Search results for: International Service Learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13226

Search results for: International Service Learning

5666 A Data-Driven Compartmental Model for Dengue Forecasting and Covariate Inference

Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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5665 Protection Not Punishment: Use of Electronic Monitoring to Reduce the Risk of Cross-Border Parental Child Abduction

Authors: Nazia Yaqub

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Globally, the number of cases of international parental child abduction has remained consistent in the past decade despite the legal provision designed to prevent and deter abduction, and so it appears the current legal approach to prevent abduction is lacking. Reflecting on the findings of an empirical study conducted by the author between 2017-19 on parental abduction from the UK, the article considers a solution to the predicament of protecting children at risk of abduction through electronic monitoring. The electronic monitoring of children has negative connotations, particularly in its use in the criminal justice system, yet in the context of family law proceedings, the article considers whether electronic monitoring could serve a protective rather than a punitive purpose. The article reflects on the use of electronic monitoring in parental abduction cases by the Family Courts and examines the ethical considerations of the proposal, drawing on the rights found in the European Convention on Human Rights and the UN Convention on the Rights of the Child.

Keywords: law, parental child abduction, electronic monitoring, legal solutions

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5664 Neural Networks Models for Measuring Hotel Users Satisfaction

Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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5663 Gender Policy in Nigeria: Implications for Sustainable Development in the Fourth Republic

Authors: Adadu Yahaya, Abdullahi Erunke Canice

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The study sets out to examine the interface that tends to exist in the relationship between gender policy and Nigeria’s socio-economic development. Despite Nigeria’s ratification of virtually all international instruments on the protection and promotion of gender rights and equality, it appears that the practice is honored in the breach than in observance; hence, these policies have not been adequately domesticated and implemented. The implication of this is that the women folks have generally been isolated from mainstream politics and their political rights and privileges truncated in the scheme of things. The paper observes that gender inequality and marginalization in Nigeria has practically occasioned the unwholesome subjugation of Nigerian women to the background, hence poses more critical questions and challenges to the national question. The consequence of this, to this paper, is that Nigeria’s development process will be adversely affected if this trend is not checked. The paper sums up with appropriate policy options which are believed to have the potentials of giving women the right pride of place in the socio-economic and political dynamics in the 21st century Nigeria and beyond.

Keywords: development, equality, gender, policy

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5662 The Experience of the Prosthetics Program in Palestine Arab American University as Model

Authors: Ahmad Dawabsheh

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The prosthetics program is an international program, found in honorable respectable universities. This program like other programs was found to serve several reasons, The most important reason is humanity, humanity free of conflict, religion, race, or war, but rather focuses on the humanitarian issue. This is what encouraged me to study this topic to help people, especially the poor in the world. The researcher will distribute a questionnaire to the faculty members and students of the department to measure the knowledge and importance of this program from the practical and theoretical sides of the local community. The researcher used the analytical method to study the subject. The research will attempt to answer the questions: What is the student's knowledge of this program? How important is this program to society?. The research aims to know the Palestinian society's need for this program. The research also aims to know the extent of students' knowledge of recent developments and new innovations in prosthetics around the world. What does the university offer to students in addition to theoretical courses?

Keywords: prosthetics, Arab American University, analytical method, questionnair

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5661 Researching International PhD Algerian Students’ Communication Challenges in Speaking When Discussing and Interacting with Their British Peers: A Researcher’s Interpretive Perspective through the Use of Semi-Structured Interview

Authors: H. Maita

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This paper addresses the issue of the speaking challenges that the Algerian PhD students experience during their studies abroad, particularly in UK territory; more specifically, this study describes how these students may deal with such challenges and whether the cultural differences is one core reason in such dilemma or not. To this end, an understanding and interpretation of what actually encompasses both linguistic interference and cultural differences are required. Throughout the paper there is an attempt to explain the theoretical basis of the interpretive research and to theoretically discuss the pivotal use of the interview, as a data collection tool, in interpretive research. Thus, the central issue of this study is to frame the theoretical perspective of the interpretive research through the discussion of PhD Algerian’s communication and interaction challenges in the EFL context. This study is a corner stone for other research studies to further investigate the issue related to communication challenges because no specific findings will be pointed out in this research.

