Search results for: innovative learning

Authors: Wang Liguang, Zhang Xueqing

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The build-operate-transfer (BOT) project delivery system has provided effective routes to mobilize private sector funds, innovative technologies, management skills and operational efficiencies for public infrastructure development and have been widely used in China during the last 20 years. Many BOT projects in China will be smoothly transferred to the government soon and the transfer stage, which is considered as the last stage, must be studied carefully and handled well to achieve the overall success of BOT projects. There will be many issues faced by both the public sector and private sector in the transfer stage of BOT projects, including project post-assessment, technology and documents transfer, personal training and staff transition, etc. and sometimes additional legislation is needed for future operation and management of facilities. However, most previous studies focused on the bidding, financing, and building and operation stages instead of transfer stage. This research identifies nine key issues in the transfer stage of BOT projects through a comprehensive study on three cases in China, and the expert interview and expert discussion meetings are held to validate the key issues and give detail analysis. A proposed framework of transfer management is prepared based on the experiences derived and lessons drawn from the case studies and expert interview and discussions, which is expected to improve the transfer management of BOT projects in practice.

Keywords: BOT project, key issues, transfer management, transfer stage

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Raul G. Angeles

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The Philippine government instituted major reforms in its educational system. The Department of Education pushes the K to 12 program that makes kindergarten mandatory and adds two years of senior high school to the country's basic education. In essence, the students’ stay in basic education particularly those who are supposedly going to college is extended. The majority of the students expressed that they will be taking the Academic Track of the Senior High School curriculum specifically the Science, Technology, Engineering and Mathematics (STEM) and General Academic (GA) strands. Almost certainly, instruction should match the students' styles and thus through this descriptive study a city survey was conducted to explore the teaching strategies preferences of junior high school students and teachers who will be promoted to senior high school during the Academic Year 2016-2017. This study was conducted in selected public and private secondary schools in Metro Manila. Questionnaires were distributed to students and teachers; and series of follow-up interviews were also carried out to generate additional information. Preferences of students are centered on employing innovations such as technology, cooperative and problem-based learning. While the students will still be covered by basic education their interests in science are sparking to a point where the usual teaching styles may no longer work to them and for that cause, altering the teaching methods is recommended to create a teacher-student style matching. Other effective strategies must likewise be implemented.

Keywords: curriculum development, effective teaching strategies, problem-based learning, senior high school, science education, technology

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Authors: Dalila Lino

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The power of play for learning and development in early childhood education is beyond question. The main goal of this study is to analyse how three contemporary early childhood pedagogical approaches, the High Scope, the Modern School Movement (MEM) and the Pedagogy of Participation integrate play in their curriculum development. From this main goal the following objectives emerged: (i) to characterize how play is integrated in the daily routine of the pedagogical approaches under study; (ii) to analyse the teachers’ role during children’s playing situations; (iii) to identify the types of play that children are more often involved. The methodology used is the qualitative approach and is situated under the interpretative paradigm. Data is collected through semi-structured interviews to 30 preschool teachers and through observations of typical daily routines. The participants are 30 Portuguese preschool classrooms attending children from 3 to 6 years and working with the High Scope curriculum (10 classrooms), the MEM (10 classrooms) and the Pedagogy of Participation (10 classrooms). The qualitative method of content analysis was used to analyse the data. To ensure confidentiality, no information is disclosed without participants' consent, and the interviews were transcribed and sent to the participants for a final revision. The results show that there are differences how play is integrated and promoted in the three pedagogical approaches. The teachers’ role when children are at play varies according the pedagogical approach adopted, and also according to the teachers’ understanding about the meaning of play. The study highlights the key role that early childhood curriculum models have to promote opportunities for children to play, and therefore to be involved in meaningful learning.

