Search results for: learning outcomes assessment

Authors: Bing Li, Zhi Li, Yilong Yang

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Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

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Authors: Jakub Zembrzuski, Bartosz Sobczyk, Mikołaj MIśkiewicz

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Besides designing new constructions, engineers all over the world must face another problem – maintenance, repairs, and assessment of the technical condition of existing bridges. To solve more complex issues, it is necessary to be familiar with the theory of finite element method and to have access to the software that provides sufficient tools which to enable create of sometimes significantly advanced numerical models. The paper includes a brief assessment of the technical condition, a description of the in situ non-destructive testing carried out and the FEM models created for global and local analysis. In situ testing was performed using strain gauges and displacement sensors. Numerical models were created using various software and numerical modeling techniques. Particularly noteworthy is the method of modeling riveted joints of the crossbeam of the viaduct. It is a simplified method that consists of the use of only basic numerical tools such as beam and shell finite elements, constraints, and simplified boundary conditions (fixed support and symmetry). The results of the numerical analyses were presented and discussed. It is clearly explained why the structure did not fail, despite the fact that the weld of the deck plate completely failed. A further research problem that was solved was to determine the cause of the rapid increase in values on the stress diagram in the cross-section of the transverse section. The problems were solved using the solely mentioned, simplified method of modeling riveted joints, which demonstrates that it is possible to solve such problems without access to sophisticated software that enables to performance of the advanced nonlinear analysis. Moreover, the obtained results are of great importance in the field of assessing the operation of bridge structures with an orthotropic plate.

Keywords: bridge, diagnostics, FEM simulations, failure, NDT, in situ testing

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Authors: Rade M. Ciric

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The paper shows the development and implementation of the syllabus of the subject 'Distribution and Industrial Networks', attended by the vocational specialist Year 4 students of the Electric Power Engineering study programme at the Higher Education Technical School of Vocational Studies in Novi Sad. The aim of the subject is to equip students with the knowledge necessary for planning, exploitation and management of distributive and industrial electric power networks in an open electricity market environment. The results of the evaluation of educational outcomes on the subject are presented and discussed.

Keywords: engineering education, power distribution network, syllabus implementation, outcome evaluation

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Authors: Alev Atak

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In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

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Authors: Neha Toppo

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Method and strategies of teaching instruction highly influence learning of students. In second language teaching, number of ways and methods has been suggested by different scholars and researchers through times. The present article deals with the role of teaching instruction in developing compositional ability of students in writing. It focuses on the secondary level students of rural areas, whose exposure to English language is limited and they face challenges even in simple compositions. The students till high school suffer with their disability in writing formal letter, application, essay, paragraph etc. They face problem in note making, writing answers in examination using their own words and depend fully on rote learning. It becomes difficult for them to give language to their own ideas. Teaching writing composition deserves special attention as writing is an integral part of language learning and students at this level are expected to have sound compositional ability for it is useful in numerous domains. Effective method of instruction could help students to learn expression of self, correct selection of vocabulary and grammar, contextual writing, composition of formal and informal writing. It is not limited to school but continues to be important in various other fields outside the school such as in newspaper and magazine, official work, legislative work, material writing, academic writing, personal writing, etc. The study is based on the experimental method, which hypothesize that guided instruction will be more effective in teaching writing compositions than usual instruction in which students are left to compose by their own without any help. In the test, students of one section are asked to write an essay on the given topic without guidance and another section are asked to write the same but with the assistance of guided instruction in which students have been provided with a few vocabulary and sentence structure. This process is repeated in few more schools to get generalize data. The study shows the difference on students’ performance using both the instructions; guided and unguided. The conclusion of the study is followed by the finding that writing skill of the students is quite poor but with the help of guided instruction they perform better. The students are in need of better teaching instruction to develop their writing skills.

Keywords: composition, essay, guided instruction, writing skill

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Authors: Farida Habib, Haya Alfozan, Eman Miligi, Najla Alotaibi

