Search results for: big health data

Authors: Butta Singh

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This paper presents a chaotic map based approach for secured embedding of patient’s confidential data in electrocardiogram (ECG) signal. The chaotic map generates predefined locations through the use of selective control parameters. The sample value difference method effectually hides the confidential data in ECG sample pairs at these predefined locations. Evaluation of proposed method on all 48 records of MIT-BIH arrhythmia ECG database demonstrates that the embedding does not alter the diagnostic features of cover ECG. The secret data imperceptibility in stego-ECG is evident through various statistical and clinical performance measures. Statistical metrics comprise of Percentage Root Mean Square Difference (PRD) and Peak Signal to Noise Ratio (PSNR). Further, a comparative analysis between proposed method and existing approaches was also performed. The results clearly demonstrated the superiority of proposed method.

Keywords: chaotic maps, ECG steganography, data embedding, electrocardiogram

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Authors: Digambar J. Darekar, Sharvari D. Darekar

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Childlessness is a universal problem. It particularly affects the mental health of childless couple. It leads to anxiety, frustration, nervousness, depression, loneliness, helplessness, hopelessness, etc. After reviewing the literature, it is found that mental health of married couples is negatively related to childlessness. To understand emotional and psychological problems of a childless couple, researcher surveyed and interviewed 50 childless couples with the help of medical practitioner and gynecologist. Personal adjustment and mental health inventory and marital adjustment inventory along with semi-structured interview questionnaire was used. On the basis of responses from the subject, distinction is made between the problems of male subjects and female subjects and common problem separately. The researcher found that childlessness leads to the conflict between in-laws, harassment, hopelessness, feeling of emptiness and vacuumed, frustration, lack of hope and desire for life, restlessness, loss of sleep, ideas of committing suicide, increased emotional distance and disturbed marital life. The childlessness leads to sorrow for women and anger for men. Men turns towards addiction and women tend to avoid social contact and face problems of social adjustments. Childless couples are sufferers of personal and marital adjustment problems which in turn affect their mental health adversely.

Keywords: childlessness, marital adjustments, mental health, social adjustment

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Authors: Muhammad Danyal Khan

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The standards of patentability are drawing a great impact upon medicine industry of Pakistan which is indirectly troubling the right to health of ordinary citizen. Globalization of intellectual property laws is directly impacting access to medicine for population in Pakistan. Pakistan has enacted Patent Ordinance 2000 to develop the standards of Patent laws in consonance with international commitments. Moreover, Pakistan is signatory to UN Millennium Development Goals (2000-2015), and three of them directly put stress upon the health standards. This article will provide a critical brief about implications of TRIPS Agreement on standards of health in Pakistan and will also propose a futuristic approach for the pharmaceutical industry. This paper will define the paradox of globalization and national preparedness on pharmaceutical patents utilizing industry statistics and case laws from Pakistan. Moreover, this work will contribute towards debate on access to medicine at legislative and interpretative levels that will further help development of equilibrium between pharmaceutical patents and right to health.

Keywords: TRIPS (Trade Related Intellectual Property Rights), patents, compulsory licensing, patent, lifesaving drugs, WTO, infringement

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Authors: Marianne Paimre

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Estonia is heralded as the most successful digital country in the world with the highly acclaimed eHealth system. Yet 40% of the 65–74-year-olds do not use the Internet at all, and digital divide between young and elderly people's use of ICT is larger than in many advanced countries. Poor access to ICT resource and insufficient digital skills can lead to detachment from digital health resources, delayed diagnoses, and increased rates of hospitalization. To reveal digital divide within the elderly population itself, the presentation focuses on the health information behavior of Estonian seniors who either continue or have stopped working after retirement to use digital health applications. The author's main interest is on access, trust, and skills to use the Internet for medical purposes. Fifteen in-depth interviews with 65+ working persons, as well as 15 interviews with full-time retirees, were conducted. Also, six think-aloud protocols were conducted. The results indicate that older adults, who due to the nature of their work, have regular access to computers, often search for health-related information online. They exposed high source criticism and were successful in solving the given tasks. Conversely, most of the fully retired older adults claimed not using computers or other digital devices and cited lack of skills as the main reason for their inactivity. Thus, when developing health applications, it should be borne in mind that the ability and willingness of older adults to use e-solutions are very different.

