Reviewerly/exHarmony huggingface dataset:
Implementing an electronic public health record for policy planning in the UK military sector: Validation of a secure hashing algorithm

The digitalisation of healthcare services is a major resource to inform policy-makers. However, the availability of data and the establishment of a data flow present new issues to address, such as data anonymisation, records' reliability, and data linkage. The veterans' population in the UK presents complex needs and many organisations provide social and healthcare support, but their databases are not linked or aggregated to provide a comprehensive overview of service planning. This study aims to test the sensitivity and specificity of a Secure Hashing Algorithm to generate a unique anonymous identifier for data linkage across different organisations in the veterans' population. A Secure Hashing Algorithm was performed by considering two input variables from two different datasets. The uniqueness of the identifier was compared against the single personal key adopted as a current standard identifier. Chi-square, sensitivity, and specificity were calculated. The results demonstrated that the unique identifier generated by the Secure Hashing Algorithm detected more unique records when compared to the current gold standard. The identifier demonstrated optimal sensitivity and specificity and it allowed an enhanced data linkage between different datasets. The adoption of a Secure Hashing Algorithm improved the uniqueness of records. Moreover, it ensured data anonymity by transforming personal information into an encrypted identifier. This approach is beneficial for big data management and for creating an aggregated system for linking different organisations and, in this way, for providing a more comprehensive overview of healthcare provision and the foundation for precision public health strategies.
Towards the portability of knowledge in reinforcement learning-based systems for automatic drone navigation

In the field of artificial intelligence (AI) one of the main challenges today is to make the knowledge acquired when performing a certain task in a given scenario applicable to similar yet different tasks to be performed with a certain degree of precision in other environments. This idea of knowledge portability is of great use in Cyber-Physical Systems (CPS) that face important challenges in terms of reliability and autonomy. This article presents a CPS where unmanned vehicles (drones) are equipped with a reinforcement learning system so they may automatically learn to perform various navigation tasks in environments with physical obstacles. The implemented system is capable of isolating the agents' knowledge and transferring it to other agents that do not have prior knowledge of their environment so they may successfully navigate environments with obstacles. A complete study has been performed to ascertain the degree to which the knowledge obtained by an agent in a scenario may be successfully transferred to other agents in order to perform tasks in other scenarios without prior knowledge of the same, obtaining positive results in terms of the success rate and learning time required to complete the task set in each case. In particular, those two indicators showed better results (higher success rate and lower learning time) with our proposal compared to the baseline in 47 out of the 60 tests conducted (78.3%).
An improved dynamic programming tracking-before-detection algorithm based on LSTM network

Abstract The detection and tracking of small and weak maneuvering radar targets in complex electromagnetic environments is still a difficult problem to effectively solve. To address this problem, this paper proposes a dynamic programming tracking-before-detection method based on a long short-term memory (LSTM) network (LSTM-DP-TBD). With the predicted target motion state provided by the LSTM network, the state transition range of the traditional DP-TBD algorithm can be updated in real time, and the detection and tracking effect achieved for maneuvering small and weak targets is also improved. Utilizing the LSTM network to model the moving state of the target, the moving features of the maneuvering target can be learned from the noisy input data. By incorporating these features into the traditional DP-TBD algorithm, the state transition set can be adjusted in time with the changes in the moving state of the target so that the new algorithm is capable of effectively recursively accumulating the movement trend of the maneuvering small and weak target. Simulation results show that the new algorithm is able to effectively accomplish the task of detecting and tracking maneuvering small and weak targets, and it achieves improved detection and tracking probabilities.
Let us explain everything: pupils’ perspectives of the affordances of mobile technology during primary science inquiry

This three-year longitudinal case study focused on the deployment of mobile technology in the form of tablet computers (iPads), during Inquiry Based Science Education (IBSE). The research took place in a larger than average primary school in the West Midlands, UK, which showed a strong commitment to Technology Enhanced Learning (TEL) resulting in iPads being used as an integral learning tool, across the entire curriculum. During the research, pupils in Upper Key Stage Two (10–11 year olds) were observed taking part in science weeks which consisted of intense periods of science inquiry, much of which was child-led. The impact of the embedded use of iPads was monitored by scrutinising pupils’ work in the form of multimedia presentations and experimental reports. Pupils’ learning behaviours and attitudes to mobile technology were explored through observations and paired interviews. The embedded use of iPads during IBSE was shown to increase science knowledge acquisition and support scientific literacy, recording of processes and aid understanding of working scientifically. Furthermore, iPads were shown to afford opportunities for personalisation of scientific learning experiences and foster collaboration at several levels, factors which were highly valued by the pupils. The outcomes of this study can be used to further inform the refinement of m-learning strategies in primary science and illuminate opportunities for developing the practice of science pedagogues.
Who are the haters? A corpus-based demographic analysis of authors of hate speech

