Reviewerly/exHarmony huggingface dataset:
PENINGKATAN PRESTASI BELAJAR SISWA KELAS III MELALUI PENERAPAN MODEL KOOPERATIF JIGSAW PADA MATA PELAJARAN MATEMATIKA TEMA 8 SD ANAK SHOLEH FULL DAY

The purpose of this study is to determine the application of the Jigsaw learning model in improving learning achievement in thematic subjects of third grade mathematics at SD Anak Sholeh FULL DAY. The type of research used is Classroom Action Research with quantitative and qualitative approaches. The PTK model used is the Kemmis and Mc Taggart model, the researchers carried out research through two cycles, namely cycle I and cycle II. With the following steps: 1) Planning, 2) Implementation, 3) Observation, 4) Reflection. The data collection instruments used include the Student Monkey Sheet (LKS), end-of-cycle test questions, observation sheets for the application of the model, and field notes. The results showed that through the application of the Jigsaw Cooperative Learning model it was proven to be able to improve student achievement. In the first cycle, the percentage increase in learning achievement was 62.50% and in the second cycle it was 84.37%. The results of the N-Gain Score get an average of 2.90 or high category. In the sense of increasing learning achievement in the second cycle increased. It was concluded that learning using the jigsaw cooperative learning model could improve student achievement.&#x0D;
UJI PRAKTIKALITAS PENGEMBANGAN LKPD DENGAN MENGGUNAKAN MODEL PEMBELAJARAN PROJECT BASED LEARNING PADA MATERI PENGUMPULAN DAN PENYAJIAN DATA

This study aims to determine the practicality development of Project Based Learning worksheets. At the practicality stage, the LKPD with the project based learning model includes very practical criteria with an average percentage of 89.78% with details of the teacher response questionnaire 90.62% and the student response questionnaire 88.59%. Based on the results of the study, it can be concluded that the LKPD in collecting material and presenting data using the project based learning model meets very valid and very practical criteria to be used as one of the learning materials in learning mathematics, especially for fifth grade students in elementary schools.&#x0D; Keywords: Practicality, LKPD, Project Based Learning
Corrigendum: Deep-learning-based surrogate model for fast and accurate simulation in pipeline transport

CORRECTION article Front. Energy Res., 09 December 2022Sec. Advanced Clean Fuel Technologies Volume 10 - 2022 | https://doi.org/10.3389/fenrg.2022.1109184
Design and Implementation of Campus Roaming Platform Based on Virtual Reality Technology

The concept of digital campus has gradually become an important trend in the development of colleges and universities.Virtualized campus is an important part of the digital campus.Virtual campus based on virtual reality technology, it builds a virtual campus scene that is immersive and interactive on the basis of campus real scene.This paper uses the Unity3D engine as a development platform to construct a virtual campus roaming system with interactive functions through simulation and 3D modeling.Compared with the traditional picture display way, the virtual reality system can show the campus landscape more intuitively.
Character data processing: from simple to complex

The article proposes multi-level materials for students of grades 7–8 to master the theme "Character data processing" in the Python programming language. The first level of complexity involves consideration of the minimum theoretical information and basic algorithms for processing character data, including algorithms for texts editing (replacing a character, deleting and inserting a character, searching for an occurrence of a given pattern); the material is aimed at students who master informatics at a basic level. The second (advanced) level of complexity implies not only actual knowledge of the material being studied, including string processing methods, but also the ability to apply it in new situations; the material can be offered to the basic school students who master informatics at an advanced level. The third (high) level of complexity involves the acquaintance of students with the Olympiad tasks; the material is aimed at the most prepared and motivated students. Working with string data, implemented at different levels of complexity, can become both an alternative and a supplement for tasks with a mathematical context, traditionally included in the content of the informatics course of the basic school.
A Modular Framework for the Analysis of the Dates Found in Manuscripts Written in the Tamil and Tamilian Grantha Scripts

This article focuses on the analysis of the dates included in the scribal colophons found in manuscripts written in the Tamil and Tamilian Grantha scripts. In order to better investigate and understand different scribal patterns, a new approach has been adopted: the dates are conceived as modular entities, which can conveniently be segmented into smaller constituents, referred to as ‘submodules’. In turn, these submodules will be scrutinised from the point of view of their constituents and their mutual relationship.
Elements of the methodology of teaching the theme "Raster computer graphics" with the help of the GIMP free graphic editor at the level of basic general education

