Search results for: structure learning

Authors: Marcel Chevalier, Léo Dupont, Sylvain Marié, Frédérique Roffet, Elena Stolyarova, William Templier, Costin Vasile

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Industrial end-users are currently facing an increasing need to reduce the risk of unexpected failures and optimize their maintenance. This calls for both short-term analysis and long-term ageing anticipation. At Schneider Electric, we tackle those two issues using both machine learning and first principles models. Machine learning models are incrementally trained from normal data to predict expected values and detect statistically significant short-term deviations. Ageing models are constructed by breaking down physical systems into sub-assemblies, then determining relevant degradation modes and associating each one to the right kinetic law. Validating such anomaly detection and maintenance models is challenging, both because actual incident and ageing data are rare and distorted by human interventions, and incremental learning depends on human feedback. To overcome these difficulties, we propose to simulate physics, systems, and humans -including asset maintenance operations- in order to validate the overall approaches in accelerated time and possibly choose between algorithmic alternatives.

Keywords: degradation models, ageing, anomaly detection, soft sensor, incremental learning

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Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

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Authors: Ghiwa Dandach

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By challenging the anti-failure bias and contributing to the theoretical territory of the attribution theory, this thesis develops a comprehensive process for entrepreneurial learning from failure. The practical implication of the findings suggests assisting entrepreneurs (current, failing, and nascent) in effectively anticipating and reflecting upon failure. Additionally, the process is suggested to enhance the level of institutional and private (accelerators and financers) support provided to entrepreneurs, the implications of which may improve future opportunities for entrepreneurial success. Henceforth, exploring learning from failure is argued to impact the potential survival of future ventures, subsequently revitalizing the economic contribution of entrepreneurship. This learning process can be enhanced with the cognitive development of causal ascriptions for failure, which eventually impacts learning outcomes. However, the mechanism with which entrepreneurs make sense of failure, reflect on the journey, and transform experience into knowledge is still under-researched. More specifically, the cognitive process of failure attribution is under-explored, majorly in the context of developing economies, calling for a more insightful understanding on how entrepreneurs ascribe failure. Responding to the call for more thorough research in such cultural contexts, this study expands the understanding of the dimensions of failure attributions as perceived by entrepreneurs and the impact of these dimensions on learning outcomes in the Lebanese context. The research adopted the exploratory interpretivism paradigm and collected data from interviews with industry experts first, followed by narratives of entrepreneurs using the qualitative multimethod approach. The holistic and categorical content analysis of narratives, preceded by the thematic analysis of interviews, unveiled how entrepreneurs ascribe failure by developing minor and major dimensions of each failure attribution. The findings have also revealed how each dimension impacts the learning from failure when accompanied by emotional resilience. The thesis concludes that exploring in-depth the dimensions of failure attributions significantly determines the level of learning generated. They are moving beyond the simple categorisation of ascriptions as primary internal or external unveiled how learning may occur with each attribution at the individual, venture, and ecosystem levels. This has further accentuated that a major internal attribution of failure combined with a minor external attribution generated the highest levels of transformative and double-loop learning, emphasizing the role of personal blame and responsibility on enhancing learning outcomes.

Keywords: attribution, entrepreneurship, reflection, sense-making, emotions, learning outcomes, failure, exit

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Authors: JaeYoon Lee, Gi-Hoon Yang, JongHan Ha, MyungGu Yeo, SeungHyun Ahn, Hyeongjin Lee, HoJun Jeon, YongBok Kim, Minseong Kim, GeunHyung Kim

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One of the important factors in tissue engineering is to design optimal biomedical scaffolds, which can be governed by topographical surface characteristics, such as size, shape, and direction. Of these properties, we focused on the effects of nano- to micro-sized hierarchical surface. To fabricate the hierarchical surface structure on poly(ε-caprolactone) (PCL) film, we employed a micro-casting technique by pressing the mold and nano-etching technique using a modified plasma process. The micro-sized topography of PCL film was controlled by sizes of the micro structures on lotus leaf. Also, the nano-sized topography and hydrophilicity of PCL film were controlled by a modified plasma process. After the plasma treatment, the hydrophobic property of the PCL film was significantly changed into hydrophilic property, and the nano-sized structure was well developed. The surface properties of the modified PCL film were investigated in terms of initial cell morphology, attachment, and proliferation using osteoblast-like-cells (MG63). In particular, initial cell attachment, proliferation and osteogenic differentiation in the hierarchical structure were enhanced dramatically compared to those of the smooth surface. We believe that these results are because of a synergistic effect between the hierarchical structure and the reactive functional groups due to the plasma process. Based on the results presented here, we propose a new biomimetic surface model that maybe useful for effectively regenerating hard tissues.