Keywords: curriculum models, early childhood education, pedagogy, play

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Authors: Warda Ajaz

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This study uses the ‘Community Capitals Framework’ (CCF) to develop a community resilience index that can serve as a useful tool for measuring resilience of communities in diverse contexts and backgrounds. CCF is an important analytical tool to assess holistic community change. This framework identifies seven major types of community capitals: natural, cultural, human, social, political, financial and built, and claims that the communities that have been successful in supporting healthy sustainable community and economic development have paid attention to all these capitals. The framework, therefore, proposes to study the community development through identification of assets in these major capitals (stock), investment in these capitals (flow), and the interaction between these capitals. Capital based approaches have been extensively used to assess community resilience, especially in the context of natural disasters and extreme events. Therefore, this study identifies key indicators for estimating each of the seven capitals through an extensive literature review and then develops an index to calculate a community resilience score. The CCF-based community resilience index presents an innovative way of operationalizing the concept of community resilience and will contribute toward decision-relevant research regarding adaptation and mitigation of community vulnerabilities to climate change-induced, as well as other adverse events.

Keywords: adverse events, community capitals, community resilience, climate change, economic development, sustainability

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Authors: Tiffany Yung Hsuan Ma

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The Whole Language Approach, which gained prominence in the 1980s, and the increasing emphasis on multimodal resources in educational research have elevated the utilization of picture books in English as a foreign language (EFL) instruction. This approach underscores real-world language application, providing EFL learners with a range of sensory stimuli, including visual elements. Additionally, the substantial impact of picture books on fostering prosocial behaviors in children has garnered recognition. These narratives offer opportunities to impart essential values such as kindness, fairness, and respect. Examining how picture books enhance vocabulary acquisition can offer valuable insights for educators in devising engaging language activities conducive to a positive learning environment. This research entails a case study involving two kindergarten-aged EFL learners and employs qualitative methods, including worksheets, observations, and interviews with parents. It centers on three pivotal inquiries: (1) The extent of young learners' acquisition of essential vocabulary, (2) The influence of these books on their behavior at home, and (3) Effective teaching strategies for the seamless integration of picture storybooks into EFL instruction for young learners. The findings can provide guidance to parents, educators, curriculum developers, and policymakers regarding the advantages and optimal approaches to incorporating picture books into language instruction. Ultimately, this research has the potential to enhance English language learning outcomes and promote moral education within the Taiwanese EFL context.

Keywords: EFL, vocabulary acquisition, young learners, picture book, moral education

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Authors: Mohd Naqiuddin Bin Husri, Siti Rahmah Abd Rahman, Dalilah Abu Bakar, Dayang Izawati Abang Masli, Meilina Ong Abdullah

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A serious shortage of prime agricultural land coupled with environmental concerns inland expansion has daunted efforts to increase the national yield average. To address this issue, maximising yield per unit hectare through quality planting material is of great importance. Breeding for improved planting materials has been a continuous effort since the early days of this industry, it is time-consuming, and the likelihood of segregation within the progenies further impedes progress in this area. Incorporation of the cloning technology in oil palm breeding programmes is therefore advantageous to expedite the development of commercial elite and high-yielding planting materials. After more than 22 years of research and development through this project, reliable protocols for liquid/suspension culture systems coupled with various innovative technologies which are effective at promoting proliferation and growth of oil palm culture have been established. Subsequently, clonal palms derived from the suspension culture system were extensively studied in the field, and the results have been encouraging. Clones such as CPS1, CPS2 and a few others recorded superior performance in comparison with D x P standard crosses.

Keywords: tissue culture, suspension culture, oil palm, Elaeis guineensis

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Authors: Anna Crivellari, Valerio Cozzani

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Even though most of the electricity produced in the entire world still comes from fossil fuels, new policies are being implemented in order to promote a more sustainable use of energy sources. Offshore renewable resources have become increasingly attractive thanks to the huge entity of power potentially obtained. However, the intermittent nature of renewables often limits the capacity of the systems and creates mismatches between supply and demand. Hydrogen is foreseen to be a promising vector to store and transport large amounts of excess renewable power by using existing oil and gas infrastructure. In this work, an offshore hybrid energy system integrating wind energy conversion with hydrogen production was conceptually defined and applied to offshore gas platforms. A techno-economic analysis was performed by considering two different locations for the installation of the innovative power system, i.e., the North Sea and the Adriatic Sea. The water depth, the distance of the platform from the onshore gas grid, the hydrogen selling price and the green financial incentive were some of the main factors taken into account in the comparison. The results indicated that the use of well-defined indicators allows to capture specifically different cost and revenue features of the analyzed systems, as well as to evaluate their competitiveness in the actual and future energy market.