Keywords: communication, EFL, interaction, linguistic interference

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5660 Inequality and Poverty Assessment on Affordable Housing in Austria: A Comprehensive Perspective on SDG 1 and SDG 10 (UniNEtZ Project)

Authors: M. Bukowski, K. Kreissl

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Social and environmental pressures in our times bear threats that often cross-border in scale, such as climate change, poverty-driven migration, demographic change as well as socio-economic developments. One of the hot topics is prevailing in many societies across Europe and worldwide, concerns 'affordable housing' and poverty-driven international and domestic migration (including displacements through gentrification processes), focusing here on the urban and regional context. The right to adequate housing and shelter is one of the recognized in the Universal Declaration of Human rights and International Covenant on Economic, Social and Cultural Rights, and as such considered as a human right of the second generation. The decreasing supply of affordable housing, especially in urban areas, has reached dimensions that have led to an increasing 'housing crisis'. This crisis, which has even reached middle-income homes, has an even more devastating impact on low income and poor households raising poverty levels. Therefore, the understanding of the connection between housing and poverty is vital to integrate and support the different stakeholders in order to tackle poverty. When it comes to issues of inequalities and poverty within the SDG framework, multi-faceted stakeholders with different claims, distribution of resources and interactions with other development goals (spill-over and trade-offs) account for a highly complex context. To contribute to a sustainable and fair society and hence to support the UN Sustainable Development Goals, the University of Salzburg participates in the Austrian-wide universities' network 'UniNEtZ'. Our joint target is to develop an options report for the Austrian Government regarding the seventeen SDGs, so far hosted by 18 Austrian universities. In this vein, the University of Salzburg; i.e., the Centre for Ethics and Poverty Research, the departments of Geography and Geology and the Department of Sociology and Political Science are focusing on the SDG 1 (No Poverty) and SDG 10 (Reduced Inequalities). Our target and research focus is to assess and evaluate the status of SDG 1 and 10 in Austria, to find possible solutions and to support stakeholders' integration. We aim at generating and deducing appropriate options as scientific support, from interdisciplinary research studies to 'Sustainability Developing Goals and their Targets' in action. For this reason, and to deal with the complexity of the Agenda 2030, we have developed a special Model for Inequalities and Poverty Assessment (IPAM). Through the example of 'affordable housing' we provide insight into the situation focusing on sustainable outcomes, including ethical and justice perceptions. The IPAM has proven to be a helpful tool in detecting the different imponderables on the Agenda 2030, assessing the situation, showing gaps and options for ethical SDG actions combining different SDG targets. Supported by expert and expert group interviews, this assessment allows different stakeholders to overview a complex and dynamic SDG challenge (here housing) which is necessary to be involved in an action finding process.

Keywords: affordable housing, inequality, poverty, sustainable development goals

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5659 A Proposal to Integrate Spatially Explicit Ecosystem Services with Urban Metabolic Modelling

Authors: Thomas Elliot, Javier Babi Almenar, Benedetto Rugani

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The integration of urban metabolism (UM) with spatially explicit ecosystem service (ES) stocks has the potential to advance sustainable urban development. It will correct the lack of spatially specificity of current urban metabolism models. Furthermore, it will include into UM not only the physical properties of material and energy stocks and flows, but also the implications to the natural capital that provides and maintains human well-being. This paper presents the first stages of a modelling framework by which urban planners can assess spatially the trade-offs of ES flows resulting from urban interventions of different character and scale. This framework allows for a multi-region assessment which takes into account sustainability burdens consequent to an urban planning event occurring elsewhere in the environment. The urban boundary is defined as the Functional Urban Audit (FUA) method to account for trans-administrative ES flows. ES are mapped using CORINE land use within the FUA. These stocks and flows are incorporated into a UM assessment method to demonstrate the transfer and flux of ES arising from different urban planning implementations.

Keywords: ecological economics, ecosystem services, spatial planning, urban metabolism

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5658 A Convolution Neural Network PM-10 Prediction System Based on a Dense Measurement Sensor Network in Poland

Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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5657 The Impact of Interrelationship between Business Intelligence and Knowledge Management on Decision Making Process: An Empirical Investigation of Banking Sector in Jordan

Authors: Issa M. Shehabat, Huda F. Y. Nimri

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This paper aims to study the relationship between knowledge management in its processes, including knowledge creation, knowledge sharing, knowledge organization, and knowledge application, and business intelligence tools, including OLAP, data mining, and data warehouse, and their impact on the decision-making process in the banking sector in Jordan. A total of 200 questionnaires were distributed to the sample of the study. The study hypotheses were tested using the statistical package SPSS. Study findings suggest that decision-making processes were positively related to knowledge management processes. Additionally, the components of business intelligence had a positive impact on decision-making. The study recommended conducting studies similar to this study in other sectors such as the industrial, telecommunications, and service sectors to contribute to enhancing understanding of the role of the knowledge management processes and business intelligence tools.

