Search results for: healthcare organisation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1842

Search results for: healthcare organisation

732 Application of Deep Neural Networks to Assess Corporate Credit Rating

Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

Abstract:

In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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731 Clique and Clan Analysis of Patient-Sharing Physician Collaborations

Authors: Shahadat Uddin, Md Ekramul Hossain, Arif Khan

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The collaboration among physicians during episodes of care for a hospitalised patient has a significant contribution towards effective health outcome. This research aims at improving this health outcome by analysing the attributes of patient-sharing physician collaboration network (PCN) on hospital data. To accomplish this goal, we present a research framework that explores the impact of several types of attributes (such as clique and clan) of PCN on hospitalisation cost and hospital length of stay. We use electronic health insurance claim dataset to construct and explore PCNs. Each PCN is categorised as ‘low’ and ‘high’ in terms of hospitalisation cost and length of stay. The results from the proposed model show that the clique and clan of PCNs affect the hospitalisation cost and length of stay. The clique and clan of PCNs show the difference between ‘low’ and ‘high’ PCNs in terms of hospitalisation cost and length of stay. The findings and insights from this research can potentially help the healthcare stakeholders to better formulate the policy in order to improve quality of care while reducing cost.

Keywords: clique, clan, electronic health records, physician collaboration

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730 An Assessment of Involuntary Migration in India: Understanding Issues and Challenges

Authors: Rajni Singh, Rakesh Mishra, Mukunda Upadhyay

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India is among the nations born out of partition that led to one of the greatest forced migrations that marked the past century. The Indian subcontinent got partitioned into two nation-states, namely India and Pakistan. This led to an unexampled mass displacement of people accounting for about 20 million in the subcontinent as a whole. This exemplifies the socio-political version of displacement, but there are other identified reasons leading to human displacement viz., natural calamities, development projects and people-trafficking and smuggling. Although forced migrations are rare in incidence, they are mostly region-specific and a very less percentage of population appears to be affected by it. However, when this percentage is transcripted in terms of volume, the real impact created by such migration can be realized. Forced migration is thus an issue related to the lives of many people and requires to be addressed with proper intervention. Forced or involuntary migration decimates peoples' assets while taking from them their most basic resources and makes them migrate without planning and intention. This in most cases proves to be a burden on the destination resources. Thus, the question related to their security concerns arise profoundly with regard to the protection and safeguards to these migrants who need help at the place of destination. This brings the human security dimension of forced migration into picture. The present study is an analysis of a sample of 1501 persons by NSSO in India (National Sample Survey Organisation), which identifies three reasons for forced migration- natural disaster, social/political problem and displacement by development projects. It was observed that, of the total forced migrants, about 4/5th comprised of the internally displaced persons. However, there was a huge inflow of such migrants to the country from across the borders also, the major contributing countries being Bangladesh, Pakistan, Sri Lanka, Gulf countries and Nepal. Among the three reasons for involuntary migration, social and political problem is the most prominent in displacing huge masses of population; it is also the reason where the share of international migrants to that of internally displaced is higher compared to the other two factors /reasons. Second to political and social problems, natural calamities displaced a high portion of the involuntary migrants. The present paper examines the factors which increase people's vulnerability to forced migration. On perusing the background characteristics of the migrants it was seen that those who were economically weak and socially fragile are more susceptible to migration. Therefore, getting an insight about this fragile group of society is required so that government policies can benefit these in the most efficient and targeted manner.

Keywords: involuntary migration, displacement, natural disaster, social and political problem

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729 Predicting the Relationship Between the Corona Virus Anxiety and Psychological Hardiness in Staff Working at Hospital in Shiraz Iran

Authors: Gholam Reza Mirzaei, Mehran Roost

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This research was conducted with the aim of predicting the relationship between coronavirus anxiety and psychological hardiness in employees working at Shahid Beheshti Hospital in Shiraz. The current research design was descriptive and correlational. The statistical population of the research consisted of all the employees of Shahid Beheshti Hospital in Shiraz in 2021. From among the statistical population, 220 individuals were selected and studied based on available sampling. To collect data, Kobasa's psychological hardiness questionnaire and coronavirus anxiety questionnaire were used. After collecting the data, the scores of the participants were analyzed using Pearson's correlation coefficient multiple regression analysis and SPSS-24 statistical software. The results of Pearson's correlation coefficient showed that there is a significant negative correlation between psychological hardiness and its components (challenge, commitment, and control) with coronavirus anxiety; also, psychological hardiness with a beta coefficient of 0.20 could predict coronavirus anxiety in hospital employees. Based on the results, plans can be made to enhance psychological hardiness through educational workshops to relieve the anxiety of the healthcare staff.