Keywords: cost analysis, energy efficiency assessment, hydrogen production, offshore wind energy

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Authors: Michelle Bulawan, Mei-Hua Chen

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Reading comprehension is crucial for acquiring information, analyzing critically, and achieving academic proficiency. However, there is a lack of growth in reading comprehension skills beyond fourth grade. The developmental shift from "learning to read" to "reading to learn" occurs around this stage. Factual knowledge and diverse views in articles enhance reading comprehension abilities. Nevertheless, some face difficulties due to evolving textual requirements, such as expanding vocabulary and using longer, more complex terminology. Most research on reading strategies has been conducted at the tertiary and secondary levels, while few have focused on the elementary levels. Furthermore, the use of character, ask, problem, solution (CAPS) charts in teaching reading has also been hardly explored. Thus, the researcher decided to explore the facilitation of active reading strategies through the CAPS chart and address the following research questions: a) What differences existed in elementary EFL learners' reading competency among those who engaged in active reading strategies and those who did not? b) What are the learners’ metacognitive skills of those who engage in active reading strategies and those who do not, and what are their effects on their reading competency? c) For those participants who engage in active reading activities, what are their perceptions about incorporating active reading activities into their English classroom learning? Two groups of elementary EFL learners, each with 18 students of the same level of English proficiency, participated in this study. Group A served as the control group, while Group B served as the experimental group. Two teachers also participated in this research; one of them was the researcher who handled the experimental group. The treatment lasts for one whole semester or seventeen weeks. In addition to the CAPS chart, the researcher also used the metacognitive awareness of reading strategy inventory (MARSI) and a ten-item, five-point Likert scale survey.

Keywords: active reading, EFL learners, metacognitive skills, reading competency, student’s perception

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

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Authors: Moet Moet Myint Lay

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Continuing professional development involves acquiring new knowledge and skills for current work and improving career opportunities in the field through continuing education (OECD, 2000). This article examines the effectiveness of CPD in improving teacher quality and the resulting need for CPD for teacher educators in Myanmar. The purpose of this study is to explore a deeper understanding of teacher-to-teacher continuing professional development in improving teacher education programs. Research questions: (1) How do teachers in Myanmar understand the idea of continuous professional development for professional development? (2) What CPD activities are required for all teachers in teachers' colleges? (3) What are the main challenges of CPD implementation in Myanmar Education College? A qualitative method using semi-structured interviews was used in this study. Seven teacher educators from Mandalay Education College participated in this study. There are three male teacher educators and four female teacher educators. All participants who responded to the semi-structured interviews were between 29 and 45 years old.The interviews revealed that professional development involves acquiring the necessary pedagogical knowledge and skills to encourage students to think creatively and critically. Teachers must participate in a variety of activities, including professional interviews, lesson study, training programs, workshops, and seminars. All results showed that teachers need English and ICT skills for teaching and learning, including extended ICT courses for those who have completed a foundation course, access to e-libraries, and inclusive education (including language teaching and learning), facilitate the assessment (formative and summative), practicum, mentoring, and coaching skills. The study concludes with practical findings that suggest an urgent need for CPD activities for teachers.

Keywords: continuous professional development, teacher educator, teacher training program), mentoring

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Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

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Authors: Diane M. Bender

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In design education, professional education is delivered in a studio, where students learn and understand their discipline. This learning methodology culminates in a final review, where students present their work before instructors and invited reviewers, known as jurors. These jurors are recognized experts who add a wide diversity of opinions in their feedback to students. This feedback can be provided in multiple formats, mainly a verbal critique of the work. To better understand how these expert reviewers prepare for a studio review, a survey was distributed to reviewers at a multi-disciplinary design school within the United States. Five design disciplines are involved in this case study: architecture, graphic design, industrial design, interior design, and landscape architecture. Respondents (n=122) provided information about if and how they received training on how to critique and participate in a final review. Common forms of training included mentorship, modeled behavior from other designers/past professors, workshops on critique from the instructing faculty prior to the crit session, and by being a practicing design professional. Respondents also gave feedback about how much the instructor provided course materials prior to the review in order to better prepare for student interaction. Finally, respondents indicated if they had interaction, and in what format, with students prior to the final review. Typical responses included participation in studio desk crits, a midterm jury member, meetings with students, and email or social media correspondence. While the focus of this study is the studio review, the findings are equally applicable to other disciplines. Suggestions will be provided on how to improve the preparation of guests in the learning process and how their interaction can positively influence student engagement.

