Search results for: remote healthcare

Authors: Shahid Razzaq

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The governments around the globe have started taking into considerations the knowledge management dynamics while formulating, implementing, and evaluating the strategies, with or without the conscious realization, for the different public sector organizations and public policy developments. Health Department of Punjab province in Pakistan is striving to deliver quality healthcare services to the community through an efficient and effective service delivery system. Despite of this struggle some employee performance issues yet exists in the form of challenge to government. To overcome these issues department took several steps including HR strategies, use of technologies and focus of hard issues. Consequently, this study was attempted to highlight the importance of soft issue that is knowledge management in its true essence to tackle their performance issues. Knowledge management in public sector is quite an ignored area in the knowledge management-a growing multidisciplinary research discipline. Knowledge-based view of the firm theory asserts the knowledge is the most deliberate resource that can result in competitive advantage for an organization over the other competing organizations. In the context of our study it means for gaining employee performance, organizations have to increase the heterogeneous knowledge bases. The study uses the cross-sectional and quantitative research design. The data is collected from the knowledge workers of Health Department of Punjab, the biggest province of Pakistan. A total of 341 sample size is achieved. The SmartPLS 3 Version 2.6 is used for analyzing the data. The data examination revealed that knowledge management processes has a strong impact on knowledge worker performance. All hypotheses are accepted according to the results. Therefore, it can be summed up that to increase the employee performance knowledge management activities should be implemented. Health Department within province of Punjab introduces the knowledge management infrastructure and systems to make effective availability of knowledge for the service staff. This knowledge management infrastructure resulted in an increase in the knowledge management process in different remote hospitals, basic health units and care centers which resulted in greater service provisions to public. This study is to have theoretical and practical significances. In terms of theoretical contribution, this study is to establish the relationship between knowledge management and performance for the first time. In case of the practical contribution, this study is to give an insight to public sector organizations and government about role of knowledge management in employ performance. Therefore, public policymakers are strongly advised to implement the activities of knowledge management for enhancing the performance of knowledge workers. The current research validated the substantial role of knowledge management in persuading and creating employee arrogances and behavioral objectives. To the best of authors’ knowledge, this study contribute to the impact of knowledge management on employee performance as its originality.

Keywords: employee performance, knowledge management, public sector, soft issues

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Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

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Authors: Saradha Priya

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Developing virtual human is very important to meet the challenges occurred in many applications where human find difficult or risky to perform the task. A robot is a machine that can perform a task automatically or with guidance. Robotics is generally a combination of artificial intelligence and physical machines (motors). Computational intelligence involves the programmed instructions. This project proposes a robotic vehicle that has a camera, PIR sensor and text command based movement. It is specially designed to perform surveillance and other few tasks in the most efficient way. Serial communication has been occurred between a remote Base Station, GUI Application, and PC.

Keywords: Zigbee, camera, pirsensor, wireless transmission, DC motor

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Authors: Chinasa U. Imo, Queen Chikwendu, Jonathan Ajuma, Mario Banuelos

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Background: Sociocultural norms primarily influence the health-seeking behavior of populations in rural communities. In the Nkporo community, Abia State, Nigeria, their sociocultural perception of diseases runs counter to biomedical definitions, wherein they rely heavily on traditional medicine and practices. In a state where birth asphyxia and sepsis account for the significant causes of death for neonates, malaria leads to the causes of other mortalities, followed by common preventable diseases such as diarrhea, pneumonia, acute respiratory tract infection, malnutrition, and HIV/AIDS. Most local mothers attribute their health conditions and that of their children to witchcraft attacks, the hand of God, and ancestral underlining. This influences how they see antenatal and postnatal care, choice of place of accessing care and birth delivery, response to children's illnesses, immunization, and nutrition. Method: To implement a community health improvement program, we adopted an asset-based community development model to address health's normative and social determinants. The first step was to use a qualitative approach to conduct a community health needs baseline assessment, involving focus group discussions with twenty-five (25) youths aged 18-25, semi-structured interviews with ten (10) officers-in-charge of primary health centers, eight (8) ward health committee members, and nine (9) community leaders. Secondly, we designed an intervention program. Going forward, we will proceed with implementing and evaluating this program. Result: The priority needs identified by the communities were malaria, lack of clean drinking water, and the need for behavioral change information. The study also highlighted the significant influence of youths on their peers, family, and community as caregivers and information interpreters. Based on the findings, the NGO SieDi-Hub collaborated with the Abia State Ministry of Health, the State Primary Healthcare Agency, and Empower Next Generations to design a one-year "Community Health Youth Champions Pilot Program." Twenty (20) youths in the community were trained and equipped to champion a participatory approach to bridging the gap between access and delivery of primary healthcare, to adjust sociocultural norms to improve health equity for people in Nkporo community – with limited education, lack of access to health information, and quality healthcare facilities using an innovative community-led improvement approach. Conclusion: Youths play a vital role in achieving health equity, being a vulnerable population with significant influence. To ensure effective primary healthcare, strategies must include cultural humility. The asset-based community development model offers valuable tools, and this article will share ongoing lessons from the intervention's behavioral change strategies with young people.