Keywords: business intelligence, knowledge management, decision making, Jordan, banking sector

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5656 Comparing Community Health Agents, Physicians and Nurses in Brazil's Family Health Strategy

Authors: Rahbel Rahman, Rogério Meireles Pinto, Margareth Santos Zanchetta

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Background: Existing shortcomings of current health-service delivery include poor teamwork, competencies that do not address consumer needs, and episodic rather than continuous care. Brazil’s Sistema Único de Saúde (Unified Health System, UHS) is acknowledged worldwide as a model for delivering community-based care through Estratégia Saúde da Família (FHS; Family Health Strategy) interdisciplinary teams, comprised of Community Health Agents (in Portuguese, Agentes Comunitário de Saude, ACS), nurses, and physicians. FHS teams are mandated to collectively offer clinical care, disease prevention services, vector control, health surveillance and social services. Our study compares medical providers (nurses and physicians) and community-based providers (ACS) on their perceptions of work environment, professional skills, cognitive capacities and job context. Global health administrators and policy makers can leverage on similarities and differences across care providers to develop interprofessional training for community-based primary care. Methods: Cross-sectional data were collected from 168 ACS, 62 nurses and 32 physicians in Brazil. We compared providers’ demographic characteristics (age, race, and gender) and job context variables (caseload, work experience, work proximity to community, the length of commute, and familiarity with the community). Providers perceptions were compared to their work environment (work conditions and work resources), professional skills (consumer-input, interdisciplinary collaboration, efficacy of FHS teams, work-methods and decision-making autonomy), and cognitive capacities (knowledge and skills, skill variety, confidence and perseverance). Descriptive and bi-variate analysis, such as Pearson Chi-square and Analysis of Variance (ANOVA) F-tests, were performed to draw comparisons across providers. Results: Majority of participants were ACS (64%); 24% nurses; and 12% physicians. Majority of nurses and ACS identified as mixed races (ACS, n=85; nurses, n=27); most physicians identified as males (n=16; 52%), and white (n=18; 58%). Physicians were less likely to incorporate consumer-input and demonstrated greater decision-making autonomy than nurses and ACS. ACS reported the highest levels of knowledge and skills but the least confidence compared to nurses and physicians. ACS, nurses, and physicians were efficacious that FHS teams improved the quality of health in their catchment areas, though nurses tend to disagree that interdisciplinary collaboration facilitated their work. Conclusion: To our knowledge, there has been no study comparing key demographic and cognitive variables across ACS, nurses and physicians in the context of their work environment and professional training. We suggest that global health systems can leverage upon the diverse perspectives of providers to implement a community-based primary care model grounded in interprofessional training. Our study underscores the need for in-service trainings to instill reflective skills of providers, improve communication skills of medical providers and curative skills of ACS. Greater autonomy needs to be extended to community based providers to offer care integral to addressing consumer and community needs.

Keywords: global health systems, interdisciplinary health teams, community health agents, community-based care

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5655 School Students’ Career Guidance in the Context of Inclusive Education in Kazakhstan: Experience and Perspectives

Authors: Laura Butabayeva, Svetlana Ismagulova, Gulbarshin Nogaibayeva, Maiya Temirbayeva, Aidana Zhussip

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The article presents the main results of the study conducted within the grant project Organizational and methodological foundations for ensuring the inclusiveness of school students’ career guidance. The main aim of the Project is to study the issue of the absence of developed mechanisms, coordinating the activities of all stakeholders in preparing school students for conscious career choice, considering their individual opportunities and special educational needs. To achieve the aim of the Project, according to the implementation plan, the analysis of foreign and national literature on the studied problem, as well as the study of the state of school students’ career guidance and their socialization in the context of inclusive education were conducted, the international experience on this issue was explored. The analysis of the national literature conducted by the authors has shown the State’s annual increase in the number of students with special educational needs as well as the rapid demand of the labor market, influencing their professional self-determination in modern society. The participants from 5 State regions, including students, their parents, general secondary schools’ administration, and educators, as well as employers, took part in the study, considering the geographical location: south, north, west, center and the cities of republican significance. To ensure the validity of the study’s results, the triangulation method was utilized, including both qualitative and quantitative methods. The data were analyzed independently and compared with each other. Ethical principles were considered during all stages of the study. The characteristics of the system of career guidance in the modern school, the role, and the involvement of stakeholders in the system of career guidance, the opinions of educators on school students’ preparedness for career choice, and the factors impeding the effectiveness of career guidance in schools were examined. The problem of stakeholders’ disunity and inconsistency, causing the systemic labor market distortions, the growth of low-skilled labor and the unemployed, including people with special educational needs, were revealed. The other issue identified by the researchers was educators’ insufficient readiness for students’ career choice preparation in the context of inclusive education. To study cutting-edge experience in organizing a system of career guidance for young people and develop mechanisms coordinating the actions of all stakeholders in preparing students for career choice, the institutions of career guidance in France, Japan, and Germany were explored by the researchers. To achieve the aim of the Project, the systemic innovative Model of school students’ professional self-determination, considering their individual opportunities and special educational needs, has been developed based on the study results and international experience. The main principles of this Model are consistency, accessibility, inclusiveness, openness, coherence, and continuity. The perspectives of students’ career guidance development in the context of inclusive education have been suggested.