Keywords: critique, design, education, evaluation, juror

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Authors: Amit Kumar Jain, Surbhi Jain

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The urban freight in a city constitutes 10 to 18 per cent of all city road traffic, and 40 per cent of air pollution and noise emissions, are directly related to commercial transport. The policy measures implemented by urban planners have sought to restrict rather than assist goods-vehicle operations. This approach has temporarily controlled the urban transport demand during peak hours of traffic but has not effectively solved transport congestion. The solution discussed in the paper envisages the development of a comprehensive network of Urban Freight Stations (UFS) connected through underground conveyor belts in the city in line with baggage segregation and distribution in any of the major airports. The transportation of freight shall be done in standard size containers/cars through rail borne carts. The freight can be despatched or received from any of the UFS. Once freight is booked for a destination from any of the UFS, it would be stuffed in the container and digitally tagged for the destination. The container would reach the destination UFS through a network of rail borne carts. The container would be de-stuffed at the destination UFS and sent for further delivery, or the consignee may be asked to collect the consignment from urban freight station. The obvious benefits would be decongestion of roads, reduction in air and noise pollution, saving in manpower used for freight transportation.

Keywords: congestion, urban freight, intelligent transport system, pollution

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Authors: Afolakemi Helen Olaleye, Ogunjobi A. O

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Since coronavirus disease 2019 (COVID-19) was first reported in Nigeria, the virus has spread to virtually all sub-Saharan Africa (SSA) countries. In Nigeria, government agencies came together to create a goal-driven taskforce in improving our response against the virus. As COVID-19 international spread has been curtailed, community spread became rampant locally, leading to many health authorities raising concerns over the scarcity of medical consumables and supplies. Here at Lagos university teaching Hospital (LUTH), we present data analysis of COVID-19 infections offered at our Hospital (LUTH) and the surrounding communities. In addition, the adopted innovative solution to control the spread of infection, methods used in filling shortages of consumables, personal protective equipment (PPE), and use of mobile video technology in patient’s consultation. The management style and strategy adopted has led to a decline in infection rates in our community and among our front line staff. The current COVID -19 crisis has created an opportunity to test and demonstrate our pandemic response and control of infectious disease along with the revealed unknown potential in our community.

Keywords: COVID-19, preparedness, response, Lagos university teaching hospital

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Authors: Eyal Boers

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This paper shall demonstrate how films can offer a valuable and innovative approach to the study of images, stereotypes, and national identity. "Black Book" ("Zwartboek", 2006), a World War Two film directed by Paul Verhoeven, tells the story of Rachel Stein, a young Jewish woman who becomes a member of a resistance group in the Netherlands. The main hypothesis in this paper maintains that Rachel's character possesses both features of the Dutch prototype (a white, secular, sexual, freedom-loving individualist who seems "Dutch" enough to be accepted into a Dutch resistance group and even infiltrate the local Nazi headquarters) and features which can be defined as specifically Jewish (a black-haired victim persecuted by the Nazis, transforming herself into a gentile, while remaining loyal to her fellow Jews and ultimately immigrating to Israel and becoming a Hebrew teacher in a Kibbutz). Finally, this paper claims that Rachel's "Dutchness" is symptomatic of Dutch nostalgia in the 21st century for the Jews as "others" who blend into dominant Dutch culture, while Rachel's "Jewish Otherness" reflects a transnational identity – one that is always shifting and traverses cultural and national boundaries. In this sense, a film about Dutch Jews in the Second World War reflects on issues of identity in the 21st Century.

