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Готові списки джерел за темами / Environmental health Data processing / Статті в журналах

Щоб переглянути інші типи публікацій з цієї теми, перейдіть за посиланням: Environmental health Data processing.

Статті в журналах з теми "Environmental health Data processing"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 11 лютого 2022

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1

Ivanov, Alexander, and Alexander Platov. "Environmental monitoring based on data processing of Internet of Things." E3S Web of Conferences 136 (2019): 01041. http://dx.doi.org/10.1051/e3sconf/201913601041.

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The concept of online monitoring of the urban environment is proposed. It is based on the online processing of hydrometeorological and traffic information received through the Internet of Things. The traditional approach of the Internet of things includes transfer and storage of huge arrays of measurements in digital form. This concept of online monitoring is primarily an analysis, evaluation of the results of processing information received from wireless networks. The concept was implemented at Nizhny Novgorod State University of Architecture and Civil Engineering in several services including Eco-routes, Quite-routes, in which the air pollution of the urban environment by vehicle emissions and the noise level from traffic flows are estimated in real time mode. The calculation is based on meteorological data and traffic flow velocity. The calculation and assessment of environment pollution is carried out at the request of the user via Internet. The concept includes micro weather and algal blooming monitoring of reservoirs and ponds. Developed services is the first to provide free short time health risk assessment for both decision makers and common internet users.

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2

Cummings, Stuart W. "Distributed Databases for Clinical Data Processing." Drug Information Journal 27, no. 4 (October 1993): 949–56. http://dx.doi.org/10.1177/009286159302700403.

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3

Pimazzoni, Monica. "Global Data Management: A Winning Approach to Clinical Data Processing." Drug Information Journal 32, no. 2 (April 1998): 569–71. http://dx.doi.org/10.1177/009286159803200230.

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4

Woods, Valerie. "Musculoskeletal disorders and visual strain in intensive data processing workers." Occupational Medicine 55, no. 2 (March 1, 2005): 121–27. http://dx.doi.org/10.1093/occmed/kqi029.

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5

Jia, Xiao Yu, and Tao Li. "Data Processing in Environmental Performance of Building Systems Applied in Residential Design." Advanced Materials Research 978 (June 2014): 145–48. http://dx.doi.org/10.4028/www.scientific.net/amr.978.145.

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In the face of the global energy and environment problems, our country carries out some measures toward energy-saving environmental protection route in the construction field, which requires architects must start from the overall design concept for the preliminary design, fully considering the benefits between the various elements of environmental performance of building system. Environmental performance of building systems involves building system, the indoor environment of regional environmental impact and influence on the earth's environment, is a complex system. This paper introduces in detail the effects of five important factors in residential design in order to save energy, the effective use of resources to build low environmental load safety, healthy, efficiency, comfortable living space, people, environment and the construction of coexistence, continuous development of new construction mode.

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6

Arisetty, Murty. "A Team-Based Approach to Clinical Data Processing." Drug Information Journal 19, no. 1 (January 1985): 81–84. http://dx.doi.org/10.1177/009286158501900113.

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7

Leighton, Charles C. "Clinical Data Processing in Retrospect and in Prospect." Drug Information Journal 20, no. 1 (January 1986): 7–15. http://dx.doi.org/10.1177/009286158602000103.

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8

Gillum, Terry L., Robert H. George, and Jack E. Leitmeyer. "An Autoencoder for Clinical and Regulatory Data Processing." Drug Information Journal 29, no. 1 (January 1995): 107–13. http://dx.doi.org/10.1177/009286159502900115.

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9

Hrzic, Rok, Timo Clemens, Daan Westra, and Helmut Brand. "Comparability in Cross-National Health Research Using Insurance Claims Data: The Cases of Germany and The Netherlands." Das Gesundheitswesen 82, S 01 (November 19, 2019): S83—S90. http://dx.doi.org/10.1055/a-1005-6792.

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Abstract Objective Comparison is a key method in learning about what works in health and healthcare. We discuss the importance of comparability in cross-national health research using health insurance claims data, develop a framework to systematically asses these threats and apply it to the German (DaTraV) and Dutch (Vektis) national-level insurance claims datasets. Methods We propose a framework of threats to the comparability of health insurance claims databases, which includes three domains: (1) representation of populations compared, (2) data sources and data processing and (3) database contents and availability for research purposes. We apply the framework to analyze the comparability of DaTraV and Vektis databases using publicly available information (organization’s websites, scientific publications) and our experiences from an interregional project on rare diseases (EMRaDi). Results Both databases were created for the same purpose (morbidity-based risk adjustment) and use the same underlying sources of data. Differences in population representation and uncertainty about data processing procedures represent potential sources of incomparability. Access for research purposes is feasible in both databases but may be subject to long processing time. Conclusions We find important threats to the comparability of the Dutch and German national insurance claims databases and by extension to validity of any comparative health studies that rely on them. Standard adjustment techniques, making more information available about data collection and processing procedures and adding more diagnosis-related descriptors offer ways to overcome the identified threats to comparability.

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10

Kraft, Robin, Ferdinand Birk, Manfred Reichert, Aniruddha Deshpande, Winfried Schlee, Berthold Langguth, Harald Baumeister, Thomas Probst, Myra Spiliopoulou, and Rüdiger Pryss. "Efficient Processing of Geospatial mHealth Data Using a Scalable Crowdsensing Platform." Sensors 20, no. 12 (June 18, 2020): 3456. http://dx.doi.org/10.3390/s20123456.