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Background: Women’s satisfaction with maternity services, especially care during labor and birth, has become highly significant to healthcare providers, administrators, and policymakers. Purpose: The aims of this study were to assess maternal satisfaction regarding the quality of care during labor and to compare the level of maternal satisfaction between women who delivered by physicians and those delivered by midwives. Methodology: A descriptive, cross-sectional, correlational design was used. A convenient sample of 180 low-risk cases of immediate postpartum women who delivered at King Abdul-Aziz medical city was recruited. Women whose babies were diagnosed with serious health problems were excluded from the study. Data were collected using a self-administered questionnaire. The validity and reliability of the questionnaire were ensured. The questionnaire included three parts, namely: demographics data, medical history, and obstetrical history, and the last part is the satisfaction assessment tool. Ethical confederations were ensured. Maternal satisfaction during labor was classified in terms of health care, health workers' communication, and the environment. Results: Regarding health care, women were highly satisfied with care received from nurse (M = 4.21 + 0.88), medical care received (M = 4.17 + 0.79), and comfort techniques (M = 4.04 + 0.91). Regarding health workers' communication, women were highly satisfied with the provider to treat with dignity and respect (M = 4.03 + 0.91) and orientation to the toilet, bathroom, washing area (M = 4.00 + 0.93). Regarding the environment, women were highly satisfied with the experience of their baby's birth (M = 4.18 + 0.98) and supplies with drugs and supplies (M = 4.09 + 0.97). There was no statistically significant difference in maternal satisfaction between women who delivered by physicians and those delivered by midwives. Conclusion: Women were generally satisfied with their labor and delivery experience. There was no difference in maternal satisfaction on the labor process between women who delivered by physicians and those delivered by midwives.

Keywords: maternity, satisfaction, labor, delivery

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Authors: Amir Ahmad Dehghani, Morteza Nabizadeh

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This paper presents the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to flood hydrograph modeling of Shahid Rajaee reservoir dam located in Iran. This was carried out using 11 flood hydrographs recorded in Tajan river gauging station. From this dataset, 9 flood hydrographs were chosen to train the model and 2 flood hydrographs to test the model. The different architectures of neuro-fuzzy model according to the membership function and learning algorithm were designed and trained with different epochs. The results were evaluated in comparison with the observed hydrographs and the best structure of model was chosen according the least RMSE in each performance. To evaluate the efficiency of neuro-fuzzy model, various statistical indices such as Nash-Sutcliff and flood peak discharge error criteria were calculated. In this simulation, the coordinates of a flood hydrograph including peak discharge were estimated using the discharge values occurred in the earlier time steps as input values to the neuro-fuzzy model. These results indicate the satisfactory efficiency of neuro-fuzzy model for flood simulating. This performance of the model demonstrates the suitability of the implemented approach to flood management projects.

Keywords: adaptive neuro-fuzzy inference system, flood hydrograph, hybrid learning algorithm, Shahid Rajaee reservoir dam

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Authors: Mark Shiu-kee Shum, Dan Shi

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The paper aims to introduce the ‘Reading to Learn, Learning to Write’ (R2L) pedagogy and its application in teaching reading and writing to non-Chinese speaking (NCS) students in Hong Kong. Guided by the teaching and learning cycles accentuated in R2L pedagogy, sufficient scaffolding was provided for students with an explicit teaching method in literacy education. To understand the influence of using R2L pedagogy on students’ reading and writing abilities across different genres, quantitative data were collected by pre- and post-test of reading and writing tasks in the two different genres of narration and explanation. The pre-test and post-test were used to assess students’ writing performance based on the three textual components of context, discourse, and graphic features, while the reading abilities were assessed at the literal, inferred and interpretive levels of reading comprehension to measure the effectiveness of R2L pedagogy on their literacy improvement. The findings show the use of R2L pedagogy has been proven more effective in improving NCS students’ writing abilities than developing their reading capacity. It is hoped that the R2L-based pedagogic practices can serve as teaching references and pedagogic rationale for L1 language teachers and raise their metalinguistic awareness in teaching Chinese to non-Chinese speaking students in Hong Kong and beyond.

Keywords: pedagogical inclusiveness, literacy education, ethnic minority, reading and writing

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Authors: Chathurika Sewwandi Kannangara, Jerome Carson

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The objective of this research is to identify strengths among the individuals with dyslexia and design a positive psychology intervention to support such individuals. Dyslexia is a combination of abilities and difficulties that affect the learning process in areas as such reading, spelling and writing. It is a persistent condition. The research aims to adapt positive psychology techniques to support individuals with dyslexia. Population of the research will be undergraduate and college level students with dyslexia. First phase of the study will be conducted on a sample of undergraduate and college level students with dyslexia in Bolton, UK. The concept of treatment in positive psychology is not only to fix the component just what is wrong, instead it is also to develop and construct on what is right in the individual. The first phase of the research aims to identify the signature strengths among the individuals with dyslexia using Interviews, Descriptions on personal experiences on ‘My life with Dyslexia’, and Values in Action (VIA) strength survey. In order to conduct the survey for individuals with dyslexia, the VIA survey has been hosted in a website which is solely developed in the form of dyslexia friendly context. Dyslexia friendly website for surveys had designed and developed following the British Dyslexia Association guidelines. The findings of the first phase would be utilized for the second phase of the research to develop the positive psychology intervention.