Keywords: hierarchical surface, lotus leaf, nano-etching, plasma treatment

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Authors: Radhia Toujani, Jalel Akaichi

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In recent years, the study of community detection in social networks has received great attention. The hierarchical structure of the network leads to the emergence of the convergence to a locally optimal community structure. In this paper, we aim to avoid this local optimum in the introduced hybrid hierarchical method. To achieve this purpose, we present an objective function where we incorporate the value of structural and semantic similarity based modularity and a metaheuristic namely bees colonies algorithm to optimize our objective function on both hierarchical level divisive and agglomerative. In order to assess the efficiency and the accuracy of the introduced hybrid bee colony model, we perform an extensive experimental evaluation on both synthetic and real networks.

Keywords: social network, community detection, agglomerative hierarchical clustering, divisive hierarchical clustering, similarity, modularity, metaheuristic, bee colony

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Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf

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We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approach

Keywords: top tagger, multivariate, deep learning, LHC, single top

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Authors: Alhusein Almahjoub, Dongyu Qiu

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This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

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Authors: Gabriela Teodorescu, Ioana Daniela Dulama

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In an ever-changing society, the education system needs to constantly evolve to meet market demands. During its 30 years of existence, Valahia University of Targoviste (VUT) tried to offer its students a series of teaching-learning schemes that would prepare them for a remarkable career. In VUT, the achievement of performance through innovation can be analyzed by reference to several key indicators (i.e., university climate, university resources, and innovative methods applied to classes), but it is possible to differentiate between activities in the classic format: participate to courses; interactive seminars and tutorials; laboratories, workshops, project-based learning; entrepreneurial activities, through simulated enterprises; mentoring activities. Thus, VUT has implemented over time a series of schemes and projects based on innovation and entrepreneurship, and in this paper, some of them will be briefly presented. All these schemes were implemented by facilitating an effective dialog with students and the opportunity to listen to their views at all levels of the University and in all fields of study, as well as by developing a partnership with students to set out priority areas. VUT demonstrates innovation and entrepreneurial capacity through its new activities for higher education, which will attract more partnerships and projects dedicated to students.

Keywords: Romania, project-based learning, entrepreneurial activities, simulated enterprises

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Authors: Sultan Ahmed Arishi

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The objective of the study was to investigate the attitude of the Saudi students attending the English Language programmes of the Royal Commission for Jubail towards using CALL, as well as to discover whether computer-assisted teaching is useful and valuable for students in learning English. Data were collected with the help of interviews and survey questionnaires. The outcomes of the investigation showed that students had a positive attitude towards CALL. Moreover, the listening skills of the students had the most substantial effect on students learning English through CALL. Unexpectedly, the teaching staff, equipment, curriculum, or even a student's poor English background was a distinct barrier that attributed to any weaknesses of using CALL, or in other words, all these factors were of a similar attitude.

Keywords: CALL, teaching aids, teaching technology, teaching English with technology, teaching English in Saudi Arabia

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Authors: Takuma Yamamoto

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Present study investigated the relationship between elementary school children’s prosocial behavior in classroom and satisfaction with school life (approval and victimization from other children) with considering from the perspective of classroom social goal structures (prosocial and compliance goal structures). Participants were 755 elementary school children (393 boys, 362 girls, mean range= 10-12, 5th grader and 6th grader) who were living in Chugoku District, Japan. They filled up questionnaire which was consisted of Murakami, Nishimura and Sakurai’s (2016) prosocial behavior toward friend scale, Kawamura and Tagami’s (1997) satisfaction in classroom scale and Ohtani, Okada, Nakaya and Ito’s (2016) classroom social goal structures scale. Regression lines that satisfaction in classroom is dependent variable and prosocial behavior is independent variable for each class were drawn. There were two types of classroom which children’s prosocial behavior correlated with satisfaction positively and did not. Then one-way MANOVA was conducted to further describe two types of classroom which prosocial behavior increased satisfaction in classroom (type 1) and prosocial behavior decreased satisfaction (type 2). MANOVA for Prosocial goal structure was significant, type 1 > type 2. There were two key findings from this study. First, MANOVA for prosocial goal structure was significant. Second, high score of prosocial goal structure was not necessary condition for the classroom type which children’s prosocial behavior correlated with satisfaction. The implications from these key findings were: (1) in the low prosocial goal structure classroom, children will not behave prosocially because of their negative expectation for the effect of prosocial behavior, (2) this study can be a contribution for classroom management that teachers need to consider about the negative possibilities of prosocial behavior when they try to increase the amount of children’s positive behavior.

