Search results for: health monitoring

Authors: Andrea Szabo Nagy, Zsofia Csanadi

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The purpose of this study was to evaluate the concentration levels of common inorganic gases, benzene and particulate matter (PM₁₀ and PM₂.₅) in ambient air of Győr (Hungary) based on the latest published monitoring data. The concentrations of PM10-bound heavy metals (Pb, Cd, As and Ni) and some polycyclic aromatic hydrocarbons (PAHs) were also assessed. The levels of pollutants were compared with the Hungarian and EU limit or target values defined for health protection and the WHO air quality guidelines (AQGs) or estimated reference levels. Based on the Hungarian or the EU air quality standards and using the Hungarian Air Quality Index it was found that mainly an excellent (SO₂, CO, C₆H₆, heavy metals) or good (NO₂, O₃, PM₁₀, PM₂.₅, benzo(a)pyrene (BaP)) air quality was observed in the urban area of Győr for the year 2016. The annual mean pollutant concentrations (excluding BaP) were not exceeded or just reached the WHO AQGs or reference levels.

Keywords: aerosols, air pollutant, air quality, health protection

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Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

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Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias

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Authors: Ben Morrow, Patrick O'Hara, Natalie Ban, Tunai Marques, Molly Fraser, Christopher Bone

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Relative to commercial fisheries, recreational fisheries are often poorly understood and pose various challenges for monitoring frameworks. In British Columbia (BC), Canada, Pacific salmon are heavily targeted by recreational fishers while also being a key source of nutrient flow and crucial prey for a variety of marine and terrestrial fauna, including endangered Southern Resident killer whales (Orcinus orca). Although commercial fisheries were historically responsible for the majority of salmon retention, recreational fishing now comprises both greater effort and retention. The current monitoring scheme for recreational salmon fisheries involves aerial-roving creel surveys. However, this method has been identified as costly and having low predictive power as it is often limited to sampling fragments of fluid and temporally dynamic fisheries. This study used imagery from two shore-based autonomous cameras in a highly active recreational fishery around Sooke, BC, and evaluated their efficacy in supplementing existing aerial-roving surveys for monitoring a recreational salmon fishery. This study involved continuous monitoring and high temporal resolution (over one million images analyzed in a single fishing season), using a deep learning-based vessel detection algorithm and a custom image annotation tool to efficiently thin datasets. This allowed for the quantification of peak-season effort from a busy harbour, species-specific retention estimates, high levels of detected fishing events at a nearby popular fishing location, as well as the proportion of the fishery management area represented by cameras. Then, this study demonstrated how it could substantially enhance the temporal resolution of a fishery through diel activity pattern analyses, scaled monthly to visualize clusters of activity. This work also highlighted considerable off-season fishing detection, currently unaccounted for in the existing monitoring framework. These results demonstrate several distinct applications of autonomous cameras for providing enhanced detail currently unavailable in the current monitoring framework, each of which has important considerations for the managerial allocation of resources. Further, the approach and methodology can benefit other studies that apply shore-based camera monitoring, supplement aerial-roving creel surveys to improve fine-scale temporal understanding, inform the optimal timing of creel surveys, and improve the predictive power of recreational stock assessments to preserve important and endangered fish species.

Keywords: cameras, monitoring, recreational fishing, stock assessment

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Authors: Paul Barasa Wanyama, Tom Wanyama

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Governments and development partners in low-income countries often prioritize building Water Sanitation and Hygiene (WaSH) infrastructure of healthcare facilities to improve maternal healthcare outcomes. However, the operation, maintenance, and utilization of this infrastructure are almost never considered. Many healthcare facilities in these countries use untreated water that is not monitored for quality or quantity. Consequently, it is common to run out of water while a patient is on their way to or in the operating theater. Further, the handwashing stations in healthcare facilities regularly run out of water or soap for months, and the latrines are typically not clean, in part due to the lack of water. In this paper, we present a system that uses Internet of Things (IoT), big data, cloud computing, and AI to initiate WaSH security in healthcare facilities, with a specific focus on maternal health. We have implemented smart sensors and actuators to monitor and control WaSH systems from afar to ensure their objectives are achieved. We have also developed a cloud-based system to analyze WaSH data in real time and communicate relevant information back to the healthcare facilities and their stakeholders (e.g., medical personnel, NGOs, ministry of health officials, facilities managers, community leaders, pregnant women, and new mothers and their families) to avert or mitigate problems before they occur.

