Search results for: life- long learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18385

Search results for: life- long learning

13165 Teachers' Beliefs and Practices in Designing Negotiated English Lesson Plans

Authors: Joko Nurkamto

Abstract:

A lesson plan is a part of the planning phase in a learning and teaching system framing the scenario of pedagogical activities in the classroom. It informs a decision on what to teach and how to landscape classroom interaction. Regardless of these benefits, the writer has witnessed the fact that lesson plans are viewed merely as a teaching document. Therefore, this paper will explore teachers’ beliefs and practices in designing lesson plans. It focuses primarily on how both teachers and students negotiate lesson plans in which the students are deemed to be the agents of instructional innovations. Additionally, the paper will talk about how such lesson plans are enacted. To investigate these issues, document analysis, in-depth interviews, participant classroom observation, and focus group discussion will be deployed as data collection methods in this explorative case study. The benefits of the paper are to show different roles of lesson plans and to discover different ways to design and enact such plans from a socio-interactional perspective.

Keywords: instructional innovation, learning and teaching system, lesson plan, pedagogical activities, teachers' beliefs and practices

Procedia PDF Downloads 151
13164 Reverse Logistics End of Life Products Acquisition and Sorting

Authors: Badli Shah Mohd Yusoff, Khairur Rijal Jamaludin, Rozetta Dollah

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The emerging of reverse logistics and product recovery management is an important concept in reconciling economic and environmental objectives through recapturing values of the end of life product returns. End of life products contains valuable modules, parts, residues and materials that can create value if recovered efficiently. The main objective of this study is to explore and develop a model to recover as much of the economic value as reasonably possible to find the optimality of return acquisition and sorting to meet demand and maximize profits over time. In this study, the benefits that can be obtained for remanufacturer is to develop demand forecasting of used products in the future with uncertainty of returns and quality of products. Formulated based on a generic disassembly tree, the proposed model focused on three reverse logistics activity, namely refurbish, remanufacture and disposal incorporating all plausible means quality levels of the returns. While stricter sorting policy, constitute to the decrease amount of products to be refurbished or remanufactured and increases the level of discarded products. Numerical experiments carried out to investigate the characteristics and behaviour of the proposed model with mathematical programming model using Lingo 16.0 for medium-term planning of return acquisition, disassembly (refurbish or remanufacture) and disposal activities. Moreover, the model seeks an analysis a number of decisions relating to trade off management system to maximize revenue from the collection of use products reverse logistics services through refurbish and remanufacture recovery options. The results showed that full utilization in the sorting process leads the system to obtain less quantity from acquisition with minimal overall cost. Further, sensitivity analysis provides a range of possible scenarios to consider in optimizing the overall cost of refurbished and remanufactured products.

Keywords: core acquisition, end of life, reverse logistics, quality uncertainty

Procedia PDF Downloads 297
13163 Chinese Students’ Use of Corpus Tools in an English for Academic Purposes Writing Course: Influence on Learning Behaviour, Performance Outcomes and Perceptions

Authors: Jingwen Ou

Abstract:

Writing for academic purposes in a second or foreign language poses a significant challenge for non-native speakers, particularly at the tertiary level, where English academic writing for L2 students is often hindered by difficulties in academic discourse, including vocabulary, academic register, and organization. The past two decades have witnessed a rising popularity in the application of the data-driven learning (DDL) approach in EAP writing instruction. In light of such a trend, this study aims to enhance the integration of DDL into English for academic purposes (EAP) writing classrooms by investigating the perception of Chinese college students regarding the use of corpus tools for improving EAP writing. Additionally, the research explores their corpus consultation behaviors during training to provide insights into corpus-assisted EAP instruction for DDL practitioners. Given the uprising popularity of DDL, this research aims to investigate Chinese university students’ use of corpus tools with three main foci: 1) the influence of corpus tools on learning behaviours, 2) the influence of corpus tools on students’ academic writing performance outcomes, and 3) students’ perceptions and potential perceptional changes towards the use of such tools. Three corpus tools, CQPWeb, Sketch Engine, and LancsBox X, are selected for investigation due to the scarcity of empirical research on patterns of learners’ engagement with a combination of multiple corpora. The research adopts a pre-test / post-test design for the evaluation of students’ academic writing performance before and after the intervention. Twenty participants will be divided into two groups: an intervention and a non-intervention group. Three corpus training workshops will be delivered at the beginning, middle, and end of a semester. An online survey and three separate focus group interviews are designed to investigate students’ perceptions of the use of corpus tools for improving academic writing skills, particularly the rhetorical functions in different essay sections. Insights from students’ consultation sessions indicated difficulties with DDL practice, including insufficiency of time to complete all tasks, struggle with technical set-up, unfamiliarity with the DDL approach and difficulty with some advanced corpus functions. Findings from the main study aim to provide pedagogical insights and training resources for EAP practitioners and learners.

Keywords: corpus linguistics, data-driven learning, English for academic purposes, tertiary education in China

Procedia PDF Downloads 49
13162 Digital Dialogue Game, Epistemic Beliefs, Argumentation and Learning

Authors: Omid Noroozi, Martin Mulder

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The motivational potential of educational games is undeniable especially for teaching topics and skills that are difficult to deal with in traditional educational situations such as argumentation competence. Willingness to argue has an association with student epistemic beliefs, which can influence whether, and the way in which students engage in argumentative discourse activities and critical discussion. The goal of this study was to explore how undergraduate students engage with argumentative discourse activities which have been designed to intensify debate, and whether epistemic beliefs are significant to the outcomes. A pre-test, post-test design was used with students who were assigned to groups of four. They were asked to argue a controversial topic with the aim of exploring various perspectives, and the 'pros and cons' on the topic of 'Genetically Modified Organisms (GMOs)'. The results show that the game facilitated argumentative discourse and a willingness to argue and challenged peers, regardless of students’ epistemic beliefs. Furthermore, the game was evaluated positively in terms of students’ motivation and satisfaction with the learning experience.