We examine the profiles of hate speech authors in a multilingual dataset of Facebook reactions to news posts discussing topics related to migrants and the LGBT+ community. The included languages are English, Dutch, Slovenian, and Croatian.First, all utterances were manually annotated as hateful or acceptable speech. Next, we used binary logistic regression to inspect how the production of hateful comments is impacted by authors' profiles (i.e., their age, gender, and language).Our results corroborate previous findings: in all four languages, men produce more hateful comments than women, and people produce more hate speech as they grow older. But our findings also add important nuance to previously attested tendencies: specific age and gender dynamics vary slightly in different languages or cultures, suggesting that distinct (e.g., socio-political) realities are at play.Finally, we discuss why author demographics are important in the study of hate speech: the profiles of prototypical "haters" can be used for hate speech detection, for sensibilization on and for counter-initiatives to the spread of (online) hatred.
Evaluating and selecting arguments in the context of higher order uncertainty

Human and artificial reasoning has to deal with uncertain environments. Ideally, probabilistic information is available. However, sometimes probabilistic information may not be precise or it is missing entirely. In such cases we reason with higher-order uncertainty. Formal argumentation is one of the leading formal methods to model defeasible reasoning in artificial intelligence, in particular in the tradition of Dung's abstract argumentation. Also from the perspective of cognition, reasoning has been considered as argumentative and social in nature, for instance by Mercier and Sperber. In this paper we use formal argumentation to provide a framework for reasoning with higher-order uncertainty. Our approach builds strongly on Haenni's system of probabilistic argumentation, but enhances it in several ways. First, we integrate it with deductive argumentation, both in terms of the representation of arguments and attacks, and in terms of utilizing abstract argumentation semantics for selecting some out of a set of possibly conflicting arguments. We show how our system can be adjusted to perform well under the so-called rationality postulates of formal argumentation. Second, we provide several notions of argument strength which are studied both meta-theoretically and empirically. In this way the paper contributes a formal model of reasoning with higher-order uncertainty with possible applications in artificial intelligence and human cognition.
Functional Objects in Urban Walking Environments and Pedestrian Trajectory Modelling

Functional objects are large and small physical entities installed in urban environments to offer specific functionalities to visitors, such as shops, escalators, and information kiosks. Instances of the novel notion are focal points of human activities and are significant in pedestrian movement. Pedestrian trajectory modelling in an urban scene is a challenging problem because of the complex patterns resulting from social interactions of the crowds and the diverse relation between pedestrians and functional objects. Many data-driven methods have been proposed to explain the complex movements in urban scenes. However, the methods considering functional objects in their formulation are rare. This study aims to reduce the knowledge gap by demonstrating the importance of pedestrian-object relations in the modelling task. The proposed modelling method, called pedestrian-object relation guided trajectory prediction (PORTP), uses a dual-layer architecture that includes a predictor of pedestrian-object relation and a series of relation-specific specialized pedestrian trajectory prediction models. The experiment findings indicate that the inclusion of pedestrian-object relation results in more accurate predictions. This study provides an empirical foundation for the novel notion and a strong baseline for future work on this topic.
Grammar-aware phrase dataset generated using a novel python package

The past technique of manual dataset preparation was time-consuming and needed much effort. Another attempt to the data acquisition method was using web scraping. Such web scraping tools also produce a bunch of data errors. For this reason, we developed "Oromo-grammar" a novel Python package that accepts a raw text file from the user, extracts every possible root verb from the text, and stores the verbs into a Python list. Our algorithm then iterates over list of root verbs to form their corresponding list of stems. Finally, our algorithm synthesizes grammatical phrases using the appropriate affixations and personal pronouns. The generated phrase dataset can indicate grammatical elements like numbers, gender, and cases. The output is a grammar-rich dataset, which is applicable to modern NLP applications like machine translation, sentence completion, and grammar and spell checker. The dataset also helps linguists and academia in teaching language grammar structures. The method can easily be reproducible to any other language with a systematic analysis and slight modifications to its affix structures in the algorithm.
Mentoring as a resource of developing the future teacher’s culture of professional self-organization