Keywords: the corona virus, commitment, hospital employees, psychological hardiness

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728 Leveraging Li-Fi to Enhance Security and Performance of Medical Devices

Authors: Trevor Kroeger, Hayden Williams, Edward Holzinger, David Coleman, Brian Haberman

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The network connectivity of medical devices is increasing at a rapid rate. Many medical devices, such as vital sign monitors, share information via wireless or wired connections. However, these connectivity options suffer from a variety of well-known limitations. Wireless connectivity, especially in the unlicensed radio frequency bands, can be disrupted. Such disruption could be due to benign reasons, such as a crowded spectrum, or to malicious intent. While wired connections are less susceptible to interference, they inhibit the mobility of the medical devices, which could be critical in a variety of scenarios. This work explores the application of Light Fidelity (Li-Fi) communication to enhance the security, performance, and mobility of medical devices in connected healthcare scenarios. A simple bridge for connected devices serves as an avenue to connect traditional medical devices to the Li-Fi network. This bridge was utilized to conduct bandwidth tests on a small Li-Fi network installed into a Mock-ICU setting with a backend enterprise network similar to that of a hospital. Mobile and stationary tests were conducted to replicate various different situations that might occur within a hospital setting. Results show that in room Li-Fi connectivity provides reasonable bandwidth and latency within a hospital like setting.

Keywords: hospital, light fidelity, Li-Fi, medical devices, security

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727 The Effect of Perceived Organizational Support and Leader Member Exchange on Turnover Intention: A Field Study in the Healthcare Industry

Authors: Mehtap Öztürk, Adem Öğüt, Emine Öğüt

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Leader member exchange is considered as relationship-based approach to leadership. The focal point of this theory is that effective leadership processes occur when leaders and followers are able to develop mature leadership relationships and thus gain access to a variety of benefits these relationships bring. In this context, it can be claimed that the quality of leader member exchange appears to have a strong affect on perceived organizational support and reduce turnover intention. The purpose of this study is to determine the relationship between the levels of leader member exchange, perceived organizational support and turnover intention on the employees of a health institution operating in the province of Konya. A field study based on survey method on 134 physicians who are employees of a health institution operating in the mentioned sample. In accordance with this purpose, it has been observed that there is a negative and statistically significant relationship between leader member exchange and turnover intention. Furthermore, it has been also realized that there is a negative and statistically significant relationship between perceived organizational support and turnover intention.

Keywords: leader member exchange, perceived organizational support, social exchange theory, turnover intention

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726 The Systematic Impact of Climatic Disasters on the Maternal Health in Pakistan

Authors: Yiqi Zhu, Jean Francois Trani, Rameez Ulhassan

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Extreme weather phenomena increased by 46% between 2007 and 2017 and have become more intense with the rise in global average temperatures. This increased intensity of climate variations often induces humanitarian crises and particularly affects vulnerable populations in low- and middle-income countries (LMICs). Expectant and lactating mothers are among the most vulnerable groups. Pakistan ranks 10th among the most affected countries by climate disasters. In 2022, monsoon floods submerged a third of the country, causing the loss of 1,500 lives. Approximately 650,000 expectant and lactating mothers faced systematic stress from climatic disasters. Our study used participatory methods to investigate the systematic impact of climatic disasters on maternal health. In March 2023, we conducted six Group Model Building (GMB) workshops with healthcare workers, fathers, and mothers separately in two of the most affected areas in Pakistan. This study was approved by the Islamic Relief Research Review Board. GMB workshops consist of three sessions. In the first session, participants discussed the factors that impact maternal health. After identifying the factors, they discussed the connections among them and explored the system structures that collectively impact maternal health. Based on the discussion, a causal loop diagram (CLD) was created. Finally, participants discussed action ideas that could improve the system to enhance maternal health. Based on our discussions and the causal loop diagram, we identified interconnected factors at the family, community, and policy levels. Mothers and children are directly impacted by three interrelated factors: food insecurity, unstable housing, and lack of income. These factors create a reinforcing cycle that negatively affects both mothers and newborns. After the flood, many mothers were unable to produce sufficient breastmilk due to their health status. Without breastmilk and sufficient food for complementary feeding, babies tend to get sick in damp and unhygienic environments resulting from temporary or unstable housing. When parents take care of sick children, they miss out on income-generating opportunities. At the community level, the lack of access to clean water and sanitation (WASH) and maternal healthcare further worsens the situation. Structural failures such as a lack of safety nets and programs associated with flood preparedness make families increasingly vulnerable with each disaster. Several families reported that they had not fully recovered from a flood that occurred ten years ago, and this latest disaster destroyed their lives again. Although over twenty non-profit organizations are working in these villages, few of them provide sustainable support. Therefore, participants called for systemic changes in response to the increasing frequency of climate disasters. The study reveals the systematic vulnerabilities of mothers and children after climatic disasters. The most vulnerable populations are often affected the most by climate change. Collaborative efforts are required to improve water and forest management, strengthen public infrastructure, increase access to WASH, and gradually build climate-resilient communities. Governments, non-governmental organizations, and the community should work together to develop and implement effective strategies to prevent, mitigate, and adapt to climate change and its impacts.

Keywords: climatic disasters, maternal health, Pakistan, systematic impact, flood, disaster relief.

