Search results for: big health data

Authors: Katalin Bodor, Zsolt Bodor, Robert Szep

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The particulate matter (PM) smaller than 2.5 μm are less studied due to the limited availability of PM₂.₅, and less information is available on the health effects attributable to PM₁₀ in Central-Eastern Europe. The objective of the current study was to assess the human health risk and characterize the spatial and temporal variation of PM₂.₅ and PM₁₀ in eight Romanian regions between the 2009-2018 and. The PM concentrations showed high variability over time and spatial distribution. The highest concentration was detected in the Bucharest region in the winter period, and the lowest was detected in West. The relative risk caused by the PM₁₀ for all-cause mortality varied between 1.017 (B) and 1.025 (W), with an average 1.020. The results demonstrate a positive relative risk of cardiopulmonary and lung cancer disease due to exposure to PM₂.₅ on the national average 1.26 ( ± 0.023) and 1.42 ( ± 0.037), respectively.

Keywords: PM₂.₅, PM₁₀, relative risk, health effect

Procedia PDF Downloads 157

Authors: A. Alrasheed, I. Connerton

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Providing patients with safe meals on a daily basis is one of the challenges in the healthcare sector. In Saudi Arabia matters related to food safety and hygiene have been the heart of the Ministry of Health (MOH) and Saudi Food and Drugs Authority (SFDA). The aim of this study is to examine the causes of inadequate implementation of food safety management systems such as HACCP in Riyadh’s MOH hospitals. By the law, food safety must be managed using a documented, HACCP based approach, and food handlers must be appropriately trained in food safety. Food handlers in Saudi Arabia are not required to provide a certificate or attend a food handling training course even in healthcare sectors. Since food safety and hygiene issues are of increasing importance for Saudi Arabian health decision makers, the SFDA has been established to apply food hygiene requirements in all food operations. It should be pointed out that the implications of food outbreaks on the whole society may potentially go beyond individual health impacts but also impact on the Nation’s health and bring about economic repercussions.

Keywords: food safety, patient, hospital, HACCP

Procedia PDF Downloads 864

Authors: A. Ratika Thakur, B. A. K. Sinha , C. R. K. Pathak

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Reproductive Tract Infections are recognized as a serious global health problem with direct impact on women. In the developing countries, prevalence of RTI is much higher relative to other health problems. Women of the reproductive age group are socially, mentally and physically more vulnerable to infections. Also, it is a well established fact that RTI has prolonged complications in women rather than men. It causes ectopic pregnancy, pelvic inflammatory diseases, miscarriage and infertility in the long course. Women perspective about infections is less studied. In this view the study was carried out with an aim to determine knowledge, perception and belief of married women towards reproductive tract infection. The study was conducted in Junga village, District Shimla, Himachal Pradesh, India. 48 women were interviewed regarding awareness, beliefs and taboos related to reproductive tract infection. Other aspects like fertility history were also taken into account. The data were collected using interviews with the help of interview schedule and interview guide. Data were recorded in the form of narratives and case studies. The analysis was done using quantitative and qualitative analysis. It was found that a majority of women were not aware about the reasons of infection. Moreover cultural beliefs, perceptions and taboos made them more vulnerable and exposed to RTI. Economic dependency upon men, lack of control in barrier methods were some of the factors that contributed to delayed treatment of women. It was found that a majority of women suffering from RTIs were silently bearing the burden and underwent treatment when the case would not rest in their hands.

