Search results for: health data

Authors: Stamatis Zoras, Vasilis Evagelopoulos, Theodoros Staurakas

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The association between elevated air pollution levels and extreme climate conditions (temperature, particulate matter, ozone levels, etc.) and mental consequences has been, recently, the focus of significant number of studies. It varies depending on the time of the year it occurs either during the hot period or cold periods but, specifically, when extreme air pollution and weather events are observed, e.g. air pollution episodes and persistent heatwaves. It also varies spatially due to different effects of air quality and climate extremes to human health when considering metropolitan or rural areas. An air pollutant concentration and a climate extreme are taking a different form of impact if the focus area is countryside or in the urban environment. In the built environment the climate extreme effects are driven through the formed microclimate which must be studied more efficiently. Variables such as biological, age groups etc may be implicated by different environmental factors such as increased air pollution/noise levels and overheating of buildings in comparison to rural areas. Gridded air quality and climate variables derived from the land surface observations network of West Macedonia in Greece will be analysed against mortality data in a spatial format in the region of West Macedonia. Artificial intelligence (AI) tools will be used for data correction and prediction of health deterioration with climatic conditions and air pollution at local scale. This would reveal the built environment implications against the countryside. The air pollution and climatic data have been collected from meteorological stations and span the period from 2000 to 2009. These will be projected against the mortality rates data in daily, monthly, seasonal and annual grids. The grids will be operated as AI-based warning models for decision makers in order to map the health conditions in rural and urban areas to ensure improved awareness of the healthcare system by taken into account the predicted changing climate conditions. Gridded data of climate conditions, air quality levels against mortality rates will be presented by AI-analysed gridded indicators of the implicated variables. An Al-based gridded warning platform at local scales is then developed for future system awareness platform for regional level.

Keywords: air quality, artificial inteligence, climatic conditions, mortality

Procedia PDF Downloads 116

Authors: Tanya L. Patimeteeporn, Murali D. Nair

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There is a wide range of literature that suggests the factors that prevent Asian American families from utilizing mental health services. These factors arise from a combination of cultural perceptions of mental illness, and methods of treating them without the use of a mental health professional. Due to the increased awareness of Asian Americans’ stigmatization to mental health, there has been an effort to create culturally competent interventions for Asian American families that would reduce opposition to mental health services. Assessment of the effectiveness of these interventions reveals practices that integrate traditional healing methods with psychoeducation are more likely to promote receptiveness of mental health services by Asian American families. The documentary in this review, demonstrates these traditional healing methods from various ethnic enclaves in Los Angeles. In addition, mental health professionals who provide these interventions to Asian American families need to consider culture-bound syndromes and the various Asian health philosophies and belief systems in order to provide a culturally sensitive holistic treatment for their clients. However, because the literature on these interventions is limited, there is a need for a larger body of evidence to accurately assess the effectiveness of these culturally competent psychoeducation interventions.

Keywords: Asian American, cultural boundaries, intervention, mental health stigma, psychoeducation, traditional healing

Procedia PDF Downloads 549

Authors: Abdelbaset M. Elghriani, Abdelsalam M. Maatuk, Isam Denna, Amira Abdulla Werfalli

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Electronic prescription software (e-prescribing) benefits patients and physicians by preventing handwriting errors and giving accurate prescriptions. E-prescribing allows prescriptions to be written and sent to pharmacies electronically instead of using handwritten notes. Significant factors that may affect the adoption of e-prescription systems include lacking technical support, financial resources to operate the systems, and change resistance from some clinicians, which have been identified as barriers to the implementation of e-prescription systems. This study aims to explore the trends and opinions of physicians and pharmacists about e-prescriptions and to identify the obstacles and benefits of the application of e-prescriptions in the health care system. A cross-sectional descriptive study was conducted at three Libyan public hospitals. Data were collected through a self-constructed questionnaire to assess the opinions regarding potential constraining factors and benefits of implementing an e-prescribing system in hospitals. Data presented as mean, frequency distribution table, cross-tabulation, and bar charts. Data analysis was performed, and the results show that technical, financial, and organizational obstacles are the most important obstacles that prevent the application of e-prescribing systems in Libyan hospitals. In addition, there was awareness of the benefits of e-prescribing, especially reducing medication dispensing errors, and a desire of physicians and pharmacists to use electronic prescriptions.