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Smart sensors and smartphones are becoming increasingly prevalent. Both can be used to gather environmental data (e.g., noise). Importantly, these devices can be connected to each other as well as to the Internet to collect large amounts of sensor data, which leads to many new opportunities. In particular, mobile crowdsensing techniques can be used to capture phenomena of common interest. Especially valuable insights can be gained if the collected data are additionally related to the time and place of the measurements. However, many technical solutions still use monolithic backends that are not capable of processing crowdsensing data in a flexible, efficient, and scalable manner. In this work, an architectural design was conceived with the goal to manage geospatial data in challenging crowdsensing healthcare scenarios. It will be shown how the proposed approach can be used to provide users with an interactive map of environmental noise, allowing tinnitus patients and other health-conscious people to avoid locations with harmful sound levels. Technically, the shown approach combines cloud-native applications with Big Data and stream processing concepts. In general, the presented architectural design shall serve as a foundation to implement practical and scalable crowdsensing platforms for various healthcare scenarios beyond the addressed use case.

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11

Wolfe, Karen. "Data Base or Word Processing: Knowing the Difference Can Make the Difference." AAOHN Journal 40, no. 4 (April 1992): 194–95. http://dx.doi.org/10.1177/216507999204000407.

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12

Le, Tinh Duc, Hien Van Le, Linh Thuy Nguyen, Thanh Kim Thi Nguyen, and Duy Tien Le. "Application of correlation and regression analysis between GPS - RTK and environmental data in processing the monitoring data of cable - stayed." Journal of Mining and Earth Sciences 61, no. 6 (December 31, 2020): 59–72. http://dx.doi.org/10.46326/jmes.2020.61(6).07.

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Structural Health Monitoring system - SHMs has been playing a vital role in monitoring large - scale structures during their performance in a lifetime, especially with the long - span bridge, such as a suspended bridge or cable - stayed bridge. In a SHM system, many kinds of sensors are used to set up at the specific locations in order to monitor and detect any changes of structures in real - time based on the changes of monitoring data as well as the changes of correlation among monitoring data types. This paper proposes a method of applying the correlation and regression analysis for processing the displacement monitoring data acquired by GPS - RTK considering the effects of environmental factors such as temperature and wind - speed. The results show that the air - temperature has high correlation with the displacements of a cable - stayed bridge acquired by GPS - RTK measurement along to specific directions while the wind - speed has low correlation. Then the general displacement of the target bridge could be recognized and regression equation is also built to predict the bridge displacement under effects of the air temperature.

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13

Noraziah, A., Mohammed Adam Ibrahim Fakherldin, Khalid Adam, and Mazlina Abdul Majid. "Big Data Processing in Cloud Computing Environments." Advanced Science Letters 23, no. 11 (November 1, 2017): 11092–95. http://dx.doi.org/10.1166/asl.2017.10227.

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14

Salsburg, David. "Deming Principles Applied to Processing Data from Case Report Forms." Drug Information Journal 36, no. 1 (January 2002): 135–41. http://dx.doi.org/10.1177/009286150203600117.

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15

Black, Dennis, Kjeld Molvig, Anna Bagniewska, Stan Edlavitch, Cary Fox, Stephen Hulley, and W. McFate Smith. "A Distributed Data Processing System for a Multicenter Clinical Trial." Drug Information Journal 20, no. 1 (January 1986): 83–92. http://dx.doi.org/10.1177/009286158602000113.

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16

Alwitt, Josh, and John Kinney. "The Impact of Document Image Management on Clinical Data Processing." Drug Information Journal 27, no. 4 (October 1993): 995–1000. http://dx.doi.org/10.1177/009286159302700409.

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17

Hunter, Jane, Peter Becker, Abdulmonem Alabri, Catharine van Ingen, and Eva Abal. "Using Ontologies to Relate Resource Management Actions to Environmental Monitoring Data in South East Queensland." International Journal of Agricultural and Environmental Information Systems 2, no. 1 (January 2011): 1–19. http://dx.doi.org/10.4018/jaeis.2011010101.

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The Health-e-Waterways Project is a multi-disciplinary collaboration between the University of Queensland, Microsoft Research and the South East Queensland Healthy Waterways Partnership (SEQ-HWP). This project develops the underlying technological framework and set of services to enable streamlined access to the expanding collection of real-time, near-real-time and static datasets related to water resource management in South East Queensland. More specifically, the system enables water resource managers to access the datasets being captured by the various agencies participating in the SEQ HWP Ecosystem Health Monitoring Program (EHMP). It also provides online access to the statistical data processing tools that enable users to analyse the data and generate online ecosystem report cards dynamically via a Web mapping interface. The authors examine the development of ontologies and semantic querying tools to integrate disparate datasets and relate management actions to water quality indicators for specific regions and periods. This semantic data integration approach enables scientists and resource managers to identify which actions are having an impact on which parameters and adapt the management strategies accordingly. This paper provides an overview of the semantic technologies developed to underpin the adaptive management framework that is the central philosophy behind the SEQ HWP.

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18

Lyons, Ronan A. "How much does quality matter: the value of data." Injury Prevention 26, no. 4 (July 21, 2020): 397–99. http://dx.doi.org/10.1136/injuryprev-2019-043369.

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In a world of competing priorities, accurate production of information on the scale of the injury burden and the effectiveness of prevention-orientated interventions and policies is important; hence, data quality matters. This article surveys the literature about what is known about data quality in the injury field and developments to improve the quality and usability of information, particularly through triangulation of data sources, data linkage and unlocking the potential for more deeply phenotyped data through natural language processing.