Keywords: career guidance, inclusive education, special educational needs, psychological and pedagogical support, model of school students’ professional self-determination

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5654 An ANOVA-based Sequential Forward Channel Selection Framework for Brain-Computer Interface Application based on EEG Signals Driven by Motor Imagery

Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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5653 Tertiary Training of Future Health Educators and Health Professionals Involved in Childhood Obesity Prevention and Treatment Strategies

Authors: Thea Werkhoven, Wayne Cotton

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Adult and childhood rates of obesity in Australia are health concerns of high national priority, retaining epidemic status in the populations affected. Attempts to prevent further increases in prevalence of childhood obesity in the population aged below eighteen years have had varied success. A multidisciplinary approach has been used, employing strategies in schools, through established health care system usage and public health campaigns. Over the last decade a plateau in prevalence has been reached in the youth population afflicted by obesity and interest has peaked in school based strategies to prevent and treat overweight and obesity. Of interest to this study is the importance of the tertiary training of future health educators or health professionals destined to be involved in obesity prevention and treatment strategies. Health educators and health professionals are considered instrumental to the success of prevention and treatment strategies, required to possess sufficient and accurate knowledge in order to be effective in their positions. A common influence on the success of school based health promoting activities are the weight based attitudes possessed by health educators, known to be negative and biased towards overweight or obese children during training and practice. Whilst the tertiary training of future health professionals includes minimal nutrition education, there is no mandatory training in health education or nutrition for pre-service health educators in Australian tertiary institutions. This study aimed to assess the impact of a pedagogical intervention on pre-service health educators and health professionals enrolled in a health and wellbeing elective. The intervention aimed to increase nutrition knowledge and decrease weight bias and was embedded in the twelve week elective. Participants (n=98) were tertiary students at a major Australian University who were enrolled in health (47%) and non-health related degrees (53%). A quantitative survey using four valid and reliable instruments was conducted to measured nutrition knowledge, antifat attitudes and weight stereotyping attitudes at baseline and post-intervention. Scores on each instrument were compared between time points to check if they had significantly changed and to determine the effect of the intervention on attitudes and knowledge. Antifat attitudes at baseline were considered low and decreased further over the course of the intervention. Scores representing weight bias did decrease but the change was not significant. Fat stereotyping attitudes became stronger over the course of the intervention and this change was significant. Nutrition knowledge significantly improved from baseline to post-intervention. The design of the nutrition knowledge and attitude amelioration content of the intervention was semi-successful in achieving its outcomes. While the level of nutrition knowledge was improved over the course of the intervention, an unintentional increase was observed in weight based prejudice which is known to occur in interventions that employ stigma reduction methodologies. Further research is required into a structured methodology that increases level of nutrition knowledge and ameliorates weight bias at the tertiary level. In this way training provided would help prepare future health educators with the knowledge, skills and attitudes required to be effective and bias free in their practice.

Keywords: education, intervention, nutrition, obesity

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5652 A Study on the Relation between Auditor Rotation and Audit Quality in Iranian Firms

Authors: Bita Mashayekhi, Marjan Fayyazi, Parisa Sefati

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Audit quality is a popular topic in accounting and auditing research because recent decades’ financial crises reduce the reliability of financial reports to public investors and cause significant doubt about the audit profession. Therefore, doing research to identify effective factors in improving audit quality is necessary for bringing back public investors’ trust to financial statements as well as audit reports. In this study, we explore the relationship between audit rotation and audit quality. For this purpose, we employ the Duff (2009) model of audit quality to measure audit quality and use a questionnaire survey of 27 audit service quality attributes. Our results show that there is a negative relationship between auditor’s rotation and audit quality as we consider the auditor’s reputation, capability, assurance, experience, and responsiveness as surrogates for audit quality. There is no evidence for verifying a same relationship when we use the auditor’s independence and expertise for measuring audit quality.

Keywords: audit quality, auditor’s rotation, reputation, capability, assurance, experience, responsiveness, independence, expertise

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5651 Learning the History of a Tuscan Village: A Serious Game Using Geolocation Augmented Reality

