Understanding student information behavior in relation to electronic information services: lessons from longitudinal monitoring and evaluation Part 1

Rowley, J.& Urquhart, C. (2007). Understanding student information behavior in relation to electronic information services: lessons from longitudinal monitoring and evaluation Part 1. Journal of the American Society for Information Science and Technology, 58(8), 1162-1174. Sponsorship: JISC

Understanding student information behavior in relation to electronic information services: lessons from longitudinal monitoring and evaluation Part 2

Urquhart, C. & Rowley, J. (2007). Understanding student information behavior in relation to electronic information services: lessons from longitudinal monitoring and evaluation Part 2. Journal of the American Society for Information Science and Technology, 58(8), 1188-1197. Sponsorship: JISC

Monitoring knowledge: a text-based approach

Schierz, A. (2007). Monitoring knowledge: a text-based approach. Terminology, 13 (2), 125-154. Sponsorship: EPSRC DTG Project IQ, EU IST-FET FP6-516169

Selecting Informative Features with Fuzzy-Rough Sets and its Application for Complex Systems Monitoring.

Q. Shen and R. Jensen, 'Selecting Informative Features with Fuzzy-Rough Sets and its Application for Complex Systems Monitoring,' Pattern Recognition, vol. 37, no. 7, pp. 1351-1363, 2004.

IDENTIFYING AND MONITORING THE ROLES OF CAVITATION IN HEATING FROM HIGH-INTENSITY FOCUSED ULTRASOUND

For high-intensity focused ultrasound (HIFU) to continue to gain acceptance for cancer treatment it is necessary to understand how the applied ultrasound interacts with gas trapped in the tissue. The presence of bubbles in the target location have been thought to be responsible for shielding the incoming pressure and increasing local heat deposition due to the bubble dynamics. We lack adequate tools for monitoring the cavitation process, due to both limited visualization methods and understanding of the underlying physics. The goal of this project was to elucidate the role of inertial cavitation in HIFU exposures in the hope of applying noise diagnostics to monitor cavitation activity and control HIFU-induced cavitation in a beneficial manner. A number of approaches were taken to understand the relationship between inertial cavitation signals, bubble heating, and bubble shielding in agar-graphite tissue phantoms. Passive cavitation detection (PCD) techniques were employed to detect inertial bubble collapses while the temperature was monitored with an embedded thermocouple. Results indicate that the broadband noise amplitude is correlated to bubble-enhanced heating. Monitoring inertial cavitation at multiple positions throughout the focal region demonstrated that bubble activity increased prefocally as it diminished near the focus. Lowering the HIFU duty cycle had the effect of maintaining a more or less constant cavitation signal, suggesting the shielding effect diminished when the bubbles had a chance to dissolve during the HIFU off-time. Modeling the effect of increasing the ambient temperature showed that bubbles do not collapse as violently at higher temperatures due to increased vapor pressure inside the bubble. Our conclusion is that inertial cavitation heating is less effective at higher temperatures and bubble shielding is involved in shifting energy deposition at the focus. The use of a diagnostic ultrasound imaging system as a PCD array was explored. Filtering out the scattered harmonics from the received RF signals resulted in a spatially- resolved inertial cavitation signal, while the amplitude of the harmonics showed a correlation with temperatures approaching the onset of boiling. The result is a new tool for detecting a broader spectrum of bubble activity and thus enhancing HIFU treatment visualization and feedback.

EVALUATION OF HARMONIC MOTION ELASTOGRAPHY AND ACOUSTO-­OPTIC IMAGING FOR MONITORING LESION FORMATION BY HIGH INTENSITY FOCUSED ULTRASOUND

Malignant or benign tumors may be ablated with high‐intensity focused ultrasound (HIFU). This technique, known as focused ultrasound surgery (FUS), has been actively investigated for decades, but slow to be implemented and difficult to control due to lack of real‐time feedback during ablation. Two methods of imaging and monitoring HIFU lesions during formation were implemented simultaneously, in order to investigate the efficacy of each and to increase confidence in the detection of the lesion. The first, Acousto‐Optic Imaging (AOI) detects the increasing optical absorption and scattering in the lesion. The intensity of a diffuse optical field in illuminated tissue is mapped at the spatial resolution of an ultrasound focal spot, using the acousto‐optic effect. The second, Harmonic Motion Imaging (HMI), detects the changing stiffness in the lesion. The HIFU beam is modulated to force oscillatory motion in the tissue, and the amplitude of this motion, measured by ultrasound pulse‐echo techniques, is influenced by the stiffness. Experiments were performed on store‐bought chicken breast and freshly slaughtered bovine liver. The AOI results correlated with the onset and relative size of forming lesions much better than prior knowledge of the HIFU power and duration. For HMI, a significant artifact was discovered due to acoustic nonlinearity. The artifact was mitigated by adjusting the phase of the HIFU and imaging pulses. A more detailed model of the HMI process than previously published was made using finite element analysis. The model showed that the amplitude of harmonic motion was primarily affected by increases in acoustic attenuation and stiffness as the lesion formed and the interaction of these effects was complex and often counteracted each other. Further biological variability in tissue properties meant that changes in motion were masked by sample‐to‐sample variation. The HMI experiments predicted lesion formation in only about a quarter of the lesions made. In simultaneous AOI/HMI experiments it appeared that AOI was a more robust method for lesion detection.

