Search results for: language learning strategies

Authors: Kamolrat Turner, Chularat Howharn

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Critical thinking and creativity are desirable competency for contemporary nurses although there are growing concerns supporting a disturbing paucity in its achievement. Nursing colleges in Thailand have developed teaching strategies and curricula that nurture critical thinking and creativity dispositions according academic levels. Objectives: This descriptive study identified critical thinking and creativity dispositions of Thai nursing students according academic levels. Methods: A cross-sectional questionnaire survey was conducted among 515 nursing students for four academic levels. All are studying at Boromarajonani College of Nursing Chon Buri, Thailand. Descriptive and univariate general linear model analysis were applied. Results: The scores on critical thinking disposition gradually increased as academic level is rising from the junior year throughout the senior year, but its scores are neutral. Scores on creativity skill is neutral and constant thorough the four academic years. The fourth grade students had slightly higher scores on creativity when compared to others. A significant relationship between critical thinking and creativity was also found. Conclusions: The scores on critical thinking disposition gradually improved which greatly increased in the senior year. However, creativity has neutrally progressed. The findings suggest the importance of targeting the development of curriculum and teaching strategies for all grades of nursing students to increase their critical thinking and creativity skills.

Keywords: critical thinking, creativity, undergraduate nursing students, competency

Procedia PDF Downloads 437

Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

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The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

Procedia PDF Downloads 127

Authors: Ann Enright

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More than ever, animal shelters need to identify ways to reduce the number of animals entering shelter facilities and the incidence of euthanasia. Managing animal overpopulation using euthanasia can have detrimental health and emotional consequences for the shelter staff involved. There are also community expectations with moral and financial implications to consider. To achieve the goals of reducing animal intake and the incidence of euthanasia, shelter best practice involves combining programs, procedures and partnerships to increase live release rates (LRR), reduce the incidence of disease, length of stay (LOS) and shelter intake whilst overall remaining financially viable. Analysing daily processes, tracking outcomes and implementing simple strategies enabled shelter staff to more effectively focus their efforts and achieve amazing results. The objective of this retrospective study was to assess the effect of implementing the capacity for care (C4C) management model. Data focusing on the average daily number of animals on site for a two year period (2016 – 2017) was exported from a shelter management system, Customer Logic (CL) Vet to Excel for manipulation and comparison. Following the implementation of C4C practices the average daily number of animals on site was reduced by >50%, (2016 average 103 compared to 2017 average 49), average LOS reduced by 50% from 8 weeks to 4 weeks and incidence of disease reduced from ≥ 70% to less than 2% of the cats on site at the completion of the study. The total number of stray cats entering the shelter due to council contracts reduced by 50% (486 to 248). Improved cat outcomes were attributed to strategies that increased adoptions and reduced euthanasia of poorly socialized cats, including foster programs. To continue to achieve improvements in LRR and LOS, strategies to decrease intake further would be beneficial, for example, targeted sterilisation programs. In conclusion, the study highlighted the benefits of using C4C as a management tool, delivering a significant reduction in animal intake and euthanasia with positive emotional, financial and community outcomes.

Keywords: animal welfare, capacity for care, cat, euthanasia, length of stay, managed intake, shelter

Procedia PDF Downloads 149

Authors: Rodrigo Arnaldo Scarpel

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Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

Procedia PDF Downloads 92

Authors: Aye Pa Pa Myo

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Writing in English is accounted as a complex process for English as a foreign language learners. Besides, committing errors in writing can be found as an inevitable part of language learners’ writing. Generally, academic writing is quite difficult for most of the students to manage for getting better scores. Students can commit common errors in their writings when they try to write academic writing. Error analysis deals with identifying and detecting the errors and also explains the reason for the occurrence of these errors. In this paper, the researcher has an attempt to examine the common errors of undergraduate students in their academic writings at Pathein University. The purpose of doing this research is to investigate the errors which students usually commit in academic writing and to find out the better ways for correcting these errors in EFL classrooms. In this research, fifty-third-year non-English specialization students attending Pathein University were selected as participants. This research took one month. It was conducted with a mixed methodology method. Two mini-tests were used as research tools. Data were collected with a quantitative research method. Findings from this research pointed that most of the students noticed their common errors after getting the necessary input, and they became more decreased committing these errors after taking mini-test; hence, all findings will be supportive for further researches related to error analysis in academic writing.

