Reviewerly/exHarmony huggingface dataset:
Pedagogical requirements for preparing future primary school teachers to develop mathematical abilities among students

The article is devoted to improving the professional training of future primary school teachers. This article is based on the normative materials, philosophical, psychological and pedagogical research in the field of education. The relevance of developing mathematical education and preparing future primary school teachers for the development of mathematical abilities among students was determined.  The article reveals conceptual approaches, which are the basis for the training of future primary school teachers. The requirements for the content of primary education, aimed at developing the individual abilities of younger students, as well as requirements for the level of training and competencies of the teacher were considered. The authors have defined the pedagogical requirements for preparing future primary school teachers to develop mathematical abilities among students, which include interdisciplinary interaction and integration of subjects within the educational program.
PENGEMBANGAN E-BOOK BERBASIS ANDROID PADA MATA PELAJARAN SISTEM KOMPUTER DI SMK YAPALIS KRIAN

This research on the development of an Android-based E-book on the Computer System material is motivated by the limitations of the media used by teachers in online learning. The purpose of this study is to find out how the development of E-books on Computer Systems subjects and determine the feasibility of E-books on Computer Systems subjects. This type of research is development research with the model used is ADDIE. Data collection techniques in this study used expert validation sheets and student response questionnaires. The development of this Android-based E-book uses the Flip Pdf Corporate Edition application.The results of the study were obtained from material experts, media experts and student response questionnaires with the percentage of media feasibility assessed by media experts getting a percentage of 96% with the "Very Eligible" category, for use and assessment from material experts getting a percentage of 84% with the category " Very Eligible" and student responses in the student questionnaire got an average score of 91.4 with the category "Very Eligible" to be used in the actual learning process in the classroom.
Impacto del COVID 19 en la educación pública en el nivel de básica primaria del departamento del Meta

March 11, 2020, the World Health Organization (WHO) declares the Sars-cov2 (COVID-19) pandemic, this document intends to put in evidence, the social impact that was generated in the public education, from the declaration of the pandemic, especially in the basic elementary level, so, it seeks to determine the consequences on the students, the difficulties of education system implemented during the pandemic and the shortcomings of the virtual education system, also seeks to propose strategies to mitigate the impact, that has interruption problems in learning, increase in school dropouts and the increase in student inequality
Particularities of Education Based on Competences in the Online Environment – Qualitative Study

In this scientific study, the author slots to identify the particularities of online learning within the framework of competence-based education.The intention is to analyze the specifics of online learning when it is a predominant and independent method in competent education and not a complementary one in the case of distance learning.After a brief historical analysis of pedagogical systems based on content, objectives and competences, the author analyses the impact that the key competences promoted at EU level.The analysis allows it to emphasize the importance of key competences by their purpose, which lies not only in the act of learning but also in the act of turning into practice.The COVID-19 has made the most of the proficiency-based pedagogy in both the university and the pre-university environment.Based on a quality study, using the Delphi method, the author used two samples to identify these particularities.In the first part of the study in relation to the specifics of competence-based learning, the author identified the top 12 aspects of learning that online are harder for teachers to achieve.Both categories of respondents (from academia and preuniversity) identified the same aspect in a group of 12. Using the results of the research and professional experience the respondents were asked to identify the main characteristics of the virtual class and to put them in correspondence with the characteristics of the real class.The group of 10 identified characteristics was similar to the 2 learning environments.In the second part of the study a number of 50 respondents, divided equally in university and pre-university were asked to respond on a scale of 1 to 10 which is the negative impact of each characteristic of the virtual class previously identified.The result shows differences between two categories of respondents, which were interpreted in the study.
Crowd Analysis and Mask Detection using Raspberry Pi-3

Now a days all world suffering from a pandemic issue of COVID-19 to control these situation and to maintain the safety of ourselves we all have to take care of the two things like do not make a crowd and wear the mask properly.And to achieve this requirement of safety this paper works with the help of fog node and camera.Managing the crowd requires an intelligent monitoring technology.In this project, we propose a method to manage the crowd by counting multiple humans in the scene by head detection.In our study, we develop a system using Raspberry Pi 3 board that detects the human heads and provide a count of humans in the region using Open CV-Python.A Haar cascade classifier is trained for human head detection.This work also proposes a fog computing-based face mask detection system for controlling the entry of a person into a facility.The proposed system uses fog nodes to process the video streams captured at various entrances into a facility.Haar-cascade-classifiers are used to detect face portions in the video frames.Each fog node deploys two Mobile Net models, where the first model deals with the dichotomy between mask and no mask case.The second model deals with the dichotomy between proper mask wear and improper mask wear case and is applied only if the first model detects mask in the facial image.This two-level classification allows the entry of people into a facility, only if they wear the mask properly The results of the analysis will be helpful in managing the crowd and mask detection in the area with the help of camera.
Expert System Diagnosing Diseases in Rubber Plants using the Dempster-Shafer Method