Authors: Irene Capecchi, Tommaso Borghini, Iacopo Bernetti

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An important tool for the enhancement of cultural sites is serious games (SG), i.e., games designed for educational purposes; SG is applied in cultural sites through trivia, puzzles, and mini-games for participation in interactive exhibitions, mobile applications, and simulations of past events. The combination of Augmented Reality (AR) and digital cultural content has also produced examples of cultural heritage recovery and revitalization around the world. Through AR, the user perceives the information of the visited place in a more real and interactive way. Another interesting technological development for the revitalization of cultural sites is the combination of AR and Global Positioning System (GPS), which integrated have the ability to enhance the user's perception of reality by providing historical and architectural information linked to specific locations organized on a route. To the author’s best knowledge, there are currently no applications that combine GPS AR and SG for cultural heritage revitalization. The present research focused on the development of an SG based on GPS and AR. The study area is the village of Caldana in Tuscany, Italy. Caldana is a fortified Renaissance village; the most important architectures are the walls, the church of San Biagio, the rectory, and the marquis' palace. The historical information is derived from extensive research by the Department of Architecture at the University of Florence. The storyboard of the SG is based on the history of the three characters who built the village: marquis Marcello Agostini, who was commissioned by Cosimo I de Medici, Grand Duke of Tuscany, to build the village, his son Ippolito and his architect Lorenzo Pomarelli. The three historical characters were modeled in 3D using the freeware MakeHuman and imported into Blender and Mixamo to associate a skeleton and blend shapes to have gestural animations and reproduce lip movement during speech. The Unity Rhubarb Lip Syncer plugin was used for the lip sync animation. The historical costumes were created by Marvelous Designer. The application was developed using the Unity 3D graphics and game engine. The AR+GPS Location plugin was used to position the 3D historical characters based on GPS coordinates. The ARFoundation library was used to display AR content. The SG is available in two versions: for children and adults. the children's version consists of finding a digital treasure consisting of valuable items and historical rarities. Players must find 9 village locations where 3D AR models of historical figures explaining the history of the village provide clues. To stimulate players, there are 3 levels of rewards for every 3 clues discovered. The rewards consist of AR masks for archaeologist, professor, and explorer. At the adult level, the SG consists of finding the 16 historical landmarks in the village, and learning historical and architectural information interactively and engagingly. The application is being tested on a sample of adults and children. Test subjects will be surveyed on a Likert scale to find out their perceptions of using the app and the learning experience between the guided tour and interaction with the app.

Keywords: augmented reality, cultural heritage, GPS, serious game

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5650 Order Fulfilment Strategy in E-Commerce Warehouse Based on Simulation: Business Customers Case

Authors: Aurelija Burinskiene

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This paper presents the study for an e-commerce warehouse. The study is aiming to improve order fulfillment activity by identifying the strategy presenting the best performance. A simulation model was proposed to reach the target of this research. This model enables various scenario tests in an e-commerce warehouse, allowing them to find out for the best order fulfillment strategy. By using simulation, model authors investigated customers’ orders representing on-line purchases for one month. Experiments were designed to evaluate various order picking methods applicable to the fulfillment of customers’ orders. The research uses cost components analysis and helps to identify the best possible order picking method improving the overall performance of e-commerce warehouse and fulfillment service to the customers. The results presented show that the application of order batching strategy is the most applicable because it brings distance savings of around 6.7 percentage. This result could be improved by taking an assortment clustering action until 8.34 percentage. So, the recommendations were given to apply the method for future e-commerce warehouse operations.

Keywords: e-commerce, order, fulfilment, strategy, simulation

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5649 Preliminary Study on the Removal of Solid Uranium Compound in Nuclear Fuel Production System

Authors: Bai Zhiwei, Zhang Shuxia

Abstract:

By sealing constraint, the system of nuclear fuel production penetrates a trace of air in during its service. The vapor in the air can react with material in the system and generate solid uranium compounds. These solid uranium compounds continue to accumulate and attached to the production equipment and pipeline of system, which not only affects the operation reliability of production equipment and give off radiation hazard as well after system retired. Therefore, it is necessary to select a reasonable method to remove it. Through the analysis of physicochemical properties of solid uranium compounds, halogenated fluoride compounds are selected as a cleaning agent, which can remove solid uranium compounds effectively. This paper studied the related chemical reaction under the condition of static test and results show that the selection of high fluoride halogen compounds can be removed solid uranium compounds completely. The study on the influence of reaction pressure with the reaction rate discovered a phenomenon that the higher the pressure, the faster the reaction rate.

Keywords: fluoride halogen compound, remove, radiation, solid uranium compound

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5648 Influence of Extractives Leaching from Larch Wood on Durability of Semi-Transparent Oil-Based Coating during Accelerated Weathering

Authors: O. Dvorak, M. Panek, E. Oberhofnerova, I. Sterbova

Abstract:

Extractives contained in larch wood (Larix decidua, Mill.) reduce the service-life of exterior coating systems, especially transparent and semi-transparent. The aim of this work was to find out whether the initial several-week leaching of extractives from untreated wood in the exterior will positively affect the selected characteristics and the overall life of the semi-transparent oil-based coating. Samples exposed to exterior leaching for 10 or 20 weeks, and the reference samples without leaching were then treated with a coating system. Testing was performed by the method of artificial accelerated weathering in the UV chamber combined with thermal cycling during 6 weeks. The changes of colour, gloss, surface wetting, microscopic analyses of surfaces, and visual damage of paint were evaluated. Only 20-week initial leaching had a positive effect. Both to increase the color stability during aging, but also to slightly increase the overall life of the tested semi-transparent coating system on larch wood.

