Academic literature on the topic 'Water detection'

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Journal articles on the topic "Water detection"

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Sankary, Nathan, and Avi Ostfeld. "Analyzing multi-variate water quality signals for water quality monitoring station placement in water distribution systems." Journal of Hydroinformatics 20, no. 6 (September 12, 2018): 1323–42. http://dx.doi.org/10.2166/hydro.2018.162.

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Abstract Placing fixed water quality monitoring stations in a water distribution system can greatly improve the security of the system via prompt detection of poor water quality. In the event that a harmful substance is injected into a water distribution system, large populations can be put at risk of exposure to the contaminant. Promptly detecting the presence of a contaminant will reduce the number of people put at risk of exposure. However, to protect against a wide variety of possible contaminants, a water quality monitoring station will need to identify contamination via recognition of anomalous changes in a suite of surrogate water quality indicators (chlorine, pH, etc.). This work attempts to place water quality monitoring stations within the water distribution at locations that best detect contamination events via surrogate water quality signals. Networks of water quality monitoring stations are designed to minimize the population affected prior to contamination event detection, and simultaneously minimize the expected number of false positive detections, under uncertain water quality conditions. Solutions generated in this study are compared to solutions designed via classical detection methods. Results show the sensor networks designed without consideration to detection via surrogate water quality parameters have higher false positive detection rates.
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Najam, Liath Ahmed, Hazim Louis Mansour, Nada Fadhil Tawfiq, and Mahmood Salim Karim. "Measurement of Radon Gas Concentrations in Tap Water Samples for Thi-Qar Governorate Using Nuclear Track Detector (CR-39)." Detection 04, no. 01 (2016): 1–8. http://dx.doi.org/10.4236/detection.2016.41001.

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Cao, Hui-Wen, Yu-Peng Jing, Shi-Rui Zhao, Xin-Wei Xu, He Tian, Xin Xin, Xiao-Ning Li, et al. "A discovery of an ultra-pure water detection method based on water mark." Modern Physics Letters B 29, no. 03 (January 30, 2015): 1450271. http://dx.doi.org/10.1142/s0217984914502716.

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The purity evaluation of deionized (DI) water is highly desirable for VLSI or ULSI industry, as the traditional "reverse osmosis filter" cannot always meet the requirement towards the DI water. The filtered DI water may still contain many contaminations which are not up to the standard for the wet cleaning of wafer surface. A novel method is presented by analyzing the residues of a water droplet after the low-temperature evaporation. The contamination contained in the water will remain during the gasification. By analyzing the residual contamination's morphology, the purity of the DI water can be estimated by employing merely a 3D laser microscope. Compared to the traditional fluorescence detecting system for water quality monitoring, it is simpler and has a lower cost. The paper describes an excellent water detection method which is meaningful for preparing ultra-pure water. Experimental results have shown that the deionized distilled (DID) water can repeatedly get a higher purity using this detection method. The DID water can be applied to the wet cleaning of wafer surface, preparation of chemical reagents and many other aspects.
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Alsamman, A., and M. Syed. "RGB-BASED DEEP SURFACE WATER CONTOUR DETECTION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 30, 2022): 827–32. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-827-2022.

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Abstract. The application of remote monitoring of surface water has focused primarily on the detection of water bodies using expensive multi-spectral IR sensors. However, critical information about surface water bodies, particularly the dynamic behavior, is better derived from water contours. We show that water body detection is inadequate in accurately capturing the contours. Furthermore, we argue that RGB-based detection should be sufficient for accurate water detection. We present a new global dataset of remote sensing images obtained from Sentinel-2 and Landsat-8 missions and contour labeled to assist in this effort. We propose a unique UNet-style contour detection system that utilizes multiscale filters to detect contours accurately. Comparisons between our proposed system, existing water detection, and other segmentation and contour detection systems show the system's effectiveness in detecting water.
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Zhang, Chuanhao. "Miniaturized detection devices powered by various heaters: A quick review under the background of water-borne disease epidemics." Advances in Engineering Technology Research 9, no. 1 (January 25, 2024): 670. http://dx.doi.org/10.56028/aetr.9.1.670.2024.

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With the progress of society and the development of productivity, the problem of water pollution and water shortage caused by water pollution is becoming more and more serious. Water-borne diseases caused by pathogenic microorganisms also bring great harm to human beings and other life forms. These microorganisms include bacteria, viruses, protozoa, and parasitic pathogens. Traditional detection methods are time-consuming and costly, and can’t meet the needs of water resource detection. Therefore, there is an urgent need for accurate, rapid, specific, and portable detection equipment for detecting pathogenic microorganisms in water. We analyzed and sorted out the detection methods and detection equipment for detecting pathogenic microorganisms that cause water-borne diseases, summarized these detection methods and detection equipment, and analyzed the advantages and disadvantages of these detection methods. We reasonably concluded that a good detection method for pathogenic microorganisms in water should have the advantages of low cost, low energy consumption, simple operation, strong specificity, and high portability, which can more easily meet the needs of the water quality detection field. Multifunctional small nucleic acid detection devices have been reported for decades, which reduce the reaction time of nucleic acid amplification from hours to minutes, and these miniaturized devices based on nucleic acid amplification are not only highly specific but also low cost, which is very suitable for resource-limited environments.
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Ge, Hongyi, Zhenyu Sun, Yuying Jiang, Xuyang Wu, Zhiyuan Jia, Guangyuan Cui, and Yuan Zhang. "Recent Advances in THz Detection of Water." International Journal of Molecular Sciences 24, no. 13 (June 30, 2023): 10936. http://dx.doi.org/10.3390/ijms241310936.