Keywords: asset-based community development, community health, primary health systems strengthening, youth empowerment

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Authors: Mohsen Shati, Seyede Salehe Mortazavi, Seyed Kazem Malakouti, Hamidreza Khanke Fazlollah Ahmadi

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Taking unnecessary or excessive medication or using drugs with no indication (polypharmacy) by people of all ages, especially the elderly, is associated with increased adverse drug reactions (ADR), medical errors, hospitalization and escalating the costs. It may be facilitated or impeded by the healthcare system. In this study, we are going to describe the role of the health system in the practice of polypharmacy in Iranian elderly. In this Inductive qualitative content analysis using Graneheim and Lundman methods, purposeful sample selection until saturation has been made. Participants have been selected from doctors, pharmacists, policy-makers and the elderly. A total of 25 persons (9 men and 16 women) have participated in this study. Data analysis after incorporating codes with similar characteristics revealed 14 subcategories and six main categories of the referral system, physicians’ accessibility, health data management, drug market, laws enforcement, and social protection. Some of the conditions of the healthcare system have given rise to polypharmacy in the elderly. In the absence of a comprehensive specialty and subspecialty referral system, patients may go to any physician office so may well be confused about numerous doctors' prescriptions. Electronic records not being prepared for the patients, failure to comply with laws, lack of robust enforcement for the existing laws and close surveillance are among the contributing factors. Inadequate insurance and supportive services are also evident. Age-specific care providing has not yet been institutionalized, while, inadequate specialist workforce playing a major role. So, one may not ignore the health system as contributing factor in designing effective interventions to fix the problem.

Keywords: elderly, polypharmacy, health system, qualitative study

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Maria Jose Mendoza Gordillo

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Introduction: Research regarding breastfeeding is devoted to how essential breastfeeding is to guarantee wellbeing for the mother and the baby from a medical standpoint relegating the cultural, material and social barriers for breastfeeding. Consequently, worldwide breastfeeding rates are low, and Ecuador is not the exception, especially among working mothers. Worldwide, health care providers have low rates of breastfeeding due to several barriers to lactation, such as the work schedule, a lack of private places for pumping while at work, and negative emotions. Goals and Methods: This study aimed to explore how do Ecuadorian women embrace their identities as nutritionists and mothers within their breastfeeding experience. The primary data come from 20 synchronous semi-structured interviews, which follow a topic guide. The interviews were recorded and transcribed verbatim. The data analysis followed the Phronetic Iterative Approach. Results: Women shifted the preconceived idea of the ideal breastfeeding that came from the medicalized discourse of breastfeeding, and that was constructed in their training as nutritionists. Although these women believe that breast milk and breastfeeding is the best way to feed a baby, the internalized ideal of breastfeeding shifted through the experience of motherhood. When these women developed their identity as mothers, they understood that the ideal breastfeeding is different from the medicalized discourse. Although they have that clash between the ideal and the external reality, they continued breastfeeding their babies and those experiences made them improve their professional practice. Conclusions: The narratives that women shared illustrate how complex it was to manage the different roles and identities that they wanted to fulfill to keep their identity of a good mother who breastfeeds her baby and, at the same time, a good healthcare provider identity. The process of breastfeeding for this group of women who are mothers and healthcare professionals appears to be a unique relational and identity negotiation process.

Keywords: breastfeeding, identity, nutritionist, qualitative

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Authors: Takashi Yamaguchi, Ichio Asanuma, Jong G. Park, Kenneth J. Mackin, John Mittleman

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In this paper, vessel detection using the artificial neural network is proposed in order to automatically construct the vessel detection model from the satellite imagery of day/night band (DNB) in visible infrared in the products of Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership (Suomi-NPP).The goal of our research is the establishment of vessel detection method using the satellite imagery of DNB in order to monitor the change of vessel activity over the wide region. The temporal vessel monitoring is very important to detect the events and understand the circumstances within the maritime environment. For the vessel locating and detection techniques, Automatic Identification System (AIS) and remote sensing using Synthetic aperture radar (SAR) imagery have been researched. However, each data has some lack of information due to uncertain operation or limitation of continuous observation. Therefore, the fusion of effective data and methods is important to monitor the maritime environment for the future. DNB is one of the effective data to detect the small vessels such as fishery ships that is difficult to observe in AIS. DNB is the satellite sensor data of VIIRS on Suomi-NPP. In contrast to SAR images, DNB images are moderate resolution and gave influence to the cloud but can observe the same regions in each day. DNB sensor can observe the lights produced from various artifact such as vehicles and buildings in the night and can detect the small vessels from the fishing light on the open water. However, the modeling of vessel detection using DNB is very difficult since complex atmosphere and lunar condition should be considered due to the strong influence of lunar reflection from cloud on DNB. Therefore, artificial neural network was applied to learn the vessel detection model. For the feature of vessel detection, Brightness Temperature at the 3.7 μm (BT3.7) was additionally used because BT3.7 can be used for the parameter of atmospheric conditions.

Keywords: artificial neural network, day/night band, remote sensing, Suomi National Polar-orbiting Partnership, vessel detection, Visible Infrared Imaging Radiometer Suite

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Authors: Christian Louis Kühner, Florian Pfeffel, Valentin Nickolai

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Taking care of children, dependents, or pets can be a difficult and time-consuming task. Especially for part- and full-time employees, it can feel exhausting and overwhelming to meet these obligations besides working a job. Thus, working mostly at home and not having to drive to the company can save valuable time and stress. This study aims to show the influence that the working model has on the job satisfaction of employees with care responsibilities in comparison to employees who do not have such obligations. Using structural equation modeling (SEM), the three work models, “work from home”, “working remotely”, and a hybrid model, have been analyzed based on 13 influencing constructs on job satisfaction. These 13 factors have been further summarized into three groups “classic influencing factors”, “influencing factors changed by remote working”, and “new remote working influencing factors”. Based on the influencing factors on job satisfaction, an online survey was conducted with n = 684 employees from the service sector. Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. In addition, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). The SEM-analysis has shown that the most significant influencing factor on job satisfaction is “identification with the work” with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis shows that the identification with the work is the most significant factor in all three work models and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that among the employees with care responsibilities, the higher the proportion of working from home in comparison to working from the office, the more satisfied the employees are with their job. Since the work models that meet the requirements of comprehensive care led to higher job satisfaction amongst employees with such obligations, adapting as a company to such private obligations by employees can be crucial to sustained success. Conversely, the satisfaction level of the working model where employees work at the office is higher for workers without caregiving responsibilities.