Keywords: larch wood, coating, durability. extractives

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5647 Manufacturing Process of Rubber Cement Composite Paver Block

Authors: Ratnadip Natwarbhai Bhoi

Abstract:

The objective of this research paper is to study waste tire crumb rubber granules as a partial concrete replacement by the different percentages of facing layer thickness and without facing layer in the production of rubber cement composite paver block. The physical properties of RCCRP compressive strength, flexural strength, abrasion strength density, and water absorption testing by the IS 15658:2006 method. All these physical properties depend upon the ratio of crumb rubber uses. The result showed that the with facing layer at 15 mm, 25 mm, totally rubberized and without facing layer had little effect on compressive strength, flexural strength and abrasion resistance properties. Water absorption is also important for the service life of the product. The crumb rubber paver block also performed quite well in both compressive strength and abrasion resistance. The rubber cement composite rubber paver block is suitable for nonstructural purposes, such as being lightweight and easy installation for the walkway, sidewalks, and playing area applications.

Keywords: rubber cement, crumb rubber, composite, layer

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5646 An Image Based Visual Servoing (IBVS) Approach Using a Linear-Quadratic Regulator (LQR) for Quadcopters

Authors: C. Gebauer, C. Henke, R. Vossen

Abstract:

Within the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2020, a team of unmanned aerial vehicles (UAV) is used to capture intruder drones by physical interaction. The challenge is motivated by UAV safety. The purpose of this work is to investigate the agility of a quadcopter being controlled visually. The aim is to track and follow a highly dynamic target, e.g., an intruder quadcopter. The following is realized in close range and the opponent has a velocity of up to 10 m/s. Additional limitations are given by the hardware itself, where only monocular vision is present, and no additional knowledge about the targets state is available. An image based visual servoing (IBVS) approach is applied in combination with a Linear Quadratic Regulator (LQR). The IBVS is integrated into the LQR and an optimal trajectory is computed within the projected three-dimensional image-space. The approach has been evaluated on real quadcopter systems in different flight scenarios to demonstrate the system's stability.

Keywords: image based visual servoing, quadcopter, dynamic object tracking, linear-quadratic regulator

Procedia PDF Downloads 124
5645 MEAL Project–Modifying Eating Attitudes and Actions through Learning

Authors: E. Oliver, A. Cebolla, A. Dominguez, A. Gonzalez-Segura, E. de la Cruz, S. Albertini, L. Ferrini, K. Kronika, T. Nilsen, R. Baños

Abstract:

The main objective of MEAL is to develop a pedagogical tool aimed to help teachers and nutritionists (students and professionals) to acquire, train, promote and deliver to children basic nutritional education and healthy eating behaviours competencies. MEAL is focused on eating behaviours and not only in nutritional literacy, and will use new technologies like Information and Communication Technologies (ICTs) and serious games (SG) platforms to consolidate the nutritional competences and habits.

Keywords: nutritional education, pedagogical ICT platform, serious games, training course

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5644 Characterization of the Music Admission Requirements and Evaluation of the Relationship among Motivation and Performance Achievement

Authors: Antonio M. Oliveira, Patricia Oliveira-Silva, Jose Matias Alves, Gary McPherson

Abstract:

The music teaching is oriented towards offering formal music training. Due to its specificities, this vocational program starts at a very young age. Although provided by the State, the offer is limited to 6 schools throughout the country, which means that the vacancies for prospective students are very limited every year. It is therefore crucial that these vacancies be taken by especially motivated children grown within households that offer the ideal setting for success. Some of the instruments used to evaluate musical performance are highly sensitive to specific previous training, what represents a severe validity problem for testing children who have had restricted opportunities for formal training. Moreover, these practices may be unfair because, for instance, they may not reflect the candidates’ music aptitudes. Based on what constitutes a prerequisite for making an excellent music student, researchers in this field have long argued that motivation, task commitment, and parents’ support are as important as ability. Thus, the aim of this study is: (1) to prepare an inventory of admission requirements in Australia, Portugal and Ireland; (2) to examine whether the candidates to music conservatories and parents’ level of motivation, assessed at three evaluation points (i.e., admission, at the end of the first year, and at the end of the second year), correlates positively with the candidates’ progress in learning a musical instrument (i.e., whether motivation at the admission may predict student musicianship); (3) an adaptation of an existing instrument to assess the motivation (i.e., to adapt the items to the music setting, focusing on the motivation for playing a musical instrument). The inclusion criteria are: only children registered in the administrative services to be evaluated for entrance to the conservatory will be accepted for this study. The expected number of participants is fifty (5-6 years old) in all the three frequency schemes: integrated, articulated and supplementary. Revisiting musical admission procedures is of particular importance and relevance to musical education because this debate may bring guidance and assistance about the needed improvement to make the process of admission fairer and more transparent.