Keywords: digital divide, digital healthcare, health information behavior, older adults

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Authors: Sareh Edalati, Nasrin Omidvar, Arezoo Haghighian Roudsari, Delaram Ghodsi, Azizollaah Zargaran

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Background and aim: Improving consumer’s food choices and providing a healthy food environment by governments is one of the essential approaches to prevent non-communicable diseases and to fulfill the sustainable development goals (SDGs). The present study aimed to provide an analysis of the nutrition labeling policy as one of the main components of the healthy food environment to provide learning lessons for the country and other low and middle-income countries. Methods: Data were collected by reviewing documents and conducting semi-structured interviews with stakeholders. Respondents were selected through purposive and snowball sampling and continued until data saturation. MAXQDA software was used to manage data analysis. A deductive content analysis was used by applying the Kingdon multiple streams and the policy triangulation framework. Results: Iran is the first country in the Middle East and North Africa region, which has implemented nutrition traffic light labeling. The implementation process has gone through two phases: voluntary and mandatory. In the voluntary labeling, volunteer food manufacturers who chose to have the labels would receive an honorary logo and this helped to reduce the food-sector resistance gradually. After this phase, the traffic light labeling became mandatory. Despite these efforts, there has been poor involvement of media for public awareness and sensitization. Also, the inconsistency of nutrition traffic light colors which are based on food standard guidelines, lack of consistency between nutrition traffic light colors, the healthy/unhealthy nature of some food products such as olive oil and diet cola and the absence of a comprehensive evaluation plan were among the pitfalls and policy challenges identified. Conclusions: Strengthening the governance through improving collaboration within health and non-health sectors for implementation, more transparency of truthfulness of nutrition traffic labeling initiating with real ingredients, and applying international and local scientific evidence or any further revision of the program is recommended. Also, developing public awareness campaigns and revising school curriculums to improve students’ skills on nutrition label applications should be highly emphasized.

Keywords: nutrition labeling, policy analysis, food environment, Iran

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Authors: Hirbaye Mokona, Abebaw Gebeyehu, Aemro Zerihun

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Introduction: Attention deficit hyperactivity disorder is serious public health problem affecting millions of children throughout the world. Method: A cross-sectional study conducted from May to June 2015 among children age 6 to 17 years living in rural area of Girja district. Multi-stage cluster sampling technique was used to select 1302 study participants. Disruptive Behavior Disorder rating scale was used to collect the data. Data were coded, entered and cleaned by Epi-Data version 3.1 and analyzed by SPSS version 20. Logistic regression analysis was used and Variables that have P-values less than 0.05 on multivariable logistic regression was considered as statistically significant. Results: Prevalence of Attention deficit hyperactivity disorder (ADHD) among children age 6 to 17 years was 7.3%. Being male [AOR=1.81, 95%CI: (1.13, 2.91)]; living with single parent [AOR=5.0, 95%CI: (2.35, 10.65)]; child birth order/rank [AOR=2.35, 95%CI: (1.30, 4.25)]; low family socio-economic status [AOR= 2.43, 95%CI: (1.29, 4.59)]; maternal alcohol/khat use during pregnancy [AOR=3.14, 95%CI: (1.37, 7.37)] and complication at delivery [AOR=3.56, 95%CI: (1.19, 10.64)] were more likely to develop Attention deficit hyperactivity disorder. Conclusion: In this study, the prevalence of Attention deficit hyperactivity disorder was similar with worldwide prevalence. Prevention and early management of its modifiable risk factors should be carryout alongside increasing community awareness.

Keywords: attention deficit hyperactivity disorder, ADHD, associated factors, children, prevalence

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Authors: S. Turkan

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In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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Authors: Ashan Wijekoon, Abi Beane, Subashini Jayawardana

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Background: Civil war in Sri Lanka ended a decade ago, leaving thousands of army veterans permanently disabled following lower-limb amputations. Quantifying long-term functional health and psychological wellbeing will inform the development of tailored home-based rehabilitation intervention. Objectives: To assess the long-term health and quality of life of Sri Lankan soldiers with traumatic lower-limb amputation.Methods and Materials: A comparative cross-sectional study was conducted in five districts of Sri Lanka. Using stratified random sample technique, two groups of 85 participants were selected; group 1, community re-integrated male army veterans with unilateral lower-limb amputation, and group 2, age and sex matched normal healthy individuals. Long-term health and quality of life (QoL) outcomes were assessed and compared between the two groups using self-administered Short-Form Health Survey-36 questionnaire (SF-36) previously validated for use in Sri Lanka. Results: Group 1 were active prosthetic users who had undergone amputation > ten years ago (Mean±SD: 21.7±5.9). The most prevalent comorbidities for group 1 and 2 were hypertension and diabetes (22.4% and 30.6% and 9.4% and 9.8%, respectively). In group 1, injury-associated long-term health outcomes included knee osteoarthritis (18.8%), knee pain (20.0%), and back pain (69.4%). Scores of physical health and psychological wellbeing were 53.1 (IQR 64.4- 43.8) and 63.5 (IQR 73.3- 51.4) for each group, respectively. Scores revealed the highest QoL related to social functioning (75 (IQR 87.5- 62.5)) and the poorest aspects of QoL related to general health (40 (IQR 50- 35)). Prevalence of comorbidities was significantly higher, and QoL outcomes were significantly lower among soldiers compared to normal healthy individuals (p<0.05).Conclusion: Higher prevalence of comorbidities, poor physical health, and lower QoL outcomes were more prevalent in soldiers with lower-limb amputation when compared to healthy counterparts.