Keywords: WaSH, internet of things, artificial intelligence, maternal health, rural communities, healthcare facilities

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Authors: Alina Rahim, Joanne Moffatt, Jessica Taylor, Joseph Hartland, Tamer Abdelrazik

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Background: In 2011, 15% of maternal deaths in Uganda were due to hypertensive disorders (pre-eclampsia and eclampsia). The majority of these deaths are avoidable with optimum antenatal care. The aim of the study was to evaluate how antenatal monitoring of pre-eclampsia was carried out in a low resource setting and to identify barriers to best practice as recommended by the World Health Organisation (WHO) as part of a 4th year medical student External Student Selected component field trip. Method: Women admitted to hospital with pre-eclampsia in rural Uganda (Villa Maria and Kitovu Hospitals) over a year-long period were identified using the maternity register and antenatal record book. It was not possible to obtain notes for all cases identified on the maternity register. Therefore a total of thirty sets of notes were reviewed. The management was recorded and compared to Ugandan National Guidelines and WHO recommendations. Additional qualitative information on routine practice was established by interviewing staff members from the obstetric and midwifery teams. Results: From the records available, all patients in this sample were managed according to WHO recommendations during labour. The rate of Caesarean section as a mode of delivery was noted to be high in this group of patients; 56% at Villa Maria and 46% at Kitovu. Antenatally two WHO recommendations were not routinely met: aspirin prophylaxis and calcium supplementation. This was due to lack of resources, and lack of attendance at antenatal clinic leading to poor detection of high-risk patients. Medical management of pre-eclampsia varied between individual patients, overall 93.3% complied with Ugandan national guidelines. Two patients were treated with diuretics, which is against WHO guidance. Discussion: Antenatal monitoring of pre-eclampsia is important in reducing severe morbidity, long-term disability and mortality amongst mothers and their babies 2 . Poor attendance at antenatal clinic is a barrier to healthcare in low-income countries. Increasing awareness of the importance of these visits for women should be encouraged. The majority of cases reviewed in this sample of women were treated according to Ugandan National Guidelines. It is recommended to commence the use of aspirin prophylaxis for women at high-risk of developing pre-eclampsia and the creation of detailed guidelines for Uganda which would allow for standardisation of care county-wide.

Keywords: antenatal monitoring, low resource setting, pre-eclampsia, Uganda

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Authors: Kalpana Rajouriya, Ajay Taneja

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Particulates are ubiquitous in the air environment and cause serious threats to human beings, such as lung cancer, COPD, and Asthma. Particulates mainly arise from industrial effluent, vehicular emission, and other anthropogenic activities. In the glass industrial city Firozabad, real-time monitoring of size segregated Particulate Matter (PM) and black carbon was done by Aerosol Black Carbon Detector (ABCD) and GRIMM portable aerosol Spectrometer at two different sites in which one site is urban and another is rural. The average mass concentration of size segregated PM during the study period (March & April 2022) was recorded as PM10 (223.73 g/m⁻³), PM5.0 (44.955 g/m⁻³), PM2.5 (59.275 g/m⁻³), PM1.0 (33.02 g/m⁻³), PM0.5 (2.05 g/m⁻³), and PM0.25 (2.99 g/m⁻³). The highest concentration of BC was found in Urban due to the emissions from diesel engines and wood burning, while NO2 was highest at the rural sites. The average concentrations of PM10 (6.08 and 2.73 times) PM2.5 exceeded the NAAQS and WHO guidelines. Particulate Matter deposition and health risk assessment was done by MPPD and USEPA model to know about the particulate matter toxicity in industrial residents. Health risk assessment results showed that Children are most likely to be affected by exposure of PM10 and PM2.5 and may have various non-carcinogenic and carcinogenic diseases. Deposition results inferred that the sensitive exposed population, especially 9 years old children, have high PM deposition as well as visualization and may be at risk of developing health-related problems from exposure to size-segregated PM. They will be discussed during presentation.

Keywords: particulate matter, black carbon, NO2, deposition of PM, health risk

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Authors: Ana Maria Carmen Ilie, Carmela Vaccaro

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Gas migration through wellbore failure, in particular from abandoned wells, is repeatedly identified as the highest risk mechanism. The vadose zone was subject to monitoring system close to the wellbore in Minerbio, methane storage site. The new technology has been well-developed and used with the purpose to provide reliable estimates of leakage parameters. Of these techniques, soil flux sampling at the soil surface, via the accumulation chamber method and soil flux sampling at the depths of 100cm below the ground surface, have been an important technique for characterizing the gas concentrations at the gas storage site. We present results of soil Radon Bq/m3, CO2%, CH4% and O2% concentration gases. Measurements have been taken for radon concentrations with an Durridge RAD7 Company, Inc., USA, instrument. We used for air and soil quality an Biogas ETG instrument monitoring system, with NDIR CO2, CH4 gas sensor and electrochemical O2 gas sensor. The measurements started in September-October 2015, where no outliers have been identified. The measurements have continued in March-April-July-August-September 2016, almost at the same time in the same place around the gas storage site, values measured 15 minutes for each sampling, to determine their concentration, their distribution and to understand the relationship among gases and atmospheric conditions. At a depth of 100 cm, the maximum soil radon gas concentrations were found to be 1770 ±±582 Bq/m3, the soil consists of 64.31% sand, 20.75% silt and 14.94% clay, and with 0.526 ppm of Uranium. The maximum concentration (September 2016), in soil at 100cm below the ground surface, with 83% sand, 8.96% silt and 7.89% clay, was about 0.06% CH4, and in atmosphere 0.06% CH4 at 40°C (T). In the other months the values have been on the range of 0.01% to 0.03% CH4. Since we did not have outliers in the gas storage site, soil-gas samples for isotopic analysis have not been done.