Keywords: academic writing, error analysis, EFL learners, mini-tests, mixed methodology

Procedia PDF Downloads 136

Authors: Briante Barretto, Haley Carreon, Anesha-Maelene Ignacio

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This research paper explores the dynamic process of cultural resilience within the context of the modern tourism of two traditional island communities (Bali, Indonesia and Guam, Micronesia). It asks the question: How do indigenous people hold on to their foundational values that define their culture while moving forward in the modern world? Both Bali and Guam serve as famous destinations for tourists from all over the world, with millions of visitors on an annual basis. Both are continually being shaped in profound ways by the forces of modernity through globalization. And both are demonstrating cultural resilience while striving to find creative ways to sustain, preserve and strengthen their values and traditions within the context of a thriving modern tourist economy. This research paper, drawing on ethnographic methodologies, and in particular participant observation and in-depth interviews, explores the many challenges both communities face and the strategies and approaches they are learning to employ that help promote sustainable tourism while contributing to cultural preservation. Drawing on the insights gained from field work in both island communities, as well as the growing literature in this field study, the paper posits important lessons that can guide and inform indigenous communities that are being drawn into the global tourism market. One powerful idea emerges in the research and one that seems to guide and shape tourism policy both indigenous communities - that this current generation should be thought of as the ancestors of future generations, and thus they have a weighty responsibility to continue to learn and strive to sustain and preserve their cultures and traditions, their natural environments, and spiritual foundations for the future.

Keywords: bali, culture, environment, guam, tourism, values

Procedia PDF Downloads 76

Authors: George Abu-Aqil, Leah Tsror, Elad Shufan, Shaul Mordechai, Mahmoud Huleihel, Ahmad Salman

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Pectobacterium and Dickeya spp which negatively affect a wide range of crops are the main causes of the aggressive diseases of agricultural crops. These aggressive diseases are responsible for a huge economic loss in agriculture including a severe decrease in the quality of the stored vegetables and fruits. Therefore, it is important to detect these pathogenic bacteria at their early stages of infection to control their spread and consequently reduce the economic losses. In addition, early detection is vital for producing non-infected propagative material for future generations. The currently used molecular techniques for the identification of these bacteria at the strain level are expensive and laborious. Other techniques require a long time of ~48 h for detection. Thus, there is a clear need for rapid, non-expensive, accurate and reliable techniques for early detection of these bacteria. In this study, infrared spectroscopy, which is a well-known technique with all its features, was used for rapid detection of Pectobacterium and Dickeya spp. at the strain level. The bacteria were isolated from potato plants and tubers with soft rot symptoms and measured by infrared spectroscopy. The obtained spectra were analyzed using different machine learning algorithms. The performances of our approach for taxonomic classification among the bacterial samples were evaluated in terms of success rates. The success rates for the correct classification of the genus, species and strain levels were ~100%, 95.2% and 92.6% respectively.

Keywords: soft rot enterobacteriaceae (SRE), pectobacterium, dickeya, plant infections, potato, solanum tuberosum, infrared spectroscopy, machine learning

Procedia PDF Downloads 107

Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

Procedia PDF Downloads 129

Authors: Safwa Yargui

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This research examines the quest for a post-war American epic poem in the age of late capitalism. It explores the possibility of an epic poem in the context of post-war late capitalist America, despite the prevailing scholarly skepticism regarding the existence of epic poetry after Milton’s Paradise Lost. The aim of this paper is to demonstrate the possibility of a post-war American epic through the argument of epic consciousness. Epic consciousness provides a significant nuance to the reading of the post-war American epic by focusing on the epic’s responsiveness to late capitalism via various language forms; cultural manifestations; and conscious distortions of late capitalist media-related language; in addition to the epic’ conscious inclusion of the process of writing a post-war epic that requires a direct engagement with American-based materials. By focusing on interdisciplinary theoretical approaches, this paper includes both socio-cultural literary theories as well as literary and epic approaches developed by scholars in their critical texts that respectively contextualize the late capitalist situation and the question of post-war American epic poetry. The major findings of this research provides a new theoretical approach to the question of post-war American epic poetry. In examining the role of consciousness, this paper aims to suggest a re-thinking of the post-war American epic that is capable of self-commitment for the purpose of achieving a new sense of epic poetry in post-war late capitalist America.

Keywords: american epic, epic consciousness, late capitalism, post-wat poetry

Procedia PDF Downloads 103

Authors: Samuel Knox, Verdon Crann, Peyman Amiri, William Crowther

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There exists a shortage of open-source firmware for allowing researchers to focus on implementing high-level planning and control strategies for multi aerial robotic systems in simulation and experiment. Within this body of work, practical firmware is presented, which performs all supplementary tasks, including communications, pre and post-experiment procedures, and emergency safety measures. This allows researchers to implement high-level planning and control algorithms for path planning, traffic management, flight formation and swarming of aerial robots. The framework is built in Python using the MAVSDK library, which is compatible with flight controllers running PX4 firmware and onboard computers based on Linux. Communication is performed using Wi-Fi and the MQTT protocol, currently implemented using a centralized broker. Finally, a graphical user interface (GUI) has been developed to send general commands and monitor the agents. This framework enables researchers to prepare customized planning and control algorithms in a modular manner. Studies can be performed experimentally and in simulation using PX4 software in the loop (SITL) and the Gazebo simulator. An example experimental use case of the framework is presented using novel distributed planning and control strategies. The demonstration is performed using off-the-shelf components and minimal setup.

