Reviewerly/exHarmony huggingface dataset:
A study on the formation of support system for Qualification Exam Learning of adult learner

Objectives This study tried to explore the Qualification Exam from the perspective of lifelong education within the broad of recognition of learning results. To provide basic data for research that explores the activation and direc-tion of learning results recognition for adult learners, considering the Qualification Exam as an academic recog-nition system for adult learners, the characteristics of the formation and change of the components that make up the learning support system were looked at.&#x0D; Methods To this end, the literature research method was applied. Various documents, research reports, stat-istical data, academic papers and dissertations, and past newspaper data related to the academic recognition sys-tem and Qualification Exam were collected, and public policy information and public relations data were collected and analyzed by visiting government websites.&#x0D; Results As a result of the study, the functions and characteristics of three components of the system supporting the learning of the Qualification Exam for adult learners were confirmed. The first, they are laws and institutions. The relevant laws laid the groundwork for the academic recognition system, and the academic recognition sys-tem, including Qualification Exam, provided educational opportunities and created an environment for learning support system based on this. The second, they are support policies and institutions. Educational institutions op-erate the class to prepare Qualification Exam, and provide learning space. The driving force for learning support has been supported by support projects and policies. Finally, the learner who motivates the above components to achieve their goals is both the target and the result.&#x0D; Conclusions The Qualification Exam was understood as a concept with a limited function of ‘the tests to get a school diplomas that people who could not attend school because of poverty'. However, through this study, it was confirmed that the Qualification Exam pursues the philosophy of lifelong education as it functions as a system for recognizing academic background and learning results in which the elements of law, system, policy, educational institution, and learner are linked.
Unlocking potential: Harnessing the power of metadata for discoverability and accessibility

Metadata plays a crucial role in organizing, discovering, and accessing publications and products. This paper explores the complex metadata ecosystem and its impact on downstream functions. Focusing on author-provided metadata, it addresses the challenges faced by authors in terms of discoverability, and offers best practices for optimizing metadata. The paper also discusses publication-level metadata standards and related initiatives. It highlights the importance of KBART files for linking subscription products and explores the three types of linking in discovery services. Additionally, it emphasizes the role of metadata in search engine optimization and social media. The paper explores how metadata can enhance accessibility and emphasizes the need for collaboration across various teams and systems. Overall, it underscores the ongoing efforts to build robust metadata pipelines and improve the user experience in information discovery and interchange.
Investigation of an algorithm for distributing panoramic image stitching, enhanced by feature point detection

In order to solve the problems of long matching time and high mis-matching rate in the feature point matching process of traditional panoramic image stitching algorithms, this paper proposes a panoramic image stitching algorithm based on SIFT and RANSAC.SIFT's algorithm has been advanced to only extract features for overlapping areas (valid regions), thus lessening the computational effort of feature detection, better aligning image features, and enhancing alignment accuracy. On the ground of their corresponding degree, the RANSAC algorithm has been increasingly improved and thus allocated varying weights to distinct feature points, and the higher the matching degree, the higher the weight assigned to the points, thus more precisely discarding mismatched point pairs. A comparison of the number of mismatched points involving relevant parameters, like degree and time of matching, the SIFT and corresponding RANSAC algorithm-based panoramic image stitching algorithm are more excellent.
A Radial Basis Function Neural Network Algorithm for the Simultaneous Retrieval of Two Meteorological Parameters from Solar Radiation

Local meteorological parameters are key in understanding the frequency of occurrence of extreme weather conditions such as floods, and droughts, among others. In this study, we present a method for simultaneous retrieval of two weather parameters. The method is based on already measured monthly average values of weather parameters from 2011 to 2016, which were used to train a Feed-forward radial basis function neural network (RBFNN) to obtain a fast and accurate method to compute global solar radiation for specified weather parameters pair. In inverse modelling, a multidimensional unconstrained non-linear optimization was employed to retrieve the weather parameters pair. The new approach was validated using weather parameter data measured at the Department of Physics, Makerere University (0.31° N, 32.58° E, 1200 m). Statistical tools were used to evaluate the method's performance. In the Feed-forward artificial neural network (ANN), the correlation coefficient (R), mean bias error (MnB), root mean square error (RMSE), and mean percentage error (MAPE) were in the ranges 0.80-0.95, -0.0011-0.0077, 0.55-1.04 and 2.49%-5.82%, respectively. The pairs (sunshine hours, relative humidity) and (sunshine hours, minimum temperature) had the highest correlation coefficient of 0.95. In the inverse artificial neural network (ANNi), the R, MnB, RMSE and MAPE were in the ranges 0.3-0.9, 0.01-0.08, 0.51-11.14 and 2.1%-14.5%, respectively. The pair (sunshine hours, relative humidity) had the highest correlation coefficients of 0.92 and 0.62, respectively. The method helps in obtaining weather parameter data sets in places where measuring equipment is lacking or during days when measuring equipment malfunctions.
TEACHING LANGUAGES IN TECHNICAL UNIVERSITIES

