Comprehensive Monitoring System Research Articles

Design of a new comprehensive continuous monitoring system for environmental radioactive aerosol

In order to comprehensive monitoring the radioactive isotopes from nuclear facilities, we developed a dual channel spectral monitoring instrument, and realized synchronous measurement for alpha, beta and gamma radionuclides. This article focuses on how to ensure its accuracy, stability and efficiency. First is the accuracy. In order to lower the interference of environmental and detector performance variation, the zero phase shift filter was designed to ensure the accuracy of characteristic peak position. Lorenz fitting algorithm was designed to reduce the effect of spectral low-energy tailing. Multi thread processing was introduced to ensure that there was sufficient time to complete our complex algorithms. Second is the stability. The complicated measuring process was decomposed into several sub-states. A state monitoring method was set up to timely dispose the abnormal operation. Third is the efficiency. Sampling process and measurement process were designed in synchronous to save monitoring time, which is especially useful for environmental low level radioactive monitoring. Continuous test for seven days shows that the detection limit is less than 0.0003Bq/m3 for U, 239Pu, and less than 0.048Bq/m3 for beta and 137Cs.

Cancer Data and Aboriginal Disparities (CanDAD)—developing an Advanced Cancer Data System for Aboriginal people in South Australia: a mixed methods research protocol

IntroductionIn Australia, Aboriginal and Torres Strait Islander People carry a greater burden of cancer-related mortality than non-Aboriginal Australians. The Cancer Data and Aboriginal Disparities Project aims to develop and test...

Safety monitoring and stability analysis of left bank high slope at Jinping-I hydropower station

At the Jinping-I hydropower station the excavation height on the slope of the left bank is about 530 m. The stability of the excavated slope is very important because of the complicated geological conditions. To analyse the process of deformation evolution of the left abutment slope during construction, a comprehensive monitoring system was employed, which combined surface deformation observations, multi-point extensometers and graphite rod extensometers. This paper describes this monitoring system and analyses the deformation development with slope excavation. We also established a 3D numerical model of the slope and simulated the whole process of excavation using the finite-difference method. Results from both monitoring and numerical simulation show that the deformation depth in the left bank slope of the Jingping-I hydropower station is over 150 m owing to large-scale excavation unloading, far greater than that of general engineering slopes. The 3D limit equilibrium method and the strength reduction method are applied to evaluate the stability of the excavated slope. The calculated factors of safety indicate that the left abutment slope is stable and safe as a whole, which is in agreement with the deformation monitoring results.

Feasibility Study for The Setting Up of a Safety System for Monitoring CO2 Storage at Prinos Field, Greece

Geological storage of CO2 in subsurface geological structures can mitigate global warming. A comprehensive safety and monitoring system for CO2 storage has been undertaken for the Prinos hydrocarbon field, offshore northern Greece; a system which can prevent any possible leakage of CO2. This paper presents various monitoring strategies of CO2 subsurface movement in the Prinos reservoir, the results of a simulation of a CO2 leak through a well, an environmental risk assessment study related to the potential leakage of CO2 from the seafloor and an overall economic insight of the system. The results of the simulation of the CO2 leak have shown that CO2 reaches the seabed in the form of gas approximately 13.7 years, from the beginning of injection. From that point onwards the amount of CO2 reaching the seabed increases until it reaches a peak at around 32.9 years. During the injection period, the CO2 plume develops only within the reservoir. During the post-injection period, the CO2 reaches the seabed and develops side branches. These correspond to preferential lateral flow pathways of the CO2 and are more extensive for the dissolved CO2 than for the saturated CO2 gas. For the environmental risk assessment, we set up a model, using ArcGIS software, based on the use of data regarding the speeds of the winds and currents encountered in the region. We also made assumptions related to the flow rate of CO2. Results show that after a period of 10 days from the start of CO2 leakage the CO2 has reached halfway to the continental shores where the “Natura” protected areas are located. CO2 leakage modelling results show CO2 to be initially flowing along a preferential flow direction, which is towards the NE. However, 5 days after the start of leakage of CO2, the CO2 is also flowing towards the ENE. The consequences of a potential CO2 leak are considered spatially limited and the ecosystem is itself capable of recovering. We have tried to determine the costs necessary for the creation of such an integrated CO2 monitoring program both during the CO2 injection phase as well as during permanent storage. The most prevalent solution consists of purchasing both seismic equipment and Echosounder systems as well as privileging a monitoring system, which uses selected boreholes. The necessary period required for monitoring the study area is at least 20 years after the end of the CO2 storage period at Prinos. To the overall monitoring time, we should also add a further 20 years that are required for the injection phase as well as 12 years for the storage phase. The operating costs for monitoring the CO2 amount to 0,38 $/ton CO2 and the total cost for EOR at Prinos amounts to 0,45 $/ton CO2.