Keywords: care responsibilities, home office, job satisfaction, structural equation modeling

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Authors: Chrysi K. Nikoloutsou, Gianna Th. Siapati

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The pandemic limitations have altered architectural education as the discourse shifted towards virtual studios and blended learning. In addition, lockdown conditions and remote working have affected habitation. Adaptability is now a key factor. The architectural studio needs to adjust to these new terms both in education and in inhabitation. This paper will investigate the operation of an architectural studio in relation to how one experiences their house due to the pandemic, based on a literature review and qualitative research methods (interviews & workshops with students). Zenetos’ prophetic ideas of ‘Electronic Urbanism’ and ‘tele-activities’ are now more present than ever.

Keywords: architectural education, pandemic, residential design, studio pedagogy

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Authors: Walter Rafael Ramos Villanueva

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The overwhelming majority of scholarship on David Chariandy’s novel Soucouyant focuses on how Adele’s dementia represents the preservation of “cultural memory” and the perniciousness of “historical trauma.” However, by metaphorizing Adele’s mental condition, these critics risk treating her dementia as mostly figurative, and they thus elide a more detailed discussion of the literal ramifications of her dementia diagnosis. To move beyond these readings, then, my paper will approach Adele’s disorder as a literal medical condition and explore how her caregiving needs affect not only her but also those around her. Soucouyant subverts traditional caregiving narratives by depicting the difficult and typically invisible labour of informal caregiving that is undertaken by the families and friends of those who are ill or otherwise disabled. Because Adele’s family is unable to access proper public healthcare resources within the community, the burden of care falls upon the protagonist and his brother, who become “parentified children.” Parentified children, according to Nancy D. Chase, are “parents to their parents, and fulfill this role at the expense of their own developmentally appropriate needs and pursuits.” The novel provides a depiction of informal caregiving that is multi-faceted and asks us to question why is it exactly that we place the burden of care on those who are not equipped to handle such pressures instead of putting the onus on the government and the public healthcare system to take care of its most vulnerable members. Ageing Studies scholar Larry Polvika notes that although policymakers often offer “pious expressions of appreciation” and acknowledge that informal caregiving is “the backbone of our long-term care system,” governmental support for these caregivers remains inadequate. It is my belief that, by showcasing the struggles of informal caregivers, Chariandy’s text combats this dangerous and empty political rhetoric.

Keywords: caregiving, dementia, literature, parentified children

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Authors: Purba Biswas, Priyanka Dey

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Worldwide rapid urbanisation has accelerated city expansion in both developed and developing nations. This unprecedented urbanisation trend due to the increasing population and economic growth has caused challenges for the decision-makers in city planning and urban management. Metropolitan cities, class-I towns, and major urban centres undergo a continuous process of evolution due to interaction between socio-cultural and economic attributes. This constant evolution leads to urban expansion in all directions. Understanding the patterns and dynamics of urban built-up growth is crucial for policymakers, urban planners, and researchers, as it aids in resource management, decision-making, and the development of sustainable strategies to address the complexities associated with rapid urbanisation. Identifying spatio-temporal patterns of urban growth has emerged as a crucial challenge in monitoring and assessing present and future trends in urban development. Analysing urban growth patterns and tracking changes in land use is an important aspect of urban studies. This study analyses spatio-temporal urban transformations and land-use and land cover changes using remote sensing and GIS techniques. Built-up growth analysis has been done for the city of Surat as a case example, using the GIS tools of NDBI and GIS models of the Built-up Urban Density Index and Shannon Entropy Index to identify trends and the geographical direction of transformation from 2005 to 2020. Surat is one of the fastest-growing urban centres in both the state and the nation, ranking as the 4th fastest-growing city globally. This study analyses the dynamics of urban built-up area transformations both zone-wise and geographical direction-wise, in which their trend, rate, and magnitude were calculated for the period of 15 years. This study also highlights the need for analysing and monitoring the urban growth pattern of class-I cities in India using spatio-temporal and quantitative techniques like GIS for improved urban management.

Keywords: urban expansion, built-up, geographic information system, remote sensing, Shannon’s entropy

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Authors: Sehrish Ather

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Introduction: To improve organizational achievements through the production of new knowledge, health policy and system research is the basic requirement. An aging population is always the source of the increased burden of chronic diseases, disabilities, mental illnesses, and other co-morbidities; therefore the provision of quality health care services to every group of the population should be achieved by making strong policy and system research for the betterment of health care system. Unfortunately, the whole world is lacking policies and system research for providing health care to their elderly population. Materials and Methods: A literature review of published studies on aging diseases was done, ranging from the year 2011-2018. Geriatric, population, health policy, system, and research were the key terms used for the search. Databases searched were Google Scholar, PubMed, Science Direct, Ovid, and Research Gate. Grey literature was searched from various websites, including IHME, Library of the University of Lahore, World Health Organization (Ageing and Life Course), and Personal communication with Neuro-physicians. After careful reviewing published and un-published information, it was decided to carry on with commentary. Results and discussion: Most of the published studies have highlighted the need to advocate the funders of health policy and stakeholders of healthcare system research, and it was detected as a major issue, research on policy and healthcare system to provide health care to 'geriatric population' was found as highly neglected area. Conclusion: It is concluded that physicians are more involved with the policy and system research regarding any type of diseases, but scientists and researchers of basic and social science are less likely to be involved in methods used for health policy and system research due to lack of funding and resources. Therefore ageing diseases should be considered as a priority, and comprehensive policy and system research should be initiated for diseases of the geriatric population.

