Reviewerly/exHarmony huggingface dataset:
Domain-Specific Hybrid BERT based System for Automatic Short Answer Grading

Effective and efficient grading has been recognized as an important issue in any educational institution.In this study, a grading system involving BERT for Automatic Short Answer Grading (ASAG) is proposed.A BERT Regressor model is finetuned using a domain-specific ASAG dataset to achieve a baseline performance.In order to improve the final grading performance, an effective strategy is proposed involving careful integration of BERT Regressor model with Semantic Text Similarity.A set of experiments is conducted to test the performance of the proposed method.Two performance metrics namely: Pearson's Correlation Coefficient and Root Mean Squared Error are used for evaluation purposes.The results obtained highlights the usefulness of proposed system for domain specific ASAG tasks in real life.
Testing for causality between remittances and inflation: Evidence from Central and Eastern Europe

The goal of this study is to examine the impact of remittance inflow on inflation using the System Generalized Method of Moments (SGMM) and Dumitrescu-Hurlin Granger causality approach in countries from Central and Eastern Europe over the period 1994 to 2019. As the levels of economic and financial development vary considerably across these countries and some of them are member states of the European Union (EU), we split them into two more homogenous groups - EU member states and non-EU countries. The application of the SGMM approach reveals that remittances have a negative and significant impact on inflation in the non- EU countries, whereas they exert positive impact in the EU member states and in the whole region overall. The Granger causality test shows a unidirectional causal relationship between remittances and inflation in all country groups, whereas the existence of a positive causal relationship from remittances to inflation has been established in twelve countries.
Assessment peculiarities of prospective philologists’ technology competence

International scientific conference “Current trends and fields of philological studies in the challenging reality” : conference proceedings (July 29–30, 2022. Riga, the Republic of Latvia). Riga, Latvia : “Baltija Publishing”, 2022. 450 pages.
Educational component “SCIENTIFIC speech and writing style” for successful completion of the third level of higher professional education

International scientific conference “Current trends and fields of philological studies in the challenging reality” : conference proceedings (July 29–30, 2022. Riga, the Republic of Latvia). Riga, Latvia : “Baltija Publishing”, 2022. 450 pages.
Heuristic approach to the organization of students’ scientific work in foreign language classes

International scientific conference “Current trends and fields of philological studies in the challenging reality” : conference proceedings (July 29–30, 2022. Riga, the Republic of Latvia). Riga, Latvia : “Baltija Publishing”, 2022. 450 pages.
Group method implementation for formation of students` intercultural competencies in formal education institutions: behavioral approach

International scientific conference “Current trends and fields of philological studies in the challenging reality” : conference proceedings (July 29–30, 2022. Riga, the Republic of Latvia). Riga, Latvia : “Baltija Publishing”, 2022. 450 pages.
Methodological Apparatus of Cognitive Modeling of Socio-Economic System (University)

Purpose of the study. The aim of the study is to improve the methodological apparatus of cognitive modeling of socio-economic systems (SES) and predicting the indicators of their functioning and development, which ensures an increase in the accuracy and reliability of the results obtained. Existing models and methods do not fully provide the necessary accuracy and reliability of models that requires the development of the mathematical apparatus of cognitive modeling in terms of improving the quality of the developed cognitive models. Materials and methods. To achieve this goal, methods of an integrated approach to solving the problem, decomposing it into interrelated stages, describing the content of each stage in their relationship and presenting a generalized version of the methodology, taking into account the characteristics of the object of study, were used. The developed approach provides creating a more accurate and reliable cognitive model. The effectiveness of the developed methodological apparatus is shown. Results. A detailed analysis of the existing criteria and approaches to solving the problem of verification of cognitive models was carried out, which showed the absence of a unified methodology and an integrated approach in solving problems of cognitive modeling of SES based on cognitive maps. A set of techniques that implement the stages of cognitive modeling has been developed. The results of a comparative analysis of the developed approach with the existing ones are presented. Conclusion. A comprehensive solution to the problem of creating a cognitive model for analyzing and predicting the activities of a university is proposed, which includes a set of stages: the stage of creating the problem field of the situation; identification of factors and relationships between them; the stage of making a cognitive map and its verification, as well as the stage of analyzing the system characteristics of the cognitive model, validating the cognitive model. The developed methodological apparatus includes a set of techniques aimed at obtaining an adequate model that provides more accurate and reliable results of modeling the object of study.
Examining the Dependability and Practicality of Analytic Rubric of Summary Writing Using Multivariate Generalizability Theory: Focusing on Japanese University Students with Lower-Intermediate Proficiency in English