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19

Berardy, Andrew, Ujué Fresán, Rodrigo A. Matos, Abigail Clarke, Alfredo Mejia, Karen Jaceldo-Siegl, and Joan Sabaté. "Environmental Impacts of Foods in the Adventist Health Study-2 Dietary Questionnaire." Sustainability 12, no. 24 (December 9, 2020): 10267. http://dx.doi.org/10.3390/su122410267.

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The objective of this study was to use life cycle assessment to estimate the environmental impacts (from farm to factory gate) of the 198 hard-coded line-items included in the food frequency questionnaire of the Adventist Health Study-2 survey and to assess differences among food groups. Life cycle inventories were created using existing data sources and primary data, and their global warming potential (GWP), land use, and water consumption impacts were assessed using the ReCiPe 2016 methodology. In addition to presenting the impacts according to weight and protein content across food groups, we include the novel addition of presenting impacts according to the NOVA classification indicating various levels of processing. Food categories were compared based on one kilogram of edible food, protein food sources were compared based on one kilogram of protein, and NOVA comparisons were based on one serving. In general, meats had the highest environmental impacts per both weight and protein content, while the lowest overall impacts per kilogram came from fruits. Meat analogs had the lowest overall impacts per kilogram of protein, contrary to expectations that additional processing would result in higher environmental impacts when compared to whole plant-based foods. Per serving, ultra-processed foods had the highest GWP, processed foods the highest land use, and minimally processed foods the highest water consumption. Results from this analysis were consistent with other studies. Results from this study suggest that meat and ultra-processed foods have the overall worst environmental impacts, but high water consumption in some minimally processed foods means that those should be carefully considered as well.

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20

Kassekert, R., M. Easwar, M. Glaser, R. Ventham, and A. Bate. "PNS271 Automation in Routine Use for Data Collection and Processing for Scalable Faster RWE Generation." Value in Health 23 (December 2020): S686. http://dx.doi.org/10.1016/j.jval.2020.08.1715.

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21

Pynzaru, Iury V. "HEALTH ASSESSMENT OF WORKERS OF MEAT PROCESSING PLANTS." Hygiene and sanitation 98, no. 3 (April 29, 2019): 280–87. http://dx.doi.org/10.18821/0016-9900-2019-98-3-280-287.

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Health assessment of workers of four meat processing plants in the Republic of Moldova in the 2011-2015 was carried out. The analysis of temporary disability showed the incidence the respiratory diseases (13.9±1.3 cases for 134.0±17.1 days per 100 workers) to prevail in the structure of disability), followed by the diseases of circulatory system (5.90±0.52 cases and 85.0±9.0 days per 100 workers) as well as the diseases of bone and muscular system (3.54±0.67 cases and 55.2±12.9 days per 100 workers), and diseases of digestive system (3.11±0.44 cases and 45.9±6.2 days of 100 workers) and injuries, poisonings and some other consequences of the influence of the external factors (3.02±0.40 cases and 48.8±10.3 days per 100 workers). Indices of the frequency and severity showed a tendency to fall. The index of diseases prevalence showed on average annually decreasing by 6.7 cases per 100 workers (R2 = 0.95), and an index of the duration of diseases for 77.0 days per 100 workers (R2 = 0,95). The meat processing plants suffered from economic losses because of the temporary disability of workers in the amount of 1892434.25 lei/107009.6 dollars. The obtained data indicate the need for the development and implementation of preventive measures.

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22

Elzein, Nahla Mohammed, Mazlina Abdul Majid, Mohammed Fakherldin, and Ibrahim Abaker Targio Hashem. "Distributed Join Query Processing for Big RDF Data." Advanced Science Letters 24, no. 10 (October 1, 2018): 7758–61. http://dx.doi.org/10.1166/asl.2018.13013.

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23

Lys, Candice, Dionne Gesink, Carol Strike, and June Larkin. "Body Mapping as a Youth Sexual Health Intervention and Data Collection Tool." Qualitative Health Research 28, no. 7 (January 5, 2018): 1185–98. http://dx.doi.org/10.1177/1049732317750862.

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In this article, we describe and evaluate body mapping as (a) an arts-based activity within Fostering Open eXpression Among Youth (FOXY), an educational intervention targeting Northwest Territories (NWT) youth, and (b) a research data collection tool. Data included individual interviews with 41 female participants (aged 13–17 years) who attended FOXY body mapping workshops in six communities in 2013, field notes taken by the researcher during the workshops and interviews, and written reflections from seven FOXY facilitators on the body mapping process (from 2013 to 2016). Thematic analysis explored the utility of body mapping using a developmental evaluation methodology. The results show body mapping is an intervention tool that supports and encourages participant self-reflection, introspection, personal connectedness, and processing difficult emotions. Body mapping is also a data collection catalyst that enables trust and youth voice in research, reduces verbal communication barriers, and facilitates the collection of rich data regarding personal experiences.

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24

Richards, John, and Todd Brozell. "Compilation and Evaluation of Ambient Respirable Crystalline Silica Air Quality Data near Sand Quarries and Processing Facilities." Atmosphere 12, no. 7 (July 13, 2021): 903. http://dx.doi.org/10.3390/atmos12070903.

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Ambient respirable crystalline silica air quality is of concern to many communities near mineral processing facilities and to regulatory agencies serving these communities. Accurate air quality data are needed to compare measured respirable crystalline silica concentrations at the fencelines of mineral processing facilities with the published health effect guideline published by the California Office of Health Hazard Assessment (OEHHA). This article is a compilation and evaluation of air quality studies around a diverse set of nineteen sand producing facilities. The respirable crystalline silica air quality data compiled by Air Control Techniques, P.C. and most of the data compiled by other researchers cited in this article have been measured using EPA Reference Method samplers adjusted for respirable crystalline silica sampling and NIOSH Method 7500 X-ray diffraction analyses. The authors conclude that (1) the ambient concentrations in the diverse set of mineral processing facilities were consistently lower than the 3.0 microgram per cubic meter chronic reference exposure level (REL) adopted by OEHHA, (2) upwind-to-downwind fenceline concentration differences were small, and (3) the fenceline t concentrations were often at background concentration levels. The authors recommend additional sampling studies to better characterize background concentrations of ambient respirable crystalline silica.

