Search results for: learning delivery modes

Authors: Antonia Harold-Barry, Eugene Dempsey

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Background: The objective is to examine the survival and outcome of infants born under 26 weeks gestation in an Irish tertiary maternity hospital from 2007-2016 and to describe the survival and neurodevelopmental outcomes of these extremely preterm infants. Method: The population is 132 infants born at 23, 24, and 25 weeks in Cork University Maternity Hospital from 2007 to 2016. Ethical approval was granted by the Cork Clinical Research Ethics Committee. Patient details were obtained from the Vermont Oxford and Badger Networks. Survival rates and Bayley scores were calculated to assess neurodevelopmental outcomes. Statistical analysis with SPSS included frequencies, distributions, and comparisons between data from 2007-2011 and 2012-2016. Results: Overall survival rate was 63%. Of the surviving babies, 61% had Bayley scores calculated. Survival stood at 39% for delivery at 23 weeks, 50% at 24 weeks, and 83% at 25 weeks. The 2012 to 2016 cohort has shown further increases in survival, with 50% of babies at 23 weeks, 58% at 24 weeks, and 89% at 25 weeks. Corresponding figures for 2007-2011 are 20%, 39%, and 75%. Gestational age and incidence of periventricular leukomalacia were statistically significant, with a p-value of 0.022. Gestational age and delivery room deaths had a p-value of 0.025, as did gestational age and birth weight. A comparison of the two cohorts (2007-2011 and 2012-2016) with the administration of antenatal steroids showed a statistically significant p-value of 0.044. Conclusion: There is less morbidity and mortality in infants born at 25 than at 23 or 24 weeks. Survival of extremely premature infants has increased significantly over the past ten years. Survival rates with normal neurodevelopmental outcomes are comparable with international standards and reflect positive changes in attitude and practices in neonatal intensive care. This study will inform parents about the potential outcomes of extreme prematurity and policy regarding the management of extreme prematurity.

Keywords: extreme of viability, neurodevelopmental outcome, periventricular leukomalacia, prematurity

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Authors: Leandro Marcos Alves Vaz

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The teaching of physics in Brazilian public schools emphasizes strongly the theoretical aspects of this science, showing its philosophical and mathematical basis, but neglecting its experimental character. Perhaps the lack of science laboratories explains this practice. In this work, we present a method of teaching physics using the computer. As alternatives to real experiments, we have the trials through simulators, many of which are free software available on the internet. In order to develop a study on the use of simulators in teaching, knowing the impossibility of simulations on all topics in a given subject, we combined these programs with phenomenological and/or experimental texts in order to mitigate this limitation. This study proposes the use of simulators and the debate using phenomenological/experimental texts on electrostatic theme in groups of the 3rd year of EJA (Adult and Youth Education) in order to verify the advantages of this methodology. Some benefits of the hybridization of the traditional method with the tools used were: Greater motivation of the students in learning, development of experimental notions, proactive socialization to learning, greater easiness to understand some concepts and the creation of collaborative activities that can reduce timidity of part of the students.

Keywords: experimentation, learning physical, simulators, youth and adult

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Authors: Sana Sayed

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The words objectives, outcomes, and assessment are commonplace in academia. Educators, especially those who use their emotional intelligence as a useful teaching tool, strive to find creative and innovative ways to connect to their students while meeting the objectives, outcomes, and assessment measures for their respective courses. However, what happens to these outcomes once the objectives have been met, students have completed a specific course, and generic letter grades have been generated? How can their knowledge and acquired skills be assessed over the course of semesters, throughout their years of study, and until their final year right before they graduate? Considering the courses students complete for different departments in various disciplines, how can these outcomes be measured, or at least maintained, across the curriculum? This research-driven paper uses the key course outcomes of first year, required writing courses and traces them in two senior level, required civil engineering design courses at the American University of Sharjah, which is located in the United Arab Emirates. The purpose of this research is two-fold: (1) to assess specific learning outcomes using a case study that focuses on courses from two different disciplines during two very distinctive years of study, and (2) to demonstrate how learning across the curriculum fosters life-long proficiencies among graduating students that are aligned with a university’s mission statement.

Keywords: assessment, learning across the curriculum, objectives, outcomes

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Authors: Victor I. Ilgisonis, Ludmila V. Konovaltseva, Vladimir P. Lakhin, Ekaterina A. Sorokina

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The analytical solutions for geodesic acoustic eigenmodes in tokamak plasmas with circular concentric magnetic surfaces are found. In the frame of ideal magnetohydrodynamics the dispersion relation taking into account the toroidal coupling between electrostatic perturbations and electromagnetic perturbations with poloidal mode number |m| = 2 is derived. In the absence of such a coupling the dispersion relation gives the standard continuous spectrum of geodesic acoustic modes. The analysis of the existence of global eigenmodes for plasma equilibria with both off-axis and on-axis maximum of the local geodesic acoustic frequency is performed.

