Search results for: learning science
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8966

Search results for: learning science

4166 Effect of R&D Human Capital Support for SMEs: An Analysis of Smes Support Program in South Korea

Authors: Misun Kim, Beomsoo Park

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Korean government has strongly supported SMEs financially and technically. It has also changed R&D manpower management so that SMEs can benefit from the knowledge of highly qualified experts. This study evaluates the impacts of such policy on SMEs and analyzes the factors affecting the growth of the firms. Then we compare the characteristics of high growth companies to general companies. This factors could be use in the future for identifying firms that would significantly benefit from manpower help.

Keywords: dispatch human Ccapital, high growth, science and technology policy, SMEs

Procedia PDF Downloads 294
4165 Teaching English in Low Resource-Environments: Problems and Prospects

Authors: Gift Chidi-Onwuta, Iwe Nkem Nkechinyere, Chikamadu Christabelle Chinyere

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The teaching of English is a resource-driven activity that requires rich resource-classroom settings for the delivery of effective lessons and the acquisition of interpersonal skills for integration in a target-language environment. However, throughout the world, English is often taught in low-resource classrooms. This paper is aimed to reveal the common problems associated with teaching English in low-resource environments and the prospects for teachers who found themselves in such undefined teaching settings. Self-structured and validated questionnaire in a closed-ended format, open question format and scaling format was administered to teachers across five countries: Nigeria, Cameroun, Iraq, Turkey, and Sudan. The study adopts situational language teaching theory (SLTT), which emphasizes a performance improvement imperative. This study inclines to this model because it maintains that learning must be fun and enjoyable like playing a favorite sport, just as in real life. Since teaching resources make learning engaging, we found this model apt for the current study. The perceptions of teachers about accessibility and functionality of teaching material resources, the nature of teaching outcomes in resource-less environments, their levels of involvement in improvisation and the prospects associated with resource limitations were sourced. Data were analysed using percentages and presented in frequency tables. Results: showed that a greater number of teachers across these nations do not have access to sufficient productive resource materials that can aid effective English language teaching. Teaching outcomes, from the findings, are affected by low material resources; however, results show certain advantages to teaching English with limited resources: flexibility and autonomy with students and creativity and innovation amongst teachers. Results further revealed group work, story, critical thinking strategy, flex, cardboards and flashcards, dictation and dramatization as common teaching strategies, as well as materials adopted by teachers to overcome low resource-related challenges in classrooms.

Keywords: teaching materials, low-resource environments, English language teaching, situational language theory

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4164 What Is At Stake When Developing and Using a Rubric to Judge Chemistry Honours Dissertations for Entry into a PhD?

Authors: Moira Cordiner

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As a result of an Australian university approving a policy to improve the quality of assessment practices, as an academic developer (AD) with expertise in criterion-referenced assessment commenced in 2008. The four-year appointment was to support 40 'champions' in their Schools. This presentation is based on the experiences of a group of Chemistry academics who worked with the AD to develop and implement an honours dissertation rubric. Honours is a research year following a three-year undergraduate year. If the standard of the student's work is high enough (mainly the dissertation) then the student can commence a PhD. What became clear during the process was that much more was at stake than just the successful development and trial of the rubric, including academics' reputations, university rankings and research outputs. Working with the champion-Head of School(HOS) and the honours coordinator, the AD helped them adapt an honours rubric that she had helped create and trial successfully for another Science discipline. A year of many meetings and complex power plays between the two academics finally resulted in a version that was critiqued by the Chemistry teaching and learning committee. Accompanying the rubric was an explanation of grading rules plus a list of supervisor expectations to explain to students how the rubric was used for grading. Further refinements were made until all staff were satisfied. It was trialled successfully in 2011, then small changes made. It was adapted and implemented for Medicine honours with her help in 2012. Despite coming to consensus about statements of quality in the rubric, a few academics found it challenging matching these to the dissertations and allocating a grade. They had had no time to undertake training to do this, or make overt their implicit criteria and standards, which some admitted they were using - 'I know what a first class is'. Other factors affecting grading included: the small School where all supervisors knew each other and the students, meant that friendships and collegiality were at stake if low grades were given; no external examiners were appointed-all were internal with the potential for bias; supervisors’ reputations were at stake if their students did not receive a good grade; the School's reputation was also at risk if insufficient honours students qualified for PhD entry; and research output was jeopardised without enough honours students to work on supervisors’ projects. A further complication during the study was a restructure of the university and retrenchments, with pressure to increase research output as world rankings assumed greater importance to senior management. In conclusion, much more was at stake than developing a usable rubric. The HOS had to be seen to champion the 'new' assessment practice while balancing institutional demands for increased research output and ensuring as many honours dissertations as possible met high standards, so that eventually the percentage of PhD completions and research output rose. It is therefore in the institution's best interest for this cycle to be maintained as it affects rankings and reputations. In this context, are rubrics redundant?