Keywords: Dutch, film, stereotypes, identity

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Authors: Aysegul Evren Yapicioglu

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The social roles and responsibilities expected from citizens are increasing due to changing global living conditions. Science education is expected to prepare conscious and sensitive students. Because today’s students are the adults of future. Precondition of this task is Teacher Education. In the past decade, one of the most important research field is socioscientific issues. This study deals with advantages and disadvantages of socioscientific issue based instruction in science classroom according to pre-service science teachers’ views. A case study approach that is one of the qualitative research design was used to explore their views. Fourteen pre-service science teachers participated to instruction process. Dolphinariums, Kyoto Protocol, genetically modified organisms, recyclable black bags’ benefits and damages, genetic tests, alternative energy sources and organ donation are examples of socioscientific issues, which were taught through activities in a special teaching course. Diaries and focus group interview were used as data collection tools. As a result of the study, the advantages of socioscientific issue based instruction in science classroom comprise of six sub-categories which are multi-skilling, social awareness development of thinking, meaningful learning, character and professional development, contribution of scientific literacy whereas disadvantages of this instruction process are challenges teachers and students, limitations of teaching and learning process in pre-service science teachers’ perspectives. Finally, this study contributes to science teachers and researchers to overcome disadvantages and benefit from the advantage of socioscientific issue based instruction in science classroom.

Keywords: science education, socioscientific issues, socioscientific issue based instruction, pre-service science teacher

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Authors: Diana Santiago, Tania Lisboa, Sophie Lee, Alexander P. Demos, Monica C. S. Vasconcelos

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Memorization has long been recognized as an arduous and anxiety-evoking task for musicians, and yet, it is an essential aspect of performance. Research shows that musicians are often not taught how to memorize. While memorization and practice strategies of professionals have been studied, little research has been done to examine how student musicians learn to practice and memorize music in different cultural settings. We present the process of developing and testing a questionnaire of music memorization and musical practice for student musicians in the UK and Brazil. A survey was developed for a cross-cultural research project aiming at examining how young orchestral musicians (aged 7–18 years) in different learning environments and cultures engage in instrumental practice and memorization. The questionnaire development included members of a UK/US/Brazil research team of music educators and performance science researchers. A pool of items was developed for each aspect of practice and memorization identified, based on literature, personal experiences, and adapted from existing questionnaires. Item development took the varying levels of cognitive and social development of the target populations into consideration. It also considered the diverse target learning environments. Items were initially grouped in accordance with a single underlying construct/behavior. The questionnaire comprised three sections: a demographics section, a section on practice (containing 29 items), and a section on memorization (containing 40 items). Next, the response process was considered and a 5-point Likert scale ranging from ‘always’ to ‘never’ with a verbal label and an image assigned to each response option was selected, following effective questionnaire design for children and youths. Finally, a pilot study was conducted with young orchestral musicians from diverse learning environments in Brazil and the United Kingdom. Data collection took place in either one-to-one or group settings to facilitate the participants. Cognitive interviews were utilized to establish response process validity by confirming the readability and accurate comprehension of the questionnaire items or highlighting the need for item revision. Internal reliability was investigated by measuring the consistency of the item groups using the statistical test Cronbach’s alpha. The pilot study successfully relied on the questionnaire to generate data about the engagement of young musicians of different levels and instruments, across different learning and cultural environments, in instrumental practice and memorization. Interaction analysis of the cognitive interviews undertaken with these participants, however, exposed the fact that certain items, and the response scale, could be interpreted in multiple ways. The questionnaire text was, therefore, revised accordingly. The low Cronbach’s Alpha scores of many item groups indicated another issue with the original questionnaire: its low level of internal reliability. Several reasons for each poor reliability can be suggested, including the issues with item interpretation revealed through interaction analysis of the cognitive interviews, the small number of participants (34), and the elusive nature of the construct in question. The revised questionnaire measures 78 specific behaviors or opinions. It can be seen to provide an efficient means of gathering information about the engagement of young musicians in practice and memorization on a large scale.

