Search results for: the health belief model
Commenced in January 2007
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Edition: International
Paper Count: 24772

Search results for: the health belief model

21382 The Impact of Economic Status on Health Status in the Context of Bangladesh

Authors: Md. S. Sabuz

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Bangladesh, a South Asian developing country, has achieved a remarkable breakthrough in health indicators during the last four decades despite immense income inequality. This phenomenon results in the mystical exclusion of marginalized people from obtaining health care facilities. However, the persistence of exclusion of the disadvantaged remains troubling. Exclusion occurs from occupational inferiority, pay and wage differences, educational backwardness, gender disparity to urban-rural complexity and eliminate the unprivileged from seeking and availing the health services. Evidence from Bangladesh shows that many sick people prefer to die at home without securing medical services because in previous times they were not treated well, not because the medical facilities were inadequate or antediluvian but the socio-economic class allows them to receive obdurate treatment. Furthermore, government and policymakers have given enormous emphasis on infrastructural development and achieving health indicators instead of ensuring quality services and inclusiveness of people from all spheres. Therefore, it is high time to address the issues concerning this and highlight the impact of economic status on health status in a sociological perspective. The objective of this study is to consider ways of assessing and exploring the impact of economic status for instance: occupational status, pay and wage variable, on health status in the context of Bangladesh. The hypotheses are that there are a significant number of factors affecting economic status which are impactful for health status eventually, but acute income inequality is a prominent factor. Illiteracy, gender disparity, remoteness, incredibility on services, superior costs, superstition etc. are the dominant indicators behind the economic factors influencing the health status. The chosen methodologies are a qualitative and quantitative approaches to accomplish the research objectives. Secondary sources of data will be used to conduct the study. Surveys will be conducted on the people who have ever been through the health care facilities and people from the different socio-economic and cultural backgrounds. Focus group discussions will be conducted to acquire the data from different cultural and regional citizens. The findings show that 48% of people who are from disadvantaged communities have been deprived of proper health care facilities. The general reasons behind this are the higher cost of medicines and other equipment. A significant number of people are unaware of the appropriate facilities. It was found that the socio-economic variables are the main influential factors that work as the driving force for both economic dimension and health status. Above all regional variables and gender, dimensions have an enormous effect on determining the health status of an individual or community. Amidst many positive achievements for example decrease in the child mortality rate, an increase in the immunization programs of the child etc., the inclusiveness of all classes of people in health care facilities has been overshadowed in Bangladesh. However, this phenomenon along with the socio-economic and cultural phenomena significantly demolishes the quality and inclusiveness of the health status of people.

Keywords: cultural context of health, economic status, gender and health, rural health care

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21381 The Effect of Institutions on Economic Growth: An Analysis Based on Bayesian Panel Data Estimation

Authors: Mohammad Anwar, Shah Waliullah

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This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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21380 Spatial Variability of Soil Pollution and Health Risks Due to Long-Term Wastewater Irrigation in Egypt

Authors: Mohamed Eladham Fadl M. E. Fadl

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In Egypt, wastewater has been used for irrigation in areas with fresh water scarcity. However, continuous applications may cause potential risks. Thus, the current study aims at screening the impacts of long-term wastewater irrigation on soil pollution and human health due to the exposure of heavy metals. Soils of nine sites in Al-Qalyubiyah Governorate, Egypt were sampled and analyzed for different properties. Wastewater resulted in a build-up of metals in soils. The pollution index (PI) showed the order of Cd > Pb > Ni > Zn. The integrated pollution index of Nemerow’s (IPIN) exceeded the safe limit of 0.7. The enrichment factor (EF) surpassed 1.0 value proving anthropogenic effects. The geo-accumulation index (Igeo) indicated that Pb, Ni, and Zn-induced none to moderate pollution, while high threats were associated with Cd. The calculated hazard index proved a potential health risk for humans, particularly children. It is recommended to perform a treatment to the wastewater used in irrigation to avoid such threats.

Keywords: pollution, health risks, heavy metals, effluent, irrigation, GIS techniques

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21379 Python Implementation for S1000D Applicability Depended Processing Model - SALERNO

Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

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21378 Using Health Literacy and Medico-Legal Guidance to Improve Restorative Dentistry Patient Information Leaflets