Keywords: dyslexia, signature strengths, positive psychology, qualitative study, learning difficulties

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Authors: Caroline Labib

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This paper reports on a qualitative study exploring the approaches teachers used to integrate computers or smart tablets into their program planning. Their aim was to integrate ICT into children’s play, thereby supporting children’s learning and development. Data was collected in preschool settings in Melbourne in 2016. Interviews with teachers, observations of teacher interactions with children and copies of teachers’ planning and observation documents informed the study. The paper looks closely at findings from two early childhood settings and focuses on exploring the differing approaches two EC teachers have adopted when integrating iPad or computers into their settings. Data analysis revealed three key approaches which have been labelled: free digital play, guided digital play and teacher-led digital use. Importantly, teacher decisions were influenced by the interplay between the opportunities that the ICT tools offered, the teachers’ prior knowledge and experience about ICT and children’s learning needs and contexts. This paper is a snapshot of two early childhood settings, and further research will encompass data from six more early childhood settings in Victoria with the aim of exploring a wide range of motivating factors for early childhood teachers trying to integrate ICT into their programs.

Keywords: early childhood education (ECE), digital play, information and communication technologies (ICT), play, and teachers' interaction approaches

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Authors: Qin-Min Ge, Shu-Ming Pan

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Emergency clinicians usually get teaching qualification after graduating from medical universities without special faculty training in China mainland. Emergency departments are overcrowded places, with large numbers of patients suffering undifferentiated illness. In the field of emergency medicine (EM), improving the faculty competencies and developing the teaching skills are important for medical education, they could enhance learners outcomes and hence affect the patients prognosis indirectly. This article highlights the necessities of faculty training in EM, illustrates the qualities a good clinical educator should qualify, advances the skills as educators in an academic setting and discusses the ways to be good clinical teachers.

Keywords: emergency education, competence, faculty training, teaching, emergency medicine

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Authors: Fabio L. Vieira, Micaelle F. C. Lemos, Luciano C. Lemos, Rafaela S. Oliveira, Ian A. Cunha

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Brazil has some challenges ahead related to population oral health, most of them associated with the need of expanding into the local level its promotion and prevention activities, offer equal access to services and promote changes in the lifestyle of the population. The program implemented an oral health initiative in public schools in the city of Salvador, Bahia. The mission was to improve oral health among students on primary and secondary education, from 2 to 15 years old, using the school as a pathway to increase access to healthcare. The main actions consisted of a team's visit to the schools with educational sessions for dental cavity prevention and individual assessment. The program incorporated a clinical surveillance component through a dental evaluation of every student searching for dental disease and caries, standardization of the dentists’ team to reach uniform classification on the assessments, and the use of an online platform to register data directly from the schools. Sequentially, the students with caries were referred for free clinical treatment on the program’s Health Centre. The primary purpose of this study was to analyze the effects and outcomes of this school-based oral health program. The study sample was composed by data of a period of 3 years - 2015 to 2017 - from 13 public schools on the suburb of the city of Salvador with a total number of assessments of 9,278 on this period. From the data collected the prevalence of children with decay on permanent teeth was chosen as the most reliable indicator. The prevalence was calculated for each one of the 13 schools using the number of children with 1 or more dental caries on permanent teeth divided by the total number of students assessed for school each year. Then the percentage change per year was calculated for each school. Some schools presented a higher variation on the total number of assessments in one of the three years, so for these, the percentage change calculation was done using the two years with less variation. The results show that 10 of the 13 schools presented significative improvements for the indicator of caries in permanent teeth. The mean for the number of students with caries percentage reduction on the 13 schools was 26.8%, and the median was 32.2% caries in permanent teeth institution. The highest percentage of improvement reached a decrease of 65.6% on the indicator. Three schools presented a rise in caries prevalence (8.9, 18.9 and 37.2% increase) that, on an initial analysis, seems to be explained with the students’ cohort rotation among other schools, as well as absenteeism on the treatment. In conclusion, the program shows a relevant impact on the reduction of caries in permanent teeth among students and the need for the continuity and expansion of this integrated healthcare approach. It has also been evident the significative of the articulation between health and educational systems representing a fundamental approach to improve healthcare access for children especially in scenarios such as presented in Brazil.

