Search results for: learning goal orientation

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: Aymen Arfaoui, Abdelkader Soumaya, Noureddine Ben Ayed

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The study region is located in the Tunisian Dorsal Backland (Central Mediterranean), which is the easternmost part of the Saharan Atlas mountain range, trending southwest-northeast. Based on our fieldwork, seismic tomography images, seismicity, and previous studies, we propose an interpretation of the relationship between the surface deformation and fault kinematics in the study area and the internal dynamic processes acting in the Central Mediterranean from the Cenozoic to the present. The subduction and dynamics of internal forces beneath the complicated Maghrebides mobile belt have an impact on the Tertiary and Quaternary tectonic regimes in the Pelagian and Atlassic foreland that is part of our study region. The left lateral reactivation of the major "Tunisian N-S Axis fault" and the development of a compressional relay between the Hammamet Korbous and Messella-Ressas faults are possibly a result of tectonic stresses due to the slab roll-back following the Africa/Eurasia convergence. After the slab segmentation and its eastward migration (5–4 Ma) and the formation of the Strait of Sicily "rift zone" further east, a transtensional tectonic regime has been installed in this area. According to seismic tomography images, the STEP fault of the "North-South Axis" at Hammamet-Korbous coincides with the western edge of the "Slab windows" of the Sicilian Channel and the eastern boundary of the positive anomalies attributed to the residual Slab of Tunisia. On the other hand, significant E-W Plio-Quaternary tectonic activity may be observed along the eastern portion of this STEP fault system in the Grombalia zone as a result of recent vertical lithospheric motion in response to the lateral slab migration eastward to Sicily Channel. According to SKS fast splitting directions, the upper mantle flow pattern beneath Tunisian Dorsal is parallel to the NE-SW to E-W orientation of the Shmin identified in the study area, similar to the Plio-Quaternary extensional orientation in the Central Mediterranean. Additionally, the removal of the lithosphere and the subsequent uplift of the sub-lithospheric mantle beneath the topographic highs of the Dorsal and its surroundings may be the cause of the dominant extensional to transtensional Quaternary regime. The occurrence of strike-slip and extensional seismic events in the Pelagian block reveals that the regional transtensional tectonic regime persists today. Finally, we believe that the geodynamic history of the study area since the Cenozoic is primarily influenced by the preexisting weak zones, the African slab detachment, and the upper mantle flow pattern in the central Mediterranean.

Keywords: Tunisia, lithospheric discontinuity (STEP fault), geodynamic evolution, Tunisian dorsal backland, strike-slip fault, seismic tomography, seismicity, central Mediterranean

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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: 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: Saimir Heta, Ilma Robo, Rialda Xhizdari, Kers Kapaj

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The stability of an ideal disinfectant should be constant regardless of the change in the atmospheric conditions of the environment where it is kept. If the conditions such as temperature or humidity change, it is understood that it will also be necessary to approach possible changes in the holding materials such as plastic or glass bottles with the aim of protecting, for example, the disinfectant from the excessive lighting of the environment, which can also be translated as an increase in the temperature of disinfectant as a fluid. Material and Methods: In this study, an attempt was made to find the most recent published data about the best possible combination of disinfectants indicated for use after dental procedures. This purpose of the study was realized by comparing the basic literature that is studied in the field of dentistry by students with the most published data in the literature of recent years about this topic. Each disinfectant is represented by a number called the disinfectant count, in which different factors can influence the increase or reduction of variables whose production remains a specific statistic for a specific disinfectant. Results: The changes in the atmospheric conditions where the disinfectant is deposited and stored in the environment are known to affect the stability of the disinfectant as a fluid; this fact is known and even cited in the leaflets accompanying the manufactured boxes of disinfectants. It is these cares, in the form of advice, which are based not only on the preservation of the disinfectant but also on the application in order to have the desired clinical result. Aldehydes have the highest constant among the types of disinfectants, followed by acids. The lowest value of the constant belongs to the class of glycols, the predecessors of which were the halogens, in which class there are some representatives with disinfection applications. The class of phenols and acids have almost the same intervals of constants. Conclusions: If the goal were to find the ideal disinfectant among the large variety of disinfectants produced, a good starting point would be to find something unchanging or a fixed, unchanging element on the basis of which the comparison can be made properties of different disinfectants. Precisely based on the results of this study, the role of the specific constant according to the specific disinfectant is highlighted. Finding an ideal disinfectant, like finding a medication or the ideal antibiotic, is an ongoing but unattainable goal.

