Reviewerly/exHarmony huggingface dataset:
Performance Analysis of Neural Machine Translation Models for ASL to ASL Gloss Conversion

One of the latest advancements in the domain of machine learning is the translation of sign language into a form of natural language. Numerous studies have concentrated on converting gestures or facial recognition from sign language. This study contributes by employing a deep learning technique for the conversion of English text to American Sign Language (ASL) with the help of neural machine network models. Research on Neural Machine Translation (NMT) architecture has advanced with the advent of the attention mechanism, which is based on queries and keys, the attention network determines the significance of each data vector. In this paper, experimentation is shown using sequential models on the ASLG-PC12 dataset, and Bilingual Evaluation Understudy (BLEU) scores are calculated for the examples from the dataset to evaluate model performance. Results on the ASLG-12 corpus depict that the Gated Recurrent Unit (GRU) model with Bahdanau attention delivers better results with text to gloss translation attempts.
Chaotic Maps and DCT-based Image Steganography-cum-encryption Hybrid Approach

Internet technologies make multimedia data communication easy and affordable; meanwhile, securing the secret and private information over the open network also becomes a major threat and challenge. Steganography and encryption are two approaches for securing secret information. Encryption converts the secret data into a scribbled form whereas steganography is a data embedding approach to secure the secret information. In this study, a 2D discrete cosine transform (DCT)-based image steganography-then-encryption hybrid method using chaotic map for hiding secret bits chaotically in least significant bits (n-LSBs) has been proposed. The proposed image steganography-then-encryption approach outperforms the existing techniques in terms of security, mean square error (MSE) and peak signal-to-noise ratio (PSNR). The key space of more than 10168 and correlation coefficient (>0.9) of cover with stego and with encrypted-stego image at different levels for different images make the proposed algorithm resistant to brute force attack.
An Ensemble Multimodal Fusion Using Naive Bayes Approach for Haptic Identification of Objects

Multimodal classification is gaining popularity recently in many areas including medical fields, human-computer interactions, etc. In multimodal object identification, ensemble-based techniques have been found to increase the accuracy to a great extent. This paper proposes an ensemble-based multimodal fusion using the Naive Bayes approach to improve the performance of multimodal classifiers in object identification. Here, image, acceleration and friction are used as the multimodal inputs and separate classifiers are developed for each input. Then based on a classifier’s prediction, a posterior probability measure of the expected prediction was calculated using the Naive Bayes theorem. Also, a diversity measure is determined using the class precision score of corresponding classifiers. Then, a weighted posterior probability measure was calculated such that the classifier with the maximum weighted posterior probability of prediction is chosen for the final prediction. The results showed a considerable improvement in accuracy when compared with existing techniques.
An FM-index Based High-Throughput Memory-Efficient FPGA Accelerator for Paired-end Short-read Mapping

This paper presents an Ferragina-Manzini index (FM-index) based paired-end short-read mapping hardware accelerator. Four techniques are proposed to significantly reduce the number of memory accesses and operations to improve the throughput. First, an interleaved data structure is proposed to reduce the processing time by 51.8% by leveraging the data locality. Second, the boundaries of possible mapping location candidates can be retrieved within only one memory access by constructing a lookup table along with the FM-index. This reduces the number of DRAM accesses by 60% with only a 64MB memory overhead. Third, an additional step is added to skip the time-consuming repetitive location candidates filtering conditionally, avoiding unnecessary operations. Lastly, an early termination method is proposed to terminate the mapping process if any location candidate with a high enough alignment score is detected, greatly decreasing the execution time. Overall, the computation time is reduced by 92.6% with only a 2% memory overhead in DRAM. The proposed methods are realized on a Xilinx Alveo U250 FPGA. The proposed FPGA accelerator processes 1,085,812,766 short-reads from the U.S. Food and Drug Administration (FDA) dataset within 35.4 minutes at 200MHz. It achieves a 1.7-to-18.6× higher throughput and the highest 99.3% accuracy by exploiting the paired-end short-read mapping, compared to state-of-the-art FPGA-based designs.
Evaluating LightGBM Classifier for Knowledge Tracing on EdNet Dataset

Knowledge tracing is critical in educational data mining to accurately predict student performance and knowledge in future interactions. In this study, we utilized the EdNet dataset to implement different classifiers and evaluate their performance in knowledge tracing. We found that the LightGBM classifier outperformed other classifiers, achieving the highest accuracy of 0.723 on the test set. Furthermore, we applied three ensemble methods, including boosting, bagging, and stacking, to investigate if they could further improve the performance of the LightGBM classifier. Our experimental results showed that the stacking method provided the most significant improvement, while the bagging and boosting methods did not yield significant improvements. These findings suggest that the LightGBM classifier, combined with the boosting method, can be an effective approach for knowledge tracing and have potential practical applications in education.
Detecting Academic Fraud at Online Tests During COVID-19 Using Machine Learning-Based Methods