Keywords: primary care, public health, oral health, school-based oral health, data management

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Authors: Babak Nemat Shahrbabaki, Arezo Fallahi, Masoomeh Hashemian

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Introduction: Health and safety are basic components of civil right. Health care systems in different countries were influenced by political, economic and cultural circumstances. In order to health services to people, these systems are organized with different forms, methods such as: prevention, treatment and rehabilitation and in this among, public satisfaction with the services provided is important. This study aimed to determine client satisfaction with family physician and relationship with physician’ demographic variables in health care centers of Jiroft county, Iran. Methods: This is a descriptive-analytical study. The collective data tool was a self-made questionnaire with two parts. The first part comprised demographic characteristics, and the second part contained 11 items for the assessment of satisfaction with family physician from different aspects. In addition, questionnaire, reliability and validity were confirmed. Random simple sampling method was used to determine samples. 234 people referred to the health centers filled questionnaire. The data were analyzed using SPSS software, and inferential statistical analysis was performed. Findings: The majority of the study population were women, married, and aged between 18 and 62 years (mean= 30.09±10.71). Total average satisfaction score was 42.63±3.68. Overall satisfaction averages were 9.47% very high, 30.04% high, 33.09% moderate, 15.12% low, and 12.28% very low. Except lodge on of family physician none of physician’ demographic variables did not effect on satisfaction index. Discussion & Conclusion: The Results showed that mean of satisfaction indexes of family physicians was high and lodge on of family physician effected on this index. Informing people about the main goals of family-doctor program will help to promote the quality of program and increase people satisfaction.

Keywords: family physician program, satisfaction, health-care centers, client

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Authors: Ashit Syngle, Inderjit Verma, Pawan Krishan

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Therapeutic approaches used previously relied on disease-modifying antirheumatic drugs (DMARDs) that had only partial clinical benefit and were associated with significant toxicity. Spironolactone, an oral aldosterone antagonist, suppresses inflammatory mediators. Clinical efficacy of spironolactone compared with placebo in patients with active psoriatic arthritis despite treatment with prior traditional DMARDs. In the 24-week, placebo-controlled study patients (n=31) were randomized to placebo and spironolactone (2 m/kg/day). Patients on background concurrent DMARDs continued stable doses (methotrexate, leflunomide, and/or sulfasalazine). Primary outcome measures were the assessment of disease activity measures i.e. 28-joint disease activity score (DAS28) and diseases activity in psoriatic arthritis (DAPSA) at week 24. The key secondary endpoint was change from baseline in Health Assessment Questionnaire–Disability Index (HAQ-DI) at week 24. Additional efficacy outcome measures at week 24 included improvements in the markers of inflammation (ESR and CRP) and pro-inflammatory cytokines TNF-α, IL-6 and IL-1. At week 24, spironolactone significantly reduced disease activity measure DAS-28 (p<0.001) and DAPSA (p=0.001) compared with placebo. Significant improvements in key secondary measures HAQ-DI (disability index) were evident with spironolactone (p=0.02) versus placebo. After week 24, there was significant reduction in pro-inflammatory cytokines level TNF-α, IL-6 (p<0.01) as compared with placebo group. However, there was no significant improvement in IL-1 in both treatment and placebo groups. There were minor side effects which did not mandate stopping of spironolactone. No change in any biochemical profile was noted after spironolactone treatment. Spironolactone was effective in the treatment of PsA, improving disease activity, physical function and suppressing the level of pro-inflammatory cytokines. Spironolactone demonstrated an acceptable safety profile and was well tolerated.

Keywords: spironolactone, inflammation, inflammatory cytokine, psoriatic arthritis

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Authors: Z. Sun

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Health communication is essential in promoting healthy lifestyles, managing disease conditions, and eventually reducing health disparities. The key elements of successful health communication always include the development of communication strategies to engage people in thinking about their health, inform them about healthy choices, persuade them to adopt safe and healthy behaviours, and eventually achieve public health objectives. The use of 'Narrative' is recognised as a kind of health communication strategy to enhance personal and public health due to its potential persuasive effect in motivating and supporting individuals change their beliefs and behaviours by inviting them into a narrative world, breaking down their cognitive and emotional resistance and enhance their acceptance of the ideas portrayed in narratives. Meanwhile, the popularity of social media has provided a novel means of communication for both healthcare stakeholders, and a special group of active social media users (influencers) have started playing a pivotal role in providing health ‘solutions’. Such individuals are often referred to as ‘influencers’ because of their central position in the online communication system and the persuasive effect their actions may have on audiences. They may have established a positive rapport with their audience, earned trust and credibility in a specific area, and thus, their audience considers the information they delivered to be authentic and influential. To our best knowledge, to date, there is no published research that examines the effect of diabetes narratives presented by social media influencers and their impacts on health-related outcomes. The primary aim of this study is to investigate the diabetes narratives presented by social media influencers in the UK because of the new dimension they bring to health communication and the potential impact they may have on audiences' health outcomes. This study is situated within the interpretivist and narrative paradigms. A mixed methodology combining both quantitative and qualitative approaches has been adopted. Qualitative data has been derived to provide a better understanding of influencers’ personal experiences and how they construct meanings and make sense of their world, while quantitative data has been accumulated to identify key social media influencers in the UK and measure the impact of diabetes narratives on audiences. Twitter has been chosen as the social media platform to initially identify key influencers. Two groups of participants are the top 10 key social media influencers in the UK and 100 audiences of each influencer, which means a total of 1000 audiences have been invited. This paper is going to discuss, first of all, the background of the research under the context of health communication; Secondly, the necessity and contribution of this research; then, the major research questions being explored; and finally, the methods to be used.

