Reviewerly/exHarmony huggingface dataset:
Assessment of Digital Capabilities among Nursing Students in UAE: A Quantitative Study

Background: Digitalization is emerging prominently in all educational environments across the globe.Accordingly, it is crucial to assess the level of digital capabilities among nursing students to be able to provide those students with the necessary support to succeed in the future of digital health.Therefore, we argue that digital literacy cannot be ignored and should be embedded in undergraduate nursing curriculum to empower students to be fully engaged in the future of digital health.Objectives: The aim of this study was to assess the level of digital capabilities among nursing students.Methods: The study was a quantitative study with cross-sectional design.200 students were recruited using a systematic random proportionate sampling technique at Nursing Colleges, United Arab Emirates.Data were collected using a structured self-administered questionnaire Digital Capabilities and Self-efficacy.Univariate analysis, Mann-Whitney U, and Kruskal-Wallis H were used for data analysis according to the type and distribution of data.Results: Superior results are seen for digital learning and development, in which participating nursing students seem competent in everyday digital literacy such as accessing learning resources.The students are competent in using the technology to complete assignments and conduct online tests, but they scored low on using the tools to search the databases effectively and have to skills to take advantage.There was no significant difference between students' level of study, parents' education, the type of devices used by the students, and their digital literacy skills.This present study reports that the digital literacy skills among nursing students in urban and rural regions differ significantly.Conclusion: Overall, students did not report any problem being involved in a digital educational environment because they are already engaged with technologies in their personal life
TECNOLOGIAS, NOVAS METODOLOGIAS, CURRÍCULO E INTERATIVIDADE: UM RELATO DE EXPERIÊNCIA EDUCACIONAL INOVADORA NO PERÍODO DA PANDEMIA

The present study is based on the literature review and aims to address references to 21st century education.We will deal with the principles that guide 21st century education, such as skills that this education aims to achieve, the basic ideals that it defends as a contemporary model.Explaining 21st century education will also address digital culture in the society in which we are inserted and how it influences the school life of our students, with the help of Digital Information and Communication Technologies (TDIC).The research also proposes to present online collaborative tools that help in the teaching-learning process, with emphasis on the tools: Blog, Coogle, Google Classroom, Padlet.Ultimately, 21st century education will help achieve what can be achieved in the 21st century.Finally, the student of this century, surrounded by technologies, needs a dynamic class to provide opportunities for their learning.
DATAVAULTS APP: PERSONAL DATA PLATFORM IN THE SMART CITIES DOMAIN AND ITS POTENTIAL INTEGRATION INTO IDS ARCHITECTURES (INTERNATIONAL DATA SPACE)

Current data sharing architectures, like International Data Space – IDS, still lack maturity and certain requirements or functionalities that prevent them from being complete solutions when it comes to implementing intelligent, exploitable, secure, and reliable data spaces on which to develop a healthy data economy. One of these main shortcomings is the treatment of personal data and it is that these reference models are highly oriented to guarantee the sovereignty of the data for industrial data, and therefore the access control and exploitation of personal data is out of their scope, forgetting the exceptional privacy and usage conditions that must be considered in this type of data. In this paper we present the DataVaults project, and the platform implemented to allow the discovery of this kind of data and at the same time, control that only those who have been specified by the owner user have access and under the terms that he has previously established. Our approach allows the exchange of information not to be limited to industrial or business domains, where sharing is focused only on impersonal industrial data. The validation will be carried out in cases of use started in Smart Cities for the treatment of data and decision-making of citizens. Key Words: Data sharing, International Data Spaces, personal data privacy, access and usage control.
Analisis Tingkat Penerimaan Mahasiswa Terhadap SIAM Poltekkes Kemenkes Riau Menggunakan TAM dan Webqual

The Riau Ministry of Health Poltekkes is a vocational tertiary institution in the Riau province health sector that has implemented a Student Academic Information System (SIAM) that supports management in the academic section, as well as a means of information and communication. But in its implementation there are still some problems, for example errors in several menus in SIAM, there is no interaction between admin staff and students as SIAM users, features that are not yet optimal in SIAM, and information on SIAM is not updated. This study aims to determine the level of student acceptance of SIAM Poltekkes Riau Ministry of Health using the Technology Acceptance Model (TAM) and Webqual methods and provide recommendations for problems that arise. Respondents in this study were 93 active students and used SEM-PLS for data processing. From the output of the analysis, it can be stated that the level of student acceptance of SIAM is good, which has a value of 13.374. This is because SIAM is easy to use, makes it easier for students to find academic information, the information is quite detailed and easy to understand, and students feel that using SIAM is the right and wise idea so that students have an interest in using SIAM. The recommendations proposed are, fixing errors in the source code so as to make SIAM easy to access and use for students. intention and interest in student behavior to use SIAM and provide encouragement so that students always use SIAM
Intelligent Optimization Algorithm for Teacher Teaching Quality Evaluation Under the Environment of Intelligent Eye Feedback Information Collection