Keywords: tokamak, MHD, geodesic acoustic mode, eigenmode

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Authors: Abdelbaky Abouzeid

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The study aimed at determining the effect of using the active learning on achievement and attitudes toward studying the human rights course for the Bahrain Teachers College students and the extent to which any differences of statistical significance according to gender and section can exist. To achieve the objectives of the study, the researcher developed and implemented research tools such as academic achievement test and the scale of attitudes towards the study of the Human Rights Course. The scale of attitudes towards Human Rights was constructed of 40 items investigating four dimensions; the cognitive dimension, the behavioral dimension, the affective dimension, and course quality dimension. The researcher then applied some of the active learning strategies in teaching this course to all students of the first year of the Bahrain Teachers College (102 male and female students) after excluding two students who did not complete the course requirements. Students were divided into five groups. These strategies included interactive lecturing, presentations, role playing, group projects, simulation, brainstorming, concept maps and mind maps, reflection and think-pair-share. The course was introduced to students during the second semester of the academic year 2016-2017. The study findings revealed that the use of active learning strategies affected the achievement of students of Bahrain Teachers College in the Human Rights course. The results of the T-test showed statistically significant differences on the pre-test and post-test in favor of the post-test. No statistically significant differences in the achievement of students according to the section and gender were found. The results also indicated that the use of active learning strategies had a positive effect on students' attitudes towards the study of the Human Rights Course on all the scale’s items. The general average reached (4.26) and the percentage reached (85.19%). Regarding the effect of using active learning strategies on students’ attitudes towards all the four dimensions of the scale, the study concluded that the behavioral dimension came first; the quality of the course came second, the cognitive dimension came third and in the fourth place came the affective dimension. No statistically significant differences in the attitude towards studying the Human Rights Course for the students according to their sections or gender were found. Based on the findings of the study, the researchers suggested some recommendations that can contribute to the development of teaching Human Rights Course at the University of Bahrain.

Keywords: attitudes, academic achievement, human rights, behavioral dimension, cognitive dimension, affective dimension, quality of the course

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Authors: Surasak Kangkhao, Chaturong Louhapensang

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This research investigates design and cultural heritage interpretations by residential architecture design in World Heritage cities: Kamphaeng Phet, Thailand reflect on the essence of design based on local identity. The research consisted of three thematic foci. First, the studies examined the contextual background that led to the genesis of the building. Second, the investigations concentrated on how its design was developed and implemented. Third, these modes of problematisation lent a basis to argue that a quality of placeness was not confined exclusively to traditional or vernacular structures but could be found from the unconventional aesthetics of Residential Architecture as well.

Keywords: expressions, local identity, residential architecture, practice, world heritage site

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Authors: Kuei-Ling Sun, Emily Chia-Yu Su

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Allergy is a hypersensitive overreaction of the immune system to environmental stimuli, and a major health problem. These overreactions include rashes, sneezing, fever, food allergies, anaphylaxis, asthmatic, shock, or other abnormal conditions. Allergies can be caused by food, insect stings, pollen, animal wool, and other allergens. Their development of allergies is due to both genetic and environmental factors. Allergies involve immunoglobulin E antibodies, a part of the body’s immune system. Immunoglobulin E antibodies will bind to an allergen and then transfer to a receptor on mast cells or basophils triggering the release of inflammatory chemicals such as histamine. Based on the increasingly serious problem of environmental change, changes in lifestyle, air pollution problem, and other factors, in this study, we both collect allergens and non-allergens from several databases and use several machine learning methods for classification, including logistic regression (LR), stepwise regression, decision tree (DT) and neural networks (NN) to do the model comparison and determine the permutations of allergen amino acid’s sequence.

Keywords: allergy, classification, decision tree, logistic regression, machine learning

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Authors: Li-Jia Chiu

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The purpose of this study is to integrate the content of professional ethics curriculum into life education. This course is a required course for the third-year students of the university. The curriculum is based on professional ethics, which can help students gain insights into a conceptual understanding of professional theory, learning the meaning and the value of life. This study enhances students' attitude toward learning through multi-teaching methods. It takes ‘professionalism’ as the subject of discussion. Additionally, the course combines the connotation and issues of the student's career development. Using the world cafe discussion method, students can think about the role of the future career, and inspire students to integrate their career development and life value reflection and connection. This study recruited the third-year undergraduate students as samples to collect data. This study was conducted in the course of the fall semester in 2016 for thematic discussions, classroom observations, course study forms, coursework, and results in publication reports, etc. The researcher conducted induction data analysis to reflect the practice and reflection of the course. The subjects included 117 students from two classes, including 54 male and 63 female students. The findings of this study comprised the following two parts: the student’s learning and teacher’s teaching reflection. The students’ gains were that: 1) The curriculum design is different from that of other subjects; 2) The curriculum is highly interactive with teachers and classmates; 3) These students are willing to actively participate and share ideas in group discussions; 4 ) They thought the possibility of further discussions with other groups of students through table-to-table discussions; 5) They experienced the respect from other students in the learning process and their appreciation of other students in the same group. The instruction reflections were as follows: 1) Students learned to get link to the value of life and future development through topical discussions; 2) After the main course design guided through gradual guidance, the students’ psychology reached a certain degree of cognition, and further themes then added would cause more sensuous learning effects; 3) Combining students’ expertise in drawing in this department (digital media design department) into curriculum design is effective in stimulating learning motivation and sense of accomplishment; 4) In order to compare and explore learning benefits, future researches are recommended to conduct the similar studies with different departments. Finally, the researcher looks forward to providing research results and findings to the related curriculum teachers as a reference for practical curriculum planning and teaching methods.