The article describes the framework of the methodology for teaching basic school students the technology of both processing digital photography and creating raster graphic images from scratch. As a software tool, it is proposed to use the free GIMP raster editor. Raster computer graphics is more complex in relation to vector graphics, since a large number of tools are used in raster graphics, and brush graphic tools (Brush, Pencil, Airbrush) are also actively used, the effective use of which requires user of basic artistic skills. The choice of the free graphic editor GIMP is due to a number of significant advantages of this software tool over analogues. These include the GNU GPL license for its use, cross-platform, relatively low system requirements, functionality close to professional raster editors, as well as a significant stack of educational and methodological literature on the technology of using GIMP in the educational process, that is generally not typical for free software. The complex user interface of the GIMP editor is due to the large number of tools and the full functionality of this software and can be mastered by basic school students, provided that an effective methodology for teaching raster graphics is used in the educational process. When creating a framework for teaching schoolchildren about raster graphics, the technology for using all groups of GIMP editor tools is demonstrated in the process of conducting practical work aimed at creating various raster graphics, the complexity of which gradually increases in proportion to the number of tools mastered by students. Also, the proposed teaching methodology takes into account all the main structural elements of professional raster graphics, namely: the technology for the effective use of the group of operations for selecting image fragments, the technology for the effective use of the group for the transformation operation, the technology for the effective use of the group of drawing tools, image layers, color channels, contours, built-in filters, creation of text elements, creation of GIF-animation.
Checklist on the theme of the lesson as a means of feedback for the teacher

The aim of a modern teacher is to create conditions for the personal, emotional and mental development of students, to include the processes of self-reflection and self-assessment in class activities to form the internal motivation of students. An analysis of the overall picture of students' understanding of the theme of the lesson, the proportion of students who have mastered the theme and have a problem with mastering, can provide the use of such a feedback tool as a checklist. The article discusses the use of checklists in an informatics lesson, the features of creating checklists on the theme of the lesson, and provides samples of checklists used in informatics lessons in grades 5–9. The proposed samples of checklists, developed taking into account the requirements of pedagogical design, are an effective means of feedback for the teacher and contribute to the development of students' skills of self-control, self-assessment, self-analysis and self-correction.
Past, Present and Future of Teaching-Learning Process in Romania

Abstract Education in Romania has been the reason for debate ever since the communist regime was abolished. Although a lot of reforms and actions to improve the system have been done in the last decades, there are still a lot of issues to be solved that prevent its innovation and efficiency. Moreover, the global pandemic has proved once more that Romania is not prepared for this century of fast technological changes, having an educational system abounding in old methods of teaching, overnight impractical reforms, untrained teachers, and a high rate of school dropout. This article intends to address important issues and present some solutions to improve the teaching-learning process in Romania no matter of the form it might take in the future. Qualitative and quantitative methods were used to collect the necessary data to have a better image of the obstacles that prevent our country from providing high standard education. The main conclusion of the research is that the teaching-learning process in our country needs to be rigorously improved in order to prepare the future generations of students for the demands of today’s society. Through analysing in-depth the mistakes of the past and learning from the present shortcomings, a long-term vision for success with real educational goals can be achieved in the future.
Pengaruh Permainan Kosakata Bahasa Inggris Melalui Digital Smart Board For Kids Terhadap Perkembangan Bahasa Anak Usia 5-6 Tahun di Era Merdeka Belajar

This research will use the Digital Smart Board for Kids game as a means of learning English vocabulary for young children. This study uses a type of quantitative research using a pre-experimental design with one group pretest-posttest. The research subjects in this study were 15 children aged 5-6 years. The selection of subjects takes into account the application of foreign languages, especially English in teaching and learning activities in kindergarten. Data collection techniques using observation and documentation. To draw conclusions from the research results, a hypothesis test was carried out using the t-test. Before conducting the t-test, the normality test and homogeneity test were first carried out on the research results. Where the alpha value is more than 0.05, the data is considered good and reliable. Hypothesis testing was carried out to determine the effect of English vocabulary games through the Digital Smart Board for Kids on the language development of children aged 5-6 years in the independent learning era. This Digital Smart Board game for kids can be played by all children, so that development in the classroom becomes more applicable, contextual and interesting. In conclusion, the Digital Smart Board game for kids can be used to develop children's language development properly, especially in terms of understanding, remembering and pronouncing/imitating English vocabulary in children aged 5-6 years in the era of independent learning.
Proposal for the Development of Educational Software for Elementary School Students in Eastern Yucatan, Mexico

Nowadays, technology is of great importance in our daily activities and several of the technological systems that are implemented help us reducing, among others, the time to perform our activities, as it happens with the time invested to acquire knowledge.Taking advantage of the use of technological devices arises the idea of developing educational software for public elementary schools in the east of the State of Yucatan, to help the teaching-learning process and thus reduce the educational backwardness in them.This paper describes the development under the eventdriven programming paradigm of some educational software, that will be of great help to teachers of public elementary schools by facilitating the learning of their students in some subjects such as mathematics, geography and Mayan culture.
Implementing a Theory of a Legal Domain