Keywords: aerial robotics, distributed framework, experimental, planning and control

Procedia PDF Downloads 119

Authors: Waleed Maqableh, Ahmad Al-Hamad, Manjit Sidhu

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Augmented reality (AR) technology has the capability to provide many benefits in the field of education as a modern technology which aided learning and improved the learning experience. This paper evaluates AR based application with multiple markers interaction technique (touch-to-print) which is designed for analyzing the kinematics of 4BL mechanism in mechanical engineering. The application is termed as AR-4BL-MAST and it allows the users to touch the symbols on a paper in natural way of interaction. The evaluation of this application was performed with mechanical engineering students and human–computer interaction (HCI) experts to test its effectiveness as a tangible user interface application where the statistical results show its ability as an interaction technique, and it gives the users more freedom in interaction with the virtual mechanical objects.

Keywords: augmented reality, multimedia, user interface, engineering, education technology

Procedia PDF Downloads 576

Authors: Samuel Asiedu-Addo, Jonathan Annan, Yarhands Dissou Arthur

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The study aims to explore the relational effect of lecturers’ personal attribute on student’s interest in statistics. In this study personal attributes of lecturers’ such as lecturer’s dynamism, communication strategies and rapport in the classroom as well as applied knowledge during lecture were examined. Here, exploratory research design was used to establish the effect of lecturer’s personal attributes on student’s interest. Data were analyzed by means of confirmatory factor analysis and structural equation modeling (SEM) using the SmartPLS 3 program. The study recruited 376 students from the faculty of technical and vocational education of the University of Education Winneba Kumasi campus, and Ghana Technology University College as well as Kwame Nkrumah University of science and Technology. The results revealed that personal attributes of an effective lecturer were lecturer’s dynamism, rapport, communication and applied knowledge contribute (52.9%) in explaining students interest in statistics. Our regression analysis and structural equation modeling confirm that lecturers personal attribute contribute effectively by predicting student’s interest of 52.9% and 53.7% respectively. The paper concludes that the total effect of a lecturer’s attribute on student’s interest is moderate and significant. While a lecturer’s communication and dynamism were found to contribute positively to students’ interest, they were insignificant in predicting students’ interest. We further showed that a lecturer’s personal attributes such as applied knowledge and rapport have positive and significant effect on tertiary student’s interest in statistic, whilst lecturers’ communication and dynamism do not significantly affect student interest in statistics; though positively related.

Keywords: student interest, effective teacher, personal attributes, regression and SEM

Procedia PDF Downloads 361

Authors: Kathryn Ewing

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Safe and accessible public spaces are vital elements of our South African cities. Public spaces hold the potential to act as important, vibrant places for learning, exchange, and practice. Public walkways, however, are some of the most neglected and extremely dangerous public spaces experienced in the local neighborhood of Gugulethu in Cape Town. Walkways feel insignificant, being recognized as informal and undetermined or retain complex fragments of formal erven. They are generally out of sight connecting minor streets and informal settlements. Community residents refer to the walkways as unsafe and dirty spaces. Local authorities allocate minimal to no municipal budgets nor maintenance plans resulting in a lack of basic services, particularly lighting and green infrastructure. ‘The Walkway Project’ presents a series of urban stories collected from co-design workshops, emotional mapping exercises, and fieldwork, including urban walks and urban talks. The narrative interprets the socio-spatial practice and complexity of informal public space in Gugulethu, Cape Town. The Walkway Project research, interrelated to the Master of Urban Design teaching and design-research studio, has a strong focus on participatory and engaged learning and action research methodology within a deliberate pedagogy. A consolidated urban design implementation plan exposes the impact and challenges of waste and water, opening the debate on relevant local solutions for resilience and safety in Cape Town. A small and neglected passage connecting two streets, commonly referred to as iThemba Walkway, is presented as a case study to show-case strategic urban design intervention strategies for urban upgrading. The iThemba walkway is a community-driven project that demonstrates active and responsible co-design and participatory development opportunities. In March 2021, when visited on an urban walk, the public space was covered by rubble and solid waste. By April 2021, the community cleaned the walkway and created an accessible passage for the school children to pass. Numerous co-design workshops have taken place over the past year. The walkway has emerged as a public space upgrading project facilitated, motivated, and implemented by multiple local partners and residents. Social maps from urban walks and talks illustrate the transformation of iThemba Walkway into an inclusive, safe, resilient, and sustainable urban space, linked to Sustainable Development Goal number 11, sustainable cities and communities. The outcomes of the upgrading project facilitate a deeper understanding of co-design methods, urban upgrading processes, and monitoring of public space and informal urbanism.