Rubber plants are one of the supports for the national economy in general for the Indonesian population, but rubber plants experience many diseases that cause the quality of rubber to decline, which has an impact on the selling price of rubber, so we need an expert system that can help the community to diagnose diseases as initial treatment in controlling disease in rubber plants, namely the expert system, using the Dempster-Shafer method, which aims to find out the diseases experienced by rubber plants easily without having to manually diagnose. The results show how the process of calculating the initial combination rule to the last combination rule is based on the selected symptoms, it can be concluded that the highest density value is P6 Moldy Rot with a density value of 0.907 x 100% = 90.7% = 91%.
Libraries Learning Commons: Exploratory Digital Media Makerspace: Welland Campus

Information about the makerspace at the Daniel J. Patterson Campus, including digital media and 3D printer options
A informação transmitida na consulta de enfermagem pré-operatória: perceção do cliente

Introduction: The preoperative nursing consultation could be understood as a privileged moment for the transmission of information to the patient in order to better prepare it for surgery and promoting it collaboration in postoperative care. For the consultation was an effective and valued intervention, it should take into account patients’ information needs and because of this, it is relevant to know patients’ perspective on this topic.  Aim: To identify the importance of the information transmitted in the consultation for the patients and to identify the contribution of the information for the patient's collaboration in the recovery.  Materials and Methods: Descriptive study with a quantitative approach. It consisted of the assessment on preoperative nursing consultation at the patients’ point of view in relation to the information transmitted and its influence their collaboration in postoperative care. A survey was prepared and applied between June and December 2018. The sample was selected for convenience, including patients with preoperative nursing consultation integrated into a multidisciplinary perioperative care program - Enhanced Recovery After Surgery, who were aware and literate.  Results: The sample consisted of 45 patients. It should be noted that 91.1% (n = 41) of patients rated the information as “very important/important”. It was found that 91.1% (n = 41) of the patients answered “I totally agree/I agree” that the information received contributed to their responsibility in the recovery process. Approximately 88.9% (n = 40) answered “I totally agree/I agree” that the information transmitted helped them to collaborate more in post-operative care.  Conclusion: The patients considered the information transmitted during the preoperative nursing consultation very important. The results suggest that more informed patients better understand their responsibility for recovery and collaborated more in postoperative care, which favors the surgical process and improves outcomes.
Detection of Congested Traffic Flow during Road Construction using Improved Background Subtraction with Two Levels RoI Definition

This study is aimed to detect traffic congestion that may occur during roadblocks of road construction. We improved the background subtraction method by considering Region of Interest (RoI) in the video frame to detect the congestion. The proposed method has experimented with video test material that shows traffic condition in the road construction site. The performance of the proposed method is evaluated using Confusion Matrix by comparing the result of the experiment with ground truth obtained visually. As a benchmarking process, the performance is also compared with the conventional background subtraction method. The result shows that the proposed method can achieve an accuracy of 83.2% for video from the first camera and 82.3% for video from the second camera. In comparison, the conventional background subtraction method only achieves 49.8% for video from the first camera and 0% for video from the second camera. Based on this evaluation, the proposed method can support implementation of efficient traffic control using adaptive traffic light that is equipped with camera.
Fostering natural world engagements: Design lessons & issues from, the My Naturewatch training programme

Nature's welfare is inter-twinned with humankinds’, requiring mass citizen-led action. Wildlife advocate Attenborough says, ‘we share responsibility for the future of life on earth, [we all have] the power to change’. The My Naturewatch project (NW) follows research through design approaches: deploying DIY devices, supporting new engagement methods between nature, technology and humans. The NW cameras assist participants in capturing images of ‘back garden’ wildlife. Authors position NW cameras as agent(s), enabling ‘designed engagement(s)’ establishing; agency, serendipity and impact.The article recounts a ‘Training Scheme’, providing nature organisation(s) methods to foster public engagement through DIY, accessible digital technologies. The scheme encouraged appropriation; suiting contextual, environmental and organisational requirements. Authors unpick experiences and issues, realised (through practice) by fourteen nationally acclaimed wildlife and conservation organisations, independently running workshops with NW tools. Findings report on issues and opportunities of; designed community engagement(s) for practitioners engaged with defining more sustainable practices.
Efficient Spatio-Temporal Network with Gated Fusion for Video Super-Resolution