The first step in eliminating academic dishonesty (in e-learning systems) is to detect fraudulent activities. There are various approaches that deal with this problem, but only few of them are based on human-computer interaction (HCI). Accordingly, we have developed a novel data acquisition model that collects information about student HCI activities. This model was applied within an open-source module, named Student Activity Tracker, available as chromium web browser extension. During the COVID-19 pandemic (in academic year of 2019/2020.), an experiment was conducted with 54 volunteer participants that performed online tests from home. As a result, 500k raw logs were collected and later processed and used to develop four machine learning models. The main contribution of this research is the proof of an obvious correlation between HCI activities and fraudulent behaviour even on such a small sample. Also, we believe that this module can help other researchers to create new data sets and build new more advanced models.
A Modular Framework for Modelling and Verification of Activities in Ambient Intelligent Systems

There is a growing need to introduce and develop formal techniques for computational models capable of faithfully modelling systems of high complexity and concurrent. Such systems are the ambient intelligent systems. This article proposes an efficient framework for the automated modelling and verification of the behavioural models capturing daily activities that occur in ambient intelligent systems based on the modularity and compositionality of Petri nets. This framework consists of different stages that incorporate Petri net techniques like composition, transformation, unfolding and slicing. All these techniques facilitate the modelling and verification of the system activities under consideration by allowing the modelling in different Petri net classes and the verification of the produced models either by using model checking directly or by applying Petri net slicing to alleviate the state explosion problem that may emerge in very complex behavioural models. Illustrative examples of ambient intelligent system applied to health and other sectors are provided to demonstrate the practicality and effectiveness of the proposed approach. Finally, to show the flexibility of the proposed framework in terms of verification, both an evaluation and comparison of the state space required for the property checking are conducted with respect to the typical model checking and slicing approach respectively.
The curriculum in action: Digital technologies – computational thinking

Technologies for Children is a comprehensive guide to teaching design and digital technologies to children from birth to 12 years. Aligned with the Early Years Learning Framework and the Australian Curriculum: Technologies, this book provides practical ideas for teaching infants, toddlers, pre-schoolers and primary-aged children. The third edition includes expanded content on teaching digital technologies, with a new chapter on computational thinking. Key topics covered include food and fibre production, engineering principles and systems, and computational thinking. The content goes beyond discussing the curriculum to consider technology pedagogies, planning, assessment and evaluation. Case studies drawn from Australian primary classrooms and early childhood centres demonstrate the transition from theory to practice. Each chapter is supported by pedagogical reflections, research activities and spotlights, as well as extensive online student resources. Written by Marilyn Fleer, this book presents innovative, engaging and student-centred approaches to integrating technologies in the classroom.
What is technologies education?

Technologies for Children is a comprehensive guide to teaching design and digital technologies to children from birth to 12 years. Aligned with the Early Years Learning Framework and the Australian Curriculum: Technologies, this book provides practical ideas for teaching infants, toddlers, pre-schoolers and primary-aged children. The third edition includes expanded content on teaching digital technologies, with a new chapter on computational thinking. Key topics covered include food and fibre production, engineering principles and systems, and computational thinking. The content goes beyond discussing the curriculum to consider technology pedagogies, planning, assessment and evaluation. Case studies drawn from Australian primary classrooms and early childhood centres demonstrate the transition from theory to practice. Each chapter is supported by pedagogical reflections, research activities and spotlights, as well as extensive online student resources. Written by Marilyn Fleer, this book presents innovative, engaging and student-centred approaches to integrating technologies in the classroom.
Key ideas in the technologies curriculum

Technologies for Children is a comprehensive guide to teaching design and digital technologies to children from birth to 12 years. Aligned with the Early Years Learning Framework and the Australian Curriculum: Technologies, this book provides practical ideas for teaching infants, toddlers, pre-schoolers and primary-aged children. The third edition includes expanded content on teaching digital technologies, with a new chapter on computational thinking. Key topics covered include food and fibre production, engineering principles and systems, and computational thinking. The content goes beyond discussing the curriculum to consider technology pedagogies, planning, assessment and evaluation. Case studies drawn from Australian primary classrooms and early childhood centres demonstrate the transition from theory to practice. Each chapter is supported by pedagogical reflections, research activities and spotlights, as well as extensive online student resources. Written by Marilyn Fleer, this book presents innovative, engaging and student-centred approaches to integrating technologies in the classroom.
References

