Reviewerly/exHarmony huggingface dataset:
Developing the communicative competence of future cultural sector specialists when designing and applying didactic web-quests

The problem and the purpose. The formation of demanded professional competencies in the training of cultural workers involves the use of various didactic technologies, including game services and platforms. The purpose of the study is to identify the features of the use of a web-quest as a game technology when training future cultural specialists to develop their communicative competence. Research methods. The methodology is based on the analysis of the potential of web-quest technology for higher education, support for UNESCO initiatives and public policy. When developing a series of problems the socio-cultural space of the quest takes into account the requirements of the digital society, the possibilities of software resources in accordance with the profession specifics and the needs of the students themselves. The platform Joyteka.com is used, which allows the user to create web-quests, quizzes, tests. 58 students of the Vyatka State University are involved (Russian Federation). Web-quests are included in the disciplines "Modern Information Technologies", "The Russian Language and Culture of Speech", "History of Culture", "History of the Vyatka Region", in individual practice tasks. The authors used the method of assessing communication and organizational tendencies. The bases for practice: museums of the city and region, houses of culture, exhibition centers. Statistical data processing was performed by means of Pearson's χ2 (chi-square) test. Results. The development and application of web-quests in the experimental group was carried out in the following stages: analysis of the community demand, the possibilities of software resources in accordance with the profession specifics and socio-cultural activities; the use of digital service; thinking over the plot component and routes of movement of participants; drawing up a plan of dialogues between characters, etc. Statistically significant differences were revealed in the qualitative changes that occurred in the pedagogical system (χ2 = 10.693; p &lt; 0.05). Conclusion presents deductions about the features of applying the web-quest to develop the communicative competence: the necessity to search for information for the plot and the place of implementation of the webquest; designation of characters and dialogues between them; the study of interactive features of the service; the compilation of texts for cards with tasks; the choice of musical accompaniment, etc. The difficulties of the proposed innovations are formulated: the creative nature of the activity when designing the sociocultural plot and the content of the game space; dependence on software in cultural institutions; technical failures of equipment; difficulties in forming and functioning of teams.
An Interactive Web Solution for Electronic Health Records Segmentation and Prediction

A vast variety of patient data has been collected and monitored through Electronic Health Records (EHR) using various tools in the healthcare. The objective of the paper is to start data acquisition and data understanding and then create a web interface for data exploration and segmentation and classification. In the data modeling phase, the objective is to create machine learning models for segmentation and classification. The first step is data acquisition from the MIMIC-III v1.4 (Clinical database) data mart. In the data understanding phase, the relationship of multiple tables is evaluated. After data wrangling the combined dataset is then used for k-means clustering techniques for obtaining chest heart failure patients clusters. In the following phase, the diagnosis text data is used for data modeling and for that various text features are created and then multiple classification techniques are applied for predicting the occurrences of death and the best model is considered for the model deployment. In the model evaluation phase, it is observed that six clusters were optimal while training the model and it is incorporated into the application for predicting the segments of the patients based on the risk levels. Few machine learning models were trained on patient’s historic diagnosis text data and the logistic regression model indicated 89% of AUC score in test data and is deployed into the application for the prediction.
Self-Attention-Based Convolutional GRU for Enhancement of Adversarial Speech Examples