Trend of Inequality in the Distribution of Health Care Resources in Iran

Background: Equity of access to health care services is one of the main goals of health system. Equity in resource distribution in health section constitutes one of the main dimensions of the equity. The aim of the study is determining how doctors, paramedics and hospital beds are distributed in Iran.Materials and Methods: This analytical study was conducted in Iran. Data on 2006-2013 were collected from Statistics Center of Iran and Iran Ministry of Health and Medical Education. After determining the population of 31 provinces and number of physician, paramedics and hospital beds in them, the equal distribution of these facilities and personnel were analyzed using Lorenz curve and Gini coefficient. Stata 12 and DASP2.2 were used for analyzing Gini index. Results: The total number of physicians, paramedics and hospital beds were 37,000, 217,000 and 138,000, respectively in 2013. Tehran as the capital of Iran had the highest percentage of beds among all provinces. The number of physicians, paramedics and hospital beds per 10,000 population of the country were 5.6, 31.3 and 18.5, respectively for 2013. The calculated Gini coefficients for each of them were 0.47, 0.39 and 0.58, respectively.Conclusion: According to Gini coefficients, physicians, paramedics and hospital beds have an unequal distribution throughout the country. However, these distributions are different in different provinces. We recommend creating a comprehensive and continuous monitoring system for equitable allocation of health care resources.[GMJ.2016;5(3):122-130]

Performance Monitoring Analysis of Liquid Ring Vacuum Pumps

Liquid ring vacuum pump which uses rotating liquid as piston to abstract and compress gas is a kind of rotating positive displacement pump. Its running state implies some fault informantion. To capture performance levels of liquid ring vacuum pump, a comprehensive performance monitoring system includes data acquisition, data reprocessing, data storage, abnormal judgment and fault alarm, performance displaying is developed in this paper. Hence, the performance levels of liquid ring vacuum pump can be observed anytime by the monitoring system, the maintenance cost can be reduced, pumps can be operated at the highest performance level as far as possible, the reliability and the maintainability of liquid ring vacuum pump can be effectively improved by this monitoring system.

Vagal Blocking for Obesity Control: a Possible Mechanism-Of-Action

Recently, the US FDA has approved "vagal blocking therapy or vBLoc® therapy" as a new treatment for obesity. The aim of the present study was to study the mechanism-of-action of "VBLOC" in rat models. Rats were implanted with VBLOC, an intra-abdominal electrical device with leads placed around gastric vagal trunks through an abdominal incision and controlled by wireless device. Body weight, food intake, hunger/satiety, and metabolic parameters were monitored by a comprehensive laboratory animal monitoring system. Brain-gut responses were analyzed physiologically. VBLOC reduced body weight and food intake, which was associated with increased satiety but not with decreased hunger. Brain activities in response to VBLOC included increased gene expression of leptin and CCKb receptors, interleukin-1β, tumor necrosis factor, and transforming growth factor β1 in the brainstem; increased CCK, somatostatin, and tyrosine hydroxylase in the hippocampus; increased NPY, AgRP, and Foxa2 in the hypothalamus; and reduced CCKb receptor, melanocortin 4 receptor, and insulin receptor in the hypothalamus. Plasma concentrations of CCK, gastrin, glucagon, GLP-1, and PYY and gastric acid secretion were unchanged in response to VBLOC. Based on the present study, we may suggest that VBLOC induces satiety through vagal signaling, leading to reduced food intake and loss of body weight.

Development of a Comprehensive Monitoring System Based on Cloud Computing and XMPP

According to the actual situation of the coexistence of multi-sensor and multi-protocol in Mine Monitoring System, a comprehensive monitoring system of network based on XMPP protocol was carried out in this paper. The characteristics of the network system structure and the scheme of virtual sensor gateway were described in detail. Moreover, a session protocol based on the XMPP protocol was proposed and the definition of API was given. Functional structure and software structure of the whole system were designed based on Zend Framework. By using the virtual server cloud technology of VMware, as well as the centralized storage method of SAN, the background monitoring server group was built. After testing, the system greatly met the requirements of safety monitoring, which also possessed the advantage of easy implement, simple operation and maintenance, and great expansibility.