Keywords: geriatric population, health care system, health policy, system research

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Authors: Ione Loots, Marco van Dijk, Jay Bhagwan

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Historically, South Africa had various small-scale hydropower installations in remote areas that were not incorporated in the national electricity grid. Unfortunately, in the 1960s most of these plants were decommissioned when Eskom, the national power utility, rapidly expanded its grid and capability to produce cheap, reliable, coal-fired electricity. This situation persisted until 2008, when rolling power cuts started to affect all citizens. This, together with the rising monetary and environmental cost of coal-based power generation, has sparked new interest in small-scale hydropower development, especially in remote areas or at locations (like wastewater treatment works) that could not afford to be without electricity for long periods at a time. Even though South Africa does not have the same, large-scale, hydropower potential as some other African countries, significant potential for micro- and small-scale hydropower is hidden in various places. As an example, large quantities of raw and potable water are conveyed daily under either pressurized or gravity conditions over large distances and elevations. Due to the relative water scarcity in the country, South Africa also has more than 4900 registered dams of varying capacities. However, institutional capacity and skills have not been maintained in recent years and therefore the identification of hydropower potential, as well as the development of micro- and small-scale hydropower plants has not gained significant momentum. An assessment model and decision support system for low head hydropower development has been developed to assist designers and decision makers with first-order potential analysis. As a result, various potential sites were identified and many of these sites were situated at existing infrastructure like weirs, barrages or pipelines. One reason for the specific interest in existing infrastructure is the fact that capital expenditure could be minimized and another is the reduced negative environmental impact compared to greenfield sites. This paper will explore the case study of retrofitting an unconventional and innovative hydropower plant to the outlet of a wastewater treatment works in South Africa.

Keywords: low head hydropower, retrofitting, small-scale hydropower, wastewater treatment works

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Authors: Michelle Nighswander

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Suicide can be a tragic response to mental illness. It is difficult for people to disclose or discuss suicidal impulses. The stigma surrounding mental health can create a reluctance to seek help for mental illness. Patients may feel pressure to exhibit a socially desirable demeanor rather than reveal these issues, especially if they sense their healthcare provider is pressed for time or does not have an extensive history with their provider. Overcoming these barriers can be challenging. Although there are several validated depression and suicide risk instruments, varying processes used to administer these tools may impact the truthfulness of the responses. A literature review was conducted to find evidence of the impact of the environment on the accuracy of depression screening. Many investigations do not describe the environment and fewer studies use a comparison design. However, three studies demonstrated that computerized self-reporting might be more likely to elicit truthful and accurate responses due to increased privacy when responding compared to a face-to-face interview. These studies showed patients reported positive reactions to computerized screening for other stigmatizing health conditions such as alcohol use during pregnancy. Computerized self-screening for depression offers the possibility of more privacy and patient reflection, which could then send a targeted message of risk to the healthcare provider. This could potentially increase the accuracy while also increasing time efficiency for the clinic. Considering the persistent effects of mental health stigma, how these screening questions are posed can impact patients’ responses. This literature review analyzes trends in depression screening methodologies, the impact of setting on the results and how this may assist in overcoming one barrier caused by stigma.

Keywords: computerized self-report, depression, mental health stigma, suicide risk

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Authors: Anastasia Constantinou, Stephen Morris

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Background: The adoption of synchronous and asynchronous telemedicine modalities for primary care consultations has exponentially increased since the COVID-19 pandemic. However, there is limited understanding of how virtual consultations influence healthcare resource utilization and other quality measures including safety, timeliness, efficiency, patient and provider satisfaction, cost-effectiveness and environmental impact. Aim: Quantify the rate of follow-up visits, emergency department visits, hospitalizations, request for investigations and prescriptions and comment on the effect on different quality measures associated with different telemedicine modalities used for primary care services and primary care referrals to secondary care Design and setting: Systematic review in primary care Methods: A systematic search was carried out across three databases (Medline, PubMed and Scopus) between August and November 2023, using terms related to telemedicine, general practice, electronic referrals, follow-up, use and efficiency and supported by citation searching. This was followed by screening according to pre-defined criteria, data extraction and critical appraisal. Narrative synthesis and metanalysis of quantitative data was used to summarize findings. Results: The search identified 2230 studies; 50 studies are included in this review. There was a prevalence of asynchronous modalities in both primary care services (68%) and referrals from primary care to secondary care (83%), and most of the study participants were females (63.3%), with mean age of 48.2. The average follow-up for virtual consultations in primary care was 28.4% (eVisits: 36.8%, secure messages 18.7%, videoconference 23.5%) with no significant difference between them or F2F consultations. There was an average annual reduction of primary care visits by 0.09/patient, an increase in telephone visits by 0.20/patient, an increase in ED encounters by 0.011/patient, an increase in hospitalizations by 0.02/patient and an increase in out of hours visits by 0.019/patient. Laboratory testing was requested on average for 10.9% of telemedicine patients, imaging or procedures for 5.6% and prescriptions for 58.7% of patients. When looking at referrals to secondary care, on average 36.7% of virtual referrals required follow-up visit, with the average rate of follow-up for electronic referrals being higher than for videoconferencing (39.2% vs 23%, p=0.167). Technical failures were reported on average for 1.4% of virtual consultations to primary care. When using carbon footprint estimates, we calculate that the use of telemedicine in primary care services can potentially provide a net decrease in carbon footprint by 0.592kgCO2/patient/year. When follow-up rates are taken into account, we estimate that virtual consultations reduce carbon footprint for primary care services by 2.3 times, and for secondary care referrals by 2.2 times. No major concerns regarding quality of care, or patient satisfaction were identified. 5/7 studies that addressed cost-effectiveness, reported increased savings. Conclusions: Telemedicine provides quality, cost-effective, and environmentally sustainable care for patients in primary care with inconclusive evidence regarding the rates of subsequent healthcare utilization. The evidence is limited by heterogeneous, small-scale studies and lack of prospective comparative studies. Further research to identify the most appropriate telemedicine modality for different patient populations, clinical presentations, service provision (e.g. used to follow-up patients instead of initial diagnosis) as well as further education for patients and providers alike on how to make best use of this service is expected to improve outcomes and influence practice.