Keywords: informal, public space, resilience, safety, upgrade, walkways

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Authors: Kumaraamy Sasikumar

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The study was conducted in Vadamarachchi-East in Sri Lanka. Data collection was done for a period of two months from June to July 2011. The main focus of this study was to examine factors contributing to mangrove deforestation within the study area, and resultant impacts from deforestation. The study found that, the main factors that have contributed to deforestation include: Long civil wars in the region, poverty which pushed people to clear the forest to earn income through the sale of firewood and timber among others, industrial development, increasing demand for farm and settlement land, limited knowledge within the local community, weak government polices and implementation strategies, and natural disasters especially the 2004 Tsunami destruction. The impacts presented are those that impact both on the environment and the economy including; loss of income sources, loss of biodiversity, climate change, desertification, conflicts in the use of forest products and loss of land productivity due to reduced fertility caused by soil erosion. However, a few strategies have been put in place by the government to ensure the sustainable use of mangrove forest products, though these have not proved successful in reducing deforestation. The recommendations make suggestions to the government and other stakeholders to work together in ensuring sustainable use of natural resources, for example implementing laws and regulations aimed at controlling deforestation among others.

Keywords: deforestation, impacts, actors, environment, economic, sustainable development

Procedia PDF Downloads 356

Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

Procedia PDF Downloads 146

Authors: Jen-Te Pai, Jao-Heng Liu, Shin-En Pai

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The impact of climate change has intensified in recent years, causing Taiwan to face higher frequency and serious natural disasters. Therefore, it is imperative for industrial parks manufacturers to promote adaptation policies in response to climate change. On the other hand, with the rise of the international anti-terrorism situation, once a terrorist attack occurs, it will attract domestic and international media attention, especially the strategic and economic status of the science park. Thus, it is necessary to formulate adaptation and mitigation strategies under climate change and social economic disasters. After reviewed the literature about climate change, urban disaster prevention, vulnerability assessment, and risk communication, the study selected 62 industrial parks compiled by the Industrial Bureau of the Ministry of Economic Affairs of Taiwan as the research object. This study explored the vulnerability and disaster prevention and disaster relief functional assessment of these industrial parks facing of natural and socio-economic disasters. Furthermore, this study explored planned adaptation of industrial parks management section and autonomous adaptation of corporate institutions in the park. The conclusion of this study is that Taiwan industrial parks with a higher vulnerability to natural and socio-economic disasters should employ positive adaptive behaviours.

Keywords: adaptive behaviours, analytic network process, vulnerability, industrial parks

Procedia PDF Downloads 152

Authors: Danzhao Cheng, Eugene Ch'ng

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Virtual Reality technologies can reconstruct cultural heritage objects and sites to a level of realism. Concentrating mostly on documenting authentic data and accurate representations of tangible contents, current virtual heritage is limited to accumulating visually presented objects. Such constructions, however, are fragmentary and may not convey the inherent significance of heritage in a meaningful way. In order to contextualise fragmentary historical contents where history can be told, a strategy is to create a guided narrative via role-playing. Such an approach can strengthen the logical connections of cultural elements and facilitate creative synthesis within the virtual world. This project successfully reconstructed the Ningbo Sanjiangkou VR site in Yuan Dynasty combining VR technology and role-play game approach. The results with 80 pairs of participants suggest that VR role-playing can be beneficial in a number of ways. Firstly, it creates thematic interactivity which encourages users to explore the virtual heritage in a more entertaining way with task-oriented goals. Secondly, the experience becomes highly engaging since users can interpret a historical context through the perspective of specific roles that exist in past societies. Thirdly, personalisation allows open-ended sequences of the expedition, reinforcing user’s acquisition of procedural knowledge relative to the cultural domain. To sum up, role-playing in VR poses great potential for experiential learning as it allows users to interpret a historical context in a more entertaining way.

Keywords: experiential learning, maritime silk road, role-playing, virtual heritage, virtual reality

Procedia PDF Downloads 170

Authors: Michele Gattullo, Vito M. Manghisi, Alessandro Evangelista, Enricoandrea Laviola