Keywords: argumentation, attitudinal change, epistemic beliefs, dialogue, digital game objectives and theoretical

Procedia PDF Downloads 399
13161 Are Oral Health Conditions Associated with Children’s School Performance and School Attendance in the Kingdom of Bahrain - A Life Course Approach

Authors: Seham A. S. Mohamed, Sarah R. Baker, Christopher Deery, Mario V. Vettore

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Background: The link between oral health conditions and school performance and attendance remain unclear among Middle Eastern children. The association has been studied extensively in the Western region; however, several concerns have been raised regarding the reliability and validity of measures, low quality of studies, inadequate inclusion of potential confounders, and the lack of a conceptual framework. These limitations have meant that, to date, there has been no detailed understanding of the association or of the key social, clinical, behavioural and parental factors which may impact the association. Aim: To examine the association between oral health conditions and children’s school performance and attendance at Grade 2 in Muharraq city in the Kingdom of Bahrain using Heilmann et al.’s (2015) life course framework for oral health. Objectives: To (1) describe the prevalence of oral health conditions among 7-8 years old schoolchildren in the city of Muharraq; (2) analyse the social, biological, behavioural, and parental pathways that link early and current life exposures with children’s current oral health status; (3) examine the association between oral health conditions and school performance and attendance among schoolchildren; (4) explore the early and current life course social, biological, behavioural and parental factors associated with children’s school outcomes. Design: A time-ordered-cross-sectional study was conducted with 466 schoolchildren aged 7-8 years and their parents from Muharraq city in KoB. Data were collected through parents’ self-administered questionnaires, children’s face-face interviews, and dental clinical examinations. Outcome variables, including school performance and school attendance data, were obtained from the parents and school records. The data were analysed using structural equation modelling (SEM). Results: Dental caries, the consequence of dental caries (PUFA/pufa), and enamel developmental defects (EDD) prevalence were 93.4%, 25.7%, and 17.2%, respectively. The findings from the SEM showed that children born in families with high SES were less likely to suffer from dentine dental caries (β= -0.248) and more likely to earn high school performance (β= 0.136) at 7-8 years of age in Muharraq. From the current life course of children, the dental plaque was associated significantly and directly with enamel caries (β= 0.094), dentine caries (β= 0.364), treated teeth (filled or extracted because of dental caries) (β= 0.121), and indirectly associated with dental pain (β= 0.057). Further, dentine dental caries was associated significantly and directly with low school performance (β= -0.155). At the same time, the dental plaque was indirectly associated with low school performance via dental caries (β = −0.044). Conversely, treated teeth were associated directly with high school performance (β= 0.100). Notably, none of the OHCs, biological, SES, behavioural, or parental conditions was related to school attendance in children. Conclusion: The life course approach was adequate to examine the role of OHCs on children’s school performance and attendance. Birth and current (7-8-year-olds) social factors were significant predictors of poor OH and poor school performance.

Keywords: dental caries, life course, Bahrain, school outcomes

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13160 More Precise: Patient-Reported Outcomes after Stroke

Authors: Amber Elyse Corrigan, Alexander Smith, Anna Pennington, Ben Carter, Jonathan Hewitt

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Background and Purpose: Morbidity secondary to stroke is highly heterogeneous, but it is important to both patients and clinicians in post-stroke management and adjustment to life after stroke. The consideration of post-stroke morbidity clinically and from the patient perspective has been poorly measured. The patient-reported outcome measures (PROs) in morbidity assessment help improve this knowledge gap. The primary aim of this study was to consider the association between PRO outcomes and stroke predictors. Methods: A multicenter prospective cohort study assessed 549 stroke patients at 19 hospital sites across England and Wales during 2019. Following a stroke event, demographic, clinical, and PRO measures were collected. Prevalence of morbidity within PRO measures was calculated with associated 95% confidence intervals. Predictors of domain outcome were calculated using a multilevel generalized linear model. Associated P -values and 95% confidence intervals are reported. Results: Data were collected from 549 participants, 317 men (57.7%) and 232 women (42.3%) with ages ranging from 25 to 97 (mean 72.7). PRO morbidity was high post-stroke; 93.2% of the cohort report post-stroke PRO morbidity. Previous stroke, diabetes, and gender are associated with worse patient-reported outcomes across both the physical and cognitive domains. Conclusions: This large-scale multicenter cohort study illustrates the high proportion of morbidity in PRO measures. Further, we demonstrate key predictors of adverse outcomes (Diabetes, previous stroke, and gender) congruence with clinical predictors. The PRO has been demonstrated to be an informative and useful stroke when considering patient-reported outcomes and has wider implications for considerations of PROs in clinical management. Future longitudinal follow-up with PROs is needed to consider association of long-term morbidity.

Keywords: morbidity, patient-reported outcome, PRO, stroke

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13159 The U.S.-Taliban Peace Deal: Two-level Game Logic and Actors’ Payoffs

Authors: Zafar Iqbal

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This article aims at analyzing the U.S.-Taliban peace deal considering the cross- pressures that both parties (U.S. and Taliban) faced and eventually paved the way for a negotiated settlement to the two-decade-long war. The paper first discusses the peace process initiated by President Obama in 2009 and then explores the factors that compelled both the parties to sign this deal. The study is based on secondary data and interviews done with the leading experts on Afghanistan along with the Taliban Qatar office spokesperson’s interview. The theoretical framework is based on the interplay of diplomacy and domestic politics: two-level games logic proposed by Robert D. Putnam. The two-level games suggest that actors involved in negotiations face cross-pressures and are constrained both by the expectations of the domestic audience and their counterpart’s zone of possible agreement. This paper will take the cross pressures for both sides as the permissive factors for the entire process of negotiations. However, there will be a slight aberration in the application of Putnam’s two-level games. In this case, it is not inter-state negotiations but between an all-powerful state and the unyielding non-state actors. The study concludes that both the parties faced domestic as well as international pressure which compelled them to sign a deal that could lead to an end of the two-decade-long war. Furthermore, it looks at the potential prospects and challenges of the deal following the U.S. withdrawal.