Keywords: explicit and implicit standards, judging quality, university rankings, research reputations

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4163 Integrating Experiential Real-World Learning in Undergraduate Degrees: Maximizing Benefits and Overcoming Challenges

Authors: Anne E. Goodenough

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One of the most important roles of higher education professionals is to ensure that graduates have excellent employment prospects. This means providing students with the skills necessary to be immediately effective in the workplace. Increasingly, universities are seeking to achieve this by moving from lecture-based and campus-delivered curricula to more varied delivery, which takes students out of their academic comfort zone and allows them to engage with, and be challenged by, real world issues. One popular approach is integration of problem-based learning (PBL) projects into curricula. However, although the potential benefits of PBL are considerable, it can be difficult to devise projects that are meaningful, such that they can be regarded as mere ‘hoop jumping’ exercises. This study examines three-way partnerships between academics, students, and external link organizations. It studied the experiences of all partners involved in different collaborative projects to identify how benefits can be maximized and challenges overcome. Focal collaborations included: (1) development of real-world modules with novel assessment whereby the organization became the ‘client’ for student consultancy work; (2) frameworks where students collected/analyzed data for link organizations in research methods modules; (3) placement-based internships and dissertations; (4) immersive fieldwork projects in novel locations; and (5) students working as partners on staff-led research with link organizations. Focus groups, questionnaires and semi-structured interviews were used to identify opportunities and barriers, while quantitative analysis of students’ grades was used to determine academic effectiveness. Common challenges identified by academics were finding suitable link organizations and devising projects that simultaneously provided education opportunities and tangible benefits. There was no ‘one size fits all’ formula for success, but careful planning and ensuring clarity of roles/responsibilities were vital. Students were very positive about collaboration projects. They identified benefits to confidence, time-keeping and communication, as well as conveying their enthusiasm when their work was of benefit to the wider community. They frequently highlighted employability opportunities that collaborative projects opened up and analysis of grades demonstrated the potential for such projects to increase attainment. Organizations generally recognized the value of project outputs, but often required considerable assistance to put the right scaffolding in place to ensure projects worked. Benefits were maximized by ensuring projects were well-designed, innovative, and challenging. Co-publication of projects in peer-reviewed journals sometimes gave additional benefits for all involved, being especially beneficial for student curriculum vitae. PBL and student projects are by no means new pedagogic approaches: the novelty here came from creating meaningful three-way partnerships between academics, students, and link organizations at all undergraduate levels. Such collaborations can allow students to make a genuine contribution to knowledge, answer real questions, solve actual problems, all while providing tangible benefits to organizations. Because projects are actually needed, students tend to engage with learning at a deep level. This enhances student experience, increases attainment, encourages development of subject-specific and transferable skills, and promotes networking opportunities. Such projects frequently rely upon students and staff working collaboratively, thereby also acting to break down the traditional teacher/learner division that is typically unhelpful in developing students as advanced learners.

Keywords: higher education, employability, link organizations, innovative teaching and learning methods, interactions between enterprise and education, student experience

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4162 Instrumental Characterization of Cyanobacteria as Polyhydroxybutyrate Producer

Authors: Eva Slaninova, Diana Cernayova, Zuzana Sedrlova, Katerina Mrazova, Petr Sedlacek, Jana Nebesarova, Stanislav Obruca

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Cyanobacteria are gram-negative prokaryotes belonging to a group of photosynthetic bacteria. In comparison with heterotrophic microorganisms, cyanobacteria utilize atmospheric nitrogen and carbon dioxide without any additional substrates. This ability of these microorganisms could be employed in biotechnology for the production of bioplastics, concretely polyhydroxyalkanoates (PHAs) which are primarily accumulated as a storage material in cells in the form of intracellular granules. In this study, there two cyanobacterial cultures from genera Synechocystis were used, namely Synechocystic sp. PCC 6803 and Synechocystis salina CCALA 192. There were optimized and used several various approaches, including microscopic techniques such as cryo-scanning electron microscopy (Cryo-SEM) and transmission electron microscopy (TEM), and fluorescence lifetime imaging microscopy using Nile red as a fluorescent probe (FLIM). Due to these instrumental techniques, the morphology of intracellular space and surface of cells were characterized. The next group of methods which were employed was spectroscopic techniques such as UV-Vis spectroscopy measured in two modes (turbidimetry and integration sphere) and Fourier transform infrared spectroscopy (FTIR). All these diverse techniques were used for the detection and characterization of pigments (chlorophylls, carotenoids, phycocyanin, etc.) and PHAs, in our case poly (3-hydroxybutyrate) (P3HB). To verify results, gas chromatography (GC) was employed concretely for the determination of the amount of P3HB in biomass. Cyanobacteria were also characterized as polyhydroxybutyrate producers by flow cytometer, which could count cells and at the same time distinguish cells including P3HB and without due to fluorescent probe called BODIPY and live/dead fluorescent probe SYTO Blue. Based on results, P3HB content in cyanobacteria cells was determined, as also the overall fitness of the cells. Acknowledgment: Funding: This study was partly funded by the projectGA19-29651L of the Czech Science Foundation (GACR) and partly funded by the Austrian Science Fund (FWF), project I 4082-B25.

