Author: SRI International
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Fast and Slow Ion Diffusion Processes in Lithium Ion Pouch Cells during Cycling Observed with Fiber Optic Strain Sensors
In this present study, various charge-cycling experiments were performed on Lithium-ion pouch cells with a particular class of FO sensors, fiber Bragg gratings (FBGs), that were externally attached to the cells.
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Using Speech to Assess Post-Traumatic Stress Disorder in Veterans
Post-Traumatic Stress Disorder (PTSD) is a serious problem for the military – it affects at least 30 percent of military service members who have spent time in war zones. Not only does PTSD affect veterans, it also impacts their families and communities. Moreover, about eight percent of the civilian population is likely to develop PTSD at some point in…
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Can Inclusive STEM High Schools Narrow the STEM Gap for Under-Represented Students?
This week, SRI Education was honored to participate in the first-ever White House Summit on Next Generation High Schools, which included discussion on how to expand science, technology, engineering and mathematics (STEM) opportunities for groups under-represented in these high-growth fields (African Americans, Hispanics, females and students from low-income families). Previous research shows that many students, especially among those…
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Supporting Parent-Child Experiences with PEG+CAT Early Math Concepts: Report to the CPB-PBS Ready To Learn Initiative (Report Highlights)
The study presented here addresses the question of how time spent viewing and playing with PBS KIDS educational, non-commercial media at home, in family settings, can foster positive outcomes for children and parents/caregivers.
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Evaluation of Response to Intervention Practices for Elementary School Reading
This study examines the implementation of RtI in Grade 1–3 reading in 13 states during the 2011–12 school year, focusing on 146 schools that were experienced with RtI.
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Vertical Water Column Survey in the Gulf of Mexico Using Autonomous Underwater Vehicle SOTAB-I
An autonomous underwater vehicle (AUV) called the Spilled Oil and Gas Tracking Autonomous Buoy system (SOTAB-I) is being developed to perform onsite measurements of oceanographic data as well as dissolved chemical substances using underwater mass spectrometry.
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Supporting Parent-Child Experiences with PEG+CAT Early Math Concepts: Report to the CPB-PBS Ready To Learn Initiative (Executive Summary)
The study focused on PEG+CAT, a first-generation transmedia program designed to promote children’s mathematics and approaches to learning (ATL) skills.
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Supporting Parent-Child Experiences with PEG+CAT Early Math Concepts: Report to the CPB-PBS Ready To Learn Initiative (Full Report)
The study presented here addresses the question of how time spent viewing and playing with PBS KIDS educational, non-commercial media at home, in family settings, can foster positive outcomes for children and parents/caregivers.
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Broadening Student Participation in Secondary Computer Science Through Principled Assessment of Computational Thinking (PACT)
Despite recent increases in enrollment, women and minorities remain underrepresented in those attaining computer science (CS) degrees and entering CS careers. The low number of students taking advanced placement CS exams in high school, which is often used as a rough measure of student interest in pursuing CS in college, shows that we have a…
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Representation and Analysis of Additively Manufactured Parts
In this paper we show that as-manufactured shapes may be represented in terms of the convolution operation to capture the additive deposition of material, measure the conformance to nominal geometry in terms of overlap volume, and model uncertainties involved in material flow and process control.
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Device Health Estimation by Combining Contextual Control Information with Sensor Data and Device Health Prognostics Utilizing Restricted Boltzmann Machine
Beyond real- time data collection, we aim to provide analysis capability to obtain insights from the data and converting the learnings into actionable recommendations.
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Scalable Relational Learning for Large Heterogeneous Networks
In this paper, we propose parallel collective matrix factorization (PCMF) that serves as a fast and flexible framework for joint modeling of large heterogeneous networks.