Keywords: life education, World Cafe, professional ethics, professionalism

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Authors: Lynn Machin

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Using the lens of a theoretical framework relating to learning to learn the intention of the case study was to explore how transferable the teaching and learning skills of a newly qualified teacher (post-compulsory education) were when used in an overseas, unfamiliar and challenging post-compulsory educational environment. Particularly, the research sought to explore how this newly qualified teacher made use of the skills developed during their teacher training and to ascertain if, and what, other skills were necessary in order for them to have a positive influence on their learners and for them to be able to thrive within a different country and learning milieu. This case study looks at the experience of a trainee teacher who recently qualified in the UK to teach in post compulsory education (i.e. post 16 education). Rather than gaining employment in a UK based academy or college of further education this newly qualified teacher secured her first employment as a teacher in a province in China. Moreover, the newly qualified teacher had limited travel experience and had never travelled to Asia. She was one of the quieter and more reserved members on the one year teacher training course and was the least likely of the group to have made the decision to work abroad. How transferable the pedagogical skills that she had gained during her training would be when used in a culturally different and therefore (to her, challenging) environment was a key focus of the study. Another key focus was to explore the dispositions being used by the newly qualified teacher in order for her to teach and to thrive in an overseas educational environment. The methodological approach used for this study was both interpretative and qualitative. Associated methods were: Observation: observing the wider and operational practice of the newly qualified teacher over a five day period, and their need, ability and willingness to be reflective, resilient, reciprocal and resourceful. Interview: semi-structured interview with the newly qualified teacher following the observation of her practice. Findings from this case study illuminate the modifications made by the newly qualified teacher to her bank of teaching and learning strategies as well as the essentiality of dispositions used by her to know how to learn and also, crucially, to be ready and willing to do so. Such dispositions include being resilient, resourceful, reciprocal and reflective; necessary in order to adapt to the emerging challenges encountered by the teacher during their first months of employment in China. It is concluded that developing the skills to teach is essential for good teaching and learning practices. Having dispositions that enable teachers to work in ever changing conditions and surroundings is, this paper argues, essential for transferability and longevity of use of these skills.

Keywords: learning, post-compulsory, resilience, transferable

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Authors: C. W. F. Che Wan Putra, M. Alshawi, M. S. Al Ahbabi, M. Jabakhanji

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The construction industry is a multi-disciplinary and multi-national industry, which has an important role to play within the overall economy of any country. There are major challenges to an improved performance within the industry. Particularly lacking is, the ability to capture the large amounts of information generated during the life-cycle of projects and to make these available, in the right format, so that professionals can then evaluate alternative solutions based on life-cycle analysis. The fragmented nature of the industry is the main reason behind the unavailability and ill utilisation of project information. The lack of adequately engaging clients and managing their requirements contributes adversely to construction budget and schedule overruns. This is a difficult task to achieve, particularly if clients are not continuously and formally involved in the design and construction process, which means that the design intent is left to designers that may not always satisfy clients’ requirements. Client lead is strongly recognised in bringing change through better collaboration between project stakeholders. However, one of the major challenges is that collaboration is operated under conventional procurement methods, which hugely limit the stakeholders’ roles and responsibilities to bring about the required level of collaboration. A research has been conducted with a typical project in the UAE. A qualitative research work was conducted including semi-structured interviews with project partners to discover the real reasons behind this delay. The case study also investigated the real causes of the problems and if they can be adequately addressed by BIM and IPD. Special focus was also placed on the Client leadership and the role the Client can play to eliminate/minimize these problems. It was found that part of the ‘key elements’ from which the problems exist can be attributed to the client leadership and the collaborative environment and BIM.

Keywords: client leadership, building information modelling (BIM), integrated project delivery (IPD), case study

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Authors: Tokihiko Akita, Seiichi Mita

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A millimeter-wave radar is the most robust against adverse environments, making it an essential environment recognition sensor for automated driving. However, the reflection signal is sparse and unstable, so it is difficult to obtain the high recognition accuracy. Deep learning provides high accuracy even for them in recognition, but requires large scale datasets with ground truth. Specially, it takes a lot of cost to annotate for a millimeter-wave radar. For the solution, utilizing a simulator that can generate an annotated huge dataset is effective. Simulation of the radar is more difficult to match with real world data than camera image, and recognition by deep learning with higher-order features using the simulator causes further deviation. We have challenged to improve the accuracy of traffic participant classification by fusing simulator and real-world data with domain adaptation technique. Experimental results with the domain adaptation network created by us show that classification accuracy can be improved even with a few real-world data.