Keywords: telemedicine, healthcare utilisation, digital interventions, environmental impact, sustainable healthcare

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Authors: Mercy D. Chirwa, Juliet Nyasulu, Lebisti Modiba, Makombo Ganga-Limando

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Maternal death review is an initiative that provides a deeper understanding of the causes and circumstances sorounding of maternal deaths in Malawi and globally. Midwives are frontline members of the healthcare team and have stories about what pregnant women go through as such they are better placed to contribute to these reviews. Despite midwives’ participation as members of the facility-based maternal death review team, maternal deaths continues to occur. A lot has been documented around processes involved in maternal review, however, not much has been written around challenges experienced by midwives in maternal death review. This study explored the challenges faced by midwives in the implementation of maternal death reviews in the context of the healthcare system in Malawi. Methodology: This was a qualitative exploratory study design. Focus group discussions and individual face-to-face interviews were used to collect data in the study. A total of 40 midwives, who met the inclusion criteria, participated in the study. Data was analysed manually using a thematic content procedure. Findings: The four major challenges identified were: knowledge and skill gaps; lack of leadership and accountability; lack of institutional political will and inconsistency in conducting FBMDR, impeding midwives’ effective contribution to the implementation of maternal death review. The practical solutions and recommendations that emerged were: need-based knowledge and skills updates, supportive leadership, effective and efficient interdisciplinary work ethics, and sustained availability of material and human resources. Conclusion: Midwives have the highest potential to contribute to the reduction of maternal deaths. Practice development strategies are required to improve their practice in all the areas they are challenged with.

Keywords: facility-based maternal death review, maternal deaths, midwife, midwife challenges

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Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

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Authors: Sahar Heidary

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Radiography and radiotherapy have emerged as crucial pillars of modern medical practice, revolutionizing diagnostics and treatment for a myriad of health conditions. This abstract highlights the pivotal role of radiography and radiotherapy in favor of healthcare and society. Radiography, a non-invasive imaging technique, has significantly advanced medical diagnostics by enabling the visualization of internal structures and abnormalities within the human body. With the advent of digital radiography, clinicians can obtain high-resolution images promptly, leading to faster diagnoses and informed treatment decisions. Radiography plays a pivotal role in detecting fractures, tumors, infections, and various other conditions, allowing for timely interventions and improved patient outcomes. Moreover, its widespread accessibility and cost-effectiveness make it an indispensable tool in healthcare settings worldwide. On the other hand, radiotherapy, a branch of medical science that utilizes high-energy radiation, has become an integral component of cancer treatment and management. By precisely targeting and damaging cancerous cells, radiotherapy offers a potent strategy to control tumor growth and, in many cases, leads to cancer eradication. Additionally, radiotherapy is often used in combination with surgery and chemotherapy, providing a multifaceted approach to combat cancer comprehensively. The continuous advancements in radiotherapy techniques, such as intensity-modulated radiotherapy and stereotactic radiosurgery, have further improved treatment precision while minimizing damage to surrounding healthy tissues. Furthermore, radiography and radiotherapy have demonstrated their worth beyond oncology. Radiography is instrumental in guiding various medical procedures, including catheter placement, joint injections, and dental evaluations, reducing complications and enhancing procedural accuracy. On the other hand, radiotherapy finds applications in non-cancerous conditions like benign tumors, vascular malformations, and certain neurological disorders, offering therapeutic options for patients who may not benefit from traditional surgical interventions. In conclusion, radiography and radiotherapy stand as indispensable tools in modern medicine, driving transformative improvements in patient care and treatment outcomes. Their ability to diagnose, treat, and manage a wide array of medical conditions underscores their favor in medical practice. As technology continues to advance, radiography and radiotherapy will undoubtedly play an ever more significant role in shaping the future of healthcare, ultimately saving lives and enhancing the quality of life for countless individuals worldwide.