Keywords: cyanobacteria, fluorescent probe, microscopic techniques, poly(3hydroxybutyrate), spectroscopy, chromatography

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4161 Embracing Transculturality by Internationalising the EFL Classroom

Authors: Karen Jacob

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Over the last decades, there has been a rise in the use of CLIL (content and language integrated learning) methodology as a way of reinforcing FL (foreign language) acquisition. CLIL techniques have also been transferred to the formal instruction-based FL classroom where through content-based lessons and project work it can very often say that teachers are ‘clilling’ in the FL classroom. When it comes to motivating students to acquire an FL, we have to take into account that English is not your run-of-the-mill FL: English is an international language (EIL). Consequently, this means that EFL students should be able to use English as an international medium of communication. This leads to the assumption that along with FL competence, speakers of EIL will need to become competent international citizens with knowledge of other societies, both contextually and geographically, and be flexible, open-minded, respectful and sensitive towards other world groups. Rather than ‘intercultural’ competence we should be referring to ‘transcultural’ competence. This paper reports the implementation of a content- and task-based approach to EFL teaching which was applied to two groups of 15 year-olds from two schools on the Spanish island of Mallorca during the school year 2015-2016. Students worked on three units of work that aimed at ‘internationalising’ the classroom by introducing topics that would encourage them to become transculturally aware of the world in which they live. In this paper we discuss the feedback given by the teachers and students on various aspects of the approach in order to answer the following research questions: 1) To what extent were the students motivated by the content and activities of the classes?; 2) Did this motivation have a positive effect on the students’ overall results for the subject; 3) Did the participants show any signs of becoming transculturally aware. Preliminary results from qualitative data show that the students enjoyed the move away from the more traditional EFL content and, as a result, they became more competent in speaking and writing. Students also appeared to become more knowledgeable and respectful towards the ‘other’. The EFL approach described in this paper takes a more qualitative approach to research by describing what is really going on in the EFL classroom and makes a conscious effort to provide real examples of not only the acquisition of linguistic competence but also the acquisition of other important communication skills that are of utmost importance in today's international arena.

Keywords: CLIL, content- and task-based learning, internationalisation, transcultural competence

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4160 Examining a Volunteer-Tutoring Program for Students with Special Education Needs

Authors: David Dean Hampton, William Morrison, Mary Rizza, Jan Osborn

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This evaluation examined the effects of a supplemental reading intervThis evaluation examined the effects of a supplemental reading intervention for students with specific learning disabilities in reading who were presented with below grade level on fall benchmark scores on DIBELS 6th ed. Revised. Participants consisted of a condition group, those who received supplemental reading instruction in addition to core + special education services and a comparison group of students who were at grade level in their fall benchmark scores. The students in the condition group received 26 weeks of Project MORE instruction delivered multiple times each week from trained volunteer tutors. Using a regression-discontinuity design, condition and comparison groups were compared on reading development growth using DIBELS ORF. Significant findings were reported for grade 2, 3, and 4. ntion for students with specific learning disabilities in reading who presented with below grade level on fall benchmark scores on DIBELS 6th ed. Revised. Participants consisted of a condition group, those who received supplemental reading instruction in addition to core + special education services and a comparison group of students who were at grade level in their fall benchmark scores. The students in the condition group received 26 weeks of Project MORE instruction delivered multiple times each week from trained volunteer tutors. Using a regression-discontinuity design, condition and comparison groups were compared on reading development growth using DIBELS ORF. Significant findings were reported for grade 2, 3, and 4.