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725 Managing the Magnetic Protection of Workers in Magnetic Resonance Imaging

Authors: Safoin Aktaou, Aya Al Masri, Kamel Guerchouche, Malorie Martin, Fouad Maaloul

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Introduction: In the ‘Magnetic Resonance Imaging (MRI)’ department, all workers involved in preparing the patient, setting it up, tunnel cleaning, etc. are likely to be exposed to ‘ElectroMagnetic fields (EMF)’ emitted by the MRI device. Exposure to EMF can cause adverse radio-biological effects to workers. The purpose of this study is to propose an organizational process to manage and control EMF risks. Materials and methods: The study was conducted at seven MRI departments using machines with 1.5 and 3 Tesla magnetic fields. We assessed the exposure of each one by measuring the two electromagnetic fields (static and dynamic) at different distances from the MRI machine both inside and around the examination room. Measurement values were compared with British and American references (those of the UK's ‘Medicines and Healthcare Regulatory Agency (MHRA)’ and the ‘American Radiology Society (ACR)’). Results: Following the results of EMF measurements and their comparison with the recommendations of learned societies, a zoning system that adapts to needs of different MRI services across the country has been proposed. In effect, three risk areas have been identified within the MRI services. This has led to the development of a good practice guide related to the magnetic protection of MRI workers. Conclusion: The guide established by our study is a standard that allows MRI workers to protect themselves against the risk of electromagnetic fields.

Keywords: comparison with international references, measurement of electromagnetic fields, magnetic protection of workers, magnetic resonance imaging

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724 Exposing the Concealed Impact: Evaluating the Role of Development Projects on Corruption Perception in Afghanistan

Authors: Jawad Taheri

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This paper investigates the impact of foreign aid-funded development projects on corruption perception in Afghanistan, utilizing instrumental variable (IV) approaches in regression analysis setting. Seven sub-categories of development projects are examined in order to have a glance over comparative usefulness of each project. The study incorporates natural disaster indicators as exogenous variables to mitigate endogeneity concerns and control variables. The findings reveal significant associations between certain types of projects and corruption perception. Road and bridge construction, irrigation, and agriculture projects are found to decrease corruption perception, fostering optimism and trust within affected communities. Mosque construction and healthcare initiatives aligned with religious beliefs also contribute to reduced corruption perception. However, drinking water projects are associated with increased corruption perception, highlighting potential challenges in their implementation. The study emphasizes the importance of well-implemented projects, cultural contexts, and effective governance in mitigating corruption and fostering trust within communities. These findings contribute to a refined understanding of the relationship between development projects and corruption perception in Afghanistan.

Keywords: foreign aid, development projects, corruption perception, Afghanistan, instrumental variable analysis, survey of Afghan people (SAP), natural disasters, exogenous variation

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723 Adaptive Swarm Balancing Algorithms for Rare-Event Prediction in Imbalanced Healthcare Data

Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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722 A PROMETHEE-BELIEF Approach for Multi-Criteria Decision Making Problems with Incomplete Information

Authors: H. Moalla, A. Frikha

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Multi-criteria decision aid methods consider decision problems where numerous alternatives are evaluated on several criteria. These methods are used to deal with perfect information. However, in practice, it is obvious that this information requirement is too much strict. In fact, the imperfect data provided by more or less reliable decision makers usually affect decision results since any decision is closely linked to the quality and availability of information. In this paper, a PROMETHEE-BELIEF approach is proposed to help multi-criteria decisions based on incomplete information. This approach solves problems with incomplete decision matrix and unknown weights within PROMETHEE method. On the base of belief function theory, our approach first determines the distributions of belief masses based on PROMETHEE’s net flows and then calculates weights. Subsequently, it aggregates the distribution masses associated to each criterion using Murphy’s modified combination rule in order to infer a global belief structure. The final action ranking is obtained via pignistic probability transformation. A case study of real-world application concerning the location of a waste treatment center from healthcare activities with infectious risk in the center of Tunisia is studied to illustrate the detailed process of the BELIEF-PROMETHEE approach.

Keywords: belief function theory, incomplete information, multiple criteria analysis, PROMETHEE method

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721 Automated Classification of Hypoxia from Fetal Heart Rate Using Advanced Data Models of Intrapartum Cardiotocography

Authors: Malarvizhi Selvaraj, Paul Fergus, Andy Shaw

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Uterine contractions produced during labour have the potential to damage the foetus by diminishing the maternal blood flow to the placenta. In order to observe this phenomenon labour and delivery are routinely monitored using cardiotocography monitors. An obstetrician usually makes the diagnosis of foetus hypoxia by interpreting cardiotocography recordings. However, cardiotocography capture and interpretation is time-consuming and subjective, often lead to misclassification that causes damage to the foetus and unnecessary caesarean section. Both of these have a high impact on the foetus and the cost to the national healthcare services. Automatic detection of foetal heart rate may be an objective solution to help to reduce unnecessary medical interventions, as reported in several studies. This paper aim is to provide a system for better identification and interpretation of abnormalities of the fetal heart rate using RStudio. An open dataset of 552 Intrapartum recordings has been filtered with 0.034 Hz filters in an attempt to remove noise while keeping as much of the discriminative data as possible. Features were chosen following an extensive literature review, which concluded with FIGO features such as acceleration, deceleration, mean, variance and standard derivation. The five features were extracted from 552 recordings. Using these features, recordings will be classified either normal or abnormal. If the recording is abnormal, it has got more chances of hypoxia.