Keywords: diabetes, health communication, narratives, social media influencers

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Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

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Authors: Seulki Lee, Seoung Bum Kim

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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

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Authors: Hachaichi Mohamed Nour El-Islem, Baouni Tahar

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Environmental sustainability rather than a trans-disciplinary and a scientific issue, is the main problem that characterizes all modern cities nowadays. In developing countries, this concern is expressed in a plethora of critical urban ills: traffic congestion, air pollution, noise, urban decay, increase in energy consumption and CO₂ emissions which blemish cities’ landscape and might threaten citizens’ health and welfare. As in the same manner as developing world cities, the rapid growth of Algiers’ human population and increasing in city scale phenomena lead eventually to increase in daily trips, energy consumption and CO₂ emissions. In addition, the lack of proper and sustainable planning of the city’s infrastructure is one of the most relevant issues from which Algiers suffers. The aim of this contribution is to estimate the carbon deficit of the City of Algiers, Algeria, using the Ecological Footprint Model (carbon footprint). In order to achieve this goal, the amount of CO₂ from fuel combustion has been calculated and aggregated into five sectors (agriculture, industry, residential, tertiary and transportation); as well, Algiers’ biocapacity (CO₂ uptake land) has been calculated to determine the ecological overshoot. This study shows that Algiers’ transport system is not sustainable and is generating more than 50% of Algiers total carbon footprint which cannot be sequestered by the local forest land. The aim of this research is to show that the Carbon Footprint Assessment might be a relevant indicator to design sustainable strategies/policies striving to reduce CO₂ by setting in motion the energy consumption in the transportation sector and reducing the use of fossil fuels as the main energy input.

Keywords: biocapacity, carbon footprint, ecological footprint assessment, energy consumption

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Authors: O. O. Oguntoye

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Product consumption constitutes an important consideration for sustainable development. Seeing how product consumption could be highly unsustainable, coupled with how existing policies on corporate responsibility do not particularly address the consumption aspect of product lifecycle, conducting this research became necessary. The research makes an attempt to provide a framework by which to gauge corporate responsibility of product suppliers in terms of their commitment towards the sustainable consumption of their products. Through an exploration of relevant literature, independently established ideas with which to assess a given product supplier were galvanised into a four-criterion framework. The criteria are: (1) Embeddedness of consumption as a factor in corporate sustainability policy, (2) Level of understanding of consumption behaviour, (3) Breadth of behaviour-influencing strategies adopted, and (4) Inclusiveness for all main dimensions of sustainability. This resulting framework was then applied in a case study involving a UK-based furniture supplier where interviews and content analysis of corporate documents were used as the mode for primary data collection. From the case study, it was found that the supplier had performed to different levels across the four themes of the assessment. Two major areas for improvement were however identified – one is for the furniture supplier to focus more proactively on understanding consumption behaviour and, two is for it to widen the scope of its current strategies for enhancing sustainable consumption of supplied furniture. As a generalisation, the framework presented here makes it possible for companies to reflect with a sense of guidance, how they have demonstrated commitment towards sustainable consumption through their values, culture, and operations. It also provides a foundation for developing standardized assessment which the current widely used frameworks such as the GRI, the Global Compact, and others do not cover. While these popularly used frameworks mainly focus on sustainability of companies within the production and supply chain management contexts (i.e. mostly ‘upstream’), the framework here provides an extension by bringing the ‘downstream’ or consumer bit into light.

Keywords: corporate sustainability, design for sustainable consumption, extended producer responsibility, sustainable consumer behaviour

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Authors: Huan-Chieh Chiu, Hung-Shuo Wu, Chien-Hao Wang, Yu-Cheng Yang, Ching-Ya Tseng, Joe-Air Jiang

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Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.