Keywords: music learning, music admission requirements, student’s motivation, parent’s motivation

Procedia PDF Downloads 142
5643 The Role of Youth Entrepreneurship in Developing the Algerian Economy

Authors: Benabdelaziz Soufyane

Abstract:

The process of developing the activity of small and medium-sized enterprises(SME), and increasing the entrepreneurial sense, is becoming at the current period as one of the main bets, where many countries around the world try to give it the great importance because of their positive role in improving the economic development indicators in these countries. As a result of the sequential changes that international economic environment lives, the biggest global economic entities has become threatened because of different secretions financial crises and economic disorders. For this lots of countries tended to search for a mechanism to help it for creating new jobs and to spur the economy in order to face the foreign competition, fot this, we find the process of creating innovative entrepreneurial activity comes at the forefront of solutions for the purpose of achieving that. For the purpose of highlighting the role of this process and its future in the economy, this study seeks to consolidate the innovation’s concept and innovative entrepreneurship, then the success’s conditions of these entrepreneurships, to conclude with recommendations , solutions and important results.

Keywords: entrepreneurship, innovation, performance, vigilance, modernity, technology, business incubators

Procedia PDF Downloads 55
5642 Embodied Cognition as a Concept of Educational Neuroscience and Phenomenology

Authors: Elham Shirvani-Ghadikolaei

Abstract:

In this paper, we examine the connection between the human mind and body within the framework of Merleau-Ponty's phenomenology. We study the role of this connection in designing more efficient learning environments, alongside the findings in physical recognition and educational neuroscience. Our research shows the interplay between the mind and the body in the external world and discusses its implications. Based on these observations, we make suggestions as to how the educational system can benefit from taking into account the interaction between the mind and the body in educational affairs.

Keywords: educational neurosciences, embodied cognition, pedagogical neurosciences, phenomenology

Procedia PDF Downloads 287
5641 Using Textual Pre-Processing and Text Mining to Create Semantic Links

Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

Abstract:

This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: semantic links, data mining, linked data, SKOS

Procedia PDF Downloads 148
5640 Physics-Informed Neural Network for Predicting Strain Demand in Inelastic Pipes under Ground Movement with Geometric and Soil Resistance Nonlinearities

Authors: Pouya Taraghi, Yong Li, Nader Yoosef-Ghodsi, Muntaseer Kainat, Samer Adeeb

Abstract:

Buried pipelines play a crucial role in the transportation of energy products such as oil, gas, and various chemical fluids, ensuring their efficient and safe distribution. However, these pipelines are often susceptible to ground movements caused by geohazards like landslides, fault movements, lateral spreading, and more. Such ground movements can lead to strain-induced failures in pipes, resulting in leaks or explosions, leading to fires, financial losses, environmental contamination, and even loss of human life. Therefore, it is essential to study how buried pipelines respond when traversing geohazard-prone areas to assess the potential impact of ground movement on pipeline design. As such, this study introduces an approach called the Physics-Informed Neural Network (PINN) to predict the strain demand in inelastic pipes subjected to permanent ground displacement (PGD). This method uses a deep learning framework that does not require training data and makes it feasible to consider more realistic assumptions regarding existing nonlinearities. It leverages the underlying physics described by differential equations to approximate the solution. The study analyzes various scenarios involving different geohazard types, PGD values, and crossing angles, comparing the predictions with results obtained from finite element methods. The findings demonstrate a good agreement between the results of the proposed method and the finite element method, highlighting its potential as a simulation-free, data-free, and meshless alternative. This study paves the way for further advancements, such as the simulation-free reliability assessment of pipes subjected to PGD, as part of ongoing research that leverages the proposed method.

Keywords: strain demand, inelastic pipe, permanent ground displacement, machine learning, physics-informed neural network

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5639 Adjuvant Effect and Mineral Addition in Aggressive Environments on the Sustainability of Using Local Materials Concretes

Authors: M. Belouadah, S. Rahmouni, N. Teballe

Abstract:

The durability of concrete is not one of its features, but its response to service loads and environmental conditions. Thus, the durability of concrete depends on a variety of material characteristics, but also the aggressiveness of the environment. Much durability problems encountered in tropical regions (region M'sila) due to the presence of chlorides and sulfates (in the ground or in the aggregate) with the additional aggravation of the effect of hot weather and arid. This lack of sustainability has a direct influence on the structure of the building and can lead to the complete deterioration of many buildings. The characteristics of the nature of fillers are evaluated based on the degree of aggressiveness of the environment considering as a means of characterization: mechanical strength, porosity. Specimens will be exposed to different storage media chemically aggressive drinking water, salts and sulfates (sodium chloride, MgSO4), solutions are not renewed or PH control solutions. The parameters taken into account are: age, the nature and degree of aggressiveness of the environment conservation, the incorporation of adjuvant type superplasticizer dosage and mineral additives.