Keywords: cardiotocography, foetus, intrapartum, hypoxia

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720 The Resource-Base View of Organization and Innovation: Recognition of Significant Relationship in an Organization

Authors: Francis Deinmodei W. Poazi, Jasmine O. Tamunosiki-Amadi, Maurice Fems

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In recent times the resource-based view (RBV) of strategic management has recorded a sizeable attention yet there has not been a considerable scholarly and managerial discourse, debate and attention. As a result, this paper gives special bit of critical reasoning as well as top-notch analyses and relationship between RBV and organizational innovation. The study examines those salient aspects of RBV that basically have the will power in ensuring the organization's capacity to go for innovative capability. In achieving such fit and standpoint, the paper joins other relevant academic discourse and empirical evidence. To this end, a reasonable amount of contributions in setting the ground running for future empirical researches would have been provided. More so, the study is guided and built on the following strength and significance: Firstly, RBV sees resources as heterogeneity which forms a strong point of strength and allows organisations to gain competitive advantage. In order words, competitive advantage can be achieved or delivered to the organization when resources are distinctively utilized in a valuable manner more than the envisaged competitors of the organization. Secondly, RBV is significantly influential in determining the real resources that are available in the organization with a view to locate capabilities within in order to attract more profitability into the organization when applied. Thus, there will be more sustainable growth and success in the ever competitive and emerging market. Thus, to have succinct description of the basic methodologies, the study adopts both qualitative as well as quantitative approach with a view to have a broad samples of opinion in establishing and identifying key and strategic organizational resources to enable managers of resources to gain a competitive advantage as well as generating a sustainable increase and growth in profit. Furthermore, a comparative approach and analysis was used to examine the performance of RBV within the organization. Thus, the following are some of the findings of the study: it is clear that there is a nexus between RBV and growth of competitively viable organizations. More so, in most parts, organizations have heterogeneous resources domiciled in their organizations but not all organizations as it was specifically and intelligently adopting the tenets of RBV to strengthen heterogeneity of resources which allows organisations to gain competitive advantage. Other findings of this study reveal that of managerial perception of RBV with respect to application and transformation of resources to achieve a profitable end. It is against this backdrop, the importance of RBV cannot be overemphasized; the study is strongly convinced and think that RBV view is one focal and distinct approach that is focused on internal to outside strategy which engenders sourcing or generating resources internally as well as having the quest to apply such internally sourced resources diligently to increase or gain competitive advantage.

Keywords: resource-based view, innovation, organisation, recognition significant relationship and theoretical perspective

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719 Preparedness Level of Disaster Management Institutions in Context of Floods in Delhi

Authors: Aditi Madan, Jayant Kumar Routray

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Purpose: Over the years flood related risks have compounded due to increasing vulnerability caused by rapid urbanisation and growing population. This increase is an indication of the need for enhancing the preparedness of institutions to respond to floods. The study describes disaster management structure and its linkages with institutions involved in managing disasters. It addresses issues and challenges associated with readiness of disaster management institutions to respond to floods. It suggests policy options for enhancing the current state of readiness of institutions to respond by considering factors like institutional, manpower, financial, technical, leadership & networking, training and awareness programs, monitoring and evaluation. Methodology: The study is based on qualitative data with statements and outputs from primary and secondary sources to understand the institutional framework for disaster management in India. Primary data included field visits, interviews with officials from institutions managing disasters and the affected community to identify the challenges faced in engaging national, state, district and local level institutions in managing disasters. For focus group discussions, meetings were held with district project officers and coordinators, local officials, community based organisation, civil defence volunteers and community heads. These discussions were held to identify the challenges associated with preparedness to respond of institutions to floods. Findings: Results show that disasters are handled by district authority and the role of local institutions is limited to a reactive role during disaster. Data also indicates that although the existing institutional setup is well coordinated at the district level but needs improvement at the local level. Wide variations exist in awareness and perception among the officials engaged in managing disasters. Additionally, their roles and responsibilities need to be clearly defined with adequate budget and dedicated permanent staff for managing disasters. Institutions need to utilise the existing manpower through proper delegation of work. Originality: The study suggests that disaster risk reduction needs to focus more towards inclusivity of the local urban bodies. Wide variations exist in awareness and perception among the officials engaged in managing disasters. In order to ensure community participation, it is important to address their social and economic problems since such issues can overshadow attempts made for reducing risks. Thus, this paper suggests development of direct linkages among institutions and community for enhancing preparedness to respond to floods.