Keywords: physicians, e-prescribing, health care system, pharmacists

Procedia PDF Downloads 128

Authors: Martin Böhmer, Agatha Dabrowski, Boris Otto

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The trend of digitization significantly changes the role of data for enterprises. Data turn from an enabler to an intangible organizational asset that requires management and qualifies as a tradeable good. The idea of a networked economy has gained momentum in the data domain as collaborative approaches for data management emerge. Traditional organizational knowledge consequently needs to be extended by comprehensive knowledge about data. The knowledge about data is vital for organizations to ensure that data quality requirements are met and data can be effectively utilized and sovereignly governed. As this specific knowledge has been paid little attention to so far by academics, the aim of the research presented in this paper is to conceptualize it by proposing a “data knowledge model”. Relevant model entities have been identified based on a design science research (DSR) approach that iteratively integrates insights of various industry case studies and literature research.

Keywords: data management, digitization, industry 4.0, knowledge engineering, metamodel

Procedia PDF Downloads 356

Authors: Samuel Munaf, Kevin Swingler, Franz Brülisauer, Anthony O’Hare, George Gunn, Aaron Reeves

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Web scraping and text mining are popular computer science methods deployed by public health researchers to augment traditional epidemiological surveillance. However, within veterinary disease surveillance, such techniques are still in the early stages of development and have not yet been fully utilised. This study presents an exploration into the utility of incorporating internet-based data to better understand the smallholder farming communities within Scotland by using online text extraction and the subsequent mining of this data. Web scraping of the livestock fora was conducted in conjunction with text mining of the data in search of common themes, words, and topics found within the text. Results from bi-grams and topic modelling uncover four main topics of interest within the data pertaining to aspects of livestock husbandry: feeding, breeding, slaughter, and disposal. These topics were found amongst both the poultry and pig sub-forums. Topic modeling appears to be a useful method of unsupervised classification regarding this form of data, as it has produced clusters that relate to biosecurity and animal welfare. Internet data can be a very effective tool in aiding traditional veterinary surveillance methods, but the requirement for human validation of said data is crucial. This opens avenues of research via the incorporation of other dynamic social media data, namely Twitter and Facebook/Meta, in addition to time series analysis to highlight temporal patterns.

Keywords: veterinary epidemiology, disease surveillance, infodemiology, infoveillance, smallholding, social media, web scraping, sentiment analysis, geolocation, text mining, NLP

Procedia PDF Downloads 101

Authors: Kimberly Tasha Jiayi Tang, Changqing Lin, Zhe Wang, Tze-Wai Wong, Md. Shakhaoat Hossain, Jian Yu, Alexis Lau

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Hong Kong has practiced a risk-based Air Quality Health Index (AQHI) system that sums hospitalization risks associated with short-term exposure to air pollu-tants. As an air pollution risk communication tool, it informs the public about the current air quality, anchoring around the World Health Organization's (WHO) 2005 Air Quality Guidelines (AQGs). Given the WHO's recent update in 2021, assessing how Hong Kong’s air quality risk communication can be en-hanced using these updated guidelines is essential. Hong Kong’s AQHI is lim-ited by solely focusing on short-term health risks, which could lead the public to underestimate cumulative health impacts. Therefore, we propose the intro-duction of a composite AQHI that reports both long-term and short-term health risks. Additionally, the WHO interim targets will be considered as anchor points for various health risk categories. Furthermore, with the increasing ozone levels in Hong Kong and Southern China due to improved NOx mitigation measures, it has been a challenging task in balancing health protection against climate mitigation. However, our findings present a promising outlook. Despite the rise in ozone levels, the combined health risks in Hong Kong and Guang-dong have seen a decline, largely due to reductions in NO2 and PM concentra-tions, both having significant health implications. By shifting from a concentra-tion-based approach to a health risk-based system like the AQHI, our study highlights the prospective of harmonizing health protection and climate mitiga-tion goals. This health-focused framework suggests that rigorous NOx controls can effective-ly serve both objectives in parallel.

Keywords: air quality management, air quality health index, health risk management, air pollution