Keywords: different disinfectants, ideal, specific constant, dental procedures

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Authors: Armando T. Zúñiga

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As the number of English Language Learners (ELLs) in public schools continues to grow, so does the achievement gap between ELLs and other student populations. In an effort to support classroom teachers with effective instructional strategies for this student population, many districts have created instructional coaching positions specifically to support classroom teachers of ELLs—ELL Teachers on Special Assignment (ELL TOSAs). This study employed a gap analysis framework to the ELL TOSA professional support program in one California school district to examine knowledge, motivation, and organizational influences (KMO) on the ELL TOSAs’ goal of supporting classroom teachers of ELLs. Three themes emerged as a result of data analysis. First, there was evidence to illustrate the interaction between knowledge and the organization. Data from ELL TOSAs indicated an understanding of the role that collaboration plays in coaching and how to operationalize it in their support of teachers. Further, all of the ELL TOSAs indicated they have received professional development on effective strategies for instructional coaching. Additionally, a large percentage of the ELL TOSAs indicated a knowledge of modeling as an effective coaching practice. Accordingly, all of the ELL TOSAs indicated that they had knowledge of feedback as an effective coaching strategy. However, there was not sufficient evidence to support that they learned the latter two strategies through professional development. A second theme surfaced as there was evidence to illustrate an interaction between motivation and the organization. Some ELL TOSAs indicated that their sense of self-efficacy was affected by conflicting roles and expectations for the job. Most of the ELL TOSAs indicated that their sense of self-efficacy was affected by an increased workload brought about by fiscal decision making. Finally, there was evidence illustrating the interaction between the organization and motivation. The majority of the of ELL TOSAs indicated that there is confusion about how their roles are perceived, leaving the ELL TOSAs to feel that their actions did not contribute to instructional change. In conclusion, five research-based recommendations to support ELL TOSA goal attainment and considerations for future research on instructional coaches for classroom teachers of ELLs are provided.

Keywords: English language development, English language acquisition, language and leadership, language coaching, English language learners, second language acquisition

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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: Mohamed A. Deyab, Ahmed E. Awadallah

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Under various conditions, we present a promising method for producing pure hydrogen energy from the electrochemical reaction of Mg metal in waste oilfield water (WOW). Mg metal and WOW are primarily consumed in this process. The results show that the hydrogen gas output is highly dependent on temperature and solution pH. The best conditions for hydrogen production were found to be a low pH (2.5) and a high temperature (338 K). For the first time, the Allyl methylimidazolium bis-trifluoromethyl sulfonyl imide) (IL) ionic liquid is used to regulate the rate of hydrogen generation. It has been confirmed that increasing the solution temperature and decreasing the solution pH accelerates Mg dissolution and produces more hydrogen per unit of time. The adsorption of IL on the active sites of the Mg surface is unrestricted by mixing physical and chemical orientation. Inspections using scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and FT-IR spectroscopy were used to identify and characterise surface corrosion of Mg in WOW. This process is also completely safe and can create energy on demand.

Keywords: hydrogen production, Mg, wastewater, ionic liquid

Procedia PDF Downloads 163

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: Nguyen Quynh Trang, Nguyễn Thị Hông Nhung

