Reviewerly/exHarmony huggingface dataset:
A modular approach to Hybrid Blockchain-based and Relational Database Architectures

In this new cloud-powered web landscape, applications may find it beneficial to focus on both efficient data storage and proper security enforcement. Blockchains provides immutable and irrefutable data, but can be quite slow, while relational databases show great efficiency. MOON is a tool designed to act as a bridge between application and databases to create a hybrid approach to database management. It enables the use of both a Relational Database and a Blockchain-based database. This paper analyzes and proposes improvements to MOON's architecture to increase compatibility, maintainability, and help advance research into the area of convergence between blockchain and traditional databases.
CoFFee: A Co-occurrence and Frequency-Based Approach to Schema Mining

A wide range of applications use semi-structured data. A characteristic of these data is that they are heterogeneous and do not follow a predefined schema, i.e., schema-less. The lack of structure makes it difficult to use this data since many applications depend on it to perform their tasks. Thus, we propose CoFFee, a schema mining approach that, given a set of heterogeneous schemas, provides a summarized schema containing a set of core attributes. To this end, CoFFee uses a strategy that combines co-occurrence and frequency of attributes. It models a set of entity schemas as a graph and uses centrality metrics to capture the co-occurrence between attributes. We evaluated CoFFee using data extracted from six DBpedia classes and compared it with two state-of-the-art approaches. The results achieved show that CoFFee produces a summarized schema of good quality, outperforming the baselines by an average of 22% of the F1 score.
Outlier detection with ontology-driven fault contextualization in the Industry 4.0

In the industrial sector, outlier detection makes it possible to quickly identify equipment failures. The evolution of Industry 4.0 is bringing challenges previously uncommon in the area. The large number of data constantly generated represents a processing challenge and can lead to the identification of a large number of outliers simultaneously. This scenario slows the troubleshooting process, delaying the identification of the source of the fault. This work presents a solution to support decision-making in a widespread failure scenario. Dependencies are represented using ontologies, to provide a clear and user-facilitated interpretation. An inference engine is used to identify the most probable causes of the failure. Performance tests demonstrate its scalability.
Adaptive Fast XGBoost for Binary Classification

Modern machine learning algorithms must be able to fast consume data streams, maintaining accurate results, even with the presence of concept drift. This work proposes AFXGB, an Adaptive Fast binary classification algorithm using XGBoost, focusing on the fast induction of labeled data streams. AFXGB uses an alternate model training strategy to achieve lean models adapted to concept drift. We compared AFXGB with other data stream classifiers using synthetic and real datasets. The results showed that AFXGB is four times faster than ARF and 22 times faster than AXGB, maintaining the same accuracy and with the fastest recovery from concept drifts, thus preserving long-term accuracy.
SIFAT WAJIB ALLAH DALAM KARYA SENI GRAFIS

The making of the final work of graphic art, this serigraphy technique is to visualize the mandotory nature of Allah, including calligraphy and chat serigraphy techniques using several color prints besides that it is also useful for pairing concepts and techniques for working in graphic arts. There are several stages in carrying out this final work including preparation, elaboration, synthesis, concept realization and completion stages. Thus, ten graphic art works that visualize the mandotory nature of Allah titles: first " Wujud ", second " Qidam ", third " Baqa ", fourth " Wahdaniah ", fifth " Qudarat ", sixth " Iradat ", seventh " Ilmu ", the eighth " Sama ", the ninth " Basar " and ten " Qalam ".Kata Kunci: Sifat Wajib Allah, arti , Seni Grafis.
PERSEPSI SISWA TERHADAP PEMBELAJARAN DARING MATA PELAJARAN SENI BUDAYA MATERI SENI RUPA KELAS VII DI SMP NEGERI 12 PADANG

The purpose of this study was to find out students' perception of online learning of Art and Culture subjects of Fine Arts Class VII at SMP Negeri 12 Padang. This research method uses a type of descriptive quantitative research. Data collection techniques in this study use questionnaire instruments and data analysis techniques using descriptive statistics with percentages. The population in this study amounted to 295 students of Grade VII SMP Negeri 12 Padang using Simple Random Sampling technique so as to determine the number of samples 20% of the total number of students is 61 students of Grade VII SMP Negeri 12 Padang. Based on the results of the overall research, it was concluded that students' perception of online learning of Art and Culture subjects in Fine Arts Class VII at SMP Negeri 12 Padang with a perception criteria score of 1.46. So it can be said that the perception of Grade VII students towards online learning in the category is very lacking.Keywords: perception, online learning, fine arts
ANALISIS METODE PEMBELAJARAN DARING TERHADAP HASIL BELAJAR SISWA KELAS VIII PADA MATERI SENI RUPA SMP N 24 PADANG