Keywords: millimeter-wave radar, object classification, deep learning, simulation, domain adaptation

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Authors: Teresa Kupczyk, Selçuk Mustafa Özcan, Joanna Kubicka

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The paper presents results of specialist literature analysis concerning learning outcomes and student satisfaction as a factor of the necessary change in the Polish higher education system. The objective of the empirical research was to determine students’ assessment of learning outcomes, satisfaction of their expectations, as well as their satisfaction with lectures and practical classes held in the traditional form, e-learning and video-conference. The assessment concerned effectiveness of time spent at classes, usefulness of the delivered knowledge, instructors’ preparation and teaching skills, application of tools, studies curriculum, its adaptation to students’ needs and labour market, as well as studying conditions. Self-assessment of learning outcomes was confronted with assessment by lecturers. The indirect objective of the research was also to identify how students assessed their activity and commitment in acquisition of knowledge and their discipline in achieving education goals. It was analysed how the studies held affected the students’ willingness to improve their skills and assessment of their perspectives at the labour market. To capture the changes underway, the research was held at the beginning, during and after completion of the studies. The study group included 86 students of two editions of full-time studies majoring in Management and specialising in “Mega-event organisation”. The studies were held within the EU-funded project entitled “Responding to challenges of new markets – innovative managerial education”. The results obtained were analysed statistically. Average results and standard deviations were calculated. In order to describe differences between the studied variables present during the process of studies, as well as considering the respondents’ gender, t-Student test for independent samples was performed with the IBM SPSS Statistics 21.0 software package. Correlations between variables were identified by calculation of Pearson and Spearman correlation coefficients. Research results suggest necessity to introduce some changes in the teaching system applied at Polish higher education institutions, not only considering the obtained outcomes, but also impact on students’ willingness to improve their qualifications constantly, improved self-assessment among students and their opportunities at the labour market.

Keywords: higher education, learning outcomes, students, change

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Authors: Troy A. Tyre

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Organizational behavior and organizational change are elements of the ever-changing global business environment. Leadership and organizational behavior are 21st century disciplines. Network marketing organizations need to understand the ever-changing nature of global business and be ready and willing to adapt to the environment. Network marketing organizations have a challenge keeping up with a rapid escalation in global growth. Network marketing growth has been steady and global. Network marketing organizations have been slow to develop a 21st century global strategy to manage the rapid escalation of growth degrading organizational behavior, job satisfaction, increasing attrition, and degrading customer service. Development of an organizational behavior and leadership theory for the 21st century to help network marketing develops a global business strategy to manage the rapid escalation in growth that affects organizational behavior. Managing growth means organizational leadership must develop and adapt to the organizational environment. Growth comes with an open mind and one’s departure from the comfort zone. Leadership growth operates in the tacit dimension. Systems thinking and adaptation of mental models can help shift organizational behavior. Shifting the organizational behavior requires organizational learning. Organizational learning occurs through single-loop, double-loop, and triple-loop learning. Triple-loop learning is the most difficult, but the most rewarding. Tools such as theory U can aid in developing a landscape for organizational behavioral development. Additionally, awareness to espoused and portrayed actions is imperatives. Theories of motivation, cross-cultural diversity, and communications are instrumental in founding an organizational behavior suited for the 21st century.

Keywords: global, leadership, network marketing, organizational behavior

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Authors: Joud Zagzoog, Amira Aldabbagh, Radiyah Hamidaddin

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This research aims to test out and observe whether artificial intelligence (AI) software and applications could actually be effective, useful, and time-saving for those who use them. Shaguf Bites, a web application that uses AI technology, claims to help students study and memorize information more effectively in less time. The website uses smart learning, or AI-powered bite-sized repetitive learning, by transforming documents or PDFs with the help of AI into summarized interactive smart flashcards (Bites, n.d.). To properly test out the websites’ effectiveness, both qualitative and quantitative methods were used in this research. An experiment was conducted on a number of students where they were first requested to use Shaguf Bites without any prior knowledge or explanation of how to use it. Second, they were asked for feedback through a survey on how their experience was after using it and whether it was helpful, efficient, time-saving, and easy to use for studying. After reviewing the collected data, we found out that the majority of students found the website to be straightforward and easy to use. 58% of the respondents agreed that the website accurately formulated the flashcard questions. And 53% of them reported that they are most likely to use the website again in the future as well as recommend it to others. Overall, from the given results, it is clear that Shaguf Bites have proved to be very beneficial, accurate, and time saving for the majority of the students.

Keywords: artificial intelligence (AI), education, memorization, spaced repetition, flashcards.