English teachers, especially those who teach summary writing to students with relatively lower proficiency in English face difficulty in teaching summary writing and while assessing their students&amp;rsquo; performances. In the classroom context, an analytic rubric is pedagogically more helpful than a holistic rubric because the teacher can confirm the strengths and weaknesses of their students&amp;rsquo; summary performance and the students can receive constructive feedback (Yamanishi et al., 2019). This study examined the practicality of the analytic rubric which consisted of four rating scales, including language use, by investigating seven in-service English teachers&amp;rsquo; honest assessment of 160 summaries of Japanese private university students who are inexperienced in writing English summaries and have lower-intermediate proficiency of English. Furthermore, this study examined the dependability of the analytic rubric using multivariate generalizability theory (Brennan, 2001). The results showed that assessing language use and judging summaries, copied, to a lesser or greater extent, from the source text was difficult because of diverse linguistic errors and the use of paraphrasing was lacking. Therefore, it is necessary to define the gravity of language errors and that of copying in more detail to develop a rubric that suits to assess the summaries written by English learners with lower-intermediate level of English.
Calculation and Performance Evaluation of Text Similarity Based on Strong Classification Features

Abstract Based on the strong classification feature recognition algorithm, the calculation algorithm of a text semantic similarity is studied with the performance evaluation in this paper. In order to achieve a general algorithm for this function, the semantic function library based on a semantic recognition code as a comparison object is designed. It drives the algorithm modules of two fuzzy neuron deep convolution machine learning, and between these two processes of machine learning, a rigid algorithm based on Fourier transform frequency domain feature is extracted. Finally, a more complex machine learning general algorithm is realized by the use of external data fuzzy algorithm and de-fuzzy algorithm before and after the algorithm module. It is also a technical innovation in this paper. Through the performance evaluation based on the subjective evaluation of volunteers, it is found that the system focuses on the text semantic similarity evaluation of the Chinese language, and achieves a comparison result of 81.78% of the artificial judgment accuracy rate, and only 5.52% of the volunteers believe that the system judgment result is completely different from that of manual judgment.
An Insight into Artificial Intelligence in Agriculture – Boon or Bane?

This paper gives an idea in regards with the impact of Artificial Intelligence in Agrarian Sector. As India is an Agrarian Country, our economy is uncommonly dependent upon the yielding of harvests and its most prominent effectiveness. Most of people in our country depends upon cultivation for their everyday requirements. The usage of Artificial Intelligence close by its capacity of learning can give an enormous impact on the country sector.AI development helps in distinctive sickness in plants, vermin and sad sustenance of residences. Man-created insight sensors can recognize and target weeds and subsequently pick which herbicide to apply inside the area. This assistants in lessened utilization of herbicides and cost save reserves. Various mechanical associations make drobots, which use PC vision and man-made awareness to screen what's more, unequivocally shower on weeds. This paper moreover discusses the new developments that opens the way to a Smart Agriculture .This paper gives an idea in regards with the impact of Artificial Intelligence in Agricultural Sector.
TRAINING in MAKING INNOVATION INTERACTIVE LEARNING MEDIA FOR TEACHERS of SMAN KARANGPANDAN

The background behind the holding of this training is the lack of knowledge about interactive learning media, in addition due to the still pandemic conditions, a teacher who is in Karangpandan high school, is required to be able to continue to provide learning even though it is online. Therefore, a teacher must be able to provide interesting and interactive learning, so that students continue to be interested in learning even though they are online. The number of learning media made using various applications requires every teacher to have an understanding and skills regarding information and communication technology. By understanding information and communication technology correctly, it can make it easier for teachers to create various interesting interactive media, in this training we will use pear-deck and class points. These two applications are perfect for teachers who want to be skilled in making interactive learning media and make teachers more creative and innovative.
Tom Erbe Interviewed by Theodore Gordon

In this interview, Tom Erbe reflects on his three decades as a developer of computer music software and hardware, both freeware and commercial. Tom met with Theodore Gordon on 8 December 2021 and discussed the beginnings of SoundHack and its roots in experimental music studio practice and hacker culture, ideas behind the design of sound processor interface and the shift from experimental software development to Eurorack modular hardware design.
PETA KERAWANAN BANJIR SUB DAS CILUTUNG BERDASARKAN DATA GEOSPASIAL