The purpose of the research is to define the features of using mentoring for the development of professional self-organization of pedagogical university students. In the article the essence of the professional self-organization culture of a future teacher is revealed. The mentoring practice is presented as its development resource; the pedagogical means of mentoring practice that increase the professional self-organization culture of a future teacher such as pedagogical reading, time-management methods, technology of pedagogical test are described. The scientific novelty consists in the extending of pedagogical knowledge about the possibilities of developing professional self-organization culture of a future teacher with the help of mentoring resources; the essence and content of pedagogical reading, time-management methods and technology of pedagogical test are introduced with the pedagogical means of mentoring practice aimed at the development of professional self-organization culture of a future teacher. As the result, it is proved that a curator can actively use the mentoring practice in pedagogical university to develop professional self-organization culture of a future teacher with the help of pedagogical reading, time-management methods and technology of pedagogical test.
Theoretical substantiation of the process model of developing the competences of students’ social interaction in teaching collaboration

The research is focused on the theoretical substantiation of the process model of developing the competences of students’ social interaction in training collaboration. In the article the essence of the competences of students’ social interaction has been revealed. It is shown that the components of these competences comprise the social-perceptive, communicative and interactive competences of social interaction and the components content is described. It is proved that the development of students’ social interaction competences is possible to put into practice in the process of training collaboration and due to its essential characteristics, content features and the organization specifics of university educational process. The scientific novelty consists in working out of a new scientific idea on the development of students’ social interaction competences in university educational process realized by means of their involvement into the subject and social content of practice-oriented and professional activity. This activity should be kept on the basis of training collaboration and the students’ performance of various social roles when solving problem variable situations. As the result, the process model of the development of students’ social interaction competences has been designed on the basis of general pedagogical mechanism that involves the students of different education pathway into training collaboration enriched with problem variable situations.
Structural and functional model of future preschool teachers’ training for the formation of economic responsibility bases of preschoolers

The research purpose is the theoretical substantiation of structural and functional model of future preschool teachers’ training for the formation of economic responsibility bases of preschoolers. In the article the definition of “economic responsibility of preschoolers” is given; the structural and functional model of future preschool teachers’ training for the formation of economic responsibility bases of preschoolers and its components are described. The scientific novelty consists in the definition of the content of the blocks of the model of future preschool teachers’ training for the formation of economic responsibility bases of preschoolers. As the result the author has designed the structural and functional model of future preschool teachers’ training for the formation of economic responsibility bases of preschoolers. The model consists of the target block, the theoretical and methodological block, the methods and procedures block and the assessments and results block and comprises the motivation, cognitive and operational components.
Card Sort Method: improve elementary school students early reading skills

Students' initial reading skills or abilities could be stronger. Some students need to be fluent in reading and understand the function of punctuation marks. Some students must learn the alphabet and need help seeing the difference between the letters b and d, p and q. This study aims to analyze the effect of the card sort method on the beginning reading ability of grade II elementary school students. This research belongs to the type of quantitative research using experimental methods. The population in this study were 48 grade II elementary school students. This study's sample consisted of 24 students who functioned as experimental classes using the Crd Sort Learning method and 24 as control classes who did not use the card sort method. The data collection technique used in this study was a preliminary reading test, with the research instrument being an oral reading commencement test. The research data were then analyzed using descriptive statistical analysis techniques and a t-test (Independent sample t-test). The results showed that the average pretest score for the experimental class was 51.50 and that for the control class was 55.67. After the learning treatment was carried out using the card sort method, the results of data analysis in the Posttest experimental class were an average of 83.17 and a control score with an average of 69.33. Based on the hypothesis test, it shows that the significant value (2-tailed) is 0.000. Because the significant value (2-tailed) is 0.000 &lt; α = 0.05, Ho is rejected, and H1 is accepted, meaning there is a difference between the card sort method and students' beginning reading abilities. Class II with classes that do not use the card sort method. Based on these results, it can be concluded that the card sort method can improve students' beginning reading skills in class II.
The Learning Media Application "BELIPARU" Oriented Towards the Mastery of Fifth-Grade Students' Concepts of the Water Cycle Material