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In this work, we explored the use of Augmented Reality (AR) to support students in laboratory lectures in Distance Learning (DL), designing an application that proved to be ready for use next semester. AR could help students in the understanding of complex concepts as well as increase their motivation in the learning process. However, despite many prototypes in the literature, it is still less used in schools and universities. This is mainly due to the perceived limited advantages to the investment costs, especially regarding changes needed in the teaching modalities. However, with the spread of epidemiological emergency due to SARS-CoV-2, schools and universities were forced to a very rapid redefinition of consolidated processes towards forms of Distance Learning. Despite its many advantages, it suffers from the impossibility to carry out practical activities that are of crucial importance in STEM ("Science, Technology, Engineering e Math") didactics. In this context, AR perceived advantages increased a lot since teachers are more prepared for new teaching modalities, exploiting AR that allows students to carry on practical activities on their own instead of being physically present in laboratories. In this work, we designed an AR application for the support of engineering students in the understanding of assembly drawings of complex machines. Traditionally, this skill is acquired in the first years of the bachelor's degree in industrial engineering, through laboratory activities where the teacher shows the corresponding components (e.g., bearings, screws, shafts) in a real machine and their representation in the assembly drawing. This research aims to explore the effectiveness of AR to allow students to acquire this skill on their own without physically being in the laboratory. In a preliminary phase, we interviewed students to understand the main issues in the learning of this subject. This survey revealed that students had difficulty identifying machine components in an assembly drawing, matching between the 2D representation of a component and its real shape, and understanding the functionality of a component within the machine. We developed a mobile application using Unity3D, aiming to solve the mentioned issues. We designed the application in collaboration with the course professors. Natural feature tracking was used to associate the 2D printed assembly drawing with the corresponding 3D virtual model. The application can be displayed on students’ tablets or smartphones. Users could interact with selecting a component from a part list on the device. Then, 3D representations of components appear on the printed drawing, coupled with 3D virtual labels for their location and identification. Users could also interact with watching a 3D animation to learn how components are assembled. Students evaluated the application through a questionnaire based on the System Usability Scale (SUS). The survey was provided to 15 students selected among those we participated in the preliminary interview. The mean SUS score was 83 (SD 12.9) over a maximum of 100, allowing teachers to use the AR application in their courses. Another important finding is that almost all the students revealed that this application would provide significant power for comprehension on their own.

Keywords: augmented reality, distance learning, STEM didactics, technology in education

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Authors: Yamamah Abdulrazaq, Lahieb A. Abrahim, Samuel E. Davies, Iain Shewring

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An electric water heater (EWH) is a powerful appliance that uses electricity in residential, commercial, and industrial settings, and the ability to control them properly will result in cost savings and the prevention of blackouts on the national grid. This article discusses the usage of timers in EWH control strategies for demand-side management (DSM). Up to the authors' knowledge, there is no systematic mapping review focusing on the utilisation of EWH control strategies in DSM has yet been conducted. Consequently, the purpose of this research is to identify and examine main papers exploring EWH procedures in DSM by quantifying and categorising information with regard to publication year and source, kind of methods, and source of data for monitoring control techniques. In order to answer the research questions, a total of 31 publications published between 1999 and 2023 were selected depending on specific inclusion and exclusion criteria. The data indicate that direct load control (DLC) has been somewhat more prevalent than indirect load control (ILC). Additionally, the mixing method is much lower than the other techniques, and the proportion of Real-time data (RTD) to non-real-time data (NRTD) is about equal.

Keywords: demand side management, direct load control, electric water heater, indirect load control, non real-time data, real-time data

Procedia PDF Downloads 87

Authors: Luzia Dominguez

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This paper explores the concept of ‘translanguaging’ and the relevance of its pedagogical application in the context of foreign language education in a multilingual urban environment. We review relevant literature discussing this theoretical concept, its scope, potential, and limitations when applied to the teaching of foreign languages. We then discuss its possible practical application in Welsh secondary schools, particularly in the most diverse areas of the Welsh capital, Cardiff (United Kingdom). The concept of translanguaging has evolved in scope, from its initial application in the teaching of Welsh and English in the Welsh bilingual context to finding a relevant space not only in the international arena of Sociolinguistics and language pedagogy but also being present in current Welsh educational policies and, presumably, practices. However, it is important to consider the actual pedagogical relevance of incorporating this concept into these policies, particularly in the teaching of Modern Foreign Languages. Additionally, it is important to examine any social factors that may influence the effectiveness of its application in the social context, in our case, a multilingual, ethnically diverse urban context. By analyzing these issues, we aim to explore possible teaching practices that could be pedagogically effective in applying the concept in Cardiff secondary schools.

Keywords: pedagogy, modern foreign languages, applied linguistics, sociolinguistics