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The study aimed to identify the effectiveness of using the mind map technique to enhance students’ medical vocabulary retention among a group of students at a higher education institution - Thai Nguyen University of Medicine and Pharmacy during the first semester of the school year 2022-2023. The research employed a quasi-experimental method, exploring primary sources such as questionnaires and the analyzed results of pre-and-post tests. Almost teachers and students showed high preferences for the implementation of the mind map technique in language teaching and learning. Furthermore, results from the pre-and-post tests between the experimental group and control one pointed out that this technique brought back positive academic performance in teaching and learning English. The research findings revealed that there should be more supportive policies to evoke the use of the mind map technique in a pedagogical context. Aim of the Study: The purpose of this research was to investigate whether using mind mapping can help students to enhance nursing students’ medical vocabulary retention and to assess the students’ attitudes toward using mind mapping as a tool to improve their vocabulary. The methodology of the study: The research employed a quasi-experimental method, exploring primary sources such as questionnaires and the analyzed results of pre-and-post tests. The contribution of the study: The research contributed to the innovation of teaching vocabulary methods for English teachers at a higher education institution. Moreover, the research helped the English teachers and the administrators at a university evoke and maintain the motivation of students not only in English classes but also in other subjects. The findings of this research were beneficial to teachers, students, and researchers interested in using mind mapping to teach and learn English vocabulary. The research explored and proved the effectiveness of applying mind mapping in teaching and learning English vocabulary. Therefore, teaching and learning activities were conducted more and more effectively and helped students overcome challenges in remembering vocabulary and creating motivation to learn English vocabulary.

Keywords: medical vocabulary retention, mind map technique, nursing students, medical vocabulary

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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: 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: Purnomo Yustianto, Robin Doss, Suhardi, Novianto Budi Kurniawan

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As a term for characterizing a process of devising a service system, the term ‘service engineering’ is still regarded as an ‘open’ research challenge due to unspecified details and conflicting perspectives. This paper presents consolidated service engineering ontologies in collecting, specifying and defining relationship between components pertinent within the context of service engineering. The ontologies are built by way of literature surveys from the collected conceptual works by collating various concepts into an integrated ontology. Two ontologies are produced: general service ontology and software service ontology. The software-service ontology is drawn from the informatics domain, while the generalized ontology of a service system is built from both a business management and the information system perspective. The produced ontologies are verified by exercising conceptual operationalizations of the ontologies in adopting several service orientation features and service system patterns. The proposed ontologies are demonstrated to be sufficient to serve as a basis for a service engineering framework.

Keywords: engineering, ontology, service, SoaML

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Authors: Chang Hung Chen

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Typically the Cause-Related Marketing (CRM) is effective for promoting products, and is also accepted as a role of communication tool for creating a positive image of the corporate. Today, companies are taking Corporate Social Responsibility (CSR) as core activities to build a goal of sustainable development. CRM is not a synonym of CSR. Actually, CRM is a part of CSR, or a type of marketing strategy in CSR framework. This article focuses on the relationship between CSR and CRM, and how the CRM improves the CSR performance of the corporate. The research was conducted through review of literature on the subject area.

Keywords: cause-related marketing, corporate social responsibility, corporate image, consumer behavior

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Authors: Shola Abidemi Olabode

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Nigeria as a country has been plagued by numerous conflicts since the British colonialists gave in to the advocacy of Nigerian dissents for independence and relinquished power in 1960. These conflicts are often motivated by different issues, from socio-political and economic issues to struggles of ethnic and religious orientation. The Niger Delta region which accounts for the country’s economic mainstay has been at the epicentre of such conflicts. Over the years, peaceful protests, and radical insurgency and resistance movements too numerous to mention have emerged in the region. The Niger Delta Avengers is an example of a recent conflict movement in the region. Using a case study approach, and looking through a cyberconflict perspective, this paper offers a discussion on the intersection between digital and social media and framing in the Niger Delta Avengers conflict. It advocates that the Niger Delta Avengers use digital and social media to legitimise and give credence to their struggle.

Keywords: digital and social media, framing, Niger delta avengers, cyberconflict, conflict

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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: 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: 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

Procedia PDF Downloads 457

Authors: Rym Zouari, Sami Ben Amar, Abdelwaheb Dogui

Abstract:

This paper presents an experimental characterization of the anisotropic mechanical behavior of 4 textile woven fabrics with different weaves (Twill 3, Plain, Twill4 and Satin 4) by off-axis tensile testing. These tests are applied according seven directions oriented by 15° increment with respect to the warp direction. Fixed and articulated jaws are used. Analysis of experimental results is done through global (Effort/Elongation curves) and local scales. Global anisotropy was studied from the Effort/Elongation curves: shape, breaking load (Frup), tensile elongation (EMT), tensile energy (WT) and linearity index (LT). Local anisotropy was studied from the measurement of strain tensor components in the central area of the specimen as a function of testing orientation and effort: longitudinal strain ɛL, transverse strain ɛT and shearing ɛLT. The effect of used jaws is also analyzed.