Recent research has identified adversarial examples which are the challenges to DNN-based ASR systems. In this paper, we propose a new model based on Convolutional GRU and Self-attention U-Net called [Formula: see text] to improve adversarial speech signals. To represent the correlation between neighboring noisy speech frames, a two-Layer GRU is added in the bottleneck of U-Net and an attention gate is inserted in up-sampling units to increase the adversarial stability. The goal of using GRU is to combine the weights sharing technique with the use of gates to control the flow of data across multiple feature maps. As a result, it outperforms the original 1D convolution used in [Formula: see text]. Especially, the performance of the model is evaluated by explainable speech recognition metrics and its performance is analyzed by the improved adversarial training. We used adversarial audio attacks to perform experiments on automatic speech recognition (ASR). We saw (i) the robustness of ASR models which are based on DNN can be improved using the temporal features grasped by the attention-based GRU network; (ii) through adversarial training, including some additive adversarial data augmentation, we could improve the generalization power of Automatic Speech Recognition models which are based on DNN. The word-error-rate (WER) metric confirmed that the enhancement capabilities are better than the state-of-the-art [Formula: see text]. The reason for this enhancement is the ability of GRU units to extract global information within the feature maps. Based on the conducted experiments, the proposed [Formula: see text] increases the score of Speech Transmission Index (STI), Perceptual Evaluation of Speech Quality (PESQ), and the Short-term Objective Intelligibility (STOI) with adversarial speech examples in speech enhancement.
TERTIARY TEACHERS’ REFLECTION ON ONLINE TEACHING IN AUSTRIA

1 Prague City University (CZECH REPUBLIC)2 Faculty of Management, Comenius University Bratislava (SLOVAKIA)3 Faculty of Education, University of Ostrava (CZECH REPUBLIC)
MERLIN’S PLAYGROUND: STUDENTS' ATTITUDES AND PERCEPTIONS OF SOLVING ELECTROMAGNETISM PROBLEMS IN A VIRTUAL REALITY ENVIRONMENT

MERLIN’S PLAYGROUND: STUDENTS' ATTITUDES AND PERCEPTIONS OF SOLVING ELECTROMAGNETISM PROBLEMS IN A VIRTUAL REALITY ENVIRONMENT
PERCEPTION AND ATTITUDES TOWARD EMERGING TECHNOLOGY OF BIOMETRICS AMONG CROATIAN STUDENTS

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 1140-1143ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.0388Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
TRENDS IN CHILDREN'S INDEPENDENT READING AND MOTIVATION: THE CONTEXT OF PEDAGOGUES' OPINIONS

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 8349-8356ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.2161Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
LET’S LEARN WITH ASTROEDU!

Appears in: EDULEARN23 Proceedings Publication year: 2023Page: 3412 (abstract only)ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.0933Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
HOW HAVING KNOWLEDGE OF POSITIVE INTELLIGENCE CAN HELP STUDENTS REACH THEIR FULL POTENTIAL: A STUDENT - ATHLETE PERSPECTIVE AT THE UNIVERSITY OF THE DISTRICT OF COLUMBIA

HOW HAVING KNOWLEDGE OF POSITIVE INTELLIGENCE CAN HELP STUDENTS REACH THEIR FULL POTENTIAL: A STUDENT - ATHLETE PERSPECTIVE AT THE UNIVERSITY OF THE DISTRICT OF COLUMBIA
RESILIENCE FOR INNOVATION PROJECTS IN THE EDUCATION SECTOR

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 6460-6469ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.1713Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
SIMPLE REGISTER TRANSFER SIMULATOR FOR TEACHING COMPUTER ARCHITECTURE

1 Slovak Academy of Sciences (SLOVAKIA)2 University of Technology, Faculty of Informatics and Information Technologies (SLOVAKIA)
MODERNIZATION OF THE EDUCATIONAL PROCESS IN THE MATHEMATICS STUDY PROGRAM USING GRAPHIC DIGITAL TECHNOLOGIES

MODERNIZATION OF THE EDUCATIONAL PROCESS IN THE MATHEMATICS STUDY PROGRAM USING GRAPHIC DIGITAL TECHNOLOGIES
ANALYSIS OF TEACHERS' MANUSCRIPTS ABOUT SCHOOL LIFE STORED IN THE ARCHIVE OF THE DEPARTMENT OF ETHNOLOGY, CROATIAN ACADEMY OF SCIENCES AND ARTS

ANALYSIS OF TEACHERS' MANUSCRIPTS ABOUT SCHOOL LIFE STORED IN THE ARCHIVE OF THE DEPARTMENT OF ETHNOLOGY, CROATIAN ACADEMY OF SCIENCES AND ARTS
TEACHER REQUIREMENTS FOR A WEBSITE PROVIDING EDUCATIONAL MATERIAL ON INLAND WATERWAY TRANSPORT: EVALUATION USING A USER-CENTERED DESIGN PROCESS