Keywords: community-based, disability, health outcomes, quality of life, soldiers

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Authors: Hyun-Woo Cho

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The real-time fault monitoring and diagnosis of large scale production processes is helpful and necessary in order to operate industrial process safely and efficiently producing good final product quality. Unusual and abnormal events of the process may have a serious impact on the process such as malfunctions or breakdowns. This work try to utilize process measurement data obtained in an on-line basis for the safe and some fault-free operation of industrial processes. To this end, this work evaluated the proposed intelligent process data monitoring framework based on a simulation process. The monitoring scheme extracts the fault pattern in the reduced space for the reliable data representation. Moreover, this work shows the results of using linear and nonlinear techniques for the monitoring purpose. It has shown that the nonlinear technique produced more reliable monitoring results and outperforms linear methods. The adoption of the qualitative monitoring model helps to reduce the sensitivity of the fault pattern to noise.

Keywords: process data, data mining, process operation, real-time monitoring

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Authors: M.Younus, M. Athar Khan, Asif Adrees

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The present research endeavour was made to investigate the Public Health impact of Salmonellosis through consuming the meat and eggs of the carrier’s birds and to see the prevalence of Salmonella enteritidis and Salmonella typhimurium from poultry feed, poultry meat, and poultry eggs and their role in the chain of transmission of salmonellae to human beings and causing food poisoning. The ultimate objective was to generate data to improve the quality of poultry products and human health awareness. Salmonellosis is one of the most wide spread food borne zoonoses in all the continents of the world. The etiological agents Salmonella enteritidis and Salmonella typhimurium not only produce the disease but during the convalescent phase (after the recovery of disease) remain carriers for indefinite period of time. The carrier state was not only the source of spread of disease with in the poultry but also caused typhoid fever in humans. The chain of transmission started from poultry feed to poultry meat and ultimately to humans as dead end hosts. In this experiment a total number of 200 samples of human stool and blood were collected randomly (100 samples of human stool and 100 samples of human blood) of 100 patients suspected from food poisoning patients from different hospitals of Lahore area for the identification of Salmonella enteritidis and Salmonella typhimurium through PCR method in order to see the public health impact of Salmonellosis through consuming the meat and eggs of the carrier birds. On the average 14 and 10 stool samples were found positive against Salmonella enteritidis and Salmonella typhimurium from each of the 25 patients from each hospital respectively in case of suspected food poisoning patients. Similarly on an average 5% and 6% blood samples were found positive from 25 patients of each hospital respectively. There was a significant difference (P< 0.05) in the sero positivity of stool and blood samples of suspected food poisoning patients as far as Salmonella enteritidis and Salmonella typhimurium was concerned. However there was no significant difference (P<0.05) between the hospitals.

Keywords: salmonella, zoonosis, food, transmission, eggs

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Authors: A. Yamaoka, S. Yukawa

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Mind wandering is a mental phenomenon of drifting away from a current task or external environment toward inner thought. This research examines the feature of mind wandering which people who have high creativity and high mental health engage in because it is expected that mind wandering which such kind of people engage in may not induce negative affect, although it can improve creativity. Sixty-seven participants were required to complete questionnaires which measured their creativity and mental health. After that, researchers conducted experience sampling method and measured the details of their mind wandering and the situation when mind wandering was generated in daily life for three days. The result showed that high creative people and high mental health people more think about positive things during mind wandering and less think about negative things. In further research, researchers will examine how to induce positive thought during mind wandering and how to inhibit negative thought during mind wandering. Doing so will contribute to improve creative problem solving without generation of negative affect.