Procedia PDF Downloads 61

Authors: D. Pogliana, A. Maso, N. Milani, D. Panzin, S. Rivaroli, J. Konin

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This case aims to identify the role of movement quality during the final stage of return to sport (RTS) in a male amateur football player 13 years old after passing the acute phase of the bilateral Osgood-Schlatter disease (OSD). The patient, after a year from passing the acute phase of OSD with the abstention of physical activity, reports bilateral anterior knee pain at the beginning of the football sport activity. Interventions: After the orthopedist check, who recommended physiotherapy sessions for the correction of motor patterns and the isometric reinforcement of the muscles of the quadriceps, the rehabilitation intervention was developed in 7 weeks through 14 sessions of neuro-motor training (NMT) with a frequency of two weekly sessions and six sessions of muscle-strengthening with a frequency of one weekly session. The sessions of NMT were carried out through free body exercises (or with overloads) with visual bio-feedback with the help of two cameras (one with anterior vision and one with lateral vision of the subject) and a big touch screen. The aim of these sessions of NMT was to modify the dysfunctional motor patterns evaluated by the 2D motion analysis test. The test was carried out at the beginning and at the end of the rehabilitation course and included five movements: single-leg squat (SLS), drop jump (DJ), single-leg hop (SLH), lateral shuffle (LS), and change of direction (COD). Each of these movements was evaluated through the video analysis of dynamic valgus knee, pelvic tilt, trunk control, shock absorption, and motor strategy. A free image analysis software (Kinovea) was then used to calculate scores. Results: Baseline assessment of the subject showed a total score of 59% on the right limb and 64% on the left limb (considering an optimal score above 85%) with large deficits in shock absorption capabilities, the presence of dynamic valgus knee, and dysfunctional motor strategies defined “quadriceps dominant.” After six weeks of training, the subject achieved a total score of 80% on the right limb and 86% on the left limb, with significant improvements in shock absorption capabilities, the presence of dynamic knee valgus, and the employment of more hip-oriented motor strategies on both lower limbs. The improvements shown in dynamic knee valgus, greater hip-oriented motor strategies, and improved shock absorption identified through six weeks of the NMT program can help a teenager amateur football player to manage the anterior knee pain during sports activity. In conclusion, NMT was a good choice to help a 13 years old male amateur football player to return to performance without pain after OSD and can also be used with all this type of athletes of the other teams' sports.

Keywords: movement analysis, neuro-motor training, knee pain, movement strategies

Procedia PDF Downloads 142

Authors: Hakimeh Masoudigavgani

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Since manufacturing firms deplete non-renewable resources and pollute air, soil, and water in greatly unsustainable manner, industrial activities or production of products are considered to be a key contributor to adverse environmental impacts. Hence, management strategies and approaches that involve an effective supply chain decision process in a manufacturing sector could be extremely significant to the application of environmental initiatives. Green manufacturing (GM) is one of these strategies which minimises negative effects on the environment through reducing greenhouse gas emissions, waste, and the consumption of energy and natural resources. This paper aims to explore what greening methods and mechanisms could be applied in the manufacturing supply chain and what are the outcomes of adopting these methods in terms of abating environmental burdens? The study is an interpretive research with an exploratory approach, using thematic analysis by coding text, breaking down and grouping the content of collected literature into various themes and categories. It is found that green supply chain could be attained through execution of some pre-production strategies including green building, eco-design, and green procurement as well as a number of in-production and post-production strategies involving green manufacturing and green logistics. To achieve an effective GM, the pre-production strategies are suggested to be employed. This paper defines GM as (1) the analysis of the ecological impacts generated by practices, products, production processes, and operational functions, and (2) the implementation of greening methods to reduce damaging influences of them on the natural environment. Analysis means assessing, monitoring, and auditing of practices in order to measure and pinpoint their harmful impacts. Moreover, greening methods involved within GM (arranged in order from the least to the most level of environmental compliance and techniques) consist of: •product stewardship (e.g. less use of toxic, non-renewable, and hazardous materials in the manufacture of the product; and stewardship of the environmental problems with regard to the product in all production, use, and end-of-life stages); •process stewardship (e.g. controlling carbon emission, energy and resources usage, transportation method, and disposal; reengineering polluting processes; recycling waste materials generated in production); •lean and clean production practices (e.g. elimination of waste, materials replacement, materials reduction, resource-efficient consumption, energy-efficient usage, emission reduction, managerial assessment, waste re-use); •use of eco-industrial parks (e.g. a shared warehouse, shared logistics management system, energy co-generation plant, effluent treatment). However, the focus of this paper is only on methods related to the in-production phase and needs further research on both pre-production and post-production environmental innovations. The outlined methods in this investigation may possibly be taken into account by policy/decision makers. Additionally, the proposed future research direction and identified gaps can be filled by scholars and researchers. The paper compares and contrasts a variety of viewpoints and enhances the body of knowledge by building a definition for GM through synthesising literature and categorising the strategic concept of greening methods, drivers, barriers, and successful implementing tactics.