Keywords: belief, infection, perception, taboo, women

Procedia PDF Downloads 372

Authors: Jolanta Jonak

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Emotional wellbeing is crucial for healthy development of children, youth, and adolescence. Lack of healthy emotional development and functioning can lead to many challenges in academic, social, and physical domains. Unfortunately, mental health problems are steadily increasing over the past several years and significantly intensified during and after the Covid 19 pandemic. Some experts warn that globally, we are entering a mental health crisis pandemic. Prior to the Covid 19 pandemic in 2020, a considerable number of youth aged 6-17 experienced a mental health disorder each year, with half of all mental health conditions beginning by age 14. The most common mental health disorders in children are Attention-Deficit/Hyperactivity Disorder (ADHD), behavior problems, anxiety, and depression. In U.S. schools, youth with these diagnoses tend to be classified under the umbrella of Emotional Disability. Several concerning trends have been emerging about the mental health of U.S. high school students. These trends have been steadily increasing for the past decade, particularly having increasing numbers of high school students who experienced persistent feelings of sadness or hopelessness, seriously considered attempting suicide, made a suicide plan, and attempted suicide. The number of students who felt persistently sad or hopeless increased across every racial and ethnic group. Parents, educators, and mental health providers are key stakeholders that are responsible for actively and effectively supporting struggling youth. A commonly faced challenge is that mental wellbeing is not supported as effectively as it should be. When effective prevention is paired with enhanced treatment developed on a multidisciplinary approach, mental health and emotional wellbeing in young people can be positively enhanced. Major health organizations including the Center for Disease Control and the National Institutes of Health encourage health professionals and other stakeholders to focus on addressing emotional wellbeing and mental health of young people.

Keywords: social emotional wellbeing, disability, learning, prevention

Procedia PDF Downloads 33

Authors: Khitam Ibrahem Shlash Mohammad

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Background: Postnatal depression is a focus of considerable research attention, but little is known about the pattern of stress across this period. Objective: to investigate the prevalence of stress after childbirth for Jordanian women and identify associated risk factors. Method: Design: A descriptive cross-sectional study. Participants were recruited six to eight weeks postpartum, provided personal, social and obstetric information, and completed the stress subscale of Depression Anxiety and Stress Scale (DASS-S), the Maternity Social Support Scale (MSSS), and Perceived Self-Efficacy Scale (PSES). Setting: maternal and child health care clinics in four health care centres in Maan city in Southern Jordan. Participants: Arabic speaking women (n = 324) between the ages of 18 and 45 years, six to eight weeks postpartum, primiparous or multiparous at low risk for obstetric complications. Data collection took place between October 2015 and January 2016. Ethical clearance was obtained prior to data collection. Results: The prevalence of postpartum stress among Jordanian women was 39.8 %. A regression analysis revealed that occupation, low social support, financial problems, difficult marital relationships, difficult relationship with family-in-law, giving birth to a female baby, difficult childbirth, and low self-efficacy were associated with postpartum stress. Conclusions and implications for practice: Jordanian women need support during pregnancy, during and after childbirth. Postpartum emotional support and assessment of symptoms of stress need to be incorporated into routine practice. The opportunity for open discussion along with increased awareness and clarification of common misconceptions about postpartum stress is necessary.

Keywords: prevalence, postpartum, stress, Jordanian women

Procedia PDF Downloads 348

Authors: Rahul Malhotra, Anurag Sharma

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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: FTTH, quad play, play service, access networks, data rate

Procedia PDF Downloads 401

Authors: Phontip Kanlahasuth

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This paper presents the environmental safety and occupational health risk assessment of rocket static test by assessing risk level from probability and severity and then appropriately applying the risk control measures. Before the environmental safety and occupational health measures are applied, the serious hazards level is 31%, medium level is 24% and low level is 45%. Once risk control measures are practically implemented, the serious hazard level can be diminished, medium level is 38%, low level is 45% and eliminated level is 17%. It is clearly shown that the environmental safety and occupational health measures can significantly reduce the risk level.