The low level of mastery of concepts by elementary school students in Indonesia, especially in science subjects, impacts students' low learning outcomes and enthusiasm for participating in teaching and learning activities. So to maximize the learning process, teachers must start utilizing the use of media. This study aims to see the effectiveness of the "BELIPARU" application media, which is oriented towards mastering the concept of fifth-grade students. This research belongs to the type of development research developed using the Borg and Gall model, with four research stages consisting of the idea gathering and reference stages, product manufacturing stage, media validation stage and material validation stage, product revision stage, and trial stage. The test subjects were conducted on 29 students in class V. This data collection method was carried out through observation, written test instruments in the form of pretest and post-test questions, and closed questionnaires for students. The data obtained in this study were then analyzed using descriptive-quantitative analysis techniques through the SPSS application, which were then thoroughly described using descriptions. The research analysis showed that the media expert test produced a percentage of 92.5% in the very good category. In comparison, the results of the material experts produced a percentage of 90.6% in the very good category, although there was a slight minor revision in the validator. Furthermore, the results of the pretest activity trials showed an average of 22.24, and the results of post-test activity testing showed an average of 64.31. Based on these results, Android-based applications are very suitable for students' learning process, especially in increasing mastery of concepts.
The model of values of the digital educational environment as a guideline for the professional education of future teachers

The study aims to establish a correspondence between the capabilities and values of the digital educational environment (DEE), educational strategies and the emerging promising competencies of a future teacher, as well as value risks in new educational conditions. The paper presents the understanding of professional education in the modern educational environment of the university as a process implemented complementarily in the environment of interpersonal interaction and in the DEE, taking into account the variable possibilities for the development of professional values by a future teacher. The scientific novelty lies in the substantiation and development of a model of DEE values to determine the ratio of traditional and new values of education in the context of professional education of future teachers. As a result, on the basis of the developed model, the researcher has formulated proposals for the harmonisation of the process of professional values mastery by future teachers in the educational environment enriched with digital tools and services.
methodological maintenance of teachers

Methods of working with young teachers on the example of the experience of the IMC Krasnoselsky district of St. Petersburg
Synergetic Properties of Lexical Structures in Chinese and English

The synergetic lexical model provides a unique framework for exploration of the interrelationships between the lexical properties of languages. Previous studies concerning several properties of this lexical model have yielded many successful fittings results, but very few studies have investigated synonymy, a major property of this model. The present study uses 825 Chinese and 848 English tokens retrieved from Chinese and English corpora, dictionaries, and thesaurus to conduct a contrastive study on the interrelations between four major properties of this lexical model: word length, word frequency, polysemy, and synonymy. The successful fittings of both languages demonstrate the cross-linguistic validity of the synergetic lexical model, though English belongs to the Germanic language family, while Chinese, a highly analytical language, is of the Sino-Tibetan language family. Moreover, our analysis of the parameters of the fitting results shows that, compared to English, Chinese possesses a greater resistance to shortening word length and a quicker response to semantic change.
LOWCODE IMPLEMENTATION OF AUTOMATIC ASSEMBLY OF TEACHER'S METHODOLOGICAL PAGES BASED ON CHATGPT RECOMMENDATIONS

This article discusses the possibility of using the ChatGPT language model to create teacher's method pages. A variant of using ChatGPT and its capabilities in the creation of appropriate text learning materials is described.Examples of using the model to create methodological pages on various subjects of university education are given. The features of communication with teachers are considered, methods of using ChatGPT in the process of teaching and research work are described. Preliminary results show that the use of ChatGPT can significantly simplify the process of creating methodological pages, free the teacher from routine work, and thus improve the quality of training.
DESCRIPTION AND IMPLEMENTATION OF THE PROGRAM FOR THE COMPETENCE FORMATION IN PROFESSIONAL COMMUNICATION OF UNDERGRADUATE STUDENTS

The artiсlе disсussеs thе сoncеpt of profеssionаl-spесiаlizеd сompеtеnсiеs, thеir сontеnt, and thеir distinсtive fеаturеs. Тhе vаluе is justifiеd аnd thе dеgrее of еffесtivеnеss of thе usе of а сompеtеnt аpproaсh in thе formаtion of profеssionаl-spесiаlizеd сompеtеnсiеs is rеvеаlеd. Тrаining modеls usеd in thе formаtion of profеssionаl-spесiаlizеd сompеtеnсiеs of undеrgrаduаtе studеnts аrе аnаlyzеd. Тhе rеlеvаnсе of thе study is justifiеd by а soсiаl rеquеst еxprеssеd in domеstiс аnd forеign rеgulаtory doсumеnts rеlаtеd to thе dеvеlopmеnt of profеssionаl, сommuniсаtive сompеtеnсiеs, improving thе quаlity of еduсаtion through pеrsonally oriеntеd lеаrning tесhnologiеs, аnd, аs а result, dеvеloping thе possibility of сitizеns’ pаrtiсipаtion in сontinuous еduсаtion.