This study aims to analyze the online learning process and analyze the effectiveness of online learning of grade VIII students at SMP N 24 Padang. This research uses qualitative approach that is descriptive analysis. The collection techniques in this research are literature studies, interviews, observations and documentation. The steps to analyze the data are data collection, display data, data reduction and conclusions/verifying. The results of this study are 1) The online learning process using the Geachool application, the teacher must have a Geschool account first, the Geschool application has a party or admin who collaborates with Google and the admin contracts to the SMP N 24 school. Padang is because at this time the learning process is carried out using the online learning method. After the teacher has an account, the admin explains what features are in the Geschool, namely: Whas's up feature, Gebook feature, Getop feature, Getrol feature, 2) Online learning is still not effective because in the online learning process it is still found. There are many obstacles, ranging from teachers who do not understand and master the application and the application of a teaching model whose features are limited to the very limited understanding of students receiving information from the Geschool given by the teacher. Effectiveness in online learning is something that must be considered in order to maximize student learning outcomes.Keywords: analysis, online learning, student learning outcomes
PENGEMBANGANaBAHAN AJAR SENI RUPA BERBASIS ELEARNING DENGAN MENGGUNAKAN WORDPRESSaUNTUK SISWA KELAS VIII SMP NEGERI 2 GUNUNG TALANG

This research aims to produce art teaching materials based on e-learning using wordpress that is valid and practical. The development model used is a 4-D model which consists of defining (defining), designing (designing), developing (developing), and distributing (disseminating). This research was only conducted until the development stage due to time constraints. This e-learning-based teaching material has been revised based on suggestions and comments from expert validators consisting of 4 art lecturers, 1 language lecturer, and 1 cultural arts teacher. E-learning based teaching materials are developed using wordpress. This development was carried out with a small-scale test consisting of 10 class VIII students of SMPN 2 Gunung Talang. The validation results obtained from the validation sheet given to the validator were with an average of 91.25% which was stated to be very valid. And the practicality test results given to students were stated to be very practical with an average of 82.7%. Based on the results obtained, it can be said that e-learning based teaching materials on model materials and illustration images are valid and practical.
Bayesian Deep Multi-Agent Multimodal Reinforcement Learning for Embedded Systems in Games, Natural Language Processing and Robotics

Nowadays, Machine Learning is one of the most dynamic fields, as it attracts strong research interest from both industry and academia alike. It is not surprising that a huge amount of funding from government agencies, universities, Tech giants and well-funded startups is currently being allocated exclusively to this field. Reinforcement Learning, one of the three major subfields of Machine Learning, has recently gained a tremendous traction due to the fact that algorithms can run more efficiently. This is mainly due to two reasons, firstly affordable and portable hardware, such as mobile phones, wearables and Internet of Things devices, now has the capacity to run these algorithms and secondly, new methods and models are being proposed that deal with the matter of efficiency from an algorithmic point of view. This proposal is concerned with dealing with open challenges in memory efficiency, while devising and applying such Reinforcement Learning algorithms for embedded systems in the domains of Games, Natural Language Processing and Robotics using Deep Learning models and Bayesian inference, a very powerful framework. Natural Language Processing is a domain of Machine Learning in which the input is given in the form of a text from a natural language that human agents use for everyday communication. It is also a domain that still faces a series of ongoing challenges, as opposed to more saturated domains, such as Computer Vision. One of them is the fact that ground truth is difficult to be decided due to the nature of text in general. Other challenges include the personalized type and tone of the conversation held by the human agents, such as formal, informal, aggressive, polite, etc. Therefore, this proposal deals with all of these matters, mainly in the subdomain of Question Answering systems, also known as chatbots, in a multi-agent setting.
Ecomindsponge theory: positioning humans in the ecosphere

We propose the theory of ecomindsponge to focus on examining the human information processing system in relation to the Earth’s ecosphere. This can help in the quest of knowing where we stand in this Universe and the basic mechanisms of how we interact with the natural environment.
Kepuasan Peserta Diklat Terhadap Penggunaan Mentimeter Sebagai Metode Pembelajaran Latsar CPNS Milenial Kabupaten Kampar