Procedia PDF Downloads 75

Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

Procedia PDF Downloads 355

Authors: Jae-Hyuk Hyun, Dong-Sung Bae, Jea-Sun Lee

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The COVID-19 pandemic emphasized the benefits of natural green space on mental health in pandemic situations. The effects of greenspace on reducing mental health disorder are detected, but limitations impede highlighting the overall effectiveness of greenspace on mental health to be valid and significant. Therefore, this study aims to comprehensively and quantitatively analyze the effectiveness and significance of greenspace in reducing mental disorders after the COVID-19 outbreak. This study adopted a systematic review to select adequate, necessary studies with significant associations between greenspace and mental health after COVID-19. Meta-analysis is performed using the selected studies for calculating and analyzing the combined effect size of greenspace on reducing mental disorder, difference of effect size in various factors of greenspace or mental health, and variables’ effects on greenspace or mental health. Also, a correlation test using MQRS and effect size is performed to determine significant correlations of factors in greenspace and mental health. The analysis confirmed the combined effect size of the association between greenspace and mental health to be interpreted as large enough (medium effect size, 0.565). Various factors consisting of greenspace or mental health had considerable effect sizes, with heterogeneity existing between studies of different greenspace and mental health aspects (subgroups). A significant correlation between factors in greenspace and mental health was identified, with correlations satisfying both reliability and effectiveness used for suggesting necessary greenspace policies with mental health benefits during the pandemic situation. Different variables of the study period, female proportion, and mean age significantly affected certain factors of greenspace or mental health, while the increase in effects of greenspace on mental health was detected as the COVID-19 period continued. Also, the regional heterogeneity of effects on the association between greenspace and mental health is recognized in all factors consisting of greenspace and mental health except for the visitation of greenspace. In conclusion, valid and significant effects were detected in various associations between greenspace and mental health. Based on the results of this study, conducting elaborate research and establishing adequate and necessary greenspace policies and strategies are recommended to effectively benefit the mental health of citizens in future pandemic situations.

Keywords: greenspace, natural environment, mental health, mental disorder, COVID-19, pandemic, systematic review, meta-analysis

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Authors: Lenka Jesonkova, Frantisek Bozek

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Trihalogenmethanes (THMs) are disinfection byproducts with non-carcinogenic and genotoxic effects. The contamination of 6 sites close to the water treatment plant has been monitored in second largest city of the Czech Republic. Health risk assessment including both non-carcinogenic and genotoxic risk for long term exposition was realized using the critical concentrations. Concentrations of trihalogenmethanes met national standards in all samples. Risk assessment proved that health risks from trihalogenmethanes are acceptable on each site.

Keywords: drinking water, health risk assessment, trihalogenmethanes, water pollution

Procedia PDF Downloads 521

Authors: Zeyad Suleiman Bataineh

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Introduction: civilian wars are associated with severe humanitarian effects that include loss of individuals and properties. Psychological dimensions are also included depression. Objectives: the main objectives of the present study were to investigate the depression level among Syrian patients who visited internal medicine clinics and other related variables. Methods and subjects: this study was conducted based on cross sectional study design. A total of 175 patients were involved. Patients were asked to fill a questionnaire to assess the level of depression that include demographic variables such as gender, age, educational level, and social status. Beck Aaron scale for depression was used. Participation in this study was voluntary, and all patients were informed about their rights to withdraw from the study without being negatively affected. Data were entered into excel spreading sheet for all participants. SPSS version 21 was used to analyze data. Data were described as means, the standard deviation for linear variables, frequencies, and percentages for categorical variables. The relationships between variables were evaluated using independent t test and One Way ANOVA test. Significance was considered at α≤0.05. Results: Depression was found in 152 (87%) of participants. The majority of participants with depression had moderate to severe depression. Depression was significantly associated gender, age, educational level, and social status (p<0.05). Conclusion: psychological rehabilitation is required for patients who experienced civilian wars.

Keywords: mental health, deprssion, health system, psychological dimension

Procedia PDF Downloads 129

Authors: Priti Kumari, Tricha Anjali

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Body Area Networks (BANs) have emerged as the most promising technology for pervasive health care applications. Since they facilitate communication of very sensitive health data, information leakage in such networks can put human life at risk, and hence security inside BANs is a critical issue. Safe distribution and periodic refreshment of cryptographic keys are needed to ensure the highest level of security. In this paper, we focus on the key distribution techniques and how they are categorized for BAN. The state-of-art pre-shared key distribution algorithms are surveyed. Possible attacks on algorithms are demonstrated with examples.

Keywords: attacks, body area network, key distribution, key refreshment, pre-shared keys

Procedia PDF Downloads 366

Authors: Mohsen Shahbakhti

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The aim of this study was to examine the relationship between self-esteem, social support and mental health in a sample of government high school students in Eshtehard city in Alborz Province in Iran. Three hundred and eleven students (boys) were included in this study. All participants completed the General Health Questionnaire (GHQ 12), Multidimensional Scale of Perceived Social Support (MSPSS -12), and Self-Esteem Scale (SS-10). The results revealed that self-esteem was positively associated with social support. Self-esteem and social support negatively associated with psychological distress. Self-esteem and social support to influence on mental health.