Keywords: radiology, radiotherapy, medical imaging, cancer treatment

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Authors: Nur A. Azmi, Suseela D. Chandran, Fadilah Puteh, Azizan Zainuddin

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Medical tourism has been associated as a global phenomenon in developed and developing countries in the 21st century. Medical tourism is defined as an activity in which individuals who travel from one country to another country to seek or receive medical healthcare. Based on the global trend, the number of medical tourists is increasing annually, especially in the Southeast Asia (SEA) region. Since the establishment of Association of Southeast Asian Nations (ASEAN) in 1967, the SEA nations have worked towards regional integration in medical tourism. The medical tourism in the SEA has become the third-largest sector that contributes towards economic development. Previous research has demonstrated several factors that affect the development of medical tourism. However, despite the already published literature on SEA's medical tourism in the last ten years there continues to be a scarcity of research on niche areas each of the SEA countries. Hence, this paper is significant in enriching the literature in the field of medical tourism particularly in showcasing the niche market of medical tourism among the SEA best players namely Singapore, Thailand, Malaysia and Indonesia. This paper also contributes in offering a comparative analysis between the said nations whether they are complementing or competing with each other in the medical tourism sector. This then, will increase the availability of information in SEA region on medical tourism. The data was collected through an in-depth interview with various stakeholders and private hospitals. The data was then analyzed using two approaches namely thematic analysis (interview data) and document analysis (secondary data). The paper concludes by arguing that the ASEAN countries have specific niche market to promote their medical tourism industry. This paper also concludes that these key nations complement each other in the industry. In addition, the medical tourism sector in SEA region offers greater prospects for market development and expansion that witnessed the emerging of new key players from other nations.

Keywords: healthcare services, medical tourism, medical tourists, SEA region, comparative analysis

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Authors: Qurratulain Faheem

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The human body often serves as a reference point to analyse the notions of self and society. Situating on Merleau-Ponty and Bourdieu theories of embodiments, this research explores the notions around the human body and its influence on the ethical considerations in regards to organ transplantation among the Muslim communities in Pakistan. The context of Pakistan makes an intriguing case study as cadaveric organ transplantation is not in practise. Whereas living organ transplantation is commonly is practised between family membersonly. These contradictory practices apparently rests on the ideologies around the human body and religious beliefs as well the personal judgements and authority of healthcare professionals. This research is a year-long ethnographic study carried out as part of doctoral studies. An anthropological approach towards organ transplantation in Pakistan brought forward various socio-cultural notions around the human body and selfhood that serve as a framework around biomedical ethical issues in various societies. Further, it surface the contradictions and issues associated with organ transplantation that makes it a dilemma situated in a nexus of various socio-cultural and political factors rather seeing it as an isolated health concern. This research is a novel study on the subject of organ transplantation in the context of Pakistan but also put forward ethnographic data that could serve as a reference in other religious societies. Further, the ethnographic data bring forward experiences and stories of organ receivers, organ donors, religious leaders, healthcare professionals, and the general public, which aspire to encourage biomedical ethicists and social-scientists to consider ethnography as a research methodology and rely upon people’s lived experiences while establishing policies and practices around biomedical ethical issues.

Keywords: organ transplantation, ethics, pakistan, gender, islam, muslims, living organ donation

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Authors: Rajapaksha J. S. R. L., Rajapaksha R. G. D. T., Ranawaka A. U. R., Rangalla R. D. M. P., Ranwala R. D. E. B., Chandratilake M. N.

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Introduction: Lesbian, gay, bisexual, and transgender (LGBT) patients experience discrimination, insensitivity, and ignorance about LGBT-specific health needs among healthcare providers. Developing the correct attitudes among medical students towards LGBT may help provide them with optimal healthcare. Objectives: This study aimed at assessing the attitudes of medical students towards the LBGT community. Methodology: A cross-sectional descriptive study was among all the medical students in the Faculty of Medicine, University of Kelaniya, Sri Lanka, using a validated online questionnaire. The questionnaire focused on eight areas. The data were descriptively analyzed, and the demographic groups were compared. Results: 358 students completed the survey. The response rate was 34.26%. Their attitudes on traditional gender roles and comfortability in interacting with LGBT people were moderate, and they disagreed with negative LGBT social beliefs. They knew less about the origin of sexuality/gender of LGBT. Although they accepted LGBT as a part of diversity, they discouraged normalizing the social practices of LGBT people. Their acceptance and association of LGBT were moderately positive. A minority has encountered LGBT in close social circles, and the majority of them were batch-mates. Although males’ knowledge about the origin of LGBT was higher, they favoured traditional gender roles more. The religious groups showed no differences. The favourability of attitudes towards LGBT reflected respondents’ political ideology. Conclusion: Although medical students’ knowledge on the sexuality/gender basis of LGBT is poor, they have moderately favourable attitudes towards them. They accept LGBT as a part of social diversity but not their social practices. Poor knowledge, lack of encounters, cultural influences, and political ideology may have influenced their attitudes.

Keywords: medical students, attitude, LGBT, diversity

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Authors: Aymen Bouzid, Jihen Ben Smida

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In this paper, we propose to prove the importance of the application of blind source separation methods on remote sensing data in order to index multispectral images. The proposed method starts with Gabor Filtering and the application of a Blind Source Separation to get a more effective representation of the information contained on the observation images. After that, a feature vector is extracted from each image in order to index them. Experimental results show the superior performance of this approach.

