Author: SRI International
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Additive Printing and Assembly for Large Area Electronic Systems
An example flexible hybrid system that wirelessly transmits data from multiple printed sensors will be described along with the considerations associated with fabrication of such a system (particularly mechanical and electrical interfacing of the printed and microelectronic elements).
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Bayesian network model for predicting insider threats
This paper introduces a Bayesian network model for the motivation and psychology of the malicious insider.
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From Printed Devices to Printed Hybrid Systems
In order to combine the benefits of digitally manufactured, mechanically flexible, distributed sensors and the high performance of silicon electronics we have developed a hybrid fabrication platform that allows for printed electronic devices to be used alongside a minimal set of pre-fabricated microelectronic components.
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Toward More Predictive Tests for Cancer Therapies
Understanding Clinical Drug Resistance at the Cellular Level Ninety-five percent of experimental cancer treatments fail during clinical development, with seventy percent of them proving to be ineffective in late phase II clinical trials. The scientific community agrees that a major reason for this failure is the lack of preclinical models that can accurately mimic cancer…
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Ganging Up on Big Data: Computer-Intermediated Collaborative Analysis
In this paper we consider opportunities for next generation analysis systems for teams, focusing on the computer-intermediated functions that support and coordinate analytic activities around big data.
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California Linked Learning District Initiative: Implications for the Future of High School Students
Since 2009, SRI Education has been funded by the James Irvine Foundation to evaluate the California Linked Learning District Initiative, an innovative approach to transforming the high school education experience through a combination of rigorous academics and work-based learning opportunities. Intended to make high school both engaging and relevant, the initiative’s goal is to effectively provide…
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How Do We Keep Students Engaged in Learning Science?
Children come to school with curiosity and questions about their world. As educators, we need to keep children curious and excited throughout their schooling—encouraging them to explore their environment, ask questions, make predictions about what they think will happen and why, and test those predictions. Toward this end, states have collaborated to develop a completely…
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Submodular Subset Selection for Large-Scale Speech Training Data
We address the problem of subselecting a large set of acoustic data to train automatic speech recognition (ASR) systems. To this end, we apply a novel data selection technique based on constrained submodular function maximization.
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DCAD: Dynamic Cell Anomaly Detection for Operational Cellular Networks
In this paper, we present Dynamic Cell Anomaly Detection (DCAD), a tool that implements an adaptive ensemble method for modeling cell behavior [5], [6].
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Effects of Thermal Treatment on Radiative Properties of HVPE Grown InP Layers
We have studied radiative properties of 21 micron thick InP layers grown by HVPE and found them comparable to those of best luminescent bulk InP virgin wafers. This opens up the possibility of implementing free-standing epitaxial InP scintillator structures endowed with surface photodiodes for registration of the scintillation.
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Towards Quantifying the Completeness of BDI Goals
We sketch a pragmatic but principled mechanism for quantifying the level of completeness of goals in a Belief-Desire-Intention–like agent.
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Articulatory features from neural networks and their role in speech recognition
This paper presents a deep neural network (DNN) to extract articulatory information from the speech signal and explores different ways to use such information in a continuous speech recognition task.