The three-dimensional eye feedback technology is used to digitize the teaching information of teachers, and the digitized information is subjected to in-depth processing such as denoising and threshold segmentation; then the state space reconstruction of the subway passenger flow information is carried out in a time series, and the developmental classroom teaching quality evaluation is based on each The development of professional quality of famous teachers and the improvement of teaching ability are the main focus and foothold, which can fully mobilize the enthusiasm and initiative of teachers to participate in teaching quality evaluation. The intelligent information collection system is not only for the information collection of traditional information collection system The process is simplified and realized, absorbing enterprises and industries to participate in the evaluation, expanding the evaluation connotation, and gradually establishing a teaching quality evaluation system that is conducive to the growth of "dual teachers and dual abilities" teachers and improving the school's ability to cultivate applied talents.
Keefektifan Bahan Ajar Unit Kegiatan Belajar Mandiri (UKBM) Teks Esksplanasi Berbasis Literasi untuk Siswa Kelas XI MAN 3 Kediri

This study aims to test the effectiveness of UKBM teaching materials Literacy-Based Explanatory Text for Class XI Students of MAN 3 Kediri. The type of research used in this research is experimental research with the Pre-Experimental Design research with the One-Group Pretest-Posttest Design model. The subjects of this study were 34 students of class XI Religion 2 MAN 3. Data collection methods used are tests, questionnaires, documentation, and observation. Meanwhile, to analyze the data using the effectiveness test. The results showed that the average pretest score was 69.24 and the posttest average score was 80.24. This means that student learning outcomes have increased by 14.28, and the average gain test is included in the moderate criteria, which is equal to 0.36 or 36%. Based on the explanation above, the use of UKBM teaching materials is effectively used to improve students' literacy skills in learning explanatory texts for class XI MAN 3 Kediri.
EDUCATIONAL SPACE OF CONTINUOUS EDUCATION OF TEACHERS: A FACILITATING APPROACH

The authors, relying on the practical work of domestic and foreign researchers, offer an effective system of organizing the educational space of continuous education of pedagogical workers on the basis of the facilitation approach. Taking into account the «digital revolution» and the possibilities of electronic (distance) learning, the transition of continuous education from «education 1.0» to «education 4.0» is proposed, which will contribute to the further development and self-development of the skills of pedagogical workers as facilitators, their social and reflective competencies. The possibilities of using educational space based on information and communication technologies for the development of social and reflective competences of pedagogical workers in the institution of continuous education have been revealed. The specified educational space is characterized by: another goal of continuous education (awareness of the multifaceted nature of professional decisions); the democratic nature of the process of professional development, equality with other participants in this process (including organizers and authors of professional development courses); development of new social and reflexive competences, knowledge and skills among pedagogical workers in the process of co-creation; the clarity of the algorithms for the use of information and communication technologies in the system of continuous education, on the basis of which pedagogical workers develop social and reflective competences, a system of values, professional attitudes, professional worldview, etc.
Vulnerability Detection with Representation Learning

It is essential to identify potentially vulnerable code in our software systems. Deep neural network techniques have been used for vulnerability detection. However, existing methods usually ignore the feature representation of vulnerable datasets, resulting in unsatisfactory model performance. Such vulnerability detection techniques should achieve high accuracy, relatively high true-positive rate, and low false-negative rate. At the same time, it needs to be able to complete the vulnerability detection of actual projects and does not require additional expert knowledge or tedious configuration. In this article, we propose and implement VDDRL (A Vulnerability Detection Method Based On Deep Representation Learning). This deep representation learning-based vulnerability detection method combines feature extraction and ensemble learning. VDDRL uses the word2vec model to convert the source code into a vector representation. Deep representations of vulnerable code are learned from vulnerable code token sequences using LSTM models and then trained for classification using traditional machine learning algorithms. The training dataset we use is derived from actual projects and contains seven different types of vulnerabilities. Through comparative experiments on datasets, VDDRL achieves an Accuracy of 95.6%–98.7%, a Precision of 91.6%–99.0%, a Recall of 84.7%–99.5%, and an F1 of 88.1%–99.2%. Both perform better than the baseline method. Our experimental results show that VDDRL is a generic, lightweight, and extensible vulnerability detection method. Compared with other methods, it has better performance and robustness.
Training needs of faculty members in KSA universities after Covid-19 pandemic , according to Goldstein and Ford's model