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The frequency range of terahertz waves (THz waves) is between 0.1 and 10 THz and they have properties such as low energy, penetration, transients, and spectral fingerprints, which are especially sensitive to water. Terahertz, as a frontier technology, have great potential in interpreting the structure of water molecules and detecting biological water conditions, and the use of terahertz technology for water detection is currently frontier research, which is of great significance. Firstly, this paper introduces the theory of terahertz technology and summarizes the current terahertz systems used for water detection. Secondly, an overview of theoretical approaches, such as the relaxation model and effective medium theory related to water detection, the relationship between water molecular networks and terahertz spectra, and the research progress of the terahertz detection of water content and water distribution visualization, are elaborated. Finally, the challenge and outlook of applications related to the terahertz wave detection of water are discussed. The purpose of this paper is to explore the research domains on water and its related applications using terahertz technology, as well as provide a reference for innovative applications of terahertz technology in moisture detection.
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Li, Yu, Jinggang Chu, Guozhen Wei, Sifan Jin, Tiantian Yang, and Bo Li. "Robust Placement of Water Quality Sensor for Long-Distance Water Transfer Projects Based on Multi-Objective Optimization and Uncertainty Analysis." Sustainability 13, no. 4 (February 8, 2021): 1834. http://dx.doi.org/10.3390/su13041834.

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It is important to place water quality sensors along open channels in long-distance water transfer projects optimally for rapid source identification and efficient management of sudden water contamination. A new framework which considers multiple objectives, including earliest detection time, lowest missing detection rate and lowest sensor cost, and combines the randomness of injected contaminant type and contaminant incident consisting of contaminant intrusion location, time and mass, was established to obtain optimal placement of water quality sensor with better robustness in this paper. The middle route of the South-to-North Water Diversion Project in China was chosen as a case study, and it was found that both missing detection rate and detection time decrease with sensor cost gradually; furthermore, given the higher detecting precision, the detection accuracy and efficiency would be improved, a smaller number of water quality sensors would be needed, and the ten key placement positions where sensor with different detecting precision placed could be identified. Under the constraints of the allowable maximum missing detection rate, 1.00%, and detection time, 120.00 min, the detecting precision of 0.20 mg/L and 38 sensors placed could be selected as the optimal sensor placement scheme. Finally, with the consideration of contaminant uncertainty, the sensor placement scheme with better robustness could be constructed. The proposed framework would be helpful in solving the problem of water quality sensor placement with high practicality and efficiency in long-distance water transfer projects.
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Higashi, Yasuhiko. "Development of Simultaneous HPLC-Fluorescence Assay of Phenol and Chlorophenols in Tap Water after Pre-Column Derivatization with 3-Chlorocarbonyl-6,7-dimethoxy-1- methyl-2(1<i>H</i>)-quinoxalinone." Detection 04, no. 01 (2016): 16–24. http://dx.doi.org/10.4236/detection.2016.41003.

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Wongniramaikul, Worawit, and Aree Choodum. "Synthesis of Polymer Sensor for Detection of Phosphate in Water." International Journal of Chemical Engineering and Applications 8, no. 3 (June 2017): 221–25. http://dx.doi.org/10.18178/ijcea.2017.8.3.660.

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Kwietniewski, Marian, Piotr Świercz, and Jarosław Chudzicki. "Modern methods for monitoring water leakages in water networks." Studia Geotechnica et Mechanica 44, no. 1 (March 1, 2022): 53–65. http://dx.doi.org/10.2478/sgem-2022-0001.

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Abstract The main idea of this article is to adopt the thesis that the main and, at the same time, the most effective (apart from proper maintenance and operation) element of the strategy of limiting water losses in water supply networks is continuous integrated monitoring of the network using the latest achievements of IT technologies, including GIS (Geographical Information System), GPS (Global Positioning System), GSM (The Global System for Mobile Communications) and software based on a cloud platform. Considering the above, the paper highlights the problem of leakages against the background of water deficit in the world and proposes a classification of methods for detecting and estimating the size of leakages. On the basis of available literature sources, selected modern and, in the authors’ opinion, most interesting water loss monitoring systems enabling leak detection and estimation of the amount of wasted water are presented. Then, these methods are analysed, pointing to their strengths and weaknesses in terms of leak detection efficiency.
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Dissertations / Theses on the topic "Water detection"

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Chienthavorn, Orapin. "Detection in superheated water chromatography." Thesis, Loughborough University, 1999. https://dspace.lboro.ac.uk/2134/32394.