Keywords: preparedness, response, disaster, flood, community, institution

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718 Human Digital Twin for Personal Conversation Automation Using Supervised Machine Learning Approaches

Authors: Aya Salama

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Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

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717 Evaluation of the Hepatitis C Virus and Classical and Modern Immunoassays Used Nowadays to Diagnose It in Tirana

Authors: Stela Papa, Klementina Puto, Migena Pllaha

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HCV is a hepatotropic RNA virus, transmitted primarily via the blood route, which causes progressive disease such as chronic hepatitis, liver cirrhosis, or hepatocellular carcinoma. HCV nowadays is a global healthcare problem. A variety of immunoassays including old and new technologies are being applied to detect HCV in our country. These methods include Immunochromatography assays (ICA), Fluorescence immunoassay (FIA), Enzyme linked fluorescent assay (ELFA), and Enzyme linked immunosorbent assay (ELISA) to detect HCV antibodies in blood serum, which lately is being slowly replaced by more sensitive methods such as rapid automated analyzer chemiluminescence immunoassay (CLIA). The aim of this study is to estimate HCV infection in carriers and chronic acute patients and to evaluate the use of new diagnostic methods. This study was realized from September 2016 to May 2018. During this study period, 2913 patients were analyzed for the presence of HCV by taking samples from their blood serum. The immunoassays performed were ICA, FIA, ELFA, ELISA, and CLIA assays. Concluding, 82% of patients taken in this study, resulted infected with HCV. Diagnostic methods in clinical laboratories are crucial in the early stages of infection, in the management of chronic hepatitis and in the treatment of patients during their disease.

Keywords: CLIA, ELISA, Hepatitis C virus, immunoassay

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716 ‘BEST BARK’ Dog Care and Owner Consultation System

Authors: Shalitha Jayasekara, Saluk Bawantha, Dinithi Anupama, Isuru Gunarathne, Pradeepa Bandara, Hansi De Silva

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Dogs have been known as "man's best friend" for generations, providing friendship and loyalty to their human counterparts. However, due to people's busy lives, they are unaware of the ailments that can affect their pets. However, in recent years, mobile technologies have had a significant impact on our lives, and with technological improvements, a rule-based expert system allows the end-user to enable new types of healthcare systems. The advent of Android OS-based smartphones with more user-friendly interfaces and lower pricing opens new possibilities for continuous monitoring of pets' health conditions, such as healthy dogs, dangerous ingestions, and swallowed objects. The proposed ‘Best Bark’ Dog care and owner consultation system is a mobile application for dog owners. Four main components for dog owners were implemented after a questionnaire was distributed to the target group of audience and the findings were evaluated. The proposed applications are widely used to provide health and clinical support to dog owners, including suggesting exercise and diet plans and answering queries about their dogs. Additionally, after the owner uploads a photo of the dog, the application provides immediate feedback and a description of the dog's skin disease.

Keywords: Convolution Neural Networks, Artificial Neural Networks, Knowledgebase, Sentimental Analysis.

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715 The Association of Southeast Asian Nations (ASEAN) and the Dynamics of Resistance to Sovereignty Violation: The Case of East Timor (1975-1999)

Authors: Laura Southgate

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The Association of Southeast Asian Nations (ASEAN), as well as much of the scholarship on the organisation, celebrates its ability to uphold the principle of regional autonomy, understood as upholding the norm of non-intervention by external powers in regional affairs. Yet, in practice, this has been repeatedly violated. This dichotomy between rhetoric and practice suggests an interesting avenue for further study. The East Timor crisis (1975-1999) has been selected as a case-study to test the dynamics of ASEAN state resistance to sovereignty violation in two distinct timeframes: Indonesia’s initial invasion of the territory in 1975, and the ensuing humanitarian crisis in 1999 which resulted in a UN-mandated, Australian-led peacekeeping intervention force. These time-periods demonstrate variation on the dependent variable. It is necessary to observe covariation in order to derive observations in support of a causal theory. To establish covariation, my independent variable is therefore a continuous variable characterised by variation in convergence of interest. Change of this variable should change the value of the dependent variable, thus establishing causal direction. This paper investigates the history of ASEAN’s relationship to the norm of non-intervention. It offers an alternative understanding of ASEAN’s history, written in terms of the relationship between a key ASEAN state, which I call a ‘vanguard state’, and selected external powers. This paper will consider when ASEAN resistance to sovereignty violation has succeeded, and when it has failed. It will contend that variation in outcomes associated with vanguard state resistance to sovereignty violation can be best explained by levels of interest convergence between the ASEAN vanguard state and designated external actors. Evidence will be provided to support the hypothesis that in 1999, ASEAN’s failure to resist violations to the sovereignty of Indonesia was a consequence of low interest convergence between Indonesia and the external powers. Conversely, in 1975, ASEAN’s ability to resist violations to the sovereignty of Indonesia was a consequence of high interest convergence between Indonesia and the external powers. As the vanguard state, Indonesia was able to apply pressure on the ASEAN states and obtain unanimous support for Indonesia’s East Timor policy in 1975 and 1999. However, the key factor explaining the variance in outcomes in both time periods resides in the critical role played by external actors. This view represents a serious challenge to much of the existing scholarship that emphasises ASEAN’s ability to defend regional autonomy. As these cases attempt to show, ASEAN autonomy is much more contingent than portrayed in the existing literature.