Keywords: special education, evidence-based practices, curriculum, tutoring

Procedia PDF Downloads 53
4159 An Efficient Motion Recognition System Based on LMA Technique and a Discrete Hidden Markov Model

Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model

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4158 Integrative Omics-Portrayal Disentangles Molecular Heterogeneity and Progression Mechanisms of Cancer

Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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4157 Identifying Factors of Wellbeing in Russian Orphans

Authors: Alexandra Telitsyna, Galina Semya, Elvira Garifulina

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Introduction: Starting from 2012 Russia conducts deinstitutionalization policy and now the main indicator of success is the number of children living in institutions. Active family placement process has resulted in residents of the institution now mainly consists of adolescents with behavioral and emotional problems, children with disabilities and groups of siblings. Purpose of science research: The purpose of science research is to identify factors for child’s wellbeing while temporary stay in an orphanage and the subjective assessment of children's level of well-being (psychological well-being). Methods: The data used for this project was collected by the questionnaire of 72 indicators, a tool for monitoring the behavior of children and caregivers, an additional questionnaire for children; well-being assessment questionnaire containing 10 scales for three age groups from preschool to older adolescents. In 2016-2018, the research was conducted in 1873 institution in 85 regions of Russia. In each region a team of academics, specialists from Non-profits, independent experts was created. Training was conducted for team members through a series of webinars prior to undertaking the assessment. The results: To ensure the well-being of the children, the following conditions are necessary: 1- Life of children in institution is organised according to the principles of family care (including the creation of conditions for attachment to be formed); 2- Contribution to find family-based placement for children (including reintegration into the primary family); 3- Work with parents of children, who are placed in an organization at the request of parents; 4- Children attend schools according to their needs; 5- Training of staff and volunteers; 6- Special environment and services for children with special needs and children with disabilities; 7- Cooperation with NGOs; 8 - Openness and accessibility of the organization. Conclusion: A study of the psychological well-being of children showed that the most emotionally stressful for children were questions about the presence and frequency of contact with relatives, and the level of well-being is higher in the presence of a trusted adult and respect for rights. The greatest contribution to the trouble is made by the time the child is in the orphanage, the lack of contact with parents and relatives, the uncertainty of the future.

Keywords: identifying factors, orphans, Russia, wellbeing

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4156 Promoting Creative and Critical Thinking in Mathematics

Authors: Ana Maria Reis D'Azevedo Breda, Catarina Maria Neto da Cruz

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The Japanese art of origami provides a rich context for designing exploratory mathematical activities for children and young people. By folding a simple sheet of paper, fascinating and surprising planar and spatial configurations emerge. Equally surprising is the unfolding process, which also produces striking patterns. The procedure of folding, unfolding, and folding again allows the exploration of interesting geometric patterns. When adequately and systematically done, we may deduce some of the mathematical rules ruling origami. As the child/youth folds the sheet of paper repeatedly, he can physically observe how the forms he obtains are transformed and how they relate to the pattern of the corresponding unfolding, creating space for the understanding/discovery of mathematical principles regulating the folding-unfolding process. As part of a 2023 Summer Academy organized by a Portuguese university, a session entitled “Folding, Thinking and Generalizing” took place. Twenty-three students attended the session, all enrolled in the 2nd cycle of Portuguese Basic Education and aged between 10 and 12 years old. The main focus of this session was to foster the development of critical cognitive and socio-emotional skills among these young learners using origami. These skills included creativity, critical analysis, mathematical reasoning, collaboration, and communication. Employing a qualitative, descriptive, and interpretative analysis of data collected during the session through field notes and students’ written productions, our findings reveal that structured origami-based activities not only promote student engagement with mathematical concepts in a playful and interactive but also facilitate the development of socio-emotional skills, which include collaboration and effective communication between participants. This research highlights the value of integrating origami into educational practices, highlighting its role in supporting comprehensive cognitive and emotional learning experiences.

Keywords: skills, origami rules, active learning, hands-on activities

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4155 FracXpert: Ensemble Machine Learning Approach for Localization and Classification of Bone Fractures in Cricket Athletes

Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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4154 The Price of Knowledge in the Times of Commodification of Higher Education: A Case Study on the Changing Face of Education

Authors: Joanna Peksa, Faith Dillon-Lee

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Current developments in the Western economies have turned some universities into corporate institutions driven by practices of production and commodity. Academia is increasingly becoming integrated into national economies as a result of students paying fees and is consequently using business practices in student retention and engagement. With these changes, pedagogy status as a priority within the institution has been changing in light of these new demands. New strategies have blurred the boundaries that separate a student from a client. This led to a change of the dynamic, disrupting the traditional idea of the knowledge market, and emphasizing the corporate aspect of universities. In some cases, where students are seen primarily as a customer, the purpose of academia is no longer to educate but sell a commodity and retain fee-paying students. This paper considers opposing viewpoints on the commodification of higher education, reflecting on the reality of maintaining a pedagogic grounding in an increasingly commercialized sector. By analysing a case study of the Student Success Festival, an event that involved academic and marketing teams, the differences are considered between the respective visions of the pedagogic arm of the university and the corporate. This study argues that the initial concept of the event, based on the principles of gamification, independent learning, and cognitive criticality, was more clearly linked to a grounded pedagogic approach. However, when liaising with the marketing team in a crucial step in the creative process, it became apparent that these principles were not considered a priority in terms of their remit. While the study acknowledges in the power of pedagogy, the findings show that a pact of concord is necessary between different stakeholders in order for students to benefit fully from their learning experience. Nevertheless, while issues of power prevail and whenever power is unevenly distributed, reaching a consensus becomes increasingly challenging and further research should closely monitor the developments in pedagogy in the UK higher education.

