Use of hierarchical cluster analysis to assess the representativeness of a baseline groundwater quality monitoring network: comparison of New Zealand’s national and regional groundwater monitoring programs

Baseline monitoring of groundwater quality aims to characterize the ambient condition of the resource and identify spatial or temporal trends. Sites comprising any baseline monitoring network must be selected to provide a representative perspective of groundwater quality across the aquifer(s) of interest. Hierarchical cluster analysis (HCA) has been used as a means of assessing the representativeness of a groundwater quality monitoring network, using example datasets from New Zealand. HCA allows New Zealand's national and regional monitoring networks to be compared in terms of the number of water-quality categories identified in each network, the hydrochemistry at the centroids of these water-quality categories, the proportions of monitoring sites assigned to each water-quality category, and the range of concentrations for each analyte within each water-quality category. Through the HCA approach, the National Groundwater Monitoring Programme (117 sites) is shown to provide a highly representative perspective of groundwater quality across New Zealand, relative to the amalgamated regional monitoring networks operated by 15 different regional authorities (680 sites have sufficient data for inclusion in HCA). This methodology can be applied to evaluate the representativeness of any subset of monitoring sites taken from a larger network.

Monitoring charged particles in indoor air using a neutral cluster and air ion spectrometer

While there are sources of ions both outdoors and indoors, ventilation systems can introduce as well as remove ions from the air. As a result, indoor ion concentrations are not directly related to air exchange rates in buildings. In this study, we attempt to relate these quantities with the view of understanding how charged particles may be introduced into indoor spaces.

Cluster-based Intrusion Detection (CBID) architecture for mobile ad hoc networks

The ad hoc networks are vulnerable to attacks due to distributed nature and lack of infrastructure. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. The clustering protocols can be taken as an additional advantage in these processing constrained networks to collaboratively detect intrusions with less power usage and minimal overhead. Existing clustering protocols are not suitable for intrusion detection purposes, because they are linked with the routes. The route establishment and route renewal affects the clusters and as a consequence, the processing and traffic overhead increases due to instability of clusters. The ad hoc networks are battery and power constraint, and therefore a trusted monitoring node should be available to detect and respond against intrusions in time. This can be achieved only if the clusters are stable for a long period of time. If the clusters are regularly changed due to routes, the intrusion detection will not prove to be effective. Therefore, a generalized clustering algorithm has been proposed that can run on top of any routing protocol and can monitor the intrusions constantly irrespective of the routes. The proposed simplified clustering scheme has been used to detect intrusions, resulting in high detection rates and low processing and memory overhead irrespective of the routes, connections, traffic types and mobility of nodes in the network. Clustering is also useful to detect intrusions collaboratively since an individual node can neither detect the malicious node alone nor it can take action against that node on its own.

Adherence, adaptation and acceptance of elderly chronic heart failure patients to receiving healthcare via telephone-monitoring

Background: Although the potential to reduce hospitalisation and mortality in chronic heart failure (CHF) is well reported, the feasibility of receiving healthcare by structured telephone support or telemonitoring is not. Aims: To determine; adherence, adaptation and acceptability to a national nurse-coordinated telephone-monitoring CHF management strategy. The Chronic Heart Failure Assistance by Telephone Study (CHAT). Methods: Triangulation of descriptive statistics, feedback surveys and qualitative analysis of clinical notes. Cohort comprised of standard care plus intervention (SC + I) participants who completed the first year of the study. Results: 30 GPs (70% rural) randomised to SC + I recruited 79 eligible participants, of whom 60 (76%) completed the full 12 month follow-up period. During this time 3619 calls were made into the CHAT system (mean 45.81 SD ± 79.26, range 0-369), Overall there was an adherence to the study protocol of 65.8% (95% CI 0.54-0.75; p = 0.001) however, of the 60 participants who completed the 12 month follow-up period the adherence was significantly higher at 92.3% (95% CI 0.82-0.97, p ≤ 0.001). Only 3% of this elderly group (mean age 74.7 ±9.3 years) were unable to learn or competently use the technology. Participants rated CHAT with a total acceptability rate of 76.45%. Conclusion: This study shows that elderly CHF patients can adapt quickly, find telephone-monitoring an acceptable part of their healthcare routine, and are able to maintain good adherence for a least 12 months. © 2007.