Keywords: elementary school children, classroom social goal structure, satisfaction with school life, prosocial behavior

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Authors: Seoi Lee, Dongjoo Chin, Heewon Kim

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Gamification refers to a technique that applies game elements to non-gaming elements, such as education and exercise, to make people more engaged in these behaviors. The purpose of this study was to identify effective elements in gamification for changing human behaviors. In order to accomplish this purpose, a survey based on learning theory was developed, especially for assessing antecedents and consequences of behaviors, and 8 popular and 8 unpopular games were selected for comparison. A total of 407 adult males and females were recruited via crowdsourcing Internet marketplace and completed the survey, which consisted of 19 questions for antecedent and 14 questions for consequences. Results showed no significant differences in consequence questions between popular and unpopular games. For antecedent questions, popular games are superior to unpopular games in character customization, play type selection, a sense of belonging, patch update cycle, and influence or dominance. This study is significant in that it reveals the elements of gamification based on learning theory. Future studies need to empirically validate whether these factors affect behavioral change.

Keywords: gamification, learning theory, antecedent, consequence, behavior change, behaviorism

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Authors: Sreekanth Reddy Ballarapu

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The perception of the whole process of teaching and learning is undergoing a drastic and radical change. More and more student-centered, pragmatic, and flexible approaches are gradually replacing teacher-centered lecturing and structural-syllabus instruction. The issue of teaching English as a Foreign language is no exception in this regard. The traditional Present-Practice-Produce (P-P-P) method of teaching English is overtaken by Task-Based Teaching which is a subsidiary branch of Communicative Language Teaching. At this juncture this article strongly tries to convey that - Task-based learning, has an advantage over other traditional methods of teaching. All teachers of English must try to customize their texts into productive tasks, apply them, and evaluate the students as well as themselves. Task Based Learning is a double edged tool which can enhance the performance of both the teacher and the taught. The sample for this case study is a class of 35 students from Semester III - Network branch at TVTC College of Technology, Adhum - Kingdom of Saudi Arabia. The students are high school passed out and aged between 19-21years.For the present study the prescribed textbook Technical English 1 by David Bonamy was used and a number of language tasks were chalked out during the pre- task stage and the learners were made to participate voluntarily and actively. The Action Research methodology was adopted within the dual framework of Communicative Language Teaching and Task-Based Learning. The different tools such as questionnaires, feedback and interviews were used to collect data. This study provides information about various techniques of Communicative Language Teaching and Task Based Learning and focuses primarily on the advantages of using a Task Based Learning approach. This article presents in detail the objectives of the study, the planning and implementation of the action research, the challenges encountered during the execution of the plan, and the pedagogical outcome of this project. These research findings serve two purposes: first, it evaluates the effectiveness of Task Based Learning and, second, it empowers the teacher's professionalism in designing and implementing the tasks. In the end, the possibility of scope for further research is presented in brief.

Keywords: action research, communicative language teaching, task based learning, perception

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Authors: Samuel Mwangi, Josephine K. Mule