Keywords: green manufacturing (GM), product stewardship, process stewardship, clean production, eco-industrial parks (EIPs)

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Aisya Zaharin

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The reporting of Islam in the Malaysian government-controlled press is complicated and occurs almost daily. This is due to the Islamisation process that has been heavily politicized in recent years. This article analyses media representations of Islam in the Malaysian media through the social responsibility theory. A provocative case study of media reporting on the “I want to touch a dog” event was analysed since dog’s saliva is ritually considered unhygienic by Muslims. This paper will not question the Islamic ruling on the dog’s issue. Instead, it calls for discussions in relation to openness and maturity in religious discourse with respect to the dog’s saliva dialogue in 1937. It applies Hage’s “minor and major reality” to explain the increasing percentage of Muslim who define their own understandings of Islam vs the government’s dogmatic versions. This paper employs Alatas’s method of “sociological investigation in Southeast Asia” by using ethnographic examination on selected mass media. Through Asiacentricity approach, this paper revisited the local framework of Alatas’s New Man encouraging Muslims to engage in knowledge and to appreciate diversities in Islamic jurisprudences. Despite government’s control, findings showed that non-Malay languages and online media are more comprehensive in reporting the news about Islam. Clearly, there has to be a re-conceptualization of Islamic discourses in the Malay-language media.

Keywords: dog, Fiqh, Islamic jurisprudence, Malaysian media, New Man, social responsibility

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Authors: Naci Büyükkaracığan, Yıldırım Akyol

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Information technology is called the technology which provides transmission of information elsewhere regardless of time, location, distance. Today, information technology is providing the occurrence of ground breaking changes in all areas of our daily lives. Information can be reached quickly to millions of people with help of information technology. In this Study, effects of information technology on students for educations and their learning preferences were demonstrated with using data obtained from questionnaires administered to students of 2015-2016 academic year at Selcuk University Kadınhanı Faik İçil Vocational School Construction Department. The data was obtained by questionnaire consisting of 30 questions that was prepared by the researchers. SPSS 21.00 package programme was used for statistical analysis of data. Chi-square tests, Mann-Whitney U test, Kruskal-Wallis and Kolmogorov-Smirnov tests were used in the data analysis for Descriptiving statistics. In a study conducted with the participation of 61 students, 93.4% of students' reputation of their own information communication device (computer, smart phone, etc.) That have been shown to be at the same rate and to the internet. These are just a computer of itself, then 45.90% of the students. The main reasons for the students' use of the Internet, social networking sites are 85.24%, 13.11% following the news of the site, as seen. All student assignments in information technology, have stated that they use in the preparation of the project. When students acquire scientific knowledge in the profession regarding their preferred sources evaluated were seen exactly when their preferred internet. Male students showed that daily use of information technology while compared to female students was statistically significantly less. Construction Package program where students are eager to learn about the reputation of 72.13% and 91.80% identified in the well which they agreed that an indispensable element in the professional advancement of information technology.

Keywords: information technologies, computer, construction, internet, learning systems

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Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

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Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

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Authors: Yountaik Leem, Sang Ho Lee

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In this paper, different goals and the ways to reach smart cities shown in many countries during planning and implementation processes will be discussed. Each country dealt with technologies which have been embedded into space as development of ICTs (information and communication technologies) for their own purposes and by their own ways. For example, European countries tried to adapt technologies to reduce greenhouse gas emission to overcome global warming while US-based global companies focused on the way of life using ICTs such as EasyLiving of Microsoft™ and CoolTown of Hewlett-Packard™ during last decade of 20th century. In the North-East Asian countries, urban space with ICTs were developed in large scale on the viewpoint of capitalism. Ubiquitous city, first introduced in Korea which named after Marc Weiser’s concept of ubiquitous computing pursued new urban development with advanced technologies and high-tech infrastructure including wired and wireless network. Japan has developed smart cities as comprehensive and technology intensive cities which will lead other industries of the nation in the future. Not only the goals and strategies but also new directions to which smart cities are oriented also suggested at the end of the paper. Like a Finnish smart community whose slogan is ‘one more hour a day for citizens,’ recent trend is forwarding everyday lives and cultures of human beings, not capital gains nor physical urban spaces.

Keywords: smart cities, urban strategy, future direction, comparative study

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Authors: Lawrence Meda, Christopher Dumas, Moses Moyo, Zayd Waghid

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As a result of some schools embracing technology to enhance students’ learning experiences in the digital era, the Faculty of Education at a University of Technology in South Africa has mandated lecturers to scale up their utilisation of technology in their teaching. Lecturers have been challenged to utilise the institution’s Learning Management System - Blackboard among other technologies - to adequately prepare trainee teachers to be able to teach competently in schools. The purpose of this study is to investigate the extent to which lecturers are utilising Blackboard to enhance their teaching. The study will be conducted using a quantitative approach, and its paradigmatic position will be positivist. The study will be done as a case study of the university’s Faculty of Education. Data will be extracted from all 100 lecturers’ Blackboard sites according to their respective modules, and it will be analysed using the four pillars of Blackboard as a conceptual framework. It is presumed that there is an imbalance on the lecturers’ utilisation of the four pillars of Blackboard as the majority use it as a content dumping site.