Keywords: creativity, experience sampling method, mental health, mind wandering

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Authors: Dipendra Kumar Yadav, Nabaraj Paudel, Anjana Yadav

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Background: Low Birth weight (LBW) is defined as the weight at birth less than 2500 grams, irrespective of the period of their gestation. LBW is an important indicator of general health status of population and is considered as the single most important predictors of infant mortality especially of deaths within the first month of life that is birth weight determines the chances of newborn survival. Objective of this study was to identify the maternal risk factors associated with low birth weight neonates. Materials and Methods: A hospital based case-control study was conducted in maternity ward of Manipal Teaching Hospital, Pokhara, Nepal from 23 September 2014 to 12 November 2014. During study period 59 cases were obtained and twice number of control group were selected with frequency matching of the mother`s age with ± 3 years and total controls were 118. Interview schedule was used for data collection along with record review. Data were entered in Epi-data program and analysis was done with help of SPSS software program. Results: From bivariate logistic regression analysis, eighteen variables were found significantly associated with LBW and these were place of residence, family monthly income, education, previous still birth, previous LBW, history of STD, history of vaginal bleeding, anemia, ANC visits, less than four ANC visits, de-worming status, counseling during pregnancy, CVD, physical workload, stress, extra meal during pregnancy, smoking and alcohol consumption status. However after adjusting confounding variables, only six variables were found significantly associated with LBW. Mothers who had family monthly income up to ten thousand rupees were 4.83 times more likely to deliver LBW with CI (1.5-40.645) and p value 0.014 compared to mothers whose family income NRs.20,001-60,000. Mothers who had previous still birth were 2.01 times more likely to deliver LBW with CI (0.69-5.87) and p value 0.02 compared to mothers who did not has previous still birth. Mothers who had previous LBW were 5.472 times more likely to deliver LBW with CI (1.2-24.93) and p value 0.028 compared to mothers who did not has previous LBW. Mothers who had anemia during pregnancy were 3.36 times more likely to deliver LBW with CI (0.77-14.57) and p value 0.014 compared to mothers who did not has anemia. Mothers who delivered female newborn were 2.96 times more likely to have LBW with 95% CI (1.27-7.28) and p value 0.01 compared to mothers who deliver male newborn. Mothers who did not get extra meal during pregnancy were 6.04 times more likely to deliver LBW with CI (1.11-32.7) and p value 0.037 compared to mothers who getting the extra meal during pregnancy. Mothers who consumed alcohol during pregnancy were 4.83 times more likely to deliver LBW with CI (1.57-14.83) and p value 0.006 compared to mothers who did not consumed alcohol during pregnancy. Conclusions: To reduce low birth weight baby through economic empowerment of family and individual women. Prevention and control of anemia during pregnancy is one of the another strategy to control the LBW baby and mothers should take full dose of iron supplements with screening of haemoglobin level. Extra nutritional food should be provided to women during pregnancy. Health promotion program will be focused on avoidance of alcohol and strengthen of health services that leads increasing use of maternity services.

Keywords: low birth weight, case-control, risk factors, hospital based study

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Authors: Amanda R. R. Oliveira, Caio F. F. C. Cunha, Juan C. L. Junior, Amorim H. P. Junior

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Children deaths are traumatic events that most often can be prevented. The technology of prevention and intervention in cases of infant deaths is available at low cost and with solid evidence and favorable results, however, with low access cover. Weight is one of the main factors related to death in the neonatal period, so the newborns of low birth weight are a population at high risk of death in the neonatal period, especially early neonatal period. This paper describes the development of a model based in neural network analysis to predict the mortality risk rating in the early neonatal period for newborns of low birth weight to identify the individuals of this population with increased risk of death. The neural network applied was trained with a set of newborns data obtained from Brazilian health system. The resulting network presented great success rate in identifying newborns with high chances of death, which demonstrates the potential for using this tool in an integrated manner to the health system, in order to direct specific actions for improving prognosis of newborns.

Keywords: low birth weight, neonatal death risk, neural network, newborn

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Authors: Rekha S., S. J. Nalini, S. Bhuvana, S. Kanmani, Vidhya Venugopal