Keywords: economic pressure, commodification, pedagogy, gamification, public service, marketization

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4153 Impact of Information and Communication Technology on Academic Performance of Senior Secondary Schools Students in Gwagwalada Area Council of Federal Capital Territory, Abuja

Authors: Suleiman Garba, Haruna Ishaku

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Information and communication technology (ICT) includes any communication device encompassing: radio, television, cellular phones, computer, satellite systems and so on, as well as the various services and applications associated with them. The significance of ICT cannot be over-emphasized in education. The teaching and learning processes have integrated with the application of ICTs for effectiveness and enhancement of academic performance among the students. Today, as the educational sector is faced with series of changes and reforms, it was noted that the problem of information technology illiteracy was a serious one among the schools’ teachers in the country as it cuts across primary, secondary schools and tertiary institutions. This study investigated the impact of ICT on the academic performance of senior secondary schools students in Gwagwalada Area Council of Federal Capital Territory (FCT), Abuja. A sample of 120 SSS III students was involved in the study. They were selected by using simple random sampling technique. A questionnaire was developed and validated through expert judgement and reliability co-efficient of 0.81 was obtained. It was used to gather relevant data from the respondents. Findings revealed that there was positive impact of ICT on academic performance of senior secondary schools students. The findings indicated the causes of poor academic performance among the students as lack of qualified teachers to teach in schools, peer group influence, and bullying. Significantly, the findings revealed that ICT had a positive impact on students’ academic performance. The null hypotheses were tested using t-test at 0.05 level of significance. It was discovered that there was significant difference between male and female secondary schools’ students' impact of ICT on academic performance in Gwagawalada Area Council of FCT-Abuja. Based on these findings, some recommendations were made which include: adequate funds should be provided towards procurement of ICT resources, relevant textbooks to enhance students’ active participation in learning processes and students should be provided with internet accessibility at inexpensive rate so as to create a platform for accessing useful information in the pursuit of academic excellence.

Keywords: academic performance, impact, information communication technology, schools, students

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4152 Proficiency Testing of English for Specific Academic Purpose: Using a Pilot Test in a Taiwanese University as an Example

Authors: Wenli Tsou, Jessica Wu

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Courses of English for specific academic purposes (ESAP) have become popular for higher education in Taiwan; however, no standardized tests have been developed for evaluating learners’ English proficiency in individual designated fields. Assuming a learner’s proficiency in a specific academic area is built up with one’s general proficiency in English with specific knowledge and vocabulary in the content areas, an adequate ESAP proficiency test may be constructed by some selected test items related to the designated academic areas. In this study, through collaboration between a language testing institution and a university in Taiwan, three sets of ESAP tests, covering three disciplinary areas of business and the workplace, science and engineering, and health and medicine majors, were developed and administered to sophomore students (N=1704) who were enrolled in ESAP courses at a university in southern Taiwan. For this study, the courses were grouped into the above-mentioned three disciplines, and students took the specialized proficiency test based on the ESAP course they were taking. Because students were free to select which ESAP course to take, each course had both major and non-major students. Toward the end of the one-semester course, ending in January, 2015, each student took two tests, one of general English (General English Proficiency Test, or GEPT) and the other ESAP. Following each test, students filled out a survey, reporting their test taking experiences. After comparing students’ two test scores, it was found that business majors and health and medical students performed better in ESAP than the non-majors in the class, whereas science and engineering majors did about the same as their non-major counterparts. In addition, test takers with CERF B2 (upper intermediate) level or above performed well in both tests, while students who are below B2 did slightly better in ESAP. The findings suggest that students’ test performance have been enhanced by their specialist content and vocabulary knowledge. Furthermore, results of the survey show that the difficulty levels reported by students are consistent with their test performances. Based on the item analysis, the findings can be used to develop proficiency tests for specific disciplines and to identify ability indicators for college students in their designated fields.