Keywords: blackboard, digital, education, technology

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Authors: Zayd Khayi

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This paper deals with the construction and analysis of the Tamazight text corpus. The grammatical structure of the Tamazight remains poorly understood, and a lack of comparative grammar leads to linguistic issues. In order to fill this gap, even though it is small, by constructed the diachronic corpus of the Tamazight language, and elaborated the program tool. In addition, this work is devoted to constructing that tool to analyze the different aspects of the Tamazight, with its different dialects used in the north of Africa, specifically in Morocco. It also focused on three Moroccan dialects: Tamazight, Tarifiyt, and Tachlhit. The Latin version was good choice because of the many sources it has. The corpus is based on the grammatical parameters and features of that language. The text collection contains more than 500 texts that cover a long historical period. It is free, and it will be useful for further investigations. The texts were transformed into an XML-format standardization goal. The corpus counts more than 200,000 words. Based on the linguistic rules and statistical methods, the original user interface and software prototype were developed by combining the technologies of web design and Python. The corpus presents more details and features about how this corpus provides users with the ability to distinguish easily between feminine/masculine nouns and verbs. The interface used has three languages: TMZ, FR, and EN. Selected texts were not initially categorized. This work was done in a manual way. Within corpus linguistics, there is currently no commonly accepted approach to the classification of texts. Texts are distinguished into ten categories. To describe and represent the texts in the corpus, we elaborated the XML structure according to the TEI recommendations. Using the search function may provide us with the types of words we would search for, like feminine/masculine nouns and verbs. Nouns are divided into two parts. The gender in the corpus has two forms. The neutral form of the word corresponds to masculine, while feminine is indicated by a double t-t affix (the prefix t- and the suffix -t), ex: Tarbat (girl), Tamtut (woman), Taxamt (tent), and Tislit (bride). However, there are some words whose feminine form contains only the prefix t- and the suffix –a, ex: Tasa (liver), tawja (family), and tarwa (progenitors). Generally, Tamazight masculine words have prefixes that distinguish them from other words. For instance, 'a', 'u', 'i', ex: Asklu (tree), udi (cheese), ighef (head). Verbs in the corpus are for the first person singular and plural that have suffixes 'agh','ex', 'egh', ex: 'ghrex' (I study), 'fegh' (I go out), 'nadagh' (I call). The program tool permits the following characteristics of this corpus: list of all tokens; list of unique words; lexical diversity; realize different grammatical requests. To conclude, this corpus has only focused on a small group of parts of speech in Tamazight language verbs, nouns. Work is still on the adjectives, prounouns, adverbs and others.

Keywords: Tamazight (Berber) language, corpus linguistic, grammar rules, statistical methods

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Authors: Ambeck Celyne Tebid, Harry S. Rampa

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The South African Education system recognises the need for all learners including those experiencing learning difficulties, to have access to a single unified system of education. For teachers to be pedagogically responsive to an increasingly diverse learner population without appropriate support has been proven to be unrealistic. As such, this has considerably hampered interest amongst teachers, especially those at the foundation phase to work within an Inclusive Education (IE) and training system. This qualitative study aimed at investigating foundation phase teachers’ experiences of school-based support teams (SBSTs) in two Full-Service (inclusive schools) and one Mainstream public primary school in the Gauteng province of South Africa; with particular emphasis on finding ways to supporting them, since teachers claimed they were not empowered in their initial training to teach learners experiencing learning difficulties. Hence, SBSTs were created at school levels to fill this gap thereby, supporting teaching and learning by identifying and addressing learners’, teachers’ and schools’ needs. With the notion that IE may be failing because of systemic reasons, this study uses Bronfenbrenner’s (1979) ecosystemic as well as Piaget’s (1980) maturational theory to examine the nature of support and experiences amongst teachers taking individual and systemic factors into consideration. Data was collected using in-depth, face-to-face interviews, document analysis and observation with 6 foundation phase teachers drawn from 3 different schools, 3 SBST coordinators, and 3 school principals. Data was analysed using the phenomenological data analysis method. Amongst the findings of the study is that South African full- service and mainstream schools have functional SBSTs which render formal and informal support to the teachers; this support varies in quality depending on the socio-economic status of the relevant community where the schools are situated. This paper, however, argues that what foundation phase teachers settled for as ‘support’ is flawed; as well as how they perceive the SBST and its role is problematic. The paper conclude by recommending that, the SBST should consider other approaches at foundation phase teacher support such as, empowering teachers with continuous practical experiences on how to deal with real classroom scenarios, as well as ensuring that all support, be it on academic or non-academic issues should be provided within a learning community framework where the teacher, family, SBST and where necessary, community organisations should harness their skills towards a common goal.

Keywords: foundation phase, full- service schools, inclusive education, learning difficulties, school-based support teams, teacher support

Procedia PDF Downloads 241