TEACHER REQUIREMENTS FOR A WEBSITE PROVIDING EDUCATIONAL MATERIAL ON INLAND WATERWAY TRANSPORT: EVALUATION USING A USER-CENTERED DESIGN PROCESS
AN AUTOMATIZED QUALITY ASSESSMENT SYSTEM BASED ON A NATURAL LANGUAGE INTERFACE FOR EXTRACTION AND PROCESSING OF RAW DATA OF THE EDUCATIONAL SYSTEM

AN AUTOMATIZED QUALITY ASSESSMENT SYSTEM BASED ON A NATURAL LANGUAGE INTERFACE FOR EXTRACTION AND PROCESSING OF RAW DATA OF THE EDUCATIONAL SYSTEM
BADGES - THE POSSIBILITY OF INCREASING MOTIVATION IN THE EDUCATIONAL PROCESS

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 4175-4179ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.1113Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
SUSTAINABLE EDUCATION MODEL FOR HUMANOID ROBOT INTEGRATION IN EDUCATIONAL PROCESS

1 Faculty of Natural Sciences and Mathematics, University of Maribor (SLOVENIA)2 Faculty of Education, University of Maribor (SLOVENIA)
WHAT HAPPENS WHEN A USER FIRST ENTERS AN ONLINE ASYNCHRONOUS LEARNING COURSE AND HOW TO DESIGN A USER-FRIENDLY ENTRY SPACE

WHAT HAPPENS WHEN A USER FIRST ENTERS AN ONLINE ASYNCHRONOUS LEARNING COURSE AND HOW TO DESIGN A USER-FRIENDLY ENTRY SPACE
FACTORS INFLUENCING EMPLOYABILITY OF NEETS 25+ IN SELECTED EUROPEAN COUNTRIES

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 5424-5428ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.1425Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
BUILDING CIRCUITS FROM SCRATCH

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 7907-7912ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.2053Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
HYPERTEXT IN EDUCATION: A 40-YEAR HISTORY

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 7182-7190ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.1883Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
AN INTERGENERATIONAL PERSPECTIVE ON GAMIFICATION IN EDUCATION AND RESEARCH

1 Centrul IT pentru Stiinta si Tehnologie, University Politehnica of Bucharest, (ROMANIA)2 Ana Aslan International Foundation (ROMANIA)3 Centrul IT pentru Stiinta si Tehnologie (ROMANIA)
EXPERIENCES IN EDUCATION: UNDERSTANDING THE ROLE OF PSYCHOMETRIC TESTING TO PREDICT OUTCOMES OF ADULT LEARNERS RETURNING TO EDUCATION ON GOVERNMENT FUNDED RESKILLING INITIATIVES

EXPERIENCES IN EDUCATION: UNDERSTANDING THE ROLE OF PSYCHOMETRIC TESTING TO PREDICT OUTCOMES OF ADULT LEARNERS RETURNING TO EDUCATION ON GOVERNMENT FUNDED RESKILLING INITIATIVES
MODELLING THE PROCESS OF IMPROVING THE ACTIVITY OF THE OFFICE OF DOCTORAL STUDIES IN UNIVERSITY

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 5155-5162ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.1351Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
WHAT HAS CHANGED? AN INSIGHT ON COMMUNIST’S YOUTH PERSPECTIVE ON EDUCATION

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 8591-8597ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.1450Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
An effective digital image watermarking scheme incorporating DCT, DFT and SVD transformations