A Flood is a natural phenomenon that causes material or non-material losses. The availability of geospatial information can be used to analyze the level of flood susceptibility. The purpose of this study was to identify and map flood-prone areas in the Cilutung sub-watershed based on geospatial data, namely land use and cover conditions, soil type, slope class, and rainfall. The method used in this study is weighting and scoring in geographic information systems (GIS). Based on the analysis, there are 4 classes of flood susceptibility in the Cilutung sub-watershed with the classification of safe, less vulnerable, moderate, and vulnerable. The distribution of flood-prone areas is almost spread over the entire Cilutung sub-watershed area, including the districts of Argapura, Banjaran, Bantarujeg, Cikijing, Cingambul, Lemahsugih, Maja, Majalengka, Malausma, Panyingkiran, Talaga, Cisitu, Jatigede, Jatigede, Tomo, and Wado. Medium class with an area of ​​22579 ha (36%), vulnerable class 18543 ha (30%), less vulnerable class 17883 ha (29%), safe class 2979 ha (5%). The most dominant parameters that cause flood vulnerability are flat slope 0-8%, latosol soil type, and land use in the form of rice fields, these parameters are spread in the southern and northern regions.
Tonality and Neoclassicism in Stravinsky’s Sonata for Piano, Mvt. 2 (1924)

&#x0D; &#x0D; &#x0D; Igor Stravinsky’s Sonata for Piano is an often overlooked yet important artifact of the composer’s neoclassicism. his treatment of tonality in the second movement is both literally and aurally more conventional than one might first guess. Stravinsky’s reliance on convention points to an ideology of continuity, one that honors the legacy of beethoven and other heroes. In doing so, Stravinsky’s Sonata brings forward old ideas wrought in new ways for a modern era. This essay examines ways of thinking about Stravinsky’s neoclassic style through analysis of the second movement of the Sonata focusing on the use of post-tonal techniques to create surprisingly tonal music.&#x0D; &#x0D; &#x0D;
Error analysis of classification learning algorithms based on LUMs loss

<p style='text-indent:20px;'>In this paper, we study the learning performance of regularized large-margin unified machines (LUMs) for classification problem. The hypothesis space is taken to be a reproducing kernel Hilbert space <inline-formula><tex-math id="M1">\begin{document}$ {\mathcal H}_K $\end{document}</tex-math></inline-formula>, and the penalty term is denoted by the norm of the function in <inline-formula><tex-math id="M2">\begin{document}$ {\mathcal H}_K $\end{document}</tex-math></inline-formula>. Since the LUM loss functions are differentiable and convex, so the data piling phenomena can be avoided when dealing with the high-dimension low-sample size data. The error analysis of this classification learning machine mainly lies upon the comparison theorem [<xref ref-type="bibr" rid="b3">3</xref>] which ensures that the excess classification error can be bounded by the excess generalization error. Under a mild source condition which shows that the minimizer <inline-formula><tex-math id="M3">\begin{document}$ f_V $\end{document}</tex-math></inline-formula> of the generalization error can be approximated by the hypothesis space <inline-formula><tex-math id="M4">\begin{document}$ {\mathcal H}_K $\end{document}</tex-math></inline-formula>, and by a leave one out variant technique proposed in [<xref ref-type="bibr" rid="b13">13</xref>], satisfying error bound and learning rate about the mean of excess classification error are deduced.
Еngineering Education: Problems and Prospects for Solution

The problem of providing personnel for the domestic economy in the conditions of the formation of its technological sovereignty is considered. The crisis of our country’s relations with European countries has caused a wave of criticism of the Russian higher education system. Most of them attacked the allegedly imposed Bologna system of higher education. The authors show that the problems of training specialists in our country are not connected with the introduced system of higher education, but with the organization and implementation of the educational process in universities. An attempt is made to highlight the pain points in the training of specialists in the country’s higher education system.
Detection of Cyberbullying in the Social Media Space using Maximum Entropy and Convolutional Neural Network

Social media has shown to be a medium for the exchange of information, conducting commerce, and even for religious and political activity. The same site has been used to disseminate cyberbullying and hate speech. Cyberbullying is an offense when a perpetrator targets a victim with online provocation and resentment, which has negative impacts on the victim's emotions, relationships, and physical health. These spew forth a lot of hate speech directed at those who have different beliefs or hold different opinions. In order to overcome these problems, this research creates a deeper neural network and maximum entropy-based model for the identification of cyberbullying. In comparison to the present systems, Convolution Neural Network is used for the superior results. The dataset gathered includes 24,783 records tweets with the categories "bullying language," "non-bullying language," and "neither" are included. According to geopolitical zones, tweets are categorized in the study. Throughout the experiment, the dataset was trained and evaluated. The model's unigram performed with 96.3 percent accuracy, the bigram model with 93.8 percent accuracy, the trigram with 88.2 percent accuracy, and the n-gram enhanced performance with 94.2 percent. The two baseline classifiers for the tweets dataset were TF-IDF (Term Frequency Inverse Document Frequency) and the characteristics of unigram, bigram, trigram, and n-grams for detection. The outcome of the model during the tweet cyberbullying will increase the memory accuracy of the bullying. The study's findings will reveal creative language and alternative spellings for cyberbullying in tweets.
Debunking strategies for misleading bar charts