S2NI: a mobile platform for nutrition monitoring from spoken data.

Diet and physical activity are important lifestyle and behavioral factors in self-management and prevention of many chronic diseases. Mobile sensors such as accelerometers have been used in the past to objectively measure physical activity or detect eating time. Diet monitoring, however, still relies on self-recorded data by end users where individuals use mobile devices for recording nutrition intake by either entering text or taking images. Such approaches have shown low adherence in technology adoption and achieve only moderate accuracy. In this paper, we propose development and validation of Speech-to-Nutrient-Information (S2NI), a comprehensive nutrition monitoring system that combines speech processing, natural language processing, and text mining in a unified platform to extract nutrient information such as calorie intake from spoken data. After converting the voice data to text, we identify food name and portion size information within the text. We then develop a tiered matching algorithm to search the food name in our nutrition database and to accurately compute calorie intake. Due to its pervasive nature and ease of use, S2NI enables users to report their diet routine more frequently and at anytime through their smartphone. We evaluate S2NI using real data collected with 10 participants. Our experimental results show that S2NI achieves 80.6% accuracy in computing calorie intake.

Assessing the sustainability of tourism products – as simple as it gets

The balance between the three dimensions of sustainability forms the basis for the successful development of a tourism region. The development of sustainable products is crucial for a destination in order to create true sustainable experiences for their guests. The research project aimed to determine the criteria for sustainable tourism and to develop a simple method for the sustainability assessment of tourism products. While most valuation methods require the presence and the analysis of a comprehensive data set, the assessment tool should enable the destination to analyse the sustainability of their products as easily as possible. Together with five Swiss tourism destinations an assessment tool was developed and tested. In a first step, the central sustainability criteria for tourism products were defined based on existing criteria sets. Then an inventory of all tourist products was created. Every single product was quantitatively assessed with regards to the sustainability criteria by the project manager of the destination management organisation (DMO). Their experiences were evaluated through qualitative interviews. The sustainability assessment using the framework showed various challenges such as the dependence of the prior knowledge of the evaluator. The variety of the products also hampers a consistent assessment and a comparison between destinations. The strengths of such a simplified model are that it allows a comparison to changes of sustainability in the product portfolio over time. In addition, it promotes the internal discussion and awareness. Using the new framework during the development of new products helps to take all criteria into account. It also supports the connection with service providers and the communication of sustainability requirements. The instrument tested represents a compromise that reduces complexity and enables the assessment of sustainability without the use of a comprehensive monitoring system – as simple as it gets.

System specifications for developing an Automatic Dependent Surveillance-Broadcast (ADS-B) monitoring system

Automatic Dependent Surveillance-Broadcast (ADS-B) is a surveillance system placed in aircraft that periodically transmits state vector estimates and other information to air traffic control centers and other nearby aircraft (and may also receive traffic and weather information from various entities). The state vector estimates are derived from navigation avionics and are transmitted via a common communications channel, which means that ADS-B is highly dependent on aircraft navigation and communication systems. ADS-B also requires ground stations to receive information from aircraft. As a result of this complex architecture, the ADS-B system is prone to various failure modes.A systematic and comprehensive performance monitoring system is required to ensure the safe use of ADS-B data for air traffic control operations. It is vital that such monitoring systems are in place before a global ADS-B implementation date is mandated by the International Civil Aviation Organization. A number of air navigation service providers and regulators have developed ADS-B performance monitoring methods without a standardized guideline for system specifications. These include Airservices Australia, the U.S. Federal Aviation Administration, EUROCONTROL, the Civil Aviation Authority of Singapore and the Civil Aviation Department of Hong Kong.This paper presents a holistic set of system specifications for ADS-B monitoring systems. In particular, the paper analyzes the ADS-B infrastructure, conducts a systematic review of existing ADS-B monitoring systems, classifies the system characteristics to identify gaps, and derives a set of specifications for developing ADS-B monitoring systems. The paper also assesses the compliance of existing ADS-B monitoring systems against the proposed specifications using a mapping exercise. The system specifications serve as a foundation or minimum requirements for air navigation service providers and original equipment manufacturers to develop systematic and comprehensive ADS-B monitoring systems.