Keywords: cross-cultural, memorization, practice, questionnaire, young musicians

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Authors: Marilei Amadeu Sabino

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Idiomatic expressions are linguistic phraseologisms present in natural languages. Known to be metaphorical linguistic combinations, a good majority of them provide elements that reveal important cultural aspects of their linguistic community through their metaphors. With the advent of Cognitive Linguistics (more specifically of Cognitive Semantics), the metaphor ceased to be related to poetic language and rhetorical embellishment and came to be seen as part of simple everyday language, reflecting the way human beings think, act and conceive reality, i. e., a fundamental mechanism of human conceptualizations of the world. In this sense, it came to be conceived as an inevitable mechanism for representing the nature of thought and language. The speakers, in conceptualizing reality, often use metaphorically parts of the body in expressions known as somatic. Several conceptual metaphors appear to be potentially universal or near-universal, because people across the world share certain bodily experiences. In these terms, many linguistic metaphors may be identical or very similar in several languages. These similarities, according to the Theory of Conceptual Metaphor, derive from universal aspects of the human body. Thus, this research aims to investigate the nature of some metaphors underlying somatic idiomatic expressions of Portuguese, Italian and English languages, establishing a pattern of similarities and differences among them from a trilingual perspective. The analysis shows that much of the studied expressions are really structurally, semantically and metaphorically identical or similar in the three languages. These findings incite relevant discussions concerning mother and foreign language learning and aim to contribute to the teaching of phraseological Lexicon as well as to materials development in mono and multilingual perspectives.

Keywords: idiomatic expressions, materials development, metaphors, phraseological lexicon, teaching and learning

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Authors: Geoffrey Sinha

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Today’s students are connected to the digital generation and technology is an integral part of their everyday lives. Clearly, this is one social revolution that is here to stay and the language classroom has been no exception. Furthermore, today’s teachers are also expected to connect with technology and online tools in their curriculum. However, it’s often difficult for teachers to know where to start, what resources and tools are available, what students should use, and most importantly, how to effectively use them in the classroom.

Keywords: language learning, new media, social media, technology

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Authors: Bruno Gontijo Batista

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This paper analyzes how the Socially Aware Design (SAwD) and the Value-oriented and Culturally Informed Approach (VCIA) design model can be used to develop an edutainment game for children with Attention Deficit Hyperactivity Disorder (ADHD). The SAwD approach seeks a design that considers new dimensions in human-computer interaction, such as culture, aesthetics, emotional and social aspects of the user's everyday experience. From this perspective, the game development was VCIA model-based, including the users in the design process through participatory methodologies, considering their behavioral patterns, culture, and values. This is because values, beliefs, and behavioral patterns influence how technology is understood and used and the way it impacts people's lives. This model can be applied at different stages of design, which goes from explaining the problem and organizing the requirements to the evaluation of the prototype and the final solution. Thus, this paper aims to understand how this model can be used in the development of an edutainment game for children with ADHD. In the area of education and learning, children with ADHD have difficulties both in behavior and in school performance, as they are easily distracted, which is reflected both in classes and on tests. Therefore, they must perform tasks that are exciting or interesting for them, once the pleasure center in the brain is activated, it reinforces the center of attention, leaving the child more relaxed and focused. In this context, serious games have been used as part of the treatment of ADHD in children aiming to improve focus and attention, stimulate concentration, as well as be a tool for improving learning in areas such as math and reading, combining education and entertainment (edutainment). Thereby, as a result of the research, it was developed, in a participatory way, applying the VCIA model, an edutainment game prototype, for a mobile platform, for children between 8 and 12 years old.

Keywords: ADHD, edutainment, SAwD, VCIA

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Authors: T. J. O Ceallaigh

Abstract:

