Development of low cost motion-sensing system

Micro-electro-mechanical system (MEMS) technology offers sensors with lower cost, smaller size, lower power consumption. In this paper, a kind of low cost motion-sensing system based MEMS sensors is developed. The objective of the design is low cost, small volume and light weight in order to be used in many fields. The constituting principle of the system is described. Algorithms and hardware of the system are researched. And the definition of coordinate, calculation of pose angle, transform of acceleration and calculation of the velocities and displacement of the moving object are presented with corresponding mathematics model and algorithms. The experiments are carried out in principle and results are given. It is proved that the low cost motion-sensing system is effective and correct.

Automated classification of human daily activities in ambulatory environment

This paper presents a human daily activity classification approach based on the sensory data collected from a single tri-axial accelerometer worn on waist belt. The classification algorithm was realized to distinguish 6 different activities including standing, jumping, sitting-down, walking, running and falling through three major steps: wavelet transformation, Principle Component Analysis (PCA)-based dimensionality reduction and followed by implementing a radial basis function (RBF) kernel Support Vector Machine (SVM) classifier. Two trials were conducted to evaluate different aspects of the classification scheme. In the first trial, the classifier was trained and evaluated by using a dataset of 420 samples collected from seven subjects by using a k-fold cross-validation method. The parameters σ and c of the RBF kernel were optimized through automatic searching in terms of yielding the highest recognition accuracy and robustness. In the second trial, the generation capability of the classifier was also validated by using the dataset collected from six new subjects. The average classification rates of 95% and 93% are obtained in trials 1 and 2, respectively. The results in trial 2 show the system is also good at classifying activity signals of new subjects. It can be concluded that the collective effects of the usage of single accelerometer sensing, the setting of the accelerometer placement and efficient classifier would make this wearable sensing system more realistic and more comfortable to be implemented for long-term human activity monitoring and classification in ambulatory environment, therefore, more acceptable by users.

Motion artefact separation in single channel doppler radar respiration measurement

Direct conversion Doppler radar has the capability to remotely monitor human respiratory activity in a non-contact form. However, the motion or movement from the subject will degrade the acquired respiration signal. As the respiration pattern is one of the essential parameters in respiratory medicine intrinsically containing more information about the respiratory function, it is particularly important to suppress or to separate these motion artefacts in order to reconstruct the corresponding patterns. Experiment results show that EMD-ICA algorithm is capable of separating the mixed respiration signal by recovering the useful information of the breathing pattern as well as the motion signatures using only a single channel measurement when using the source separation algorithm. This reduces the complexity and the cost of the sensing system while removing the undesirable artefacts. A high correlation was also observed from the recovered respiration pattern in comparison to the standard respiration strap for both experiments setup (a seated and a supine position).

Use of geographical information system and remote sensing techniques for planning culture-based fisheries in non-perennial reservoirs of Sri Lanka

 The presence of a wide areal extent of small-sized village reservoirs offers a considerable potential for the development of culture-based fisheries (CBFs) in Sri Lanka. To this end, this study uses geographical information systems (GISs) and remote sensing (RS) techniques to determine the morphometric and biological characteristics most useful for classifying non-perennial reservoirs for CBF development and for assessing the influence of catchment land-use patterns on potential CBF yields. The reservoir shorelines at full water supply level were mapped with a Global Positioning System to determine shoreline length and reservoir areal extent. The ratio of shoreline length to reservoir extent, which was reported to be a powerful predictor variable of CBF yields, could be reliably quantified using RS techniques. The areal extent of reservoirs, quantified with RS techniques (RS extent), was used to estimate the ratio of forest cover plus scrubland cover to RS extent and was found to be significantly related to the CBF yield (R2 = 0.400; P < 0.05). The results of this study indicated that morphometric characteristics and catchment land-use patterns, which might be viewed as indices of biological productivity, can be quantified using RS and GIS techniques. © 2014 Wiley Publishing Asia Pty Ltd.

A low-cost intelligent gas sensing device for military applications

The field of electronic noses and gas sensing has been developing rapidly since the introduction of the silicon based sensors. There are numerous systems that can detect and indicate the level of a specific gas. We introduce here a system that is low power, small and cheap enough to be used in mobile robotic platforms while still being accurate and reliable enough for confident use. The design is based around a small circuit board mounted in a plastic case with holes to allow the sensors to protrude through the top and allow the natural flow of gas evenly across them. The main control board consists of a microcontroller PCB with surface mount components for low cost and power consumption. The firmware of the device is based on an algorithm that uses an Artificial Neural Network (ANN) which receives input from an array of gas sensors. The various sensors feeding the ANN allow the microcontroller to determine the gas type and quantity. The Testing of the device involves the training of the ANN with a number of different target gases to determine the weightings for the ANN. Accuracy and reliability of the ANN is validated through testing in a specific gas filled environment.