Keywords: english for specific academic purposes (ESAP), general english proficiency test (GEPT), higher education, proficiency test

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4151 Evaluation of a Higher Diploma in Mental Health Nursing Using Qualitative and Quantitative Methods: Effects on Student Behavior, Attitude and Perception

Authors: T. Frawley, G. O'Kelly

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The UCD School of Nursing, Midwifery and Health Systems Higher Diploma in Mental Health (HDMH) nursing programme commenced in January 2017. Forty students successfully completed the programme. Programme evaluation was conducted from the outset. Research ethics approval was granted by the UCD Human Research Ethics Committee – Sciences in November 2016 (LS-E-16-163). Plan for Sustainability: Each iteration of the programme continues to be evaluated and adjusted accordingly. Aims: The ultimate purpose of the HDMH programme is to prepare registered nurses (registered children’s nurse (RCN), registered nurse in intellectual disability (RNID) and registered general nurse (RGN)) to function as effective registered psychiatric nurses in all settings which provide care and treatment for people experiencing mental health difficulties. Curriculum evaluation is essential to ensure that the programme achieves its purpose, that aims and expected outcomes are met and that required changes are highlighted for the programme’s continuing positive development. Methods: Both quantitative and qualitative methods were used in the evaluation. A series of questionnaires were used (the majority pre and post programme) to determine student perceptions of the programme, behaviour and attitudinal change from commencement to completion. These included the student assessment of learning gains (SALG); mental health knowledge schedule (MAKS); mental health clinician attitudes scale (MICA); reported and intended behaviour scale (RIBS); and community attitudes towards the mentally ill (CAMI). In addition, student and staff focus groups were conducted. Evaluation methods also incorporated module feedback. Outcome/Results: The evaluation highlighted a very positive response in relation to the achievement of programme outcomes and preparation for future work as registered psychiatric nursing. Some areas were highlighted for further development, which have been taken cognisance of in the 2019 iteration of the programme.

Keywords: learning gains, mental health, nursing, stigma

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4150 Application of Regularized Low-Rank Matrix Factorization in Personalized Targeting

Authors: Kourosh Modarresi

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The Netflix problem has brought the topic of “Recommendation Systems” into the mainstream of computer science, mathematics, and statistics. Though much progress has been made, the available algorithms do not obtain satisfactory results. The success of these algorithms is rarely above 5%. This work is based on the belief that the main challenge is to come up with “scalable personalization” models. This paper uses an adaptive regularization of inverse singular value decomposition (SVD) that applies adaptive penalization on the singular vectors. The results show far better matching for recommender systems when compared to the ones from the state of the art models in the industry.

Keywords: convex optimization, LASSO, regression, recommender systems, singular value decomposition, low rank approximation

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4149 Solution of Hybrid Fuzzy Differential Equations

Authors: Mahmood Otadi, Maryam Mosleh

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The hybrid differential equations have a wide range of applications in science and engineering. In this paper, the homotopy analysis method (HAM) is applied to obtain the series solution of the hybrid differential equations. Using the homotopy analysis method, it is possible to find the exact solution or an approximate solution of the problem. Comparisons are made between improved predictor-corrector method, homotopy analysis method and the exact solution. Finally, we illustrate our approach by some numerical example.

Keywords: fuzzy number, fuzzy ODE, HAM, approximate method

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4148 AI/ML Atmospheric Parameters Retrieval Using the “Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN)”

Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

Abstract:

Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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4147 Emotion Recognition in Video and Images in the Wild

Authors: Faizan Tariq, Moayid Ali Zaidi

Abstract:

Facial emotion recognition algorithms are expanding rapidly now a day. People are using different algorithms with different combinations to generate best results. There are six basic emotions which are being studied in this area. Author tried to recognize the facial expressions using object detector algorithms instead of traditional algorithms. Two object detection algorithms were chosen which are Faster R-CNN and YOLO. For pre-processing we used image rotation and batch normalization. The dataset I have chosen for the experiments is Static Facial Expression in Wild (SFEW). Our approach worked well but there is still a lot of room to improve it, which will be a future direction.

Keywords: face recognition, emotion recognition, deep learning, CNN

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4146 On the Way to the European Research Area: Programmes of the European Union as Factor of the Innovation Development the Scientific Organization in Ukraine

Authors: Yuri Nikitin, Veronika Rukas

Abstract:

Within the framework of the FP7 project "START" the cooperation with European research centres has had a positive impact on raising the level of innovation researches and the introduction of innovations Institute for Super hard Materials of the National Academy of Sciences (ISM NAS) of Ukraine in the economy of Europe and Ukraine, which in turn permits to speeds up the way for Ukrainian science to the European research area through the creation in Ukraine the scientific organizations of innovative type.

