Reviewerly/exHarmony huggingface dataset:
Effect of algebraic language and problem text wording on problem model accuracy when solving age word problems

Abstract The use of the algebraic method for solving word problems is a challenging topic for secondary school students. Students’ difficulties are usually associated with extracting the problem’s network of relationships between quantities and with formalizing these relationships into algebraic language in a problem model. Both sources can coexist and interact; thus, it is usually not possible to determine which source of difficulty is more relevant. In addition, there are specific errors, such as the error by multiple referents for the unknown, which are directly linked to the wording of the problem text, and in which the same two sources of error coexist. In this work, we present the results of an experiment conducted with 255 secondary school students assessing the effect of two common difficulties on the accuracy of problem models and on the rate of multiple referents for the unknown. The first difficulty is the use of algebraic language in the construction of the problem model; the second is the use of the same expression to designate different quantities within the problem text. We used a 2 × 2 between-between design, with one factor related to the symbolic language (algebraic or arithmetic) in which the problem model is constructed, and the other factor related to the actual language features of the text problem. Our results indicate that overall, the main source of difficulty for students is the use of algebraic language to formalize a problem model, representing a large effect size.
Student Acceptance of Using Apps to Achieve Learning Outcomes in Architecture and Environment

The use of mobile apps for learning is not common in learning of technical modules in architecture, but studies have been advocated to learn its potential two decades ago. E-learning has supplemented traditional learning in Malaysian Universities since 2004. The Covid-19 pandemic forced education to be conducted virtually. Lecturers with knowledge of blended learning were able to switch to virtual learning but had challenges. The challenge of this module is access to environmental lab and data loggers that would need travelling and sharing of devices. Apps for measuring weather data led to minor adjustment in teaching and learning without altering the learning outcome. The students' perception of learning was captured in a survey with 114 responses. The result evidenced that students had a good learning experience by reporting high mean value for all the items. All Pearson's Correlation values showed positive with moderate to very high correlation between the factors. Post-pandemic teaching and learning in universities need to explore the potential of m-learning.
Alternative methods for solving a hyperbolic system of equations in a simplified water hammer problem

The paper addresses a mathematical model of the transient process in a pipeline, namely, a water hammer model. Based on this model, a mixed problem for a system of partial differential equations of hyperbolic type is set. In this paper, we obtain formulas for the exact solution of the Cauchy problem for a linear homogeneous hyperbolic system. We compare the effectiveness of explicit and implicit numerical methods for solving a simplified system of water hammer equations.
Aristotelian Fragments and Subdiagrams for the Boolean Algebra B5

On a descriptive level, this paper presents a number of logical fragments which require the Boolean algebra B5, i.e., bitstrings of length five, for their semantic analysis. Two categories from the realm of natural language quantification are considered, namely, proportional quantification with fractions and percentages—as in two thirds/66 percent of the children are asleep—and normative quantification—as in not enough/too many children are asleep. On a more theoretical level, we study two distinct Aristotelian subdiagrams in B5, which are the result of moving from B5 to B4 either by collapsing bit positions or by deleting bit positions. These two operations are also argued to shed a new light on earlier results from Logical Geometry, in which the collapsing or deletion of bit positions triggers a shift from B4 to B3.
Optimizing the Structure and Parameters of Local Wastewater Disposal System Based on Flow Models

The paper investigates the issues of transporting wastewater from small settlements to centralized sewage treatment facilities, taking into account the use of various modes of transport. For each mode of transport we determined the dependences of life cycle costs on the amount of wastewater flow and its transportation over different distances. Taking into account these dependences we obtained the ranges for the use of road and pipeline transport and developed methods for optimizing the structure and parameters of local wastewater disposal systems.
"Operationalizing collaborative problem-solving skills: A framework for assessment and development in the digital age"

"This article delves into the operationalization of collaborative problem-solving (CPS) skills, focusing on the essential aspects required to effectively apply CPS in the modern digital age. The article emphasizes the growing significance of CPS skills as technology-based work and the automation of routine tasks demand proficiency in addressing non-routine, complex challenges. To enable successful CPS, a new set of skills including information literacy, divergent thinking, and problem-solving, both individually and collaboratively, are explored. The article investigates the strategies and approaches employed by individuals and teams when engaging in collaborative problem solving, with an emphasis on knowledge sharing and skill pooling. The study highlights the criticality of CPS as an invaluable skill set, enabling individuals to effectively collaborate and overcome intricate problems. Moreover, as contemporary work environments increasingly rely on successful group problem solving, the significance of operationalizing CPS is expected to continue growing in the future. Keywords: collaborative problem solving, problem solving, PISA, literacy, Human-to-Human, Human-to-Agent, Twenty-first Century Skills."
Embedding-Based Deep Neural Network and Convolutional Neural Network Graph Classifiers

