Reviewerly/exHarmony huggingface dataset:
Implementation of Golang and ReactJS in the COVID-19 Vaccination Reservation System

SARS-COV-2, or COVID-19, has become a global threat. Since it was determined to become a pandemic status in Indonesia, various efforts have been taken by the government, one of which is the mass vaccination program. After going through a long journey to test its effectiveness, quality and safety through various stages of research and trials, the COVID-19 vaccine is officially distributed to the public. The vaccination program is critical to combating the COVID-19 pandemic since it can reduce morbidity and mortality rates and supports achieving herd immunity against the COVID-19 virus. During the mass vaccination process, queues and crowds are often encountered, which can potentially increase the spread of the COVID-19 virus. This research aims to anticipate the risk of transmission in the vaccination process by building a vaccination reservation system. This system is built by implementing two leading technologies: the Go programming language (Golang) and JavaScript with the ReactJS library.
Taking into account “who said what” in abstract argumentation: Complexity results

We propose a new paradigm for reasoning over abstract argumentation frameworks where the “who said what” relation, associating each argument with the set of agents who claimed it, is taken into account, along with possible information on the trustworthiness of the agents. Specifically, we extend the traditional reasoning based on the classical verification and acceptance problems and introduce a reasoning paradigm investigating how the “robustness” of a set of arguments S (in terms of being an extension or not) or of an argument a (in terms of being accepted or not) can change if what has been claimed by some agents is ignored (as if these agents were removed from the dispute modeled by the argumentation framework). In this regard, we address the problems of searching the “minimum extent” of the removal of agents that makes a set S an extension or an argument a accepted. Compared with the case where only the “yes/no” answer of the traditional verification and acceptance problems are available, the knowledge of such a minimum provides the analyst with further insights allowing them to better judge the robustness of S and a. We consider the above minimization problems in two variants, where the agents are associated with a measure of their trustworthiness or not and provide a thorough characterization of their complexities.
Quizlet Time: Interactive Didactic Platforms as a Part of Digital Educational Space

Objectives: The article is devoted to the discussion and analysis of educational problems appeared in a Covid-19 pandemic and post-pandemic period in Russia. It discusses positive and negative aspects of a modern digital educational approach to foreign languages training within e-learning dominant due to a pandemic and its consequences. The authors stress that pandemic and post-pandemic period influenced all the spheres of a mankind existence and the most powerful impact was made in the field of a digital communication and e-learning methodology supported by a rapid development of IT. The authors consider that the diversity of technical educational tools brought a certain mess into the educational process as it was recommended to use the most suitable platform answering the demands of a curriculum within a particular educational organization. The authors of the article took an attempt to analyze the existing didactic platforms, particularly Quizlet platform, by introducing them into a teaching process, and describe pros and cons of this mobile application within a personal experience. Methodology: The methodology of our research includes several theoretical and empirical investigation methods such as the method of analysis, comparison, experiment and observation.
Behavioral Study of Customer Using Deep Learning Techniques

With the fast headways in web advancements and development in online business, individuals are showing interest in purchasing items online in light of the surveys of clients who will be who have proactively purchased that thing or item. The fundamental goal of this task is to foster an AI model that can group or order the client surveys as certain or negative. With the assistance of opinion investigation E-business stages will get clearness about client intrigued items and issues confronted in regards to their intrigued items. This assists with fostering their internet based business by contacting various individuals and publicizing the items and subsequently further develop the dealers profile so it is a success circumstance to both the merchant and the web based business stage. Normal language handling is one of the methods to get the expectation of a text based input. The machine ought to have the option to comprehend the feeling behind the audit and afterward group it as good or pessimistic. Consequently, it is critical to get the client's viewpoint and arrange the audit in like manner. This needs an exceptionally precise framework or AI model to have the option to anticipate the survey accurately. Profound learning is a high level strategy which has the abilities to give high precision of the models created.
The Application of The Expert System in English Reading Teaching