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25

Dawson, Daniel E., Trevor S. Farthing, Michael W. Sanderson, and Cristina Lanzas. "Transmission on empirical dynamic contact networks is influenced by data processing decisions." Epidemics 26 (March 2019): 32–42. http://dx.doi.org/10.1016/j.epidem.2018.08.003.

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26

Shin, Sung-Hwan, Jeong-Guon Ih, and Hyuk Jeong. "Statistical processing of subjective listening test data for PSQ." Noise Control Engineering Journal 51, no. 4 (2003): 232. http://dx.doi.org/10.3397/1.2839718.

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27

O’Shea, Michael J., Jonas Toupal, Hasibe Caballero-Gómez, Thomas P. McKeon, Marilyn V. Howarth, Richard Pepino, and Reto Gieré. "Lead Pollution, Demographics, and Environmental Health Risks: The Case of Philadelphia, USA." International Journal of Environmental Research and Public Health 18, no. 17 (August 27, 2021): 9055. http://dx.doi.org/10.3390/ijerph18179055.

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Lead (Pb) soil contamination in urban environments represents a considerable health risk for exposed populations, which often include environmental justice communities. In Philadelphia, Pennsylvania (PA), Pb pollution is a major concern primarily due to extensive historical Pb-smelting/processing activity and legacy use of Pb-based paints and leaded gasoline. The U.S. Environmental Protection Agency (USEPA) organized and/or compiled community-driven soil sampling campaigns to investigate Pb content in surface soils across Philadelphia. Using these data (n = 1277), combined with our own dataset (n = 1388), we explored the spatial distribution of Pb content in soils across the city using ArcGIS. While assessing Zone Improvement Plan (ZIP)-code level data, we found strong correlations between factors, such as the percentage of children with elevated blood lead levels (% EBLL) and % minority population as well as between % EBLL and % children in poverty. We developed a “Lead Index” that took demographics, median measured Pb-in-soil content, and % EBLLs into account to identify ZIP codes in need of further assessment. Our results will be used to help lower the Pb-exposure risk for vulnerable children living in disproportionately burdened communities.

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28

Yoo, Sunyong, Dong-Wook Kim, Young-Eun Kim, Jong Heon Park, Yeon-Yong Kim, Kyu-dong Cho, Mi-Ji Gwon, Jae-In Shin, and Eun-Joo Lee. "Data resource profile: the allergic disease database of the Korean National Health Insurance Service." Epidemiology and Health 43 (January 21, 2021): e2021010. http://dx.doi.org/10.4178/epih.e2021010.

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Researchers have been interested in probing how the environmental factors associated with allergic diseases affect the use of medical services. Considering this demand, we have constructed a database, named the Allergic Disease Database, based on the National Health Insurance Database (NHID). The NHID contains information on demographic and medical service utilization for approximately 99% of the Korean population. This study targeted 3 major allergic diseases, including allergic rhinitis, atopic dermatitis, and asthma. For the target diseases, our database provides daily medical service information, including the number of daily visits from 2013 and 2017, categorized by patients’ characteristics such as address, sex, age, and duration of residence. We provide additional information, including yearly population, a number of patients, and averaged geocoding coordinates by eup, myeon, and dong district code (the smallest-scale administrative units in Korea). This information enables researchers to analyze how daily changes in the environmental factors of allergic diseases (e.g., particulate matter, sulfur dioxide, and ozone) in certain regions would influence patients’ behavioral patterns of medical service utilization. Moreover, researchers can analyze long-term trends in allergic diseases and the health effects caused by environmental factors such as daily climate and pollution data. The advantages of this database are easy access to data, additional levels of geographic detail, time-efficient data-refining and processing, and a de-identification process that minimizes the exposure of identifiable personal information. All datasets included in the Allergic Disease Database can be downloaded by accessing the National Health Insurance Service data sharing webpage (https://nhiss.nhis.or.kr).

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29

Behrens, Grit, Klaus Schlender, and Florian Fehring. "Data mining methods of healthy indoor climate coefficients for comfortable well-being." Environmental Protection and Natural Resources 29, no. 3 (September 1, 2018): 7–12. http://dx.doi.org/10.2478/oszn-2018-0013.

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Abstract This article provides information about a currently developed measurement and analysis system ‘Smart Monitoring’, which is used on scientific project in terms of healthy indoor air coefficients, as well as the processing of the collected data for machine learning algorithms. The target is to reduce CO2 emissions caused by wrong ventilation habits in building sector after renovation process in older buildings.

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30

Stasytyte-Bunevičiene, Dalia, Algirdas Juozulynas, and Antanas Jurgelenas. "INFLUENCE OF UNFAVOURABLE ENVIRONMENTAL FACTORS UPON HEALTH OF WORKERS AND CORRECTION OF RESULTANT ALTERATIONS." JOURNAL OF ENVIRONMENTAL ENGINEERING AND LANDSCAPE MANAGEMENT 13, no. 3 (September 30, 2005): 141–45. http://dx.doi.org/10.3846/16486897.2005.9636862.