Keywords: leakage gas monitoring, lithology, soil gas, methane

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Authors: Xinyi Zhao, Furong Tian

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Mycotoxins are secondary metabolic products of fungi. These are poisonous, carcinogens and mutagens in nature and pose a serious health threat to both humans and animals, causing severe illnesses and even deaths. The rapid, simple and cheap detection methods of mycotoxins are of immense importance and in great demand in the food and beverage industry as well as in agriculture and environmental monitoring. Lateral flow immunochromatographic strips (ICSTs) have been widely used in food safety, environment monitoring. Forty-six papers were identified and reviewed on Google Scholar and Scopus for their limit of detection and nanomaterial on Lateral flow immunochromatographic strips on different types of mycotoxins. The papers were dated 2001-2021. Twenty five papers were compared to identify the lowest limit of detection of among different mycotoxins (Aflatoxin B1: 10, Zearalenone:5, Fumonisin B1: 5, Trichothecene-A: 5). Most of these highly sensitive strips are competitive. Sandwich structure are usually used in large scale detection. In conclusion, the mycotoxin receives that most researches is aflatoxin B1 and its limit of detection is the lowest. Gold-nanopaticle based immunochromatographic test strips has the lowest limit of detection. Five papers involve smartphone detection and they all detect aflatoxin B1 with gold nanoparticles. In these papers, quantitative concentration results can be obtained when the user uploads the photograph of test lines using the smartphone application.

Keywords: aflatoxin B1, limit of detection, gold nanoparticle, lateral flow immunochromatographic strips, mycotoxins

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Authors: Prakash Thapa, Gye Choon Park, Sung Gi Kwon, Jin Lee

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The generation of electric power from a proton exchange membrane (PEM) fuel cell is influenced by temperature, pressure, humidity, flow rate of reactant gaseous and partial flooding of membrane electrode assembly (MEA). Among these factors, temperature and cathode flooding are the most affecting parameters on the performance of fuel cell. This paper describes the detail design and effect of these parameters on PEM fuel cell. Performance of all parameters was monitored, analyzed and controlled by using 5KWatt PEM fuel cell. In the real-time data communication for remote monitoring and control of PEM fuel cell, a normalized least mean square algorithm in cognitive radio environment is used. By the use of this method, probability of energy signal detection will be maximum which solved the frequency shortage problem. So the monitoring system hanging out and slow speed problem will be solved. Also from the control unit, all parameters are controlled as per the system requirement. As a result, PEM fuel cell generates maximum electricity with better performance.

Keywords: proton exchange membrane (PEM) fuel cell, pressure, temperature and humidity sensor (PTH), efficiency curve, cognitive radio network (CRN)

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Authors: Yasser Sanad, Thu Trang Dao

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Introduction: Implementing the One Health (OH) approach requires an integrated, interdisciplinary, and cross-sectoral methodology. OH is a key tool for developing and implementing programs and projects and includes developing ambitious policies that consider the common needs and benefits of human, animal, plant, and ecosystem health. OH helps humanity readjust its path to environmentally friendly and impartial sustainability. As co-leader of the Global Health Security Agenda’s Zoonotic Disease Action Package, Vietnam pioneered a strong OH approach to effectively address early waves of the COVID-19 outbreak in-country. Context and Aim: The repeated surges in COVID-19 in Vietnam challenged the capabilities of the national system and disclosed the gaps in multi-sectoral coordination and resilience. To address this, FHI 360 advocated for the standardization of the OH platform by government actors to increase the resiliency of the system during and post COVID-19. Methods: FHI 360 coordinated technical resources to develop and implement evidence-based OH policies, promoting high-level policy dialogue between the Ministries of Health, Agriculture, and the Environment, and policy research to inform developed policies and frameworks. Through discussions, an OH-building Partnership (OHP) was formed, linking climate change, the environment, and human and animal health. Findings: The OHP Framework created a favorable policy environment within and between sectors, as well as between governments and international health security partners. It also promoted strategic dialogue, resource mobilization, policy advocacy, and integration of international systems with National Steering Committees to ensure accountability and emphasize national ownership. Innovative contribution to policy, practice and/or research: OHP was an effective evidence-based research-to-policy platform linking to the National One Health Strategic Plan (2021-2025). Collectively they serve as a national framework for the implementation and monitoring of OH activities. Through the adoption of policies and plans, the risk of zoonotic pathogens, environmental agent spillover, and antimicrobial resistance can be minimized through strengthening multi-sectoral OH collaboration for health security.