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Authors: Hari Sharan Pandit

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Mathematics teaching in Nepal has been centralized and guided by the notion of transfer of knowledge and skills from teachers to students. The overemphasis on the ‘algorithm-centric’ approach to mathematics teaching and the focus on ‘role–learning’ as the ultimate way of solving mathematical problems since the early years of schooling have been creating severe problems in school-level mathematics in Nepal. In this context, the author argues that students should learn real-world mathematical problems through various interesting, creative and collaborative, as well as artistic and alternative ways of knowing. The collaboration-incorporated pedagogy is a distinct pedagogical approach that offers a better alternative as an integrated and interdisciplinary approach to learning that encourages students to think more broadly and critically about real-world problems. The paper, as a summarized report of action research designed, developed and implemented by the author, focuses on the needs and usefulness of collaboration-incorporated pedagogy in the Nepali context to make mathematics teaching more meaningful for producing creative and critical citizens. This paper is useful for mathematics teachers, teacher educators and researchers who argue on arts integration in mathematics teaching.

Keywords: peer teaching, metacognitive approach, mitigating, action research

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Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

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Authors: Nezha Badi

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It has been shown in the literature that Algerian university students suffer from low levels of reading comprehension proficiency, which hinder their overall proficiency in English. This low level is mainly related to the methodology of teaching reading which is employed by the teacher in the classroom (a teacher-centered environment), as well as students’ poor sense of self-efficacy to undertake reading comprehension activities. Arguably, what is needed is an approach necessary for enhancing students’ self-beliefs about their abilities to deal with different reading comprehension activities. This can be done by providing them with opportunities to take responsibility for their own learning (learners’ autonomy). As a result of learning autonomy, learners’ beliefs about their abilities to deal with certain language tasks may increase, and hence, their language learning ability. Therefore, this experimental research study attempts to assess the extent to which an integrated approach combining one particular reading approach known as ‘collaborative strategic reading’ (CSR), and teacher’s attributional feedback (on students’ reading performance and strategy use) can improve the reading comprehension skill and the sense of self-efficacy of EFL Algerian university students. It also seeks to examine students’ main reasons for their successful or unsuccessful achievements in reading comprehension activities, and whether students’ attributions for their reading comprehension outcomes can be modified after exposure to the instruction. To obtain the data, different tools including a reading comprehension test, questionnaires, an observation, an interview, and learning logs were used with 105 second year Algerian EFL university students. The sample of the study was divided into three groups; one control group (with no treatment), one experimental group (CSR group) who received a CSR instruction, and a second intervention group (CSR Plus group) who received teacher’s attribution feedback in addition to the CSR intervention. Students in the CSR Plus group received the same experiment as the CSR group using the same tools, except that they were asked to keep learning logs, for which teacher’s feedback on reading performance and strategy use was provided. The results of this study indicate that the CSR and the attributional feedback intervention was effective in improving students’ reading comprehension proficiency and sense of self-efficacy. However, there was not a significant change in students’ adaptive and maladaptive attributions for their success and failure d from the pre-test to the post-test phase. Analysis of the perception questionnaire, the interview, and the learning logs shows that students have positive perceptions about the CSR and the attributional feedback instruction. Based on the findings, this study, therefore, seeks to provide EFL teachers in general and Algerian EFL university teachers in particular with pedagogical implications on how to teach reading comprehension to their students to help them achieve well and feel more self-efficacious in reading comprehension activities, and in English language learning more generally.

Keywords: attributions, attributional feedback, collaborative strategic reading, self-efficacy

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Authors: Hernández Yasmín, Ochoa Alberto, Hurtado Diego

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The aim of this study is developing an intelligent tutoring system for electrical operators training with virtual reality systems at the laboratory center of partials discharges LAPEM. The electrical domain requires efficient and well trained personnel, due to the danger involved in the partials discharges field, qualified electricians are required. This paper presents an overview of the intelligent tutor adaptive learning design and user interface with VR. We propose the develop of constructing a model domain of a subset of partial discharges enables adaptive training through a trainee model which represents the affective and knowledge states of trainees. According to the success of the intelligent tutor system with VR, it is also hypothesized that the trainees will able to learn the electrical domain installations of partial discharges and gain knowledge more efficient and well trained than trainees using traditional methods of teaching without running any risk of being in danger, traditional methods makes training lengthily, costly and dangerously.

Keywords: intelligent tutoring system, artificial intelligence, virtual reality, partials discharges, adaptive learning

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Yuanxiang Miao

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Couchsurfing is a free homestay and social networking service accessible via the website and mobile app. Couchsurfers can directly request free accommodations from others and receive offers from each other. However, it is typically difficult for people to make a decision that accepts or declines a request when they receive it from Couchsurfers because they do not know each other at all. People are expected to meet up with some Couchsurfers who are kind, generous, and interesting while it is unavoidable to meet up with someone unfriendly. This paper utilized classification algorithms of Machine Learning to help people to find out the Good Couchsurfers and Not Good Couchsurfers on the Couchsurfing website. By knowing the prior experience, like Couchsurfer’s profiles, the latest references, and other factors, it became possible to recognize what kind of the Couchsurfers, and furthermore, it helps people to make a decision that whether to host the Couchsurfers or not. The value of this research lies in a case study in Kyoto, Japan in where the author has hosted 54 Couchsurfers, and the author collected relevant data from the 54 Couchsurfers, finally build a model based on classification algorithms for people to predict Couchsurfers. Lastly, the author offered some feasible suggestions for future research.