Technologies for Children is a comprehensive guide to teaching design and digital technologies to children from birth to 12 years. Aligned with the Early Years Learning Framework and the Australian Curriculum: Technologies, this book provides practical ideas for teaching infants, toddlers, pre-schoolers and primary-aged children. The third edition includes expanded content on teaching digital technologies, with a new chapter on computational thinking. Key topics covered include food and fibre production, engineering principles and systems, and computational thinking. The content goes beyond discussing the curriculum to consider technology pedagogies, planning, assessment and evaluation. Case studies drawn from Australian primary classrooms and early childhood centres demonstrate the transition from theory to practice. Each chapter is supported by pedagogical reflections, research activities and spotlights, as well as extensive online student resources. Written by Marilyn Fleer, this book presents innovative, engaging and student-centred approaches to integrating technologies in the classroom.
Detecting Anomalies in Simulated Nuclear Data Using Autoencoders

Concerns over cybersecurity in critical systems have grown significantly over the last decade. The increase in the successful attacks against infrastructure, major corporations, and governments has led to major investment in mitigating and preventing cyberattacks. At the same time, there has been a significant interest in utilizing data in operations, with machine learning applications becoming a popular area of study. One industry exploring machine learning applications is the nuclear industry. Because of the sensitive nature of nuclear systems, the question if attacks on nuclear data can be detected has begun to take urgency. This study explores the use of autoencoders to detect anomalies in nuclear data that could be potentially used to evaluate the operating status of a nuclear system. Data from a generic pressurized water reactor simulator used in a previous study to diagnose transients was used to train an autoencoder model using Keras. A separate portion of these data was altered by adding statistical noise for validation. Four different levels of noise were used in this experiment. Once the autoencoder was trained, a threshold was calculated using the average mean square error of the predictions and the standard deviation from that loss. Points above the threshold were classified as anomalies while points below were considered unaltered. For the initial level of noise, the model was able to score near perfect in recall, capturing all but 13 of the 13 884 altered points. However, in terms of precision, the model misclassified a number of unaltered points as altered, resulting in a score of 73.76%. To test the sensitivity of the model, the amount of noise was reduced three times, and as expected, the performance of the model worsened with each reduction. Still, the high performance in identifying altered points for higher levels of noise is an encouraging first step in developing anomaly detection systems for nuclear data.
PROFESSIONAL DEVELOPMENT AND CREATING CHANGE OF TEACHING BY TAKING PART IN A COURSE IN DIGITAL PEDAGOGY AND DIDACTICS

PROFESSIONAL DEVELOPMENT AND CREATING CHANGE OF TEACHING BY TAKING PART IN A COURSE IN DIGITAL PEDAGOGY AND DIDACTICS
ICT IN CHILDREN'S COMPULSORY PRE-SCHOOL EDUCATION

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 2334-2338ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.0683Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
PODCAST AS E-LEARNING METHODOLOGY IN FOOD SCIENCE AND NUTRITION AT UNIVERSITY LEVEL

R.M. CámaraM. CámaraM.C. MatallanaM.C. Sánchez-MataV. Fernández-RuizP. MoralesP. García-HerreraE. ArranzS. Fernández-ToméM. Ciudad-MuleroL. DomínguezE.N. VegaC. Tamayo-VivesT. Jaramillo
COMPETITIONS AS REQUIRED ASSESSMENTS IN CYBER SECURITY EDUCATION

Appears in: EDULEARN23 Proceedings Publication year: 2023Page: 2252 (abstract only)ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.0663Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
SEEING THE INVISIBLE: INCLUSIVE DIGITALIZATION OF LOW VISION STUDENTS IN SCHOOL EDUCATION

R. Navarro Cerveró1R. Sixto Iglesias1P. Carrolaggi2S. Randaccio3L. Pietra3C. Zoli3T. Hauge4S. Orstenvik4M. Castelnuovo5B. Poli6C. Teofili5M. Pellegrino5G. Gening6L. Mosquera6O. Simerea6M. Rafecas6M. Puerto7
PEDAGOGY IN DIGITAL AGE AFTER THE COVID-19 PANDEMIC – A CASE STUDY WITH UNDERGRADUATE LIFE SCIENCE STUDENTS

PEDAGOGY IN DIGITAL AGE AFTER THE COVID-19 PANDEMIC – A CASE STUDY WITH UNDERGRADUATE LIFE SCIENCE STUDENTS
PUTTING THE PIECES TOGETHER: COMBINING INTERDEPENDENT SUPPORT STRUCTURES FOR FOSTERING DIGITAL COMPETENCIES OF PRE-SERVICE TEACHERS IN A PROJECT-BASED APPROACH

PUTTING THE PIECES TOGETHER: COMBINING INTERDEPENDENT SUPPORT STRUCTURES FOR FOSTERING DIGITAL COMPETENCIES OF PRE-SERVICE TEACHERS IN A PROJECT-BASED APPROACH
THE PARADOXICAL LIFE OF ANDRAGOGUES

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 1378-1386ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.0438Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
A SERVICE-LEARNING EXPERIENCE FOR FIGHTING FAKE NEWS ABOUT FOOD AND NUTRITION