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Access control as a security technique regulates who or what can access resources. It is a fundamental concept in security that minimizes risks to the institutions that use access control. Regulating access to institutions of higher learning is key to ensure only authorized personnel and students are allowed into the institutions. The use of biometrics has been criticized due to the setup and maintenance costs, hygiene concerns, and trepidations regarding data privacy, among other apprehensions. Facial recognition is arguably a fast and accurate way of validating identity in order to guard protected areas. It guarantees that only authorized individuals gain access to secure locations while requiring far less personal information whilst providing an additional layer of security beyond keys, fobs, or identity cards. This exploratory study sought to investigate the use of facial recognition in controlling access in institutions of higher learning in Kenya. The sample population was drawn from both private and public higher learning institutions. The data is based on responses from staff and students. Questionnaires were used for data collection and follow up interviews conducted to understand responses from the questionnaires. 80% of the sampled population indicated that there were many security breaches by unauthorized people, with some resulting in terror attacks. These security breaches were attributed to stolen identity cases, where staff or student identity cards were stolen and used by criminals to access the institutions. These unauthorized accesses have resulted in losses to the institutions, including reputational damages. The findings indicate that security breaches are a major problem in institutions of higher learning in Kenya. Consequently, access control would be beneficial if employed to curb security breaches. We suggest the use of facial recognition technology, given its uniqueness in identifying users and its non-repudiation capabilities.

Keywords: facial recognition, access control, technology, learning

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Authors: Natalia Sáez, Dina Shulfman

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There is an important research gap regarding accessible pedagogical techniques for teaching foreign languages to adults with visual impairments. English as a foreign language (EFL), in particular, is needed in many countries to expand occupational opportunities and improve living standards. Within EFL research, teaching and learning prepositions have only recently gained momentum, considering that they constitute one of the most difficult structures to learn in a foreign language and are fundamental for communicating about spatial relations in the world, both on the physical and imaginary levels. Learning to use prepositions would not only facilitate communication when referring to the surrounding tangible environment but also when conveying ideas about abstract topics (e.g., justice, love, society), for which students’ sociocultural knowledge about space could play an important role. By potentiating visually impaired students’ ability to construe mental spatial imagery, this study made efforts to explore pedagogical techniques that cater to their strengths, helping them create new worlds by welcoming and expanding their sociocultural funds of knowledge as they learn to use English prepositions. Fifteen visually impaired adults living in Chile participated in the study. Their first language was Spanish, and they were learning English at the intermediate level of proficiency in an EFL workshop at La Biblioteca Central para Ciegos (The Central Library for the Blind). Within this workshop, a series of activities and interviews were designed and implemented with the intention of uncovering students’ spatial funds of knowledge when learning literal/physical uses of three English prepositions, namely “in,” “at,” and “on”. The activities and interviews also explored whether students used their original spatial funds of knowledge when learning metaphorical uses of these prepositions and if their use of spatial imagery changed throughout the learning activities. Over the course of approximately half a year, it soon became clear that the students construed mental images of space when learning both literal/physical and metaphorical uses of these prepositions. This research could inform a new approach to inclusive language education using pedagogical methods that are relevant and accessible to students with visual impairments.

Keywords: EFL, funds of knowledge, prepositions, spatial cognition, visually impaired students

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Authors: Mohammad Hadi Mahmoodi, Soroor Zekrati

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The aim of this study was to investigate the relationship between hemispheric dominance and intonation learning of Iranian EFL students. In order to gain this goal, 52 female students from three levels of beginner, elementary and intermediate in Paradise Institute, and 18 male university students at Bu-Ali Sina University constituted the sample. In order to assist students learn the correct way of applying intonation to their everyday speech, the study proposed an interactive approach and provided students with visual aid through which they were able to see the intonation pattern on computer screen using 'Speech Analyzer' software. This software was also used to record subjects’ voice and compare them with the original intonation pattern. Edinburg Handedness Questionnaire (EHD), which ranges from –100 for strong left-handedness to +100 for strong right-handedness was used to indicate the hemispheric dominance of each student. The result of an independent sample t-test indicated that girls learned intonation pattern better than boys, and that right brained students significantly outperformed the left brained ones. Using one-way ANOVA, a significant difference between three proficiency levels was also found. The posthoc Scheffer test showed that the exact difference was between intermediate and elementary, and intermediate and beginner levels, but no significant difference was observed between elementary and beginner levels. The findings of the study might provide researchers with some helpful implications and useful directions for future investigation into the domain of the relationship between mind and second language learning.

Keywords: intonation, hemispheric dominance, visual aid, language learning, second language learning

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Authors: Xiao Liulingzi

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It is important for using multi-sensory teaching in music learning. This article aims to provide knowledge in multi-sensory learning and teaching music in primary school. For primary school students, in addition to the training of basic knowledge and skills of music, students' sense of participation and creativity in music class are the key requirements, especially the flexibility and dynamics in music class, so that students can integrate into music and feel the music. The article explains the multi-sensory sense in music learning, the differences between multi-sensory music teaching and traditional music teaching, and music multi-sensory teaching in primary schools in China.