Keywords: anisotropy, off-axis tensile test, strain fields, textile woven fabric

Procedia PDF Downloads 362

Authors: Kaoru Tomita

Abstract:

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

Procedia PDF Downloads 255

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

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Authors: Nigel P. Coutts, Stellina Z. Sim

Abstract:

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 157

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 220

Authors: Jonathan D. Recchi

Abstract:

Introduction: Workplace violence is a major concern for nurses throughout the United States and is a rising occupational health hazard that has been exacerbated by both the Covid-19 pandemic and increasing patient and family member incivility. De-escalation training has been found to be an evidence-based tool for emergency department nurses to help avoid or mitigate high-risk situations that could lead to workplace violence. Many healthcare organizations either do not provide de-escalation training to their staff or only provide it sparingly, such as during new employee orientation. There is limited research in the literature on the psychological benefits of de-escalation training. Purpose: The purpose of this study is to determine if there are psychological and organizational advantages to providing emergency department nurses with de-escalation training. Equipping emergency department nurses with skills that are essential to de-escalate violent or potentially violent patients may help prevent physical, mental, and/or psychological damage to the nurse because of violence and/or threatening acts. The hypothesis is that providing de-scalation training to emergency department nurses will lead to increased nurse confidence in dealing with aggressive patients, increased resiliency, increased professional quality of life, and increased intention to stay with their current organization. This study aims to show that organizations would benefit from providing de-escalation training to all nurses operating in high-risk areas on a regular basis. Significance: Showing psychological benefits to providing evidence-based de-escalation training can provide healthcare organizations with the ability to retain a more resilient and prepared workforce. Method: This study uses a pre-experimental cross-sectional pre-/post-test design using a convenience sample of emergency department registered nurses employed across Jefferson Health Northeast (Jefferson Torresdale, Jefferson Bucks, and Jefferson Frankford. Inclusion criteria include registered nurses who work full or part-time, with 51% or more of their clinical time spent in direct clinical care. Excluded from participation are registered nurses in orientation, per-diem nurses, temporary and/or travel nurses, nurses who spend less than 51% of their time in direct patient care, and nurses who have received de-escalation training within the past two years. This study uses the Connor-Davidson Resilience Scale 10 (CD-RISC-10), the Clinician Confidence in Coping with Patient Aggression Scale, the Press Ganey Intention To Stay question, and the Professional Quality of Life Scale. Results: A Paired t-Test will be used to analyze the mean scores of the three scales and one question pre and post-intervention to determine if there is a statistically significant difference in RN resiliency, confidence in coping with patient aggression, intention to stay, and professional quality of life. Discussion and Conclusions: Upon completion, the outcomes of this intervention will show the importance of providing evidence-based de-escalation training to all nurses operating within the emergency department.

Keywords: de-escalation, nursing, emergency department, workplace violence

Procedia PDF Downloads 106

Authors: Bichi Muktar Sani

Abstract:

The philosophy of Physical and Health Education is to develop academic and professional competency which will enable individuals earn a living and render unique services to the society and also provide good basis of knowledge and experience that characterize an educated and fully developed person through physical activities. With the increase of sedentary activities such as watching television, playing videogames, increased computer technology, automation and reduction of high school Physical and Health Education schedules, young people are most likely to become overweight, and less fit. Physical Education is a systematic instruction in sports, training, practice, gymnastics, exercises, and hygiene given as part of a school or college program. Physical and Health Education is the study, practice, and appreciation of the art and science of human movement. Physical and Health Education is course in the curricula that utilizes the learning in the cognitive, affective, and psychomotor domains in a lay or movement exploration setting. The paper made some recommendations on the way forward.

Keywords: issues, challenges, physical education, school

Procedia PDF Downloads 46