M.C. Sánchez MataM. CámaraM.C. MatallanaM.L. Pérez RodríguezV. Fernández-RuizP. MoralesP. García-HerreraE. ArranzS. Fernández-ToméR.M. CámaraM. Ciudad-MuleroL. DomínguezE.N. VegaC. Tamayo-VivesL. González-Zamorano
A Comparative Analysis between the Construction ‘S+Shi+V+De+O’ and the Construction ‘S+Shi+V+O+De’

This paper analyzed the construction ‘S+Shi(是)+V+De(的)+O’ and the construction ‘S+Shi(是)+V+O+De(的)’. The analysis results are as follows. First, the state situation type verbs cannot appear in the construction ‘S+Shi (是)+V+De(的)+O’, but can appear in the construction ‘S+Shi(是)+V+O+De (的)’. When the state verb appears in the construction ‘S+Shi(是)+V+O+De (的)’, it functions as a verum-focus structure. Second, activity situation type verbs with strong durative property cannot appear in the construction ‘S+Shi (是)+V+De(的)+O’, but can appear in the construction ‘S+Shi(是)+V+O+De (的)’. When a strong durative verb appears in the construction ‘S+Shi (是)+V+O+De(的)’, it is interpreted as a nominalized sentence and functions as a predicate-focus structure. Next, when a less durative verb appears in the construction ‘S+Shi(是)+V+De(的)+O’, the tense of the sentence is interpreted as the past and functions as an argument-focus structure. And, a less durative verb generally cannot appear in the construction ‘S+Shi(是)+V+O+De(的)’, but can appear when S is a generic noun phrase, and in this case, the tense of the sentence is interpreted as the present and functions as a predicate-focus structure. In the case of semelfactive situation type verbs, they can appear in the construction ‘S+Shi(是)+V+De(的)+O’, but cannot appear in the construction ‘S+Shi(是)+V+O+De(的)’. In addition, when the semelfactive verbs appear in the construction ‘S+Shi(是)+V+De(的)+O’, the tense of the sentence is interpreted as the past and functions as an argument-focus structure. Third, acomplishment and achievment situation type verbs can appear in construction ‘S+Shi(是)+V+De(的)+O’, but cannot appear in the construction ‘S+Shi(是)+V+O+De(的)’. And, when two types of verbs appear in the construction ‘S+Shi(是)+V+De(的)+O’, the tense of the sentence is always interpreted as the past and functions as an argument-focus structure.
Case Analysis and Suggestions for the Development of Digital Textbooks for University Chinese Subjects

This paper mentioned the necessity of developing digital textbooks for university Chinese subjects and presented digital textbook types and development plans suitable for university Chinese subjects based on the cases and characteristics of digital textbooks. Digital textbooks refer to textbooks developed to enable learning based on digital devices, including related digital learning materials and learning support functions, in addition to existing e-books. Representative examples of digital textbooks used in Korea can be seen as digital textbooks currently used in elementary, middle, and high schools. The development and use of digital textbooks in elementary and secondary education is a global trend, and the digitization of elementary and secondary education textbooks is expected to cause the digitization of university textbooks in the near future. Except for digital textbooks in elementary, middle, and high schools, digital textbooks are largely divided into two types. There is a method of requesting the production of digital textbooks to a developer based on book-type textbooks, and a method of making digital textbooks directly by instructors through an online platform. In the case of classes where the instructor’s subject continuity is guaranteed, the number of students or classes is small, and all students can use digital textbooks, the instructor can directly create digital textbooks suitable for the subject through the platform and provide them to students. On the other hand, if the continuity of the instructor’s subject is not guaranteed and several classes are taught with the same textbook, it is safe and efficient to use digital textbooks provided by developers based on book-type textbooks. For each Chinese subject at each university, it is necessary to select a development type suitable for the characteristics of each subject.
REALIZATION OF ADAPTIVE PROGRESS BARS IN MOODLE FOR ATTESTED COMPETENCIES AND QUALIFICATIONS FOR LEARNERS IN HIGHER EDUCATION INSTITUTIONS PSYCHOLOGY COURSES CONSIDERING QUALIFICATIONS-BASED LEARNING

REALIZATION OF ADAPTIVE PROGRESS BARS IN MOODLE FOR ATTESTED COMPETENCIES AND QUALIFICATIONS FOR LEARNERS IN HIGHER EDUCATION INSTITUTIONS PSYCHOLOGY COURSES CONSIDERING QUALIFICATIONS-BASED LEARNING
HOW AND WHY DOES THE DEMAND OF AN EXAM QUESTION CHANGE IF WE MANIPULATE IT SO IT CAN BE AUTO-MARKED?

Appears in: EDULEARN23 Proceedings Publication year: 2023Page: 2798 (abstract only)ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.0795Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain