Search results for: learning preferences

Authors: Rie Adachi

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In Japan, it is required to improve students’ English communicative proficiency and the Education Ministry will start English education for the third grade and upper from year 2020 on. Considering the problems with the educational system, Content and Language Integrated Learning (CLIL) is more appropriate to be employed in elementary schools rather than just introducing English lessons. Effective CLIL takes place in the 4Cs Framework, and different strategies are used in various activities, such as arts and crafts, bodily expression, singing, playing roles, etc. After a CLIL workshop for local teachers focused on the 4Cs, the writer conducted a survey of the 36 participants using a questionnaire and found that they did not know the word CLIL, but seemed to have an interest after attending the workshop. The writer concluded that researchers and practitioners need to spread awareness of the 4Cs framework, to apply CLIL into Japanese educational context, to provide CLIL teacher training program and so on, in order to practice CLIL in Japanese elementary schools and nurture students with a global mindset.

Keywords: CLIL, 4Cs, homeroom teachers, intercultural understanding

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Authors: Shreyansh Jain Jeetmal, Shobith P. Chadaga, Shreyas H. Srinivas

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Internet of Things (IoT) is seen as the next major step in the ongoing revolution in the Information Age. It is predicted that in the near future billions of embedded devices will be communicating with each other to perform a plethora of tasks with or without human intervention. One of the major ongoing hotbed of research activity in IoT is Human Computer Interaction (HCI). HCI is used to facilitate communication between an intelligent system and a user. An intelligent system typically comprises of a system consisting of various sensors, actuators and embedded controllers which communicate with each other to monitor data collected from the environment. Communication by the user to the system is typically done using voice. One of the major ongoing applications of HCI is in home automation as a personal assistant. The prime objective of our project is to implement a use case of HCI for home automation. Our system is designed to detect and recognize the users and personalize the appliances in the house according to their individual preferences. Our HCI system is also capable of speaking with the user when certain commands are spoken such as searching on the web for information and controlling appliances. Our system can also monitor the environment in the house such as air quality and gas leakages for added safety.

Keywords: human computer interaction, internet of things, computer vision, sensor networks, speech to text, text to speech, android

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Authors: Joy Aworookoroh

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Writing is one of the active skills in language learning. Students of English as a foreign language are expected to write efficiently and proficiently in the language; however, there are usually challenges to optimal performance and competence in writing. Errors, on the other hand, in a foreign language learning situation are more positive than negative as they provide the basis for solving the limitations of the students. This paper investigates the situation in the Department of English, Taraba State University Jalingo. Students are administered a descriptive writing test across different levels of study. The target students are multilingual with an L1 of either Kuteb, Hausa or Junkun languages. The essays are accessed to identify the different kinds of errors in them alongside the classification of the order. Errors of correctness, clarity, engagement, and delivery were identified. However, the study identified that the degree of errors reduces alongside the experience and exposure of the students to an EFL classroom.

Keywords: errors, writings, descriptive essay, multilingual

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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

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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

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Authors: Ezgi Nevruz, Kasirga Yildirak, Ashis SenGupta

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Comparing or ranking risks is the main motivating factor behind the human trait of making choices. Cumulative prospect theory (CPT) is a preference theory approach that evaluates perception and bias in decision making under risk and uncertainty. We aim to investigate the aggregate claims of different risk classes in terms of their comparability and amenability to ordering when the impact of risk perception is considered. For this aim, we prioritize the aggregate claims taken as actuarial risks by using various stochastic ordering relations. In order to prioritize actuarial risks, we use stochastic relations such as stochastic dominance and stop-loss dominance that are proposed in the frame of partial order theory. We take into account the dependency of the individual claims exposed to similar environmental risks. At first, we modify the zero-utility premium principle in order to obtain a solution for the stop-loss premium under CPT. Then, we propose a stochastic stop-loss dominance of the aggregate claims and find a relation between the stop-loss dominance and the first-order stochastic dominance under the dependence assumption by using properties of the familiar as well as some emerging multivariate claim distributions.

Keywords: cumulative prospect theory, partial order theory, risk perception, stochastic dominance, stop-loss dominance

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Authors: Xi Zhang

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Much has been written about the promotion of Standard Mandarin and the negative effects it may have had on the development of non-Mandarin dialects. Less discussed, however, is the fate of northern Chinese dialects that are only marginally different from Standard Mandarin and the effect Standard Mandarin promotion may have had on such dialects. In this paper, we seek to bridge this gap by looking at language preferences in the family and the generational differences that they reflect. Specifically, we survey Mandarin dialect speakers from Xinle county in Hebei province, whose local dialect is similar but not identical to Standard Mandarin. We sample more than 160 families with pre-middle school children and ask the parents a series of questions that probe language behavior, language ability, and language attitude within the family with regard to educating the young. Our study shows that although most parents still speak the Xinle dialect, Standard Mandarin has become the language taught to the majority of children. We also show that only one-third of parents choose to preserve elements of Xinle dialect in the language they teach to their children. We analyze the possible factors (e.g., subjective, geographical, social, and external) that influence language choice and show how these factors collectively contribute to the current state of family language choice for educational purposes. Finally, based on our findings, we offer recommendations for coordinating the promotion of Standard Mandarin and dialect preservation in similar Mandarin-speaking regions.

Keywords: Diglossia, language planning, Mandarin, standard-with-dialects

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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

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Authors: B. Bricklin Zeff

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This research explores the development and application of a specialized chatbot tailored for a nursing English course, with a primary objective of augmenting student engagement through situational content and responsiveness to key expressions and vocabulary. Introducing the chatbot, elucidating its purpose, and outlining its functionality are crucial initial steps in the research study, as they provide a comprehensive foundation for understanding the design and objectives of the specialized chatbot developed for the nursing English course. These elements establish the context for subsequent evaluations and analyses, enabling a nuanced exploration of the chatbot's impact on student engagement and language learning within the nursing education domain. The subsequent exploration of the intricate language model development process underscores the fusion of scientific methodologies and artistic considerations in this application of artificial intelligence (AI). Tailored for educators and curriculum developers in nursing, practical principles extending beyond AI and education are considered. Some insights into leveraging technology for enhanced language learning in specialized fields are addressed, with potential applications of similar chatbots in other professional English courses. The overarching vision is to illuminate how AI can transform language learning, rendering it more interactive and contextually relevant. The presented chatbot is a tangible example, equipping educators with a practical tool to enhance their teaching practices. Methodologies employed in this research encompass surveys and discussions to gather feedback on the chatbot's usability, effectiveness, and potential improvements. The chatbot system was integrated into a nursing English course, facilitating the collection of valuable feedback from participants. Significant findings from the study underscore the chatbot's effectiveness in encouraging more verbal practice of target expressions and vocabulary necessary for performance in role-play assessment strategies. This outcome emphasizes the practical implications of integrating AI into language education in specialized fields. This research holds significance for educators and curriculum developers in the nursing field, offering insights into integrating technology for enhanced English language learning. The study's major findings contribute valuable perspectives on the practical impact of the chatbot on student interaction and verbal practice. Ultimately, the research sheds light on the transformative potential of AI in making language learning more interactive and contextually relevant, particularly within specialized domains like nursing.

Keywords: chatbot, nursing, pragmatics, role-play, AI

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Authors: Jiao Li

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Language teachers have been expected to play diversified new roles in times of educational changes. Considering the critical role that materials play in teaching and learning, language teachers have been increasingly involved in developing materials. Using identity as an analytic lens, this study aims to explore language teachers’ experiences as materials developers in China, focusing on the challenges they face and responses to them. It will adopt a multimethod approach. At the first stage, about 12 language teachers who have developed or are developing materials will be interviewed to have a broad view of their experiences. At the second stage, three language teachers who are developing materials will be studied by collecting interview data, policy documents, and data obtained from online observation of their group meetings so as to gain a deeper understanding of their experiences in materials development. It is expected that this study would have implications for teacher development, materials development, and curriculum development as well.