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Introduction: Pregnant women's occupational heat exposure has been linked to foetal abnormalities and pregnancy complications. The presence of heat in the workplace is expected to lead to Adverse Pregnancy Outcomes (APO), especially in tropical countries where temperatures are rising and workplace cooling interventions are minimal. For effective interventions, in-depth understanding and evidence about occupational heat stress and APO are required. Methodology: Approximately 800 pregnant women in and around Chennai who were employed in jobs requiring moderate to hard labour participated in the cohort research. During the study period (2014-2019), environmental heat exposures were measured using a Questemp WBGT monitor, and heat strain markers, such as Core Body Temperature (CBT) and Urine Specific Gravity (USG), were evaluated using an Infrared Thermometer and a refractometer, respectively. Using a valid HOTHAPS questionnaire, self-reported health symptoms were collected. In addition, a postpartum follow-up with the mothers was done to collect APO-related data. Major findings of the study: Approximately 47.3% of pregnant workers have workplace WBGTs over the safe manual work threshold value for moderate/heavy employment (Average WBGT of 26.6°C±1.0°C). About 12.5% of the workers had CBT levels above the usual range, and 24.8% had USG levels above 1.020, both of which suggested mild dehydration. Miscarriages (3%), stillbirths/preterm births (3.5%), and low birth weights (8.8%) were the most common unfavorable outcomes among pregnant employees. In addition, WBGT exposures above TLVs during all trimesters were associated with a 2.3-fold increased risk of adverse fetal/maternal outcomes (95% CI: 1.4-3.8), after adjusting for potential confounding variables including age, education, socioeconomic status, abortion history, stillbirth, preterm, LBW, and BMI. The study determined that WBGTs in the workplace had direct short- and long-term effects on the health of both the mother and the foetus. Despite the study's limited scope, the findings provided valuable insights and highlighted the need for future comprehensive cohort studies and extensive data in order to establish effective policies to protect vulnerable pregnant women from the dangers of heat stress and to promote reproductive health.

Keywords: adverse outcome, heat stress, interventions, physiological strain, pregnant women

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Authors: A. Hoppe, T. Kagele, B. Hall, A. Nichols, B. Messner

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The Spokane Street Medicine (SSM) Program aims to deliver medical care to members of Spokane, Washington, experiencing homelessness. Street medicine is designed to function in a non-traditional setting to help deliver healthcare to the underserved homeless population. In this analysis, clinical charts from street and shelter encounters made by the Spokane Street Medicine Program in early 2021 were reviewed in order to better understand the healthcare inequities prevalent among people experiencing homelessness in Spokane, WA. Pain, wound-care, and follow-up efforts were predominant concerns among the homeless population. More than half of the conditions addressed were acute, and almost a quarter of all chief complaints involved chronic unmanaged conditions. This analysis gives reason for the priorities of the SSM Program to be focused on pain, wound-care, and follow-up efforts. Understanding the specific medical needs of this population will allow for better resource allocation and improved health outcomes among people experiencing homelessness.

Keywords: equity issues in public health, health disparities, health services accessibility, medical public health, street medicine

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Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Effective traffic management and infrastructure planning are crucial for the development of smart cities and intelligent transportation systems. This study addresses the challenge of data scarcity by generating realistic synthetic traffic data using the PeMS-Bay dataset, improving the accuracy and reliability of predictive modeling. Advanced synthetic data generation techniques, including TimeGAN, GaussianCopula, and PAR Synthesizer, are employed to produce synthetic data that replicates the statistical and structural characteristics of real-world traffic. Future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is planned to capture both spatial and temporal correlations, further improving data quality and realism. The performance of each synthetic data generation model is evaluated against real-world data to identify the best models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are utilized to model and predict complex temporal dependencies within traffic patterns. This comprehensive approach aims to pinpoint areas with low vehicle counts, uncover underlying traffic issues, and inform targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study supports data-driven decision-making that enhances urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory, synthetic data generation, traffic management

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Authors: Ye Sun, Han-Youl Lee, Kathy Musa-Veloso, Nabil Bosco

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Japan has been experiencing global ageing of population with the World’s leading life expectancy (80.8 y for men and 86.9 y for women) and among the lowest birth rate. Preventive nutrition-based approaches have been identified by the health authorities as one of the strategies to increase the healthy life expectancy and reduce the healthcare costs. However, the nutritional needs and status of the senior population have not been well characterized to provide targeted solutions. This study aims to describe the age- and gender-specific prevalence of inadequacy of macro- and micronutrients intake based on the latest Japan National Health and Nutrition Survey (JNHNS) 2014. JNHNS collected data on the consumption of foods and beverages using 1-day semi-weight household dietary record. Nutrient intake levels were then calculated using the Japanese standard tables of food composition. Where applicable, Japanese population-specific estimated average requirements (EAR) were used as a benchmark to determine the prevalence of potential nutrient intake inadequacy, and adequate intake (AI) were used for nutrients with no available EARs. In all, 3403 senior adults aged 60 y and above and 3324 young adults aged 19 to 59 y were included in the 2014 JNHNS. Age- and gender-specific differences were observed in the mean nutrient intakes as well as the prevalence of inadequacy. Among the 22 nutrients examined, the prevalence of inadequacy for iron, vitamin C, magnesium, potassium, and folic acid in the senior adults was significantly lower than young adults, suggesting potentially healthier dietary choices by the seniors. However, there was still a considerable proportion of seniors who did not meet the requirement for key nutrients like vitamin B1 (67%), calcium (57%), vitamin A (48%), magnesium (47%), vitamin E (44%), and vitamin B6 (41%). Inadequate nutrient intake is generally more prevalent among elderly males than females for many nutrients, with the exception of iron (prevalence of inadequacy: 21% versus 42%) which could partly be explained by the higher intake recommendations for the females. In conclusion, high prevalence of nutrient inadequacy exists in older adults, with a potentially worsened picture for men. Such inadequacies could have multiple health implications including physical frailty and mental health. Further study is warranted to investigate the food consumption patterns that could explain the observed nutrient inadequacies, and to eventually develop nutrition-based solutions tailored to the needs of specific subgroups of the population.