Keywords: Couchsurfing, Couchsurfers prediction, classification algorithm, hospitality tourism platform, hospitality sciences, machine learning

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Authors: Santri Emilin Pingsaboi Djahimo, Ikhfi Imaniah

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Helping students recognize both their strengths and weaknesses is a beneficial strategy for teachers to be implemented in the classroom, and feedback has been acknowledged as an effective tool to achieve this goal. It will allow teachers to assess the students’ progress, provide targeted support for them, and adjust both teaching and learning strategies. This research has investigated the importance of feedback in English as a Foreign Language (EFL) speaking class in East Nusa Tenggara Province, Indonesia. Through a qualitative study, it has shed light on the crucial roles of feedback in the process of English Language Teaching (ELT), especially, in the context of developing oral communication or speaking skills. Additionally, it has also examined students’ responses to feedback from their teacher by grouping them based on their semester, scores (GPA), and gender. This study, which seeks to provide insights into how feedback practices can be optimized to maximize learning outcomes in the English-speaking classroom, has revealed that these groups of students have different level of needs for feedback, yet all prefer constructive feedback. Looking at the results, it is highly expected that this study can contribute to a deeper understanding of the correlation between feedback and English language learning outcomes, particularly, in terms of speaking proficiency.

Keywords: feedback, English as a foreign language, speaking class, English language teaching

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Authors: Mikiyas Yonas Fufa

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- Maternal and child health service was a critical service which may have many risks and many maternal and newborn mortality is there if not managed properly. In middle and low countries like Ethiopia accessibility and quality of MCH service is low. During this COVID-19 Pandemics even the pervious access of MCH will be decreased. So many pregnant mothers are not attending their ANC, Delivery and other services in the hospital because they think they are more vulnerable to COVID-19. This condition may make an increase of maternal and neonatal morbidity and mortality. The innovation is an idea (which is development of a mobile app prepared by Maternity Foundation organization that focuses on midwifery care. The app has detailed videos on danger signs in pregnancy and procedures during labor and delivery). By telling this to clients it is planned to explore the perception, attitude towards this innovation and barriers to accepting it. What is planned to study is to explore the perceptions and barriers towards using of new idea which is innovation of mHealth on the MCH services. It is planned to interview the pregnant mothers who come for ANC at health facility and mothers who are absent from their appointment of services. In this way it is planned to explore how the mothers accept this idea and what barriers make them from accepting this idea. This is a phenomenological qualitative study and application of diffusion of innovation theory on the MCH services. The participant will be selected by using quota sampling methods for the mother who are interviewed at hospitals and snowball/quota sampling methods for the mother who are absent from their appointment/visits. Sample size of the participant depends on the saturation of data/idea. Each participant will be interviewed based the open-ended questionnaires, and the interview will be recorded then transcribed then finally analyzed by the open code 4.03. Beneficiaries: The federal ministry of health prepares them to develop the apk of mhealth. Health professionals in the MCH will have a low overload and accessibility and the quality of care will be increased during COVID-19 Different collaborations will be participated and promote the mother to enjoy the new idea.

Keywords: COVID-19, m health, MCH, diffusion of innovation

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Authors: Eun-Seop Kim, Eun-Ha Jang, Rana R. Kim, Sae-Byul Jang

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Objective: Preterm labor is the most common antecedent of preterm birth(PTB), which is characterized by regular uterine contraction before 37 weeks of pregnancy and cervical change. In acute preterm labor, tocolytics are administered as the first-line medication to suppress uterine contractions but rarely delay pregnancy to 37 weeks of gestation. On the other hand, according to the Korean Traditional Medicine, PTB is caused by the deficiency of Qi and unnecessary energy in the body of the mother. The aim of this study was to demonstrate the benefit of Traditional Korean Medicine as an adjuvant therapy in management of early uterine contractions and the prevention of PTB. Methods: It is a case report of a 38-year-old woman (0-0-6-0) hospitalized for irregular uterine contractions and cervical change at 33+3/7 weeks of gestation. Past history includes chemical pregnancies achieved by Artificial Rroductive Technology(ART), one stillbirth (at 7 weeks) and a laparoscopic surgery for endometriosis. After seven trials of IVF and articificial insemination, she had succeeded in conception via in-vitro fertilization (IVF) with help of Traditional Korean Medicine (TKM) treatments. Due to irregular uterine contractions and cervical changes, 2 TKM were prescribed: Gami-Dangguisan, and Antae-eum, known to nourish blood and clear away heat. 120ml of Gami-Dangguisan was given twice a day monring and evening along with same amount of Antae-eum once a day from 31 August 2013 to 28 November 2013. Tocolytics (Ritodrine) was administered as a first aid for maintenance of pregnancy. Information regarding progress until the delivery was collected during the patient’s visit. Results: On admission, the cervix of 15mm in length and cervical os with 0.5cm-dilated were observed via ultrasonography. 50% cervical effacement was also detected in physical examination. Tocolysis had been temporarily maintained. As a supportive therapy, TKM herbal preparations(gami-dangguisan and Antae-eum) were concomitantly given. As of 34+2/7 weeks of gestation, however intermittent uterine contractions appeared (5-12min) on cardiotocography and vaginal bleeding was also smeared at 34+3/7 weeks. However, enhanced tocolytics and continuous administration of herbal medicine sustained the pregnancy to term. At 37+2/7 weeks, no sign of labor with restored cervical length was confirmed. The woman gave a term birth to a healthy infant via vaginal delivery at 39+3/7 gestational weeks. Conclusions: This is the first successful case report about a preter labor patient administered with conventional tocolytic agents as well as TKM herbal decoctions, delaying delivery to term. This case deserves attention considering it is rare to maintain gestation to term only with tocolytic intervention. Our report implies the potential of herbal medicine as an adjuvant therapy for preterm labor treatment. Further studies are needed to assess the safety and efficacy of TKM herbal medicine as a therapeutic alternative for curing preterm birth.