Keywords: neo-Taliban insurgency, negotiations, two-level game, U.S.-Taliban peace deal, U.S. withdrawal

Procedia PDF Downloads 202
13158 Detection and Classification of Rubber Tree Leaf Diseases Using Machine Learning

Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

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Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

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13157 Effects of Analogy Method on Children's Learning: Practice of Rainbow Experiments

Authors: Hediye Saglam

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This research has been carried out to bring in the 6 acquisitions in the 2014 Preschool Teaching Programme of the Turkish Ministry of Education through the method of analogy. This research is practiced based on the experimental pattern with pre-test and final test controlling groups. The working group of the study covers the group between 5-6 ages. The study takes 5 weeks including the 2 weeks spent for pre-test and the final test. It is conducted with the preschool teacher who gives the lesson along with the researcher in the in-class and out-of-class rainbow experiments of the students for 5 weeks. 'One Sample T Test' is used for the evaluation of the pre-test and final test. SPSS 17 programme is applied for the analysis of the data. Results: As an outcome of the study it is observed that analogy method affects children’s learning of the rainbow. For this very reason teachers should receive inservice training for different methods and techniques like analogy. This method should be included in preschool education programme and should be applied by teachers more often.

Keywords: acquisitions of preschool education programme, analogy method, pre-test/final test, rainbow experiments

Procedia PDF Downloads 501
13156 Engaging Citizen, Sustaining Service Delivery of Rural Water Supply in Indonesia

Authors: Rahmi Yetri Kasri, Paulus Wirutomo

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Citizen engagement approach has become increasingly important in the rural water sector. However, the question remains as to what exactly is meant by citizen engagement and how this approach can lead to sustainable service delivery. To understand citizen engagement, this paper argues that we need to understand basic elements of social life that consist of social structure, process, and culture within the realm of community’s living environment. Extracting from empirical data from Pamsimas villages in rural West Java, Indonesia, this paper will identify basic elements of social life and environment that influence and form the engagement of citizen and government in delivering and sustaining rural water supply services in Indonesia. Pamsimas or the Water Supply and Sanitation for Low Income Communities project is the biggest rural water program in Indonesia, implemented since 1993 in more than 27,000 villages. The sustainability of this sector is explored through a rural water supply service delivery life-cycle, starts with capital investment, operational and maintenance, asset expansion or renewal, strategic planning for future services and matching cost with financing. Using mixed-method data collection in case study research, this paper argues that increased citizen engagement contributes to a more sustainable rural water service delivery.

Keywords: citizen engagement, rural water supply, sustainability, Indonesia

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13155 The Link between Childhood Maltreatment and Psychological Distress: The Mediation and Moderation Roles of Cognitive Distortion, Alexithymia, and Eudemonic Well-Being

Authors: Siqi Fang, Man Cheung Chung

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This study examined the inter-relationship between childhood maltreatment, cognitive distortion, alexithymia, eudemonic well-being, and psychological distress. One hundred and eighty-two university students participated in the study and completed an online survey comprising the Childhood Trauma Questionnaire, Cognitive Distortion Scale, Toronto Alexithymia Scale, Psychological Well-Being Scale, and General Health Questionnaire-28. Hierarchical multiple regression analysis showed that child maltreatment, perceptions of hopelessness and helplessness, preoccupation with danger, personal growth, and purpose in life predicted psychological distress. However, alexithymia was not a significant predictor. Further analysis using the regression models with bootstrapping procedure showed that feeling hopeless, helpless and preoccupation with danger mediated the path between child maltreatment and psychological distress. Meanwhile, coping with beliefs in personal growth and life purpose moderated the mediation effects of distorted cognition on psychological distress. To conclude, childhood maltreatment is associated with psychological distress. This relationship is influenced by people’s perceptions of life being hopeless, helpless or dangerous. At the same time, the effect of hopelessness, helplessness, and feelings of danger also depends on the degree of using coping strategies of positive psychological functioning.

Keywords: alexithymia, childhood maltreatment, cognitive distortion, eudemonic well-being, psychological distress

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13154 Collaborative Data Refinement for Enhanced Ionic Conductivity Prediction in Garnet-Type Materials

Authors: Zakaria Kharbouch, Mustapha Bouchaara, F. Elkouihen, A. Habbal, A. Ratnani, A. Faik

Abstract:

Solid-state lithium-ion batteries have garnered increasing interest in modern energy research due to their potential for safer, more efficient, and sustainable energy storage systems. Among the critical components of these batteries, the electrolyte plays a pivotal role, with LLZO garnet-based electrolytes showing significant promise. Garnet materials offer intrinsic advantages such as high Li-ion conductivity, wide electrochemical stability, and excellent compatibility with lithium metal anodes. However, optimizing ionic conductivity in garnet structures poses a complex challenge, primarily due to the multitude of potential dopants that can be incorporated into the LLZO crystal lattice. The complexity of material design, influenced by numerous dopant options, requires a systematic method to find the most effective combinations. This study highlights the utility of machine learning (ML) techniques in the materials discovery process to navigate the complex range of factors in garnet-based electrolytes. Collaborators from the materials science and ML fields worked with a comprehensive dataset previously employed in a similar study and collected from various literature sources. This dataset served as the foundation for an extensive data refinement phase, where meticulous error identification, correction, outlier removal, and garnet-specific feature engineering were conducted. This rigorous process substantially improved the dataset's quality, ensuring it accurately captured the underlying physical and chemical principles governing garnet ionic conductivity. The data refinement effort resulted in a significant improvement in the predictive performance of the machine learning model. Originally starting at an accuracy of 0.32, the model underwent substantial refinement, ultimately achieving an accuracy of 0.88. This enhancement highlights the effectiveness of the interdisciplinary approach and underscores the substantial potential of machine learning techniques in materials science research.