Keywords: one health, national policies, health security, COVID-19, Vietnam

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Authors: Barbara Kyampeire, Gerald Karyeijja

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This study investigated the influence of local community participation on the adoption of new agricultural technology in Uganda, using the case study of Smooth Cayenne Pineapples in Kayunga District, Uganda. The mechanism of adoption of new technologies is often not fully understood and this prompted the study. The study adopted a descriptive, co relational, survey design. The researcher used questionnaire survey, focus group discussion as methods of data collection. A total of 152 respondents including adopters and non-adopters of new technology for producing pineapples were selected from 8 farmer groups in Kayunga District. The results indicated that the participation of the community in the planning, implementation and the monitoring and evaluation of the adoption of the new technology for producing pineapples was low thus reducing the adoption of the new technology in the District. The researcher concluded that community participation significantly influences the adoption of new agricultural technology by members of a particular community. The study thus recommended that: first, there is need for maximum involvement of members of the community in the planning, implementation and monitoring of any new agricultural technology; secondly, there is need for continued sharing of information about new agricultural technologies being introduced; and finally, community members must be equipped with Monitoring and Evaluation (M&E) skills in order to make them monitor the progress made by the new agricultural technologies.

Keywords: adoption, community, technology, implementation

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Authors: Maciej Zaręba, Sławomir Lasota

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Knowing the degree of dependencies between the sets of input signals and selected sets of indicators that measure a production system's effectiveness is of great importance in the industry. This paper introduces the SELM method that enables the selection of sets of input signals, which affects the most the selected subset of indicators that measures the effectiveness of a production system. For defined set of output indicators, the method quantifies the impact of input signals that are gathered in the continuous monitoring production system.

Keywords: manufacturing operation management, signal relationship, continuous monitoring, production systems

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Authors: Raeesa Moolla, Ryan S. Johnson

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Air travel, and the use of airports, has experienced proliferative growth in the past few decades, resulting in the concomitant release of air pollutants. Air pollution needs to be monitored because of the known relationship between exposure to air pollutants and increased adverse effects on human health. This study monitored a group of volatile organic compounds (VOCs); specifically BTEX (viz. benzene, toluene, ethyl-benzene and xylenes), as many are detrimental to human health. Through the use of passive sampling methods, the spatial variability of BTEX within an international airport was investigated, in order to determine ‘hotspots’ where occupational exposure to BTEX may be intensified. The passive sampling campaign revealed BTEX_total concentrations ranged between 12.95–124.04 µg m^-3. Furthermore, BTEX concentrations were dispersed heterogeneously within the airport. Due to the slow wind speeds recorded (1.13 m.s^-1); the hotspots were located close to their main BTEX sources. The main hotspot was located over the main apron of the airport. Employees working in this area may be chronically exposed to these emissions, which could be potentially detrimental to their health.

Keywords: air pollution, air quality, hotspot monitoring, volatile organic compounds

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Authors: Santos Cabrera, Halbert Yesid, Moncada Nino, Alvaro Fernando, Rincon Cuta, Yeisson Alexis

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The present work evaluates the feasibility of implementing a health and use monitoring system (HUMS), based on vibration analysis as a condition-based maintenance program for the UH60L 'Blackhawk' helicopters. The mixed approach used consists of contributions from national and international experts, the analysis of data extracted from the software (Meridium), the correlation of variables derived from the diagnosis of availability, the development, and application of the HUMS system, the evaluation of the latter through of the use of instruments designed for the collection of information using the DELPHI method and data capture with the device installed in the helicopter studied. The results obtained in the investigation reflect the context of maintenance in aerial operations, a reduction of operation and maintenance costs of over 2%, better use of human resources, improvement in availability (5%), and fulfillment of the aircraft’s security standards, enabling the implementation of the monitoring system (HUMS) in the condition-based maintenance program. New elements are added to the study of maintenance based on condition -specifically, in the determination of viability based on qualitative and quantitative data according to the methodology. The use of condition-based maintenance will allow organizations to adjust and reconfigure their strategic, logistical, and maintenance capabilities, aligning them with their strategic objectives of responding quickly and adequately to changes in the environment and operational requirements.

Keywords: air transportation sustainability, HUMS, maintenance based condition, maintenance blackhawk capability

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Authors: Carolina Gouveia, José Vieira, Pedro Pinho

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The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.