Assessing the representativeness of a groundwater quality monitoring network

The monitoring sites comprising a state of the environment (SOE) network must be carefully selected to ensure that they will be representative of the broader resource. Hierarchical cluster analysis (HCA) is a data-driven technique that can potentially be employed to assess the representativeness of a SOE monitoring network. The objective of this paper is to explore the use of HCA as an approach for assessing the representativeness of the New Zealand National Groundwater Monitoring Programme (NGMP), which is comprised of 110 monitoring sites across the country.

Ask : a health advocacy program for adolescents with an intellectual disability : a cluster randomised controlled trial

Background Adolescents with intellectual disability often have poor health and healthcare. This is partly as a consequence of poor communication and recall difficulties, and the possible loss of specialised paediatric services. Methods/Design A cluster randomised trial was conducted with adolescents with intellectual disability to investigate a health intervention package to enhance interactions among adolescents with intellectual disability, their parents/carers, and general practitioners (GPs). The trial took place in Queensland, Australia, between February 2007 and September 2010. The intervention package was designed to improve communication with health professionals and families’ organisation of health information, and to increase clinical activities beneficial to improved health outcomes. It consisted of the Comprehensive Health Assessment Program (CHAP), a one-off health check, and the Ask Health Diary, designed for on-going use. Participants were drawn from Special Education Schools and Special Education Units. The education component of the intervention was delivered as part of the school curriculum. Educators were surveyed at baseline and followed-up four months later. Carers were surveyed at baseline and after 26 months. Evidence of health promotion, disease prevention and case-finding activities were extracted from GPs clinical records. Qualitative interviews of educators occurred after completion of the educational component of the intervention and with adolescents and carers after the CHAP. Discussion Adolescents with intellectual disability have difficulty obtaining many health services and often find it difficult to become empowered to improve and protect their health. The health intervention package proposed may aid them by augmenting communication, improving documentation of health encounters, and improving access to, and quality of, GP care. Recruitment strategies to consider for future studies in this population include ensuring potential participants can identify themselves with the individuals used in promotional study material, making direct contact with their families at the start of the study, and closely monitoring the implementation of the educational intervention.

Condition monitoring and operational decision making in semiconductor manufacturing

Today, the majority of semiconductor fabrication plants (fabs) conduct equipment preventive maintenance based on statistically-derived time- or wafer-count-based intervals. While these practices have had relative success in managing equipment availability and product yield, the cost, both in time and materials, remains high. Condition-based maintenance has been successfully adopted in several industries, where costs associated with equipment downtime range from potential loss of life to unacceptable affects to companies’ bottom lines. In this paper, we present a method for the monitoring of complex systems in the presence of multiple operating regimes. In addition, the new representation of degradation processes will be used to define an optimization procedure that facilitates concurrent maintenance and operational decision-making in a manufacturing system. This decision-making procedure metaheuristically maximizes a customizable cost function that reflects the benefits of production uptime, and the losses incurred due to deficient quality and downtime. The new degradation monitoring method is illustrated through the monitoring of a deposition tool operating over a prolonged period of time in a major fab, while the operational decision-making is demonstrated using simulated operation of a generic cluster tool.