Keywords: lithium batteries, all-solid-state batteries, machine learning, solid state electrolytes

Procedia PDF Downloads 54
13153 Fabric-Reinforced Cementitious Matrix (FRCM)-Repaired Corroded Reinforced Concrete (RC) Beams under Monotonic and Fatigue Loads

Authors: Mohammed Elghazy, Ahmed El Refai, Usama Ebead, Antonio Nanni

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Rehabilitating corrosion-damaged reinforced concrete (RC) structures has been accomplished using various techniques such as steel plating, external post-tensioning, and external bonding of fiber reinforced polymer (FRP) composites. This paper reports on the use of an innovative technique to strengthen corrosion-damaged RC structures using fabric-reinforced cementitious matrix (FRCM) composites. FRCM consists of dry-fiber fabric embedded in cement-based matrix. Twelve large-scale RC beams were constructed and tested in flexural monotonic and fatigue loads. Prior to testing, ten specimens were subjected to accelerated corrosion process for 140 days leading to an average mass loss in the tensile steel bars of 18.8 %. Corrosion was restricted to the main reinforcement located in the middle third of the beam span. Eight corroded specimens were repaired and strengthened while two virgin and two corroded-unrepaired/unstrengthened beams were used as benchmarks for comparison purpose. The test parameters included the FRCM materials (Carbon-FRCM, PBO-FRCM), the number of FRCM plies, the strengthening scheme, and the type of loading (monotonic and fatigue). The effects of the pervious parameters on the flexural response, the mode of failure, and the fatigue life were reported. Test results showed that corrosion reduced the yield and ultimate strength of the beams. The corroded-unrepaired specimen failed to meet the provisions of the ACI-318 code for crack width criteria. The use of FRCM significantly increased the ultimate strength of the corroded specimen by 21% and 65% more than that of the corroded-unrepaired specimen. Corrosion significantly decreased the fatigue life of the corroded-unrepaired beam by 77% of that of the virgin beam. The fatigue life of the FRCM repaired-corroded beams increased to 1.5 to 3.8 times that of the corroded-unrepaired beam but was lower than that of the virgin specimen. The specimens repaired with U-wrapped PBO-FRCM strips showed higher fatigue life than those repaired with the end-anchored bottom strips having similar number of PBO-FRCM-layers. PBO-FRCM was more effective than Carbon-FRCM in restoring the fatigue life of the corroded specimens.

Keywords: corrosion, concrete, fabric-reinforced cementitious matrix (FRCM), fatigue, flexure, repair

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13152 Bedouin of Silicon Wadi: A Case Study Analysis of the Multi-Level Perspectives and Factors Affecting Bedouin Entrepreneurialism as Obstacles to Entry into the Israeli High-Tech Industry

Authors: Frazer G. Thompson

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Israel is a nation of cultural and historical diversity, yet the success factors for a modern Bedouin-Arab high-tech entrepreneur seem to be different from those of other Jewish-Israeli citizens. The purpose of this descriptive narrative case study is to explore how an Arab-Israeli all Negev-Bedouin technology company has succeeded in the Israeli high-tech industry by utilizing technology and engineering career opportunities available to Bedouin youth for ‘Sadel Tech,’ at Be’er-Sheva, the Negev, Israel. Methods: The strategy of inquiry seeks to explore real-life contextual understandings, multi-level perspectives, and the cultural influences of personal, community, educational, and entrepreneurial factors. The research methodology includes in-depth one-on-one interviews, focus group sessions, and overt observation to explore the meaning and understanding of the constructs toward determining the effect all or a few of the elements may have on the overall success factors of the company. Results: Study results indicate that the state-run educational system in Israel fails to adequately integrate important aspects of Bedouin culture into the learning environment. However, Bedouin entrepreneurs are finding ways to compensate for these inadequacies by utilizing non-traditional methods of teaching, learning, and doing business. Government incentives for Bedouin start-ups are also recognized as contributors. Employees of Sadel live and work in the Negev, the Gaza Strip, and the West Bank, further informing the study that the traditions of tribal etiquette continue to contribute to modern Bedouin-Arab business culture. Conclusion: Bedouin's business success in Israel is a multi-dimensional concept. While cultural acumen plays a prominent and unique role for both Arab-Israelis and Jewish-Israelis in economic and entrepreneurial pursuits, the marginalization of the Bedouin continues to contribute to the lack of educational and professional opportunities for Bedouin in Israel. Although recognized as important at the government level, programs necessary to implement the infrastructure required to support Bedouin entrepreneurship in Israel remain infantile. The Israeli Government is providing opportunities through grants and other incentives for Bedouin entrepreneurial start-ups, indicating that Israel has recognized the impact of this growing demographic. However, although many Bedouin graduates from University each year with advanced degrees, opportunities for Bedouin within the Israeli high-tech sector remain scarce.