Keywords: damage level monitoring, drift ratio, fragility curve, smart grid, transmission tower

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Authors: Niall J. English, Sylvia Leatham, Maria Isabel Meza Silva, Denis P. Dowling

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The training and education of under- and post-graduate students can be promoted by more active learning especially in engineering, overcoming more passive and vicarious experiences and approaches in their documented effectiveness. However, the possibility of outreach to young pupils and school-children in primary and secondary schools is a lesser explored area in terms of Education and Public Engagement (EPE) efforts – as relates to feedback and influence on shaping 3rd-level engineering training and education. Therefore, the outreach and school-visit agenda constitutes an interesting avenue to observe how active learning, careers stimulus and EPE efforts for young children and teenagers can teach the university sector, to improve future engineering-teaching standards and enhance both quality and capabilities of practice. This intervention involved careers-outreach efforts to lead to statistical determinations of motivations towards engineering, manufacturing and training. The aim was to gauge to what extent this intervention would lead to an increased careers awareness in engineering, using the method of the schools-visits programme as the means for so doing. It was found that this led to an increase in engagement by school pupils with engineering as a career option and a greater awareness of the importance of manufacturing.

Keywords: outreach, education and public engagement, careers, peer interactions

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Authors: Golak Bihari Mahanta, Bibhuti Bhusan Biswal, B. B. V. L. Deepak, Amruta Rout, Gunji Balamurali

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Robots are widely used in the manufacturing industry for rapid production with higher accuracy and precision. With the help of End-of-Arm Tools (EOATs), robots are interacting with the environment. Robotic grippers are such EOATs which help to grasp the object in an automation system for improving the efficiency. As the robotic gripper directly influence the quality of the product due to the contact between the gripper surface and the object to be grasped, it is necessary to design and optimize the gripper mechanism configuration. In this study, geometric and kinematic modeling of the parallel gripper is proposed. Grey wolf optimizer algorithm is introduced for solving the proposed multiobjective gripper optimization problem. Two objective functions developed from the geometric and kinematic modeling along with several nonlinear constraints of the proposed gripper mechanism is used to optimize the design variables of the systems. Finally, the proposed methodology compared with a previously proposed method such as Teaching Learning Based Optimization (TLBO) algorithm, NSGA II, MODE and it was seen that the proposed method is more efficient compared to the earlier proposed methodology.

Keywords: gripper optimization, metaheuristics, , teaching learning based algorithm, multi-objective optimization, optimal gripper design

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Authors: Catarina Cruz, Ana Breda

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In the early years, until the children’s entrance at the elementary school, they are stimulated by their educators, through rich and attractive contexts, to explore and develop skills in different domains, from the socio-emotional to the cognitive. Many of these contexts trigger real or imaginary situations, familiar or not, through resources or pedagogical practices that incite children's curiosity, questioning, expression of ideas or emotions, social interaction, among others. Later, when children enter at the elementary school, their activity at school becomes more focused on developing skills in the cognitive domain, namely acquiring learning from different subject areas, such as Mathematics, Natural Sciences, History, among others. That is, to ensure that children develop the standardized learning recommended in the guiding curriculum documents, they spend part of their time applying formulas, memorizing information, following instructions, and so on, and in this way not much time is left to listen children, to learn about their interests and likes, as well as their perspective and questions about the surround world. In Elementary School, especially in the 1st Cycle, children are naturally curious, however, sometimes this skill is subtly conditioned by adults. Curious children learn more, since they have an intrinsic desire to know more, especially about what is unknown. When children think on subjects or themes that they are interested in or curious about, they attribute more meaning to this learning and retain it for longer. Therefore, it is important to approach subjects in the classroom that seduce or captivate children's attention, trigger them curiosity, and allow to hear their ideas. There are several resources, strategies and pedagogical practices to awaken children's curiosity, to explore their knowledge, to understand their perspectives and their way of thinking, to know a little more about their personality and to provide space for dialogue. The storytelling, its narrative’s exploration and interpretation is one of those pedagogical practices. Children’s literature, about real or imaginary subjects, stimulate children’s insights supported into their experiences, emotions, learnings and personality, and promote opportunities for children express freely their feelings and thoughts. This work focuses on a session developed with children in the 3rd year of schooling, from a Portuguese 1st Cycle Basic School, in which the story "From the Outside In and From the Inside Out" was presented. The story’s presentation was mainly centred on children’s activity, who read excerpts and interpreted/explored them through a dialogue led by one of the authors. The study presented here intends to show an example of how an exploration of a children's story can trigger ideas, thoughts, emotions or attitudes in children in the 3rd year of elementary school. To answer the research question, this work aimed to: identify ideas, thoughts, emotions or attitudes that emerged from the exploration of story; analyse aspects of the story and the orchestration/conduction of dialogue with/between children that facilitated or inhibited the emergence of ideas, thoughts, emotions or attitudes by children,