Video super-resolution (VSR) has drawn much attention in research community recently. As the typical three-dimensional (3D) signals, how to exploit spatio-temporal features in videos effectively and efficiently is critical for VSR. Most methods explore spatio-temporal feature through optical flow estimation and motion compensation. Although promising, these methods suffer from the trade-off between model performance and complexity. In this paper, we present a novel efficient spatio-temporal network (denoted as “ESTN") for VSR, which is designed to separately encode spatial and temporal video frames through two parallel streams. In particular, several 2D and 3D convolutions are utilized to encode on the central frame and consecutive frames for feature extraction. Besides, for the better ability of adaptive alignment at the feature level, instead of direct addition, we propose to learn a gate module consisting of deformable convolution to fuse the spatial and temporal features from the two streams. Such design enables efficient spatio-temporal exploration and maintains a lightweight model. Experiments demonstrate that the proposed ESTN achieves competitive or even better performance than its competitors with similar parameters.
COLLABORATING AT MICROSCOPIC AND MASSIVE SCALES: THE CHALLENGE AND VALUE OF COVID ISOLATION FOR CRITICAL INTERNET STUDIES

Global events like a pandemic or climate change are massive in scope but experienced at the local, lived, microscopic level. What sorts of methodologies and mindsets can help critical internet researchers, functioning as interventionists or activists, find traction by oscillating between these levels? How can we push (further) against the boundaries of research methods to build stronger coalitions and more impactful outcomes for social change among groups of scholars/researchers? This panel presents four papers addressing these questions based on a large scale online autoethnography in 2020. This “Massive/Micro” project simultaneously used and studied the angst and novelty of isolation during a pandemic, activating researchers, activists, and artists to explore the massive yet microscopic properties of COVID-19 as a “glocal” phenomenon. The challenge? Working independently and microscopically through intense focus on the Self but also working with distributed, largely unknown collaborators, in multiple platforms. The emerging shape of the project itself showcases the challenges and possibilities of how research projects at scale can (or don’t) reflect and build social movements. The panel’s four papers situate the project through a kaleidoscope of perspectives featuring participants from 7 countries, who variously explore: the value of the project for precarious or early career researchers, how MMS worked as both collaborative space and critical pedagogy, how non-institutional or playful experimentation in asynchronous collaborations can lead to new synergies; and how MMS developed an independent life of its own, beyond studying COVID to generating multiple communities of future digital research practice.
AdaBoost integration with Genetic Algorithm for Psychological Aptitude Result Interpretation Model

SMA Darma Yudha Pekanbaru has a special program to facilitate students in knowing their interests and talents. The process is carried out by conducting special tests that can only be carried out by a certified psychologist. The psychologist is an educational worker under the division of guidance and counseling. The results of the test will be interpreted by psychologists with an output in the form of interests that can be used to determine the selection of majors in further study in college. Moreover, the results of the interpretation also contain recommendations of interest and talent for a career after the learner graduated from college. However, the recommendations of interest and talent are the result of unilateral analysis by psychologists without a supporting device to confirm the truth and accuracy. In this case the author will conduct research in the form of analysis of the results of interpretation issued by the psychologist of course with a variety of assessment instruments and not only that, to further ensure the results of interpretation, the author conducts analysis using 2 (two) machine learning methods and will then be done in order to get the best results. In this study, the authors used machine learning by comparing the results of analysis from 2 (two) methods namely Naive Bayes and Decision Trees Classifier which then the classification results will be improved with AdaBoost.
Comic Studies THE POTENTIAL OF WAYANG RAMAYANA R.A KOSASIH COMICS AS A MEDIA (KOMPLEMENTER) OF JUNIOR HIGH SCHOOL LEARNING IN CENTRAL JAVA

Local content for junior high school content in Javanese language lessons is the story of Ramayana. Junior high school curriculum version 2013, uses Kidang Kencana story segment in Ramayana as Basic Competence 3 in Semester 2 outcome, and students have difficulty understanding it due to various factors. On the other hand, R.A Kosasih made a wayang comic titled Rama and Sinta (Ramayana). Therefore, the aim of this research is to examine whether the comic Rama and Sinta (Ramayana) can be used as a learning medium for junior high school students in Central Java. This is a qualitative research with an empirical approach. The results of the analysis show that there are similarities in the contents of the story, characters, settings and the story line of the Ramayana between the Javanese language textbook and the comic. Therefore, it can be concluded that the comic Rama and Sinta (Ramayana) can be used as a learning medium in Javanese language subjects through language translation, because the content is in accordance with the curriculum.
Special Section on Scalable Computing for Blockchain Systems