We describe a system for constructing, evaluating and visualising arguments based on a theory of a legal domain, developed using the Angelic methodology and the Carneades argumentation system. The visualisation can be used to explain particular cases and to refine and maintain the theory. A full implementation of the well known US Trade Secrets Domain is used to illustrate the process.
An End-to-End Pipeline from Law Text to Logical Formulas

We propose a pipeline for converting natural English law texts into logical formulas via a series of structural representations. Text texts are first parsed using a formal grammar derived from light-weight annotations. An intermediate representation called assembly logic is then used for logical interpretation and supports translations to different back-end logics and visualisations. The approach, while rule-based and explainable, is also robust: it can deliver useful results from day one, but allows subsequent refinements and variations.
Fundamental Revisions on Constraint Hierarchies for Ethical Norms

This paper studies constraint hierarchies for ethical norms, which are unwritten and may be relaxed if they conflict with stronger norms. Since such ethical norms are unwritten, initial representations of ethical norms may contain errors. For correcting those errors, this paper examines fundamental revisions on constraint hierarchies for ethical norms. Although some revisions on representations for ethical norms have been suggested, revisions on constraint hierarchies for ethical norms have not been completely investigated. In this paper, we categorize two fundamental types of revisions on such constraint hierarchies, namely preference revision and content revision. We also compare effects of those revisions in the criteria of syntactic and semantic changes, which are common criteria of revisions on legal theories. From the comparison, we found that preference revision tentatively makes lower syntactic changes. However, its computation is intractable, incomplete, and potentially makes a large number of semantic changes. On the other hand, we show that content revision on constraint hierarchies can make a small number of semantic changes. However, the content revision tentatively produce a large number of syntactic changes. This comparison leads to the possibility of optimization between preference revision and content revision, which we think is an interesting future work.
Legal Text Summarization Using Argumentative Structures

Legal text summarization focuses on the automated creation of summaries for legal texts. We show that the argumentative structure of judgments can improve the selection of guiding principles as a specific kind of summary using judgments of the German Federal Court of Justice as measured by the ROUGE metric. We evaluate our first results and put them in the context of our ongoing work.
An Automata-Based Formalism for Normative Documents with Real-Time

Deontic logics have long been the tool of choice for the formal analysis of normative texts. While various such logics have been proposed many deal with time in a qualitative sense, i.e., reason about the ordering but not timing of events, it was only in the past few years that real-time deontic logics have been developed to reason about time quantitatively. In this paper we present timed contract automata, an automata-based deontic modelling approach complementing these logics with a more operational view of such normative clauses and providing a computational model more amenable to automated analysis and monitoring.
Ontology Construction for Building Fire Emergency Response

The fire investigation report in the past ten years shows that all kinds of building fire is always the most frequent fire type. In this paper, B-FERO2 ontology model for building fire emergency response is established on the basis of clarifying the research scope of building ontology and its own breadth and depth. First, upper ontology of building fire emergency response is established. Then, the ontology model is constructed from the aspects of building fire response process, response role, fire extinguishing mode and so on, and Protege method is selected to implement the building fire emergency response ontology. Finally, the validity and integrity of the ontology model of building fire emergency response are tested by qualitative evaluation method.
Building a “Blockchain+” Short Video Push System

The “blockchain+” short video push system is an important field worthy of study in the current short video platforms. Blockchain technology is used to effectively promote the processing speed of short video platforms for user portraits and strengthen the intelligent audit of short video contents according to its unique characteristics, such as decentralized and multi-node. In this paper, we will discuss the data processing, calculation management and application methods of short video push system based on blockchain technology, to elicit the new development of short video push system.
Estimating Hidden Parameters from a Dataset with Large Amount of Missing Data

Dealing with missing data is a fundamental problem in data science. In some rare cases, the large amount of missing data can be a big problem for any data analysing tasks. In this paper, we propose a method based on maximum likelihood estimation and expectation maximization to get estimation on the hidden parameter with large amount of missing data in the dataset. We perform the numerical experiments to validate the feasibility and stability of our method. We test the algorithm for different patterns of missing data, different amount of samples and different noise levels. The result indicates that the algorithm is effective in handling large amount of missing data if enough samples are provided.
Evaluation and Optimization Method of Enterprise Data System Based on FAHP-CEEMDAN