Main issue: This article examines the problem-based language teaching technology at a technical university. Designing a problem-based situation helps to increase motivation in language learning. The introduction and use of new educational technologies has a positive effect on the quality of language learning. The project method contributes to the development of cognitive competence of technical university students. Purpose: to analyze the problem-based teaching technology, design method for the process of teaching Kazakh and Russian languages ​​in technical universities. In order to realize this goal, it is necessary to use a communicative approach, problem situation design, problem formulation, problem solving process, proof of the correctness of the solution, project proposal form in the educational process. Methods: descriptive method, analysis and synthesis methods were used during the research. Results and their importance: introduction of problem teaching technology and the project method into the educational process improves the quality of language teaching, and most importantly, teaches thinking, reasoning, finding creative, rational solutions, gets used to working individually and in small groups. The authors presented a practical experience of using the project activity method in language classes held at a technical university. It was determined that the project method can be used in the study of any subject of the work study program by carrying out a test. Active teaching methods are the main core of the lesson. The project method allows to form communicative competence and develop students' ability to think creatively
THE ARTISTIC CONCEPT OF "FORESIGHT" IN THE SPACE OF THE TEXT AND WAYS OF OBJECTIFICATION OF ITS MEANING

The article is devoted to revealing the role of the artistic concept in the formation of the deep meaning of the text and its conceptual space. The purpose of the work is to clarify the concept of "artistic concept", describe its features, study its conceptual space within the text. The study of the artistic concept is relevant due to the lack of identification of its features, the lack of clarification of its status as an object of any science, the unresolved issue of its conceptual space, the lack of a methodology for analyzing a literary text and the author's style. Methods used in the work: conceptual analysis, associative experiment. Results: the artistic concept is considered, its structure (which includes the following components: conceptual, significant, figurative, cultural-mental, nominative), the features of the artistic concept are described, its conceptual space is studied, the methods of its objectification are identified. The scientific novelty of the article lies in the study of the still insufficiently studied problem of the artistic concept, its functioning within the framework of the text and the study of various methods of objectification, the identification of its functions. The authors determined the associative links of the main and specific concepts, considered as associative-cognitive and associative-figurative. The associative experiment made it possible to identify associate concepts, its associative field, in which it acts as the core, and species functions as peripheral concepts. Conclusions are drawn about the need to study the artistic concept within the framework of an integral paradigm that combines the knowledge of different sciences, using their methods, which contributes to the study of the properties of this concept, to identify its role in the formation of the conceptual space of the text, actualizing the concept, various meanings of the text.
Introducing Hypergraph (Beta) 🎉

Hypergraph helps researchers reset research publishing, by publicly documenting research step by step, before the issues of after-the-fact articles even begin.
ALGORITHM FOR MULTI-CRITERIA ANALYSIS OF TEXT INFORMATION

The article is devoted to the problem of formalization of requirements for various objects and systems. Such a rigorous recording of requirements will allow not only to form their necessary and sufficient set, but also to choose the optimal order of their fulfillment – that is, to solve the problem of ranking. For this purpose, a review of relevant scientific publications of Russian scientists is carried out, in which the point of view on the formal form of recording such requirements is presented. The results of the review are systematized in tabular form. All years of publications have a range of 15 years, the field of application of requirements presents a great variety from design of information systems and mechanical devices in spacecraft to educational planning, and the proposed forms of recording consist of separate formulas and text descriptions to full-fledged models and programming languages.&#x0D; According to the results of the review, appropriate conclusions are drawn, namely the following: the relevance of the problem (at least for the last 15 years), the lack of quality solutions, a multitude of proposed forms of record with a small predominance of analytical models and programming languages, poor automation of work with requirements. It is concluded that there are no solutions, even potentially applicable for the formation of a system of requirements for information security of information systems in a unified notation. The necessity of creation of own mathematical toolkit is substantiated both for unified formalization of all requirements of various types and purposes, and for carrying out optimization measures over them on the choice of the list and order of execution. In conclusion the novelty of the conducted research, theoretical and practical significance of the work are indicated.
ALGORITHM FOR MULTI-CRITERIA ANALYSIS OF TEXT INFORMATION