Keywords: self-esteem, social support, mental health, high school students

Procedia PDF Downloads 486

Authors: Jamilu Lawal Ajiya

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Background: Physical activity is essential for improving maternal health outcomes, particularly in low- and middle-income countries like Nigeria. Objective: The aim is to evaluate the effectiveness of physical activity interventions on maternal health outcomes among Nigerian pregnant women. Methods: Systematic review and meta-analysis of randomized controlled trials (RCTs) conducted in Nigeria, published in English, and focusing on physical activity and maternal health outcomes. Results: Ten RCTs (N=1,200) were included. Physical activity interventions significantly reduced the risk of gestational diabetes, hypertension and preterm birth. Also, the study found that brisk walking and aerobic exercise were more effective than yoga. Conclusion: Physical activity interventions improve maternal health outcomes among Nigerian pregnant women. Policy changes and public health programs should prioritize physical activity promotion during pregnancy. This study informs healthcare providers, policymakers, and researchers on the effectiveness of physical activity interventions in improving maternal health outcomes in Nigeria.

Keywords: physical activity, maternal health, Nigeria, randomized controlled trials

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Authors: Cindy Agyemang

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This study seeks to find out if racial sentiment toward immigrants still matters in the United States with COVID-19 present. It is argued that previous studies on immigration and racial attitudes or race conducted do not consider how health-related pandemics influence public opinion on immigration and the racial attitudes of people during severe health-related pandemics. In doing so, this paper hypothesizes that respondents' racial sentiment towards immigrants during this pandemic will influence their views on opposing immigration, those that believe the president handled cases on COVID-19 better are more likely to oppose immigration, and party affiliation affects respondents' views on immigration and COVID-19. For testing these hypotheses, the 2012, 2016, and 2020 American National Election Studies data was used. In accordance with the expectations of this study, it was observed that there was a statistically significant relationship between all my estimated models. This paper concludes that racial sentiment toward immigrants still matters even more in the United States, especially with the existence of health-related pandemics.

Keywords: COVID-19, immigration, racial attitudes, partisanship

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Authors: Ceren Akyüz, Ingo Froboese

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Health literacy has gained importance with the further spread of the coronavirus disease (COVID-19) worldwide and has been associated with health status in various chronic diseases. Many studies indicate that mental health can be improved by low- or moderate-intensity activity, and several studies have been proposed to explain the relationship between physical activity and mental health. The aim of the present study is to investigate the levels of physical activity, health literacy, and depression in first- and- second generation Turkish people in Germany. The research consists of 434 participants (255 females, 179 males; age 38.09 ± 13.73). 40.8 % of participants are married, and 59.2 % of participants are single. Education levels are mostly at university level (54.8 %), and graduate level is 18.9 %. While 24.9 % of the participants are second generation, 75.1 % of participants are first generation. All analyses were stratified on gender, marital status, education, generation and income status, and five age categories: 18–30, 31–40, 41–50, 51–60, and 61–79, which were defined to account for age-specific trends while maintaining sufficient cell size for statistical analysis. A correlation of depression with physical activity and health literacy levels between first- and- second generation Turks in Germany was evaluated in order to find out whether there are significant differences between the two populations and demographic variables (gender, marital status, education, generation, income status) with carrying out questionnaires which are European Health Literacy Survey Questionnaire (HLS-EU-Q47), International Physical Activity Questionnaire ( IPAQ) and the Patient Health Questionnaire-9 (PHQ-9).

Keywords: health literacy, turks in germany, migrants, depression, physical activity

Procedia PDF Downloads 84

Authors: Moses E. Emetere, M. L. Akinyemi

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Agricultural activities in the South–West Nigeria are mitigated by the global increase in temperature. The unpredictive surface temperature of the area had increased health challenges amongst other social influence. The satellite data of surface temperatures were compared with the ground station Davis weather station. The differential heating of the lower atmosphere were represented mathematically. A numerical predictive model was propounded to forecast future surface temperature.

Keywords: numerical predictive model, surface temperature, satellite date, ground data