Keywords: bio-signals, DC component, Doppler effect, ellipse fitting, radar, SDR

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Authors: Mohamed Amhal, Jose Sayritupac

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Photovoltaic (PV) systems have risen as one of the modern renewable energy sources that are used in wide ranges to produce electricity and deliver it to the electrical grid. In parallel, monitoring systems have been deployed as a key element to track the energy production and to forecast the total production for the next days. The reliability of the PV energy production has become a crucial point in the analysis of PV systems. A deeper understanding of each phenomenon that causes a gain or a loss of energy is needed to better design, operate and maintain the PV systems. This work analyzes the current losses distribution in PV systems starting from the available solar energy, going through the DC side and AC side, to the delivery point. Most of the phenomena linked to energy losses and gains are considered and modeled, based on real time monitoring data and datasheets of the PV system components. An analysis of the order of magnitude of each loss is compared to the current literature and commercial software. To date, the analysis of PV systems performance based on a breakdown structure of energy losses and gains is not covered enough in the literature, except in some software where the concept is very common. The cutting-edge of the current analysis is the implementation of software tools for energy losses estimation in PV systems based on several energy losses definitions and estimation technics. The developed tools have been validated and tested on some PV plants in France, which are operating for years. Among the major findings of the current study: First, PV plants in France show very low rates of soiling and aging. Second, the distribution of other losses is comparable to the literature. Third, all losses reported are correlated to operational and environmental conditions. For future work, an extended analysis on further PV plants in France and abroad will be performed.

Keywords: energy gains, energy losses, losses distribution, monitoring, photovoltaic, photovoltaic systems

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Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

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Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

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Authors: Rakesh Choudhary, Ajay Kumar, Deepak Sharma

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The main goal of this paper is to investigate the challenges and benefits of IoT integration in biogas production. This overview explains how the inclusion of IoT can enhance biogas production efficiency. Therefore, such collected data can be explored by advanced analytics, including Artificial intelligence (AI) and Machine Learning (ML) algorithms, consequently improving bio-energy processes. To boost biogas generation efficiency, this report examines the use of IoT devices for real-time data collection on key parameters, e.g., pH, temperature, gas composition, and microbial growth. Real-time monitoring through big data has made it possible to detect diverse, complex trends in the process of producing biogas. The Informed by advanced analytics can also help in improving bio-energy production as well as optimizing operational conditions. Moreover, IoT allows remote observation, control and management, which decreases manual intervention needed whilst increasing process effectiveness. Such a paradigm shift in the incorporation of IoT technologies into biogas production systems helps to achieve higher productivity levels as well as more practical biomass quality biomethane through real-time monitoring-based proactive decision-making, thus driving continuous performance improvement.

Keywords: internet of things, biogas, renewable energy, sustainability, anaerobic digestion, real-time monitoring, optimization

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Authors: Eszter Repasi, Akos Koller

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Our genetic information determines our look, physiology, sports performance and all our features. Maximizing the performances of athletes have adopted a science-based approach to the nutritional support. Nowadays genetics studies have blended with nutritional sciences, and a dynamically evolving, new research field have appeared. Nutritional genomics is needed to be used by nutritional experts. This is a recent field of nutritional science, which can provide a solution to reach the best sport performance using correlations between the athlete’s genome, nutritions, molecules, included human microbiome (links between food, microbiome and epigenetics), nutrigenomics and nutrigenetics. Nutritional genomics has a tremendous potential to change the future of dietary guidelines and personal recommendations. Experts need to use new technology to get information about the athletes, like nutritional genomics profile (included the determination of the oral and gut microbiome and DNA coded reaction for food components), which can modify the preparation term and sports performance. The influence of nutrients on the genes expression is called Nutrigenomics. The heterogeneous response of gene variants to nutrients, dietary components is called Nutrigenetics. The human microbiome plays a critical role in the state of health and well-being, and there are more links between food or nutrition and the human microbiome composition, which can develop diseases and epigenetic changes as well. A nutritional genomics-based profile of athletes can be the best technic for a dietitian to make a unique sports nutrition diet plan. Using functional food and the right food components can be effected on health state, thus sports performance. Scientists need to determine the best response, due to the effect of nutrients on health, through altering genome promote metabolites and result changes in physiology. Nutritional biochemistry explains why polymorphisms in genes for the absorption, circulation, or metabolism of essential nutrients (such as n-3 polyunsaturated fatty acids or epigallocatechin-3-gallate), would affect the efficacy of that nutrient. Controlled nutritional deficiencies and failures, prevented the change of health state or a newly discovered food intolerance are observed by a proper medical team, can support better sports performance. It is important that the dietetics profession informed on gene-diet interactions, that may be leading to optimal health, reduced risk of injury or disease. A special medical application for documentation and monitoring of data of health state and risk factors can uphold and warn the medical team for an early action and help to be able to do a proper health service in time. This model can set up a personalized nutrition advice from the status control, through the recovery, to the monitoring. But more studies are needed to understand the mechanisms and to be able to change the composition of the microbiome, environmental and genetic risk factors in cases of athletes.