Keywords: rocket static test, hazard, risk, risk assessment, risk analysis, environment, safety, occupational health, acceptable risk, probability, severity, risk level

Procedia PDF Downloads 579

Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

Procedia PDF Downloads 173

Authors: Lingerew Nebere Kassie, Ping-Yu Chang, Hsin-Hua Huang, , Chaw-Son Chen

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Transient electromagnetic (TEM) data plays a crucial role in hydrogeological and environmental applications, providing valuable insights into geological structures and resistivity variations. However, the presence of noise often hinders the interpretation and reliability of these data. Our study addresses this issue by utilizing a FASTSNAP system for the TEM survey, which operates at different modes (low, medium, and high) with continuous adjustments to discretization, gain, and current. We employ a denoising approach that processes the raw data obtained from each acquisition mode to improve signal quality and enhance data reliability. We use a signal-averaging technique for each mode, increasing the signal-to-noise ratio. Additionally, we utilize wavelet transform to suppress noise further while preserving the integrity of the underlying signals. This approach significantly improves the data quality, notably suppressing severe noise at late times. The resulting denoised data exhibits a substantially improved signal-to-noise ratio, leading to increased accuracy in parameter estimation. By effectively denoising TEM data, our study contributes to a more reliable interpretation and analysis of underground structures. Moreover, the proposed denoising approach can be seamlessly integrated into existing ground-based TEM data processing workflows, facilitating the extraction of meaningful information from noisy measurements and enhancing the overall quality and reliability of the acquired data.

Keywords: data quality, signal averaging, transient electromagnetic, wavelet transform

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Authors: Obasan Kehinde

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Social Infrastructure such as transport, telecommunications, energy, water, health, housing, and educational facilities have become part and parcel of human existence and have since been seen as prerequisite for the development of any economy. It is difficult to imagine a modern world without these facilities. Using a survey research design, data was gathered through a multi-stage sampling and a random sampling method from a total of 117 respondents, the study investigates the role of social infrastructure on the performance of entrepreneurs drawn from 10 Local Government Areas across two carefully selected states in the South-West, Nigeria. The data was analyzed using a descriptive statistical analysis and a t-test. The result shows that the impact of social infrastructure on entrepreneur performance is significant at 0.00 level of significant. Thus, this study recommends that entrepreneurs should take note of the social infrastructures available in the environment for the purpose of citing business in order to reduce the cost of production and other business costs.

Keywords: social infrastructure, entrepreneur performance, entrepreneurship, business

Procedia PDF Downloads 388

Authors: Randa M. Ali, Naguiba F. Loutfy, Osama M. Awad

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Background: Leishmaniasis is a worldwide disease, affecting 88 countries, it is estimated that about 350 million people are at risk of leishmaniasis. Overall prevalence is 12 million people with annual mortality of about 60,000. Annual incidence is 1,500,000 cases of cutaneous leishmaniasis (CL) worldwide and half million cases of visceral Leishmaniasis (VL). Objectives: The objective of this study was to assess primary health care physicians knowledge (PHP) and attitude about leishmaniasis and to assess awareness of local inhabitants about the disease and its vector in four areas in west Alexandria, Egypt. Methods: This study was a cross sectional survey that was conducted in four PHC units in west Alexandria. All physicians currently working in these units during the study period were invited to participate in the study, only 20 PHP completed the questionnaire. 60 local inhabitant were selected randomly from the four areas of the study, 15 from each area; Data was collected through two different specially designed questionnaires. Results: 11(55%) percent of the physicians had satisfactory knowledge, they answered more than 9 (60%) questions out of a total 14 questions about leishmaniasis and sandfly. The second part of the questionnaire is concerned with attitude of the primary health care physicians about leishmaniasis, 17 (85%) had good attitude and 3 (15%) had poor attitude. The second questionnaire showed that the awareness of local inhabitants about leishmaniasis and sandly as a vector of the disease is poor and needs to be corrected. Most of the respondents (90%) had not heard about leishmaniasis, Only 3 (5%) of the interviewed inhabitants said they know sandfly and its role in transmission of leishmaniasis. Conclusions: knowledge and attitudes of physicians are acceptable. However, there is, room for improvement and could be done through formal training courses and distribution of guidelines. In addition to raising the awareness of primary health care physicians about the importance of early detection and notification of cases of lesihmaniasis. Moreover, health education for raising awareness of the public regarding the vector and the disease is necessary because related studies have demonstrated that if the inhabitants do not perceive mosquitoes to be responsible for diseases such as malaria they do not take enough measures to protect themselves against the vector.