Authors: Hasneet K. Kalsi, Julie K. Kilgariff

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Introduction: Within dentistry, the process for gaining informed consent has become more complex. To consent for treatment, patients must understand all reasonable treatment options and associated risks and benefits. Consenting is therefore deeply embedded in health literacy. Patients attending for dental consultation are often presented with an array of information and choices, yet studies show patients recall less than half of the information provided immediately after. Appropriate and comprehensible patient information leaflets (PILs) may be useful aid memories. In 2016 the World Health Organisation set improving health literacy as a global priority. Soon after, Scotland’s 2017-2025 Making it Easier: A Health Literacy Action Plan followed. This project involved the review of Restorative PILs used within Dundee Dental Hospital to assess the Content and Readability. Method: The current PIL on Root Canal Treatment (RCT) was created in 2011. This predates the Montgomery vs. NHS Lanarkshire case, a ruling which significantly impacted dental consenting processes, as well as General Dental Council’s (GDC’s) Standards for the Dental Team and Faculty of General Dental Practice’s Good Practice Guidance on Clinical Examination and Record-Keeping. Current evidence-based guidance, including that stipulated by the GDC, was reviewed. A 20-point Essential Content Checklist was designed to conform to best practice guidance for valid consenting processes. The RCT leaflet was scored against this to ascertain if the content was satisfactory. Having ensured the content satisfied medicolegal requirements, health literacy considerations were reviewed regarding readability. This was assessed using McLaughlin’s Simple Measure of Gobbledygook (SMOG) formula, which identifies school stages that would have to be achieved to comprehend the PIL. The sensitivity of the results to alternative readability methods were assessed. Results: The PIL was not sufficient for modern consenting processes and reflected a suboptimal level of health literacy. Evaluation of the leaflet revealed key content was missing, including information pertaining to risks and benefits. Only five points out of the 20-point checklist were present. The readability score was 16, equivalent to a level 2 in National Adult Literacy Standards/Scottish Credit and Qualification Framework Level 5; 62% of Scottish adults are able to read to this standard. Discussion: Assessment of the leaflet showed it was no longer fit for purpose. Reasons include a lack of pertinent information, a text-heavy leaflet lacking flow, and content errors. The SMOG score indicates a high level of comprehension is required to understand this PIL, which many patients may not possess. A new PIL, compliant with medicolegal and health literacy guidance, was designed with patient-driven checklists, notes spaces for annotations/ questions and areas for clinicians to highlight important case-specific information. It has been tested using the SMOG formula. Conclusion: PILs can be extremely useful. Studies show that interactive use can enhance their effectiveness. PILs should reflect best practice guidance and be understood by patients. The 2020 leaflet designed and implemented aims to fulfill the needs of a modern healthcare system and its service users. It embraces and embeds Scotland’s Health Literacy Action Plan within the consenting process. A review of further leaflets using this model is ongoing.

Keywords: consent, health literacy, patient information leaflet, restorative dentistry

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21377 Optimal Portfolio of Multi-service Provision based on Stochastic Model Predictive Control

Authors: Yifu Ding, Vijay Avinash, Malcolm McCulloch

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As the proliferation of decentralized energy systems, the UK power system allows small-scale entities such as microgrids (MGs) to tender multiple energy services including energy arbitrage and frequency responses (FRs). However, its operation requires the balance between the uncertain renewable generations and loads in real-time and has to fulfill their provision requirements of contract services continuously during the time window agreed, otherwise it will be penalized for the under-delivered provision. To hedge against risks due to uncertainties and maximize the economic benefits, we propose a stochastic model predictive control (SMPC) framework to optimize its operation for the multi-service provision. Distinguished from previous works, we include a detailed economic-degradation model of the lithium-ion battery to quantify the costs of different service provisions, as well as accurately describe the changing dynamics of the battery. Considering a branch of load and generation scenarios and the battery aging, we formulate a risk-averse cost function using conditional value at risk (CVaR). It aims to achieve the maximum expected net revenue and avoids severe losses. The framework will be performed on a case study of a PV-battery grid-tied microgrid in the UK with real-life data. To highlight its performance, the framework will be compared with the case without the degradation model and the deterministic formulation.

Keywords: model predictive control (MPC), battery degradation, frequency response, microgrids

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21376 Joint Training Offer Selection and Course Timetabling Problems: Models and Algorithms

Authors: Gianpaolo Ghiani, Emanuela Guerriero, Emanuele Manni, Alessandro Romano

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In this article, we deal with a variant of the classical course timetabling problem that has a practical application in many areas of education. In particular, in this paper we are interested in high schools remedial courses. The purpose of such courses is to provide under-prepared students with the skills necessary to succeed in their studies. In particular, a student might be under prepared in an entire course, or only in a part of it. The limited availability of funds, as well as the limited amount of time and teachers at disposal, often requires schools to choose which courses and/or which teaching units to activate. Thus, schools need to model the training offer and the related timetabling, with the goal of ensuring the highest possible teaching quality, by meeting the above-mentioned financial, time and resources constraints. Moreover, there are some prerequisites between the teaching units that must be satisfied. We first present a Mixed-Integer Programming (MIP) model to solve this problem to optimality. However, the presence of many peculiar constraints contributes inevitably in increasing the complexity of the mathematical model. Thus, solving it through a general purpose solver may be performed for small instances only, while solving real-life-sized instances of such model requires specific techniques or heuristic approaches. For this purpose, we also propose a heuristic approach, in which we make use of a fast constructive procedure to obtain a feasible solution. To assess our exact and heuristic approaches we perform extensive computational results on both real-life instances (obtained from a high school in Lecce, Italy) and randomly generated instances. Our tests show that the MIP model is never solved to optimality, with an average optimality gap of 57%. On the other hand, the heuristic algorithm is much faster (in about the 50% of the considered instances it converges in approximately half of the time limit) and in many cases allows achieving an improvement on the objective function value obtained by the MIP model. Such an improvement ranges between 18% and 66%.