Keywords: gene-diet interaction, multidisciplinary team, microbiome, diet plan

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Authors: M. Kamel, A. Hoayek, M. Batton-Hubert

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With the increase of network virtualization and the disparity of vendors, the continuous monitoring and detection of anomalies cannot rely on static rules. An advanced analytical methodology is needed to discriminate between ordinary events and unusual anomalies. In this paper, we focus on log data (textual data), which is a crucial source of information for network performance. Then, we introduce an algorithm used as a pipeline to help with the pretreatment of such data, group it into patterns, and dynamically label each pattern as an anomaly or not. Such tools will provide users and experts with continuous real-time logs monitoring capability to detect anomalies and failures in the underlying system that can affect performance. An application of real-world data illustrates the algorithm.

Keywords: logs, anomaly detection, ML, scoring, NLP

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Authors: Ayşe Coban, Orhan Coban, Haldun Soydal, Sükrü Sürücü

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While health is a source of prosperity for individuals, it is also one of the most important determinants of economic growth for a country. Health, by increasing the productivity of labor, contributes to economic growth. Therefore, countries should give the necessary emphasis to health services. The primary aim of this study is to analyze the changes occurring in health services in Turkey by examining the developments in the sector. In this scope, the second aim of the study is to reveal the place of health expenditures in the Turkish economy. As a result of the analysis in the dataset, in which the 1999-2013 periods is considered, it was determined that some increase in health expenditures took place and that the increase in the share of health expenditures in GDP was too small. Furthermore, analysis of the results points out that in financing health expenditures, the public sector is prominent compared to the private sector.

Keywords: health, health service, health expenditures, Turkey

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Authors: Qidi Lin, Jinbin Huang, Weile Liang

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This paper introduces a video sharing platform based on WiFi, which consists of camera, mobile phone and PC server. This platform can receive wireless signal from the camera and show the live video on the mobile phone captured by camera. In addition that, it is able to send commands to camera and control the camera’s holder to rotate. The platform can be applied to interactive teaching and dangerous area’s monitoring and so on. Testing results show that the platform can share the live video of mobile phone. Furthermore, if the system’s PC sever and the camera and many mobile phones are connected together, it can transfer photos concurrently.

Keywords: Wifi Camera, socket mobile, platform video monitoring, remote control

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Authors: Yali Liu, Maria Avello Iturriagagoitia

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Background: Fitness applications (apps) are one of the most popular mobile health (mHealth) apps. These apps can help prevent/control health issues such as obesity, which is one of the most serious public health challenges in the developed world in recent decades. Compared with the traditional intervention like face-to-face treatment, it is cheaper and more convenient to use fitness apps to interfere with physical activities and healthy behaviors. Nevertheless, fitness applications apps tend to have high abandonment rates and low levels of user engagement. Therefore, maintaining the endurance of users' usage is challenging. In fact, previous research shows a variety of strategies -goal-setting, self-monitoring, coaching, etc.- for promoting fitness and health behavior change. These strategies can influence the users’ perseverance and self-monitoring of the program as well as favoring their adherence to routines that involve a long-term behavioral change. However, commercial fitness apps rarely incorporate these strategies into their design, thus leading to a lack of engagement with the apps. Most of today’s mobile services and brands engage their users proactively via push notifications. Push notifications. These notifications are visual or auditory alerts to inform mobile users about a wide range of topics that entails an effective and personal mean of communication between the app and the user. One of the research purposes of this article is to implement the application of behavior change strategies through push notifications. Proposes: This study aims to better understand the influence that effective use of push notifications combined with the behavioral change strategies will have on users’ engagement with the fitness app. And the secondary objectives are 1) to discuss the sociodemographic differences in utilization of push notifications of fitness apps; 2) to determine the impact of each strategy in customer engagement. Methods: The study uses a combination of the Consumer Engagement Theory and UTAUT2 based model to conduct an online survey among current users of fitness apps. The questionnaire assessed attitudes to each behavioral change strategy, and sociodemographic variables. Findings: Results show the positive effect of push notifications in the generation of consumer engagement and the different impacts of each strategy among different groups of population in customer engagement. Conclusions: Fitness apps with behavior change strategies have a positive impact on increasing users’ usage time and customer engagement. Theoretical experts can participate in designing fitness applications, along with technical designers.