Amorphous Placement and Informed Diffusion for Timely Monitoring by Autonomous, Resource-Constrained, Mobile Sensors

Personal communication devices are increasingly equipped with sensors for passive monitoring of encounters and surroundings. We envision the emergence of services that enable a community of mobile users carrying such resource-limited devices to query such information at remote locations in the field in which they collectively roam. One approach to implement such a service is directed placement and retrieval (DPR), whereby readings/queries about a specific location are routed to a node responsible for that location. In a mobile, potentially sparse setting, where end-to-end paths are unavailable, DPR is not an attractive solution as it would require the use of delay-tolerant (flooding-based store-carry-forward) routing of both readings and queries, which is inappropriate for applications with data freshness constraints, and which is incompatible with stringent device power/memory constraints. Alternatively, we propose the use of amorphous placement and retrieval (APR), in which routing and field monitoring are integrated through the use of a cache management scheme coupled with an informed exchange of cached samples to diffuse sensory data throughout the network, in such a way that a query answer is likely to be found close to the query origin. We argue that knowledge of the distribution of query targets could be used effectively by an informed cache management policy to maximize the utility of collective storage of all devices. Using a simple analytical model, we show that the use of informed cache management is particularly important when the mobility model results in a non-uniform distribution of users over the field. We present results from extensive simulations which show that in sparsely-connected networks, APR is more cost-effective than DPR, that it provides extra resilience to node failure and packet losses, and that its use of informed cache management yields superior performance.

An Information Theoretic Framework for Field Monitoring Using Autonomously Mobile Sensors

We consider a mobile sensor network monitoring a spatio-temporal field. Given limited cache sizes at the sensor nodes, the goal is to develop a distributed cache management algorithm to efficiently answer queries with a known probability distribution over the spatial dimension. First, we propose a novel distributed information theoretic approach in which the nodes locally update their caches based on full knowledge of the space-time distribution of the monitored phenomenon. At each time instant, local decisions are made at the mobile nodes concerning which samples to keep and whether or not a new sample should be acquired at the current location. These decisions account for minimizing an entropic utility function that captures the average amount of uncertainty in queries given the probability distribution of query locations. Second, we propose a different correlation-based technique, which only requires knowledge of the second-order statistics, thus relaxing the stringent constraint of having a priori knowledge of the query distribution, while significantly reducing the computational overhead. It is shown that the proposed approaches considerably improve the average field estimation error by maintaining efficient cache content. It is further shown that the correlation-based technique is robust to model mismatch in case of imperfect knowledge of the underlying generative correlation structure.

A demonstration of wireless sensing for long-term monitoring of water quality

At a time when technological advances are providing new sensor capabilities, novel network capabilities, long-range communications technologies and data interpreting and delivery formats via the World Wide Web, we never before had such opportunities to sense and analyse the environment around us. However, the challenges exist. While measurement and detection of environmental pollutants can be successful under laboratory-controlled conditions, continuous in-situ monitoring remains one of the most challenging aspects of environmental sensing. This paper describes the development and test of a multi-sensor heterogeneous real-time water monitoring system. A multi-sensor system was deployed in the River Lee, County Cork, Ireland to monitor water quality parameters such as pH, temperature, conductivity, turbidity and dissolved oxygen. The R. Lee comprises of a tidal water system that provides an interesting test site to monitor. The multi-sensor system set-up is described and results of the sensor deployment and the various challenges are discussed.

Design of miniaturized wireless sensor mote and actuator for building monitoring and control

In this paper, a wireless sensor network mote hardware design and implementation are introduced for building deployment application. The core of the mote design is based on the 8 bit AVR microcontroller, Atmega1281 and 2.4 GHz wireless communication chip, CC2420. The module PCB fabrication is using the stackable technology providing powerful configuration capability. Three main layers of size 25 mm2 are structured to form the mote; these are RF, sensor and power layers. The sensors were selected carefully to meet both the building monitoring and design requirements. Beside the sensing capability, actuation and interfacing to external meters/sensors are provided to perform different management control and data recording tasks. Experiments show that the developed mote works effectively in giving stable data acquisition and owns good communication and power performance.

Continuous non-destructive monitoring of cell health using impedance based interdigitated electrode structured sensors

This article examines some preliminary tests which were performed in order to evaluate the best electrode configuration (width and spacing) for cell culture analyses. Biochips packaged with indium tin oxide (ITO) interdigitated electrodes (IDEs) were used to perform impedance measurements on A549 cells cultured on the surface of the biochip. Several tests were carried out using a 10 mM solution of Sodium Chloride (NaCl), cell medium and the cell culture itself to characterize some of the configurations already fabricated in the facilities at Tyndall National Institute.

