Reviewerly/exHarmony huggingface dataset:
Practical Aspects of Studying Quantities in the Educational Field of Mathematics

The article presents the results of a study of the "Measurement" core module, in which basic mathematical competences acquired by adolescents in the course of pedagogical interaction, requiring the application of innovative methods and approaches, are laid down. Productive educational technologies, which foster development, were applied. The applications of traditional and innovative methods, means and approaches in the course of pedagogical interaction in the educational of field of Mathematics, "Measurement" core module, are sought. The goal is achieved with a survey, based on answers to standardized questions and through face-to-face conversations with the respondents. The results show that, in practice, kindergartens do not encourage the experiment-based search for knowledge about quantities. There is a lack of knowledge surrounding the use of autodidactic games, wherein they are related to quantities and measurements, as well as episodical use of innovative methods and technologies. There is substantial proof that there is a need to increase teachers’ professional competences, as far as the application of innovative methods and approaches within the study core “Measurement”. Prospects for improving the qualifications of teachers on the subject are outlined.
On Several New Dempster-Shafer-Inspired Uncertainty Measures Applicable for Active Learning

Uncertainty-based sampling is one of the most successful and commonly used techniques in active learning. The key element of this approach is an uncertainty function that measures the informativeness of cases from the data pool and is one of the main query selection criteria. In this paper, we investigate the mathematical properties of popular uncertainty functions. We also propose a new family of functions that are inspired by Dempster-Shafer’s theory of evidence. Finally, we conduct a series of experiments in which we test the proposed functions against commonly used benchmarks. We argue that our approach is a safe choice for real-life active learning applications.
A Causal Disentangled Multi-granularity Graph Classification Method

Graph data widely exists in real life, with large amounts of data and complex structures. It is necessary to map graph data to low-dimensional embedding. Graph classification, a critical graph task, mainly relies on identifying the important substructures within the graph. At present, some graph classification methods do not combine the multi-granularity characteristics of graph data. This lack of granularity distinction in modeling leads to a conflation of key information and false correlations within the model. So, achieving the desired goal of a credible and interpretable model becomes challenging. This paper proposes a causal disentangled multi-granularity graph representation learning method (CDM-GNN) to solve this challenge. The CDM-GNN model disentangles the important substructures and bias parts within the graph from a multi-granularity perspective. The disentanglement of the CDM-GNN model reveals important and bias parts, forming the foundation for its classification task, specifically, model interpretations. The CDM-GNN model exhibits strong classification performance and generates explanatory outcomes aligning with human cognitive patterns. In order to verify the effectiveness of the model, this paper compares the three real-world datasets MUTAG, PTC, and IMDM-M. Six state-of-the-art models, namely GCN, GAT, Top-k, ASAPool, SUGAR, and SAT are employed for comparison purposes. Additionally, a qualitative analysis of the interpretation results is conducted.
What is a “Site”? Human Scales, Embodied Experiences, and the Physical-Digital Interface

Digital technology has disrupted the traditional notion of a "site" as a physical space, to be experienced purely in bodily terms. No longer are websites merely perfunctory adjuncts to their physical sites, performing simple functions like disseminating visitors' information and transactions like ticket sales and fundraising. The increasing prevalence of virtual tours, interactive content, and the large amount of other data that can be housed on the virtual site makes the virtual visit less of a consolation prize and more of an interesting experience in its own right. At the same time, the physical site is not disappearing, despite these technological advances and the factors impeding physical travel (including the coronavirus epidemic, and environmental concerns about air- and long-distance travel), but remain primary to our own embodied experience of the world. The juxtaposition of physical sites and their corresponding digital ones raises both conceptual issues (to do with what now constitutes a "site", particularly that of a well-known attraction or venue) and practical ones about how our narratives, methodologies, and terminologies increasingly have to deal with this gap or duality.
Navigational Strategies for Mobile Robots Using Rough Mereological Potential Fields and Weighted Distance to Goal

The present study examines the path planning methods based on rough mereological potential fields for remote mobile robots, building upon a modification of an originally designed project to prepare a foundation for three-dimensional path planning. For this purpose, we have implemented our own library for robot control and developed relevant algorithms - including AR marker recognition, image-based robot detection, and path planning based on the rough mereological potential field in conjunction with a weighted distance to the goal. These algorithms are also customized to facilitate tests in a laboratory setting. Using a video camera, the study captures real-time imagery, allowing for the continuous updating of the robot’s position on the designated map. In this paper, we show how to find the right path that a robot follows while constantly updating its position. Furthermore, the research refines the precision of the optimal path through the application of smoothing techniques, ensuring an optimized trajectory from the robot’s starting point to its destination. We demonstrate a special Euclidean distance responsible for path optimization. We present a complete project in the work, with all the elements to reproduce it. We carried out real-world tests using the Smart Element Hub cube with LED screen of the lego robot inventor kit.
On kNN Class Weights for Optimising G-Mean and F1-Score

We present two novel theorems that allow for estimating the weight parameter in (weighted) kNN while dealing with imbalanced data. More precisely, the theorems for G-mean and F1-score are presented. The theorems assume ‘totally random’ distribution i.e. lack of dependency between features and class value. These results can be used for setting the default weights of classes for kNN-type classifiers, e.g. for imbalanced learning problems. Moreover, these theorems taken together illustrate the fact that without a precise specification of the particular performance measure we are interested in, the ‘best classifier’ term can be ambiguous or even misleading.
Link Prediction for Attribute and Structure Learning Based on Attention Mechanism