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Superheated water has been used successfully as an eluent in liquid chromatography and has been coupled to various modes of detection, ultraviolet (UV), fluorescence, and nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS). A number of compounds were examined on poly(styrene-divinylbenzene) (PS-OVB), polybutadiene (PBO), and octadecylsilyl bonded silica (OOS) column with isothermal and temperature programmes.
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Bergua, Canudo José Francisco. "Nanobiosensors for contaminants detection in water." Doctoral thesis, TDX (Tesis Doctorals en Xarxa), 2020. http://hdl.handle.net/10803/670394.

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Aquesta tesi té com a objectiu desenvolupar biosensors per al monitoratge ambiental. Primer, s'ha desenvolupat un biosensor colorimètric basat en lateral flow strips (LFS) per a la detecció i quantificació d'Escherichia coli com a indicador fecal universal. En aquest cas, nanopartícules d'or (AuNP) s'utilitzen com a transductors òptics i anticossos policlonals com a elements de bioreconeixement per capturar, marcar i indicar la presència del bacteri. Paral·lelament, s'ha desenvolupat un sistema de filtració per millorar la sensibilitat dels LFS. L'optimització del flux de la mostra a través dels diferents materials s'ha realitzat mitjançant una tècnica innovadora basada en el seguiment del flux del bacteri bioluminescent Aliivibrio fischeri, similar en grandària i forma a E. coli. Finalment, aquests LFS s'han provat amb mostres d'aigua de rius i aigües residuals, mostrant una sensibilitat similar i bona reproductibilitat i selectivitat en tots els casos. En segon lloc, s'ha desenvolupat un biosensor de toxicitat bioluminescent per a la detecció i quantificació de pesticides en mostres d'aigua. En particular, Aliivibrio fischeri, un bacteri bioluminescent, s'ha utilitzat com a element de bioreconeixement i transductor perquè augmenta i disminueix la bioluminescència d'acord amb la concentració de compostos tòxics en les mostres d'aigua. A més, l'òxid de grafè (GO) s'ha utilitzat com un potenciador del creixement no específic per promoure el creixement bacterià i augmentar la sensibilitat del sistema al detectar parcialment la bioluminescència emesa per A. fischeri. La detecció i quantificació de la bioluminescència es va realitzar amb un telèfon mòbil que permet una avaluació de la toxicitat de l'aigua de forma portàtil, més barata, i més fàcil d'utilitzar que els estàndards en els laboratoris. En tercer lloc, s'ha desenvolupat una plataforma portàtil basada en un telèfon mòbil per a realitzar assajos que requereixen una detecció òptica, incloent assaigs colorimètrics, fluorescents i bioluminescents. Aquesta plataforma s'ha utilitzat per dur a terme i analitzar proves ELISA estàndard basades en resultats colorimètrics per a la detecció de la immunoglobulina humana i una proteïna del coronavirus. A més, el sistema permet realitzar un seguiment de l'agregació de AuNPs en funció del color de la solució. D'altra banda, la plataforma s'ha utilitzat per detectar i quantificar quantum dots (QD) i altres indicadors fluorescents (per exemple, fluoresceïna), i per a fer proves ELISA fluorescents basades en aquests transductors. A més, la plataforma permet realitzar lectures bioluminiscents amb aplicacions com l'anàlisi de la toxicitat de l'aigua. Finalment, la plataforma és útil per al cultiu de bacteris, mesuraments de terbolesa i detecció de resistència a antibiòtics.
Esta tesis tiene como objetivo desarrollar biosensores para el monitoreo ambiental. Primero, se ha desarrollado un biosensor colorimétrico basado en lateral flow strips (LFS) para la detección y cuantificación de Escherichia coli como indicador fecal universal. En este caso, nanopartículas de oro (AuNP) se utilizan como transductores ópticos y anticuerpos policlonales como elementos de bioreconocimiento para capturar, marcar e indicar la presencia de la bacteria. Paralelamente, se ha desarrollado un sistema de filtración para mejorar la sensibilidad de las LFS. La optimización del flujo de la muestra a través de los diferentes materiales ha realizado mediante una técnica innovadora basada en el seguimiento del flujo de la bacteria bioluminiscente Aliivibrio fischeri, similar en tamaño y forma a E. coli. Finalmente, estos LFB se han probado con muestras de agua de ríos y aguas residuales, mostrando una sensibilidad similar y buena reproducibilidad y selectividad en todos los casos. En segundo lugar, se ha desarrollado un biosensor de toxicidad bioluminiscente para la detección y cuantificación de pesticidas en muestras de agua. En particular, Aliivibrio fischeri, una bacteria bioluminiscente, se ha utilizado como elemento de bioreconocimiento y transductor porque aumenta y disminuye la bioluminiscencia de acuerdo con la concentración de compuestos tóxicos en las muestras de agua. Además, el óxido de grafeno (GO) se ha utilizado como un potenciador del crecimiento no específico para promover el crecimiento bacteriano y aumentar la sensibilidad del sistema al detectar parcialmente la bioluminiscencia emitida por A. fischeri. La detección y cuantificación de la bioluminiscencia se realizó con un teléfono móvil que permite una evaluación de la toxicidad del agua de forma portátil, más barata, y más fácil de usar que los estándares en los laboratorios. En tercer lugar, se ha desarrollado una plataforma portátil basada en un teléfono móvil para realizar ensayos que requieren una detección óptica, incluyendo ensayos colorimétricos, fluorescentes y bioluminiscentes. Esta plataforma se ha utilizado para llevar a cabo y analizar pruebas ELISA estándar basadas en resultados colorimétricos para la detección de la inmunoglobulina humana y una proteína del coronavirus. Además, el sistema permite realizar un seguimiento de la agregación de AuNPs en función del color de la solución. Por otro lado, la plataforma se ha utilizado para detectar y cuantificar quantum dots (QD) y otros indicadores fluorescentes (por ejemplo, fluoresceína), así como para realizar pruebas ELISA fluorescentes basadas en estos transductores. Además, la plataforma permite realizar lecturas bioluminiscentes con aplicaciones como el análisis de la toxicidad del agua. Finalmente, la plataforma es útil para el cultivo de bacterias, mediciones de turbidez y detección de resistencia a antibióticos.
This thesis aims to develop biosensing tools for environmental monitoring. First, a colorimetric lateral flow biosensor (LFB) has been developed for the detection and quantification of Escherichia coli as a universal fecal indicator. Gold nanoparticles (AuNPs) are used as optical transducers and polyclonal antibodies as the biorecognition elements to capture, tag and indicate the presence of the bacteria. In parallel, a filtration system has been developed to improve the sensitivity of the LFBs. The optimization of the flow properties of the different lateral flow materials has been done by an innovative technique based on the tracking of the flow of the bioluminescent bacteria Aliivibrio fischeri, similar in size and shape to E. coli. Eventually, these LFBs have been tested with river and sewage waters, showing similar sensitivity and good reproducibility and selectivity in all the cases. Second, a bioluminescent toxicity biosensor has been developed for the detection and quantification of pesticides in water samples. In particular, Aliivibrio fischeri, a bioluminescent bacteria, has been used as the biorecognition element and the transducer because it turns up and down bioluminescence according to the concentration of toxic compounds within the water samples. Besides, graphene-oxide (GO) has been used as a non-specific growth enhancer to promote bacterial growth and increase the sensitivity of the system by partially screening the bioluminescence emitted by A. fischeri. The detection and quantification of the bioluminescence has been performed by a smartphone that allows for a cheaper, more user friendly, and portable water toxicity assessment. Third, a smartphone-based portable platform has been developed for the performance of optical sensing, including colorimetric, fluorescent, and bioluminescent assays. This platform has been used to perform and read standard ELISA tests based on colorimetric outputs for human IgG and coronavirus detection. In addition, the system allows for tracking AuNPs aggregation based on the color output of the solution. On the other hand, the platform has been used to detect and quantify quantum dots (QDs) and other fluorescent reporters (i.e. fluorescein), as well as performing fluorescent ELISA tests based on these transducers. Next, the platform allows for bioluminescent readouts with applications in toxicity analysis. Eventually, the platform is suitable for bacteria culture, turbidity measurements, and drug screening for antibiotic resistances assessment.
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Gao, Yan. "Leak detection in plastic water pipes." Thesis, University of Southampton, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.423122.