Monitoring the vegetation start of season (SOS) across the island of Ireland using the MERIS global vegetation index

The aim of this study was to develop a methodology, based on satellite remote sensing, to estimate the vegetation Start of Season (SOS) across the whole island of Ireland on an annual basis. This growing body of research is known as Land Surface Phenology (LSP) monitoring. The SOS was estimated for each year from a 7-year time series of 10-day composited, 1.2 km reduced resolution MERIS Global Vegetation Index (MGVI) data from 2003 to 2009, using the time series analysis software, TIMESAT. The selection of a 10-day composite period was guided by in-situ observations of leaf unfolding and cloud cover at representative point locations on the island. The MGVI time series was smoothed and the SOS metric extracted at a point corresponding to 20% of the seasonal MGVI amplitude. The SOS metric was extracted on a per pixel basis and gridded for national scale coverage. There were consistent spatial patterns in the SOS grids which were replicated on an annual basis and were qualitatively linked to variation in landcover. Analysis revealed that three statistically separable groups of CORINE Land Cover (CLC) classes could be derived from differences in the SOS, namely agricultural and forest land cover types, peat bogs, and natural and semi-natural vegetation types. These groups demonstrated that managed vegetation, e.g. pastures has a significantly earlier SOS than in unmanaged vegetation e.g. natural grasslands. There was also interannual spatio-temporal variability in the SOS. Such variability was highlighted in a series of anomaly grids showing variation from the 7-year mean SOS. An initial climate analysis indicated that an anomalously cold winter and spring in 2005/2006, linked to a negative North Atlantic Oscillation index value, delayed the 2006 SOS countrywide, while in other years the SOS anomalies showed more complex variation. A correlation study using air temperature as a climate variable revealed the spatial complexity of the air temperature-SOS relationship across the Republic of Ireland as the timing of maximum correlation varied from November to April depending on location. The SOS was found to occur earlier due to warmer winters in the Southeast while it was later with warmer winters in the Northwest. The inverse pattern emerged in the spatial patterns of the spring correlates. This contrasting pattern would appear to be linked to vegetation management as arable cropping is typically practiced in the southeast while there is mixed agriculture and mostly pastures to the west. Therefore, land use as well as air temperature appears to be an important determinant of national scale patterns in the SOS. The TIMESAT tool formed a crucial component of the estimation of SOS across the country in all seven years as it minimised the negative impact of noise and data dropouts in the MGVI time series by applying a smoothing algorithm. The extracted SOS metric was sensitive to temporal and spatial variation in land surface vegetation seasonality while the spatial patterns in the gridded SOS estimates aligned with those in landcover type. The methodology can be extended for a longer time series of FAPAR as MERIS will be replaced by the ESA Sentinel mission in 2013, while the availability of full resolution (300m) MERIS FAPAR and equivalent sensor products holds the possibility of monitoring finer scale seasonality variation. This study has shown the utility of the SOS metric as an indicator of spatiotemporal variability in vegetation phenology, as well as a correlate of other environmental variables such as air temperature. However, the satellite-based method is not seen as a replacement of ground-based observations, but rather as a complementary approach to studying vegetation phenology at the national scale. In future, the method can be extended to extract other metrics of the seasonal cycle in order to gain a more comprehensive view of seasonal vegetation development.

Remote electricity actuation and monitoring mote

This work presents the design and evaluation of the REAM (Remote Electricity Actuation and Monitoring) node based around the modular Tyndall Mote platform. The REAM node enables the user to remotely actuate power to a mains power extension board while sampling the current, voltage, power and power factor of the attached load. The node contains a current transformer interfaced to an Energy Metering IC which continuously samples current and voltage. These values are periodically read from the part by a PIC24 microcontroller, which calculates the RMS current and voltage, power factor and overall power. The resultant values can then be queried wirelessly employing the Tyndall 802.15.4 compliant wireless module.

Towards persistent structural health monitoring through sustainable wireless sensor networks

This paper documents the design, implementation and characterisation of a wireless sensor node (GENESI Node v1.0), applicable to long-term structural health monitoring. Presented is a three layer abstraction of the hardware platform; consisting of a Sensor Layer, a Main Layer and a Power Layer. Extended operational lifetime is one of the primary design goals, necessitating the inclusion of supplemental energy sources, energy awareness, and the implementation of optimal components (microcontroller(s), RF transceiver, etc.) to achieve lowest-possible power consumption, whilst ensuring that the functional requirements of the intended application area are satisfied. A novel Smart Power Unit has been developed; including intelligence, ambient available energy harvesting (EH), storage, electrochemical fuel cell integration, and recharging capability, which acts as the Power Layer for the node. The functional node has been prototyped, demonstrated and characterised in a variety of operational modes. It is demonstrable via simulation that, under normal operating conditions within a structural health monitoring application, the node may operate perpetually.