Keywords: ageing, national health and nutrition survey, nutrients, nutrition

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Authors: F.Sadoughi, A. Sarsarshahi, L, Eerfannia, S.M.A. Khatami

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Hospital information systems with lots of ability would lead to health care quality improvement. Evaluation of this system has done according different method and criteria. The main goal of present study is to prioritize the most important factors which are influence these systems evaluation. At the first step, according relevant literature, three main factor and 29 subfactors extracted. Then, study framework was designed. Based on analytical hierarchical process (AHP), 28 paired comparisons with Saaty range, in a questionnaire format obtained. Questionnaires were filled by 10 experts in health information management and medical informatics field. Human factors with weight of 0.55 were ranked as the most important. Organization (0.25) and technology (0.14) were in next place. It seems MADM methods such as AHP have enough potential to use in health research and provide positive opportunities for health domain decision makers.

Keywords: Analytical hierarchy process, Multiple criteria decision-making (MCDM), Hospital information system, Evaluation factors

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: H. B. Grobler, K. Du Plooy, P. Kruger, S. Ellis

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Objectives: The primary objective of the study was to determine the common mental disorders (CMD) identified by professional South African rugby players and its correlation with their mental toughness, as a first step towards developing such a programme within a larger research project. Design: Survey research, within the theoretical perspective of field theory, was conducted, utilising an adaptation of an already existing mental health questionnaire. The aim was to obtain feedback from as many possible professional South African rugby players in order to make certain generalizations and come to conclusions with regard to the current mental health experiences of these rugby players. Methods: Non-randomized sampling was done, linking it with internet research in the form of the online completion of a questionnaire. A sample of 215 rugby players participated and completed the online questionnaire. Permission was obtained to make use of an existing questionnaire, previously used by the specific authors with retired professional rugby players. A section on mental toughness was added. Data were descriptively analysed by means of the SPSS software platform. Results: Results indicated that the most significant problem that the players are experiencing, is a problem with alcohol (47.9%). Other problems that featured are distress (16.3%), sleep disturbances (7%), as well as anxiety and depression (4.2%). 4.7% of the players indicated that they smoke. 3.3% of the players experience themselves as not being mentally tough. A positive correlation between mental toughness and sound sleep (0.262) was found while a negative correlation was found between mental toughness and the following: anxiety/depression (-0.401), anxiety/depression positive (-0.423), distress (-0.259) and common mental disorder problems in general (-0.220). Conclusions: Although the presence of CMD at first glance do not seem significantly high amongst all the players, it must be considered that if one player in a team experiences the presence of CMD, it will have an impact on his mental toughness and most likely on his performance, as well as on the performance of the whole team. It is therefore important to ensure mental health in the whole team, by addressing individual CMD problems. A mental health support programme is therefore needed to be implemented to the benefit of these players within the South African context.

Keywords: common mental disorders, mental toughness, professional athletes, rugby players

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Authors: Suglo Tohari Luri

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Data analysis is an important aspect of business performance. With the application of artificial intelligence within databases, selecting a suitable database engine for an application design is also very crucial for business data analysis. The application of business intelligence (BI) software into some relational databases such as Neo4j has proved highly effective in terms of customer data analysis. Yet what remains of great concern is the fact that not all business organizations have the neo4j business intelligence software applications to implement for customer data analysis. Further, those with the BI software lack personnel with the requisite expertise to use it effectively with the neo4j database. The purpose of this research is to demonstrate how the Neo4j program code alone can be applied for the analysis of e-commerce website customer visits. As the neo4j database engine is optimized for handling and managing data relationships with the capability of building high performance and scalable systems to handle connected data nodes, it will ensure that business owners who advertise their products at websites using neo4j as a database are able to determine the number of visitors so as to know which products are visited at routine intervals for the necessary decision making. It will also help in knowing the best customer segments in relation to specific goods so as to place more emphasis on their advertisement on the said websites.