Keywords: ASEAN, east timor, intervention, sovereignty

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714 Moral Distress among Nurses Working in Hospitals in Jazan: A Cross-Sectional Study

Authors: Hussain Darraj

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Background: Healthcare workers, especially nurses, are subjected to a great risk of psychological stress, mostly moral distress. Therefore, it is crucial to address moral distress in nurses. Objectives: The aim of this study is to study the extent of moral distress among hospital nurses in Jazan. Methods: This study used a cross-sectional study design, which included 419 nurses from Jazan hospitals. A questionnaire was used to measure moral distress and its related factors. Results: The average total score for moral distress among the study participants is 134.14, with a standard deviation of 53.94. Moreover, the current study findings indicate that those over the age of 35 years who work as nurse managers, working in critical departments, have the intention to leave a position, have received ethical training or workshops, have provided care for COVID-19 cases, or work in a department with staff shortages are associated with the experience of higher-level moral stress. Conclusion: Nurses are recommended to be provided with ongoing education and resources in order to reduce moral distress and create a positive work atmosphere for nurses. Moreover, the current study sheds light on the importance of organizational support to provide enough resources and staffing in order to reduce moral distress among nurses. Further research is needed to focus on other health professionals and moral distress. Moreover, future studies are also required to explore the strategies to reduce moral distress levels among nurses.

Keywords: moral distress, Jazan, nurses, hospital

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713 Investigating Nurses’ Burnout Experiences on TikTok

Authors: Claire Song

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Background: TikTok is an emerging social media platform creating an outlet for nurses to express and communicate their nursing experiences and stress related to nursing. Purpose: This study investigates the lived experiences of nursing burnout shared on TikTok. Method: The cross-sectional content analysis examines the video content, format, type, and quantitative indicators, including the number of likes and comments. Results: A total of 35 videos and 18616 comments were examined, published between November 2020 and May 2023. Combined, these 35 videos received 24859 comments and 1159669 of likes. Most of the videos included nurses, and 12 included nurses in professional attire. Three videos included interviewers in the video, but the rest of the videos were self-recorded. Four themes of nurses’ burnout experiences were identified: 1) high-intensity work environment, 2) negative internal perception, 3) culture of nursing work, and 4) poor teamwork experience. Conclusion: This study explored the description of nurses’ burnout experiences via a creative platform. Social media, such as TikTok, is a valuable outlet for healthcare providers to express and share their experiences. Future research might consider using the social media platform to explore coping strategies and resilience in nurses who experienced burnout.

Keywords: burnout, emotional wellbeing, nursing, social media

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712 Brain Tumor Detection and Classification Using Pre-Trained Deep Learning Models

Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri

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Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.

Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation

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711 Health Belief Model to Predict Sharps Injuries among Health Care Workers at First Level Care Facilities in Rural Pakistan

Authors: Mohammad Tahir Yousafzai, Amna Rehana Siddiqui, Naveed Zafar Janjua

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We assessed the frequency and predictors of sharp injuries (SIs) among health care workers (HCWs) at first level care facilities (FLCF) in rural Pakistan. HCWs working at public clinic (PC), privately owned licensed practitioners’ clinic (LPC) and non-licensed practitioners’ clinic (NLC) were interviewed on universal precautions (UPs) and constructs of health belief model (HBM) to assess their association with SIs through negative-binomial regression. From 365 clinics, 485 HCWs were interviewed. Overall annual rate of Sis was 192/100 HCWs/year; 78/100 HCWs among licensed prescribers, 191/100 HCWs among non-licensed prescribers, 248/100 HCWs among qualified assistants, and 321/100 HCWs among non-qualified assistants. Increasing knowledge score about bloodborne pathogens (BBPs) transmission (rate-ratio (RR): 0.93; 95%CI: 0.89–0.96), fewer years of work experience, being a non-licensed prescriber (RR: 2.02; 95%CI: 1.36–2.98) licensed (RR: 2.86; 9%CI: 1.81–4.51) or non-licensed assistant (RR: 2.78; 95%CI: 1.72–4.47) compared to a licensed prescriber, perceived barriers (RR: 1.06;95%CI: 1.03–1.08), and compliance with UPs scores (RR: 0.93; 95%CI: 0.87–0.97) were significant predictors of SIs. Improved knowledge about BBPs, compliance with UPs and reduced barriers to follow UPs could reduce SIs to HCWs.

Keywords: health belief model, sharp injuries, needle stick injuries, healthcare workers

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710 Unusual High Origin and Superficial Course of Radial Artery: A Case Report with Embryological Explanation

Authors: Anasuya Ghosh, Subhramoy Chaudhury

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During routine cadaveric dissection at gross anatomy lab of our institution, a radial artery was found with unusual origin and superficial course. Normally the radial artery takes its origin as one of the terminal branches of brachial artery at the level of the neck of radius. It usually lies along the lateral border of fore arm deep to the brachioradialis muscle. While dissecting a 72-year-old Caucasian female cadaver, it was found that the right sided radial artery originated from the upper part of brachial artery of arm, 2 cm below the lower border of teres major muscle, from the lateral aspect of brachial artery. Then the radial artery superficially crossed the brachial artery and median nerve from lateral to medial direction and rested superficially at the cubital fossa. Embryologically, it can be explained as a failure of disappearance, or abnormal persistence of some insignificant embryonic vessels may give rise to this kind of vascular anomalies. As radial artery is one of the most important upper limb arteries, its variation and related complications are clinically significant. This unusual origin and course of radial artery should be kept in mind by all healthcare providers including surgeons and radiologists during routine venipuncture, orthopedic and plastic surgeries of arm, coronary angiographic procedures in radial approach etc. to prevent unwanted complications.