Keywords: educational changes, teacher development, teacher identity, teacher learning, materials development

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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

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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: Kunyu Yan

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Early childhood music education plays a significant role in an individual’s growth. Music can help children understand themselves and relate to others, and make connections between family, school, and society. In recent years, with the development of early childhood education in China, an increasing number of kindergartens have been established, and many of them pay more attention to music education. This research has two main aims. One is to discover how and why music is used in both public and private kindergartens. The second aim is to make recommendations for widening the use of music in kindergartens. In order to achieve these aims, the research uses two main methods. Firstly, it considers the historical background and cultural context of early childhood education in China; and secondly, it uses an approach that compares public and private kindergartens. In this research, six kindergartens were chosen from Qingdao city in Shandong Province as case studies, including 3 public kindergartens and 3 private kindergartens. This research was based on using three types of data collection methods: observation, semi-structured interviews with teachers, and questionnaires with parents. Participant and non-participant observational methods were used and included in daily routines at the kindergartens in order to experience the situation of music education first-hand. Interviews were associated with teachers’ views of teaching and learning music, the perceptions of the music context, and their strategies of using music. Lastly, the questionnaire was designed to obtain the views of current music education from the children’s parents in the respective kindergartens. The results are shown with three main themes: (1) distinct characteristics of public kindergartens (e.g., similar equipment, low tuition fee, qualified teachers, etc); (2) distinct characteristics of private kindergartens (e.g., various tuition fees, own teaching system, trained teachers, etc); and (3) differences between public and private kindergartens (e.g., funding, requirements for teachers, parents’ demands, etc). According to the results, we can see that the main purpose of using music in China is to develop the musical ability of children, and teachers focus on musical learning, such as singing in tune and playing instruments. However, as revealed in this research, there are many other uses and functions of music in these educational settings, including music used for non-musical learning (e.g., counting, learning language, etc.) or in supporting social routines.

Keywords: differences between private and public school, early childhood education, music education, uses and functions of music

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Authors: Kevser Cakmak, Adrián Montesano, Lourdes Artigas, Marta Salla, Clara Mateu

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The main objective of this research is to explore the relational letter writing technique as an intervention in couple therapy for reconnecting couples with their values and ethical preferences. This is a recently developed therapeutic tool within the framework of Narrative Therapy that consists of two interviews and a letter writing task, in which a meta-conversation between the relationship itself, the couple members, and the therapists is fostered. Although this specific therapeutic technique can be used within the therapy process, in this case study, it is used as a brief stand-alone narrative intervention for a middle age heterosexual couple breast cancer survivor. Couple’s relational and personal wellbeing was monitored before, during, and after the intervention by means of the dyadic adjustment and the clinical outcomes in routine evaluation-outcome measure, respectively. The couple showed a significant improvement after the intervention in both levels. The content of the letter writing exercises was qualitatively analysed to explore the reconstruction of their ethical values. Results from both methods are integrated in order to get an in-depth perspective of the newly developed tool. The potential of the letter writing technique as stand-alone and as adjunct brief intervention is discussed.

Keywords: couple therapy, narrative therapy, psychotherapy tool, relational letter writing

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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: Irdawati Bay Nalls

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This study looked at Bilingual First Language Acquisition (BFLA) Spanish-English Mexican Americans across an elementary public school in the United States and the possibility of maintaining harmonious bilingualism. Adopting a phenomenological approach, with a focus on the status of bilingualism in education within a marginalized community, classroom observations, and small group and one-on-one interviews were conducted. This study explored the struggles of these bilinguals as they acculturated in America through their attempt to blend heritage and societal languages and cultural practices. Results revealed that bilinguals as young as 5 years old expressed their need to retain Spanish as a heritage language while learning English. 12 years old foresee that Spanish will not be taught to them in schools and highlighted the need to learn Spanish outside the school environments. Their voices revealed counter-narratives on identity and the need to maintain harmonious bilingualism as these students strived to give equal importance to the learning of English and Spanish as first languages despite the setbacks faced.