Participants in the Basic Training for Candidates for Civil Servants at BPSDM Riau Province are millennials, attached to technology, digital learning applications, and provide satisfaction to them, in this case using Mentimeter as a learning application. In a quasi-experimental way, this study describes the perception of the participant's satisfaction scale on the use of Mentimeter as a learning application for the Millennial Generation Civil Servant Latsar Class E Class E, Kampar Regency at BPSDM Riau Province. Satisfaction scale is measured through tangibles, reliability, responsiveness, assurance, and empathy. This finding proves that as a millennial generation learning application, the satisfaction of CPNS Latsar participants with the use of Mentimeter is at the "Very Satisfactory" level because the mean value of satisfaction in each dimension is on a scale of 4.30 - 5.00. The use of a Mentimeter is also appropriate because it can answer the challenges and developments of the times that are attached to information and digital technology. Utilizing Mentimeter implies that it is important for education and training providers, especially BPSDM Riau Province to always maintain satisfaction and improve learning service innovation according to the needs of millennial generation CPNS Latsar participants. The next recommendation is very possible to evaluate digital learning so that the Mentimeter application can be effectively used by various groups of learners.
An Enhanced ELECTRE II Method for Multi-Attribute Ontology Ranking with Z-Numbers and Probabilistic Linguistic Term Set

The high number of ontologies available on the web to date makes it increasingly difficult to select appropriate ontologies for reuse. Many studies have attempted to provide support for ontology selection and ranking; however, the existing studies provide support for ontology ranking from an objective perspective as opposed to a subjective perspective. They do not take into account the qualitative aspects of ontologies. Furthermore, the existing methods have a limited focus on group environments. In this paper, a multi-criteria decision-making approach is presented for ontology ranking with the development of an enhanced model combining the ELECTRE II model with the Z-Probabilistic Linguistic Term Set (ZPLTS). The ZPLTS-ELECTRE II model enables decision-makers to model ontology ranking problems using both numerical and linguistic data. Furthermore, the newly proposed model provides support for ontology ranking in group settings, with an emphasis on modeling the differing levels of credibility of decision-makers using the ZPLTS, which allows decision-makers to not only specify their opinion but also specify their level of credibility. The model was applied to rank a set of mental health ontologies obtained from the BioPortal repository. The results showed that the method was able to rank the ontologies successfully. The results were further compared with the traditional ELECTRE II and the PLTS ELECTRE II methods, displaying superior modeling capabilities. This paper demonstrated the effectiveness of the newly proposed ZPLTS-ELECTRE II model for ontology ranking in a real-world context, but the method is not constrained to the ontology ranking domain; rather, it may be applied to other real-world decision problems as well.
Studying Future Educational Psychologists’ Readiness for Innovation Management Competencies in Universities of Kazakhstan

The aim of the research is to analyze the professional readiness of future high school educational psychologists for innovative management activities.The effectiveness of innovation management activities in the educational environment depends on educational psychologists' acquired competencies.The experimental study included a survey of 320 graduate students majoring in Pedagogy and Psychology at eight leading Kazakhstani universities and regional experts' assessment on the readiness of graduates for innovative managerial work in educational institutions.The sampling technique used to select the sample audience is the convenience based, exponential non-discriminative snowball sampling where the initial subjects are recruited from campus or through social groups based on ease of accessibility and the rest are selected based on referrals made by the selected students.The article reveals the importance of the personality component of educational psychologists' professional readiness for innovative management.In addition, it gives an expert assessment of the effectiveness of training educational psychologists for innovative management in educational institutions.Studying the future educational psychologists' readiness for innovative managerial competencies remains relevant for researchers.It is associated with the need for purposeful investigation and formation of professional competencies according to general patterns and alterations in vocational training in higher educational institutions.In this regard, educational psychologists' training with managerial competencies should become one of the priority directions of practical psychology development in Kazakhstan.
Korean Preservice Teachers’ Perspectives on Flipped Learning in the EFL Context

This study investigated preservice teachers’ perspectives on flipped learning approaches in the EFL context in Korea. Fifteen preservice teachers agreed to participate in this study. Major data sources were focus group and interviews. These sources were audio-recorded and transcribed verbatim. Then, the transcripts were interpreted and analyzed through thematic analysis to explore individuals’ thoughts and opinions in depth. Findings revealed that the participants had positive thoughts and attitudes toward flipped learning. They thought that flipped learning increased their autonomy and self-regulation. The participants also addressed several benefits and shortcomings of flipped learning. Implications of research and pedagogy are discussed in the final section of this study.
Complex Business Intelligence Queries in Natural Language

