Currents (GICs) arise from spatio-temporal changes to Earth's magnetic field, which arise from the interaction of the solar wind with Earth's magnetosphere, and drive catastrophic destruction to our technologically dependent society. Hence, computational models to forecast GICs globally with large forecast horizon, high spatial resolution and temporal cadence are of increasing importance to perform prompt necessary mitigation. Since GIC data is proprietary, the time variability of the horizontal component of the magnetic field perturbation (dB/dt) is used as a proxy for GICs. In this work, we develop a fast, global dB/dt forecasting model, which forecasts 30 min into the future using only solar wind measurements as input. The model summarizes 2 hr of solar wind measurement using a Gated Recurrent Unit and generates forecasts of coefficients that are folded with a spherical harmonic basis to enable global forecasts. When deployed, our model produces results in under a second, and generates global forecasts for horizontal magnetic perturbation components at 1 min cadence. We evaluate our model across models in literature for two specific storms of 5 August 2011 and 17 March 2015, while having a self-consistent benchmark model set. Our model outperforms, or has consistent performance with state-of-the-practice high time cadence local and low time cadence global models, while also outperforming/having comparable performance with the benchmark models. Such quick inferences at high temporal cadence and arbitrary spatial resolutions may ultimately enable accurate forewarning of dB/dt for any place on Earth, resulting in precautionary measures to be taken in an informed manner.</p

Translation and Cross-Cultural Adaptation of English Version of Kiddy-KINDL to Filipino Language in Assessing the Children\u27s Health-Related Quality of Life (CHRQoL)

Background: Children\u27s health-related quality of life (CHRQoL) involves a child\u27s aim, expectations, standards, or concerns regarding overall health and its domains. The Kiddy-KINDL questionnaire is a tool to measure CHRQoL from information directly derived from children. It has been translated to various languages, except Filipino. This study would provide Filipino healthcare professionals with another functional tool for pediatric evaluation. Objective: To translate the English version of Kiddy-KINDL to Filipino and to determine its validity, test-retest reliability, and internal consistency of the Kiddy-KINDL in assessing the children\u27s health-related quality of life (CHRQoL). Methods: The study involved 3 Phases: Translation, Pilot Testing, and Reliability Phase. The English version of Kiddy-KINDL was cross-culturally adapted and translated into Filipino through a forward and backward translation process. Face validity was performed with 40 participants during the pilot testing phase. Test-retest reliability testing was performed with a total of 116 pairs of children, ages four to six, and their guardian living in Metropolitan Manila. Results: In phases 1 and 2, there were a total of 5 versions before the final Filipino version was considered acceptable. In phase 3, the test-retest reliability score of each dimension ranged from 0.18 to 0.98. The total reliability scores were 0.77 and 0.98 for adults and children, respectively. The internal consistency score was found to be acceptable in both questionnaires. Conclusion: The Filipino-translated Kiddy-KINDL has acceptable face validity results, test-retest reliability, and internal consistency scores