Keywords: heuristic, MIP model, remedial course, school, timetabling

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21375 The Impacts of Negative Moral Characters on Health: An Article Review

Authors: Mansoor Aslamzai, Delaqa Del, Sayed Azam Sajid

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Introduction: Though moral disorders have a high burden, there is no separate topic regarding this problem in the International Classification of Diseases (ICD). Along with the modification of WHO ICD-11, spirituality can prevent the rapid progress of such derangement as well. Objective: This study evaluated the effects of bad moral characters on health, as well as carried out the role of spirituality in the improvement of immorality. Method: This narrative article review was accomplished in 2020-2021 and the articles were searched through the Web of Science, PubMed, BMC, and Google scholar. Results: Based on the current review, most experimental and observational studies revealed significant negative effects of unwell moral characters on the overall aspects of health and well-being. Nowadays, a lot of studies established the positive role of spirituality in the improvement of health and moral disorder. The studies concluded, facilities must be available within schools, universities, and communities for everyone to learn the knowledge of spirituality and improve their unwell moral character world. Conclusion: Considering the negative relationship between unwell moral characters and well-being, the current study proposes the addition of moral disorder as a separate topic in the WHO International Classification of Diseases. Based on this literature review, spirituality will improve moral disorder and establish excellent moral traits.

Keywords: bad moral characters, effect, health, spirituality and well-being

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21374 A One-Dimensional Model for Contraction in Burn Wounds: A Sensitivity Analysis and a Feasibility Study

Authors: Ginger Egberts, Fred Vermolen, Paul van Zuijlen

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One of the common complications in post-burn scars is contractions. Depending on the extent of contraction and the wound dimensions, the contracture can cause a limited range-of-motion of joints. A one-dimensional morphoelastic continuum hypothesis-based model describing post-burn scar contractions is considered. The beauty of the one-dimensional model is the speed; hence it quickly yields new results and, therefore, insight. This model describes the movement of the skin and the development of the strain present. Besides these mechanical components, the model also contains chemical components that play a major role in the wound healing process. These components are fibroblasts, myofibroblasts, the so-called signaling molecules, and collagen. The dermal layer is modeled as an isotropic morphoelastic solid, and pulling forces are generated by myofibroblasts. The solution to the model equations is approximated by the finite-element method using linear basis functions. One of the major challenges in biomechanical modeling is the estimation of parameter values. Therefore, this study provides a comprehensive description of skin mechanical parameter values and a sensitivity analysis. Further, since skin mechanical properties change with aging, it is important that the model is feasible for predicting the development of contraction in burn patients of different ages, and hence this study provides a feasibility study. The variability in the solutions is caused by varying the values for some parameters simultaneously over the domain of computation, for which the results of the sensitivity analysis are used. The sensitivity analysis shows that the most sensitive parameters are the equilibrium concentration of collagen, the apoptosis rate of fibroblasts and myofibroblasts, and the secretion rate of signaling molecules. This suggests that most of the variability in the evolution of contraction in burns in patients of different ages might be caused mostly by the decreasing equilibrium of collagen concentration. As expected, the feasibility study shows this model can be used to show distinct extents of contractions in burns in patients of different ages. Nevertheless, contraction formation in children differs from contraction formation in adults because of the growth. This factor has not been incorporated in the model yet, and therefore the feasibility results for children differ from what is seen in the clinic.

Keywords: biomechanics, burns, feasibility, fibroblasts, morphoelasticity, sensitivity analysis, skin mechanics, wound contraction

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21373 Supplier Risk Management: A Multivariate Statistical Modelling and Portfolio Optimization Based Approach for Supplier Delivery Performance Development

Authors: Jiahui Yang, John Quigley, Lesley Walls

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In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

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21372 Forecasting Silver Commodity Prices Using Geometric Brownian Motion: A Stochastic Approach

Authors: Sina Dehghani, Zhikang Rong

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Historically, a variety of approaches have been taken to forecast commodity prices due to the significant implications of these values on the global economy. An accurate forecasting tool for a valuable commodity would significantly benefit investors and governmental agencies. Silver, in particular, has grown significantly as a commodity in recent years due to its use in healthcare and technology. This manuscript aims to utilize the Geometric Brownian Motion predictive model to forecast silver commodity prices over multiple 3-year periods. The results of the study indicate that the model has several limitations, particularly its inability to work effectively over longer periods of time, but still was extremely effective over shorter time frames. This study sets a baseline for silver commodity forecasting with GBM, and the model could be further strengthened with refinement.