Image watermarking prevents copyright infringements by attaching visible/invisible watermark images as authentication identities in the owner’s documents. The article made analysis on the advantages of different transformations for choosing better combinations to make the watermark embedding process and observed that watermarking techniques incorporating discrete cosine transform (DCT) provide better resistance towards JPEG based potential attacks, discrete Fourier transform (DFT) has strong energy compaction with geometrical invariance properties to resist geometric attacks while singular value decomposition (SVD) provides stability, proportion invariance and rotation invariance properties and it provides strong resistance against noise based attacks. Considering these advantages of different transformations, the article presents a new non-blind watermarking algorithm by utilizing advantages of DFT, DCT and SVD transforms while attaching secret contents in cover images. The algorithm starts by applying DFT followed by onion peel decomposition (OPD) for decomposing Fourier domain carrier image to four frequency sub images. The scheme then applies DCT on the frequency bands and orders them in zigzag fashion to form four individual frequency arrays. In the final step of embedding process, it embeds four copies of watermark singular value contents in DFT domain with the carrier image singular value contents to produce the watermarked image. The experimental results based on subjective and objective metrics on various test images from standard image databases with different test conditions demarcate the stability of new algorithm in producing high quality watermarked images with fewer distortions even when the watermarked images are extremely distorted by potential attacks.
ANALISIS BUTIR SOAL USBN MATA PELAJARAN BAHASA INDONESIA DI SMA KABUPATEN ACEH BARAT

This study aims to find out the validity, reliability, difficulty level, differentiation, and function item problem of USBN casting in Bahasa Indonesia subjects at SMA Aceh Barat. The approach in this study is a quantitative approach. This research uses a type of quantitative descriptive research. The sample of this study amounted to 5 schools and this research data is 40 question from the answer sheet of 50 students in each school. Data collection techniques with document studies. The data analysis techniques in this study used the AnatesV4.02 program. Analysis of problem items with a computer is a quantitative review of the question item whose calculations use the anates V4.02 application. The results of this study showed that the validity of USBN problems in Bahasa Indonesia subjects at SMA Aceh Barat district obtained 74valid questions with a validity level of 0.32-0.40 and 126 invalid questions with a degree of invalidity of 0.20. This invalidity is caused by the inaccuracy of explanation of each material by the teacher in the school so that students are unable to understand about the essence of the sentence. Reliability of USBN subjects in Bahasa Indonesia at SMA West Aceh district shows 0.61-0.73 in high reliability category. High school that gained the low reliability category was SMA Woyla of value 0.31. This is because the low understanding of students so as to cause problems classified in is very difficult. The difficulty level of USBN problems in Bahasa Indonesia subjects in SMA Kabupaten Aceh Barat can be seen from the difficulty index between 0.00 to 1.0. The degree of difficulty that dominates the difficulty level in each question studied is in the moderate category. The difficulty of this medium problem is influenced by the inaccuracy of the material provided by the teacher so that the student is not able to understand it completely. In addition, the question that is used as an evaluation is born from materials that are not taught by the teacher. The differentiation of USBN subjects in Bahasa Indonesia at SMA Aceh Barat district shows the percentage value includes a very good differentiation question 2 questions, good 56 questions, enough 71, and bad 71 questions. A series of differentiating power quality levels of this question appears that the differentiation of problems with very good quality is less compared to the quality of the differentiation of the problem with the category of good, sufficient, and bad. This quality difference because each question does not go through a validation and reliable process so as to have an effect on the differentiating power of each question. The casting function of USBN subjects in Bahasa Indonesia at SMA Aceh Barat consists of five levels including very good
Combining attention mechanism and Feature Selection Module for Real-time semantic segmentation

Existing semantic segmentation neural networks require a large amount of floating-point operations and have long running times, and the computational power of current mobile devices is still insufficient compared to laboratory conditions. To address this issue, this paper proposes a semantic segmentation algorithm based on multiple activation functions and feature extraction modules. Firstly, ELU is used to replace the RELU of the main network, which provides more accurate and effective feature extraction for important features of input images, making subsequent classification tasks more efficient. Then, a feature extraction module with an added attention mechanism is introduced to enhance the spatial and channel information of important feature maps containing too many details, while reducing redundant feature maps. Experimental results show that the proposed algorithm achieves an average intersection-over-union (mIoU) of 78.55% on the Cityscapes test set with a resolution input of 1024×2048, while the parameter count is only 3.24M and GFLOPs are only 38.35.
Improve pixel-wise structured light system calibration method