Keywords: multi-sensory, teaching practice, primary music classroom, China

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Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

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The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

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Authors: Esther Pearl Palmer

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Driven by the increased pressure on Higher Education Institutions (HEIs) to produce work-ready graduates for the modern world of work, this study reflects on triad teaching and learning practices to increase student engagement and employability. In the South African higher education context, the employability of graduates is imperative in strengthening the country’s economy and in increasing competitiveness. Within this context, the field of Human Resource Management (HRM) calls for innovative methods and approaches to teaching and learning and assessing the skills and competencies of graduates to render them employable. Digital competency in Human Resource Information Systems (HRIS) is an important component and prerequisite for employment in HRM. The purpose of this research is to reflect on the subject HRIS developed by lecturers at the Central University of Technology, Free State (CUT), with the intention to actively engage students in real-world learning activities and increase their employability. The Enrichment Triad Model (ETM) was used as theoretical framework to develop the subject as it supports a triad teaching and learning approach to education. It is, furthermore, an inter-structured model that supports collaboration between industry, academics and students. The study follows a mixed-method approach to reflect on the learning experiences of the industry, academics and students in the subject field over the past three years. This paper is a work in progress and seeks to broaden the scope of extant studies about student engagement in work-related learning to increase employability. Based on the ETM as theoretical framework and pedagogical practice, this paper proposes that following a triad teaching and learning approach will increase work-related skills of students. Findings from the study show that students, academics and industry alike regard educational opportunities that incorporate active learning experiences with the world of work enhances student engagement in learning and renders them more employable.

Keywords: digital competence, enriched triad model, human resource information systems, student engagement, triad pedagogy.

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Authors: Zoja Raud, Valery Vodovozov

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The paper focuses on the distance laboratory organisation for training the electrical engineering staff and students in the fields of electrical drive and power electronics. To support online knowledge acquisition and professional enhancement, new challenges in remote education based on an active learning approach with self-assessment have been emerged by the authors. Following the literature review and explanation of the improved assessment methodology, the concept and technological basis of the labs arrangement are presented. To decrease the gap between the distance study of the up-to-date equipment and other educational activities in electrical engineering, the improvements in the following-up the learners’ progress and feedback composition are introduced. An authoring methodology that helps to personalise knowledge acquisition and enlarge Web-based possibilities is described. Educational management based on self-assessment is discussed.

Keywords: advanced training, active learning, distance learning, electrical engineering, remote laboratory, self-assessment

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Authors: Shatha Ghareeb, Rawaa Al-Jumeily, Thar Baker

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In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.

Keywords: admissions, algorithms, cloud computing, differentiation, fog computing, levelling, machine learning

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Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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Authors: Felix Oromena Egara, Moeketsi Mosia

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The study aimed to evaluate the impact of blended learning on mathematics retention among secondary school students. Conducted in the Isoko North Local Government Area of Delta State, Nigeria, the research involved 1,235 senior class one (SS 1) students. Employing a non-equivalent control group pre-test-post-test quasi-experimental design, a sample of 70 students was selected from two secondary schools with ICT facilities through purposive sampling. Random allocation of students into experimental and control groups was achieved through balloting within each selected school. The investigation included three assessment points: pre-Mathematics Achievement Test (MAT), post-MAT, and post-post-MAT (retention), administered systematically by the researchers. Data collection utilized the established MAT instrument, which demonstrated a high reliability score of 0.86. Statistical analysis was conducted using the Statistical Package for Social Sciences (SPSS) version 28, with mean and standard deviation addressing study questions and analysis of covariance scrutinizing hypotheses at a significance level of .05. Results revealed significantly greater improvements in mathematics retention scores among students exposed to blended learning compared to those instructed through conventional methods. Moreover, noticeable differences in mean retention scores were observed, with male students in the blended learning group exhibiting notably higher performance. Based on these findings, recommendations were made, advocating for mathematics educators to integrate blended learning, particularly in geometry teaching, to enhance students’ retention of mathematical concepts.