Graphs are useful to communicate concisely about complex issues. Although they facilitate intuitive reading of data, trends, and predictions, hasty readers may still come to the wrong conclusions, especially if graphs are misleading due to violated design conventions. To prevent misinformation from spreading by misleading graphs, this two-survey experimental study investigates the effectiveness of four correction methods as debunking strategies to correct bar charts with manipulated vertical axes. All four methods showed positive effects. The most effective one is aimed at correcting the initial image by presenting an accurate alternative graph. A reduced effect remained visible after one week.
Meta-RangeSeg: LiDAR Sequence Semantic Segmentation Using Multiple Feature Aggregation

LiDAR sensor is essential to the perception system in autonomous vehicles and intelligent robots. To fulfill the real-time requirements in real-world applications, it is necessary to efficiently segment the LiDAR scans. Most of previous approaches directly project 3D point cloud onto the 2D spherical range image so that they can make use of the efficient 2D convolutional operations for image segmentation. Although having achieved the encouraging results, the neighborhood information is not well-preserved in the spherical projection. Moreover, the temporal information is not taken into consideration in the single scan segmentation task. To tackle these problems, we propose a novel approach to semantic segmentation for LiDAR sequences named Meta-RangeSeg, where a new range residual image representation is introduced to capture the spatial-temporal information. Specifically, Meta-Kernel is employed to extract the meta features, which reduces the inconsistency between the 2D range image coordinates input and 3D Cartesian coordinates output. An efficient U-Net backbone is used to obtain the multi-scale features. Furthermore, Feature Aggregation Module (FAM) strengthens the role of range channel and aggregates features at different levels. We have conducted extensive experiments for performance evaluation on SemanticKITTI and SemanticPOSS. The promising results show that our proposed Meta-RangeSeg method is more efficient and effective than the existing approaches. Our full implementation is publicly available at https://github.com/songw-zju/Meta-RangeSeg .
Four Way Human Quantum Turiyam Cognition Analysis

Recently, the Turiyam set was introduced for characterization of data sets beyond true, false and uncertain regions. This set is able to represent unknown, undefined, or conduit metaphor of human quantum cognition. One of the examples is USA-Russia conflicts or Cold war is beyond the characterization of win, draw or loss. It is totally based on the conduit metaphor of USA and Russia. In this case, a set of countries may support Russia (Sr) can be characterized as true regions. A set of countries does not support Russia (i.e. supporting the USA) can be characterized as false regions (Su). A set of countries supports both Russia-USA based on the given situation. These types of countries and their vote is uncertain. The fourth case is some countries like India, China, UAE choose nothing to fulfill their conduit metaphor. It is called Turiyam or four dimension cognition. The characterization of this four dimension data and its graphical visualization is one of the crucial tasks for the current researchers. To tackle this issue, the current paper will try to introduce a method for characterization of this undefined, unknown or Turiyam cognition via a defined interval-set. The objective is to provide a way to explore them in known graph (t), not known graph (f), partial graph (i) or unknown graph (l) with an example.
A Comparative Case Study on the Operation Process of the Education Welfare at School according to the Placement of Educational Welfare Workers

Objectives The purpose of this study is to compare the operation process of educational welfare at schools, identify limitations, and suggest improvement methods.&#x0D; Methods Considering the placement of educational workers, school level, school location, and number of students, focus group interview and written investigation were conducted on 8 target schools, 16 school faculties. Written investigation and focus group interview questions were constructed based on the CIPP model. The collected data were analyzed based on the CIPP model.&#x0D; Results The educational welfare operation process of the unit school differed depending on the placement of educational workers. First, schools with educational workers tried to realize universal welfare that focuses on satisfying various educational welfare needs for all students, while schools without educational workers focused on the target and scope of educational welfare for students of a specific class. Second, most schools with educational workers were systematically organized into departments, budgeting, and functions and roles of manpower, while schools without educational workers had difficulty operating due to limited manpower, organization, and budget input. Third, in the case of schools with educational workers, various types of support are provided based on the school's internal and external cooperation system, while schools without educational workers have difficulty in selecting target students, case management, and linking with external resources. Finally, regarding the achievements of educational welfare, schools with educational workers presented visible achievements such as student growth, community change, and improvement of educational equity, while non-arranged schools presented visible achievements such as improved academic achievement and positive peer relations.&#x0D; Conclusions Schools should view all students as potential targets of educational welfare. In order to realize educational welfare in daily educational activities, ‘integrated growth support team’ should be established or strengthened on an organizational basis, ‘integrated growth case management’ on a content basis, and ‘cooperative governance’ on a professional basis.