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Social and Behavioral Sciences Commons™
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- Assistive Technology (1)
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Articles 1 - 10 of 10
Full-Text Articles in Social and Behavioral Sciences
User Feedback On Celebratory Technology Model For Reducing Stigma, Evelyn Lawrie, Daniel Dinh, Sav Avalos, Jack De Bruyn, Spencer Au, Christian Lopez, Ray Tan, Cyrus Fa'amafoe
User Feedback On Celebratory Technology Model For Reducing Stigma, Evelyn Lawrie, Daniel Dinh, Sav Avalos, Jack De Bruyn, Spencer Au, Christian Lopez, Ray Tan, Cyrus Fa'amafoe
Student Scholar Symposium Abstracts and Posters
Social stigma is a complex manifestation that affects humanity, particularly individuals with disabilities and other marginalized groups, including those with physical, cognitive, and emotional conditions. Society often judges these individuals' interactions with the world, and many technologies designed to assist those with disabilities attempt to change their daily interactions and behaviors. Nonetheless, when the emphasis is placed on validating disabled identities, there is a potential for it to be seen as "inspiration porn." This approach might inadvertently reduce inclusivity and do little to challenge negative stereotypes; it can also lead to the objectification of individuals with disabilities. Therefore, this project …
First Approximation Of Population Distributions On The International Space Station, Justin St. P. Walsh, Rao Hamza Ali, Alice C. Gorman, Amir Kanan Kashefi
First Approximation Of Population Distributions On The International Space Station, Justin St. P. Walsh, Rao Hamza Ali, Alice C. Gorman, Amir Kanan Kashefi
Art Faculty Articles and Research
This paper presents an analysis of data derived from thousands of publicly available photographs showing life on the International Space Station (ISS) between 2000 and 2020. Our analysis uses crew and locational information from the photographs’ metadata to identify the distribution of different population groups—by gender, nationality, and space agency affiliation—across modules of the ISS, for the first time. Given the significance of the ISS as the most intensively inhabited space habitat to date, an international cooperative initiative involving 26 countries and five space agencies, and one of the most expensive building projects ever undertaken by humans, developing an understanding …
Causes And Effects Of Shisper Glacial Lake Outburst Flood Event In Karakoram In 2022, Sandeep Kumar Mondal, Vatsal D. Patel, Rishikesh Bharti, Ramesh P. Singh
Causes And Effects Of Shisper Glacial Lake Outburst Flood Event In Karakoram In 2022, Sandeep Kumar Mondal, Vatsal D. Patel, Rishikesh Bharti, Ramesh P. Singh
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Karakoram Himalayas are vulnerable to glacial lake outburst floods (GLOFs), which cause catastrophic floods in the surrounding areas. The increasing natural and anthropogenic activities, especially in the Indo-Gangetic Plains at the southern flank of the towering Himalayas, could be the cause of climate change affecting the frequency of the natural hazards in the Himalayas. In the present study, a detailed analysis of the Shisper Lake breach of 7 May 2022 is carried out using satellite remote sensing. A decreasing trend in the glacial mass balance is observed between 2017 and 2021; in this period, frequent GLOF episodes occurred. A pronounced …
Application Of Model-Based Time Series Prediction Of Infrared Long-Wave Radiation Data For Exploring The Precursory Patterns Associated With The 2021 Madoi Earthquake, Jingye Zhang, Ke Sun, Junqing Zhu, Ning Mao, Dimitar Ouzounov
Application Of Model-Based Time Series Prediction Of Infrared Long-Wave Radiation Data For Exploring The Precursory Patterns Associated With The 2021 Madoi Earthquake, Jingye Zhang, Ke Sun, Junqing Zhu, Ning Mao, Dimitar Ouzounov
Mathematics, Physics, and Computer Science Faculty Articles and Research
Taking the Madoi MS 7.4 earthquake of 21 May 2021 as an example, this paper proposes using time series prediction models to predict the outgoing long-wave radiation (OLR) anomalies and study short-term pre-earthquake signals. Five time series prediction models, including autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM), were trained with the OLR time series data of the aseismic moments in the 5° × 5° spatial range around the epicenter. The model with the highest prediction accuracy was selected to retrospectively predict the OLR values during the aseismic period and before the earthquake in the area. It …
Ideology Prediction From Scarce And Biased Supervision: Learn To Disregard The “What” And Focus On The “How”!, Chen Chen, Dylan Walker, Venkatesh Saligrama
Ideology Prediction From Scarce And Biased Supervision: Learn To Disregard The “What” And Focus On The “How”!, Chen Chen, Dylan Walker, Venkatesh Saligrama
Business Faculty Articles and Research
We propose a novel supervised learning approach for political ideology prediction (PIP) that is capable of predicting out-of-distribution inputs. This problem is motivated by the fact that manual data-labeling is expensive, while self-reported labels are often scarce and exhibit significant selection bias. We propose a novel statistical model that decomposes the document embeddings into a linear superposition of two vectors; a latent neutral context vector independent of ideology, and a latent position vector aligned with ideology. We train an end-to-end model that has intermediate contextual and positional vectors as outputs. At deployment time, our model predicts labels for input documents …
