SRI International
-
Bayesian network model for predicting insider threats
This paper introduces a Bayesian network model for the motivation and psychology of the malicious insider.
-
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.
-
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…
-
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.
-
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…
-
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…
-
Design of a Peptide Inhibitor of Tyrosine Kinase 2
The development of antisense peptide inhibitors is a relatively unexplored area of research, and here we investigate inhibitory peptides specific for the Janus-associated kinase (JAK) family member, tyrosine kinase 2 (TYK2).
-
Poor Autonomic Nervous System Functioning During Sleep in Recently Detoxified Alcohol-Dependent Men and Women
We investigated nighttime ANS functioning, and the relation between ANS activity and severity of alcohol dependence in chronic alcoholism.
-
Robust Features and System Fusion for Reverberation-robust Speech Recognition
In this work, we present robust acoustic features motivated by the knowledge gained from human speech perception and production, and demonstrate that these features provide reasonable robustness to reverberation effects compared to traditional mel-filterbank-based features.
-
Characterization of High Frequency Neuronal Oscillations During a Sustained Attention Task in Cynomolgus Macaques Following NMDA Receptor Antagonism
-
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].
-
Neuroscience Meets Cryptography: Crypto Primitives Secure against Rubber Hose Attacks
We present a defense against coercion attacks using the concept of implicit learning from cognitive psychology. We use a carefully crafted computer game to plant a secret password in the participant’s brain without the participant having any conscious knowledge of the trained password.