Procedia PDF Downloads 474

Authors: David Bakker, Nikki Rickard

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Smartphone apps hold immense potential as mental health and wellbeing tools. Support can be made easily accessible and can be used in real-time while users are experiencing distress. Furthermore, data can be collected to enable machine learning and automated tailoring of support to users. While many apps have been developed for mental health purposes, few have adhered to evidence-based recommendations and even fewer have pursued experimental validation. This paper details the development and experimental evaluation of an app, MoodMission, that aims to provide support for low moods and anxiety, help prevent clinical depression and anxiety disorders, and serve as an adjunct to professional clinical supports. MoodMission was designed to deliver cognitive behavioural therapy for specifically reported problems in real-time, momentary interactions. Users report their low moods or anxious feelings to the app along with a subjective units of distress scale (SUDS) rating. MoodMission then provides a choice of 5-10 short, evidence-based mental health strategies called Missions. Users choose a Mission, complete it, and report their distress again. Automated tailoring, gamification, and in-built data collection for analysis of effectiveness was also included in the app’s design. The development process involved construction of an evidence-based behavioural plan, designing of the app, building and testing procedures, feedback-informed changes, and a public launch. A randomized controlled trial (RCT) was conducted comparing MoodMission to two other apps and a waitlist control condition. Participants completed measures of anxiety, depression, well-being, emotional self-awareness, coping self-efficacy and mental health literacy at the start of their app use and 30 days later. At the time of submission (November 2016) over 300 participants have participated in the RCT. Data analysis will begin in January 2017. At the time of this submission, MoodMission has over 4000 users. A repeated-measures ANOVA of 1390 completed Missions reveals that SUDS (0-10) ratings were significantly reduced between pre-Mission ratings (M=6.20, SD=2.39) and post-Mission ratings (M=4.93, SD=2.25), F(1,1389)=585.86, p < .001, np2=.30. This effect was consistent across both low moods and anxiety. Preliminary analyses of the data from the outcome measures surveys reveal improvements across mental health and wellbeing measures as a result of using the app over 30 days. This includes a significant increase in coping self-efficacy, F(1,22)=5.91, p=.024, np2=.21. Complete results from the RCT in which MoodMission was evaluated will be presented. Results will also be presented from the continuous outcome data being recorded by MoodMission. MoodMission was successfully developed and launched, and preliminary analysis suggest that it is an effective mental health and wellbeing tool. In addition to the clinical applications of MoodMission, the app holds promise as a research tool to conduct component analysis of psychological therapies and overcome restraints of laboratory based studies. The support provided by the app is discrete, tailored, evidence-based, and transcends barriers of stigma, geographic isolation, financial limitations, and low health literacy.

Keywords: anxiety, app, CBT, cognitive behavioural therapy, depression, eHealth, mission, mobile, mood, MoodMission

Procedia PDF Downloads 272

Authors: Meenal Badki

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We address the issue of active feature determination, where the objective is to determine the set of examples on which additional data (such as lab tests) needs to be gathered, given a large number of examples with some features (such as demographics) and some examples with all the features (such as the complete Electronic Health Record). We note that certain features may be more costly, unique, or laborious to gather. Our proposal is a general active learning approach that is independent of classifiers and similarity metrics. It allows us to identify examples that differ from the full data set and obtain all the features for the examples that match. Our comprehensive evaluation shows the efficacy of this approach, which is driven by four authentic clinical tasks.

Keywords: feature determination, classification, active learning, sample-efficiency

Procedia PDF Downloads 77

Authors: Usma Iftikhar, Khorshed Alam

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Background: Digital health platforms and digital health interventions are gaining increasing importance with the shift to online health-seeking behaviour, especially post-Covid. Subsequently, the importance of digital health literacy is increasingly being recognized. With the surge in culturally and linguistically diverse populations in First World countries, especially females, the predictors of digital health access in this population remain elusive. Keeping in view the inadequate digital infrastructure in rural and remote Australia, with lack of specialist services, the determinants of digital access gain even more importance. Objectives: The objective of this research are to measure the digital health literacy levels in this population, including the predictors of digital health literacy like sociodemographics and the correlation between the predictors and digital health literacy levels. Methods: A population-based quantitative survey was carried out in Regional Queensland from Jan 2022- Dec 2023 on culturally and linguistically diverse adult females. Sociodemographics like age, literacy levels, socioeconomic status, access to digital devices were recorded after informed consent. Digital health literacy levels were measured by specially designed questionnaires. The relationship between sociodemographics and digital health literacy levels was estimated by Pearson correlation. Results: Mean DHL was 2.66 + 0.35. There was a negative significant relationship (p<0.005) between demographics like age and access to a digital device with digital health literacy levels. Also observed was a positive significant relationship between literacy levels and proficiency in English. Conclusion: Age, literacy levels and English proficiency are some of the highest predictors of digital health access. This is important because remote areas rely on digital health access due to less developed health infrastructure, including specialist services. Guide for Policy makers to focus on the populations most in need.

Keywords: digital health literacy, eHealth literacy, culturally and linguistically diverse, ethnic minorities, regional areas, rural and remote areas

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Authors: Sombol Mokhles

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This paper tries to show the prospects of utilising (big)data for enabling just the transition of diverse cities. Our key purpose is to offer a framework of applications and implications of utlising (big) data in comparing sustainability transitions across different cities. Relying on the cosmopolitan comparison, this paper explains the potential application of (big) data but also its limitations. The paper calls for adopting a data-driven and just perspective in including different cities around the world. Having a just and inclusive approach at the front and centre ensures a just transition with synergistic effects that leave nobody behind.