Subject matter driven programs such as immersion programs are increasingly popular across the world. These programs have allowed for extensive experimentation in the realm of second language teaching and learning and have been at the centre of many research agendas since their inception. Even though immersion programs are successful, especially in terms of second language development, they remain complex to implement and not always as successful as what we would hope them to be. Among all the challenges these varied programs face, research indicates that the primary issue lies in the difficulty to create well-balanced programs where both content instruction and language/literacy instruction can be targeted simultaneously. Initial teacher education and professional development experiences are key drivers of successful language immersion education globally. They are critical to the supply of teachers with the mandatory linguistic and cultural competencies as well as associated pedagogical practices required to ensure learners’ success. However, there is a significant dearth of research on professional development experiences of immersion teachers. We lack an understanding of the nature of their expertise and their needs in terms of professional development as well as their perceptions of the primary challenges they face as they attempt to formulate a coherent pedagogy of integrated language and content instruction. Such an understanding is essential if their specific needs are to be addressed appropriately and thus improve the overall quality of immersion programs. This paper reports on immersion teacher perceptions of online professional development experiences that have a positive impact on their ability to facilitate language and content connections in instruction. Twenty Irish-medium immersion teachers engaged in the instructional integration of language and content in a systematic and developmental way during a year-long online professional development program. Data were collected from a variety of sources e.g., an extensive online questionnaire, individual interviews, reflections, assignments and focus groups. This study provides compelling evidence of the potential of online professional development experiences as a pedagogical framework for understanding the complex and interconnected knowledge demands that arise in content and language integration in immersion. Findings illustrate several points of access to classroom research and pedagogy and uncover core aspects of high impact online experiences. Teachers identified aspects such as experimentation and risk-taking, authenticity and relevance, collegiality and collaboration, motivation and challenge and teacher empowerment. The potential of the online experiences to foster teacher language awareness was also identified as a contributory factor to success. The paper will conclude with implications for designing meaningful and effective online CLIL professional development experiences.

Keywords: content and language integrated learning , immersion pedagogy, professional development, teacher language awareness

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Authors: Mansour N. Jadid

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This paper describes the implementation of a GIS to provide decision support for successfully monitoring the movements and storage of materials, hence ensuring that finished products travel from the point of origin to the destination construction site through the supply-chain management (SCM) system. This system ensures the efficient operation of suppliers, manufacturers, and distributors by determining the shortest path from the point of origin to the final destination to reduce construction costs, minimize time, and enhance productivity. These systems are essential to the construction industry because they reduce costs and save time, thereby improve productivity and effectiveness. This study describes a typical supply-chain model and a geographical information system (GIS)-based SCM that focuses on implementing an electronic document management system, which maps the application framework to integrate geodetic support with the supply-chain system. This process provides guidance for locating the nearest suppliers to fill the information needs of project members in different locations. Moreover, this study illustrates the use of a GIS-based SCM as a collaborative tool in innovative methods for implementing Web mapping services, as well as aspects of their integration by generating an interactive GIS for the construction industry platform.

Keywords: construction, coordinate, engineering, GIS, management, map

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Jaime Carpio-García, Elena Blanco-Fernández, Jorge Rodríguez-Hernández, Daniel Castro-Fresno

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Geosynthetic mechanical behavior vs temperature or vs aging has been widely studied independently during the last years, both in laboratory and in outdoor conditions. This paper studies this behavior deeper, considering that geosynthetics have to perform adequately at different outdoor temperatures once they have been subjected to a certain degree of aging, and also considering the different geosynthetic structures made of the same material. This combining effect has been not considered so far, and it is important to ensure the performance of geosynthetics, especially where high temperatures are expected. In order to fill this gap, six commercial geosynthetics with different internal structures made of polypropylene (PP), high density polyethylene (HDPE), bitumen and polyvinyl chloride (PVC), or even a combination of some of them have been mechanically tested at mild temperature (20ºC or 23ºC) and at warm temperature (45ºC) before and after specific exposition to air at standardized high temperature in order to simulate 25 years of aging due to oxidation. Besides, for 45ºC tests, an innovative heating system during test for high deformable specimens is proposed. The influence of the combining effect of aging, structure and temperature in the product behavior have been analyzed and discussed, concluding that internal structure is more influential than aging in the mechanical behavior of a geosynthetic versus temperature.