Risk-based crowd massing early warning approach for public places: A case study in China

Beijing municipal government plans to establish a comprehensive real-time monitoring and risk identification technological system basically covering the targeted districts with crowded pedestrian traffic. The system aims to send out alarm in crowded places through analyzing quantitative data from intelligent real-time monitoring devices installed in key locations. An early warning signal is derived from the judgment of current status of the crowd, and this research aims to explain the mechanism of how to judge crowd status. Classically risk is defined as multiplication of impact and probability of occurrence of an event. Here, a 2-D risk matrix is established to judge the crowd status by probability (duration of the pedestrian status) plus consequence (strength of the pedestrian status). After installed intelligent monitoring devices in key locations, the online observations of crowd movement within the targeted district can produce the early warning alarm ahead of time. Such alarm is expected to provide the local administrator 10min to prevent potential undesired chaos by taking proper controlling actions. This paper is a case study in a specific area in China. This system can be used in many areas such as sporting events and religious gatherings.

High-resolution atmospheric inversion of urban CO2 emissions during the dormant season of the Indianapolis Flux Experiment (INFLUX).

Based on a uniquely dense network of surface towers measuring continuously the atmospheric concentrations of greenhouse gases (GHGs), we developed the first comprehensive monitoring systems of CO2 emissions at high resolution over the city of Indianapolis. The urban inversion evaluated over the 2012-2013 dormant season showed a statistically significant increase of about 20% (from 4.5 to 5.7 MtC ± 0.23 MtC) compared to the Hestia CO2 emission estimate, a state-of-the-art building-level emission product. Spatial structures in prior emission errors, mostly undetermined, appeared to affect the spatial pattern in the inverse solution and the total carbon budget over the entire area by up to 15%, while the inverse solution remains fairly insensitive to the CO2 boundary inflow and to the different prior emissions (i.e., ODIAC). Preceding the surface emission optimization, we improved the atmospheric simulations using a meteorological data assimilation system also informing our Bayesian inversion system through updated observations error variances. Finally, we estimated the uncertainties associated with undetermined parameters using an ensemble of inversions. The total CO2 emissions based on the ensemble mean and quartiles (5.26-5.91 MtC) were statistically different compared to the prior total emissions (4.1 to 4.5 MtC). Considering the relatively small sensitivity to the different parameters, we conclude that atmospheric inversions are potentially able to constrain the carbon budget of the city, assuming sufficient data to measure the inflow of GHG over the city, but additional information on prior emission error structures are required to determine the spatial structures of urban emissions at high resolution.

Experimental Methods for Investigation of Shape Memory Based Elastocaloric Cooling Processes and Model Validation.

Shape Memory Alloys (SMA) using elastocaloric cooling processes have the potential to be an environmentally friendly alternative to the conventional vapor compression based cooling process. Nickel-Titanium (Ni-Ti) based alloy systems, especially, show large elastocaloric effects. Furthermore, exhibit large latent heats which is a necessary material property for the development of an efficient solid-state based cooling process. A scientific test rig has been designed to investigate these processes and the elastocaloric effects in SMAs. The realized test rig enables independent control of an SMA's mechanical loading and unloading cycles, as well as conductive heat transfer between SMA cooling elements and a heat source/sink. The test rig is equipped with a comprehensive monitoring system capable of synchronized measurements of mechanical and thermal parameters. In addition to determining the process-dependent mechanical work, the system also enables measurement of thermal caloric aspects of the elastocaloric cooling effect through use of a high-performance infrared camera. This combination is of particular interest, because it allows illustrations of localization and rate effects - both important for efficient heat transfer from the medium to be cooled. The work presented describes an experimental method to identify elastocaloric material properties in different materials and sample geometries. Furthermore, the test rig is used to investigate different cooling process variations. The introduced analysis methods enable a differentiated consideration of material, process and related boundary condition influences on the process efficiency. The comparison of the experimental data with the simulation results (of a thermomechanically coupled finite element model) allows for better understanding of the underlying physics of the elastocaloric effect. In addition, the experimental results, as well as the findings based on the simulation results, are used to improve the material properties.