Keywords: big data, just sustainable transition, cosmopolitan city comparison, cities

Procedia PDF Downloads 99

Authors: Anupama Singh, Papia Raj

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Though Municipal Solid Waste (MSW) is a worldwide problem, yet its implications are enormous in developing countries, as they are unable to provide proper Municipal Solid Waste Management (MSWM) for the large volume of MSW. As a result, the collected wastes are dumped in open dumping at landfilling sites while the uncollected wastes remain strewn on the roadside, many-a-time clogging drainage. Such unsafe and inadequate management of MSW causes various public health hazards. For example, MSW directly on contact or by leachate contaminate the soil, surface water, and ground water; open burning causes air pollution; anaerobic digestion between the piles of MSW enhance the greenhouse gases i.e., carbon dioxide and methane (CO2 and CH4) into the atmosphere. Moreover, open dumping can cause spread of vector borne disease like cholera, typhoid, dysentery, and so on. Patna, the capital city of Bihar, one of the most underdeveloped provinces in India, is a unique representation of this situation. Patna has been identified as the ‘garbage city’. Over the last decade there has been an exponential increase in the quantity of MSW generation in Patna. Though a large proportion of such MSW is recyclable in nature, only a negligible portion is recycled. Plastic constitutes the major chunk of the recyclable waste. The chemical composition of plastic is versatile consisting of toxic compounds, such as, plasticizers, like adipates and phthalates. Pigmented plastic is highly toxic and it contains harmful metals such as copper, lead, chromium, cobalt, selenium, and cadmium. Human population becomes vulnerable to an array of health problems as they are exposed to these toxic chemicals multiple times a day through air, water, dust, and food. Based on analysis of health data it can be emphasized that in Patna there has been an increase in the incidence of specific diseases, such as, diarrhoea, dysentry, acute respiratory infection (ARI), asthma, and other chronic respiratory diseases (CRD). This trend can be attributed to improper MSWM. The results were reiterated through a survey (N=127) conducted during 2014-15 in selected areas of Patna. Random sampling method of data collection was used to better understand the relationship between different variables affecting public health due to exposure to MSW and lack of MSWM. The results derived through bivariate and logistic regression analysis of the survey data indicate that segregation of wastes at source, segregation behavior, collection bins in the area, distance of collection bins from residential area, and transportation of MSW are the major determinants of public health issues. Sustainable recycling is a robust method for MSWM with its pioneer concerns being environment, society, and economy. It thus ensures minimal threat to environment and ecology consequently improving public health conditions. Hence, this paper concludes that sustainable recycling would be the most viable approach to manage MSW in Patna and would eventually reduce public health hazards.

Keywords: municipal solid waste, Patna, public health, sustainable recycling

Procedia PDF Downloads 326

Authors: Modesta E. Ezema, Christopher C. Ezema, Christian C. Ugwu, Udoka F. Eze, Florence M. Babalola

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Some employees knowingly or unknowingly contribute to loss of data and also expose data to threat in the process of getting their jobs done. Many organizations today are faced with the challenges of how to secure their data as cyber criminals constantly devise new ways of attacking the organization’s secret data. However, this paper enlists the latest strategies that must be put in place in order to protect these important data from being attacked in a collaborative work place. It also introduces us to Advanced Persistent Threats (APTs) and how it works. The empirical study was conducted to collect data from the employee in data centers on how data could be protected from malicious codes and cyber criminals and their responses are highly considered to help checkmate the activities of malicious code and cyber criminals in our work places.

Keywords: data, employee, malware, work place

Procedia PDF Downloads 385

Authors: Lynne Briggs, Patricia Fronek, Judy Siu.

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This qualitative study aimed to gain a better understanding of the perceptions and barriers to receiving seasonal influenza and pneumococcal vaccines among Australian and Hong Kong adults aged ≥ 65 years. The findings showed that vaccine uptake for the two diseases was lower in Hong Kong than in Australia. Common and divergent issues identified included the impact of different health systems, the promotion of vaccination by health professionals, beliefs about hospitals and clinics, traditional and alternative medicines, perceptions of risk, and personal responsibility. Objective of the research: The objective of this comparison study was to gain a better understanding of the perceptions and barriers to receiving seasonal influenza and pneumococcal vaccines among Australian and Hong Kong adults aged ≥ 65 years. Methodology: This qualitative study used semi structured face to face interviews for data collection in both countries. Thematic analysis of the data allowed for a comparison of the main themes identified across the two countries. Main Contribution of the Research: Differences in vaccine uptake between Australian and Hong Kong was attributable to differing health systems, including access, prevention, socioeconomic status, and cultural attitudes. Understanding the needs of older people would enhance vaccine uptake for these two preventable diseases.