Keywords: blended learning, flipped classroom model, secondary school students, station rotation model

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Authors: Christian Uchechukwu Gilbert

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Generativism in language design investigates the framework on which varying sentence structures are built in the English language. Propounded by Noam Chomsky in 1965, the theory transforms sentences from an active structure to a passive one by the application of established rules of the theory. Resident in the body of syntax, the rules include movement, insertion, substitution, and deletion rules. Using the movement rule, the analysis is armed with the qualitative research method, on which the works of scholars were duly consulted for more insight and in line with the academic practice in research activities. The investigation showed that the rules of competent grammar explain the formulation of sentences in a language and how transformation takes place among sentences from a deep structure to a surface structure with accurate results. The structural differences that could be got through dative movement and the deletion of the preposition; passivisation got from an active sentence by the insertion of the preposition “by” a “be verb” and the aspect tense marker “–en”, held as the creative aspect of language vocabulary and the subject-auxiliary inversion that exchanges the auxiliary of a sentence with the subject of the same sentence thereby transforming a kennel sentence to a polar question, viewed as an external argument under θ-theory. Generativism in language design, therefore, changes available types of sentences and relates one form of linguistic category with others in language design.

Keywords: language, generate, transformation, structure, design

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Authors: Rafael Dias Silva

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The school is a social institution that should promote learning situations that remain throughout life. Based on this, the teaching activities promoted in museum spaces can represent an educational strategy that contributes to the learning process in a more meaningful way. This article systematizes a series of elements that guide the use of these spaces for the scientific literacy of deaf students and as experiences of this nature are favorable for the school development through the concept of the circularity. The methodology for the didactic use of these spaces of non-formal education is one of the reflections developed in this study and how such environments can contribute to the learning in the classroom. To develop in the student the idea of ​​association making him create connections with the curricular proposal and notice how the proposed activity is articulated. It is in our interest that the experience lived in the museum be shared collaborating for the construction of a scientific literacy and cultural identity through the research.

Keywords: accessibility in museums, Brazilian sign language, deaf students, teacher training

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Authors: Katherine O'Grady-Bray

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For some deaf children, reading books can be a challenge. Frank Barnes School (FBS) provides guided reading time with Teachers of the Deaf, in which they read books with deaf children using a bilingual approach. The vocabulary and context of the story is explained to deaf children in BSL so they develop skills bridging English and BSL languages. However, the success of this practice is only achieved if the person is fluent in both languages. FBS piloted a scheme to convert an Oxford Reading Tree (ORT) book into an e-book that can be read using tablets. Deaf readers at FBS have access to both languages (BSL and English) during lessons and outside the classroom. The pupils receive guided reading sessions with a Teacher of the Deaf every morning, these one to one sessions give pupils the opportunity to learn how to bridge both languages e.g. how to translate English to BSL and vice versa. Generally, due to our pupils’ lack of access to incidental learning, gaining new information about the world around them is limited. This highlights the importance of quality time to scaffold their language development. In some cases, there is a shortfall of parental support at home due to poor communication skills or an unawareness of how to interact with deaf children. Some families have a limited knowledge of sign language or simply don’t have the required learning environment and strategies needed for language development with deaf children. As the majority of our pupils’ preferred language is BSL we use that to teach reading and writing English. If this is not mirrored at home, there is limited opportunity for joint reading sessions. Development of the e-Book required planning and technical development. The overall production took time as video footage needed to be shot and then edited individually for each page. There were various technical considerations such as having an appropriate background colour so not to draw attention away from the signer. Appointing a signer with the required high level of BSL was essential. The language and pace of the sign language was an important consideration as it was required to match the age and reading level of the book. When translating English text to BSL, careful consideration was given to the nonlinear nature of BSL and the differences in language structure and syntax. The e-book was produced using Apple’s ‘iBook Author’ software which allowed video footage of the signer to be embedded on pages opposite the text and illustration. This enabled BSL translation of the content of the text and inferences of the story. An interpreter was used to directly ‘voice over’ the signer rather than the actual text. The aim behind the structure and layout of the e-book is to allow parents to ‘read’ with their deaf child which helps to develop both languages. From observations, the use of e-books has given pupils confidence and motivation with their reading, developing skills bridging both BSL and English languages and more effective reading time with parents.

Keywords: bilingual book, e-book, BSL and English, bilingual e-book

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Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan

Abstract:

Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.