Keywords: programs of the EU, innovative scientific results, innovation competence of the staff, commercialization in business of industry of the Europe and Ukraine

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4145 Comparing the Apparent Error Rate of Gender Specifying from Human Skeletal Remains by Using Classification and Cluster Methods

Authors: Jularat Chumnaul

Abstract:

In forensic science, corpses from various homicides are different; there are both complete and incomplete, depending on causes of death or forms of homicide. For example, some corpses are cut into pieces, some are camouflaged by dumping into the river, some are buried, some are burned to destroy the evidence, and others. If the corpses are incomplete, it can lead to the difficulty of personally identifying because some tissues and bones are destroyed. To specify gender of the corpses from skeletal remains, the most precise method is DNA identification. However, this method is costly and takes longer so that other identification techniques are used instead. The first technique that is widely used is considering the features of bones. In general, an evidence from the corpses such as some pieces of bones, especially the skull and pelvis can be used to identify their gender. To use this technique, forensic scientists are required observation skills in order to classify the difference between male and female bones. Although this technique is uncomplicated, saving time and cost, and the forensic scientists can fairly accurately determine gender by using this technique (apparently an accuracy rate of 90% or more), the crucial disadvantage is there are only some positions of skeleton that can be used to specify gender such as supraorbital ridge, nuchal crest, temporal lobe, mandible, and chin. Therefore, the skeletal remains that will be used have to be complete. The other technique that is widely used for gender specifying in forensic science and archeology is skeletal measurements. The advantage of this method is it can be used in several positions in one piece of bones, and it can be used even if the bones are not complete. In this study, the classification and cluster analysis are applied to this technique, including the Kth Nearest Neighbor Classification, Classification Tree, Ward Linkage Cluster, K-mean Cluster, and Two Step Cluster. The data contains 507 particular individuals and 9 skeletal measurements (diameter measurements), and the performance of five methods are investigated by considering the apparent error rate (APER). The results from this study indicate that the Two Step Cluster and Kth Nearest Neighbor method seem to be suitable to specify gender from human skeletal remains because both yield small apparent error rate of 0.20% and 4.14%, respectively. On the other hand, the Classification Tree, Ward Linkage Cluster, and K-mean Cluster method are not appropriate since they yield large apparent error rate of 10.65%, 10.65%, and 16.37%, respectively. However, there are other ways to evaluate the performance of classification such as an estimate of the error rate using the holdout procedure or misclassification costs, and the difference methods can make the different conclusions.

Keywords: skeletal measurements, classification, cluster, apparent error rate

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4144 Digital Revolution a Veritable Infrastructure for Technological Development

Authors: Osakwe Jude Odiakaosa

Abstract:

Today’s digital society is characterized by e-education or e-learning, e-commerce, and so on. All these have been propelled by digital revolution. Digital technology such as computer technology, Global Positioning System (GPS) and Geographic Information System (GIS) has been having a tremendous impact on the field of technology. This development has positively affected the scope, methods, speed of data acquisition, data management and the rate of delivery of the results (map and other map products) of data processing. This paper tries to address the impact of revolution brought by digital technology.

Keywords: digital revolution, internet, technology, data management

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4143 Towards Intercultural Competence in EFL Textbook: the Case of ‘New Prospects’

Authors: Kamilia Mebarki

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The promotion of intercultural competence plays an important role in foreign language education. The outcome of intercultural educationalists‟ studies was the adoption of intercultural language learning and a modified version of the Communicative Competence that encompasses an intercultural component enabling language learners to communicate successfully interculturally. Intercultural Competencehas an even more central role in teaching English as a foreign language (EFL) since efforts are critical to preparing learners for intercultural communisation in our global world. In these efforts, EFL learning materials are a crucial stimulus for developing learners’ intercultural competence. There has been a continuous interest in the analysis of EFL textbooks by researcher all over the world. One specific area that has received prominent attention in recent years is a focus on how the cultural content of EFL materials promote intercultural competence. In the Algerian context, research on the locally produced EFL textbooks tend to focus on investigating the linguistic and communicative competence. The cultural content of the materials has not yet been systematically researched. Therefore, this study contributes to filling this gap by evaluating the locally published EFL textbook ‘New Prospects’ used at the high school level as well as investigating teachers’ views and attitudes on the cultural content of ‘New Prospects’ alongside two others locally produced EFL textbooks ‘Getting Through’ and ‘At the Crossroad’ used at high school level. To estimate the textbook’s potential of developing intercultural competence, mixed methods, a combination of quantitative and qualitative data collection, was used in the material evaluation analysed via content analysis and in the survey questionnaire and interview with teachers.Data collection and analysis were supported by the frameworks developed by the researcher for analysing the textbook, questionnaire, and interview. Indeed, based on the literature, three frameworks/ models are developed in this study to analyse, on one hand, the cultural contexts and themes discussed in the material that play an important role in fostering learners’ intercultural awareness. On the other hand, to evaluate the promotion of developing intercultural competence.