Keywords: storytelling, children’s perspectives, soft skills, non-formal learning contexts, orchestration

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Authors: Bastien Sanglard, Lou Magnat, Ligia Barna, Julian Carrey, Sébastien Lachaize

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Cooking is a primary need for humans, several techniques being used around the globe based on different sources of energy: electricity, solid fuel (wood, coal...), fuel or liquefied petroleum gas. However, all of them leads to direct or indirect greenhouse gas emissions and sometimes health damage in household. Therefore, the solar concentrated power represent a great option to lower the damages because of a cleaner using phase. Nevertheless, the construction phase of the solar cooker still requires primary energy and materials, which leads to environmental impacts. The aims of this work is to analyse the ecological impacts of a commercialaluminium parabola and to compare it with other means of cooking, taking the boiling of 2 litres of water three times a day during 40 years as the functional unit. Life cycle assessment was performed using the software Umberto and the EcoInvent database. Calculations were realized over more than 13 criteria using two methods: the international panel on climate change method and the ReCiPe method. For the reflector itself, different aluminium provenances were compared, as well as the use of recycled aluminium. For the structure, aluminium was compared to iron (primary and recycled) and wood. Results show that climate impacts of the studied parabola was 0.0353 kgCO2eq/kWh when built with Chinese aluminium and can be reduced by 4 using aluminium from Canada. Assessment also showed that using 32% of recycled aluminium would reduce the impact by 1.33 and 1.43 compared to the use of primary Canadian aluminium and primary Chinese aluminium, respectively. The exclusive use of recycled aluminium lower the impact by 17. Besides, the use of iron (recycled or primary) or wood for the structure supporting the reflector significantly lowers the impact. The impact categories of the ReCiPe method show that the parabola made from Chinese aluminium has the heaviest impact - except for metal resource depletion - compared to aluminium from Canada, recycled aluminium or iron. Impact of solar cooking was then compared to gas stove and induction. The gas stove model was a cast iron tripod that supports the cooking pot, and the induction plate was as well a single spot plate. Results show the parabolic solar cooker has the lowest ecological impact over the 13 criteria of the ReCiPe method and over the global warming potential compared to the two other technologies. The climate impact of gas cooking is 0.628kgCO2/kWh when used with natural gas and 0.723 kgCO2/kWh when used with a bottle of gas. In each case, the main part of emissions came from gas burning. Induction cooking has a global warming potential of 0.12 kgCO2eq/kWh with the electricity mix of France, 96.3% of the impact being due to electricity production. Therefore, the electricity mix is a key factor for this impact: for instance, with the electricity mix of Germany and Poland, impacts are 0.81kgCO2eq/kWh and 1.39 kgCO2eq/kWh, respectively. Therefore, the parabolic solar cooker has a real ecological advantages compared to both gas stove and induction plate.

Keywords: life cycle assessement, solar concentration, cooking, sustainability

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Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

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Authors: Ehsan Sadie

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Today, the cost of repair and maintenance of structures is very important and by studying the behavior of reinforced concrete structures Will become specified several factors such as : Design and calculation errors, lack of proper implementation of structural changes, the damage caused by the introduction of random loads, concrete corrosion and environmental conditions reduce durability of the structures . Meanwhile building codes alteration also cause changes in the assessment and review of the design and structure rather if necessary will be improved and strengthened in the future.

Keywords: concrete building , expandable cement, honeycombed surface , reinforcement corrosion

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Authors: Caridad Maylin-Aguilar, Beatriz Duarte-Monedero