Keywords: brachial artery anomalies, brachio-radial artery, high origin radial artery, superficial radial artery

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709 Risk Factors for Fall in Elderly with Diabetes Mellitus Type 2 in Jeddah Saudi Arabia 2022: A Cross-Sectional Study

Authors: Rami S. Alasmari, Abdullah Al Zahrani, Hattan A. Hassani, Hattan A. Hassani, Nawwaf A. Almalky, Abdullah F. Bokhari, Alwalied A. Hafez

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Diabetes mellitus type 2 (DMT2) is a major chronic condition that is considered common among elderly people, with multiple potential complications that could contribute to falls. However, this concept is not well understood, thus, the aim of this study is to determine whether diabetes is an independent risk factor for falls in elderly. In this observational cross-sectional study, 309 diabetic patients aged 60 or more who visited the primary healthcare centers of the Ministry of National Guard Health Affairs in Jeddah were chosen via convenience sampling method. To collect the data, Semi-structured Fall Risk Assessment questionnaire and Fall Efficacy Score scale were used. The mean age of the participants was estimated to be 68.5 (SD:7.4) years. Among the participants, 48.2% experienced falling before, and 63.1% of them suffered falls in the past 12-months. The results showed that gait problems were independently associated with a higher likelihood of fall among the elderly patients (OR = 1.98, 95%CI, 1.08 to 3.62, p = 0.026. This paper suggests that diabetes mellitus is an independent fall risk factor among elderly. Therefore, identifying such patients as being at higher risk and prompt referral to a specialist falls clinic is recommended.

Keywords: diabetes, fall, elderly, risk factors

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708 The Differences of Vascular Endothelial Growth Factor Levels in Serum to Determine Follicular Adenoma and Follicular Carcinoma of Thyroid

Authors: Tery Nehemia Nugraha Joseph, J. D. P. Wisnubroto

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Thyroid cancer is a healthcare problem with high morbidity and mortality. Follicular adenoma and follicular carcinoma are thyroid tumors from the thyroid follicular cells differentiation with a microfollicular pattern that consists of follicular cuboidal cells. vascular endothelial growth factor (VEGF) is a potent and powerful mitogen for endothelial cells and increases vascular permeability. Therefore, due to an increase in thyroid-stimulating hormone (TSH), VEGF production is activated in the thyroid that leads to the end of mitogenic TSH stimulation and initiation of angiogenesis. The differences in VEGF levels in the follicular carcinoma of thyroid tissue with follicular adenoma thyroid can be used as a basis in differentiating the two types of neoplasms. This study aims to analyze VEGF in the serum so that it can be used to differentiate the types of thyroid carcinoma before surgery. This study uses a cross-sectional research design. Samples were carried out by taking serum samples, and the VEGF levels were calculated. Data were analyzed using the Mann-Whitney test. The results found a significant difference between VEGF levels in the follicular carcinoma thyroid group and VEGF levels in the follicular adenoma thyroid group with a value of p = 0.007 (p < 0.05). The results obtained are 560,427 ± 160,506 ng/mL in the type of follicular carcinoma thyroid and 320.943 ± 134.573 ng/mL in the type of follicular adenoma thyroid. VEGF levels between follicular adenoma and follicular carcinoma are different. VEGF levels are higher in follicular carcinoma thyroid than follicular adenoma thyroid.

Keywords: follicular adenoma thyroid, follicular carcinoma thyroid, thyroid, VEGF

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707 Blockchain-Resilient Framework for Cloud-Based Network Devices within the Architecture of Self-Driving Cars

Authors: Mirza Mujtaba Baig

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Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

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706 Evaluating the Knowledge and Skill of Final Year Pharmacy Students in Maternal and Child Health at a University in South Africa