Keywords: behavioral change, customer engagement, fitness app, push notification, UTAUT2

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Authors: Akram Khaleghei, Ghosheh Balagh, Viliam Makis

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In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, residual life prediction

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Authors: Paula Costa, Ana Picado, Filomena Pinto, Justina Catarino

Abstract:

Environmental impact associated with large scale shale gas development is of major concern to the public, policy makers and other stakeholders. To assess this impact on the atmosphere, it is important to monitoring ambient air quality prior to and during all shale gas operation stages. Baseline observations can provide a standard of the pre-shale gas development state of the environment. The lack of baseline concentrations was identified as an important knowledge gap to assess the impact of emissions to the air due to shale gas operations. In fact baseline monitoring of air quality are missing in several regions, where there is a strong possibility of future shale gas exploration. This makes it difficult to properly identify, quantify and characterize environmental impacts that may be associated with shale gas development. The implementation of a baseline air monitoring program is imperative to be able to assess the total emissions related with shale gas operations. In fact, any monitoring programme should be designed to provide indicative information on background levels. A baseline air monitoring program should identify and characterize targeted air pollutants, most frequently described from monitoring and emission measurements, as well as those expected from hydraulic fracturing activities, and establish ambient air conditions prior to start-up of potential emission sources from shale gas operations. This program has to be planned for at least one year accounting for ambient variations. In the literature, in addition to GHG emissions of CH4, CO2 and nitrogen oxides (NOx), fugitive emissions from shale gas production can release volatile organic compounds (VOCs), aldehydes (formaldehyde, acetaldehyde) and hazardous air pollutants (HAPs). The VOCs include a.o., benzene, toluene, ethyl benzene, xylenes, hexanes, 2,2,4-trimethylpentane, styrene. The concentrations of six air pollutants (ozone, particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), sulphur oxides (SOx), and lead) whose regional ambient air levels are regulated by the Environmental Protection Agency (EPA), are often discussed. However, the main concern in the emissions to air associated to shale gas operations, seems to be the leakage of methane. Methane is identified as a compound of major concern due to its strong global warming potential. The identification of methane leakage from shale gas activities is complex due to the existence of several other CH4 sources (e.g. landfill, agricultural activity or gas pipeline/compressor station). An integrated monitoring study of methane emissions may be a suitable mean of distinguishing the contribution of different sources of methane to ambient levels. All data analysis needs to be carefully interpreted taking, also, into account the meteorological conditions of the site. This may require the implementation of a more intensive monitoring programme. So, it is essential the development of a low-cost sampling strategy, suitable for establishing pre-operations baseline data as well as an integrated monitoring program to assess the emissions from shale gas operation sites. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640715.

Keywords: air emissions, baseline, green house gases, shale gas

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Authors: Wisit Wichitkosoom

Abstract:

Objective:The majority of the hisk-risk patients (ST-elevation myocardial infarction (STEMI), Acute cerebrovascular accident, Sepsis, Acute Traumatic patient ) are admitted to district or lacal hospitals (average 1-1.30 hr. from Udonthani general hospital, Northeastern province, Thailand) without proper facilities. The referral system was support to early care and early management at pre-hospital stage and prepare for the patient data to higher hospital. This study assessed the reduction in treatment delay achieved by pre-hospital diagnosis and referral directly to Udonthani General Hospital. Methods and results: Four district or local hospitals without proper facilities for treatment the very high-risk patient were serving the study region. Pre-hospital diagnoses were established with the simple technology such as LINE, SMS, telephone and Fax for concept of LEAN process and then the telemedicine, by ambulance monitoring (ECG, SpO2, BT, BP) in both real time and snapshot mode was administrated during the period of transfer for safety transfer concept (inter-hospital stage). The standard treatment for patients with STEMI, Intracranial injury and acute cerebrovascular accident were done. From 1 October 2012 to 30 September 2013, the 892 high-risk patients transported by ambulance and transferred to Udonthani general hospital were registered. Patients with STEMI diagnosed pre-hospitally and referred directly to the Udonthani general hospital with telemedicine closed monitor (n=248). The mortality rate decreased from 11.69% in 2011 to 6.92 in 2012. The 34 patients were arrested on the way and successful to CPR during transfer with the telemedicine consultation were 79.41%. Conclusion: The proper innovation could apply for health care system. The very high-risk patients must had the closed monitoring with two-way communication for the “safety transfer period”. It could modified to another high-risk group too.

Keywords: safety transfer, telemedicine, critical patients, medical and health sciences

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Authors: Oladapo Tolulope Ibitoye

Abstract:

It has become imperative to harmonize energy poverty alleviation and carbon footprint reduction. This is geared towards embracing independent power generation at local levels to reduce the popular ambiguity in the transmission of generated power. Also, it will contribute towards the total adoption of electric vehicles and direct current (DC) appliances that are currently flooding the global market. Solar power system is gaining momentum as it is now an affordable and less complex alternative to fossil fuel-based power generation. Although, there are many issues associated with solar power system, which resulted in deprivation of optimum working capacity. One of the key problems is inadequate monitoring of the energy pool from solar irradiance, which can then serve as a foundation for informed energy usage decisions and appropriate solar system control for effective energy pooling. The proposed technique utilized Internet of Things (IoT) in developing a system to automate solar irradiance pooling by controlling solar photovoltaic panels autonomously for optimal usage. The technique is potent with better solar irradiance exposure which results into 30% voltage pooling capacity than a system with static solar panels. The evaluation of the system show that the developed system possesses higher voltage pooling capacity than a system of static positioning of solar panel.