Our previously proposed pixel-wise structured light system calibration method works well within a depth range. Yet, it is difficult to be employed for large depth range calibration because making a calibration target to achieve high-calibration accuracy is non-trivial. This paper discusses two possible means to address this challenge, adapting the standard feature detection algorithm and employ another step to create pixel-wise error functions by measuring a flat surface. Experimental results demonstrate that either method could further improve measurement accuracy of the pixel-wise calibration method, especially for large depth range measurements.
Exploring Wordle- Based on Improved Machine Learning Models

This paper presents three models for predicting, classifying, and evaluating game data, which is collected from Wordle's Twitter account. Model I is a predictive model based on an improved LSTM algorithm that uses Sliding window to improve accuracy. By using short-term predictions, the training set is updated, reducing long-term uncertainty. Model II is a predictive distribution model based on PLS and MLP algorithms, PLS algorithm is used to predict the linear part, while the MLP algorithm compensates for the deficiency in the nonlinear part. Model III is a K-means classification model that uses the elbow rule to determine the K-value of 2, which divides games into two categories: Hard Type and Easy Type. The difficulty assessment value determines which category a game falls into. The results from this study demonstrate the effectiveness and accuracy of the proposed models in analyzing complex and variable data and provide insights into the correlation between different game attributes and their impact on game difficulty.
VeriBench: Analyzing the Performance of Database Systems with Verifiability

Database systems are paying more attention to data security in recent years. Immutable systems such as blockchains, verifiable databases, and ledger databases are equipped with various verifiability mechanisms to protect data. Such systems often adopt different threat models, and techniques, therefore, have different performance implications compared to traditional database systems. So far, there is no uniform benchmarking tool for evaluating the performance of these systems, especially at the level of verification functions. In this paper, we first survey the design space of the verifiability-enabled database systems along five dimensions: threat model, authenticated data structure (ADS), query processing, verification, and auditing. Based on this survey, we design and implement VeriBench, a benchmark framework for verifiability-enabled database systems. VeriBench enables a fair comparison of systems designed with different underlying technologies that share the client-side verification scheme, and focuses on design space exploration to provide a deeper understanding of different system design choices. VeriBench incorporates micro- and macro-benchmarks to provide a comprehensive evaluation. Further, VeriBench is designed to enable easy extension for benchmarking new systems and workloads. We run VeriBench to conduct a comprehensive analysis of state-of-the-art systems comprising blockchains, ledger databases, and log transparency technologies. The results expose the weaknesses and strengths of each underlying design choice, and the insights should serve as guidance for future development.
A Bit of History

It seems appropriate to place the official birth of Underwater Acoustics at the year 1826, when the Swiss physicist Jean-Daniel Colladon performed a memorable experiment at Lake Geneva: at night, and in the company of the French mathematician Jacques Charles François Sturm, which was on another boat at a distance of 10 km, Colladon repeatedly knocked on a bell located underwater; at the same time he could also produce a brilliant spark by igniting a small amount of powder.
Applying Machine Learning for American Sign Language Recognition: A Brief Survey

Sign languages play a crucial role in enabling differently-abled people to communicate and express their feelings. The advent of newer technologies in machine learning and sensors has led us to build more sophisticated and complex human-computer interfaces. However, a cost-effective commercial sign language recognition system is still not available. In this paper, we have highlighted recent advancements and limitations related to sign language recognition systems. We have focused our study on American sign language (ASL), which is one of the most widely used sign languages. We have tried to classify most of the surveyed work into two broad areas based on data acquisition techniques: visual and sensor-based approaches. We have also listed publicly available datasets that could be used for further research. This paper aims to provide a clear insight into advancement in the field of sign language recognition systems using American sign language.