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Problem-based learning (PBL) is a useful tool for adult and practice oriented audiences, as University students. As a consequence of the huge disruption caused by the COVID pandemic in the hospitality industry, hotels of all categories closed down in Spain from March 2020. Since that moment, the luxury segment was blooming with optimistic prospects for new openings. Hence, Hospitality students were expecting a positive situation in terms of employment and career development. By the beginning of the 2020-21 academic year, these expectations were seriously harmed. By October 2020, only 9 of the 32 hotels in the luxury segment were opened with an occupation rate of 9%. Shortly after, the evidence of a second wave affecting especially Spain and the homelands of incoming visitors bitterly smashed all forecasts. In accordance with the situation, a team of four professors and practitioners, from four different subject areas, developed a real case, inspired in one of these hotels, the 5-stars Emperatriz by Barceló. Students in their 2nd course were provided with real information as marketing plans, profit and losses and operational accounts, employees profiles and employment costs. The challenge for them was to act as consultants, identifying potential courses of action, related to best, base and worst case. In order to do that, they were organized in teams and supported by 4th course students. Each professor deployed the problem in their subject; thus, research on the customers behavior and feelings were necessary to review, as part of the marketing plan, if the current offering of the hotel was clear enough to guarantee and to communicate a safe environment, as well as the ranking of other basic, supporting and facilitating services. Also, continuous monitoring of competitors’ activity was necessary to understand what was the behavior of the open outlets. The actions designed after the diagnose were ranked in accordance with their impact and feasibility in terms of time and resources. Also they must be actionable by the current staff of the hotel and their managers and a vision of internal marketing was appreciated. After a process of refinement, seven teams presented their conclusions to Emperatriz general manager and the rest of professors. Four main ideas were chosen, and all the teams, irrespectively of authorship, were asked to develop them to the state of a minimum viable product, with estimations of impacts and costs. As the process continues, students are nowadays accompanying the hotel and their staff in the prudent reopening of facilities, almost one year after the closure. From a professor’s point of view, key learnings were 1.- When facing a real problem, a holistic view is needed. Therefore, the vision of subjects as silos collapses, 2- When educating new professionals, providing them with the resilience and resistance necessaries to deal with a problem is always mandatory, but now seems more relevant and 3.- collaborative work and contact with real practitioners in such an uncertain and changing environment is a challenge, but it is worth when considering the learning result and its potential.

Keywords: problem-based learning, hospitality recovery, collaborative learning, resilience

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Authors: Mirza Mujtaba Baig

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

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

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Authors: M. N. Kadir, M. M. H. Oliver, T. Naher

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The study assesses the areal extent of riverine flood in the flood-prone area of Faridpur District of Bangladesh using hydrological model and Geographic Information System (GIS). In the context of preparing the inundation map, flood frequency analysis was carried out to assess flooding for different flood magnitudes. Flood inundation maps were prepared based on DEM, and discharge at the river using Delft-3D model. LANDSAT satellite images have been used to develop a land cover map in the study area. The land cover map was used for mapping of cropland area. By incorporating the inundation maps on the land cover map, agricultural damage was assessed. Present monetary values of crop damage were collected through field survey from actual flood of the study area. Two different inundation maps were produced from the model for the year 2000 and 2016. In the year 2000, the floods began in the month of July, whereas in the case of the year 2016 is started in August. Under both cases, most of the areas were found to have been flooded in the month of September followed by flood recession. In order to prepare the land cover maps, four categories of LCs were considered viz., cropland, water body, trees, and rivers. Among the 755791 acres area of Faridpur District, the croplands were categorized to be 334,589 acres, followed by water bodies (279900 acres), trees (101930 acres) and rivers 39372 (acres). Damage assessment data revealed that 40% of the total cropland area had been affected by the flood in the year 2000, whereas only 19% area was affected by the 2016 flood. The study concluded that September is the critical month for cropland protection since the highest flood is expected at this time of the year in Faridpur. The northwestern and the southwestern part of the district was categorized as most vulnerable to flooding.

Keywords: agricultural damage, Delft-3d, flood management, land cover map

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Authors: Emily Jin, Harry Sharples, Anne Weist

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Introduction: NICE Evidence Search Student Champion Scheme is a peer-assisted learning scheme that aims to improve the routine use of evidence-based information by future health and social care staff. The focus is on the NICE evidence search portal that provides selected information from more than 800 reliable health, social care, and medicines sources, including up-to-date guidelines and information for the public. This paper aims to evaluate the effectiveness of the scheme when implemented in Liverpool School of Medicine and to understand the experiences of those attending. Methods: Twelve student champions were recruited and trained in February 2020 as peer tutors during a workshop facilitated by NICE. Cascade sessions were then organised and delivered on an optional basis for students, in small groups of < 10 to approximately 70 attendees. Surveys were acquired immediately before and 8-12 weeks after cascade sessions (n=47 and 45 respectively). Data from these surveys facilitated the analysis of the scheme. Results: Surveys demonstrated 74% of all attendees frequently searched for health and social care information online as a part of their studies. However, only 15% of attendees reported having prior formal training on searching for health information, despite receiving such training earlier on in the curriculum. After attending cascade sessions, students reported a 58% increase in confidence when searching for information using evidence search, from a pre-session a baseline of 36%. Conclusion: NICE Evidence Search Student Champion Scheme provided clear benefits for attending students, increasing confidence in searching for peer-reviewed, mainly secondary sources of health information. The lack of reported training represents the unmet need that the champion scheme satisfies, and this likely benefits student champions as well as attendees. Increasing confidence in searching for healthcare information online may support future evidence-based decision-making.

Keywords: evidence-based medicine, NICE, medical education, medical school, peer-assisted learning

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