Wireless Sensor Networks for Condition Monitoring in the Railway Industry : a Survey

In recent years, the range of sensing technologies has expanded rapidly, whereas sensor devices have become cheaper. This has led to a rapid expansion in condition monitoring of systems, structures, vehicles, and machinery using sensors. Key factors are the recent advances in networking technologies such as wireless communication and mobile adhoc networking coupled with the technology to integrate devices. Wireless sensor networks (WSNs) can be used for monitoring the railway infrastructure such as bridges, rail tracks, track beds, and track equipment along with vehicle health monitoring such as chassis, bogies, wheels, and wagons. Condition monitoring reduces human inspection requirements through automated monitoring, reduces maintenance through detecting faults before they escalate, and improves safety and reliability. This is vital for the development, upgrading, and expansion of railway networks. This paper surveys these wireless sensors network technology for monitoring in the railway industry for analyzing systems, structures, vehicles, and machinery. This paper focuses on practical engineering solutions, principally,which sensor devices are used and what they are used for; and the identification of sensor configurations and network topologies. It identifies their respective motivations and distinguishes their advantages and disadvantages in a comparative review

Miniature Untethered EEG Recorder Improves Advanced Neuroscience Methodologies

Rodent electroencephalography (EEG) in preclinical research is frequently conducted in behaving animals. However, the difficulty inherent in identifying EEG epochs associated with a particular behavior or cue is a significant obstacle to more efficient analysis. In this paper we highlight a new solution, using infrared event stamping to accurately synchronize EEG, recorded from superficial sites above the hippocampus and prefrontal cortex, with video motion tracking data in a transgenic Alzheimer’s disease (AD) mouse model. Epochs capturing specific behaviors were automatically identified and extracted prior to further analysis. This was achieved by the novel design of a ultra- miniature wearable EEG recorder, the NAT-1 device, and its in- situ IR recording module. The device is described in detail, and its contribution to enabling new neuroscience is demonstrated

Investigating Novel 3D Modular Schemes for Large Array Topologies : Power Modeling and Prototype Feasibility.

This paper presents the Tiled Computing Array (TCA), a simple, uniform, 3D-mesh packaging at inter-board level, for massively parallel computers. In particular, the power modelling and practical feasibility of the system is examined. TCA eliminates the need for hierarchical rackmount-structures and introduces short and immediate data channels in multiple physical orientations, allowing a more direct physical mapping of 3D computational topology to real hardware. A dedicated simulation platform has been developed, and an engineered prototype demonstrator has been built. This paper explores the feasibility of the TCA concept for current hardware technologies and systems, evaluates power modeling and validation, and highlights some of the novel design challenges associated with such a system. Evaluations of physical scalability toward large-scale systems are reported, showing that TCA is a promising approach

Evaluating a Miniature Multisensor Biosignal Recorder for Unsupervised Parkinson’s Disease Monitoring

An improved miniature biosignal data sensor and recorder device is described, (NAT-1-4G) with 3-axis accelerometer, and a 500 Sa/sec all-channel recording capacity of 36 hours or more with a single zinc-air battery cell, and up to 6 days at 100 Sa/Sec for accelerometer only. Like the previous NAT-1 prototype device, this measures less than 18´22´10 mm and weighs less than 2.3 grams, including the battery. In this paper we describe the device in detail, and introduce the presentation of tremor data measurement captured in the context of Parkinson’s disease fore-arm monitoring. The NAT-1-4G device itself has already achieved translation to commercialization and is currently available

The Cellular Neural Network Associative Processor, C-NNAP

. This paper describes a novel associative processor that uses neural associative memories as its processing elements. The machine has been designed to tackle problems in AI and computer vision, using nodes that allow rapid search using inexact information over very large data sets. The associative processor is ideally suited as a pattern processing machine, which is where most of the application work has been centered. This is because it is capable of taking large subsections of images and performing matching and comparisons on these. Each processing element of the associative processor is an Advanced Distributed Associative Memory (ADAM) which is capable of storing large numbers of pattern associations, yet they allow rapid access. As a neural network, the memory performs associative match, not by conventional CAM (Content Addressable Memory) approaches, but by forming a mapping between the patterns to be associated. The benefit of this is rapid access, fault tolerance and an abilit..

The Lancet Psychiatry Commission on psychological treatments research in tomorrow's science

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