Observation of ions and particles near busy roads using a Neutral Cluster and Air Ion Spectrometer (NAIS)

Motor vehicles emit large quantities of ions in the form of both charged particles and molecular cluster ions. While, the health effects of inhalation of charged particles is largely unexplored, the concentrations near busy roads and the distance to which these particles and ions are carried have important implications for the exposure of the large percentage of the population that lives close to such roadways. We measured ion concentrations using a neutral cluster and air ion spectrometer (NAIS) near seven busy roads carrying on the average approximately 7000 vehicles hr-1 including about 15% heavy duty diesel vehicles. In this study, charged particle concentrations were measured as a function of downwind distance from the road for the first time. We show that, at a moderate wind speed of 2.0 m s-1, mean charged particle concentrations at the kerb were of the order of 2x104 cm-3 and, more importantly, decreased as d 0.6 where d is the distance from the road. While cluster ions were rapidly depleted by attachment to particles and were not carried to more than about 20 m from the road, elevated concentrations of charged particle were detected up to at least 400 m from the road. Most of the charge on the downwind side was carried on the larger particles, with no excess charge on particles smaller than about 10 nm. At 30 nm, particles carried more than double the charge they would normally carry in equilibrium. There are very few measurements of ions near road traffic and this is the first study of the spatial dispersion of charged particles from a road.

Suppression of cluster ions during particle formation events in the atmosphere

Cluster ions and charged and neutral nanoparticle concentrations were monitored using a neutral cluster and air ion spectrometer (NAIS) over a period of one year in Brisbane, Australia. The study yielded 242 complete days of usable data, of which particle formation events were observed on 101 days. Small, intermediate and large ion concentrations were evaluated in real time. In the diurnal cycle, small ion concentration was highest during the second half of the night while large ion concentrations were a maximum during the day. The small ion concentration showed a decrease when the large ion concentration increased. Particle formation was generally followed by a peak in the intermediate ion concentration. The rate of increase of intermediate ions was used as the criteria for identifying particle formation events. Such events were followed by a period of growth to larger sizes and usually occurred between 8 am and 2 pm. Particle formation events were found to be related to the wind direction. The gaseous precursors for the production of secondary particles in the urban environment of Brisbane have been shown to be ammonia and sulfuric acid. During these events, the nanoparticle number concentrations in the size range 1.6 to 42 nm, which were normally lower than 1x104 cm-3, often exceeded 5x104 cm-3 with occasional values over 1x105 cm-3. Cluster ions generally occurred in number concentrations between 300 and 600 cm-3 but decreased significantly to about 200 cm-3 during particle formation events. This was accompanied by an increase in the large ion concentration. We calculated the fraction of nanoparticles that were charged and investigated the occurrence of possible overcharging during particle formation events. Overcharging is defined as the condition where the charged fraction of particles is higher than in charge equilibrium. This can occur when cluster ions attach to neutral particles in the atmosphere, giving rise to larger concentrations of charged particles in the short term. Ion-induced nucleation is one of the mechanisms of particle formation in the atmosphere, and overcharging has previously been considered as an indicator of this process. The possible role of ions in particle formation was investigated.

Charged particles and cluster ions produced during cooking activities

Previous studies showed that a significant number of the particles present in indoor air are generated by cooking activities, and measured particle concentrations and exposures have been used to estimate the related human dose. The dose evaluation can be affected by the particle charge level which is usually not considered in particle deposition models. To this purpose, in this paper we show, for the very first time, the electric charge of particles generated during cooking activities and thus extending the interest on particle charging characterization to indoor micro-environments, so far essentially focused on outdoors. Particle number, together with positive and negative cluster ion concentrations, was monitored using a condensation particle counter and two air ion counters, respectively, during different cooking events. Positively-charged particle distribution fractions during gas combustion, bacon grilling, and eggplant grilling events were measured by two Scanning Mobility Particle Sizer spectrometers, used with and without a neutralizer. Finally, a Tandem Differential Mobility Analyzer was used to measure the charge specific particle distributions of bacon and eggplant grilling experiments, selecting particles of 30, 50, 80 and 100 nm in mobility diameter. The total fraction of positively-charged particles was 4.0%, 7.9%, and 5.6% for gas combustion, bacon grilling, and eggplant grilling events, respectively, then lower than other typical outdoor combustion-generated particles.