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Samuelsson, Oscar. "Fault detection in water resource recovery facilities." Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-329777.

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Reliable sensor values are important for resource-efficient control and operations of wastewater treatment processes. Automatic fault detection methods are necessary to monitor the increasing amount of data produced in any modern water resource recovery facility (WRRF). Most on-line measurements exhibit large variations under normal conditions, due to considerable variations in the influent flow. The work reported in this licentiate thesis deals with fault detection in WRRFs. In the first paper, we studied how Gaussian process regression (GPR), a probabilistic machine learning method, could be applied for fault detection in WRRFs. The results showed that the standard parameter estimation method for GPR suffered from local optima which could be solved by instead estimating the distribution of the parameters with a sequential Monte Carlo algorithm (GPR-SMC). The GPR-SMC allowed for automatic estimation of missing data in a simulated influent flow signal with high noise, which is a representative signal for on-line sensors in WRRFs. In addition, the GPR-SMC provided uncertainty predictions for the estimated data and accurate sensor noise estimates. Care should be taken in selecting a suitable kernel for GPR, since the results were in contrast to the general assumption that prior knowledge can easily be encoded by means of selecting a proper kernel. Here, the autocorrelation graph was found useful as diagnostic tool for selecting a proper kernel. In the second paper, we studied how active fault detection (AFD) could be used to reveal information about the sensor status. The AFD was implemented by evaluating the change in a dissolved oxygen (DO)-signal caused by the sensor's automatic cleaning system. Fault signatures were obtained for fouling and several other sensor faults such as a worn out or mechanically damaged membrane. This demonstrates the potential of AFD, not only for fault detection, but also for fault diagnosis. Interestingly, the progression of the sensor bias due to organic biofilm fouling differed depending on the measurement technique used within the DO-sensor. This is new knowledge that is valuable for process control and should be further studied. The AFD was implemented on a full scale system to demonstrate its applicability, which is rarely done in research papers in the field of WRRFs.
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Gelin, Martin, and Skogsberg Rikard Fridsén. "Water Contamination Detection With Artificial Neural Networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-295605.