In order to help enterprises obtain greater data analysis advantages and optimize enterprise data system, this paper proposes a data evaluation optimization model. The model uses the index weight analysis method, empirical mode decomposition algorithm by improving the collection, calculation of expert judgment weight of the signal as the data system of subjective evaluation weight value, and through the fuzzy measurement analysis method, the weight is compared with the weight of the actual data system of the enterprise, calculate the maturity of the system and reflect the current state of the data system, so as to analyze and optimize the data system and reflect the competitive advantage and data value of the enterprise The experimental results show that the data analysis model is objective and effective, which is of great help to enterprise data system optimization.
An Entity Relationship Extraction Model Based on BERT-BLSTM-CRF Algorithm for Cosmetics Domain

In view of the lack of timeliness in the regulation of the cosmetics field, we establish a model for extracting the relationship between entities in the cosmetics field, assist the relevant departments in building an intelligent regulatory system, and rely on data to achieve scientific decision-making and effective regulation. In this paper, we use the BERT (Bidirectional Encoder Representations from Transformers) network model to train the word vectors, and combine the BLSTM (bidirectional long short-term memory) network with the fused positional attention mechanism to perform entity relationship extraction, and the extracted relationship features extracted by the BERT neural network are incorporated into the word dimension text vector, and then the entity pairs are extracted by the BLSTM with the fused positional attention mechanism, and finally the predicted labels are decoded by CRF (Conditional Random Field). The experimental results show that the BERT-BLSTM-CRF-based entity relationship extraction model in cosmetics domain constructed in this paper exhibits good feature extraction and classification performance.
Approximation of Broad Learning System and Convolution Function Applied on Face Classification

Broad Learning System (BLS) is a very fast and effective discriminative learning which is developed by C. L. P. Chen, Z. Liu and others. It avoids the shortcomings of complex model design and large amount of calculation in deep learning. This paper studies the approximation capability of BLS for continuous functions defined on a compact set. It is proved that if the activation function of the enhancement node of BLS is not polynomial, for any continuous function f(x)∈C(K) defined on the compact set K, there is limmq→ ∞,nk→ ∞‖f(x)-fw(x)‖22=0, that is ∀ ε&gt;0, ∃nk ∈ N, mq∈N’, and parameter set w, so that ‖f(x)-fw(x)‖22&lt;ε. A reconstructed model of BLS which is combined the CNN network with the BLS is applied to numerical experiments. The semi-supervised broad learning system(SS-BLS) and its algorithm are proposed. Then, SS-BLS and convolution function are combined to establish SS-CBLS, the numerical experiments of SS-CBLS on face classification are carried out by ORL and Yale face database respectively
Forward-Backward Diffusion and Pruning-Based Cost Aggregation for Non-Local Stereo Matching

Minimum spanning tree (MST) has been devised for non-local cost aggregation to solve the stereo matching problem. However, the cost aggregation is employed directly from leaf toward root node, then in an inverse pass without considering any decision rules. And a small amount of noise is also existed in stereo image pairs. Both of the limitations often lead to failure in achieving more competitive results. This paper presents a novel stereo matching algorithm using forward-backward diffusion and pruning-based cost aggregation. In “forward-backward” process, the raw image pairs are smoothened on a horizontal tree structure as well as retaining image edges sharp. During cost aggregation, the MST where a complete graph involves the whole image pixels is cut off self-adaptively when the depth edge information is referred to. Each node in this tree receives supports from all other nodes which belong to similar depth regions. Meanwhile, an enhanced edge similarity function between two nearest neighboring nodes is formulated to deal with the small-weight-accumulation problem in textureless regions. Consequently, the cost volume can be well aggregated. The proposed method is demonstrated on Middlebury v.2 &amp; v.3 datasets and can obtain good performance in disparity accuracy compared with other five MST based stereo matching methods.
ST-AGNN: Spatial-Temporal Attention Graph Neural Network for Pedestrian Trajectory Prediction

Accurate and fast prediction of pedestrian trajectory is very important. However, the interaction between pedestrians is complex, pedestrians are affected not only by their own motion but also by the neighboring pedestrians. Some methods do not extract the pedestrian motion features completely. It is easy to ignore a few of important features of pedestrians. The Spatial-Temporal Attention Graph Convolutional Network (ST-AGNN) for pedestrian trajectory prediction is proposed in this paper. ST-AGNN model can extract the spatial interaction features of each time step and stack the spatial features to obtain the spatial-temporal features. It can predict the future trajectory by using Temporal Convolutional Network (TCN). We evaluate the average displacement error (ADE) and final displacement error (FDE) of the proposed method on ETH and UCY datasets. The experimental results show that the proposed method is effective in accuracy and efficiency.