Keywords: geometric Brownian motion, commodity, risk management, volatility, stochastic behavior, price forecasting

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21371 Simulating Economic Order Quantity and Reorder Point Policy for a Repairable Items Inventory System

Authors: Mojahid F. Saeed Osman

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Repairable items inventory system is a management tool used to incorporate all information concerning inventory levels and movements for repaired and new items. This paper presents development of an effective simulation model for managing the inventory of repairable items for a production system where production lines send their faulty items to a repair shop considering the stochastic failure behavior and repair times. The developed model imitates the process of handling the on-hand inventory of repaired items and the replenishment of the inventory of new items using Economic Order Quantity and Reorder Point ordering policy in a flexible and risk-free environment. We demonstrate the appropriateness and effectiveness of the proposed simulation model using an illustrative case problem. The developed simulation model can be used as a reliable tool for estimating a healthy on-hand inventory of new and repaired items, backordered items, and downtime due to unavailability of repaired items, and validating and examining Economic Order Quantity and Reorder Point ordering policy, which would further be compared with other ordering strategies as future work.

Keywords: inventory system, repairable items, simulation, maintenance, economic order quantity, reorder point

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21370 Access to Sexual Reproductive Health (SRH) Education and Services to Deaf Adolescents in Wakiso, Uganda - The Ugandan Perspective

Authors: Racheal Ayanga, Nancy Katumba Muwangala, Jane Babirye, Harriet Kivumbi

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Background: Deaf adolescents are vulnerable. Deafness limits their access to resources that are accessed by their hearing peers. There is minimal attention placed on the SRH needs of persons with disabilities, especially in developing countries. We sought to assess barriers to access of SRH education and services for deaf adolescents in Uganda. Methods: We performed a cross sectional study using a questionnaire on knowledge of and access to SRH education and services from a selected sample of deaf adolescents aged 13-19 years at Wakiso Secondary school for the deaf. A consecutive sample of eligible participants was asked to join the study after obtaining informed consent until the target sample size was reached. Results: From 01 Jul 2022 to 30 Jan 2023, 70 quantitative interviews were conducted. Participants’ mean age was 17 years, and 66% were female. 89% had heard about several components of SRH. 99% reported a need for education and services but had challenges with access 85% of the time. 54% reported receipt of education and services from government or private facilities, and the rest from friends, parents, siblings, teachers and the internet. Conclusion: Government needs to look into availing tailored, sustainable SRH education/services to deaf adolescents at health facilities and teach health workers sign language. SRH education to parents, teachers and communities of deaf adolescents improves access in hard-to-reach areas. Integration of services into routine health care is key in creating and improving models of access to wider communities of persons with disabilities to improve their mental health.

Keywords: sexual and reproductive health, deaf, adolescents, education, services, disabilities, mental health, hard-to-reach areas

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21369 Services-Oriented Model for the Regulation of Learning

Authors: Mohamed Bendahmane, Brahim Elfalaki, Mohammed Benattou

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One of the major sources of learners' professional difficulties is their heterogeneity. Whether on cognitive, social, cultural or emotional level, learners being part of the same group have many differences. These differences do not allow to apply the same learning process at all learners. Thus, an optimal learning path for one, is not necessarily the same for the other. We present in this paper a model-oriented service to offer to each learner a personalized learning path to acquire the targeted skills.

Keywords: learning path, web service, trace analysis, personalization

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21368 Presenting a Knowledge Mapping Model According to a Comparative Study on Applied Models and Approaches to Map Organizational Knowledge

Authors: Ahmad Aslizadeh, Farid Ghaderi

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Mapping organizational knowledge is an innovative concept and useful instrument of representation, capturing and visualization of implicit and explicit knowledge. There are a diversity of methods, instruments and techniques presented by different researchers following mapping organizational knowledge to reach determined goals. Implicating of these methods, it is necessary to know their exigencies and conditions in which those can be used. Integrating identified methods of knowledge mapping and comparing them would help knowledge managers to select the appropriate methods. This research conducted to presenting a model and framework to map organizational knowledge. At first, knowledge maps, their applications and necessity are introduced because of extracting comparative framework and detection of their structure. At the next step techniques of researchers such as Eppler, Kim, Egbu, Tandukar and Ebner as knowledge mapping models are presented and surveyed. Finally, they compare and a superior model would be introduced.