The repercussions of the Corona crisis (COVID-19) cast its shadows on the world, and the world’s systems joined forces to confront it, including, of course, the KSA, which presented a pioneering model in managing this crisis, and one of the lessons learned here is the change of the educational pattern and the trend towards electronic and virtual mode. Which calls for a change in the culture of the traditional work at the level of the entire university educational system. Therefore, the current study was concerned with identifying the training needs (TNA) of faculty members in Saudi universities according to the Goldstein and Ford's model to determine the necessary training needs for the post-COVID-19 period; to achieve the goal of the study. A questionnaire consisting of (36) items was applied (414) faculty members from (6) Saudi public universities. The field study reached a set of results, the most important of which are: The total percentage of the training gap in the proposed needs was (77.18%),And (79.22%) in professional needs, (78.74%) in administrative needs and (78.56%) in personal needs, and the most important proposed personal needs were (providing support and advice to injured students and their families during emergencies and pandemics according to the degree of risk (yellow - orange - red). The study recommended the establishment of a training unit to be located in the general office of the Ministry of Education under the Minister’s office, and its main function is to organize training programs for faculty members in universities to face crises imposed by emerging conditions such as the spread of pandemics, in addition to providing (frames) training competencies from faculty members to provide courses and provide Financial and logistical support for organizing these training.
An introductional lecture on chaotic systems through Lorenz attractor and forced Lotka Volterra equation for interdisciplinary education

Is it possible to predict the future? How accurate is the prediction for the future? These questions are fascinating and intriguing ones in particular for young generations who look at their future with curiosity. For a long time, many have tried to quantitatively predict future behavior of systems more accurately with techniques such as time series analysis and derived dynamical models based on observed data. The paper proposes a lecture structure in which elements of chaos, which greatly impacts the predictive capabilities of dynamical models, are introduced through two classical examples of nonlinear dynamical systems, namely Lorenz attractor and Lotka-Volterra equations. In a possible lecture, these two structures are introduced in a basic and intuitive way, followed by equilibria analyses and Lyapunov control approaches. The paper intends to give a possible structure of an interdisciplinary lecture in chaotic systems, for all students in general and non-engineering students in particular, to kindle students’ interest in challenging ideas and models. By presenting an intuitive learning-based approach and the results of the implementation, the paper contributes to the discourse on interdisciplinary education. The lecture is a part of a course within a Complementary Study at Leuphana Unversity of Lüneburg. The material which inspired the proposed lecture structure is taken from the scripts of the Master Complementary Course titled Modelling and Control of Dynamical Systems using Linear and Nonlinear Differential Equations held at Leuphana University of Lüneburg.
Virtual Reality Cognitive-Behavioral Therapy Biofeedback System for Glossophobia

The fear of public speaking is one of the most common social phobias causing anxiety problems in many people. In this context, this project focuses on developing a tool capable of helping mental health professionals using virtual reality as a controlled environment in expository therapies, in this case applied to Glossophobia. To enhance the creation of self-control mechanisms in these patients, the use of virtual reality is explored with the aid of Neuro and Biofeedback, allowing the visualization in real time of the physiological response to the stimuli of the virtual environment.
Image segmentation for blind lanes based on improved SegNet model

The position of blind lanes must be correctly determined in order for blind people to travel safely. Aiming at the low accuracy and slow speed of traditional blind lanes image segmentation algorithms, a semantic segmentation method based on SegNet and MobileNetV3 is proposed. The main idea is to replace the coding part of the original SegNet model with the feature extraction part of MobileNetV3 and remove the pooling layer. Blind lanes images were collected through online search and self-shooting, and then the data were manually marked by LabelMe software and trained on TensorFlow deep learning framework. The experimental results show that the improved model has high segmentation accuracy and recognition speed. The pixel accuracy of blind lanes segmentation is 98.21%, the mean intersection over union is 96.29%, and the average time for processing a 416 × 416 image is 0.057 s, which meets the real-time requirements of the blind guidance system.
Paleofidelity: An R Package for Measuring and Visualizing Live-Dead Fidelity