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Drinking water is one of our most important re- sources, so the ability to reliably monitor harmful contaminations in our water distribution network is vital. In order to minimize false alarms for water monitoring, while keeping a high sensitivity, a machine learning approach was evaluated in this project. Measurement data captured with a new kind of sensor, an electronic tongue, was provided by Linköping university. The solution was an artificial neural network, in the structure of an Autoencoder, which could learn the dynamic behaviour of natural deviations and with a false alarm rate of approximately one false alarm per week. This was done by evaluating the data and assembling an input structure to account for daily cyclic phenomena, which then was used to train the neural network. The solution could detect anomalies as small as 1.5% by comparing the input with the reconstructed vector, and raise an alarm. In conclusion, an Autoencoder is a viable method for detecting anomalies in water quality.
Drickvatten är en av våra mest värdefulla tillgångar, det är därför mycket viktigt att det finns sätt att pålitligt övervaka om dricksvattennätet blivit förorenat. För att kunna minimera antalet falsklarm och samtidigt ha hög känslighet mot dessa föroreningar undersöktes och implementerades en lösning med maskininlärningsalgoritmer. Mätdata tillhandahölls av Linköpings universitet och kom från en ny sensor kallad elektronisk tunga. Lösningen var ett artificiellt neuralt nätverk i form av en Autoencoder, som kunde lära sig det dynamiska beteende som ofarliga avvikelser utgjorde. Detta gav en lösning som i medel gav ett falsklarm per sju dagar. Detta gjordes genom att utvärdera rådata och konstruera en struktur på indata som tar hänsyn till dygnsbunda naturliga fenomen. Denna struktur användes sedan för att träna det neurala nätverket. Lösningen kunde upptäcka fel ner till 1.5% genom att jämföra indata med den rekonstruerade vektorn, och på så sätt ge ett alarm.
Kandidatexjobb i elektroteknik 2020, KTH, Stockholm
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Nobliá, Matilda, and Christian Ryan. "Contamination Event Detection in Water Distribution Systems." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214698.

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In any society, making sure that its citizens havea clean water supply is a fundamental issue. By modernizingthe way water distribution systems (WDSs) are monitored andcontrolled, the impact of contamination can be maintained andminimized. By using sensors that monitor relevant physicalparameters, a system that detects contamination and limitspopulation exposure can be designed. To achieve this, the workpresented in this report is focused on three main topics.Firstly, parameters for determining water quality are examined.This is the basis for choosing relevant sensors. Secondly,a study of contamination event detection (CED) is presented, inparticular a method to determine whether water is contaminatedor not based on sensor measurements is proposed. This iscompleted through the use of binary hypothesis testing as wellas examining existing sensors. Thirdly, the problem of optimalsensor placement in a WDS is studied. In extension, a greedyalgorithm is implemented to optimally place sensors in a modelof real-world network.
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Mvelase, Mashinga Johannes. "Radon escape from water." Thesis, University of the Western Cape, 2010. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_3869_1307688700.

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This thesis aims to measure the rate of radon loss from water in a systematic way. The dependence on surface area, temperature and concentration will be investigated. The experiments were done at UWC by creating radon using radium sources and then measuring the radon concentrations inside a vacuum chamber to obtain the speed of radon escape from the water. The results are compared to a model [Cal 2002] where the radon concentration in the air and hence the transfer rate is measured using a RAD7 radon detector. Since the equations cannot be solved analytically, a numerical solution is employed. The radon transfer velocity coefficient is found to be (1.9±
0.5)×
10-6m/s. This value indicates that the escape of radon should not be a problem when a sample is open to the air for a minute or two.

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Walrath, Karen Elizabeth. "Evanescent wave spectroscopy for detection of water and water treeing in polymers." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/40582.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
Includes bibliographical references (p. 185-191).
by Karen Elizabeth Walrath.
Ph.D.
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Wennberg, Aina Charlotte. "PCR-detection of Vibrio cholerae in ballast water." Thesis, Norwegian University of Science and Technology, Department of Biotechnology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-6883.

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Parent, Uribe Santiago. "Endotoxins detection and control in drinking water systems." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=100231.