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Intensified formation of free radicals is one of the most important unfavourable consequences of factors of industry acting upon human organism. Under physiological conditions, antioxidative system preserves from harmful influence of free radicals. To avoid a disturbing influence of oxidative stress upon the processes of human homeosthasis, additional quantities of antioxidants are indispensable. Dynamics of alterations of markers of oxidative stress caused by unfavourable industrial factors of metal processing (chemical agents, vibration, noise) under impact of native biomodulators were studied using native pollen. The programme was performed on 50 workers of metal processing, 9 males and 41 female, who used pollen during a period of 1 month. Control group consisted of 57 persons, 10 males and 47 females living and working under the same conditions. Blood tests (diene conjugates, malonic dialdehyde and katalase) using spectrophotometric methodology were studied before and after the course of treatment. After the treatment, contents of metabolites of lipid peroxidation, diene conjugates and malonic dialdehyde in blood serum essentially reduced. Activity of catalase decreased significantly in blood serum of males and regularly smoking females. In conclusion, presented data demonstrate antioxidative efficiency of native pollen and suggest more often applying of native biomodulators in cases with alterated processes of homeosthasis under impact of unfavourable environmental factors.

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31

Szentmiklósi, L., Zs Révay, and G. L. Molnár. "Three-dimensional data processing for time resolved gamma-ray spectrometry." Journal of Radioanalytical and Nuclear Chemistry 265, no. 2 (July 2005): 213–19. http://dx.doi.org/10.1007/s10967-005-0811-9.

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32

Garcia-Rivera, E., J. Park, Z. Doctor, A. Lopez-Marquez, D. Sheinson, C. S. Meyer, and T. M. To. "PND83 IDENTIFYING NEUROMYELITIS OPTICA PATIENTS FROM INSURANCE CLAIMS DATA USING NFERX, A NATURAL LANGUAGE PROCESSING-BASED PLATFORM." Value in Health 23 (May 2020): S275. http://dx.doi.org/10.1016/j.jval.2020.04.975.

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33

Ioannidou, Despoina, Laure Malherbe, Maxime Beauchamp, Nicolas Saby, Roseline Bonnard, and Julien Caudeville. "Characterization of Environmental Health Inequalities Due to Polyaromatic Hydrocarbon Exposure in France." International Journal of Environmental Research and Public Health 15, no. 12 (November 28, 2018): 2680. http://dx.doi.org/10.3390/ijerph15122680.

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Reducing environmental health inequalities has become a major focus of public health efforts in France, as evidenced by the French action plans for health and the environment. To evaluate environmental inequalities, routine monitoring networks provide a valuable source of data on environmental contamination, which can be used in integrated assessments, to identify overexposed populations and prioritize actions. However, available databases generally do not meet sufficient spatial representativeness to characterize population exposure, as they are usually not assembled for this specific purpose. The aim of this study was to develop geoprocessing procedures and statistical methods to build spatial environmental variables (water, air, soil, and food pollutant concentrations) at a fine resolution, and provide appropriate input for the exposure modelling. Those methods were designed to combine in situ monitoring data with correlated auxiliary information (for example, atmospheric emissions, population, and altitude), in order to better represent the variability of the environmental compartment quality. The MODUL’ERS multimedia exposure model developed by INERIS (French Institute for industrial Environment and Risks) was then used to assess the transfer of substances from the environment to humans, through inhalation and ingestion pathway characterization. We applied the methodology to a carcinogenic Polycyclic Aromatic Hydrocarbon substance, benzo[a]pyrene(B[a]P), to map spatialized exposure indicators, at the national scale. The largest environmental contribution corresponded to the ingestion pathway. Data processing algorithms and calculation of exposure will be integrated into the French coordinated integrated environment and health platform PLAINE (PLteforme intégrée d’Analyse des INégalités Environnementales) which has been developed to map and analyze environmental health inequalities.

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Yeprintsev, S. A. "GEOINFORMATION TECHNOLOGIES AS A MECHANISM FOR ASSESSING ENVIRONMENTAL RISKS TO PUBLIC HEALTH IN THE CONDITIONS OF TECHNOGENIC AIR POLLUTION IN CITIES." ECOLOGY ECONOMY INFORMATICS. GEOINFORMATION TECHNOLOGIES AND SPACE MONITORING 2, no. 5 (2020): 9–13. http://dx.doi.org/10.23885/2500-123x-2020-2-5-9-15.

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ic health requires processing large amounts of data from long-term research, which necessitates the use of modern geoinformation technologies. Geoinformation technologies are a mechanism for assessing environmental risks to public health in conditions of man-made air pollution in cities. The results obtained in the course of long-term monitoring studies are summarized in the GIS environment “Environmental and socio-economic conditions of cities in Central Russia”. The collection of information to characterize the functional and planning structure and landscape and environmental conditions for the model regions was carried out on the basis of special field research, processing of stock, including cartographic, material of regional integrated and sectoral environmental agencies. Currently, Russia and the world have different approaches to assessing the environmental risk for the population living in industrial cities. In Russia, the methodology of the center for hygiene is most widely used. Erisman, as well as the methodology for assessing environmental risk developed by Professor V. Prevalence. Of studies environmental and social conditions in the city of Voronezh, conducted by researchers of Voronezh state University under the direction of Professor S.A. Kurolap collected in electronic health-environmental GIS-Atlas of the city of Voronezh. The Atlas contains maps showing the state of the environment, public health, and environmental risks in various parts of the city of Voronezh. Currently, various researchers have proposed a number of methodologies for geoinformation assessment of environmental safety of the population of large cities. At the same time, there is no unified approach to assessing environmental comfort that covers its various components, which makes it advisable to develop an integrated methodology based on the data available to us.