Keywords: blind source separation, content based image retrieval, feature extraction multispectral, satellite images

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Authors: Mirim Kim, Won-Oak Oh

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Purpose: The purpose of this study was to identify hospitalized children's fall risk factors, fall prevention status and fall prevention strategies recognized by nurses and caregivers of hospitalized children and present an ecological model for fall preventive management in hospitalized children. Method: The participants of this study were 14 nurses working in medical institutions and having more than one year of child care experience and 14 adult caregivers of children under 6 years of age receiving inpatient treatment at a medical institution. One to one interview was attempted to identify their perception of fall preventive management. Transcribed data were analyzed through latent content analysis method. Results: Fall risk factors in hospitalized children were 'unpredictable behavior', 'instability', 'lack of awareness about danger', 'lack of awareness about falls', 'lack of child control ability', 'lack of awareness about the importance of fall prevention', 'lack of sensitivity to children', 'untidy environment around children', 'lack of personalized facilities for children', 'unsafe facility', 'lack of partnership between healthcare provider and caregiver', 'lack of human resources', 'inadequate fall prevention policy', 'lack of promotion about fall prevention', 'a performanceism oriented culture'. Fall preventive management status of hospitalized children were 'absence of fall prevention capability', 'efforts not to fall', 'blocking fall risk situation', 'limit the scope of children's activity when there is no caregiver', 'encourage caregivers' fall prevention activities', 'creating a safe environment surrounding hospitalized children', 'special management for fall high risk children', 'mutual cooperation between healthcare providers and caregivers', 'implementation of fall prevention policy', 'providing guide signs about fall risk'. Fall preventive management strategies of hospitalized children were 'restrain dangerous behavior', 'inspiring awareness about fall', 'providing fall preventive education considering the child's eye level', 'efforts to become an active subject of fall prevention activities', 'providing customed fall prevention education', 'open communication between healthcare providers and caregivers', 'infrastructure and personnel management to create safe hospital environment', 'expansion fall prevention campaign', 'development and application of a valid fall assessment instrument', 'conversion of awareness about safety'. Conclusion: In this study, the ecological model of fall preventive management for hospitalized children reflects various factors that directly or indirectly affect the fall prevention of hospitalized children. Therefore, these results can be considered as useful baseline data for developing systematic fall prevention programs and hospital policies to prevent fall accident in hospitalized children. Funding: This study was funded by the National Research Foundation of South Korea (grant number NRF-2016R1A2B1015455).

Keywords: fall down, safety culture, hospitalized children, risk factors

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Authors: Panos Xenos, Milton Nektarios, John Yfantopoulos

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Background: Policy makers, professional organizations and payers have introduced a variety of initiatives and reforms for the health systems worldwide, aimed at improving hospital efficiency. Their efforts are concentrated in two main categories: to constrain increasing healthcare costs and to enhance quality of services provided. Research Objectives: This study examines the efficiency of 112 Greek public hospitals for the year 2009, evaluates the importance of bootstrapping techniques and investigates the effect of contextual factors on hospital efficiency. Furthermore, the effect of qualitative evidence, on hospital efficiency is explored using data from 28 large hospitals. Methods: We applied Data Envelopment Analysis, augmented by bootstrapping techniques, to estimate efficiency scores. In order to measure the effect of environmental factors on hospital efficiency we used Tobit regression analysis. The significance of our models is evaluated using statistical tests to compare distributions. Results: The Kolmogorov-Smirnov test between the original and the bootstrap-corrected efficiency indicates that their distributions are significantly different (p-value<0.01). The environmental factors, that seem to influence efficiency, are Occupancy Rating and the ratio between Outpatient Visits and Inpatient Days. Results indicate that the inclusion of the quality variable in DEA modelling generates statistically significant variations in efficiency scores (p-value<0.05). Conclusions: The inclusion of quality variables and the use of bootstrap resampling in efficiency analysis impose a statistically significant effect on the distribution of efficiency scores. As a policy conclusion we highlight the importance of these methods on hospital efficiency analysis and, by implication, on healthcare resource allocation.

Keywords: hospitals, efficiency, quality, data envelopment analysis, Greek public hospital sector

Procedia PDF Downloads 297

Authors: Neda Orak, Mostafa Zarei

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Environmental assessment is an important session in environment management. Since various methods and techniques have been produces and implemented. Remote sensing (RS) is widely used in many scientific and research fields such as geology, cartography, geography, agriculture, forestry, land use planning, environment, etc. It can show earth surface objects cyclical changes. Also, it can show earth phenomena limits on basis of electromagnetic reflectance changes and deviations records. The research has been done on mangrove forests assessment by RS techniques. Mangrove forests quantitative analysis in Basatin and Bidkhoon estuaries was the aim of this research. It has been done by Landsat satellite images from 1975- 2013 and match to ground control points. This part of mangroves are the last distribution in northern hemisphere. It can provide a good background to improve better management on this important ecosystem. Landsat has provided valuable images to earth changes detection to researchers. This research has used MSS, TM, +ETM, OLI sensors from 1975, 1990, 2000, 2003-2013. Changes had been studied after essential corrections such as fix errors, bands combination, georeferencing on 2012 images as basic image, by maximum likelihood and IPVI Index. It was done by supervised classification. 2004 google earth image and ground points by GPS (2010-2012) was used to compare satellite images obtained changes. Results showed mangrove area in bidkhoon was 1119072 m2 by GPS and 1231200 m2 by maximum likelihood supervised classification and 1317600 m2 by IPVI in 2012. Basatin areas is respectively: 466644 m2, 88200 m2, 63000 m2. Final results show forests have been declined naturally. It is due to human activities in Basatin. The defect was offset by planting in many years. Although the trend has been declining in recent years again. So, it mentioned satellite images have high ability to estimation all environmental processes. This research showed high correlation between images and indexes such as IPVI and NDVI with ground control points.