Keywords: preterm labor, traditional Korean medicine, herbal medicine, integrative treatment, complementary and alternative medicine

Procedia PDF Downloads 363

Authors: Kashika P. H.

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The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

Procedia PDF Downloads 101

Authors: Derssie Mebratu

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As a large variety of micro services, web services, social graphic applications, and media applications are continuously developed, it is substantially vital to design and build a reliable, efficient, and faster memory tiering system. Despite limited design, implementation, and deployment in the last few years, several techniques are currently developed to improve a memory tiering system in a cloud. Some of these techniques are to develop an optimal scanning frequency; improve and track pages movement; identify pages that recently accessed; store pages across each tiering, and then identify pages as a hot, warm, and cold so that hot pages can store in the first tiering Dynamic Random Access Memory (DRAM) and warm pages store in the second tiering Compute Express Link(CXL) and cold pages store in the third tiering Non-Volatile Memory (NVM). Apart from the current proposal and implementation, we also develop a new technique based on a machine learning algorithm in that the throughput produced 25% improved performance compared to the performance produced by the baseline as well as the latency produced 95% improved performance compared to the performance produced by the baseline.

Keywords: machine learning, bayesian optimization, memory tiering, CXL, DRAM

Procedia PDF Downloads 91

Authors: Adi Gielgun-Katz, Alina S. Rusu

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In the last two decades, education systems worldwide have integrated new pedagogical methods and strategies in lesson plans, such as innovative technologies, social-emotional learning (SEL), gamification, mixed learning, multiple literacies, and many others. Visual language, such as photographs, is known to transcend cultures and languages, and it is commonly used by youth to express positions and affective states in social networks. Therefore, visual language needs more educational attention as a linguistic and communicative component that can create connectedness among the students and their teachers. Nowadays, when SEL is gaining more and more space and meaning in the area of academic improvement in relation to social well-being, and taking and sharing pictures is part of the everyday life of the majority of people, it becomes natural to add the visual language to SEL approach as a reinforcement strategy for connecting education to the contemporary culture and language of the youth. This article presents a program conducted in a high school class in Israel, which combines the five SEL with photography techniques, i.e., Social-Emotional Learning Visual Empowerments (SELVEs) program (experimental group). Another class of students from the same institution represents the control group, which is participating in the SEL program without the photography component. The SEL component of the programs addresses skills such as: troubleshooting, uncertainty, personal strengths and collaboration, accepting others, control of impulses, communication, self-perception, and conflict resolution. The aim of the study is to examine the effects of programs on the level of the five SEL aspects in the two groups of high school students: Self-Awareness, Social Awareness, Self-Management, Responsible Decision Making, and Relationship Skills. The study presents a quantitative assessment of the SEL programs’ impact on the students. The main hypothesis is that the students’ questionnaires' analysis will reveal a better understanding and improvement of the five aspects of the SEL in the group of students involved in the photography-enhanced SEL program.

Keywords: social-emotional learning, photography, education program, adolescents

Procedia PDF Downloads 74

Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality

Procedia PDF Downloads 159

Authors: Raveendranath Veeramani, Sunil Jonathan Holla, Parkash Chand, Sunil Chumber

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Gray’s Anatomy for Students has been a well-appreciated book among undergraduate students of anatomy in Asia. However, the current curricular requirements of anatomy require a more focused and organized approach. The editors of the first South Asia edition of Gray’s Anatomy for Students hereby highlight the modifications and importance of this edition. There is an emphasis on active learning by making the clinical relevance of anatomy explicit. Learning anatomy in context has been fostered by the association between anatomists and clinicians in keeping with the emerging integrated curriculum of the 21st century. The language has been simplified to aid students who have studied in the vernacular. The original illustrations have been retained, and few illustrations have been added. There are more figure numbers mentioned in the text to encourage students to refer to the illustrations while learning. The text has been made more student-friendly by adding generalizations, classifications and summaries. There are useful review materials at the beginning of the chapters which include digital resources for self-study. There are updates on imaging techniques to encourage students to appreciate the importance of essential knowledge of the relevant anatomy to interpret images, due emphasis has been laid on dissection. Additional importance has been given to the cranial nerves, by describing their relevant details with several additional illustrations and flowcharts. This new edition includes innovative features such as set inductions, outlines for subchapters and flowcharts to facilitate learning. Set inductions are mostly clinical scenarios to create interest in the need to study anatomy for healthcare professions. The outlines are a modern multimodal facilitating approach towards various topics to empower students to explore content and direct their learning and include learning objectives and material for review. The components of the outline encourage the student to be aware of the need to create solutions to clinical problems. The outlines help students direct their learning to recall facts, demonstrate and analyze relationships, use reason to explain concepts, appreciate the significance of structures and their relationships and apply anatomical knowledge. The 'structures to be identified in a dissection' are given as Level I, II and III which represent the 'must know, desirable to know and nice to know' content respectively. The flowcharts have been added to get an overview of the course of a structure, recapitulate important details about structures, and as an aid to recall. There has been a great effort to balance the need to have content that would enable students to understand concepts as well as get the basic material for the current condensed curriculum.