Suppression of cluster ions during rapidly increasing particle number concentration events in the environment

We show that the cluster ion concentration (CIC) in the atmosphere is significantly suppressed during events that involve rapid increases in particle number concentration (PNC). Using a neutral cluster and air ion spectrometer, we investigated changes in CIC during three types of particle enhancement processes – new particle formation, a bushfire episode and an intense pyrotechnic display. In all three cases, the total CIC decreased with increasing PNC, with the rate of decrease being greater for negative CIC than positive. We attribute this to the greater mobility, and hence the higher attachment coefficient, of negative ions over positive ions in the air. During the pyrotechnic display, the rapid increase in PNC was sufficient to reduce the CIC of both polarities to zero. At the height of the display, the negative CIC stayed at zero for a full 10 min. Although the PNCs were not significantly different, the CIC during new particle formation did not decrease as much as during the bushfire episode and the pyrotechnic display. We suggest that the rate of increase of PNC, together with particle size, also play important roles in suppressing CIC in the atmosphere.

Capnography monitoring during procedural sedation and analgesia: A systematic review protocol

Background An important potential clinical benefit of using capnography monitoring during procedural sedation and analgesia (PSA) is that this technology could improve patient safety by reducing serious sedation-related adverse events, such as death or permanent neurological disability, which are caused by inadequate oxygenation. The hypothesis is that earlier identification of respiratory depression using capnography leads to a change in clinical management that prevents hypoxaemia. As inadequate oxygenation/ventilation is the most common reason for injury associated with PSA, reducing episodes of hypoxaemia would indicate that using capnography would be safer than relying on standard monitoring alone. Methods/design The primary objective of this review is to determine whether using capnography during PSA in the hospital setting improves patient safety by reducing the risk of hypoxaemia (defined as an arterial partial pressure of oxygen below 60 mmHg or percentage of haemoglobin that is saturated with oxygen [SpO2] less than 90 %). A secondary objective of this review is to determine whether changes in the clinical management of sedated patients are the mediating factor for any observed impact of capnography monitoring on the rate of hypoxaemia. The potential adverse effect of capnography monitoring that will be examined in this review is the rate of inadequate sedation. Electronic databases will be searched for parallel, crossover and cluster randomised controlled trials comparing the use of capnography with standard monitoring alone during PSA that is administered in the hospital setting. Studies that included patients who received general or regional anaesthesia will be excluded from the review. Non-randomised studies will be excluded. Screening, study selection and data extraction will be performed by two reviewers. The Cochrane risk of bias tool will be used to assign a judgment about the degree of risk. Meta-analyses will be performed if suitable. Discussion This review will synthesise the evidence on an important potential clinical benefit of capnography monitoring during PSA within hospital settings. Systematic review registration: PROSPERO CRD42015023740

Complex symbolic sequence clustering and multiple classifiers for predictive process monitoring

This paper addresses the following predictive business process monitoring problem: Given the execution trace of an ongoing case,and given a set of traces of historical (completed) cases, predict the most likely outcome of the ongoing case. In this context, a trace refers to a sequence of events with corresponding payloads, where a payload consists of a set of attribute-value pairs. Meanwhile, an outcome refers to a label associated to completed cases, like, for example, a label indicating that a given case completed “on time” (with respect to a given desired duration) or “late”, or a label indicating that a given case led to a customer complaint or not. The paper tackles this problem via a two-phased approach. In the first phase, prefixes of historical cases are encoded using complex symbolic sequences and clustered. In the second phase, a classifier is built for each of the clusters. To predict the outcome of an ongoing case at runtime given its (uncompleted) trace, we select the closest cluster(s) to the trace in question and apply the respective classifier(s), taking into account the Euclidean distance of the trace from the center of the clusters. We consider two families of clustering algorithms – hierarchical clustering and k-medoids – and use random forests for classification. The approach was evaluated on four real-life datasets.