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A., Busari Sherif, Dunmoye Abibat F., and Akingbade Kayode F. "Development of Arduino-based Data Acquisition System for Environmental Monitoring using Zigbee Communication Protocol." APTIKOM Journal on Computer Science and Information Technologies 1, no. 3 (November 1, 2016): 109–18. http://dx.doi.org/10.11591/aptikom.j.csit.119.

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Data Acquisition Systems (DAS) are used for a variety of applications such as environmental monitoring, indoor climate control, health management and medical diagnostics, traffic surveillance and emergency response, disaster management among others. This paper presents the design of a DAS for monitoring environmental temperature, pressure and relative humidity. The system employs Arduino Uno microcontroller for signal processing and Zigbee transceivers operating on the 2.4 GHz license-free Industrial, Scientific and Medical (ISM) band as communication modules at both the transmitter and receiver ends. While the transmitter board houses the sensors, a GPS module and an LCD, the receiver system is interfaced with a PC which runs a developed MATLAB GUI for data display and analysis and it incorporates an SD card for data storage. The battery-powered system is a low cost, low-power consumption system which serves as a mini-weather station with real-time data logging, wireless communication and tracking capabilities.

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Sada, Yvonne, Jason Hou, Peter Richardson, Hashem El-Serag, and Jessica Davila. "Validation of Case Finding Algorithms for Hepatocellular Cancer From Administrative Data and Electronic Health Records Using Natural Language Processing." Medical Care 54, no. 2 (February 2016): e9-e14. http://dx.doi.org/10.1097/mlr.0b013e3182a30373.

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Labron Carter, Perry, Jason M. Post, and Cynthia L. Sorrensen. "Spatial Environmental Inequality in Lubbock, Texas." Current Research Journal of Social Sciences and Humanities 1, no. 1 (June 25, 2018): 01–12. http://dx.doi.org/10.12944/crjssh.1.1.01.

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Environmental inequality assumes a near proximity of environmental health hazards, hazardous waste processing and releasing facilities to minority and low-income communities. Research in environmental inequality and environment justice over the past twenty years suggests that hazardous waste facilities are often located near minority and low-income neighborhoods. We conducted a study evaluating and quantifying environmental inequality in Lubbock County, Texas. Our study analyzed both spatial and statistical relationships between population demographics and spatial proximity to hazardous waste releasing facilities. Hazardous waste facility data used in the study were collected from the Environmental Protection Agency’s Toxic Release Inventory (TRI). Population statistics from the U.S. Census comprise the demographic data for this analysis. Spatial regression models were estimated to evaluate the relationship between distance from TRI sites and neighborhood / census block group demographics. A statistically significant relationship with proximity to hazardous waste facilities was found in communities having significant minority populations.

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Weigand, Matthias, Michael Wurm, Stefan Dech, and Hannes Taubenböck. "Remote Sensing in Environmental Justice Research—A Review." ISPRS International Journal of Geo-Information 8, no. 1 (January 10, 2019): 20. http://dx.doi.org/10.3390/ijgi8010020.

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Human health is known to be affected by the physical environment. Various environmental influences have been identified to benefit or challenge people’s physical condition. Their heterogeneous distribution in space results in unequal burdens depending on the place of living. In addition, since societal groups tend to also show patterns of segregation, this leads to unequal exposures depending on social status. In this context, environmental justice research examines how certain social groups are more affected by such exposures. Yet, analyses of this per se spatial phenomenon are oftentimes criticized for using “essentially aspatial” data or methods which neglect local spatial patterns by aggregating environmental conditions over large areas. Recent technological and methodological developments in satellite remote sensing have proven to provide highly detailed information on environmental conditions. This narrative review therefore discusses known influences of the urban environment on human health and presents spatial data and applications for analyzing these influences. Furthermore, it is discussed how geographic data are used in general and in the interdisciplinary research field of environmental justice in particular. These considerations include the modifiable areal unit problem and ecological fallacy. In this review we argue that modern earth observation data can represent an important data source for research on environmental justice and health. Especially due to their high level of spatial detail and the provided large-area coverage, they allow for spatially continuous description of environmental characteristics. As a future perspective, ongoing earth observation missions, as well as processing architectures, ensure data availability and applicability of ’big earth data’ for future environmental justice analyses.

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Carpenter, Joseph E., Arthur S. Chang, Alvin C. Bronstein, Richard G. Thomas, and Royal K. Law. "Identifying Incidents of Public Health Significance Using the National Poison Data System, 2013–2018." American Journal of Public Health 110, no. 10 (October 2020): 1528–31. http://dx.doi.org/10.2105/ajph.2020.305842.

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Data System. The American Association of Poison Control Centers (AAPCC) and the Centers for Disease Control and Prevention (CDC) jointly monitor the National Poison Data System (NPDS) for incidents of public health significance (IPHSs). Data Collection/Processing. NPDS is the data repository for US poison centers, which together cover all 50 states, the District of Columbia, and multiple territories. Information from calls to poison centers is uploaded to NPDS in near real time and continuously monitored for specific exposures and anomalies relative to historic data. Data Analysis/Dissemination. AAPCC and CDC toxicologists analyze NPDS-generated anomalies for evidence of public health significance. Presumptive results are confirmed with the receiving poison center to correctly identify IPHSs. Once verified, CDC notifies the state public health department. Implications. During 2013 to 2018, 3.7% of all NPDS-generated anomalies represented IPHSs. NPDS surveillance findings may be the first alert to state epidemiologists of IPHSs. Data are used locally and nationally to enhance situational awareness during a suspected or known public health threat. NPDS improves CDC’s national surveillance capacity by identifying early markers of IPHSs.