Keywords: BFLA, Mexican-American, bilingual, harmonious bilingualism

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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: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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World-wide spread of coronavirus grows the concern about planning for the excess demand of hospital services in response to COVID-19 pandemic. The surge in the hospital services demand beyond the current capacity leads to shortage of ICU beds and ventilators in some parts of US. In this study, we forecast the required number of hospital beds and possible shortage of beds in US during COVID-19 pandemic to be used in the planning and hospitalization of new cases. In this paper, we used a data on COVID-19 deaths and patients’ hospitalization besides the data on hospital capacities and utilization in US from publicly available sources and national government websites. we used a novel ensemble modelling of deep learning networks, based on stacking different linear and non-linear layers to predict the shortage in hospital beds. The results showed that our proposed approach can predict the excess hospital beds demand very well and this can be helpful in developing strategies and plans to mitigate this gap.

Keywords: COVID-19, deep learning, ensembled models, hospital capacity planning

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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

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Authors: Joseph George, Anne Kotteswara Roa

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Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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Authors: Nishtha Kumar

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In order to understand how people like their interiors and how they feel inside a space, it is important to know the effect that the Colour of the space has on these individuals. Understanding this effect with the help of variables like colour choices of walls, furnishings, lighting, and the lifestyle of people will give a more clear understanding of the individual’s preferences and choices and how they feel about various colours and spaces. This paper focuses on understanding the various moods of people and the psychological effect that the colour of space has on the person living in it. An extensive literature review was conducted to analyse the effect of these variables of colour on the moods of people living in residential interiors. Alongside, a questionnaire survey was conducted to note the responses of people living in residential buildings who have got their interiors done regarding how different colours in their houses makes them feel and if it affects their mood. The results of this survey have helped in providing a better understanding of the relationship between various colours and how different people associate different moods with the same colour. Thus, such results allow us to have a deeper understanding of the effect of colour in residential interiors on individuals and how the colour of a space can affect the state of mind and mood of an individual. This result helps interior designers to incorporate colours into space according to the moods of the individual and understand how every colour depicts a different emotion in different human beings.

Keywords: colour, residental interiors, psychological effect, people, different moods

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Authors: Rosilah Hassan, Karam Dhafer Mayoof, Norngainy Mohd Tawil, Shamshubaridah Ramlee

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Application of adaptive online quiz system and a design are performed in this paper. The purpose of adaptive quiz system is to establish different questions automatically for each student and measure their competence on a definite area of discipline. This model determines students competencies in cases like distant-learning which experience challenges frequently. Questions are specialized to allow clear deductions about student gains; they are able to identify student competencies more effectively. Also, negative effects of questions requiring higher knowledge than competency over student’s morale and self-confidence are dismissed. The advantage of the system in the quiz management requires less total time for measuring and is more flexible. Self sufficiency of the system in terms of repeating, planning and assessment of the measurement process allows itself to be used in the individual education sets. Adaptive quiz technique prevents students from distraction and motivation loss, which is led by the questions with quite lower hardness level than student’s competency.