One of the most significant graph data analysis tasks is graph classification, as graphs are complex data structures used for illustrating relationships between entity pairs. Graphs are essential in many domains, such as the description of chemical molecules, biological networks, social relationships, etc. Real-world graphs are complicated and large. As a result, there is a need to find a way to represent or encode a graph’s structure so that it can be easily utilized by machine learning models. Therefore, graph embedding is considered one of the most powerful solutions for graph representation. Inspired by the Doc2Vec model in Natural Language Processing (NLP), this paper first investigates different ways of (sub)graph embedding to represent each graph or subgraph as a fixed-length feature vector, which is then used as input to any classifier. Thus, two supervised classifiers—a deep neural network (DNN) and a convolutional neural network (CNN)—are proposed to enhance graph classification. Experimental results on five benchmark datasets indicate that the proposed models obtain competitive results and are superior to some traditional classification methods and deep-learning-based approaches on three out of five benchmark datasets, with an impressive accuracy rate of 94% on the NCI1 dataset.
Towards a Unified Architecture Powering Scalable Learning Models with IoT Data Streams, Blockchain, and Open Data

The huge amount of data produced by the Internet of Things need to be validated and curated to be prepared for the selection of relevant data in order to prototype models, train them, and serve the model. On the other side, blockchains and open data are also important data sources that need to be integrated into the proposed integrative models. It is difficult to find a sufficiently versatile and agnostic architecture based on the main machine learning frameworks that facilitate model development and allow continuous training to continuously improve them from the data streams. The paper describes the conceptualization, implementation, and testing of a new architecture that proposes a use case agnostic processing chain. The proposed architecture is mainly built around the Apache Submarine, an unified Machine Learning platform that facilitates the training and deployment of algorithms. Here, Internet of Things data are collected and formatted at the edge level. They are then processed and validated at the fog level. On the other hand, open data and blockchain data via Blockchain Access Layer are directly processed at the cloud level. Finally, the data are preprocessed to feed scalable machine learning algorithms.
Ways to ensure the effective implementation of the Russian education export strategy

The study aims to identify the key areas of the Russian academic, economic and sociocultural sphere that can be positively influenced by the Russian education export strategy in order to specify the ways of organizing educational process and social adaptation of foreign students that would contribute to the most successful implementation of all aspects of this strategy. The paper examines the reasons why states pay great attention to the internationalization of their higher education system and also identifies the main areas of the Russian university environment, economy and culture that are the beneficiaries of the influx of foreign students to the Russian Federation. Furthermore, the scientific work explores the ways to improve the system of higher education that will allow organizing the studying and recreation of foreign students in such a manner that all the most important problems related to the implementation of education export are successfully solved and reflected in Russia’s scientific, industrial and cultural development, both at the national level and internationally. The scientific novelty lies in presenting new ways to adapt the educational process at the university to the educational needs of foreign students, as well as in offering methods for improving the socializing, cultural-educational and career guidance work of universities, which together are able to ensure foreign students’ formation not only as qualified professionals, but also as the professionals with a pronounced positive perception of Russia who respect our culture and seek to cooperate with Russian organizations in one form or another. As a result of achieving the research objectives, the role of education export in the policy of many countries has been determined, which consists in ensuring stable high incomes and in strengthening the leading position of the state on the international stage. The main directions of the academic, economic and sociocultural spheres significantly affected by all the multitude of activities undertaken in the process of education export have been identified. The main parameters of university education that require modernization with regard to the development of the Russian higher education export strategy have been determined. The need for integration of additional disciplines in Russian into the educational route of foreign students throughout the entire course of study at the university has been argued. The need for advanced training of the teaching staff in terms of the methodology of teaching disciplines in Russian as a foreign language has been noted. The importance of the active involvement of foreign students in the university environment and the sociocultural city life has been shown. The correlation between the increase in the number of potential foreign applicants who would like to earn a degree in a Russian university and ensuring the high quality of education for foreign students along with the creation of favorable conditions for their effective sociocultural adaptation has been proved.
Predicting Handling Covid-19 Opinion using Naive Bayes and TF-IDF for Polarity Detection