Monitoring Dam Stability Using Psi And Sbas Analysis, Rejoice Thomas, Wenzhao Li, Shahryar Fazli, Nikolay Grisel Todorov, Hesham El-Askary
Monitoring Dam Stability Using Psi And Sbas Analysis, Rejoice Thomas, Wenzhao Li, Shahryar Fazli, Nikolay Grisel Todorov, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
Water preservation and maximization of its efficient use is key in areas facing water scarcity like California. One of the most important resources available to us are dams, which are useful to address a variety of needs like water supply, flood control, and maintaining environmental flows. However, if not managed properly, dams can be disastrous to humans and wildlife alike, different water species, habitats, and even impact water quality for a region. In this context, we have used newer Synthetic Aperture Radar Interferometry techniques like Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS) to estimate the displacement rates at …
Counterventions: A Reparative Reflection On Interventionist Hci, Rua Mae Williams, Louanne E. Boyd, Juan E. Gilbert
Counterventions: A Reparative Reflection On Interventionist Hci, Rua Mae Williams, Louanne E. Boyd, Juan E. Gilbert
Engineering Faculty Articles and Research
Research in HCI applied to clinical interventions relies on normative assumptions about which bodies and minds are healthy, valuable, and desirable. To disrupt this normalizing drive in HCI, we define a “counterventional approach” to intervention technology design informed by critical scholarship and community perspectives. This approach is meant to unsettle normative assumptions of intervention as urgent, necessary, and curative. We begin with a historical overview of intervention in HCI and its critics. Then, through reparative readings of past HCI projects in autism intervention, we illustrate the emergent principles of a counterventional approach and how it may manifest research outcomes that …
Para Cima Y Pa’ Abajo: Building Bridges Between Hci Research In Latin America And In The Global North, Pedro Reynolds-Cuéllar, Marisol Wong-Villacres, Karla A. Badillo-Urquiola, Mayra Donaji Barrera-Machuca, Franceli L. Cibrian, Marianela Ciolfi Felice, Carolina Fuentes, Laura Sanely Gaytán-Lugo, Vivian Genaro Motti, Monica Perusquía-Hernández, Oscar A. Lemus
Para Cima Y Pa’ Abajo: Building Bridges Between Hci Research In Latin America And In The Global North, Pedro Reynolds-Cuéllar, Marisol Wong-Villacres, Karla A. Badillo-Urquiola, Mayra Donaji Barrera-Machuca, Franceli L. Cibrian, Marianela Ciolfi Felice, Carolina Fuentes, Laura Sanely Gaytán-Lugo, Vivian Genaro Motti, Monica Perusquía-Hernández, Oscar A. Lemus
Engineering Faculty Articles and Research
The Human-computer Interaction (HCI) community has the opportunity to foster the integration of research practices across the Global South and North to begin overcoming colonial relationships. In this paper, we focus on the case of Latin America (LATAM), where initiatives to increase the representation of HCI practitioners lack a consolidated understanding of the practices they employ, the factors that influence them, and the challenges that practitioners face. To address this knowledge gap, we employ a mixed-methods approach, comprising a survey (66 respondents) and in-depth interviews (19 interviewees). Our analyses characterize a set of research perspectives on how HCI is practiced …
Timing And Magnitude Of Drought Impacts On Carbon Uptake Across A Grassland Biome, Andrew Felton, Gregory R. Goldsmith
Timing And Magnitude Of Drought Impacts On Carbon Uptake Across A Grassland Biome, Andrew Felton, Gregory R. Goldsmith
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Although drought is known to negatively impact grassland functioning, the timing and magnitude of these impacts within a growing season remains unresolved. Previous small-scale assessments indicate grasslands may only respond to drought during narrow periods within a year; however, large-scale assessments are now needed to uncover the general patterns and determinants of this timing. We combined remote sensing datasets of gross primary productivity and weather to assess the timing and magnitude of grassland responses to drought at 5 km2 temporal resolution across two expansive ecoregions of the western US Great Plains biome: the C4-dominated shortgrass steppe and …
Predicting Suicidal And Self-Injurious Events In A Correctional Setting Using Ai Algorithms On Unstructured Medical Notes And Structured Data, Hongxia Lu, Alex Barrett, Albert Pierce, Jianwei Zheng, Yun Wang, Chun Chiang, Cyril Rakovski
Predicting Suicidal And Self-Injurious Events In A Correctional Setting Using Ai Algorithms On Unstructured Medical Notes And Structured Data, Hongxia Lu, Alex Barrett, Albert Pierce, Jianwei Zheng, Yun Wang, Chun Chiang, Cyril Rakovski
Mathematics, Physics, and Computer Science Faculty Articles and Research
Suicidal and self-injurious incidents in correctional settings deplete the institutional and healthcare resources, create disorder and stress for staff and other inmates. Traditional statistical analyses provide some guidance, but they can only be applied to structured data that are often difficult to collect and their recommendations are often expensive to act upon. This study aims to extract information from medical and mental health progress notes using AI algorithms to make actionable predictions of suicidal and self-injurious events to improve the efficiency of triage for health care services and prevent suicidal and injurious events from happening at California's Orange County Jails. …