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Endotoxins are a constituent of the lipopolysaccharide (LPS) complexes present in the outer layer of the cell wall of most Gram-negative bacteria and some cyanobacteria. The ingestion by a typical adult of amounts exceeding 1,000 endotoxin units (EUs) can cause fever, diarrhoea, vomiting, acute respiratory illnesses, and lung inflammation. In contrast, much smaller doses may lead to protective immunity against allergic diseases.
Endotoxins can be released in the air as well as in the water; previous studies have mainly focused on airborne endotoxins. Although many studies on endotoxins in raw and treated drinking waters have been performed, few have assessed seasonal variations and none have been conducted in Eastern Canada. Furthermore, a clear understanding of removal of endotoxins by various water treatment processes is still required.
Two methods to measure the concentrations of endotoxin were used and compared, the Limulus Amebocyte Lysate test (LAL) and the recombinant Factor C test (rFC). Raw water samples were taken from various drinking water sources around the Island of Montreal. The effects of free chlorine, UV radiation, and ozone were studied in batch experiments on filtered water samples via typical dosages and fluences used in drinking water treatment facilities. Residual concentrations for free chlorine were 0.8 and 1.6 mg/L; ozone doses were 0.5 and 1 mg/L; UV fluences were 40 and 100 mWs/cm2. Detention times of 20 and 60 minutes were tested for chlorine and 5 and 20 minutes for ozone. Grab sampling from three drinking water treatment plants in the Montreal area was performed during the months of June and late August/September 2006 and January 2007. Processes at these plants include coagulation and flocculation, sand filtration, ozonation and disinfection by chlorine. To test the variation in endotoxin concentrations during a sand filter cycle, samples were withdrawn directly from a filter in one of the treatment plants studied. The filtration cycle, from one backwash to the next one, lasts 72 h. Samples were collected immediately before the backwash, at the beginning and at the end of the ripening period, at the beginning of the filtration cycle and 48 h later, which corresponds to a half cycle period.
Of the two endotoxin detection methods used, LAL consistently gave slightly higher values compared to rFC; rFC also required more expensive hardware, but the method was less tedious and reagent costs were lower. Results presented, unless otherwise stated, were obtained with the rFC method. Endotoxin levels decreased in raw water samples between June and September. Concentrations ranged from 20 to 30 EU/mL in June, and decreased to 10 to 14 EU/mL in August and beyond. For the disinfection processes, the UV and free chlorine doses tested had little or no effect on the endotoxin concentrations, but ozone reduced the concentrations by up to 75%. Sand filtration and flocculation showed significant endotoxin removal efficiencies (50--60%). Levels remained around 5 EU/mL throughout the remaining treatment processes regardless of the influent concentration. Hence, endotoxin inactivation by free chlorine and UV does not occur with typical doses used in drinking water treatment plants; in contrast, flocculation and sand filtration, as well as ozonation, are much more effective.
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Books on the topic "Water detection"

1

Association, American Water Works, ed. Water audits and leak detection. Denver, CO: American Water Works Association, 1990.

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1935-, Schwartzbrod L., ed. Viruses in water systems: Detection and identification. New York: VCH, 1988.

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Clark, Stuart A., K. Clive Thompson, C. William Keevil, and Mark S. Smith, eds. Rapid Detection Assays for Food and Water. Cambridge: Royal Society of Chemistry, 2001. http://dx.doi.org/10.1039/9781847551818.

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A, Clark Stuart, ed. Rapid detection assays for food and water. Cambridge: Royal Society of Chemistry, 2001.

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Manea, F. Wet electrochemical detection of organic impurities. New York: Nova Science Publishers, 2010.

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Abo-Amer, Aly E. Molecular approach for detection of waterborne pathogens. Hauppauge, N.Y: Nova Science Publisher's, 2011.

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Foundation, AWWA Research, and United States. Environmental Protection Agency, eds. Improved mycobacterium avium complex detection methods. Denver, CO: Awwa Research Foundation, 2008.

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Offenhartz, Barbara H. Enzyme-based detection of chlorinated hydrocarbons in water. Cincinnati, OH: U.S. Environmental Protection Agency, Hazardous Waste Engineering Research Laboratory, 1985.

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Offenhartz, Barbara H. Enzyme-based detection of chlorinated hydrocarbons in water. Cincinnati, OH: U.S. Environmental Protection Agency, Hazardous Waste Engineering Research Laboratory, 1985.

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United States. National Aeronautics and Space Administration., ed. Advanced water vapor lidar detection system: Final report. [Washington, DC: National Aeronautics and Space Administration, 1998.

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Book chapters on the topic "Water detection"

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Yang, Hongwei, and Wenjin Zhao. "Detection of Water." In Encyclopedia of Lunar Science, 1–9. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-05546-6_122-1.

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Yang, Hongwei, and Wenjin Zhao. "Detection of Water." In Encyclopedia of Lunar Science, 197–204. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-319-14541-9_122.

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Norgren, R. "Sensory Detection of Water." In Thirst, 221–31. London: Springer London, 1991. http://dx.doi.org/10.1007/978-1-4471-1817-6_13.

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Tharani, Mohbat, Abdul Wahab Amin, Fezan Rasool, Mohammad Maaz, Murtaza Taj, and Abubakar Muhammad. "Trash Detection on Water Channels." In Neural Information Processing, 379–89. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92185-9_31.

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Starr, Justin. "Other Leak Detection Technologies." In Water and Wastewater Pipeline Assessment Technologies, 133–50. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9780429198731-7.

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Haap, Jasmin, and Edith Classen. "Analytical Approach for the Detection of Micro-sized Fibers from Textile Laundry." In Springer Water, 73–79. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71279-6_11.

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Darsana, P., and K. Varija. "Leakage Detection Studies for Water Supply Systems—A Review." In Water Resources Management, 141–50. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5711-3_10.

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Shaban, Amin, and Farouk El-Baz. "Landsat Satellite Images for Lineaments Detection: A Tool to Identify Groundwater Productivity in Lebanon." In Springer Water, 251–71. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15549-9_15.