The Southern Ocean as a constraint to reduce uncertainty in future ocean carbon sinks

Abstract. Earth system model (ESM) simulations exhibit large biases compares to observation-based estimates of the present ocean CO2 sink. The inter-model spread in projections increases nearly 2-fold by the end of the 21st century and therefore contributes significantly to the uncertainty of future climate projections. In this study, the Southern Ocean (SO) is shown to be one of the hot-spot regions for future uptake of anthropogenic CO2, characterized by both the solubility pump and biologically mediated carbon drawdown in the spring and summer. We show, by analyzing a suite of fully interactive ESMs simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) over the 21st century under the high-CO2 Representative Concentration Pathway (RCP) 8.5 scenario, that the SO is the only region where the atmospheric CO2 uptake rate continues to increase toward the end of the 21st century. Furthermore, our study discovers a strong inter-model link between the contemporary CO2 uptake in the Southern Ocean and the projected global cumulated uptake over the 21st century. This strong correlation suggests that models with low (high) carbon uptake rate in the contemporary SO tend to simulate low (high) uptake rate in the future. Nevertheless, our analysis also shows that none of the models fully capture the observed biophysical mechanisms governing the CO2 fluxes in the SO. The inter-model spread for the contemporary CO2 uptake in the Southern Ocean is attributed to the variations in the simulated seasonal cycle of surface pCO2. Two groups of model behavior have been identified. The first one simulates anomalously strong SO carbon uptake, generally due to both too strong a net primary production and too low a surface pCO2 in December–January. The second group simulates an opposite CO2 flux seasonal phase, which is driven mainly by the bias in the sea surface temperature variability. We show that these biases are persistent throughout the 21st century, which highlights the urgent need for a sustained and comprehensive biogeochemical monitoring system in the Southern Ocean to better constrain key processes represented in current model systems.

Regulation of Adaptive Thermogenesis by the Gut Microbiome

BackgroundAlterations in the gut microbiome contribute to obesity, but the mechanisms by which the gut microbiome regulates energy expenditure and balance are unclear. Adaptive thermogenesis in both humans and mice occurs when changes in ambient temperatures activate thermogenic brown and beige adipose tissue to dissipate energy as heat.AimsThis study was designed to examine the influence of cold ambient temperature on the gut microbiome and to elucidate the contribution of the gut microbiome to adaptive thermogenesis.MethodsC57BL/6 mice were maintained for 3 d at ambient temperatures of 30 °C (thermoneutral), 22 °C (mild cold stress), or 4 °C (severe cold stress). Temperature‐conditioned gut microbiomes were analyzed for predominant gut microbial phyla by qPCR of extracted fecal DNA and were transplanted into commensal‐depleted (antibiotic treated) recipient mice housed at 22 °C. The mice were fed a high fat‐diet, and after 5 w, intraperitoneal glucose tolerance tests were performed. Germ‐free and commensal depleted mice were housed at 30 °C, 22 °C, and 4 °C within a temperature‐controlled comprehensive laboratory animal monitoring system that was custom‐designed to maintain sterile conditions. Indirect calorimetry was performed to determine rates of O2 consumption (VO2) and CO2 production (VCO2). Energy expenditures and respiratory exchange ratios (RER) were calculated using VO2 and VCO2 values. Physical activity was measured according to beam breaks from light sensors within the cages. Core body temperatures were measured using rectal probes. Fecal metabolites were measured by gas chromatography.ResultsHousing mice for 3 d at 4 °C resulted in a dramatic 95% reduction in the abundance of Bacteroidetes and a 62% increase in Firmicutes, the two predominant microbial phyla in the gut. Mice that received a 4 °C‐conditioned microbiome gained less body weight in response to high fat‐feeding and exhibited improved glucose tolerance compared to mice that received the 30 °C‐ or 22 °C‐conditioned microbiomes. Without appreciable changes in core body temperatures, germ‐free and commensal‐depleted mice exhibited reduced energy expenditures at both 30 °C and 4 °C. This occurred despite increased physical activities in germ‐free mice, which were most pronounced at 4 °C. Indicative of preferential utilization of lipids as energy substrates, RER values were reduced in germ free mice at 30 °C and 4 °C, as were fecal contents of short‐chain fatty acids.ConclusionsThe gut microbiome plays a fundamental role in regulating adaptive thermogenesis, potentially by altering intestinal lipid availability or absorption. These effects may be transferred among mice and influence the metabolic response to over‐nutrition. We speculate that impaired thermogenesis in the setting of microbial dysbiosis contributes to the pathogenesis of obesity.Support or Funding InformationBrigham and Women's Hospital, Department of Medicine, Innovation Evergreen Fund and The Harvard Digestive Diseases Center (NIH P30 DK034854).