Hydro-acoustic remote sensing of benthic biological communities on the shallow South East Australian continental shelf

Information regarding the composition and extent of benthic habitats on the South East Australian continental shelf is limited. In this habitat mapping study, multibeam echosounder (MBES) data are integrated with precisely geo-referenced video ground-truth data to quantify benthic biotic communities at Cape Nelson, Victoria, Australia. Using an automated decision tree classification approach, 5 representative biotic groups defined from video analysis were related to hydro-acoustically derived variables in the Cape Nelson survey area. Using a combination of multibeam bathymetry, backscatter and derivative products produced highest overall accuracy (87%) and kappa statistic (0.83). This study demonstrates that decision tree classifiers are capable of integrating variable data types for mapping distributions of benthic biological assemblages, which are important in maintaining biodiversity and other system services in the marine environment.

Dynamic privacy assessment in a smart house environment using multimodal sensing

Surveillance applications in private environments such as smart houses require a privacy management policy if such systems are to be accepted by the occupants of the environment. This is due to the invasive nature of surveillance, and the private nature of the home. In this article, we propose a framework for dynamically altering the privacy policy applied to the monitoring of a smart house based on the situation within the environment. Initially the situation, or context, within the environment is determined; we identify several factors for determining environmental context, and propose methods to quantify the context using audio and binary sensor data. The context is then mapped to an appropriate privacy policy, which is implemented by applying data hiding techniques to control access to data gathered from various information sources. The significance of this work lies in the examination of privacy issues related to assisted-living smart house environments. A single privacy policy in such applications would be either too restrictive for an observer, for example, a carer, or too invasive for the occupants. We address this by proposing a dynamic method, with the aim of decreasing the invasiveness of the technology, while retaining the purpose of the system.

Comonitoring of adenosine and dopamine using the wireless instantaneous neurotransmitter concentration system : proof of principle : laboratory investigation

Object

The authors of previous studies have demonstrated that local adenosine efflux may contribute to the therapeutic mechanism of action of thalamic deep brain stimulation (DBS) for essential tremor. Real-time monitoring of the neurochemical output of DBS-targeted regions may thus advance functional neurosurgical procedures by identifying candidate neurotransmitters and neuromodulators involved in the physiological effects of DBS. This would in turn permit the development of a method of chemically guided placement of DBS electrodes in vivo. Designed in compliance with FDA-recognized standards for medical electrical device safety, the authors report on the utility of the Wireless Instantaneous Neurotransmitter Concentration System (WINCS) for real-time comonitoring of electrical stimulation–evoked adenosine and dopamine efflux in vivo, utilizing fast-scan cyclic voltammetry (FSCV) at a polyacrylonitrile-based (T-650) carbon fiber microelectrode (CFM).
Methods

The WINCS was used for FSCV, which consisted of a triangle wave scanned between −0.4 and +1.5 V at a rate of 400 V/second and applied at 10 Hz. All voltages applied to the CFM were with respect to an Ag/AgCl reference electrode. The CFM was constructed by aspirating a single T-650 carbon fiber (r = 2.5 μm) into a glass capillary and pulling to a microscopic tip using a pipette puller. The exposed carbon fiber (the sensing region) extended beyond the glass insulation by ~ 50 μm. Proof of principle tests included in vitro measurements of adenosine and dopamine, as well as in vivo measurements in urethane-anesthetized rats by monitoring adenosine and dopamine efflux in the dorsomedial caudate putamen evoked by high-frequency electrical stimulation of the ventral tegmental area and substantia nigra.
Results

The WINCS provided reliable, high-fidelity measurements of adenosine efflux. Peak oxidative currents appeared at +1.5 V and at +1.0 V for adenosine, separate from the peak oxidative current at +0.6 V for dopamine. The WINCS detected subsecond adenosine and dopamine efflux in the caudate putamen at an implanted CFM during high-frequency stimulation of the ventral tegmental area and substantia nigra. Both in vitro and in vivo testing demonstrated that WINCS can detect adenosine in the presence of other easily oxidizable neurochemicals such as dopamine comparable to the detection abilities of a conventional hardwired electrochemical system for FSCV.
Conclusions

Altogether, these results demonstrate that WINCS is well suited for wireless monitoring of high-frequency stimulation-evoked changes in brain extracellular concentrations of adenosine. Clinical applications of selective adenosine measurements may prove important to the future development of DBS technology.