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Wainwright, Milton. "Detection Methods for Water-Borne Pathogens." In An Introduction to Environmental Biotechnology, 95–99. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5251-2_9.

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Shah, Krupal, Shreya Sabu, and Vedashree Chaphekar. "Water Leakage Detection Using Neural Networks." In Proceedings of the Future Technologies Conference (FTC) 2020, Volume 1, 484–98. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63128-4_37.

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Conference papers on the topic "Water detection"

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Balazs, Zoltan, Sveta Miladinov, and Chris Pickard. "Breach detection system testing methodology." In 2014 Second Workshop on Anti-malware Testing Research (WATeR). IEEE, 2014. http://dx.doi.org/10.1109/water.2014.7015756.

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Markel, Zane, and Michael Bilzor. "Building a machine learning classifier for malware detection." In 2014 Second Workshop on Anti-malware Testing Research (WATeR). IEEE, 2014. http://dx.doi.org/10.1109/water.2014.7015757.

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Jackson, Darren, Kaare Anderson, and Weston Heuer. "Liquid Water Detection Algorithm for the Magnetostrictive Ice Detector." In International Conference on Icing of Aircraft, Engines, and Structures. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2023. http://dx.doi.org/10.4271/2023-01-1430.

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<div class="section abstract"><div class="htmlview paragraph"> For nearly a century, ice build-up on aircraft surfaces has presented a safety concern for the aviation industry. Pilot observations of visible moisture and temperature has been used a primary means to detect conditions conducive to ice accretion on aircraft critical surfaces. To help relieve flight crew workload and improve aircraft safety, various ice detection systems have been developed. Some ice detection systems have been successfully certified as the primary means of detecting ice, negating the need for the flight crew to actively monitor for icing conditions. To achieve certification as a Primary ice detection system requires detailed substantiation of ice detector performance over the full range of icing conditions and aircraft flight conditions. Some notable events in the aviation industry have highlighted certain areas of the icing envelope that require special attention. </div><div class="htmlview paragraph"> Following the CRJ accident in Fredericton, New Brunswick, Canada, in December 1997, industry interest and scrutiny in the performance of ice detection systems at warmer temperatures has increased. [ <span class="xref"> 1 </span> ] In particular, the concern lies in potential differences between ice accretion on the ice detector sensing surfaces and the critical aircraft surfaces (e.g. wing, nacelle). This has led both the FAA and EASA to update advisory material to ensure that ice detector performance at low freezing fractions is addressed. </div><div class="htmlview paragraph"> To minimize this concern and alleviate the risk, Collins Aerospace (Rosemount Aerospace, Inc.) has developed an enhanced ice detection algorithm for its magnetostrictive ice detector (MID). Traditionally the MID has only been used to detect ice accretion resulting from supercooled liquid water. This new algorithm enables the MID to sense the presence of non-freezing liquid water on its sensing surface and couple that with ambient temperature information to provide a signal when conditions may be conducive for ice accretion on critical aircraft surfaces. </div><div class="htmlview paragraph"> The discussion in this paper describes the development of this new algorithm for the MID and performance verification of the algorithm through icing wind tunnel testing and icing flight tests. </div></div>
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Gao, Shang-qi, Zhi-bin Sun, Yuan-da Jiang, Chao Wang, and Ke-ming Du. "Optical properties of water for the Yangbajing water cherenkov detector." In International Symposium on Photoelectronic Detection and Imaging 2011, edited by John C. Zarnecki, Carl A. Nardell, Rong Shu, Jianfeng Yang, and Yunhua Zhang. SPIE, 2011. http://dx.doi.org/10.1117/12.900762.

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Arredondo, Armando Vazquez. "DETECTION OF WATER LEAKS USING EFSOP WATER DETECTION TECHONOLOGY®." In 46º Seminário de Aciaria - Internacional. São Paulo: Editora Blucher, 2017. http://dx.doi.org/10.5151/1982-9345-26678.

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Nath, Pabitra, Trishna Das, Utpal Bora, Nabadweep Chamuah, Iftak Hussain, and Diganta Hatiboruah. "Accurate estimation of mercury level concentration in water using smartphone." In Optical Sensing and Detection, edited by Francis Berghmans and Anna G. Mignani. SPIE, 2018. http://dx.doi.org/10.1117/12.2304710.

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Mambretti, S., and E. Orsi. "Genetic algorithms for leak detection in water supply networks." In Urban Water 2012. Southampton, UK: WIT Press, 2012. http://dx.doi.org/10.2495/uw120061.

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Mukherji, Soumyo, and Sutapa Chandra. "Conducting polymer-based optical sensor for heavy metal detection in drinking water." In Optical Sensing and Detection, edited by Francis Berghmans and Anna G. Mignani. SPIE, 2018. http://dx.doi.org/10.1117/12.2306719.

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Faruque, Hossain Mansur Resalat, Md Zubair Ebne Rafique, Jing Bai, and Yu Yao. "Water Bubble Detection in Turbid Water Using Polarimetric imaging." In CLEO: Applications and Technology. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/cleo_at.2023.jtu2a.67.