Keywords: knowledge mapping, knowledge management, comparative study, business and management

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21367 Chronically Ill Patient Satisfaction: An Indicator of Quality of Service Provided at Primary Health Care Settings in Alexandria

Authors: Alyaa Farouk Ibrahim, Gehan ElSayed, Ola Mamdouh, Nazek AbdelGhany

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Background: Primary health care (PHC) can be considered the first contact between the patient and the health care system. It includes all the basic health care services to be provided to the community. Patient's satisfaction regarding health care has often improved the provision of care, also considered as one of the most important measures for evaluating the health care. Objective: This study aims to identify patient’s satisfaction with services provided at the primary health care settings in Alexandria. Setting: Seven primary health care settings representing the seven zones of Alexandria governorate were selected randomly and included in the study. Subjects: The study comprised 386 patients attended the previously selected settings at least twice before the time of the study. Tools: Two tools were utilized for data collection; sociodemographic characteristics and health status structured interview schedule and patient satisfaction scale. Reliability test for the scale was done using Cronbach's Alpha test, the result of the test ranged between 0.717 and 0.967. The overall satisfaction was computed and divided into high, medium, and low satisfaction. Results: Age of the studied sample ranged between 19 and 62 years, more than half (54.2%) of them aged 40 to less than 60 years. More than half (52.8%) of the patients included in the study were diabetics, 39.1% of them were hypertensive, 19.2% had cardiovascular diseases, the rest of the sample had tumor, liver diseases, and orthopedic/neurological disorders (6.5%, 5.2% & 3.2%, respectively). The vast majority of the study group mentioned high satisfaction with overall service cost, environmental conditions, medical staff attitude and health education given at the PHC settings (87.8%, 90.7%, 86.3% & 90.9%, respectively), however, medium satisfaction was mostly reported concerning medical checkup procedures, follow-up data and referral system (41.2%, 28.5% & 28.9%, respectively). Score level of patient satisfaction with health services provided at the assessed Primary health care settings proved to be significantly associated with patients’ social status (P=0.003, X²=14.2), occupation (P=0.011, X²=11.2), and monthly income (P=0.039, X²=6.50). In addition, a significant association was observed between score level of satisfaction and type of illness (P=0.007, X²=9.366), type of medication (P=0.014, X²=9.033), prior knowledge about the health center (P=0.050, X²=3.346), and highly significant with the administrative zone (P=0.001, X²=55.294). Conclusion: The current study revealed that overall service cost, environmental conditions, staff attitude and health education at the assessed primary health care settings gained high patient satisfaction level, while, medical checkup procedures, follow-up, and referral system caused a medium level of satisfaction among assessed patients. Nevertheless, social status, occupation, monthly income, type of illness, type of medication and administrative zones are all factors influencing patient satisfaction with services provided at the health facilities.

Keywords: patient satisfaction, chronic illness, quality of health service, quality of service indicators

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21366 Monte Carlo Estimation of Heteroscedasticity and Periodicity Effects in a Panel Data Regression Model

Authors: Nureni O. Adeboye, Dawud A. Agunbiade

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This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.

Keywords: audit fee lagrange multiplier test, heteroscedasticity, lagrange multiplier test, Monte-Carlo scheme, periodicity

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21365 The Application of a Hybrid Neural Network for Recognition of a Handwritten Kazakh Text

Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

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The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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21364 Modeling the Saltatory Conduction in Myelinated Axons by Order Reduction

Authors: Ruxandra Barbulescu, Daniel Ioan, Gabriela Ciuprina

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The saltatory conduction is the way the action potential is transmitted along a myelinated axon. The potential diffuses along the myelinated compartments and it is regenerated in the Ranvier nodes due to the ion channels allowing the flow across the membrane. For an efficient simulation of populations of neurons, it is important to use reduced order models both for myelinated compartments and for Ranvier nodes and to have control over their accuracy and inner parameters. The paper presents a reduced order model of this neural system which allows an efficient simulation method for the saltatory conduction in myelinated axons. This model is obtained by concatenating reduced order linear models of 1D myelinated compartments and nonlinear 0D models of Ranvier nodes. The models for the myelinated compartments are selected from a series of spatially distributed models developed and hierarchized according to their modeling errors. The extracted model described by a nonlinear PDE of hyperbolic type is able to reproduce the saltatory conduction with acceptable accuracy and takes into account the finite propagation speed of potential. Finally, this model is again reduced in order to make it suitable for the inclusion in large-scale neural circuits.