The Nitric Oxide (NO)-Sensing Repressor NsrR of Neisseria meningitidis Has a Compact Regulon of Genes Involved in NO Synthesis and Detoxification

We have analyzed the extent of regulation by the nitric oxide (NO)-sensitive repressor NsrR from Neisseria meningitidis MC58, using microarray analysis. Target genes that appeared to be regulated by NsrR, based on a comparison between an nsrR mutant and a wild-type strain, were further investigated by quantitative real-time PCR, revealing a very compact set of genes, as follows: norB (encoding NO reductase), dnrN (encoding a protein putatively involved in the repair of nitrosative damage to iron-sulfur clusters), aniA (encoding nitrite reductase), nirV (a putative nitrite reductase assembly protein), and mobA (a gene associated with molybdenum metabolism in other species but with a frame shift in N. meningitidis). In all cases, NsrR acts as a repressor. The NO protection systems norB and dnrN are regulated by NO in an NsrR-dependent manner, whereas the NO protection system cytochrome c′ (encoded by cycP) is not controlled by NO or NsrR, indicating that N. meningitidis expresses both constitutive and inducible NO protection systems. In addition, we present evidence to show that the anaerobic response regulator FNR is also sensitive to NO but less so than NsrR, resulting in complex regulation of promoters such as aniA, which is controlled by both FNR and NsrR: aniA was found to be maximally induced by intermediate NO concentrations, consistent with a regulatory system that allows expression during denitrification (in which NO accumulates) but is down-regulated as NO approaches toxic concentrations.

A new interpolation error expansion based reversible watermarking algorithm considering the human visual system

Reversible watermarking has merged over the past few years as a promising solution for copyright protection, especially for applications like remote sensing, medical imaging and military applications which require lossless recovery of the host media. In this paper, we aim to extend the additive interpolation error expansion technique in [16]. We will consider the human visual system (HVS) to improve the embedding rate while maintaining the image visual quality. To this end, the just noticeable difference (JND) is used to embed more watermark bits. The experimental results show that the proposed algorithm can improve the embedding rate while preserving the image visual quality. © 2014 IEEE.

Designing a responsive material system with physical computing

This paper focuses on an investigation to explore architectural design potentials with a responsive material system and physical computing. Contemporary architects and designers are seeking to integrate physical computing in responsive architectural designs; however, they have largely borrowed from engineering technology's mechanical devices and components. There is the opportunity to investigate an unexplored design approach to exploit the responsive capacity of material properties as alternatives to the current focus on mechanical components and discrete sensing devices. This opportunity creates a different design paradigm for responsive architecture that investigates the potential to integrate physical computing with responsive materials as one integrated material system. Instead of adopting highly intricate and expensive materials, this approach is explored through accessible and off-the-shelf materials to form a responsive material system, called Lumina. Lumina is implemented as an architectural installation called Cloud that serves as a morphing architectural skin. Cloud is a proof of concept to embody a responsive material system with physical computing to create a reciprocal and luminous architectural intervention for a selected dark corridor. It represents a different design paradigm for responsive architecture through alternative exploitation of contemporary materials and parametric design tools. © 2014, The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong.

Mobile phone-based electrochemiluminescence sensing exploiting the 'USB On-The-Go' protocol

A low-cost system to generate, control and detect electrochemiluminescence using a mobile smartphone is described. A simple tone-detection integrated circuit is used to switch power sourced from the phone's Universal Serial Bus (USB) 'On-The-Go' (OTG) port, using audible tone pulses played over the device's audio jack. We have successfully applied this approach to smartphones from different manufacturers and with different operating system versions. ECL calibrations of a common luminophore, tris(2,2′-bipyridine)ruthenium(II) ([Ru(bpy)3]²⁺), with 2-(dibutylamino)ethanol (DBAE) as a co-reactant, showed no significant difference in light intensities when an electrochemical cell was controlled by a mobile phone in this manner, compared to the same calibration generated using a conventional potentiostat. Combining this novel approach to control the applied potential with the measurement of the emitted light through the smart phone camera (using an in-house built Android app), we explored the ECL properties of a water-soluble iridium(III) complex that emits in the blue region of the spectrum. The iridium(III) complex exhibited superior co-reactant ECL intensities and limits of detection to that of the conventional [Ru(bpy)3]²⁺ luminophore.

A brief review on offshore wind turbine fault detection and recent development in condition monitoring based maintenance system

Offshore wind turbine requires more systematized operation and maintenance strategies to ensure systems are harmless, profitable and cost-effective. Condition monitoring and fault diagnostic systems ominously plays an important role in offshore wind turbine in order to cut down maintenance and operational costs. Condition monitoring techniques which describing complex faults and failure mode types and their generated traceable signs to provide cost-effective condition monitoring and predictive maintenance and their diagnostic schemes. Continuously monitor the condition of critical parts are the most efficient way to improve reliability of wind turbine. Implementation of Condition Based Maintenance (CBM) strategy provides right time maintenance decisions and Predictive Health Monitoring (PHM) data to overcome breakdown and machine downtime. Fault detection and CBM implementation is challenging for off shore wind farm due to the complexity of remote sensing, components health and predictive assessment, data collection, data analysis, data handling, state recognition, and advisory decision. The rapid expansion of wind farms, advanced technological development and harsh installation sites needs a successful CM approach. This paper aims to review brief status of recent development of CM techniques and focusing with major faults takes place in gear box and bearing, rotor and blade, pitch, yaw and tower system and generator and control system.