Live-dead fidelity analysis, one of the key approaches of conservation paleobiology, aims to measure the congruence between living communities and sympatric death assemblages. Typically, data involve compositional matrices with counts of specimens grouped by variables (typically taxa) and observations (typically sampling units). The most common targets of live-dead comparisons are diversity fidelity (especially alpha diversity and evenness) and compositional fidelity (faunal agreement). A beta version of a new package dedicated to analyzing and visualizing live-dead fidelity is available on GitHub (R package: “PaleoFidelity”). The package allows for measuring diversity fidelity (dead-live offset in sample-standardized species richness), evenness fidelity (dead-live offset in Hulbert’s Pie evenness), and compositional fidelity estimated by correlation (Spearman, Kendall, and Pearson) and similarity (Bray, Chao, etc.) measures. The package includes a resampling model for assessing expected values of correlation and similarity measures under the null model of perfect live-dead congruence. In addition, tests and confidence intervals based on resampling protocols are provided to allow for statistical assessment of fidelity patterns. Finally, PaleoFidelity includes plot functions for visualizing live-dead congruence in diversity or faunal composition. The current version of the package can be installed in R or R Studio using the following statement: devtools::install_github(‘mjkowalewski/PaleoFidelity’, build_vignettes = TRUE).
Differences in healthcare professionals' perceptions of robots' usefulness, challenges, cautions, ethical issues, and intermediary roles by the experience of robot use

This study aimed to determine differences in healthcare professionals' perceptions of robots' usefulness, challenges, cautions, ethical issues, and intermediary roles by the experience robot use. The questionnaire was distributed to 180 participants, and 151 responses (84% valid response rate) were analyzed, excluding participants who did not give consent or data with missing values. The participants were divided into two groups according to whether they had had the following experiences: 1) using a robot in their daily life, 2) seeing a robot being used while at work, or 3) using a robot while at work. Group comparisons were performed using Welch's t-test or Mann-Whitney U test, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{p} &lt; 0.05$</tex> was used as the significance level in all calculations. Factor 2 (Usefulness of robots) scores were significantly higher for participants who reported having used robots in their daily lives. Factor 4 (Inconveniences of using robots) was significantly higher for participants who reported having used robots while at work. However, no significant differences were found for Factor 1 (The role of the intermediaries); Factor 3 (Ethical issues of concern in robot use); and Factor 5 (Dangers of robots). Findings from this study that robots are useful but currently used robots need intermediary assistance and improvement.
Expert System to Diagnose Dental and Oral Disease Using Naive Bayes Method

The high cost of consulting and checking teeth or mouth makes residents reluctant to go to the doctor. In order to facilitate the consultation, a system is needed that can predict the dental and oral diseases that he is suffering from without having to go to the doctor for consultation on the disease. An expert system is a system that transmits human knowledge to a computer, so that computers can solve problems such as those that are usually tried by experts. Experts defined here are people who have special abilities who can solve problems that ordinary people cannot solve. Research on dental and oral disease expert systems for the manufacture of this expert system used the Naive Bayes method. The decision to diagnose dental and oral disease is carried out through a consultation process between the system and the user, If the answers entered match the applicable regulations, then the system will share the results of the diagnosis of dental and oral diseases that he suffers from. We recommend that the procedures for collecting data in conducting this research are: interviews and literature review. In making this expert system using the Naive Bayes method, it is hoped that it can help residents identify diseases, or share solutions to problems with their teeth and mouth without going to the doctor first.
Application of an Inquiry-Based Learning Space (ILS) GRAASP in the Course of Differential Equations for Engineering Students Within the Framework of the Project Wp@ELAB

With the evolution of Information and Communication Technologies (ICT) and the progressive growth of Virtual Learning Environments (VLE), new development needs arise in terms of teaching-learning methodologies in the classroom. On the other hand, the remote education for the COVID-19 health emergency worldwide had a positive impact in the virtual education, increasing the number of online courses through virtual platforms, in which researchers and teachers will be able to develop and implement classroom learning spaces, among which Massive Open Online Courses (MOOC's) and Inquiry-Based Learning Spaces (ILS) stand out. This paper presents the application process of an ILS of differential equations through the free resource GRAASP and published in the Golabz platform during Differential Equations of the Universidad Nacional Abierta y a Distancia. Hake's gain is used for learning assessment, an average gain of 0.37 was found, which implies a medium learning gain.