Keywords: influenza vaccine uptake, pneumonia vaccine uptake, vaccination of the elderly, hesitancy vaccine

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Authors: N. Mathew, A. Qureshi, D. C. Khakha, R. Sagar

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Adolescents in India, account for one-fifth of the total population and are a significant human resource. Present study was conducted to find out various life stressors of adolescents, coping strategies adopted by them and the impact of stress on adolescent mental health. A descriptive, cross sectional study conducted on schools in the south zone of Delhi, capital city of the country. Data was collected on 360 adolescents between the age group of 13-17 years on socio-demographic profile, Adolescent life event stress scale, brief cope and youth self report for ages 11-18. Adolescents had significantly higher stress on uncontrollable events such as family events, relocation events, accident events and ambiguous events as compared to controllable events such as sexual events, deviance events and autonomy events (p<0.01).Adolescent stress was significantly correlated with various demographic variables in the study. The most frequently used coping strategies by the adolescents were positive reframing, planning, active coping, and instrumental support. It has also been found that the stress has a significant impact on adolescent mental health in the form of either internalizing problems such as anxious, withdrawn and somatic problems or externalizing problems such as rule breaking and aggressive behaviors. Out of the total sample of 360 adolescents 150 were identified as having psycho-social morbidity, including 59 borderline cases and 91 high-risk cases Study pointed out the need for mental health screening among the adolescents and also indicated the need for mental health inputs in educational institutions.

Keywords: adolecents, stress, coping, mental health

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Authors: Ahmed Noor Al-qayyim, Barlas Özden Çağlayan

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Structural failure is caused mainly by damage that often occurs on structures. Many researchers focus on obtaining very efficient tools to detect the damage in structures in the early state. In the past decades, a subject that has received considerable attention in literature is the damage detection as determined by variations in the dynamic characteristics or response of structures. This study presents a new damage identification technique. The technique detects the damage location for the incomplete structure system using output data only. The method indicates the damage based on the free vibration test data by using “Two Points - Condensation (TPC) technique”. This method creates a set of matrices by reducing the structural system to two degrees of freedom systems. The current stiffness matrices are obtained from optimization of the equation of motion using the measured test data. The current stiffness matrices are compared with original (undamaged) stiffness matrices. High percentage changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply supported steel beam model structure after inducing thickness change in one element. Where two cases are considered, the method detects the damage and determines its location accurately in both cases. In addition, the results illustrate that these changes in stiffness matrix can be a useful tool for continuous monitoring of structural safety using ambient vibration data. Furthermore, its efficiency proves that this technique can also be used for big structures.

Keywords: damage detection, optimization, signals processing, structural health monitoring, two points–condensation

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Authors: Nadir A. Carreon, Christa Sonderer, Aakarsh Rao, Roman Lysecky

Abstract:

With the advent of complex software and increased connectivity, the security of life-critical medical devices is becoming an increasing concern, particularly with their direct impact on human safety. Security is essential, but it is impossible to develop completely secure and impenetrable systems at design time. Therefore, it is important to assess the potential impact on the security and safety of exploiting a vulnerability in such critical medical systems. The common vulnerability scoring system (CVSS) calculates the severity of exploitable vulnerabilities. However, for medical devices it does not consider the unique challenges of impacts to human health and privacy. Thus, the scoring of a medical device on which human life depends (e.g., pacemakers, insulin pumps) can score very low, while a system on which human life does not depend (e.g., hospital archiving systems) might score very high. In this paper, we propose a medical vulnerability scoring system (MVSS) that extends CVSS to address the health and privacy concerns of medical devices. We propose incorporating two new parameters, namely health impact, and sensitivity impact. Sensitivity refers to the type of information that can be stolen from the device, and health represents the impact on the safety of the patient if the vulnerability is exploited (e.g., potential harm, life-threatening). We evaluate fifteen different known vulnerabilities in medical devices and compare MVSS against two state-of-the-art medical device-oriented vulnerability scoring systems and the foundational CVSS.

Keywords: common vulnerability system, medical devices, medical device security, vulnerabilities

Procedia PDF Downloads 169

Authors: Jia Yi Yap, Angela S. H. Lee

Abstract:

With the use of big data technologies, organization can get result that they are interested in. Big data technologies simply load all the data that is useful for the organizations and provide organizations a better way of analysing data. The purpose of this research is to get employees’ opinion from films in Malaysia to explore the use of big data technologies in their organization in order to provide how it may affect the perception of the employees on job performance. Therefore, in order to identify will accepting big data technologies in the organization affect the perception of the employee, questionnaire will be distributed to different employee from different Small and medium-sized enterprises (SME) organization listed in Malaysia. The conceptual model proposed will test with other variables in order to see the relationship between variables.