Keywords: leishmaniasis, PHP, knowledge, attitude, local inhabitants

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Authors: Hironori Karachi, Haruka Yamashita

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Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

Procedia PDF Downloads 124

Authors: Sachin Nagargoje

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Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

Procedia PDF Downloads 116

Authors: Nahwera L., Constance A. N. Nsibamb, Mukana R., Daniel T. Goon

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Regular physical activity is a cornerstone of maintaining good health. Studies have shown that physical inactivity leads to overweight and obesity, a risk factor for non-communicable diseases and a public health challenge. Health clubs provide therapeutic exercises to clients desiring to reduce their weight; however, the exercise routines offered in these health clubs are insufficient to reduce their body weight. A convenient sample of 100 clients. Exercise routines were determined using a questionnaire. Height, weight, waist, and hip circumferences were measured. Body mass index (BMI), waist circumference, and waist-to-hip ratio (WHR) assessed body weight status. About 75% of clients exercised three or more times per week; 96% participated in modern intensity exercises for 30 minutes, aerobic dance (88%), treadmill (56%), cycling (51%), rope skipping (45%), and 14% in strengthening activities. The BMI of male and female clients was 64.2% and 83.0%, respectively. There was no significant correlation (p≤0.05) between BMI and WHR (p=0.336), although there was a significant correlation between BMI and waist circumference (p=0.000). There was no significant relationship between BMI and WHR for males (p= .336) and between BMI and WHR for females (p=.806). Although most clients visiting health clubs meet the recommended frequency, intensity, and duration of exercise, they are overweight and obese. Appropriate exercise and nutritional programs should be incorporated into health clubs offering therapeutic and rehabilitative exercises to clients.

Keywords: Body weight status, exercise routines, health clubs, exercises

Procedia PDF Downloads 80

Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

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Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

Procedia PDF Downloads 251

Authors: Elizaveta S. Prokofyeva, Svetlana V. Maltseva, Roman D. Zaitsev

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Rapidly evolving modern data analysis technologies in healthcare play a large role in understanding the operation of the system and its characteristics. Nowadays, one of the key tasks in urban healthcare is to optimize the resource allocation. Thus, the application of data analysis in medical institutions to solve optimization problems determines the significance of this study. The purpose of this research was to establish the dependence between the indicators of the effectiveness of the medical institution and its resources. Hospital discharges by diagnosis; hospital days of in-patients and in-patient average length of stay were selected as the performance indicators and the demand of the medical facility. The hospital beds by type of care, medical technology (magnetic resonance tomography, gamma cameras, angiographic complexes and lithotripters) and physicians characterized the resource provision of medical institutions for the developed models. The data source for the research was an open database of the statistical service Eurostat. The choice of the source is due to the fact that the databases contain complete and open information necessary for research tasks in the field of public health. In addition, the statistical database has a user-friendly interface that allows you to quickly build analytical reports. The study provides information on 28 European for the period from 2007 to 2016. For all countries included in the study, with the most accurate and complete data for the period under review, predictive models were developed based on historical panel data. An attempt to improve the quality and the interpretation of the models was made by cluster analysis of the investigated set of countries. The main idea was to assess the similarity of the joint behavior of the variables throughout the time period under consideration to identify groups of similar countries and to construct the separate regression models for them. Therefore, the original time series were used as the objects of clustering. The hierarchical agglomerate algorithm k-medoids was used. The sampled objects were used as the centers of the clusters obtained, since determining the centroid when working with time series involves additional difficulties. The number of clusters used the silhouette coefficient. After the cluster analysis it was possible to significantly improve the predictive power of the models: for example, in the one of the clusters, MAPE error was only 0,82%, which makes it possible to conclude that this forecast is highly reliable in the short term. The obtained predicted values of the developed models have a relatively low level of error and can be used to make decisions on the resource provision of the hospital by medical personnel. The research displays the strong dependencies between the demand for the medical services and the modern medical equipment variable, which highlights the importance of the technological component for the successful development of the medical facility. Currently, data analysis has a huge potential, which allows to significantly improving health services. Medical institutions that are the first to introduce these technologies will certainly have a competitive advantage.