Mixed is a combination of traditional and new methods. The main difference between the two methods lies in their reading methods. The old method focuses on students' understanding ability, while the new method emphasizes stu-dents' vocabulary development and fluency. In this way, they can be said to be different from each other, but they are also very similar in some ways. What is mixed teaching model is a teaching method with both traditional and modern character-istics. It modern teaching methods, so it can be regarded as an excellent way to learn English reading in college. The main contents are as follows: 1) teach students to read with new and old methods; 2) Cultivate students' ability to understand, analyze and synthesize information.
A Framework of Internet of Things (Iot) for the Manufacturing and Image Classification System

In order to prevent excessive energy usage and to identify water pollution, alternately, genuine process industry detection and picture categorization are now required. Scientists are looking for a limited and efficient IoT (Iot) device that would detect and assess the real-time state of industrial machinery since implementing automation in economic industries is often an expensive project. Additionally, the IoT technology may be used to classify images in order to find water contamination. This study has compared several picture binary classifiers and described the advantages and price of the IoT that is now accessible. On the basis of the opinions of returned questionnaires, a main numerical survey approach has been used to gather relevant data. After then, the “Normative” selecting method was used to analyse the main data and support a comparative evaluation. Internet of things iot (Sensor Networks) is a less advanced product that can be included into both small- and large-scale industrial businesses, according to research and analysis. For identifying contamination of water, classification IoT has been shown to be effective, and texture analysis is less expensive than spatial analysis.
Hybridized Encrypted Communications System based on Fragmentation for Cloud Infrastructure

Users are unsure if they should use some systems, such as the cloud, since robotics has raised the potential of theft or other risks. The abundance of services that the cloud offers has increased consumption. Therefore, The cloud resources should be safeguarded against to possible dangers in order providing faster and efficient efficiency. A number of security measures have been proposed to accomplish security. A couple of them used the concept of “splitting,” in which content is broken down into smaller parts, secured, and then stored across several locations. These precautions were enough for safeguarding, however because of the section, they brought forth a brand-new issue with data loss. By limiting the theft of customer tasks and info and lowering the chance of Errors has been addressed with the development of a capacitation in a secure environment. The information was broken down into parts and protected using a robust cybersecurity method that included SSL and Boolean techniques in these systems to decrease uncertainty that employed a set of requirements. The Vital sign rifle database server site's replication displays and stores a considerable amount of data, including various image kinds, audio, and written text. Results in terms of picture size after encryption, storage time, and data leak were much better than those obtained with the earlier approaches.
Communication Decipher: Text to Speech and Hand Gesture to Speech Conversion

Communication between people with some kind of disabilities has always been a problem faced by our society. Communication between a normal person and a physically challenged person has always been a challenging task. Mute people can use sign language to communicate with one another, but it is hard to communicate with someone who doesn't understand the sign language. The blind cannot read the normal text and rely on the Braille scripts. Many of the modern-day researches focus on addressing the issues of one of the above challenges, but not all. This paper aims to venture into the field of assistive learning tools, where the work described can help teach the Kannada alphabet to everyone, irrespective of their disabilities. Using this system, the visually impaired can hear the information represented as text by converting the text into speech. The deaf/mute can communicate by converting the speech input into text output, or the hand sign input into text and audio output. In exceptional cases where a person is deaf, mute and blind can use the Braille letter board. The assistive system is built on Raspberry Pi with Image Processing and Speech Recognition techniques. The designed system works with 99 % accuracy.
STUDENTS' PERCEPTIONS TOWARD THE QUALITY OF ONLINE EDUCATION DURING COVID-19 PANDEMIC