Keywords: Bedouin education, Bedouin entrepreneur, economic anthropology, ethnic business opportunities, Israeli tech, Silicon Wadi

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13151 Comparison of Machine Learning-Based Models for Predicting Streptococcus pyogenes Virulence Factors and Antimicrobial Resistance

Authors: Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Diego Santibañez Oyarce, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

Streptococcus pyogenes is a gram-positive bacteria involved in a wide range of diseases and is a major-human-specific bacterial pathogen. In Chile, this year the 'Ministerio de Salud' declared an alert due to the increase in strains throughout the year. This increase can be attributed to the multitude of factors including antimicrobial resistance (AMR) and Virulence Factors (VF). Understanding these VF and AMR is crucial for developing effective strategies and improving public health responses. Moreover, experimental identification and characterization of these pathogenic mechanisms are labor-intensive and time-consuming. Therefore, new computational methods are required to provide robust techniques for accelerating this identification. Advances in Machine Learning (ML) algorithms represent the opportunity to refine and accelerate the discovery of VF associated with Streptococcus pyogenes. In this work, we evaluate the accuracy of various machine learning models in predicting the virulence factors and antimicrobial resistance of Streptococcus pyogenes, with the objective of providing new methods for identifying the pathogenic mechanisms of this organism.Our comprehensive approach involved the download of 32,798 genbank files of S. pyogenes from NCBI dataset, coupled with the incorporation of data from Virulence Factor Database (VFDB) and Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. These datasets provided labeled examples of both virulent and non-virulent genes, enabling a robust foundation for feature extraction and model training. We employed preprocessing, characterization and feature extraction techniques on primary nucleotide/amino acid sequences and selected the optimal more for model training. The feature set was constructed using sequence-based descriptors (e.g., k-mers and One-hot encoding), and functional annotations based on database prediction. The ML models compared are logistic regression, decision trees, support vector machines, neural networks among others. The results of this work show some differences in accuracy between the algorithms, these differences allow us to identify different aspects that represent unique opportunities for a more precise and efficient characterization and identification of VF and AMR. This comparative analysis underscores the value of integrating machine learning techniques in predicting S. pyogenes virulence and AMR, offering potential pathways for more effective diagnostic and therapeutic strategies. Future work will focus on incorporating additional omics data, such as transcriptomics, and exploring advanced deep learning models to further enhance predictive capabilities.

Keywords: antibiotic resistance, streptococcus pyogenes, virulence factors., machine learning

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13150 Analysis of Trend and Variability of Rainfall in the Mid-Mahanadi River Basin of Eastern India

Authors: Rabindra K. Panda, Gurjeet Singh

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The major objective of this study was to analyze the trend and variability of rainfall in the middle Mahandi river basin located in eastern India. The trend of variation of extreme rainfall events has predominant effect on agricultural water management and extreme hydrological events such as floods and droughts. Mahanadi river basin is one of the major river basins of India having an area of 1,41,589 km2 and divided into three regions: Upper, middle and delta region. The middle region of Mahanadi river basin has an area of 48,700 km2 and it is mostly dominated by agricultural land, where agriculture is mostly rainfed. The study region has five Agro-climatic zones namely: East and South Eastern Coastal Plain, North Eastern Ghat, Western Undulating Zone, Western Central Table Land and Mid Central Table Land, which were numbered as zones 1 to 5 respectively for convenience in reporting. In the present study, analysis of variability and trends of annual, seasonal, and monthly rainfall was carried out, using the daily rainfall data collected from the Indian Meteorological Department (IMD) for 35 years (1979-2013) for the 5 agro-climatic zones. The long term variability of rainfall was investigated by evaluating the mean, standard deviation and coefficient of variation. The long term trend of rainfall was analyzed using the Mann-Kendall test on monthly, seasonal and annual time scales. It was found that there is a decreasing trend in the rainfall during the winter and pre monsoon seasons for zones 2, 3 and 4; whereas in the monsoon (rainy) season there is an increasing trend for zones 1, 4 and 5 with a level of significance ranging between 90-95%. On the other hand, the mean annual rainfall has an increasing trend at 99% significance level. The estimated seasonality index showed that the rainfall distribution is asymmetric and distributed over 3-4 months period. The study will help to understand the spatio-temporal variation of rainfall and to determine the correlation between the current rainfall trend and climate change scenario of the study region for multifarious use.

Keywords: Eastern India, long-term variability and trends, Mann-Kendall test, seasonality index, spatio-temporal variation

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13149 Sustainable Micro Architecture: A Pattern for Urban Release Areas

Authors: Saber Fatourechian

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People within modern cities have faced macro urban values spreads rapidly through current style of living. Unexpected phenomena without any specific features of micro scale, humanity and urban social/cultural patterns. The gap between micro and macro scale is unidentified and people could not recognize where they are especially in the interaction between life and city. Urban life details were verified. Micro architecture is a pattern in which human activity derives from human needs in an unconscious position. Sustainable attitude via micro architecture causes flexibility in decision making through micro urbanism essentially impacts macro scale. In this paper the definition of micro architecture and its relation with city and human activity are argued, there after the interaction between micro and macro scale is presented as an effective way for urban sustainable development.

Keywords: micro architecture, sustainability, human activity, city

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13148 Ama de Casa: Gender Division of Labor the Response to Environmental and Economic Constraints, Ecuador

Authors: Tyrus C. Torres, Michael Harris

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In a coastal town of Ecuador, the role of women is commonly defined as an ama de casa, a woman who works in the house, raises children, and contributes to the community. This project, under the guidance of Dr. Michael Harris from the Florida Atlantic University, seeks to understand how the role of an ama de casa provides a secure environment for men and women, coexists with economic and environmental constraints that explain the origins of how this environment has been formed. The coastal community aspects of familia (family), trabajo (work), relación (relationships), machismo (masculinity), feminista (femininity), and the culture of Ecuador define the ways of life in a coastal setting. This ethnographic research project included the following methodologies: environment mapping, conducting interviews, surveys, participant observation, direct and indirect observations, and integration into daily life. Immersion into the daily life and building relationships with the local people allowed the documentation of intricacies of both the cultural and social spheres. The findings of this research offer insight on how culture, economics, and environment can form female and male agency. Our investigation shows that occupations such as fishermen, laborers, ama de casas, and even students utilize occupational routes to create social agency in the face of economic and environmental constraints in Ecuador.