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Fritz, Roschelle L., and Roxanne Vandermause. "Data Collection via In-Depth Email Interviewing: Lessons From the Field." Qualitative Health Research 28, no. 10 (January 17, 2017): 1640–49. http://dx.doi.org/10.1177/1049732316689067.

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This methods article is a reflection on the use of in-depth email interviewing in a qualitative descriptive study. The use of emailing to conduct interviews is thought to be an effective way to collect qualitative data. Building on current methodological literature in qualitative research regarding in-depth email interviewing, we move the conversation toward elicitation of quality data and management of multiple concurrent email interviews. Excerpts are shared from a field journal that was kept throughout one study, with commentary on developing insights. Valuable lessons learned include the importance of (a) logistics and timing related to the management of multiple concurrent email interviews, (b) language and eliciting the data, (c) constructing the email, and (d) processing text-based data and preparing transcripts. Qualitative researchers seeking deeply reflective answers and geographically diverse samples may wish to consider using in-depth email interviews.

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Rosu, Iulian-Alin, Marius-Mihai Cazacu, Otilia Prelipceanu, and Maricel Agop. "A Turbulence-Oriented Approach to Retrieve Various Atmospheric Parameters Using Advanced Lidar Data Processing Techniques." Atmosphere 10, no. 1 (January 18, 2019): 38. http://dx.doi.org/10.3390/atmos10010038.

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The article is aimed at presenting a semi-empirical model coded and computed in the programming language Python, which utilizes data gathered with a standard biaxial elastic lidar platform in order to calculate the altitude profiles of the structure coefficients of the atmospheric refraction index C N 2 ( z ) and other associated turbulence parameters. Additionally, the model can be used to calculate the PBL (Planetary Boundary Layer) height, and other parameters typically employed in the field of astronomy. Solving the Fernard–Klett inversion by correlating sun-photometer data obtained through our AERONET site with lidar data, it can yield the atmospheric extinction and backscatter profiles α ( z ) and β ( z ) , and thus obtain the atmospheric optical depth. Finally, several theoretical notions of interest that utilize the solved parameters are presented, such as approximated relations between C N 2 ( z ) and the atmospheric temperature profile T ( z ) , and between the scintillation of backscattered lidar signal and the average wind speed profile U ( z ) . These obtained profiles and parameters also have several environmental applications that are connected directly and indirectly to human health and well-being, ranging from understanding the transport of aerosols in the atmosphere and minimizing the errors in measuring it, to predicting extreme, and potentially-damaging, meteorological events.

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Beeley, P. A., M. S. Heimlich, J. B. Edward, L. G. I. Bennett, and J. A. Page. "A new microcomputer program for processing data in neutron activation analysis." Journal of Radioanalytical and Nuclear Chemistry Articles 169, no. 2 (March 1993): 453–61. http://dx.doi.org/10.1007/bf02043002.

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Diaz, Kristian, and Ying-Khai Teh. "Design and Power Management of a Secured Wireless Sensor System for Salton Sea Environmental Monitoring." Electronics 9, no. 4 (March 25, 2020): 544. http://dx.doi.org/10.3390/electronics9040544.

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An embedded system composed of commercial off the shelf (COTS) peripherals and microcontroller. The system will collect environmental data for Salton Sea, Imperial Valley, California in order to understand the development of environmental and health hazards. Power analysis of each system features (i.e. Central Processing Unit (CPU) core, Input/Output (I/O) buses, and peripheral (temperature, humidity, and optical dust sensor) are studied. Software-based power optimization utilizes the power information with hardware-assisted power gating to control system features. The control of these features extends system uptime in a field deployed finite energy scenario. The proposed power optimization algorithm can collect more data by increasing system up time when compared to a Low Power Energy Aware Processing (LEAP) approach. Lastly, the 128 bit Advanced Encryption Standard (AES) algorithm is applied on the collected data using various parameters. A hidden peripheral requirement that must be considered during design are also noted to impact the efficacy of this method.

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Takeshita, Shinji, Hooman Farzaneh, and Mehrnoosh Dashti. "Life-Cycle Assessment of the Wastewater Treatment Technologies in Indonesia’s Fish-Processing Industry." Energies 13, no. 24 (December 14, 2020): 6591. http://dx.doi.org/10.3390/en13246591.

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In this paper, a comprehensive life-cycle assessment (LCA) is carried out in order to evaluate the multiple environmental-health impacts of the biological wastewater treatment of the fish-processing industry throughout its life cycle. To this aim, the life-cycle impact assessment method based on endpoint modeling (LIME) was considered as the main LCA model. The proposed methodology is based on an endpoint modeling framework that uses the conjoint analysis to calculate damage factors for human health, social assets, biodiversity, and primary production, based on Indonesia’s local data inventory. A quantitative microbial risk assessment (QMRA) is integrated with the LIME modeling framework to evaluate the damage on human health caused by five major biological treatment technologies, including chemical-enhanced primary clarification (CEPC), aerobic-activated sludge (AS), up-flow anaerobic sludge blanket (UASB), ultrafiltration (UF) and reverse osmosis (RO) in this industry. Finally, a life-cycle costing (LCC) is carried out, considering all the costs incurred during the lifetime. The LCA results revealed that air pollution and gaseous emissions from electricity consumption have the most significant environmental impacts in all scenarios and all categories. The combined utilization of the UF and RO technologies in the secondary and tertiary treatment processes reduces the health damage caused by microbial diseases, which contributes significantly to reducing overall environmental damage.