Keywords: IPVI index, Landsat sensor, maximum likelihood supervised classification, Nayband National Park

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Authors: Hemant Kumar, Nilendu Das

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A study based on ANN structure gives us the information to predict the size of the future in realizing a past event. ANN, IMD (Indian meteorological department) data and remote sensing were used to enable a number of parameters for calculating the size that may occur in the future. A threshold selected specifically above the high-frequency harvest reached the area during the selected seismic activity. In the field of human and local biodiversity it remains to obtain the right parameter compared to the frequency of impact. But during the study the assumption is that predicting seismic activity is a difficult process, not because of the parameters involved here, which can be analyzed and funded in research activity.

Keywords: ANN, Bayesion class, earthquakes, IMD

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Authors: E. Tuğba Topçu, Ebru E. Kazan, Erhan Büken

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Emergency nurses are the first health care professional to generally observe the patients, communicate patients’ family or relatives, touch the properties of patients and contact to laboratory sample of patients. Also, they are the encounter incidents related crime, people who engage in violence or suspicious injuries frequently. So, documentation of patients’ condition came to the hospital and conservation of evidence are important in the inquiry of forensic medicine. The aim of the study was to determine the knowledge level of healthcare professional working at the emergency services regarding their approaches to common forensic cases. The study was comprised of 404 healthcare professional working (nurse, emergency medicine technician, health officer) at the emergency services of 6 state hospitals, 6 training and 6 research hospitals and 3 university hospitals in Ankara. Data was collected using questionnaire form which was developed by researches in the direction of literature. Questionnaire form is comprised of two sections. The first section includes 17 questions related demographic information about health care professional and 4 questions related Turkish laws. The second section includes 43 questions to the determination of knowledge level of health care professional’s working in the emergency department, about approaches to frequently encountered forensic cases. For the data evaluation of the study; Mann Whitney U test, Bonferroni correction Kruskal Wallis H test and Chi Square tests have been used. According to study, it’s said that there is no forensic medicine expert in the foundation by 73.4% of health care professionals. Two third (66%) of participants’ in emergency department reported daily average 7 or above forensic cases applied to the emergency department and 52.1% of participants did not evaluate incidents came to the emergency department as a forensic case. Most of the participants informed 'duty of preservation of evidence' is health care professionals duty related forensic cases. In result, we determinated that knowledge level of health care professional working in the emergency department, about approaches to frequently encountered forensic cases, is not the expected level. Because we found that most of them haven't received education about forensic nursing.Postgraduates participants, educated health professional about forensic nursing, staff who applied to sources about forensic nursing and staff who evaluated emergency department cases as forensic cases have significantly higher level of knowledge. Moreover, it’s found that forensic cases diagnosis score is the highest in health officer and university graduated. Health care professional’s deficiency in knowledge about forensic cases can cause defects in operation of the forensic process because of mistakes in collecting and conserving of evidence. It is obvious that training about the approach to forensic nursing should be arranged.

Keywords: emergency nurses, forensic case, forensic nursing, level of knowledge

Procedia PDF Downloads 284

Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

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Authors: Diana F. Lopes, Jorge Simoes, José Martins, Eduardo Castro

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Health professionals are the keystone of any health system, by delivering health services to the population. Given the time and cost involved in training new health professionals, the planning process of the health workforce is particularly important as it ensures a proper balance between the supply and demand of these professionals and it plays a central role on the Health 2020 policy. In the past 40 years, the planning of the health workforce in Portugal has been conducted in a reactive way lacking a prospective vision based on an integrated, comprehensive and valid analysis. This situation may compromise not only the productivity and the overall socio-economic development but the quality of the healthcare services delivered to patients. This is even more critical given the expected shortage of the health workforce in the future. Furthermore, Portugal is facing an aging context of some professional classes (physicians and nurses). In 2015, 54% of physicians in Portugal were over 50 years old, and 30% of all members were over 60 years old. This phenomenon associated to an increasing emigration of young health professionals and a change in the citizens’ illness profiles and expectations must be considered when planning resources in healthcare. The perspective of sudden retirement of large groups of professionals in a short time is also a major problem to address. Another challenge to embrace is the health workforce imbalances, in which Portugal has one of the lowest nurse to physician ratio, 1.5, below the European Region and the OECD averages (2.2 and 2.8, respectively). Within the scope of the HEALTH 2040 project – which aims to estimate the ‘Future needs of human health resources in Portugal till 2040’ – the present study intends to get a comprehensive dynamic approach of the problem, by (i) estimating the needs of physicians and nurses in Portugal, by specialties and by quinquenium till 2040; (ii) identifying the training needs of physicians and nurses, in medium and long term, till 2040, and (iii) estimating the number of students that must be admitted into medicine and nursing training systems, each year, considering the different categories of specialties. The development of such approach is significantly more critical in the context of limited budget resources and changing health care needs. In this context, this study presents the drivers of the healthcare needs’ evolution (such as the demographic and technological evolution, the future expectations of the users of the health systems) and it proposes a Bayesian methodology, combining the best available data with experts opinion, to model such evolution. Preliminary results considering different plausible scenarios are presented. The proposed methodology will be integrated in a user-friendly decision support system so it can be used by politicians, with the potential to measure the impact of health policies, both at the regional and the national level.

Keywords: bayesian estimation, health economics, health workforce planning, human health resources planning

Procedia PDF Downloads 244