Keywords: ordinary concretes, marble powder fillers, adjuvant, strength

Procedia PDF Downloads 256
5638 Applying an Automatic Speech Intelligent System to the Health Care of Patients Undergoing Long-Term Hemodialysis

Authors: Kuo-Kai Lin, Po-Lun Chang

Abstract:

Research Background and Purpose: Following the development of the Internet and multimedia, the Internet and information technology have become crucial avenues of modern communication and knowledge acquisition. The advantages of using mobile devices for learning include making learning borderless and accessible. Mobile learning has become a trend in disease management and health promotion in recent years. End-stage renal disease (ESRD) is an irreversible chronic disease, and patients who do not receive kidney transplants can only rely on hemodialysis or peritoneal dialysis to survive. Due to the complexities in caregiving for patients with ESRD that stem from their advanced age and other comorbidities, the patients’ incapacity of self-care leads to an increase in the need to rely on their families or primary caregivers, although whether the primary caregivers adequately understand and implement patient care is a topic of concern. Therefore, this study explored whether primary caregivers’ health care provisions can be improved through the intervention of an automatic speech intelligent system, thereby improving the objective health outcomes of patients undergoing long-term dialysis. Method: This study developed an automatic speech intelligent system with healthcare functions such as health information voice prompt, two-way feedback, real-time push notification, and health information delivery. Convenience sampling was adopted to recruit eligible patients from a hemodialysis center at a regional teaching hospital as research participants. A one-group pretest-posttest design was adopted. Descriptive and inferential statistics were calculated from the demographic information collected from questionnaires answered by patients and primary caregivers, and from a medical record review, a health care scale (recorded six months before and after the implementation of intervention measures), a subjective health assessment, and a report of objective physiological indicators. The changes in health care behaviors, subjective health status, and physiological indicators before and after the intervention of the proposed automatic speech intelligent system were then compared. Conclusion and Discussion: The preliminary automatic speech intelligent system developed in this study was tested with 20 pretest patients at the recruitment location, and their health care capacity scores improved from 59.1 to 72.8; comparisons through a nonparametric test indicated a significant difference (p < .01). The average score for their subjective health assessment rose from 2.8 to 3.3. A survey of their objective physiological indicators discovered that the compliance rate for the blood potassium level was the most significant indicator; its average compliance rate increased from 81% to 94%. The results demonstrated that this automatic speech intelligent system yielded a higher efficacy for chronic disease care than did conventional health education delivered by nurses. Therefore, future efforts will continue to increase the number of recruited patients and to refine the intelligent system. Future improvements to the intelligent system can be expected to enhance its effectiveness even further.

Keywords: automatic speech intelligent system for health care, primary caregiver, long-term hemodialysis, health care capabilities, health outcomes

Procedia PDF Downloads 92
5637 Assessment Literacy Levels of Mathematics Teachers to Implement Classroom Assessment in Ghanaian High Schools

Authors: Peter Akayuure

Abstract:

One key determinant of the quality of mathematics learning is the teacher’s ability to assess students adequately and effectively and make assessment an integral part of the instructional practices. If the mathematics teacher lacks the required literacy to perform classroom assessment roles, the true trajectory of learning success and attainment of curriculum expectations might be indeterminate. It is therefore important that educators and policymakers understand and seek ways to improve the literacy level of mathematics teachers to implement classroom assessments that would meet curriculum demands. This study employed a descriptive survey design to explore perceived levels of assessment literacy of mathematics teachers to implement classroom assessment with the school based assessment framework in Ghana. A 25-item classroom assessment inventory on teachers’ assessment scenarios was adopted, modified, and administered to a purposive sample of 48 mathematics teachers from eleven Senior High Schools. Seven other items were included to further collect data on their self-efficacy towards assessment literacy. Data were analyzed using descriptive and bivariate correlation statistics. The result shows that, on average, 48.6% of the mathematics teachers attained standard levels of assessment literacy. Specifically, 50.0% met standard one in choosing appropriate assessment methods, 68.3% reached standard two in developing appropriate assessment tasks, 36.6% reached standard three in administering, scoring, and interpreting assessment results, 58.3% reached standard four in making appropriate assessment decisions, 41.7% reached standard five in developing valid grading procedures, 45.8% reached standard six in communicating assessment results, and 36.2 % reached standard seven by identifying unethical, illegal and inappropriate use of assessment results. Participants rated their self-efficacy belief in performing assessments high, making the relationships between participants’ assessment literacy scores and self-efficacy scores weak and statistically insignificant. The study recommends that institutions training mathematics teachers or providing professional developments should accentuate assessment literacy development to ensure standard assessment practices and quality instruction in mathematics education at senior high schools.

Keywords: assessment literacy, mathematics teacher, senior high schools, Ghana

Procedia PDF Downloads 107