Keywords: Ecuador, ethnography, gender division of labor, gender roles

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13147 A Palmprint Identification System Based Multi-Layer Perceptron

Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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13146 An Approach to Addressing Homelessness in Hong Kong: Life Story Approach

Authors: Tak Mau Simon Chan, Ying Chuen Lance Chan

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Homelessness has been a popular and controversial debate in Hong Kong, a city which is densely populated and well-known for very expensive housing. The constitution of the homeless as threats to the community and environmental hygiene is ambiguous and debatable in the Hong Kong context. The lack of an intervention model is the critical research gap thus far, aside from the tangible services delivered. The life story approach (LSA), with its unique humanistic orientation, has been well applied in recent decades to depict the needs of various target groups, but not the homeless. It is argued that the life story approach (LSA), which has been employed by health professionals in the landscape of dementia, and health and social care settings, can be used as a reference in the local Chinese context through indigenization. This study, therefore, captures the viewpoints of service providers and users by constructing an indigenous intervention model that refers to the LSA in serving the chronically homeless. By informing 13 social workers and 27 homeless individuals in 8 focus groups whilst 12 homeless individuals have participated in individual in-depth interviews, a framework of LSA in homeless people is proposed. Through thematic analysis, three main themes of their life stories was generated, namely, the family, negative experiences and identity transformation. The three domains solidified framework that not only can be applied to the homeless, but also other disadvantaged groups in the Chinese context. Based on the three domains of family, negative experiences and identity transformation, the model is applied in the daily practices of social workers who help the homeless. The domain of family encompasses familial relationships from the past to the present to the speculated future with ten sub-themes. The domain of negative experiences includes seven sub-themes, with reference to the deviant behavior committed. The last domain, identity transformation, incorporates the awareness and redefining of one’s identity and there are a total of seven sub-themes. The first two domains are important components of personal histories while the third is more of an unknown, exploratory and yet to-be-redefined territory which has a more positive and constructive orientation towards developing one’s identity and life meaning. The longitudinal temporal dimension of moving from the past – present - future enriches the meaning making process, facilitates the integration of life experiences and maintains a more hopeful dialogue. The model is tested and its effectiveness is measured by using qualitative and quantitative methods to affirm the extent that it is relevant to the local context. First, it contributes to providing a clear guideline for social workers who can use the approach as a reference source. Secondly, the framework acts as a new intervention means to address problem saturated stories and the intangible needs of the homeless. Thirdly, the model extends the application to beyond health related issues. Last but not least, the model is highly relevant to the local indigenous context.

Keywords: homeless, indigenous intervention, life story approach, social work practice

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13145 Optimizing AI Voice for Adolescent Health Education: Preferences and Trustworthiness Across Teens and Parent

Authors: Yu-Lin Chen, Kimberly Koester, Marissa Raymond-Flesh, Anika Thapar, Jay Thapar

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Purpose: Effectively communicating adolescent health topics to teens and their parents is crucial. This study emphasizes critically evaluating the optimal use of artificial intelligence tools (AI), which are increasingly prevalent in disseminating health information. By fostering a deeper understanding of AI voice preference in the context of health, the research aspires to have a ripple effect, enhancing the collective health literacy and decision-making capabilities of both teenagers and their parents. This study explores AI voices' potential within health learning modules for annual well-child visits. We aim to identify preferred voice characteristics and understand factors influencing perceived trustworthiness, ultimately aiming to improve health literacy and decision-making in both demographics. Methods: A cross-sectional study assessed preferences and trust perceptions of AI voices in learning modules among teens (11-18) and their parents/guardians in Northern California. The study involved the development of four distinct learning modules covering various adolescent health-related topics, including general communication, sexual and reproductive health communication, parental monitoring, and well-child check-ups. Participants were asked to evaluate eight AI voices across the modules, considering a set of six factors such as intelligibility, naturalness, prosody, social impression, trustworthiness, and overall appeal, using Likert scales ranging from 1 to 10 (the higher, the better). They were also asked to select their preferred choice of voice for each module. Descriptive statistics summarized participant demographics. Chi-square/t-tests explored differences in voice preferences between groups. Regression models identified factors impacting the perceived trustworthiness of the top-selected voice per module. Results: Data from 104 participants (teen=63; adult guardian = 41) were included in the analysis. The mean age is 14.9 for teens (54% male) and 41.9 for the parent/guardian (12% male). At the same time, similar voice quality ratings were observed across groups, and preferences varied by topic. For instance, in general communication, teens leaned towards young female voices, while parents preferred mature female tones. Interestingly, this trend reversed for parental monitoring, with teens favoring mature male voices and parents opting for mature female ones. Both groups, however, converged on mature female voices for sexual and reproductive health topics. Beyond preferences, the study delved into factors influencing perceived trustworthiness. Interestingly, social impression and sound appeal emerged as the most significant contributors across all modules, jointly explaining 71-75% of the variance in trustworthiness ratings. Conclusion: The study emphasizes the importance of catering AI voices to specific audiences and topics. Social impression and sound appeal emerged as critical factors influencing perceived trustworthiness across all modules. These findings highlight the need to tailor AI voices by age and the specific health information being delivered. Ensuring AI voices resonate with both teens and their parents can foster their engagement and trust, ultimately leading to improved health literacy and decision-making for both groups. Limitations and future research: This study lays the groundwork for understanding AI voice preferences for teenagers and their parents in healthcare settings. However, limitations exist. The sample represents a specific geographic location, and cultural variations might influence preferences. Additionally, the modules focused on topics related to well-child visits, and preferences might differ for more sensitive health topics. Future research should explore these limitations and investigate the long-term impact of AI voice on user engagement, health outcomes, and health behaviors.