Keywords: data analysis, demand modeling, healthcare, medical facilities

Procedia PDF Downloads 138

Authors: Yog Raj Sood, Rajnish Shrivastava, Anchal Wadhwa

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Power transformer is one of the electrical equipment that has a central and critical role in the power system. In order to avoid power transformer failure, information system that provides the transformer condition is needed. This paper presents an information system to know the exact situations prevailing within the transformer by declaring its health index. Health index of a transformer is decided by considering several diagnostic tools. The current work deals with UV-Vis, IFT, FP, BDV and Water Content. UV/VIS results have been pre-accessed using separate FL controller for concluding with the Furan contents. It is broadly accepted that the life of a power transformer is the life of the oil/ paper insulating system. The method relies on the use of furan analysis (insulation paper), and other oil analysis results as a means to declare health index. Fuzzy logic system is used to develop the information system. The testing is done on 5 samples of oil of transformers of rating 132/66 KV to obtain the results and results are analyzed using fuzzy logic model.

Keywords: interfacial tension analyzer (ift), flash point (fp), furfuraldehyde (fal), health index

Procedia PDF Downloads 628

Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Said Boularouk, Didier Josselin, Eitan Altman

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In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: TTS, ontology, open street map, visually impaired

Procedia PDF Downloads 291

Authors: Jiaxin Shi, Kaifeng Hao, Qingfan An, Zeng Peng

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Due to a lack of data sources and data processing techniques, it has always been difficult to quantify public space quality, which includes urban construction quality and how it is perceived by people, especially in large urban areas. This study proposes a quantitative research method based on the consideration of emotional health and physical health of the built environment. It highlights the low quality of public areas in Tianjin, China, where there are many negative elements. Deep learning technology is then used to measure how effectively people perceive urban areas. First, this work suggests a deep learning model that might simulate how people can perceive the quality of urban construction. Second, we perform semantic segmentation on street images to identify visual elements influencing scene perception. Finally, this study correlated the scene perception score with the proportion of visual elements to determine the surrounding environmental elements that influence scene perception. Using a small-scale labeled Tianjin street view data set based on transfer learning, this study trains five negative spatial discriminant models in order to explore the negative space distribution and quality improvement of urban streets. Then it uses all Tianjin street-level imagery to make predictions and calculate the proportion of negative space. Visualizing the spatial distribution of negative space along the Tianjin Inner Ring Road reveals that the negative elements are mainly found close to the five key districts. The map of Tianjin was combined with the experimental data to perform the visual analysis. Based on the emotional assessment, the distribution of negative materials, and the direction of street guidelines, we suggest guidance content and design strategy points of the negative phenomena in Tianjin street space in the two dimensions of perception and substance. This work demonstrates the utilization of deep learning techniques to understand how people appreciate high-quality urban construction, and it complements both theory and practice in urban planning. It illustrates the connection between human perception and the actual physical public space environment, allowing researchers to make urban interventions.

Keywords: human perception, public space quality, deep learning, negative elements, street images

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Authors: Phillipa Denise Peart