There are many public responses about implementing government policies related to Covid-19. Some have positive and negative opinions, especially on the official social media portal of the government. Twitter is one social media where people are free to express their opinions. This study aims to find out the opinion of sentiment analysis on Twitter in implementing government policies related to Covid-19 to classify public opinion. Several stages in analyzing public sentiment are taken from the tweet data. The first step is data mining to get the tweets that will be analyzed later. Furthermore, cleaning tweet data and equalizing tweet data into lowercase. After that, perform the tweet's basic word search process and calculate its appearance frequency. Then calculate using the Naïve Bayes method and determine the sentiment classification of the tweet. The results showed that Indonesia's public sentiment about covid-19 prevention is neutral. The performance of the application shows an Accuracy value of 76.7%. In conclusion this means that the Indonesian government needs to evaluate the policies taken to deal with COVID-19 to create positive opinions to create solid cooperation between the government and the government. Residents in tackling the COVID-19 outbreak.
Defects Prediction Method for Radiographic Images Based on Random PSO Using Regional Fluctuation Sensitivity

This paper presents an advanced methodology for defect prediction in radiographic images, predicated on a refined particle swarm optimization (PSO) algorithm with an emphasis on fluctuation sensitivity. Conventional PSO models with stable velocity are often beleaguered with challenges in precisely pinpointing defect regions in radiographic images, attributable to the lack of a defect-centric approach and the propensity for premature convergence. The proposed fluctuation-sensitive particle swarm optimization (FS-PSO) model, distinguished by an approximate 40% increase in particle entrapment within defect areas and an expedited convergence rate, necessitates a maximal additional time consumption of only 2.28%. The model, also characterized by reduced chaotic swarm movement, enhances efficiency through the modulation of movement intensity concomitant with the escalation in swarm size. The FS-PSO algorithm's performance was rigorously evaluated via a series of simulations and practical blade experiments. The empirical findings evince that the FS-PSO model substantially outperforms the conventional stable velocity model, particularly in terms of shape retention in defect extraction.
Identification and location method of strip ingot for autonomous robot system using kmeans clustering and color segmentation

Abstract In order to improve the efficiency of autonomous robot sorting steel ingots, this paper proposes a two‐dimensional weighted equivalent clustering‐based progressive probabilistic hough transform (2D‐WEC‐PPHT) algorithm for the problem of identifying and locating strip ingots in automatic picking strip ingot palletizing. First, the steel ingot image is preprocessed and the PPHT linear detection method is used to extract the edge linear information of the steel ingot. Second, the angle and position information are normalized and weighted, and a two‐dimensional clustering distance calculation method is proposed for two‐dimensional clustering of the extracted line information. Besides, the clustering line clusters with close angles were processed into equivalent lines by mean fitting. Then, the average threshold method was used to segment the ingot between each two fitting lines, and the minimum rectangle was used to box the segmentation part. The centroid of the box‐selected rectangle is the positioning center of the ingot, and the long side angle of the box‐selected rectangle is the deviation angle information of the ingot. Finally, the experimental results show that the number of redundant lines detected by the 2D‐WEC‐PPHT is significantly less than that of traditional methods such as HT and PPHT. The positioning speed of ingot is faster than that of HT and PPHT, and the processing time is reduced from 20 s to 10 s. In the case of large proportion of old ingots with weak reflection, the recognition accuracy reached 93.5%, and the angular and position positioning accuracy were 2.270° and 11.675 mm, respectively. The recognition accuracy of new ingots with strong reflection reached 99.574%, which met the requirements of picking positioning accuracy.
Technical Means in the Neo-Avant-Garde by Stanislav Krasovitsky