Keywords: e-learning, adaptive system, security, quiz database

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Authors: Pratham Baheti, Rohan Sanghi, Aditya Gupta

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In the largely populated city of New Delhi, India, there are a lot of people that travel by two-wheelers. Majority of the people wear helmets while traveling and know how important it is to wear helmets for their safety. Still, the number of deaths because of road accidents involving two-wheelers is significant. We had conducted a survey by traveling within and in the outskirts of Delhi so as to see the variation in data and in the opinion of people towards helmet being a safety device rather than to escape the traffic police. We conducted a survey at traffic junctions and crossings of all the stakeholders and collected feedback on the Helmet scenario in India. According to the survey, the possible reason for these deaths is that the people, being unaware of helmet safety standards (ISI standards for helmets), buy helmets with fake ISI mark from unauthorized helmet sellers for a cheap price. Also, for the people who do not wear a helmet at all or wear a helmet just because it is a law, the reasons that they do not want to wear a helmet is heavyweight, lack of ventilation, inconvenience due to a strap, and hair problems. To address all these problems, we are designing a helmet with reduced weight and also working on the Helmet’s retention system and ventilation. We plan to provide this product at a cheap cost whilst maintaining the ISI standards so that a larger section of the population would be able to afford the helmet.

Keywords: safety, survey, ISI marks, stakeholders, helmet

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Authors: Kaoru Tomita

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This study explores how visual information helps us to learn foreign language pronunciation. Visual assistance and its effect for learning foreign language have been discussed widely. For example, simplified illustrations in textbooks are used for telling learners which part of the articulation organs are used for pronouncing sounds. Vowels are put into a chart that depicts a vowel space. Consonants are put into a table that contains two axes of place and manner of articulation. When comparing a still picture and a moving picture for visualizing learners’ pronunciation, it becomes clear that the former works better than the latter. The visualization of vowels was applied to class activities in which native and non-native speakers’ English was compared and the learners’ feedback was collected: the positions of six vowels did not scatter as much as they were expected to do. Specifically, two vowels were not discriminated and were arranged very close in the vowel space. It was surprising for the author to find that learners liked analyzing their own pronunciation by linking formant ones and twos on a sheet of paper with a pencil. Even a simple method works well if it leads learners to think about their pronunciation analytically.

Keywords: feedback, pronunciation, visualization, vowel

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Authors: Heikki Ruohomaa, Vesa Salminen

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Regions are facing huge competition to attract companies, businesses, inhabitants, students, etc. This way to improve living and business environment, which is rapidly changing due to digitalization. On the other hand, from the industry's point of view, the availability of a skilled labor force and an innovative environment are crucial factors. In this context, qualified staff has been seen to utilize the opportunities of digitalization and respond to the needs of future skills. World Manufacturing Forum has stated in the year 2019- report that in next five years, 40% of workers have to change their core competencies. Through digital transformation, new technologies like cloud, mobile, big data, 5G- infrastructure, platform- technology, data- analysis, and social networks with increasing intelligence and automation, enterprises can capitalize on new opportunities and optimize existing operations to achieve significant business improvement. Digitalization will be an important part of the everyday life of citizens and present in the working day of the average citizen and employee in the future. For that reason, the education system and education programs on all levels of education from diaper age to doctorate have been directed to fulfill this ecosystem strategy. Goal: The Fourth Industrial Revolution will bring unprecedented change to societies, education organizations and business environments. This article aims to identify how education, education content, the way education has proceeded, and overall whole the education business is changing. Most important is how we should respond to this inevitable co- evolution. Methodology: The study aims to verify how the learning process is boosted by new digital content, new learning software and tools, and customer-oriented learning environments. The change of education programs and individual education modules can be supported by applied research projects. You can use them in making proof- of- the concept of new technology, new ways to teach and train, and through the experiences gathered change education content, way to educate and finally education business as a whole. Major findings: Applied research projects can prove the concept- phases on real environment field labs to test technology opportunities and new tools for training purposes. Customer-oriented applied research projects are also excellent for students to make assignments and use new knowledge and content and teachers to test new tools and create new ways to educate. New content and problem-based learning are used in future education modules. This article introduces some case study experiences on customer-oriented digital transformation projects and how gathered knowledge on new digital content and a new way to educate has influenced education. The case study is related to experiences of research projects, customer-oriented field labs/learning environments and education programs of Häme University of Applied Sciences.