Keywords: big data technologies, employee, job performance, questionnaire

Procedia PDF Downloads 300

Authors: Shengdan Yang

Abstract:

The outbreak of the COVID-19 pandemic in early 2020 has made public health issues to be re-examined. The value of green space configuration is an important measure of community health quality. By combining quantitative and qualitative methods, the structure and function of community green space can be better evaluated. This study selects Wuhan Kunhou Community as the site and proposes to analyze the daily health service function of the community's green infrastructure. Through GIS-based spatial analysis, case study, and field investigation, this study evaluates the accessibility of green infrastructure and discusses the ideal green space form based on health indicators. The findings show that Kunhou Community lacks access to green infrastructure and public space for daily activities. The research findings provide a bridge between public health indicators and community space planning and propose design suggestions for green infrastructure planning.

Keywords: accessibility, community health, GIS, green infrastructure

Procedia PDF Downloads 114

Authors: Chechen Liao, Pui-Lai To, Yi-Hui Wang

Abstract:

Recently location-based augmented reality games (LBS+AR) have become increasingly popular as a major form of entertainment. Location-based augmented reality games have provided a lot of opportunities for face-to-face interaction among players. Prior studies also indicate that the social side of location-based augmented reality games are one of the major reasons for players to engage in the games. However, the impact of the usage of location-based augmented reality games has not been well explored. The study examines how interpersonal interaction affects social capital and health through playing location-based augmented reality games. The study also investigates how social capital mediates the relationships between interpersonal interaction and health. The study uses survey method to collect data. Six-hundred forty-seven questionnaires are collected. Structural equation modeling is used to investigate the relationships among variables. The causal relationships between variables in the research model are tested. The results of the study indicated that four interpersonal attraction attributes, including ability, proximity, similarity, and familiarity, are identified by ways of factor analysis. Interpersonal attraction is important for location-based augmented reality game-players to develop bonding and bridging social capital. Bonding and bridging social capital have a positive impact on the mental and social health of game-players. The results of the study provide academic and practical implications for future growth of location-based augmented reality games.

Keywords: health, interpersonal interaction, location-based augmented reality games, social capital

Procedia PDF Downloads 260

Authors: Teresa Smith, Farrah Jacquez

Abstract:

Health-risk behaviors (e.g., smoking, poor diet) directly increase the risk for chronic disease and morbidity. There is substantial evidence of a negative association between socioeconomic status (SES) and engagement in health-risk behaviors. However, due to the complexity of SES, researchers have suggested looking beyond this factor to fully understand the mechanisms that underlie engagement in health-risk behaviors. Stress is one plausible mechanism through which SES impacts health-risk behaviors. Currently, it remains unclear how stress occurring across the life course might impact health behaviors and explain the association between SES and these behaviors. To address the gaps in the literature, 172 adults between the ages of 18-49 were surveyed about their lifetime stress exposure, sociodemographic variables, and health-risk behaviors via an online recruitment portal, Prolific. Five major findings emerged from the current study. First, SES was negatively associated with engagement in health-risk behaviors and lifetime stress above and beyond current stress and other relevant demographics. Second, lifetime stress was significantly associated with health-risk behaviors above and beyond current stress and relevant demographic variables. Third, lifetime stress fully mediated the association between SES and health-risk behaviors above and beyond current stress and other demographics. Fourth, the severity of stress experienced emerged as the most significant lifetime stress variable that explains the relation between SES and health-risk behaviors. Fifth and finally, lower SES and experiencing financial and legal/crime stressors increased the likelihood of engaging in health-risk behaviors. The current study results align with previous research and suggest that stress occurring over the lifespan impacts the relation between SES and health-risk behaviors, which are in turn known to impact health outcomes. However, our findings move the current literature forward by providing a more nuanced understanding of the specific aspects of stress that influence this association. Specifically, the severity of stress experienced across the entire lifespan was the most important aspect of stress when examining the association between SES and health-risk behaviors. Further, individuals most at risk for engaging in health-risk behaviors are those of the lowest SES and experience financial and legal/crime stressors. These findings have the potential to inform interventions and policies aimed at addressing health-risk behaviors by providing a more sophisticated understanding of the impact of stress.

Keywords: stress, health behaviors, socioeconomic status, health

Procedia PDF Downloads 147