Keywords: artificial intelligence, trustworthiness, voice, adolescent

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13144 Statistical Analysis Approach for the e-Glassy Mortar And Radiation Shielding Behaviors Using Anova

Authors: Abadou Yacine, Faid Hayette

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Significant investigations were performed on the use and impact on physical properties along with the mechanical strength of the recycled and reused E-glass waste powder. However, it has been modelled how recycled display e-waste glass may affect the characteristics and qualities of dune sand mortar. To be involved in this field, an investigation has been done with the substitution of dune sand for recycled E-glass waste and constant water-cement ratios. The linear relationship between the dune sand mortar and E-glass mortar mix % contributes to the model's reliability. The experimental data was exposed to regression analysis using JMP Statistics software. The regression model with one predictor presented the general form of the equation for the prediction of the five properties' characteristics of dune sand mortar from the substitution ratio of E-waste glass and curing age. The results illustrate that curing a long-term process produced an E-glass waste mortar specimen with the highest compressive strength of 68 MPa in the laboratory environment. Anova analysis indicated that the curing at long-term has the utmost importance on the sorptivity level and ultrasonic pulse velocity loss. Furthermore, the E-glass waste powder percentage has the utmost importance on the compressive strength and improvement in dynamic elasticity modulus. Besides, a significant enhancement of radiation-shielding applications.

Keywords: ANOVA analysis, E-glass waste, durability and sustainability, radiation-shielding

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13143 Design-Based Elements to Sustain Participant Activity in Massive Open Online Courses: A Case Study

Authors: C. Zimmermann, E. Lackner, M. Ebner

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Massive Open Online Courses (MOOCs) are increasingly popular learning hubs that are boasting considerable participant numbers, innovative technical features, and a multitude of instructional resources. Still, there is a high level of evidence showing that almost all MOOCs suffer from a declining frequency of participant activity and fairly low completion rates. In this paper, we would like to share the lessons learned in implementing several design patterns that have been suggested in order to foster participant activity. Our conclusions are based on experiences with the ‘Dr. Internet’ MOOC, which was created as an xMOOC to raise awareness for a more critical approach to online health information: participants had to diagnose medical case studies. There is a growing body of recommendations (based on Learning Analytics results from earlier xMOOCs) as to how the decline in participant activity can be alleviated. One promising focus in this regard is instructional design patterns, since they have a tremendous influence on the learner’s motivation, which in turn is a crucial trigger of learning processes. Since Medieval Age storytelling, micro-learning units and specific comprehensible, narrative structures were chosen to animate the audience to follow narration. Hence, MOOC participants are not likely to abandon a course or information channel when their curiosity is kept at a continuously high level. Critical aspects that warrant consideration in this regard include shorter course duration, a narrative structure with suspense peaks (according to the ‘storytelling’ approach), and a course schedule that is diversified and stimulating, yet easy to follow. All of these criteria have been observed within the design of the Dr. Internet MOOC: 1) the standard eight week course duration was shortened down to six weeks, 2) all six case studies had a special quiz format and a corresponding resolution video which was made available in the subsequent week, 3) two out of six case studies were split up in serial video sequences to be presented over the span of two weeks, and 4) the videos were generally scheduled in a less predictable sequence. However, the statistical results from the first run of the MOOC do not indicate any strong influences on the retention rate, so we conclude with some suggestions as to why this might be and what aspects need further consideration.

Keywords: case study, Dr. internet, experience, MOOCs, design patterns

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13142 Infrared Lightbox and iPhone App for Improving Detection Limit of Phosphate Detecting Dip Strips

Authors: H. Heidari-Bafroui, B. Ribeiro, A. Charbaji, C. Anagnostopoulos, M. Faghri

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In this paper, we report the development of a portable and inexpensive infrared lightbox for improving the detection limits of paper-based phosphate devices. Commercial paper-based devices utilize the molybdenum blue protocol to detect phosphate in the environment. Although these devices are easy to use and have a long shelf life, their main deficiency is their low sensitivity based on the qualitative results obtained via a color chart. To improve the results, we constructed a compact infrared lightbox that communicates wirelessly with a smartphone. The system measures the absorbance of radiation for the molybdenum blue reaction in the infrared region of the spectrum. It consists of a lightbox illuminated by four infrared light-emitting diodes, an infrared digital camera, a Raspberry Pi microcontroller, a mini-router, and an iPhone to control the microcontroller. An iPhone application was also developed to analyze images captured by the infrared camera in order to quantify phosphate concentrations. Additionally, the app connects to an online data center to present a highly scalable worldwide system for tracking and analyzing field measurements. In this study, the detection limits for two popular commercial devices were improved by a factor of 4 for the Quantofix devices (from 1.3 ppm using visible light to 300 ppb using infrared illumination) and a factor of 6 for the Indigo units (from 9.2 ppm to 1.4 ppm) with repeatability of less than or equal to 1.2% relative standard deviation (RSD). The system also provides more granular concentration information compared to the discrete color chart used by commercial devices and it can be easily adapted for use in other applications.

Keywords: infrared lightbox, paper-based device, phosphate detection, smartphone colorimetric analyzer

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13141 Smart Development Proposals for an Indian Village

Authors: J. E. M. Macwan, D. A. Pastagia, Reeta Meena

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Government of Gujarat (India) wishes to create smart villages to improve the quality of life. The significance of these efforts will result into higher rural productivity. The main aim of this research is to identify, design and propose implementable planning solutions suited for an Indian village set up. The methodology adopted is to create a database by conducting onsite study as well as gathering public opinion to help researchers to satisfy rural needs. The outcome of this research exercise is a planning design preparation and channelizing funds in right direction for a result oriented better village shape. The proposals are accepted after slight modifications by the stakeholders. Planning solutions were designed through public participatory approach. To control rural Urban migration, villagers were offered better quality of life.