Keywords: education process, digitalization content, digital tools for education, learning environments, transdisciplinary co-operation

Procedia PDF Downloads 162

Authors: N. Ould cherchali, M. S. Boucherit, L. Barazane, A. Morsli

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Photovoltaic power is widely used to supply isolated or unpopulated areas (lighting, pumping, etc.). Great advantage is that this source is inexhaustible, it offers great safety in use and it is clean. But the dynamic models used to describe a photovoltaic system are complicated and nonlinear and due to nonlinear I-V and P–V characteristics of photovoltaic generators, a maximum power point tracking technique (MPPT) is required to maximize the output power. In this paper, two online techniques of maximum power point tracking using robust controller for photovoltaic systems are proposed, the first technique use fuzzy logic controller (FLC) and the second use sliding mode controller (SMC) for photovoltaic systems. The two maximum power point tracking controllers receive the partial derivative of power as inputs, and the output is the duty cycle corresponding to maximum power. A Photovoltaic generator with Boost converter is developed using MATLAB/Simulink to verify the preferences of the proposed techniques. SMC technique provides a good tracking speed in fast changing irradiation and when the irradiation changes slowly or is constant the panel power of FLC technique presents a much smoother signal with less fluctuations.

Keywords: fuzzy logic controller, maximum power point, photovoltaic system, tracker, sliding mode controller

Procedia PDF Downloads 525

Authors: Faiza Babur Khan, Sohail Asghar

Abstract:

With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

Procedia PDF Downloads 306

Authors: Arjita Jhingran

Abstract:

The pandemic was a turning point for flexible employment. In today’s market, employees prefer companies that provide the autonomy to change their work environment and are flexible. Post pandemic employees have become accustomed to modifying, re-designing, and re-aligning their work environment, task, and the way they interact with co-workers based on their preferences after working from home for a long time. In this scenario, the concept of job crafting has come to the forefront, and research on the subject has expanded, particularly during COVID-19. Managers who provide opportunities to craft the job are driving enhanced engagement and well-being. The current study will aim to examine the impact of job crafting on work engagement and psychological well-being among 385 working professionals, ranging in the age group of 21- 39 years. (M age=30 years). The study will also draw comparisons between freelancers and full-time employees, as freelancers have been considered to have more autonomy over their job. A comparison-based among MNC or startups will be studied; as for the majority of startups, autonomy is a primary motivator. Moreover, a difference based on the level of experience will also be observed, which will add to the body of knowledge. The data will be collected through Job Crafting Questionnaire, Utrecht Work Engagement Scale, and Psychological Well-Being Scale. To infer the findings, correlation analysis will be used to study the relationship among variables, and a Three way ANOVA will be used to draw comparisons.

Keywords: job crafting, work engagement, well-being, freelancers, start-ups

Procedia PDF Downloads 92

Authors: Nigel P. Coutts, Stellina Z. Sim

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Research suggests that the pedagogy we utilize when teaching mathematics contributes to a negative attitude towards the discipline. Worried by this, we have explored teaching mathematics for understanding, fluency, and confidence. We investigated strategies to engage students with the beauty of mathematics, moving them beyond mimicry and memorization. The result is an integrated pedagogy and curriculum arrangement which combines concept-based mathematics with Number Talks, Visible Thinking Routines, and Teaching for Understanding. Our qualitative research shows that students self-report greater self-confidence and heightened engagement with mathematical thinking. Teacher reflections on student learning echo this finding. As a result of this, we advocate for teacher training in the implementation of a concept-based curriculum supplemented with Number Talk strategies.

Keywords: mathematical thinking, teaching for understanding, student confidence, concept-based learning, engagement

Procedia PDF Downloads 133

Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

Abstract:

The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

Procedia PDF Downloads 198