Keywords: action potential, myelinated segments, nonlinear models, Ranvier nodes, reduced order models, saltatory conduction

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21363 A Deep Learning Model with Greedy Layer-Wise Pretraining Approach for Optimal Syngas Production by Dry Reforming of Methane

Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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21362 Demographic Characteristics as a Determinant of the use of Health Care Services: Case of Nsukka, Southwest Nigeria

Authors: Beatrice Adeoye

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Studies have associated social and demographic characteristics as strong determinants of utilization of health care services; however, not much has been done to explore the dynamics of these variables in Nigeria. This empirical study explores the link between demographic factors and the future use of health care services in Nsukka, southeast Nigeria. A total of 543 respondents were selected using multi-stage sampling technique. The findings of the study showed that majority (56.9%) of the respondents were female while 43.1% were male. More of the respondents were married (50.3%) while 41.80/0 of the respondents were between ages 26-35. Testing the demographic characteristics regarding where people will prefer to go first for treatment with multiple regression, It is only Sex as a demographic variable that indicates positive association for future occurrence to where people will prefer to go first for treatment with 0.08 significance. Age and education indicates no association considering their level of significance. This result shows that sex is one of the determinant factors of where and when people will go for treatment. This is pointing out the realities regarding African society where in the family setting, it is the father that dictates the cause of action. Also to buttress these findings, cross tabulating age with who determines where and when to go for treatment, findings show that majority (58.9%) within age 26-35 said their spouses decide on where and when to go for treatment. Findings showed that patriarchy still plays an important role in the utilization of health care delivery among the people studied.

Keywords: Demographic characters, Determinant, Health Care, treatment, self-medication, symptom,

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21361 Destructive Groups: The Impact on Adolescent Mental Health and Social Integration

Authors: Dušica Kovačević

Abstract:

This study explores the influence of destructive groups on the mental health and social integration of high school students in Loznica, Serbia. Despite increasing concerns, there is a significant lack of research on the impact of these groups on adolescents in this region. This qualitative study aims to fill this gap by examining the prevalence of destructive groups, their psychological effects on students, and their broader social implications. Data were collected through surveys and in-depth interviews with high school students, educators, and mental health professionals. The study focuses on key mental health indicators, such as anxiety, depression, and identity formation, alongside social factors, including peer relationships and community engagement. Additionally, it defines coping mechanisms and supporting strategies employed by students affected by these groups. The findings reveal substantial psychological and social challenges faced by students exposed to destructive groups, including increased levels of anxiety and depression, disrupted identity development, and impaired social integration. Insights into the personal experiences of these students provide a detailed understanding of the groups’ impact, underscoring the need for targeted interventions. This research offers evidence-based recommendations for educators, mental health practitioners, and policymakers. It emphasizes the importance of developing effective educational programs and support services to enhance the well-being of high school advocates for proactive measures to protect adolescent mental health and promote healthy social values within educational and community settings.

Keywords: adolescents, mental health, destructive groups, social integration, qualitative study, high school students, Serbia

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21360 Effective and Innovative Health Promotion Interventions for Promoting Life-Long Opportunities through Better Health and Nutrition Beginning from Early Childhood

Authors: Nadeesha Sewwandi, Dilini Shashikala, Rajarathnam Kanapathy, Shivakumaran Viyasan, Saman Kumara, Duminda Guruge

Abstract:

Introduction: Nutrition is fundamental for good health and development during the early years of life. This study describes how rural community does interventions for improving the nutrition and health of children less than 5 year ages using health promotion approach and this study was conducted with children society and mothers groups in a rural village called Welankulama in Sri Lanka. Methodology: The details got from Public Health Midwife in this village showed there were malnourished children under 5 years age. So, we discussed this problem with the children society, mothers groups and identified the determinants with them. Then they wanted to address some of the determinants that they prioritized from their discussions. ‘Evening school’ was a new place to this village to do collective feeding for small children. ‘Mobile library’ was another new concept in this village and nutrition books, evidence collection were there to read for villagers. Mothers marked the foods given to their kids in a book called ‘Nutrition book’. And also mothers tend to mark the level of eating foods to motivate their children in a ‘Hapana calendar’. Results: In terms of results, malnourished children under 5 years age got reduced and the number of children having illnesses got reduced. Marking nutrition book and ‘Hapana calendar’ were become as trend among mothers. Apart from the above, there was good improvement of physical, social and emotional wellbeing of children. Children who received early stimulation with nutrition supplements had better outcomes than children who only received nutrition supplements, thereby amplifying the impact of nutrition. Conclusion: Health promotion interventions are helped to change nutritional behaviors of early childhood in rural community and it makes children healthier and better able to learn.