Authors: E. O. Egieyeh, N. Butler, R. Coetzee, M. Van Huyssteen, A. Bheekie

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Background: High rate of maternal and child mortality is a global concern. Nationally, it constitutes one of South Africa’s quadruple burdens of diseases. Pharmacists have a crucial role in maternal and child health care delivery and as such should be equipped with adequate knowledge and skill required to contribute to maternal and child well-being. The International Pharmaceutical Federation statement of policy (2013) outlines pharmacist-led interventions in accordance with the World Health Organisation’s interventions in maternal, new-born and child health care. The South African Pharmacy Council’s guideline on Good Pharmacy Practice (2010) also stipulates the minimum standards required to participate in reproductive, maternal and child care. Pharmacy schools are obliged to train pharmacy students to meet priority health needs of the population so that graduates are ‘fit for purpose’. The purpose of the study is to evaluate the knowledge and skill of final year pharmacy students at a university in South Africa to determine their preparedness to contribute effectively to maternal and child health care. Method: A quantitative, descriptive, non-randomized baseline study was conducted among the final year students at the School of Pharmacy. Data was collected using a questionnaire designed in sections to assess knowledge of contraception, maternal and child health directed at the primary care level and framed within the scope of practice required of an entry-level generalist pharmacist. Participants’ skill in infant growth assessment was assessed in a section of the questionnaire in a written format. Participants ticked the topics they had been exposed to on a curriculum content assessment tool which was not graded. A pilot study examined the clarity and suitability of question items, and duration to complete the questionnaire. A score of 50% in each section of the questionnaire indicated a pass. The questionnaire was delivered in campus lecture venue. Results: Of the 102 students in final year, 53 (52%) students consented to participate in the study. Only 13.2% of participants scored above 50% in each section. Forty five (85%) participants scored above 50% in the contraception section while 40 (75%) scored less than 50% in the skills assessment. Less than half (45.3%) of the participants had a total score above 50%. Being a parent or working part-time as pharmacist assistance did not have any influence on the performance of the participants. Evaluation of participants’ curriculum content exposure showed differences in exposure to the various topics. Exposure to contraception teaching received the most recognition. Conclusion: Maternal and child health curriculum content should be reviewed at the university to enhance the knowledge and skill of pharmacy graduates.

Keywords: final year pharmacy students, knowledge and skill, maternal and child health, South Africa

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705 Mobi-DiQ: A Pervasive Sensing System for Delirium Risk Assessment in Intensive Care Unit

Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

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Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

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704 Reinventing Smart Tourism via Use of Smart Gamified and Gaming Applications in Greece

Authors: Sofia Maria Poulimenou, Ioannis Deliyannis, Elisavet Filippidou, Stamatella Laboura

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Smart technologies are being actively used to improve the experience of travel and promote or demote a destination’s reputation via a wide variety of social media applications and platforms. This paper conceptualises the design and deployment of smart management apps to promote culture, sustainability and accessibility within two destinations in Greece that represent the extremes of visiting scale. One is the densely visited Corfu, which is a UNESCO’s heritage site. The problems caused by the lack of organisation of the visiting experience and infrastructures affect all parties interacting within the site: visitors, citizens, public and private sector. Second is Kilkis, a low tourism destination with high seasonality and mostly inbound tourism. Here the issue faced is that traditional approaches to inform and motivate locals and visitors to explore and taste of the culture have not flourished. The problem is apprehended via the design and development of two systems named “Hologrammatic Corfu” for Corfu old town and “BRENDA” for the area of Kilkis. Although each system is designed independently, featuring different solutions to the problems, both approaches have been designed by the same team and a novel gaming and gamification methodology. The “Hologramatic Corfu” application has been designed, for the exploration of the site covering user requirments before, during and after the trip, with the use of transmedia content such as photos, 360-degree videos, augmented reality and hologrammatic videos. Also, a statistical analysis of travellers’ visits to specific points of interest is actively utilized enabling visitors to dynamically re-rooted during their visit, safeguarding sustainability and accessibility and inclusivity along the entire tourism cycle. “BRENDA” is designed specifically to promote gastronomic and historical tourism. This serious game implements and combines gaming and gamification elements in order to connect local businesses with cultural points of interest. As the environment of the project has a strong touristic orientation, “BRENDA” supports food-related gamified processes and historical games involving active participation of both local communities (content providers) and visitors (players) which are more likely to be successfully performed in the informal environment of travelling and promote sustainable tourism experiences. Finally, the paper presents the ability to re-use existing gaming components within new areas of interest via minimal adaptation and the use of transmedia aspects that enables destinations to be rebranded into smart destinations.

Keywords: smart tourism, gamification, user experience, transmedia content

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703 Social Support and Self-Regulation on Changes in Exercise Behavior Among Infertile Women: A Cross-Sectional Study to Comparison of External and Internal Factors

Authors: Babak Nemat

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Background: Exercise behavior (EB) has a significant impact on infertility, but the magnitude of the effect is not easily determined. The aim of the present study was to assess the effect of social support and self-regulation, as external and internal factors, on changes in exercise behavior among infertile women. Methods: For a cross-sectional study conducted in Sanandaj (Iran) in 2023, we recruited infertile women (n=483) from 35 comprehensive healthcare centers by means of convenience sampling. Standardized face-to-face interviews were conducted using established and reliable instruments for the assessment of EB, social support, and self-regulation. Logistic regression models were applied to assess the association between EB, social support and self-regulation. Results: The majority of the participants (56.7%) had secondary infertility, while 70.8% of them did not perform any exercise. Self-regulation and social support were significantly higher in women with secondary infertility than in those with primary infertility (p < 0.01). Self-regulation was significantly lower in women whose height was below 160 centimeters (cm) (p<0.05). Social support was significantly higher among participants aged ≥ 35 years and weighing ≥ 60 kilograms (kg) (p < 0.01). The odds of EB adoption increased with self-regulation and social support (OR=1.05, 95% CI=1.02-1.09, p <0.01), (OR=1.06, 95% CI=1.02-1.11, p <0.01). Conclusion: Social support and self-regulation almost equally influenced EB in infertile women. Designing support and consultation programs can be considered in encouraging infertile women to exercise in future research.

Keywords: social support, regulation, infertility, women

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