The article presents the author's algorithm for multi-criteria analysis of textual information, the main purpose of which is to increase the efficiency of emergency services, including the Ministry of Emergency Situations of Russia. This algorithm is based on a comprehensive assessment of information coming from social networks using a range of different types of heterogeneous data studies.&#x0D; The developed algorithm will speed up data collection, optimize their analysis, develop preventive scenarios for possible incidents, as well as reduce resource costs, optimize management proposals and justify decisions made.
The New Information Retrieval Problem: Data Availability

ABSTRACT The goals of open science are driven by policies requiring data management, sharing, and accessibility. One way of measuring the impact of open science policies on scientific knowledge is to access data that has been prepared for re‐use. But how accessible/available are data resources? In this paper, we discuss a method for exploring and locating datasets made available by scientists from federally funded projects in the US. The data pathways method was tested on federal awards. Here we describe the method and the results from analyzing fifty federal awards granted by the National Science Foundation to pursue data resources and their availability in publications, data repositories, or institutional repositories. The data pathways approach contributes to the development of a practical approach on availability that captures the current ways in which data are accessible from federally funded science projects –ranging from institutional repositories, journal data deposit, PI and project web pages, and science data platforms, among other found possibilities. This paper discusses some background and motivations for such a method, the method, research design, barriers encountered when searching for data resources from projects, and how this method can be useful to future studies of data availability.
<scp>HERU</scp> Ontology for Linking Chinese Classics Texts and its Commentaries

ABSTRACT Commentaries are derivative texts formed by commentators' interpretations of classics texts, which not only reflect the commentators' understanding and values in their era but also play an irreplaceable role in contemporary people's understanding of classics texts. At present, the literature in which commentaries are written collected by the library is organized in commentator‐centered and it is difficult to efficiently collect all the commentaries of the same classic texts and analyze the citations in the annotation texts. The development of Semantic Web technology has changed the way of knowledge representation and provided new ideas and methods for the organization and sharing of commentaries. We use the seven‐step method to design the HERU ontology. Finally, we conduct a semantic annotation experiment using some commentaries of the Analects of Confucius as an example to illustrate the practicality of the ontology in constructing annotation diachronic evolution and citation data. This study is of great significance to the inheritance and interpretation of Chinese classics and has reference significance for the semantic management between classic texts and their commentaries in other countries.
Managing Information Gaps and <scp>Non‐Information</scp>

ABSTRACT While the focus of information science and technology research is in information, sometimes the lack of information, information gaps and non‐information can make an equally great or even greater difference. The purpose of this panel is to nuance the understanding of the absence of information and addressing the gap in theorising, investigating and working with information gaps and ‘non‐information’ across the information field. Panellists present research conceptualising, documenting, and describing information gaps and non‐information and how they are dealt with in the information field specifically addressing: 1) how conceptualisations of information gaps and non‐information influence how they emerge as describable entities; 2) what approaches to manage information gaps and non‐information exist in information science and technology research; 3) what aspects of information gaps and non‐information different approaches address, make visible and invisible; and 4) how novel insights from the current state‐of‐the‐art research can be translated to practice, policies and actions.
Building a Bigger Table: Food Research, Methods, Policy, and Action in Library and Information Science

ABSTRACT Growing global concerns over food safety, food price inflation, and climate change demand urgent attention in scientific fields. Food information behavior and practice have been a vibrant and growing research area in library and information science, following the user‐centered paradigm shift and everyday life information needs, seeking, and use research since the 1970s. Research has shown that people engage with informal and embodied information to guide food practices (e.g., shopping, cooking, eating, and sustainability transitions). Food and health research challenge research methods and approaches in everyday information behavior and inform everyday practices, technological services, policies, and actions. In this panel, following a brief introduction, each panelist will share their research approaches and/or findings about food, health, and information research. We aim to invite and foster an open discussion with audiences to explore research opportunities, challenges, and approaches to studying food in library and information science.
<scp>AI‐Based</scp> Research Tool for Large Genealogical Corpora: The Case of Jewish Communities Worldwide