Keywords: early childhood, nutrition, determinants, health promotion process

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21359 Urban Health and Strategic City Planning: A Case from Greece

Authors: Alexandra P. Alexandropoulou, Andreas Fousteris, Eleni Didaskalou, Dimitrios A. Georgakellos

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As urbanization is becoming a major stress factor not only for the urban environment but also for the wellbeing of city dwellers, incorporating the issues of urban health in strategic city planning and policy-making has never been more relevant. The impact of urbanization can vary from low to severe and relates to all non-communicable diseases caused by the different functions of cities. Air pollution, noise pollution, water and soil pollution, availability of open green spaces, and urban heat island are the major factors that can compromise citizens' health. Urban health describes the effects of the social environment, the physical environment, and the availability and accessibility to health and social services. To assess the quality of urban wellbeing, all urban characteristics that might have an effect on citizens' health must be considered, evaluated, and introduced in integrated local planning. A series of indices and indicators can be used to better describe these effects and set the target values in policy making. Local strategic planning is one of the most valuable development tools a local city administration can possess; thus, it has become mandatory under Greek law for all municipalities. It involves a two-stage procedure; the first aims to collect, analyse and evaluate data on the current situation of the city (administrative data, population data, environmental data, social data, swot analysis), while the second aims to introduce a policy vision described and supported by distinct (nevertheless integrated) actions, plans and measures to be implemented with the aim of city development and citizen wellbeing. In this procedure, the element of health is often neglected or under-evaluated. A relative survey was conducted among all Greek local authorities in order to shed light on the current situation. Evidence shows that the rate of incorporation of health in strategic planning is lacking behind. The survey also highlights key hindrances and concerns raised by local officials and suggests a path for the way forward.

Keywords: urban health, strategic planning, local authorities, integrated development

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21358 Off-Topic Text Detection System Using a Hybrid Model

Authors: Usama Shahid

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Be it written documents, news columns, or students' essays, verifying the content can be a time-consuming task. Apart from the spelling and grammar mistakes, the proofreader is also supposed to verify whether the content included in the essay or document is relevant or not. The irrelevant content in any document or essay is referred to as off-topic text and in this paper, we will address the problem of off-topic text detection from a document using machine learning techniques. Our study aims to identify the off-topic content from a document using Echo state network model and we will also compare data with other models. The previous study uses Convolutional Neural Networks and TFIDF to detect off-topic text. We will rearrange the existing datasets and take new classifiers along with new word embeddings and implement them on existing and new datasets in order to compare the results with the previously existing CNN model.

Keywords: off topic, text detection, eco state network, machine learning

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21357 Model-Based Field Extraction from Different Class of Administrative Documents

Authors: Jinen Daghrir, Anis Kricha, Karim Kalti

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The amount of incoming administrative documents is massive and manually processing these documents is a costly task especially on the timescale. In fact, this problem has led an important amount of research and development in the context of automatically extracting fields from administrative documents, in order to reduce the charges and to increase the citizen satisfaction in administrations. In this matter, we introduce an administrative document understanding system. Given a document in which a user has to select fields that have to be retrieved from a document class, a document model is automatically built. A document model is represented by an attributed relational graph (ARG) where nodes represent fields to extract, and edges represent the relation between them. Both of vertices and edges are attached with some feature vectors. When another document arrives to the system, the layout objects are extracted and an ARG is generated. The fields extraction is translated into a problem of matching two ARGs which relies mainly on the comparison of the spatial relationships between layout objects. Experimental results yield accuracy rates from 75% to 100% tested on eight document classes. Our proposed method has a good performance knowing that the document model is constructed using only one single document.

Keywords: administrative document understanding, logical labelling, logical layout analysis, fields extraction from administrative documents

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21356 Learning Performance of Sports Education Model Based on Self-Regulated Learning Approach

Authors: Yi-Hsiang Pan, Ching-Hsiang Chen, Wei-Ting Hsu

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The purpose of this study was to compare the learning effects of the sports education model (SEM) to those of the traditional teaching model (TTM) in physical education classes in terms of students learning motivation, action control, learning strategies, and learning performance. A quasi-experimental design was utilized in this study, and participants included two physical educators and four classes with a total of 94 students in grades 5 and 6 of elementary schools. Two classes implemented the SEM (n=47, male=24, female=23; age=11.89, SD=0.78) and two classes implemented the TTM (n=47, male=25, female=22, age=11.77; SD=0.66). Data were collected from these participants using a self-report questionnaire (including a learning motivation scale, action control scale, and learning strategy scale) and a game performance assessment instrument, and multivariate analysis of covariance was used to conduct statistical analysis. The findings of the study revealed that the SEM was significantly better than the TTM in promoting students learning motivation, action control, learning strategies, and game performance. It was concluded that the SEM could promote the mechanics of students self-regulated learning process, and thereby improve students movement performance.