The papers in this special section focus scalable computing for blockchain systems.
Perceptions about the design of informational materials used in the fight against COVID-19 in Portugal and Brazil

Abstract This study aimed to assess perceptions on the graphical informational materials designed to help in the fight against COVID-19 in Portugal and Brazil. We assessed the perceptions using an online survey incorporating the AttrakDiff2TM questionnaire. The results show that the perception of risk with relation to the COVID-19 pandemic is high among the respondents, and that they believe that they will have mild symptoms if infected by the virus. The results also show that the materials available in these countries were poorly designed and not effective in promoting adequate behaviour change. These findings can contribute to future design projects whose aim is to design risk communication materials to inform and guide people facing health crisis situations.
Manual Wheelchair Stroke Time Estimation Using Hand-Mounted Sensor

Individuals living with spinal cord injury who use manual wheelchairs are dependent on their upper limb for mobility.The propulsion of a manual wheelchair is physically demanding for upper limb muscles.Repetitive loads applied to the shoulder expose manual wheelchair users to shoulder injury and pain.In fact, 30% to 70% of manual wheelchair users experience shoulder pain and injury as a results of repetitive shoulder strain injury.Considering the dependence of wheelchair users' lives on their upper limb for daily routine and mobility, shoulder injury is a considerable burden and directly affects their quality of life and independence.Previous studies identified the association between shoulder injury and manual wheelchair stroke-related kinematic and kinetic parameters, with stroke time, velocity, average peak resultant force applied to pushrim, and the stroke length being the most clinically relevant parameters.These parameters are considered as reference criteria and are mostly measured by SmartWheel and motion-capture systems.However, they are limited to lab environment and are time and labour-intensive.Therefore, there is a need to develop a different method to assessthe risk of repetitive shoulder strain injury to mitigate these issues.The purpose of this study was to propose a method based on an inertial measurement unit (IMU) mounted on hand to estimate stroke time.IMU is capable of measuring three dimensional acceleration and can be used in field and remote areas.For this purpose, five volunteers were recruited to perform five rounds of wheelchair propelling.In each round, participants performed ten strokes while the SmartWheel analyzed the push on the handrim and IMU measured the hand acceleration.Then the measured magnitude of the resultant jerk vector was used to detect the hand contact and hand release, and calculate stroke time.The stroke time obtained from the IMU method was validated against the one from SmartWheel.The mean error (standard deviation) and relative mean error (mean error divided to the stroke time duration) of stroke time estimated using IMU compared to ones obtained by SmartWheel were 67 (23) millisecond and 0.8% (0.4%).This study revealed that hand-mounted IMU was able to estimate the stroke time with high accuracy.
Implementation of Design Sprint in Cowin Mobile-Based Application

Cowin is an investment platform in the cattle breeding sector and has been operating for several years in Pekanbaru. Currently, Cowin wants to increase its business development by expanding its target market by creating a mobile-based investment application. Since its beginning, Cowin has had a website application to make it easier for investors to invest online. However, according to the user specifications before implementing design sprint, the features contained in the website application are considered impractical to use, because they do not have much time to see cattle monitoring routinely through the website. So the purpose of this study is to identify investor's needs and problems when they want to invest in Cowin to build a good mobile-based application. The results of this study is a mobile-based Cowin application that has validated three times consisting of 2 times the task completion rate and 1-time usability testing using a likert scale. Through this research, the mobile applications that have been built is easy to learn and understand, but still need improvements in branding in the future so the investors will be interested in recommending this application to others.
Implementasi Kubernetes Cluster Menggunakan Vagrant

The development of technology that can package an application and its needs in a virtualization called container, therefore it takes software that can do management of containers, one of which is Docker. But the need is always increasing the system is not able to accommodate many applications, therefore it takes software that is able to do clustering container management in large quantities. One such software is cabernets. After conducting high-availability testing, scalability and performance testing on cabernets cluster technology applied to vagrant and KVM virtualization. High-availability testing consisting of failover, failback and load balancer can be simulated on both virtualizations. Latency /delay in vagrant virtualization is greater than KVM virtualization with latency/delay difference when accessed by 20 users of 2.66 seconds, 40 users of 1.67 seconds and 60 users of 6.03 seconds. Then the CPU and Memory resource usage on vagrant virtualization is greater. The difference in the percentage of CPU and Memory usage in vagrant virtualization and KVM when accessed by 20 users is CPU 9% and Memory 5%, 40 users are CPU 7% and Memory 7%, 60 users are CPU 9% and Memory 10%.