Keywords: stream speed, urban roads, machine learning, traffic flow

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Authors: Abdelrahman Taha, Niloofar Malekghaini, Hamed Ebrahimian, Ramin Motamed

Abstract:

This paper compares the substructure and direct methods for soil-structure interaction (SSI) analysis in the time domain. In the substructure SSI method, the soil domain is replaced by a set of springs and dashpots, also referred to as the impedance function, derived through the study of the behavior of a massless rigid foundation. The impedance function is inherently frequency dependent, i.e., it varies as a function of the frequency content of the structural response. To use the frequency-dependent impedance function for time-domain SSI analysis, the impedance function is approximated at the fundamental frequency of the structure-soil system. To explore the potential limitations of the substructure modeling process, a two-dimensional reinforced concrete frame structure is modeled using substructure and direct methods in this study. The results show discrepancies between the simulated responses of the substructure and the direct approaches. To isolate the effects of higher modal responses, the same study is repeated using a harmonic input motion, in which a similar discrepancy is still observed between the substructure and direct approaches. It is concluded that the main source of discrepancy between the substructure and direct SSI approaches is likely attributed to the way the impedance functions are calculated, i.e., assuming a massless rigid foundation without considering the presence of the superstructure. Hence, a refined impedance function, considering the presence of the superstructure, shall be developed. This refined impedance function is expected to significantly improve the simulation accuracy of the substructure approach for structural systems whose behavior is dominated by the fundamental mode response.

Keywords: direct approach, impedance function, soil-structure interaction, substructure approach

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Authors: Ju May Wen, Chun Hung Lin, Eric Zhi Feng Liu

Abstract:

Flow theory implies that people are persuaded by happiness. By focusing on an activity, people turn a blind eye to external factors. This study explores the influence of educational board games and fundamental Chinese language teaching on students’ learning motivation and flow experience. Fifty-three students studying Chinese language fundamental courses were used in the study. These students were divided into three groups: (1) flash card teaching group; (2) educational original board game teaching group; and (3) educational Chinese board game teaching group. Chinese language teaching was integrated with the educational board game titled ‘Transportation GO.’ The students were observed playing this game as the teacher collected quantitative and qualitative data. Quantitative data was collected from the learning motivation scale and flow experience scale. Qualitative data was collected through observing, recording, and visiting. The first result found that the three groups integrated with Chinese language teaching could maintain students’ high learning motivation and high flow experience. Second, there was no significant difference between the flow experience of the flash card group and the educational original board game group. Third, there was a significant difference in the flow experience and learning motivation of the educational Chinese board game group vs. the other groups. This study suggests that the experimental model can be applied to advanced Chinese language teaching. Apart from oral and literacy skills, the study of educational board games integrated with Chinese language teaching to enforce student writing skills will be continued.

Keywords: Chinese language instruction, educational board game, learning motivation, flow experience

Procedia PDF Downloads 174

Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

Abstract:

Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

Procedia PDF Downloads 369

Authors: Undiyaundeye Florence Atube, Ugar Innocent A.

Abstract:

Young children are active learners who use all their senses to build concepts and ideas from their experiences. The process of learning, the content and the outcomes, is vital for young children. They need time to explore whether they are satisfied with what is learnt. Of all levels of education, early childhood education is considered to be most critical for the social, emotional, cognitive and physical development. For this reason, the teachers for early years need to play a significant role in the teaching and learning process through the provision of a friendly environment in the school. A case study approach was used in this study. The information was gathered through various methods like class observation, field notes, documents analysis, group processes, and semi structured interviews. The group processes participants and interviewees were taken from some stakeholders such as parents, students, teachers, and head teachers from public schools, to have a broad and comprehensive analysis, informal interaction with different stakeholders and self-reflection was used to clarify aspects of varying issues and findings. The teachers’ roles in developing a child friendly environment in personal capacity to learning were found to improve a pupils learning ability. Prior to early child development education, learning experiences and pedagogical content knowledge played a vital role in engaging teachers in developing their thinking and teaching practice. Children can be helped to develop independent self-control and self-reliance with careful planning and development of the child’s experience with sensitive and appropriate interaction by the educator to propel eagerness to learn through the provision of a friendly environment.

Keywords: child friendly environment, early childhood, education and development, teaching, learning and the curriculum

Procedia PDF Downloads 369