Investigation of modal identification and modal identifiability of a cable-stayed bridge with Bayesian framework

In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.

Voluntary exercise improves hypothalamic and metabolic function in obese mice.

Exercise plays a critical role in regulating glucose homeostasis and body weight. However, the mechanism of exercise on metabolic functions associated with the CNS has not been fully understood. C57BL6 male mice (n=45) were divided into three groups: normal chow diet, high-fat diet (HFD) treatment, and HFD along with voluntary running wheel exercise training for 12 weeks. Metabolic function was examined by the Comprehensive Lab Animal Monitoring System and magnetic resonance imaging; phenotypic analysis included measurements of body weight, food intake, glucose and insulin tolerance tests, as well as insulin and leptin sensitivity studies. By immunohistochemistry, the amount changes in the phosphorylation of signal transducer and activator of transcription 3, neuronal proliferative maker Ki67, apoptosis positive cells as well as pro-opiomelanocortin (POMC)-expressing neurons in the arcuate area of the hypothalamus was identified. We found that 12 weeks of voluntary exercise training partially reduced body weight gain and adiposity induced by an HFD. Insulin and leptin sensitivity were enhanced in the exercise training group verses the HFD group. Furthermore, the HFD-impaired POMC-expressing neuron is remarkably restored in the exercise training group. The restoration of POMC neuron number may be due to neuroprotective effects of exercise on POMC neurons, as evidenced by altered proliferation and apoptosis. In conclusion, our data suggest that voluntary exercise training improves metabolic symptoms induced by HFD, in part through protected POMC-expressing neuron from HFD and enhanced leptin signaling in the hypothalamus that regulates whole-body energy homeostasis.

Is low frequency ocean sound increasing globally?

Low frequency sound has increased in the Northeast Pacific Ocean over the past 60 yr [Ross (1993) Acoust. Bull. 18, 5-8; (2005) IEEE J. Ocean. Eng. 30, 257-261; Andrew, Howe, Mercer, and Dzieciuch (2002) J. Acoust. Soc. Am. 129, 642-651; McDonald, Hildebrand, and Wiggins (2006) J. Acoust. Soc. Am. 120, 711-717; Chapman and Price (2011) J. Acoust. Soc. Am. 129, EL161-EL165] and in the Indian Ocean over the past decade, [Miksis-Olds, Bradley, and Niu (2013) J. Acoust. Soc. Am. 134, 3464-3475]. More recently, Andrew, Howe, and Mercer's [(2011) J. Acoust. Soc. Am. 129, 642-651] observations in the Northeast Pacific show a level or slightly decreasing trend in low frequency noise. It remains unclear what the low frequency trends are in other regions of the world. In this work, data from the Comprehensive Nuclear-Test Ban Treaty Organization International Monitoring System was used to examine the rate and magnitude of change in low frequency sound (5-115 Hz) over the past decade in the South Atlantic and Equatorial Pacific Oceans. The dominant source observed in the South Atlantic was seismic air gun signals, while shipping and biologic sources contributed more to the acoustic environment at the Equatorial Pacific location. Sound levels over the past 5-6 yr in the Equatorial Pacific have decreased. Decreases were also observed in the ambient sound floor in the South Atlantic Ocean. Based on these observations, it does not appear that low frequency sound levels are increasing globally.

System-Aware Smart Network Management for Nano-Enriched Water Quality Monitoring

This paper presents a comprehensive water quality monitoring system that employs a smart network management, nano-enriched sensing framework, and intelligent and efficient data analysis and forwarding protocols for smart and system-aware decision making. The presented system comprises two main subsystems, a data sensing and forwarding subsystem (DSFS), and Operation Management Subsystem (OMS). The OMS operates based on real-time learned patterns and rules of system operations projected from the DSFS to manage the entire network of sensors. The main tasks of OMS are to enable real-time data visualization, managed system control, and secure system operation. The DSFS employs a Hybrid Intelligence (HI) scheme which is proposed through integrating an association rule learning algorithm withfuzzylogic and weighted decision trees. The DSFS operation is based on profiling and registering raw data readings, generated from a set of optical nanosensors, as profiles of attribute-value pairs. As a case study, we evaluate our implemented test bed via simulation scenarios in a water quality monitoring framework. The monitoring processes are simulated based on measuring the percentage of dissolved oxygen and potential hydrogen (PH) in fresh water. Simulation results show the efficiency of the proposed HI-based methodology at learning different water quality classes.