Keywords: data, engine, intelligence, customer, neo4j, database

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Authors: Leen Al Kassab, Sarah Johns, Helen Noble, Nawal Nour, Elizabeth Janiak, Sarrah Shahawy

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Introduction: Immigrant and refugee women experience disparities in sexual and reproductive health (SRH) outcomes, partially as a result of barriers to SRH literacy and to regular healthcare access and engagement. Despite the existing data highlighting growing needs for culturally relevant and structurally competent care, interventions are scarce and not well-documented. Methods: In this IRB-approved study, we used a community-based participatory research approach, with the assistance of a community advisory board, to conduct a qualitative needs assessment of SRH knowledge and service engagement with immigrant and refugee women from Africa or the Middle East and currently residing in Boston. We conducted a total of nine focus group discussions (FGDs) in partnership with medical, community, and religious centers, in six languages: Arabic, English, French, Somali, Pashtu, and Dari. A total of 44 individuals participated. We explored migrant and refugee women’s current and evolving SRH care needs and gaps, specifically related to the development of interventions and clinical best practices targeting SRH literacy, healthcare engagement, and informed decision-making. Recordings of the FGDs were transcribed verbatim and translated by interpreter services. We used open coding with multiple coders who resolved discrepancies through consensus and iteratively refined our codebook while coding data in batches using Dedoose software. Results: Participants reported immigrant adaptation experiences, discrimination, and feelings of trust, autonomy, privacy, and connectedness to family, community, and the healthcare system as factors surrounding SRH knowledge and needs. The context of previously learned SRH knowledge was commonly noted to be in schools, at menstruation, before marriage, from family members, partners, friends, and online search engines. Common themes included empowering strength drawn from religious and cultural communities, difficulties bridging educational gaps with their US- born daughters, and a desire for more SRH education from multiple sources, including family, health care providers, and religious experts & communities. Regarding further SRH education, participants’ preferences varied regarding ideal platform (virtual vs. in-person), location (in religious and community centers or not), smaller group sizes, and the involvement of men. Conclusions: Based on these results, empowering SRH initiatives should include both community and religious center-based, as well as clinic-based, interventions. Interventions should be composed of frequent educational workshops in small groups involving age-grouped women, daughters, and (sometimes) men, tailored SRH messaging, and the promotion of culturally, religiously, and linguistically competent care.

Keywords: community, immigrant, religion, sexual & reproductive health, women's health

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Authors: Martin Adlington, Boris Ceranic, Sally Shazhad

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In an effort to reduce carbon emissions, changes in UK regulations, such as Part L Conservation of heat and power, dictates improved thermal insulation and enhanced air tightness. These changes were a direct response to the UK Government being fully committed to achieving its carbon targets under the Climate Change Act 2008. The goal is to reduce emissions by at least 80% by 2050. Factors such as climate change are likely to exacerbate the problem of overheating, as this phenomenon expects to increase the frequency of extreme heat events exemplified by stagnant air masses and successive high minimum overnight temperatures. However, climate change is not the only concern relevant to overheating, as research signifies, location, design, and occupation; construction type and layout can also play a part. Because of this growing problem, research shows the possibility of health effects on occupants of buildings could be an issue. Increases in temperature can perhaps have a direct impact on the human body’s ability to retain thermoregulation and therefore the effects of heat-related illnesses such as heat stroke, heat exhaustion, heat syncope and even death can be imminent. This review paper presents a comprehensive evaluation of the current literature on the causes and health effects of overheating in buildings and has examined the differing applied assessment approaches used to measure the concept. Firstly, an overview of the topic was presented followed by an examination of overheating research work from the last decade. These papers form the body of the article and are grouped into a framework matrix summarizing the source material identifying the differing methods of analysis of overheating. Cross case evaluation has identified systematic relationships between different variables within the matrix. Key areas focused on include, building types and country, occupants behavior, health effects, simulation tools, computational methods.