The article deals with the introduction of new technical devices by Russian religious poet Stanislav Krasovitsky, which connects the tradition of zaum in the avant-garde with the search for a new mystery. As a pioneer of religious poetry during the Thaw period, Krasovitsky anticipated the mystery turn in Soviet culture: the use in rock operas, films and animations of the mystery plot as capable of uniting the various symbols of world culture. For Krasovitsky, the main technical device is the introduction of new letters into the Russian alphabet, taken from Greek and Latin, which allow conveying visual impressions through an unusual combination of sounds and creating a special atmosphere of mystery. It is shown that this project by Krasovitsky is closely related to the development of semiotics and cybernetics and the understanding of scripts as implementing programmed pragmatics in special operational symbols. Krasovitsky did not engage in poetic production for more than two decades, preferring religious asceticism, but at the same time he developed a theoretical justification for his turn from the avant-garde to mystery along the lines of the acts of the Baroque era. He constructed a consistent historiosophy in which paganism, the cult of Apollo, and Christianity were the three stages in the acquisition of truth, and each stage corresponded to its signs, letters, and symbols, containing both semantics and iconically marked pragmatics. This allowed Krasovitsky to combine reflections on the nature of letters with reflections on ritual, and to create late poetry already simply as legitimizing his own priestly rituals. This study allows us to clarify the peculiarities of perception of religious and philosophical issues in the culture of the Soviet period and show how formal experiments, including those supported by a specific medium of typewriter, allowed a new arrangement of verbal and visual elements in the work.
Interpretation of a Literary Text in Cinema: V.O. Bogomolov's Novel “Ivan” and A.A. Tarkovsky's Film “Ivanovo Childhood”

The article explores film screening as a special form of literary text. Within the framework of the study, the concept of cinema screening, its classification and features of types, strengths and weaknesses of this format are considered. The problems arising during the transfer of literary works of art to the cinema screen are also characterized, around which discussions do not stop to this day. The study of these issues is carried out not only in theory, but also in practice, which is presented in the form of a comparison of V.O. Bogomolov's novel "Ivan" (1957) and the film A.A. Tarkovsky's Ivanovo Childhood (1962). In addition to identifying the differences between the original literary work and its transfer to the language of cinema, expressed in deviation from following the literary artistic text, changing individual scenes, added episodes and expanding some storylines of the original literary work, the creative task set by the director is determined, and how exactly it was achieved. The main research methods are the analysis of scientific literature on the research topic (used for a detailed examination of cinema screening as a special form of literary text) and comparative analysis (used when comparing the original literary text (V.O. Bogomolov's novel Ivan) and its film adaptation (A.A. Tarkovsky's film Ivanovo Childhood)). Because of the comparative analysis, a conclusion is drawn that contains answers to the questions: which of the types of film adaptations does this film belong to, as it is expressed in the film, and the reasons that led to this result are revealed.
The image processing for creating 3D model in teaching computer science

The subject of computer science can be implemented at every level of education. It offers a creative space for the modernization of education. The image processing and the creation of 2D and 3D models are an actual problem in computer science. The digital technologies and modern methods are useful in solving many tasks in this area. The paper presents procedures which are easy to implement in the teaching of computer science at secondary schools. We will focus on the creation of real spatial models of small objects. The mastering the curriculum is highly supported by the active involvement of students in creation of models. We have designed a teaching module for inclusion, the creation of a real model in the subject’s content, by combination of project and problem-based teaching. Students learn by actively participating in solving partial problems. They can incorporate into the solution of real projects on the chosen topic. The project method allows students to work in groups and solve a complex practical tasks by practical activities. Our aim is to motivate students to mastering the curriculum via an active learning method “learning by doing”, by represents a real problem from everyday life, by using modern (mobile) technologies. The ability to collaborate, learn by discovering and exploring influences the development of a learning strategies.
Assessment of Accuracy of Digitally Generated Overlays Compared to Conventional Overlays For Simulated Bitemark Analysis on Cheese Blocks

Background: The bite injury or bite mark is examined as corroborative evidence in serious crimes such as rape, murder, robbery, and other forms of physical and sexual violence. The goal of this study was to comparatively evaluate the accuracy of overlays made with a digital, two-dimensional method compared to those made by directly tracing bite marks and using bite mark images obtained with a photocopier. Materials and Methods: A total of 61 participants were included in the study, of whom 31 were males with ages ranging between 18-65 years and 30 were females. The simulated bitemarks on the cheese block were used to prepare three sets of overlays, first by the way of hand-tracing, followed by a photocopying technique and a third set of overlays prepared using computer software called Adobe Photoshop version CS6 on a personal computer. Each pair of overlays and the study cast was then matched using 5-point criteria given by the ABFO guidelines, and a score between 0-3 was assigned to each observation. Results: The overall scores obtained in each group (A-hand-tracing, B-photocopy, C-digital method) were then compared amongst themselves for associations. By applying the Kruskal Wallis ANOVA test, the manual technique had a 29.5% positive matching rate, in photocopying method 32.8%, and the digital overlay 72.1%, which was significant. Conclusion: In conclusion, the digital overlay method outperformed the hand-tracing and photocopying methods in terms of minimizing the subjective errors and was found to be the most precise and dependable method.