Keywords: self-regulated learning theory, learning process, curriculum model, physical education

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21355 Strategies to Mitigate Disasters at the Hajj Religious Festival Using GIS and Agent Based Modelling

Authors: Muteb Alotaibi, Graham Clarke, Nick Malleson

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The Hajj religious festival at Mina in Saudi Arabia has always presented the opportunity for injuries or deaths. For example, in 1990, a stampede killed 1426 pilgrims, whilst in 1997, 343 people were killed and 1500 injured due to a fire fuelled by high winds sweeping through the tent city in Mina.Many more minor incidents have occurred since then. It is predicted that 5 million pilgrims will soon perform the ritual at Mina (which is, in effect, a temporary city built each year in the desert), which might lead in the future to severe congestion and accidents unless the research is conducted on actions that contribute positively to improving the management of the crowd and facilitating the flow of pilgrims safely and securely. To help prevent further disasters, it is important to first plan better, more accessible locations for emergency services across Mina to ensure a good service for pilgrims. In this paper, we first use a Location Allocation Model (LAM) within a network GIS to examine the optimal locations for key services in the temporary city of Mina. This has been undertaken in relation to the location and movement of the pilgrims during the six day religious festival. The results of various what-if scenarios have been compared against the current location of services. A major argument is that planners should be flexible and locate facilities at different locations throughout the day and night. The use of location-allocation models in this type of comparative static mode has rarely been operationalised in the literature. Second, we model pilgrim movements and behaviours along with the most crowded parts of the network. This has been modelled using an agent-based model. This model allows planners to understand the key bottlenecks in the network and at what usage levels the paths become critically congested. Thus the paper has important implications and recommendations for future disaster planning strategies. This will enable planners to see at what stage in the movements of pilgrims problems occur in terms of potential crushes and trampling incidents. The main application of this research was only customised for pedestrians as the concentration only for pedestrians who move to Jamarat via foot. Further, the network in the middle of Mina was only dedicated for pedestrians for safety, so no Buses, trains and private cars were allowed in this area to prevent the congestion within this network. Initially, this research focus on Mina city as ‘temporary city’ and also about service provision in temporary cities, which is not highlighted in literature so far. Further, it is the first study which use the dynamic demand to optimise the services in the case of day and night time. Moreover, it is the first study which link the location allocation model for optimising services with ABM to find out whether or not the service location is located in the proper location in which it’s not affecting on crowd movement in mainstream flow where some pilgrims need to have health services.

Keywords: ABM, crowd management, hajj, temporary city

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21354 Thermal and Mechanical Finite Element Analysis of a Mineral Casting Machine Frame

Authors: H. Zou, B. Wang

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Thermal distortion of the machine tool plays a critical role in its machining accuracy. This study investigates the thermal performance of a high-precision machine frame with future-oriented mineral casting components. A thermo-mechanical finite element model (FEM) was established to evaluate the thermal behavior of the frame under environmental thermal fluctuations. The validity of the presented FEM model was confirmed experimentally by a series of laser interferometer tests. Good agreement between numerical and experimental results demonstrates that the proposed model can accurately predict the thermal deformation of the frame with thermo-mechanical coupling effect. The results also show that keeping the workshop in thermally stable conditions is crucial for improving the machine accuracy of the system with large scale components. The goal of this paper is to investigate the feasibility of innovative mineral casting material applied in high-precision drilling machine and to provide a strategy for machine tool industry seeking a perfect substitute for classic frame materials such as cast iron and granite.

Keywords: thermo-mechanical model, finite element method, laser interferometer, mineral casting frame

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21353 Evaluating Health-Related Quality of Life of Lost to Follow-Up Tuberculosis Patients in Yemen

Authors: Ammar Ali Saleh Jaber, Amer Hayat Khan, Syed Azhar Syed Sulaiman

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Tuberculosis (TB) is considered as a major disease that affects daily activities and impairs health-related quality of life (HRQoL). The impact of TB on HRQoL can affect treatment outcome and may lead to treatment defaulting. Therefore, this study aims to evaluate the HRQoL of TB treatment lost to follow-up during and after treatment in Yemen. For this aim, this prospective study enrolled a total of 399 TB lost to follow-up patients between January 2011 and December 2015. By applying HRQoL criteria, only 136 fill the survey during treatment. Moreover, 96 were traced and fill out the HRQoL survey. All eight HRQol domains were categorized into the physical component score (PCS) and mental component score (MCS), which were calculated using QM scoring software. Results show that all lost to follow-up TB patients reported a score less than 47 for all eight domains, except general health (67.3) during their treatment period. Low scores of 27.9 and 29.8 were reported for emotional role limitation (RE) and mental health (MH), respectively. Moreover, the mental component score (MCS) was found to be only 28.9. The trace lost follow-up shows a significant improvement in all eight domains and a mental component score of 43.1. The low scores of 27.9 and 29.8 for role emotion and mental health, respectively, in addition to the MCS score of 28.9, show that severe emotional condition and reflect the higher depression during treatment period that can result to lost to follow-up. The low MH, RE, and MCS can be used as a clue for predicting future TB treatment lost to follow-up.

Keywords: Yemen, tuberculosis, health-related quality of life, Khat

Procedia PDF Downloads 173