COVID-19 pandemic has not only impacted human life but also impacted quality of online education, right after the shift from traditional face-to-face to e-learning. This study was conducted to investigate the perception of this type of learning amongst UPB students, being focused around the following areas: number of students taking online courses and the geographic areas served, quality standards for online learning and supportive services, planning and leadership in online learning.This study utilized quantitative methods and was conducted by distributing an online questionnaire to UPB's students. A total of 231 valid unduplicated responses were used to investigate the perceptions of online course-management, underlying factors that contribute to those perceptions (positive or negative), reconsidering the overall online learning activities initiated by university teachers. The following independent variables were investigated in this survey, based on students own online learning experiences, in contrast to traditional learning: interactivity, teacher facilitation, structure, learning style and self-motivation. The findings of this research revealed that electronic learning, the core method of teaching the curriculum due to the wide worldwide spread the COVID-19 pandemic, requires an improvement of online instructional practices, in terms of a more interactive active approach, a well-thought-out strategy, a conceptual framework of online education combining knowledge from different domain: Pedagogy, Didactic, Computer Assisted Instruction (CAI), IT and Psychology - as potential determinants of a successful online learning. The observations captured in this report reflect the measure of satisfaction of UPB's students regarding the educational services offer of the learning program, adapted to the online environment, taking into account the specificities of this organization and communication environment.
DIGITALIZATION AND LEVELS OF QUALIFICATION

The article is based on an analysis of current documents issued at European level, by the European Commission, CEDEFOP, USA-Department for Labor and also at national level, on digital education and establishing the necessary competencies at different levels of education. For the first time, a correlation is made between the qualification levels in the National Qualifications Framework and the competences / skills currently existing in the specialized literature as a narrative. This classification comes to the aid of education specialists to show them what needs to be taught to pupils and students according to their mental capacity in what we call digital education. We must take into account the development of the minds of young people, in conjunction with the taught elements of digital education, otherwise we can mentally destroy them in the long run. The aspects presented in this article refer to young people of medium level of development for whom a digital education strategy is made and those underdeveloped. For the digital age, it is clear that a national strategy for digital education is needed. This must include the competencies and learning outcomes specific to each qualification level in the education system, including teacher training, and the technology required. In this paper we show that at European level important steps have been taken in this direction, there is an Action Plan based on a recommendation of the Council, supplemented with competencies and related levels. Thus, we are presenting a proposal for coordination between the levels of digital skills and those of education and qualifications, which should come to the aid of those entitled to regulate the situation of digital education.
PROJECT-BASED AND PROBLEM-BASED TEACHING PROGRAMMING

The article reports on the methods and forms of teaching programming used by the authors during the COVID-19 coronavirus pandemic. It describes how the authors communicated and discussed with the learners, how they changed and adapted their full-time teaching to distance learning, how they managed to maintain and adapt the best practices from classical teaching programming, and how teaching aids were changed to practical distance learning. They also analyse the suitability of some methods for distance learning such as problem-based and project-based teaching programming; programming according to instructions; use of classic and interactive electronic textbooks; use of programming courses via the internet; computer game programming, and gamification of programming. The process of programming is highly creative. A good programmer must possess a range of skills that he uses and combines to solve diverse problems. The source code does not mean a strict write-down of an algorithm. The source code reflects the skilful and optimal use of all elements of the programming environment that the programmer uses. Those elements include (besides the flow-control structures, miscellaneous statements like assigning the value, subroutine call, doing various operations and likewise) standard (ordinal or primitive) and compound data types and data structures (records, sets, enumerations, classes and similar) of the programming language. The problem solved by the programmer is represented using different data structures defined in the default packages delivered within the standard installation. The process often puts the programmer in defining new data structures (classes) to better express the data needed for the final solution. Encapsulating the data into the suitable classes within the proper data model often noticeably simplifies the solution. Thus, one of the programmer's skills is the ability to transform the problem to the proper data elements (classes) or the proper data model. In other words: to create a valid data model.
THE PROJECT OF TEXT ADVENTURE GAME FOR STUDYING THE PARAMEDICAL ALGORITHMS

First aid skills are the important part of medical's competency. The set of instructions for first aid operations are officially approved by the state. This instruction texts are the algorithms. Medical students are studying these algorithms in the special course. First of all, we convert the instructions from text to the graphical flowcharts (according to ISO 5807-85 standard) for checking the ambiguity and possible misunderstanding. The execution process of such algorithms is one of typical "complex open ended assignments". We have the classification of typical user errors. On the base of this errors we construct the set of alternative choices for all steps of algorithm. Every such set will convert to the answers for multiple choice question (MCQ). There are repeated cyclic question for student (executor): "what you will do?" or "what is your next operation?" We plan to build the special environment for gamification of the learning process. Short version will have only one right way - sequence of answers. Every wrong answer will lead the error message - "your patient is dead" and explanation why it happened. In the more complex model we evaluate the patient state and student can read the comments and the errors list only after the end of the algorithm execution. This year (2020) we plan to make the first iteration: text-based online adventure game, one content set, based on the first aid instructions that are approved in Ukraine. The next iteration will use first aid instructions that are accepted in other countries, starting from countries of EU. We suppose future development of this game will be like a well-known history of evolution of computer games. This project will be part of the second co-author PhD thesis
Implementation of a Research-oriented Model of Learning in the Subject Technique in Lower Secondary Education with a Focus on the Cognitive Domain