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Black Asian and Minority Ethnic (BAME) people are more at risk of developing mental health disorders because they are more exposed to unfavorable social, economic, and environmental circumstances. These include housing, education, employment, community development, stigma, and discrimination. However, the majority of BAME mental health intervention studies focus on treatment with therapeutically effective drugs and use basic economic methods to evaluate their effectiveness; as a result, little is invested in the economic assessment of psychosocial interventions in BAME mental health. The UK government’s austerity programme and reduced funds for mental health services, has increased the need for the evaluation and assessment of initiatives to focus on value for money. The No Health without Mental Health policy (2011) provides practice guidance to practitioners, but there is little or no mention of the need to provide mental health initiatives targeted at BAME communities that are effective in terms of their impact and the cost-effectiveness. This, therefore, appears to contradict with and is at odds with the wider political discourse, which suggests there should be an increasing focus on health economic evaluation. As a consequence, it could be argued that whilst such policies provide direction to organisations to provide mental health services to the BAME community, by not requesting effective governance, assurance, and evaluation processes, they are merely paying lip service to address these problems and not helping advance knowledge and practice through evidence-based approaches. As a result, BAME communities suffer due to lack of efficient resources that can aid in the recovery process. This research study explores the mental health initiatives targeted at BAME communities, and analyses the techniques used when examining the cost effectiveness of mental health initiatives for BAME mental health communities. Using critical discourse analysis as an approach and method, mental health services will be selected as case studies, and their evaluations will be examined, alongside the political drivers that frame, shape, and direct their work. In doing so, it will analyse what the mental health policies initiatives are, how the initiatives are directed and demonstrate how economic models of evaluation are used in mental health programmes and how the value for money impacts and outcomes are articulated by mental health programme staff. It is anticipated that this study will further our understanding in order to provide adequate mental health resources and will deliver creative, supportive research to ensure evaluation is effective for the government to provide and maintain high quality and efficient mental health initiatives targeted at BAME communities.

Keywords: black, Asian and ethnic minority, economic models, mental health, health policy

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Authors: Siti Rohana Mohd Yatim, Ku Halim Ku Hamid, Kamariah Noor Ismail, Zulkifli Abdul Rashid

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The aim of this study is to investigate odour emission profiles from storage of food waste and to assess the potential health risk caused by exposure to volatile compounds. Food waste decomposition process was conducted for 14 days and kept at 20°C and 30°C in self-made bioreactor. VOCs emissions from both samples were collected at different stages of decomposition starting at day 0, day 1, day 3, day 5, day 7, day 10, day 12 and day 14. It was analyzed using TD-GC/MS. Findings showed that various VOCs were released during decomposition of food waste. Compounds produced were influenced by time, temperature and the physico-chemical characteristics of the compounds. The most abundant compound released was dimethyl disulfide. Potential health risk of exposure to this compound is represented by hazard ratio, HR, calculated at 1.6 x 1011. Since HR equal to or less than 1.0 is considered negligible risk, this indicates that the compound posed a potential risk to human health.

Keywords: volatile organic compounds, decomposition process, food waste, health risk

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Authors: Phayong Thepaksorn

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The objective of this study was to assess whether living in proximity to a roofing fiber cement factory in southern Thailand was associated with physical, mental, social, and spiritual health domains measured in a self-reported health risk assessment (HRA) questionnaire. A cross-sectional study was conducted among community members divided into two groups: near population (living within 0-2 km of factory) and far population (living within 2-5 km of factory)(N=198). A greater proportion of those living far from the factory (65.34%) reported physical health problems than the near group (51.04 %)(p=0.032). This study has demonstrated that the near population group had higher proportion of participants with positive ratings on mental assessment (30.34%) and social health impacts (28.42%) than far population group (10.59% and 16.67 %, respectively) (p<0.001). The near population group (29.79%) had similar proportion of participants with positive ratings in spiritual health impacts compared with far population group (27.08%). Among females, but not males, this study demonstrated that a higher proportion of the near population had a positive summative score for the self-HRA, which included all four health domain, compared to the far population (p <0.001 for females; p=0.154 for males). In conclusion, this self-HRA of physical, mental, social, and spiritual health domains reflected the risk perceptions of populations living in the vicinity of the roofing fiber cement factory. This type of tool can bring attention to population concerns and complaints in the factory’s surrounding community. Our findings may contribute to future development of self-HRA for HIA development procedure in Thailand.