Keywords: overheating, climate change, thermal comfort, health

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Authors: P. Bharathiraja

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Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

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Authors: Amy Stringer, Resa Chandler

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High Intensity Interval Training (HIIT) involves a 3-10-minute circuit of various exercises which is a viable alternative to a traditional cardiovascular and strength training regimen. Research suggests that measures of health-related fitness can either be maintained or actually improve with the use of this training method. After conducting a 6-week HIIT research study with 10-14 year old children, considerations for using a daily HIIT workout are presented. Is the use of HIIT with children a reasonable consideration for physical education programs? The benefits and challenges of this type of an intervention are identified. This study is significant in that achieving fitness gains in a small amount of daily class time is an attractive concept – especially for physical education teachers who often do not have the time necessary to accomplish all of their curricular goals in the amount of class time assigned. Basic methodologies include students participating in a circuit of exercises for 7-10 minutes at 80-95% of max heart rate as measured by heart rate monitors. Student pre and post fitness test data were collected for cardio-vascular endurance, muscular endurance, and body composition. Research notes as well as commentary by the teachers and researchers who participated in the HIIT study contributed to the understanding of the cost-benefit analysis. Major findings of the study are that HIIT has limited effectiveness but is a good choice for limited class times. Student efficacy of their ability to complete the exercises and visible heart rate data were considered to be significant factors in success of the HIIT study. The effective use of technology promoting positive audience effect during the display of heart rate data was more important at the beginning of the study than at the end. Student ‘buy-in’ and motivation, teacher motivation and ‘buy-in’, the variety of activities in the circuit and the fitness level of the student at the beginning of the study were also findings influencing the fitness outcomes of the study. Concluding Statement: High intensity interval training can be used effectively in a secondary physical education program. It is not a ‘magic bullet’ to produce health-related fitness outcomes in every student but it is an effective tool to enhance student fitness in a limited time and contribute to the goals of the program.

Keywords: cardio vascular fitness, children, high intensity interval training, physical education

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Authors: Xiaowen Zhang, Wanda Luen-Wun Siu

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The paper reviews the insights gained in combating COVID-19 in the US, Japan, and China. After evaluation and investigation, we found that China’s and Japan’s experience of fighting COVID-19 is commendable. The Chinese government and the Japanese administration have implemented highly effective governance and public health course of action to fight COVID-19. Government-led epidemic control with a staunch belief in science can roll out effective pandemic control strategies. In contrast, the US failed to react to COVID-19 effectively. The relaxed public health measures of ending shutdowns prematurely were not working. When the US keeps business open after the spring shutdown, COVID-19 cases are soaring. Such experiences inform us effective governance and a mandatory and stricter approach can better curb a pandemic than milder measures in handling a public health emergency. And China and Japan, where collectivistic culture reins, can better maneuver a public health crisis with collective efforts.

Keywords: US, China, Japan, COVID-19

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Authors: Yina F. Muñoz, Alexander Paz, Hanns De La Fuente-Mella, Joaquin V. Fariña, Guilherme M. Sales

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The primary approach for estimating bridge deterioration uses Markov-chain models and regression analysis. Traditional Markov models have problems in estimating the required transition probabilities when a small sample size is used. Often, reliable bridge data have not been taken over large periods, thus large data sets may not be available. This study presents an important change to the traditional approach by using the Small Data Method to estimate transition probabilities. The results illustrate that the Small Data Method and traditional approach both provide similar estimates; however, the former method provides results that are more conservative. That is, Small Data Method provided slightly lower than expected bridge condition ratings compared with the traditional approach. Considering that bridges are critical infrastructures, the Small Data Method, which uses more information and provides more conservative estimates, may be more appropriate when the available sample size is small. In addition, regression analysis was used to calculate bridge deterioration. Condition ratings were determined for bridge groups, and the best regression model was selected for each group. The results obtained were very similar to those obtained when using Markov chains; however, it is desirable to use more data for better results.

Keywords: concrete bridges, deterioration, Markov chains, probability matrix

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Authors: Fan Ye

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Adverse weather conditions, particularly those with low visibility, are critical to the driving tasks. However, the direct relationship between visibility distances and traffic flow/roadway safety is uncertain due to the limitation of visibility data availability. The recent growth of deployment of Road Weather Information Systems (RWIS) makes segment-specific visibility information available which can be integrated with other Intelligent Transportation System, such as automated warning system and variable speed limit, to improve mobility and safety. Before applying the RWIS visibility measurements in traffic study and operations, it is critical to validate the data. Therefore, an attempt was made in the paper to examine the validity and viability of RWIS visibility data by comparing visibility measurements among RWIS, airport weather stations, and weather information recorded by police in crash reports, based on Ohio data. The results indicated that RWIS visibility measurements were significantly different from airport visibility data in Ohio, but no conclusion regarding the reliability of RWIS visibility could be drawn in the consideration of no verified ground truth in the comparisons. It was suggested that more objective methods are needed to validate the RWIS visibility measurements, such as continuous in-field measurements associated with various weather events using calibrated visibility sensors.

Keywords: RWIS, visibility distance, low visibility, adverse weather

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Authors: Rahul Malhotra

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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: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

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Authors: Vahid Bayrami Rad

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In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

Procedia PDF Downloads 60