Keywords: smart village, digitization, development plan, gram panchayats

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13140 Machine Learning Techniques in Bank Credit Analysis

Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: artificial neural networks (ANNs), classifier algorithms, credit risk assessment, logistic regression, machine Learning, support vector machines

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13139 Study of Sustainability Indicators in a Milk Production Process

Authors: E. Lacasa, J. L. Santolaya, I. Millán

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The progress toward sustainability implies maintaining and preferably improving both, human and ecosystem well-being, according to a triple bottom line that includes the environmental, economic and social dimensions. The life cycle assessment (LCA) is a method applicable to all production sectors that aims to quantify the environmental pressures and the benefits related to goods and services, as well as the trade-offs and the scope for improving areas of the production process. While using LCA to measure the environmental dimension of sustainability is widespread, similar approaches for the economic and the social dimensions still have limited application worldwide and there is a need for consistent and robust methods and indicators. This paper focuses on the milk production process and presents the analysis of the flows exchanged by an industrial installation through accounting all the energy and material inputs and the associated emissions and waste outputs at this stage of its life cycle. The functional unit is one litre of milk produced. Different metrics and indicators are used to assess the three dimensions of sustainability. Metrics considered useful to assess the production activities are the total water and energy consumptions and the milk production volume of each cow. The global warming, the value added and the working hours are indicators used to measure each sustainability dimension. The study is performed with two types of feeding of the cows, which includes a change in percentages of components as well. Nutritional composition of the milk obtained is almost kept. It is observed that environmental and social improvements involve high economic costs.

Keywords: milk production, sustainability, indicators, life cycle assessment

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13138 Global Health, Humanitarian Medical Aid, and the Ethics of Rationing

Authors: N. W. Paul, S. Michl

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In our globalized world we need to appreciate the fact that questions of health and justice need to be addressed on a global scale, too. The way in which diverse governmental and non-governmental initiatives are trying to answer the need for humanitarian medical aid has long since been a visible result of globalized responsibility. While the intention of humanitarian medical aids seems to be evident, the allocation of resources has become more and more an ethical and societal challenge. With a rising number and growing dimension of humanitarian catastrophes around the globe the search for ethically justifiable ways to decide who might benefit from limited resources has become a pressing question. Rooted in theories of justice (Rawls) and concepts of social welfare (Sen) we developed and implemented a model for an ethically sound distribution of a limited annual budget for humanitarian care in one of the largest medical universities of Germany. Based on our long lasting experience with civil casualties of war (Afghanistan) and civil war (Libya) as well as with under- and uninsured and/or stateless patients we are now facing the on-going refugee crisis as our most recent challenge in terms of global health and justice. Against this background, the paper strives to a) explain key issues of humanitarian medical aid in the 21st century, b) explore the problem of rationing from an ethical point of view, c) suggest a tool for the rational allocation of scarce resources in humanitarian medical aid, d) present actual cases of humanitarian care that have been managed with our toolbox, and e) discuss the international applicability of our model beyond local contexts.

Keywords: humanitarian care, medical ethics, allocation, rationing

Procedia PDF Downloads 394
13137 TutorBot+: Automatic Programming Assistant with Positive Feedback based on LLMs

Authors: Claudia Martínez-Araneda, Mariella Gutiérrez, Pedro Gómez, Diego Maldonado, Alejandra Segura, Christian Vidal-Castro

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The purpose of this document is to showcase the preliminary work in developing an EduChatbot-type tool and measuring the effects of its use aimed at providing effective feedback to students in programming courses. This bot, hereinafter referred to as tutorBot+, was constructed based on chatGPT and is tasked with assisting and delivering timely positive feedback to students in the field of computer science at the Universidad Católica de Concepción. The proposed working method consists of four stages: (1) Immersion in the domain of Large Language Models (LLMs), (2) Development of the tutorBot+ prototype and integration, (3) Experiment design, and (4) Intervention. The first stage involves a literature review on the use of artificial intelligence in education and the evaluation of intelligent tutors, as well as research on types of feedback for learning and the domain of chatGPT. The second stage encompasses the development of tutorBot+, and the final stage involves a quasi-experimental study with students from the Programming and Database labs, where the learning outcome involves the development of computational thinking skills, enabling the use and measurement of the tool's effects. The preliminary results of this work are promising, as a functional chatBot prototype has been developed in both conversational and non-conversational versions integrated into an open-source online judge and programming contest platform system. There is also an exploration of the possibility of generating a custom model based on a pre-trained one tailored to the domain of programming. This includes the integration of the created tool and the design of the experiment to measure its utility.

Keywords: assessment, chatGPT, learning strategies, LLMs, timely feedback

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13136 Evaluation of Different Fertilization Practices and Their Impacts on Soil Chemical and Microbial Properties in Two Agroecological Zones of Ghana

Authors: Ansong Richard Omari, Yosei Oikawa, Yoshiharu Fujii, Dorothea Sonoko Bellingrath-Kimura

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Renewed interest in soil management aimed at improving the productive capacity of Sub Saharan Africa (SSA) soils has called for the need to analyse the long term effect of different fertilization systems on soil. This study was conducted in two agroecological zones (i.e., Guinea Savannah (GS) and Deciduous forest (DF)) of Ghana to evaluate the impacts of long term (> 5 years) fertilization schemes on soil chemical and microbial properties. Soil samples under four different fertilization schemes (inorganic, inorganic and organic, organic, and no fertilization) were collected from 20 farmers` field in both agroecological zones. Soil analyses were conducted using standard procedures. All average soil quality parameters except extractable C, potential mineralizable nitrogen and CEC were significantly higher in DF sites compared to GS. Inorganic fertilization proved superior in soil chemical and microbial biomass especially in GS zone. In GS, soil deterioration index (DI) revealed that soil quality deteriorated significantly (−26%) under only organic fertilization system whereas soil improvement was observed under inorganic and no fertilization sites. In DF, either inorganic or organic and inorganic fertilization showed significant positive effects on soil quality. The high soil chemical composition and enhanced microbial biomass in DF were associated with the high rate of inorganic fertilization.

Keywords: deterioration index, fertilization scheme, microbial biomass, tropical agroecological zone

Procedia PDF Downloads 398