ABSTRACT This paper presents a new methodology for AI‐based research and exploration of large genealogical corpora. The proposed approach is based on an automatic quantitative question‐answering (QA) system that enables researchers to ask questions in natural language and learn about trends related to individuals, families, and communities in the corpus of the study. The proposed methodology includes: 1) an automatic method for training dataset generation, 2) a transformer‐based table selection method, and 3) an optimized transformer‐based quantitative QA model. The findings indicate that the proposed architecture outperforms the state‐of‐the‐art models by achieving 87% accuracy on the large corpus of Jewish genealogical data. This study may have practical implications for genealogical information centers and museums, making genealogical data research easy and scalable for experts as well as the general public.
Enriching Library Holdings for English Language Learners: Applying Traditional Readability Formulas and Modern Cohesion Methods to Film

ABSTRACT This study evaluates the effectiveness of various readability measures when assessing the difficulty of film materials for English Language Learners (ELLs). Library materials catering to ELLs are frequently limited to formal instruction texts and fiction materials. This study explores the feasibility of less laborious, computational text assessment methods to better understand library holdings from the perspective of ELL appropriateness. The investigation applies traditional formulaic readability measures and modern cohesion methods to film subtitle data. While text difficulty assessment with readability measures has been widely studied, there is a need to investigate which measures are most suitable for film application. In addition to evaluating existing readability measures, a more robust composite score is also presented, combining aspects of traditional readability formulas and modern cohesion methods. The experiments were conducted on real‐world datasets and tested on film data marked for difficulty by ELLs.
A New Ontology for Restaurant Review Sentiment Analysis

ABSTRACT Understanding the aspects of a restaurant that contribute to people's sentiment is crucial for restaurant owners and marketers to improve customer experiences. A sentiment ontology for restaurant review sentiment analysis was proposed in this study. The proposed ontology identified six aspects of a restaurant evaluation: food, service, ambience, cleanliness, location, and price, based on 1,000 annotated Yelp data. Applying the proposed ontology in the annotated Yelp data showed that it helped improve the sentiment analysis accuracy by 11.2% on average. We believe that this study provides insights into the key factors that contribute to restaurant review sentiments.
From Ice Cores to Dinosaurs: Curation Behaviors of Physical Collections Managers

ABSTRACT Large investments of public funds to curate huge volumes of various physical samples acquired and stored over decades, and in some cases centuries, provide ample reasons to make these items as openly accessible, as easily discoverable, and as well‐documented as possible to ensure this investment results in reuse. The purpose of this study is to understand the curation behaviors of managers of physical collections. Six focus groups were conducted with twenty participants from several physical sample communities. Participants responded to open‐ended questions that relate to the entire data lifecycle for their research objects. Results indicated that physical collections would benefit from use of universal metadata and data storage standards to increase sharing across domains. Both of these factors contribute to access and use obstacles all these collections face in different ways. In the context of managers requiring more investments to encourage reuse of these invaluable items, this study hopes to provide preliminary domain‐agnostic data to inform design of collections cyberinfrastructure, resources, and services using actual curation behaviors.
Reading Comprehension in Information Retrieval (<scp>RCIR</scp>) for Personalized Results

ABSTRACT Recent research on personalized retrieval technology has been actively conducted to meet the needs of users for seeking adequate information. To refine the retrieval, researchers are considering user behavior patterns in a variety of ways. In this study, we use eye‐tracking metadata to predict users' levels of comprehension as textual evidence for IR processes. Furthermore, we incorporated eye‐tracking metadata on the Automated Readability Index (ARI), a readability assessment tool of an English text. Our research is largely divided into two tasks: i) comprehension evaluation task (CET) and ii) comprehension‐based retrieval task (CRT). In the CET task, for predicting the comprehension level, we applied various regression models. Among them, the Voting regressor demonstrated the highest performance with a Spearman's 𝜌 of 0.68. In the CRT task, we incorporated the level of comprehension predicted in the CET task and ARI score into the ranking results. We derived a sentenceBERT to find the relevant text for a query and the Normalized Discounted Cumulative Gain (nDCG) for evaluating the CRT task. The nDCG score for Comprehension Level only and that with ARI together were 0.65 and 0.78, respectively. Thus, applying ARI resulted in a higher nDCG score compared to comprehension level only.
Explanation Relevance Index – A New Way of Assessing the Quality of Explanations Based on Learned Features

The XAI methods began to emerge as a response for the black-box methods used to make decisions that could not be explained, even if checked by humans they were correct. This created the need for a better evaluation for these methods. In this paper we propose a new method for evaluation based on features. The main advantage of applying ERI to CNNs explanations are: a fully automated way to measure the quality of an explanation and the fact that the score uses the same information as the CNN, in this way being able to offer a measure of the quality of explanation that can be validated automatically.