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We investigated the feasibility of using polarimetric imaging for water bubble detection in turbid water. We demonstrated that the best strategy is to utilize total internal reflection and capture the degree of circular polarization images.
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Chaudhari, Archana, Shaunak Joshi, Shekhar Shegokar, and Krushna Rudrawar. "Water Weed Hyacinth Detection." In 2023 International Conference on Integration of Computational Intelligent System (ICICIS). IEEE, 2023. http://dx.doi.org/10.1109/icicis56802.2023.10430233.

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Reports on the topic "Water detection"

1

Apps, Christopher, and Tyler Johnson. PR244-173902-R01 On-water Leak Detection System Evaluation. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), July 2018. http://dx.doi.org/10.55274/r0011504.

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The hydrocarbon industry is directing efforts towards reducing the environmental impact of operation through improving pipeline performance and addressing evolving regulatory requirements. As a result, many different external leak detection technologies have been recently developed; however, it is challenging to test these systems with real hydrocarbon products. The research project described herein evaluated the performance of six external leak detection systems intended to identify the presence of hydrocarbon products on the surface of water. The scope was limited to an idealized freshwater environment. Tests were conducted with five hydrocarbon test fluids (gasoline, diesel, Synthetic Sweet Blend, Access Western Blend and Cold Lake Blend) along with three additional test fluids (canola oil, salt water and motor oil). Canola oil was considered as a candidate surrogate fluid and salt water as a possible source of false alarms, while motor oil was considered as a candidate surrogate fluid or a false alarm trigger, depending on the field application. Testing was performed by releasing each test fluid onto the surface of a water basin with six sensors located equidistant from the release point. Each sensor's response to contact with the test fluid was monitored and compared based on time to detection and estimated slick thickness at detection.
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Apps, Christopher. PR-244-193900-R01 Oil-on-water Leak Detection Technology Evaluation Phase 2. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), January 2020. http://dx.doi.org/10.55274/r0011647.

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Industry is directing efforts toward reducing the environmental impact of operation through improving pipeline performance and addressing evolving regulatory requirements. As a result, external leak detection technologies have been recently developed; however, it is challenging to test these systems with real hydrocarbon products in-situ. This research project was developed to assess these external leak detection technologies' abilities to identify the presence of hydrocarbon products on the surface of water. In the first phase of the project, testing was limited to an idealized freshwater environment under ambient conditions. The second phase, described herein, was expanded to a freshwater environment under freezing conditions, where the surface of the water has frozen over. Testing was performed by releasing each test fluid (diesel, Synthetic Sweet Blend and Access Western Blend) into basins containing individual sensors. Releases were performed above the ice surface, below the ice surface, and onto the water surface after freeze/thaw cycles. Each sensor's response to contact with the test fluid was monitored and compared based on time to detection and estimated slick thickness at detection.
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Wick, Charles H., and Patrick E. McCubbin. Water Sample Analysis With the Integrated Virus Detection System. Fort Belvoir, VA: Defense Technical Information Center, June 2010. http://dx.doi.org/10.21236/ada532453.

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Allendorf, Mark D. Colorimetric Detection of Water Vapor Using Metal-Organic Framework Composites. Office of Scientific and Technical Information (OSTI), December 2017. http://dx.doi.org/10.2172/1415015.

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C Svoboda, R., A. Bernstein, W. Coleman, and S. Dazeley. Feasibility Study for Large Water-Based Neutron and Neutrino Detection. Office of Scientific and Technical Information (OSTI), March 2007. http://dx.doi.org/10.2172/1036852.

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Deininger. PR-443-13605-R01 Sensors for Gas Quality Monitoring. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), May 2014. http://dx.doi.org/10.55274/r0010127.

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The purpose of this project was to determine the suitability of low cost environmental air quality sensors, for detection of pipeline gas quality. In particular, this project examined options for detection and quantification of hydrogen sulfide (H2S), water (H2O), and oxygen (O2). All of the sensors used were based on Synkeras existing anodic aluminum oxide (AAO) platform and detection chemistry. The key challenge of this effort was laboratory based demonstration of the feasibility of detecting these three components in natural gas at pressures exceeding 1 atmosphere
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Sun, Jian-Qiao. Sample Concentration Systems for Chemical and Biological Agent Detection in Water. Fort Belvoir, VA: Defense Technical Information Center, December 2001. http://dx.doi.org/10.21236/ada399976.

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Nelson, Matthew P., and Patrick J. Treado. Optical Detection of Biological and Chemical Threats in Food and Water. Fort Belvoir, VA: Defense Technical Information Center, August 2006. http://dx.doi.org/10.21236/ada455251.

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Cooper, Robert Lee, Peter Marleau, and Patrick J. Griffin. Ground water and snow sensor based on directional detection of cosmogenic neutrons. Office of Scientific and Technical Information (OSTI), June 2011. http://dx.doi.org/10.2172/1177063.

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Rose, Joan B., and D. J. Grimes. Reevaluation of Microbial Water Quality: Powerful New Tools for Detection and Risk Assessment. Fort Belvoir, VA: Defense Technical Information Center, May 2001. http://dx.doi.org/10.21236/ada389605.

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