Natural Language Interface to Database (NLIDB) eliminates the need for an end user to use complex query languages like SQL by translating the input natural language state-ments to SQL automatically.Although NLIDB systems have seen rapid growth of interest recently, the current state-ofthe-art systems can at best handle point queries to retrieve certain column values satisfying some filters, or aggrega-tion queries involving basic SQL aggregation functions.In this demo, we showcase our NLIDB system with extended capabilities for business applications that require complex nested SQL queries without prior training or feedback from human in-the-loop.In particular, our system uses novel al-gorithms that combine linguistic analysis with deep domain reasoning for solving core challenges in handling nested queries.To demonstrate the capabilities, we propose a new benchmark dataset containing realistic business intelligence queries, conforming to an ontology derived from FIBO and FRO financial ontologies.In this demo, we will showcase a wide range of complex business intelligence queries against our benchmark dataset, with increasing level of complexity.The users will be able to examine the SQL queries generated, and also will be provided with an English description of the interpretation.
Gaps in the Colombian Education System and the Commitment of Young Entrepreneurs with the Support of ICTs

This research aims to associate and analyze different concepts such as Socio-Formative Evaluations; Leadership; coverage of information and communication technologies and education; and B Corporations. All this in order to be able to relate it to the educational processes in Colombia and also the contribution that students and/or graduates can make to higher education institutions. This is a qualitative research of documentary review type, its purpose is to be able to conceptualize and reveal connections of great importance with the topics treated, based on other measurements and reviews of theories previously carried out. A consultation of bibliographic sources and direct sources of information was carried out.
Sinüs Toplam Modeli ile Küresel Güneş Radyasyon Tahmini

Renewable and clean energy sources are currently needed for the long-term growth of nations and to decrease the negative environmental effects of fossil fuels. One of the most significant sources of energy is solar energy. Understanding the radiation properties of the solar energy is crucial for making the most use of solar energy in a certain region. In addition, reliable solar energy measurements are necessary for research into climate change, one of the most pressing problems confronting humanity today. Nowadays, solar energy harvesting systems are widely used to satisfy the world's increasing energy needs. Satellite-based solar radiation forecasts currently provide the high spatial and temporal resolution, global, diffuse, and direct sunlight data needed for solar power system planning and efficient utilization. In this study, the solar radiation values of the determined area were estimated using sum of sine model for n=1,n=2,n=3 in the Matlab program. Several statistical error analysis tests were used to evaluate the performance of the developed models. The estimated solar radiation values demonstrate how effectively the proposed prediction models performs.
Integrating augmented reality technology to enhance student's learning in physical education

In practically every professional sport, the usage of linked computerized performances and monitoring components, data analysis, augmented and virtual reality are standard things. Augmented reality in sporting is being shaped by the interaction of devices and information and communication technology advances. Nevertheless, without analysis, the data collected are useless. In the sporting industry, scientists and researchers are becoming more and more essential to human operations. Even if a variety of data, technology, new measurements, and analytics are readily available on our life, most participants in professional sports do not yet show a strong interest in sports analysis. In this study, we explore augmented reality tools in sport activities and consider augmented reality tools to improve health conditions of students at the universities.
The role of psychological safety in online tourism and hospitality learning

This study proposes and tests a conceptual framework to examine how tourism and hospitality students’ psychological safety and personal resourcefulness in online learning reach their tourism and hospitality threshold learning outcomes. This research develops a conceptual framework integrating the conservation of resources and social information processing theories and the findings of a qualitative study through a sequential mixed-methods approach. Subsequently, the model is tested with online survey data using a structural equation modelling technique. The results suggest that, for psychological safety, students’ computer self-efficacy and peer collaboration significantly affect overall students’ perceived graduate outcomes, whereas lecturer support has no significant impact. Further analysis of the results, along with theoretical and practical implications, are likewise discussed.
A holistic analysis to identify the efficiency of data growth using a standardized method of non-functional requirements in graph applications

In the modern era, several opportunities are provided to transfer data through graph models in which digital transformation plays a vital role. Maintaining the data using several devices will cause a processing time delay. Data collection is an important task in all data processing units, as is storing this type of information, as is providing security on this data through a database. To improve this process, the data retrieval is done using a graph data model. The proposed method is used to find the best way to store each record in a graph database rather than in another cloud or distributed database. In this, various techniques used in providing a better solution for data processing are done on graph databases without schema. To provide a good solution without any time delay, the graph analytics algorithm will help in making decisions on better results. In this method, many applications will be taken as case studies for finding the best relationship on the given graph database. In this, the collected data will be converted into graph format, an easy way of finding the duplication. The data model generated on each vertex is converted into low- and high-dimensional data forms. This chapter will go over a number of real-time Neo4j applications that are used to find optimal relationships on various datasets in an efficient manner.