Keywords: cement dust, health impact assessment, risk assessment, walk-though survey

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Authors: Walid Fantazi

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The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

Procedia PDF Downloads 248

Authors: Tri Murti, Muhammad Hanafiah Juni, Hejar Abdul Rahman, Salmiah Binti Said

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The diarrhoeal disease continues to be a leading cause of childhood mortality in countries such as Indonesia, where it is estimated to be responsible for 300,000 deaths annually in children under the age of years. Morbidity survey the Ministry of Health of Indonesia from 2000 to 2010 showed incidence diarrhoea remains a leading cause of infant mortality. Causes of death from diarrhoea is related to poor governance both at home and in health facilities. Despite the improvement of health facilities and government effort to reduce the occurrence of diarrhoea among children and death from diarrhoea, the incidence of diarrhoea among children area still high.

Keywords: management diarrheal disease, practices mother, treatment, diarrhoea among children

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Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

Abstract:

The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

Procedia PDF Downloads 111

Authors: Arash Kosari, Ali Araghi

Abstract:

A mathematical model for an optical-fiber communication channel is developed which results in an expression that calculates the throughput and loss of the corresponding link. The data are assumed to be transmitted by using of separate photons with different polarizations. The derived model also shows the dependency of data throughput with length of the channel and depolarization factor. It is observed that absorption of photons affects the throughput in a more intensive way in comparison with that of depolarization. Apart from that, the probability of depolarization and the absorption of radiated photons are obtained.

Keywords: absorption, data throughput, depolarization, optical fiber

Procedia PDF Downloads 282

Authors: Krishna Gopal Lageju

Abstract:

On 25th April 2015, a 7.6 magnitude earthquake struck Gorkha district of Nepal, which resulted over 8,790 deaths and 22,300 injuries. In addition, almost one-third of the country’s healthcare service has been disrupted. A total of 1,211 health facilities became non-operational, due to 446 completely and other 765 partially damaged. Nearly 84 percent (375 out of 446) of the completely damaged health facilities are in the 14 most affected districts. As a result, the ability of health facilities to respond to health care needs has been harshly affected. In addition, 18 health workers lost their lives and 75 are injured, which added further challenges in the delivery of health services. Thus, to address the immediate health needs in the most devastated areas, Nepal Red Cross Society (NRCS) in coordination with IFRC and Nepal Government, 8 Field hospitals established with surgical capacities, where around 492 international Emergency Response Units (ERUs) Members are mobilized for 3 months period. More than 54,000 patients have been treated in the Red Cross operated field hospitals. Trauma cases accounted 9,180 (17%) of the total patients off which 1,285 (14%) are major surgical cases. Most of the case loads 44,830 (83%) are outpatients and 9,180 patients got inpatients service. Similarly, 112 births have been performed in the field hospitals. Inpatient mortality rate remained 1.5% (21 deaths), many of them are presented with critical injuries or illnesses. No outbreak has been seen during the ERU operation. Deployment of ERUs together with national health workers are very important to address the immediate health needs of the affected communities. This will ease for transition and handover of emergency service and equipments to local provider. Likewise, capacity building of local staff as on the job training on various clinical teachings would be another important issue to look at before phasing out such services.

Keywords: trauma management, critical injuries, earthquake, health

Procedia PDF Downloads 236

Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

Abstract:

Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

Procedia PDF Downloads 444

Authors: Viana Hassan

Abstract:

Each year, 600 million tourists travelled abroad to practice several types of tourism. Nowadays, whatever is the type of tourism practiced it considered as a real public health problem which can contribute the spread of several diseases such as AIDS, H1N1, NDM1 With regard to HIV/AIDS, Lebanon is always considered as a low HIV prevalence country. However, the potential risks associated with the mobility of the population, migration and tourism. The total number of cases reported by the ministry of health since 1989 until the end of 2011 is of 1455 cases, with an average of 85 new cases per year over the last three years. The main reason of the increased number is Travel and migration which represent 50% of the risks reported by cumulative cases. Given the interest of this kind of epidemic it would be interesting to study the Evolution of HIV/ AIDS and its relation with travel and tourism The main aim of this research is to study in general the relation between tourism and health, more specific to understand the relation between Tourism and AIDS, the problem of the transmission of HIV in Lebanon, the ways of contamination and the countries in which these people are contaminated.

Keywords: AIDS, tourism, health, Lebanon

Procedia PDF Downloads 329