Keywords: solar system, internet of things, renewable energy, power monitoring

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Authors: Flavio Cannavo

Abstract:

Continuous evaluation of the status of potentially hazardous volcanos plays a key role for civil protection purposes. The importance of monitoring volcanic activity, especially for energetic paroxysms that usually come with tephra emissions, is crucial not only for exposures to the local population but also for airline traffic. Presently, real-time surveillance of most volcanoes worldwide is essentially delegated to one or more human experts in volcanology, who interpret data coming from different kind of monitoring networks. Unfavorably, the high nonlinearity of the complex and coupled volcanic dynamics leads to a large variety of different volcanic behaviors. Moreover, continuously measured parameters (e.g. seismic, deformation, infrasonic and geochemical signals) are often not able to fully explain the ongoing phenomenon, thus making the fast volcano state assessment a very puzzling task for the personnel on duty at the control rooms. With the aim of aiding the personnel on duty in volcano surveillance, here we introduce a system based on an ensemble of data-driven classifiers to infer automatically the ongoing volcano status from all the available different kind of measurements. The system consists of a heterogeneous set of independent classifiers, each one built with its own data and algorithm. Each classifier gives an output about the volcanic status. The ensemble technique allows weighting the single classifier output to combine all the classifications into a single status that maximizes the performance. We tested the model on the Mt. Etna (Italy) case study by considering a long record of multivariate data from 2011 to 2015 and cross-validated it. Results indicate that the proposed model is effective and of great power for decision-making purposes.

Keywords: Bayesian networks, expert system, mount Etna, volcano monitoring

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Authors: Asinguza P. Allan

Abstract:

The Advocacy for Better Health aims to equip citizens with enabling environment and systems to effectively advocate for strong action plans to improve health services. This is because the 2020 Government target for Uganda to transform into a middle income country will be achieved if investment is made in keeping the population healthy and productive. Citizen participation as an important foundation for change has been emphasized to gather data through participatory rural appraisal and inform evidence-based advocacy for recruitment and motivation of human resources. Citizens conduct problem ranking during advocacy forums on staffing levels and health worker absenteeism. Citizens prioritised inadequate number of midwives and absenteeism. On triangulation, health worker to population ratio in Uganda remains at 0.25/1,000 which is far below the World Health Organization (WHO) threshold of 2.3/1,000. Working with IntraHealth, the project advocated for recruitment of critical skilled staff (doctors and midwives) and scale up health workers motivation strategy to reduce Uganda’s Neonatal Mortality Rate of 22/1,000 and Maternal Mortality Ratio of 320/100,000. Government has committed to increase staffing to 80% by 2018 (10 districts have passed ordinances and revived use of duty rosters to address health worker absenteeism. On the other hand, the better health advocacy debate has been elevated with need to increase health sector budget allocations from 8% to 10%. The project has learnt that building a body of evidence from citizens enhances the advocacy agenda. Communities will further monitor government commitments to reduce Neonatal Mortality Rate and Maternal Mortality Ratio. The project has learnt that interface meeting between duty bearers and the community allows for immediate feedback and the process is a strong instrument for empowerment. It facilitates monitoring and performance evaluation of services, projects and government administrative units (like district assemblies) by the community members themselves. This, in turn, makes the human resources in health to be accountable, transparent and responsive to communities where they work. This, in turn, promotes human resource performance.

Keywords: advocacy, empowerment, evidence, human resources

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Authors: Lorenza Abbracciavento, Valerio De Biagi

Abstract:

Infrastructures are key elements to ensure the operational functionality of the transport system. The collapse of a single bridge or, equivalently, a tunnel can leads an entire motorway to be considered completely inaccessible. As a consequence, the paralysis of the communications network determines several important drawbacks for the community. Recent chronicle events have demonstrated that ensuring the functional continuity of the strategic infrastructures during and after a catastrophic event makes a significant difference in terms of life and economical losses. Moreover, it has been observed that RC structures located in mountain environments show a worst state of conservation compared to the same typology and aging structures located in temperate climates. Because of its morphology, in fact, the mountain environment is particularly exposed to severe collapse and deterioration phenomena, generally: natural hazards, e.g. rock falls, and meteorological hazards, e.g. freeze-thaw cycles or heavy snows. For these reasons, deep investigation on the characteristics of these processes becomes of fundamental importance to provide smart and sustainable solutions and make the infrastructure system more resilient. In this paper, the design of a monitoring system in mountainous environments is presented and analyzed in its parts. The method not only takes into account the peculiar climatic conditions, but it is integrated and interacts with the environment surrounding.

Keywords: structural health monitoring, resilience of bridges, mountain infrastructures, infrastructural network, maintenance

Procedia PDF Downloads 77