In this paper, attention is paid to the inquiry-oriented model of students’ education in the subject Technique in lower secondary education. The proposed model reflects the long-term needs of students’ education in the subject Technique, which, in spite of the updated content of the curriculum in the Educational Standard of the subject Technique, have not yet been fulfilled. These issues are addressed within the KEGA project No. 006UMB-4/2022 in the years 2022–2024. The project is funded by the Ministry of Education and Science of the Slovak Republic. In the article we present basic information about the background, objectives, about the research team and the planned outputs of the problem.
Personalized Decentralized Federated Learning with Knowledge Distillation

Personalization in federated learning (FL) functions as a coordinator for clients with high variance in data or behavior. Ensuring the convergence of these clients' models relies on how closely users collaborate with those with similar patterns or preferences. However, it is generally challenging to quantify similarity under limited knowledge about other users' models given to users in a decentralized network. To cope with this issue, we propose a personalized and fully decentralized FL algorithm, leveraging knowledge distillation techniques to empower each device so as to discern statistical distances between local models. Each client device can enhance its performance without sharing local data by estimating the similarity between two intermediate outputs from feeding local samples as in knowledge distillation. Our empirical studies demonstrate that the proposed algorithm improves the test accuracy of clients in fewer iterations under highly non-independent and identically distributed (non-i.i.d.) data distributions and is beneficial to agents with small datasets, even without the need for a central server.
A new 3D P-wave velocity model for the greater Alpine Region from 24 years of local earthquakes data.

The European Alps and its surrounding mountain belts (e.g., the northern Apennines, the northwestern Dinarides, and the western Carpathians) forms a tectonically complex system, referred as the &amp;#8220;greater Alpine region&amp;#8221; (GAR). Although being extensively &amp;#160;investigated, the evolving dynamic tectonic system and microplates relation are still under debate.From 2016-2019 the AlpArray project, with its seismic network of ~700 broadband sensors, created an unprecedented chance to uniformly investigate the recorded seismicity in the GAR. After the successful compilation of the AlpArray research seismicity catalog (AARSC, Bagagli et al., 2022) we took a major leap to repick the seismicity reported by the European-Mediterranean Seismological Centre (EMSC) from May 2007 to December 2015. We use the same approach as for the AARSC to repick and consistently relocate 1397 events. Eventually, we consistently and homogeneously re-calculated the local magnitudes on the vertical component only (MLv). This allows a better data selection for the inversion stages, avoiding the magnitude scales mixing reported in bulletins. In addition to these two dataset, we also use the already published dataset for the latest GAR tomography spanning the time-period from January 1996 to May 2007 (Diehl et al., 2009). These three combined dataset have an average picking error observations of 0.2 seconds and provide an unique opportunity to perform a local earthquake tomography (LET) in the GAR.We select 2343 MLv &gt;=2.5 well-locatable events (azimuthal gap &lt;180 degree, number of P-observations &gt; 7) for the calculation of a new Minimum 1D model for the GAR. For the inversion procedure, we select 2285 events for a total of 84664 rays. The 99% of the rays are shorter than 350 km. We use SIMULPS software to derive the 3D P-wave velocity model using a model parametrization of 20x20x10 km cells in the well-resolved area.&amp;#160;The preliminary velocity model correctly delineates the GAR major tectonic features, and due to the dense ray coverage it provides excellent resolution of the shallow crustal heterogeneities. This model will help the seismological community push forward the understanding of the GAR geodynamics.