Keywords: intercultural communication, intercultural communicative competence, intercultural competence, EFL materials

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4142 Optics Meets Microfluidics for Highly Sensitive Force Sensing

Authors: Iliya Dimitrov Stoev, Benjamin Seelbinder, Elena Erben, Nicola Maghelli, Moritz Kreysing

Abstract:

Despite the revolutionizing impact of optical tweezers in materials science and cell biology up to the present date, trapping has so far extensively relied on specific material properties of the probe and local heating has limited applications related to investigating dynamic processes within living systems. To overcome these limitations while maintaining high sensitivity, here we present a new optofluidic approach that can be used to gently trap microscopic particles and measure femtoNewton forces in a contact-free manner and with thermally limited precision.

Keywords: optofluidics, force measurements, microrheology, FLUCS, thermoviscous flows

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4141 Problem Solving: Process or Product? A Mathematics Approach to Problem Solving in Knowledge Management

Authors: A. Giannakopoulos, S. B. Buckley

Abstract:

Problem solving in any field is recognised as a prerequisite for any advancement in knowledge. For example in South Africa it is one of the seven critical outcomes of education together with critical thinking. As a systematic way to problem solving was initiated in mathematics by the great mathematician George Polya (the father of problem solving), more detailed and comprehensive ways in problem solving have been developed. This paper is based on the findings by the author and subsequent recommendations for further research in problem solving and critical thinking. Although the study was done in mathematics, there is no doubt by now in almost anyone’s mind that mathematics is involved to a greater or a lesser extent in all fields, from symbols, to variables, to equations, to logic, to critical thinking. Therefore it stands to reason that mathematical principles and learning cannot be divorced from any field. In management of knowledge situations, the types of problems are similar to mathematics problems varying from simple to analogical to complex; from well-structured to ill-structured problems. While simple problems could be solved by employees by adhering to prescribed sequential steps (the process), analogical and complex problems cannot be proceduralised and that diminishes the capacity of the organisation of knowledge creation and innovation. The low efficiency in some organisations and the low pass rates in mathematics prompted the author to view problem solving as a product. The authors argue that using mathematical approaches to knowledge management problem solving and treating problem solving as a product will empower the employee through further training to tackle analogical and complex problems. The question the authors asked was: If it is true that problem solving and critical thinking are indeed basic skills necessary for advancement of knowledge why is there so little literature of knowledge management (KM) about them and how they are connected and advance KM?This paper concludes with a conceptual model which is based on general accepted principles of knowledge acquisition (developing a learning organisation), knowledge creation, sharing, disseminating and storing thereof, the five pillars of knowledge management (KM). This model, also expands on Gray’s framework on KM practices and problem solving and opens the doors to a new approach to training employees in general and domain specific areas problems which can be adapted in any type of organisation.

Keywords: critical thinking, knowledge management, mathematics, problem solving

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4140 Biomechanical Analysis and Interpretation of Pitching Sequences for Enhanced Performance Programming

Authors: Corey F. Fitzgerald

Abstract:

This study provides a comprehensive examination of the biomechanical sequencing inherent in pitching motions, coupled with an advanced methodology for interpreting gathered data to inform programming strategies. The analysis is conducted utilizing state-of-the-art biomechanical laboratory equipment capable of detecting subtle changes and deviations, facilitating highly informed decision-making processes. Through this presentation, the intricate dynamics of pitching sequences are meticulously discussed to highlight the complex movement patterns accessible and actionable for performance enhancement purposes in the weight room.

Keywords: sport science, applied biomechanics, strength and conditioning, applied research

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4139 Using Support Vector Machines for Measuring Democracy

Authors: Tommy Krieger, Klaus Gruendler

Abstract:

We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.

Keywords: democracy, democracy index, machine learning, support vector machines

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4138 Education of Purchasing Professionals in Austria: Competence Based View

Authors: Volker Koch

Abstract:

This paper deals with the education of purchasing professionals in Austria. In this education, equivalent and measurable criteria are collected in order to create a comparison. The comparison shows the problem. To make the aforementioned comparison possible, methodologies such as KODE-Competence Atlas or presentations in a matrix form are used. The result shows the content taught and whether there are any similarities or interesting differences in the current Austrian purchasers’ formations. Purchasing professionals learning competencies are also illustrated in the study result.

Keywords: competencies, education, purchasing professional, technological-oriented

Procedia PDF Downloads 283
4137 A Data-Driven Compartmental Model for Dengue Forecasting and Covariate Inference

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

Abstract:

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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