Keywords: Grays anatomy, South Asia, human anatomy, students anatomy

Procedia PDF Downloads 196

Authors: Smita Singh

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Objective: The Faculty of Chemistry Education at Humboldt University has developed ‘Studium’, a web application designed to enhance long-term self-regulated learning (SRL) and academic achievement. Leveraging advanced generative AI, ‘Studium’ offers a dynamic and adaptive educational experience tailored to individual learning preferences and languages. The application includes evolving tools for personalized notetaking from preferred sources, customizable presentation capabilities, and AI-assisted guidance from academic documents or textbooks. It also features workflow automation and seamless integration with collaborative platforms like Miro, powered by AI. This study aims to propose a model that combines generative AI with traditional features and customization options, empowering students to create personalized learning environments that effectively address the challenges of SRL. Method: To achieve this, the study included graduate and undergraduate students from diverse subject streams, with 15 participants each from Germany and India, ensuring a diverse educational background. An exploratory design was employed using a speed dating method with enactment, where different scenario sessions were created to allow participants to experience various features of ‘Studium’. The session lasted for 50 minutes, providing an in-depth exploration of the platform's capabilities. Participants interacted with Studium’s features via Zoom conferencing and were then engaged in semi-structured interviews lasting 10-15 minutes to gain deeper insights into the effectiveness of ‘Studium’. Additionally, online questionnaire surveys were conducted before and after the session to gather feedback and evaluate satisfaction with self-regulated learning (SRL) after using ‘Studium’. The response rate of this survey was 100%. Results: The findings of this study indicate that students widely acknowledged the positive impact of ‘Studium’ on their learning experience, particularly its adaptability and intuitive design. They expressed a desire for more tools like ‘Studium’ to support self-regulated learning in the future. The application significantly fostered students' independence in organizing information and planning study workflows, which in turn enhanced their confidence in mastering complex concepts. Additionally, ‘Studium’ promoted strategic decision-making and helped students overcome various learning challenges, reinforcing their self-regulation, organization, and motivation skills. Conclusion: This proposed model emphasizes the need for effective integration of personalized AI tools into active learning and SRL environments. By addressing key research questions, our framework aims to demonstrate how AI-assisted platforms like “Studium” can facilitate deeper understanding, maintain student motivation, and support the achievement of academic goals. Thus, our ideal model for AI-assisted educational platforms provides a strategic approach to enhance student's learning experiences and promote their development as self-regulated learners. This proposed model emphasizes the need for effective integration of personalized AI tools into active learning and SRL environments. By addressing key research questions, our framework aims to demonstrate how AI-assisted platforms like ‘Studium’ can facilitate deeper understanding, maintain student motivation, and support the achievement of academic goals. Thus, our ideal model for AI-assisted educational platforms provides a strategic approach to enhance student's learning experiences and promote their development as self-regulated learners.

Keywords: self-regulated learning (SRL), generative AI, AI-assisted educational platforms

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Authors: Pedro Martinez-Santos, Víctor Gómez-Escalonilla, Silvia Díaz-Alcaide, Esperanza Montero, Miguel Martín-Loeches

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Groundwater monitoring networks are critical in evaluating the vulnerability of groundwater resources to depletion and contamination, both in space and time. Groundwater monitoring networks typically grow over decades, often in organic fashion, with relatively little overall planning. The groundwater monitoring networks in the Madrid area, Spain, were reviewed for the purpose of identifying gaps and opportunities for improvement. Spatial analysis reveals the presence of various monitoring networks belonging to different institutions, with several hundred observation wells in an area of approximately 4000 km2. This represents several thousand individual data entries, some going back to the early 1970s. Major issues included overlap between the networks, unknown screen depth/vertical distribution for many observation boreholes, uneven time series, uneven monitored species, and potentially suboptimal locations. Results also reveal there is sufficient information to carry out a spatial and temporal analysis of groundwater vulnerability based on machine learning applications. These can contribute to improve the overall planning of monitoring networks’ expansion into the future.

Keywords: groundwater monitoring, observation networks, machine learning, madrid

Procedia PDF Downloads 71