31 research outputs found
A Survey of Existing Programs for Problem Students in the First-Class Districts of Washington State
It was the purpose of this study to determine what programs were being used in the first-class school districts of Washington State for students who had problems that had caused, or could have caused, their removal from the regular classes, and to analyze these programs in light of other programs that seem to be successful throughout the nation
Case study: Bio-inspired self-adaptive strategy for spike-based PID controller
A key requirement for modern large scale
neuromorphic systems is the ability to detect and diagnose faults
and to explore self-correction strategies. In particular, to perform
this under area-constraints which meet scalability requirements
of large neuromorphic systems. A bio-inspired online fault
detection and self-correction mechanism for neuro-inspired PID
controllers is presented in this paper. This strategy employs a
fault detection unit for online testing of the PID controller; uses a
fault detection manager to perform the detection procedure
across multiple controllers, and a controller selection mechanism
to select an available fault-free controller to provide a corrective
step in restoring system functionality. The novelty of the
proposed work is that the fault detection method, using synapse
models with excitatory and inhibitory responses, is applied to a
robotic spike-based PID controller. The results are presented for
robotic motor controllers and show that the proposed bioinspired
self-detection and self-correction strategy can detect
faults and re-allocate resources to restore the controller’s
functionality. In particular, the case study demonstrates the
compactness (~1.4% area overhead) of the fault detection
mechanism for large scale robotic controllers.Ministerio de Economía y Competitividad TEC2012-37868-C04-0
Case Study - Spiking Neural Network Hardware System for Structural Health Monitoring
This case study provides feasibility analysis of adapting Spiking Neural Networks (SNN) based Structural Health Monitoring (SHM) system to explore low-cost solution for inspection of structural health of damaged buildings which survived after natural disaster that is, earthquakes or similar activities. Various techniques are used to detect the structural health status of a building for performance benchmarking, including different feature extraction methods and classification techniques (e.g., SNN, K-means and artificial neural network etc.). The SNN is utilized to process the sensory data generated from full-scale seven-story reinforced concrete building to verify the classification performances. Results show that the proposed SNN hardware has high classification accuracy, reliability, longevity and low hardware area overhead
Meta-analysis: the association of oesophageal adenocarcinoma with symptoms of gastro-oesophageal reflux
Aliment Pharmacol Ther 2010; 32: 1222–1227Endoscopic screening has been proposed for patients with symptoms of gastro-oesophageal reflux disease (GERD) in the hope of reducing mortality from oesophageal adenocarcinoma. Assessing the net benefits of such a strategy requires a precise understanding of the cancer risk in the screened population.To estimate precisely the association between symptoms of GERD and oesophageal adenocarcinoma.Systematic review and meta-analysis of population-based studies with strict ascertainment of exposure and outcomes.Five eligible studies were identified. At least weekly symptoms of GERD increased the odds of oesophageal adenocarcinoma fivefold (odds ratio = 4.92; 95% confidence interval = 3.90, 6.22), and daily symptoms increased the odds sevenfold (random effects summary odds ratio = 7.40, 95% confidence interval = 4.94, 11.1), each compared with individuals without symptoms or less frequent symptoms. Duration of symptoms was also associated with oesophageal adenocarcinoma, but with very heterogeneous results, and unclear thresholds.Frequent GERD symptoms are strongly associated with oesophageal adenocarcinoma. These results should be useful in developing epidemiological models of the development of oesophageal adenocarcinoma, and in models of interventions aimed at reducing mortality from this cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79186/1/j.1365-2036.2010.04471.x.pd
Artificial Neural Microcircuits for use in Neuromorphic System Design
Artificial Neural Networks (ANNs) are one of the most widely employed forms of biomorphic computation. However (unlike the biological nervous systems they draw inspiration from) the current trend is for ANNs to be structurally homogeneous. Furthermore, this structural homogeneity requires the application of complex training & learning tools that produce application specific ANNs, susceptible to pitfalls like overfitting. In this paper, an alternative approach is suggested, inspired by the role played in biology by Neural Microcircuits, the so called “fundamental processing elements” of organic nervous systems. How large neural networks can be assembled using Artificial Neural Microcircuits, intended as off-the-shelf components, is articulated; before showing the results of initial work to produce a catalogue of such Microcircuits though the use of Novelty Search
Barrett's esophagus: clinical features, obesity, and imaging
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87127/1/j.1749-6632.2011.06044.x.pd
Genetic Biomarkers of Barrett’s Esophagus Susceptibility and Progression to Dysplasia and Cancer: A Systematic Review and Meta-Analysis
Dr. Albert Petitpas teaching (ca. 1992)
A photograph of Al Petitpas, tenured professor of Psychology of Springfield College, teaching, ca. 1992. There are two students looking up at him.Dr. Albert Petitpas holds an Ed.D. in Counseling Psychology from Boston University and an M. Ed. in College Counseling from Northeastern University. Dr. Petitpas taught and has done research in Athletic Counseling and Career Development at Springfield College from 1978. Dr. Petitpas was the Director of the National Football Foundation Center for Youth Development Through Sport. Dr. Petitpas main interests were in youth development through sport, career development, transitions, and the role of counseling in the application of sport psychology. He also has taught courses such as Issues and Techniques in Counseling Athletes, Lab in Counseling Athletes, Principles of Counseling, and Career Development