SRI International
-
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…
-
Synchrony of Anterior Cingulate Cortex and Insular-Striatal Activation Predicts Ambiguity Aversion in Individuals with Low Impulsivity
To test how dACC functional network connectivity would be modulated by uncertainty and differ between individuals, 24 healthy participants underwent functional MRI in 3 sequential runs: 1 resting-state and 2 decision-making task runs. Individuals with lower nonplanning impulsiveness made greater use of a Pass option and avoided uncertain ambiguous situations.
-
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.
-
Blended Learning Report
With funding from the Michael & Susan Dell Foundation, SRI’s Center for Technology in Learning studied the adoption of blended learning models in selected schools in California and Louisiana associated with five different charter management organizations during the 2011-12 school year. This research report presents the findings of this formative and summative research effort, including…
-
On the Feasibility of Deploying Cell Anomaly Detection in Operational Cellular Networks
In this paper, we build on our previous work and study the feasibility of an operational deployment of an adaptive ensemble-method framework for modeling cell behavior.
-
Forensic Prescreening System Using Coded Aperture Snapshot Spectral Imager
We present a camera system for instantaneous, non-destructive capture of spectral signatures for forensic analysis. Our system detects highly probative samples in the forensic scene mixed by the multiple target objects by combining a coded aperture snapshot spectral imager with a multi-spectral detection algorithm.
-
Late Fusion and Calibration for Multimedia Event Detection Using Few Examples
In this paper, we present two parametric approaches to late fusion: a normalization scheme for arithmetic mean fusion (logistic averaging) and a fusion scheme based on logistic regression, and compare them to widely used rule-based fusion schemes.
-
Unscented Transform for iVector-Based Noisy Speaker Recognition
In this paper, it is proposed to substitute the first order VTS by an unscented transform, where unlike VTS, the nonlinear function is not applied over the clean model parameters directly, but over a set of sampled points.
-
Effective Use of DCTS for Contextualizing Features for Speaker Recognition
This article proposes a new approach for contextualizing features for speaker recognition through the discrete cosine transform (DCT).