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Munira, Sirajum, James J. Dynes, Mofizul Islam, Fahad Khan, Theresa Adesanya, Tom Z. Regier, Kurt A. Spokas, and Annemieke Farenhorst. "Relative proportions of organic carbon functional groups in biochars as influenced by spectral data collection and processing." Chemosphere 283 (November 2021): 131023. http://dx.doi.org/10.1016/j.chemosphere.2021.131023.

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Kumi-Boateng, B., and E. Stemn. "Spatial Analysis of Artisanal and Small-Scale Mining in the Tarkwa-Nsuaem Municipality of Ghana." Ghana Mining Journal 20, no. 1 (July 7, 2020): 66–74. http://dx.doi.org/10.4314/gm.v20i1.8.

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Abstract In recent times there have been lots of public outcry on the environmental and public health and safety effects of Artisanal and Small-scale gold Mining (ASM) and the need to monitor ASM activities for reclamation purposes. To effectively develop and deploy policy responses to the environmental and human health effects of ASM, knowledge of the locations and distribution of ASM sites is a prerequisite. However, information regarding ASM hotspots and spatial distribution, the scope and types of ASM operations are hard to find. Therefore, this research was designed to use satellite-based data to map out ASM sites, focusing on the Tarkwa-Nsuaem municipality as the study area. Several image processing techniques were applied on a Landsat 8 satellite image downloaded from the US Geological Survey website. The image processing resulted in the identification of 221 clusters of ASM sites, representing 12.72% of the total size of the study area. To further explore the effects of these ASM sites, Areas of Interest (AOI) including forest reserve, rivers, large-scale mines and urban settlements were defined. By selecting and analysing the location and distribution of the ASM sites in relations to the AOI, the study was effective in identifying environmentally sensitive and critical areas warranting the urgent attention of society to mitigate the health, safety and ecosystem service effects of ASM in the study area. By identifying the environmental sensitive areas being affected by ASM, the findings could support the prioritisation of reclamation efforts. Keywords: Artisanal Small-Scale Mining, Satellite Image, Environmental Effect, Public Health and Safety

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Al-Hadhrami, Ahmed, and Andrew B. Lawson. "Bayesian hierarchical modeling of latent period switching in small-area putative health hazard studies." Statistical Methods in Medical Research 20, no. 1 (August 26, 2010): 5–28. http://dx.doi.org/10.1177/0962280210374256.

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In recent years, small area risk assessment modelling and data analysis around putative hazard sources has become a fundamental part of public health and environmental sciences. In this study, we address a fundamental problem in the analysis of such data, when intermittent operation of facilities could lead to evidence for latent periods of risk. This study examines the development of Bayesian models for the latent switching operating period of putative hazard sources such as nuclear processing plants and waste disposal incinerators. The developed methodology is applied in a simulation study as well as to a real data example.

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Harris, Paul, Sarah Lindley, Martin Gallagher, and Raymond Agius. "Identification and verification of ultrafine particle affinity zones in urban neighbourhoods: sample design and data pre-processing." Environmental Health 8, Suppl 1 (2009): S5. http://dx.doi.org/10.1186/1476-069x-8-s1-s5.

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Mohler, H. Justin, Arthur S. Rood, Helen A. Grogan, Emily A. Caffrey, and John E. Till. "Analysis of Environmental Data to Support Quantification of Historical Releases from a Former Uranium Processing Facility in Apollo, Pennsylvania." Health Physics 120, no. 5 (February 11, 2021): 495–509. http://dx.doi.org/10.1097/hp.0000000000001368.

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Bartholomäus, Sebastian, Yannik Siegert, Hans Werner Hense, and Oliver Heidinger. "Secure Linking of Data from Population-Based Cancer Registries with Healthcare Data to Evaluate Screening Programs." Das Gesundheitswesen 82, S 02 (December 10, 2019): S131—S138. http://dx.doi.org/10.1055/a-1031-9526.

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Abstract Background The evaluation of population-based screening programs, like the German Mammography Screening Program (MSP), requires collection and linking data from population-based cancer registries and other sources of the healthcare system on a case- specific level. To link such sensitive data, we developed a method that is compliant with German data protection regulations and does not require written individual consent. Methods Our method combines a probabilistic record linkage on encrypted identifying data with ‘blinded anonymisation’. It ensures that all data either are encrypted or have a defined and measurable degree of anonymity. The data sources use a software to transform plain-text identifying data into a set of irreversibly encrypted person cryptograms, while the evaluation attributes are aggregated in multiple stages and are reversibly encrypted. A pseudonymisation service encrypts the person cryptograms into record assignment numbers and a downstream data-collecting centre uses them to perform the probabilistic record linkage. The blinded anonymisation solves the problem of quasi-identifiers within the evaluation data. It allows selecting a specific set of the encrypted aggregations to produce data export with ensured k-anonymity, without any plain-text information. These data are finally transferred to an evaluation centre where they are decrypted and analysed. Our approach allows creating several such generalisations, with different resulting suppression rates allowing dynamic balance information depth with privacy protection and also highlights how this affects data analysability. Results German data protection authorities approved our concept for the evaluation of the impact of the German MSP on breast cancer mortality. We implemented a prototype and tested it with 1.5 million simulated records, containing realistically distributed identifying data, calculated different generalisations and the respective suppression rates. Here, we also discuss limitations for large data sets in the cancer registry domain, as well as approaches for further improvements like l-diversity and how to reduce the amount of manual post-processing. Conclusion Our approach enables secure linking of data from population-based cancer registries and other sources of the healthcare system. Despite some limitations, it enables evaluation of the German MSP program and can be generalised to be applicable to other projects.

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