Keywords: geosynthetics, mechanical behavior, temperature, aging, internal structure

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Authors: Angie M. Wolf, DeVone Boggan

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This paper highlights an innovative and nontraditional violence prevention program that is making a noticeable impact in what was once one of the country’s most violent communities. With unique and tailored strategies, the Operation Peacemaker Fellowship, established in Richmond, California, combines components of evidence-based practices with a community-oriented focus on relationships and mentoring to fill a gap in services and increase community safety. In an effort to highlight these unique strategies and provide a blueprint for other communities with violent crime problems, the authors of this paper hope to clearly delineate how one community is moving forward with vanguard approaches to invest in the lives of young men who once were labeled the communities’ most violent, even the most deadly, youth. The impact of this program is evidenced through the fellows’ own voices as they illuminate the experience of being in the Fellowship. In interviews, fellows’ describe how participating in this program has transformed their lives, and the lives of those they love. The authors of this article spent more than two years researching this Fellowship program in order to conduct an evaluation of it and, ultimately, to demonstrate how this program is a testament to the power of relationship and love combined with evidence-based practices, consequently enriching the lives of youth and the community that embraces them.

Keywords: gun violence prevention, high risk youth, law, policing justice

Procedia PDF Downloads 406

Authors: Mohsin Ali Shaikh, Weiguo Song, Rehmat Karim, Muhammad Kashan Surahio, Muhammad Usman Shahid

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Fire investigations face challenges due to the complexity of fire development, and real-world accidents lack repeatability, making it difficult to apply standardized approaches. The unpredictable nature of fires and the unique conditions of each incident contribute to the complexity, requiring innovative methods and tools for effective analysis and reconstruction. This study proposes to provide the modern accident analysis model through numerical reconstruction for fire investigation in textile buildings. This method employs computer simulation to enhance the overall effectiveness of textile-building investigations. The materials and evidence collected from past incidents reconstruct fire occurrences, progressions, and catastrophic processes. The approach is demonstrated through a case study involving a tragic textile factory fire in Karachi, Pakistan, which claimed 257 lives. The reconstruction method proves invaluable for determining fire origins, assessing losses, establishing accountability, and, significantly, providing preventive insights for complex fire incidents.

Keywords: fire investigation, numerical simulation, fire safety, fire incident, textile building

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Authors: Danielle Schneider, Ying Xie

Abstract:

Middle school science, technology, engineering, and math (STEM) teachers experience an exceptional challenge in the expectation to incorporate curricula that builds strong spatial reasoning skills on rudimentary geometry concepts. Because spatial ability is so closely tied to STEM students’ success, researchers are tasked to determine effective instructional practices that create an authentic learning environment within the immersive virtual reality learning environment (IVRLE). This study looked to investigate the effect of the IVRLE on middle school STEM students’ spatial reasoning skills as a methodology to benefit the STEM middle school students’ spatial reasoning skills. This experimental study was comprised of thirty 7th-grade STEM students divided into a treatment group that was engaged in an immersive VR platform where they engaged in building an object in the virtual realm by applying spatial processing and visualizing its dimensions and a control group that built the identical object using a desktop computer-based, computer-aided design (CAD) program. Before and after the students participated in the respective “3D modeling” environment, their spatial reasoning abilities were assessed using the Middle Grades Mathematics Project Spatial Visualization Test (MGMP-SVT). Additionally, both groups created a physical 3D model as a secondary measure to measure the effectiveness of the IVRLE. The results of a one-way ANOVA in this study identified a negative effect on those in the IVRLE. These findings suggest that with middle school students, virtual reality (VR) proved an inadequate tool to benefit spatial relation skills as compared to desktop-based CAD.

Keywords: virtual reality, spatial reasoning, CAD, middle school STEM

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Authors: Wang Shuen-Tai, Lin Yu-Ching, Chang Hsi-Ya

Abstract:

Cloud computing is the innovative and leading information technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. In this paper, we aim at the development of workflow management system for cloud computing platforms based on our previous research on the dynamic allocation of the cloud computing resources and its workflow process. We took advantage of the HTML 5 technology and developed web-based workflow interface. In order to enable the combination of many tasks running on the cloud platform in sequence, we designed a mechanism and developed an execution engine for workflow management on clouds. We also established a prediction model which was integrated with job queuing system to estimate the waiting time and cost of the individual tasks on different computing nodes, therefore helping users achieve maximum performance at lowest payment. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for cloud computing platform. This development also helps boost user productivity by promoting a flexible workflow interface that lets users design and control their tasks' flow from anywhere.

Keywords: web-based, workflow, HTML5, Cloud Computing, Queuing System

Procedia PDF Downloads 300