Link prediction is an important research direction in complex network analysis, which aims to infer the likelihood of future connections between pairs of nodes in the network that have not yet produced edges. In real life, many relationships can be described through the network, and many practical problems can be transformed into link prediction problems. However, existing link prediction methods either rely heavily on network structure information or cannot effectively integrate network structure information and attribute information. To solve the above problems, this paper proposes a new link prediction framework ASLAM based on the attention mechanism and the adaptive extraction strategy of attribute information and structural information. Specifically, ASLAM first constructs the node semantic representation with the attribute attention mechanism, then constructs the node structure representation with the neighborhood attention mechanism, and finally makes the final prediction by adaptive merging semantic representation and structure representation. Experiments on nine real datasets show that the proposed algorithm has a great improvement in performance compared with the baseline method. Compared with the 11 baseline methods, AUC and AP increased by 0.08%–3.1% and 0.05%–3.4%, respectively, indicating the superiority of the ASLAM method.
Artificial Intelligence in Education – Pedagogical Reflections

This theoretical framework represents an author’s reflective approach, characterized by a predominant focus on descriptive, analytical, and prognostic elements. It aims to introduce artificial intelligence virtual assistants, and explore their potential in the educational context of preschool children, students and university students within the pedagogical scientific community. The paper is a theoretical analysis encompassing the understandings of virtual assistants, their evolution, pedagogical potential and pertinent reservations related to their application in education. Additionally, a concise questionnaire is administered to Bulgarian students and professors, gauging their attitudes towards the use of artificial intelligence in university didactics. Importantly, it is imperative to emphasize that this investigation does not challenge traditional pedagogical approaches; rather, it serves to complement and enrich the existing theoretical and practical knowledge base. Such enrichment becomes essential in response to the shifting dynamics of societies in the post-digital era, alongside the distinctive characteristics of the contemporary learning generations. As society progresses towards an increasingly digital future, the transformation of education into a more digital-oriented landscape becomes an inevitable necessity.
Criteria and systems for individual assessment of a scientist: world experience

The scientific research method of bibliometrics has been used for many years to evaluate and analyze specific areas of research; However, the structure according to which the results of the scientific work of individual researchers are assessed using bibliometric methods has not yet been clearly formulated. This work is aimed at searching, identifying and developing key indicators of a scientist’s individual performance and the factors that shape this performance. Today, the most common and most convenient ways to determine the degree of effectiveness of individual researchers’ scientific searches is the number of publications and the number of citations. However, they do not fully reflect the results that researchers have in opposite fields of knowledge, for example, physics and linguistics. The presented research includes the development of practical recommendations for the selection and focus of individual indicators and criteria, respectively, in the areas of their application (branches of the scientist’s scientific activity). The findings and results obtained can be used as a basis for further scientific research on this topic, as well as for the development of government methods for individual assessment of a scientist during various events, such as competitions, scholarships, etc.
A Blended Teaching Procedure of Spatial Statistics Course based on the Knowledge Map Analysis of Teaching Methods of Science

The era of big data has brought increasing attention to spatial statistics due to the vast amounts of spatially-referenced data from sources such as remote sensing, GPS tracking, and social media. However, traditional spatial statistics courses are often teacher-centered, leading to students struggling with the concepts and lacking practical application skills. This article presents a knowledge map analysis of science education teaching methods and proposes a novel teaching procedure for the spatial statistics course. Bibliometrics and scientific mapping techniques were employed to analyze citation data from the Web of Science (WOS) and China National Knowledge Internet (CNKI) from 2000 to 2022. The study identified the research status and development trends of science teaching methods and proposed a blended teaching approach based on an intelligent problem library, combining multiple methods and online teaching materials, to enhance students' learning outcomes. This research offers valuable insights into effective teaching methods, emphasizing the need to adapt strategies to specific course requirements. It also highlights the usefulness of R and VOSviewer software in conducting knowledge map analyses of teaching methods in science education. Although further testing is necessary to determine the effectiveness of the proposed reform, this study has significant implications for science education.
Script-Generated Picture Book Technology Based on Large Language Models and AIGC

This paper mainly discusses how to use the large language models such as GPT and Ernie model combined with the AIGC tools represented by stable diffusion, which uses a random story script to generate images with fixed style, character characteristics, and continuous plots. The article provides a detailed introduction to how to build an assembly line, using a large language model and a story script to generate the prompt words required for stable diffusion. Subsequently, by comparing the characteristics of traditional picture book production and the image results of using language models word prompts, summarize the limitations of text to images. This leads to a supervised multi round iterative LoRA model scheme that utilizes the CLIP to achieve character IP fixation. Simultaneously using the ControlNet model and inpainting to preprocess and reprocess the image can achieve controllable character poses and fixed backgrounds in the picture book. Finally, we will evaluate and summarize the new scheme and analyze its strengths in picture book creation accordingly.
Forming of Computational Skills through Online Simulators

The article suggests a form of organizing students' independent work using digital technologies (math simulators made up of STACK-type tasks), which provide not only control and assessment of the quality of students' work, but also contribute to the development of students' computing skills, provide instant feedback and provide the training function of the proposed tasks. The analysis of the positive and negative aspects of the impact of online simulators on the course of students' education was carried out. The economic advantages of using online simulators for a teacher by students are discussed.
A type of public - key block cipher algorithm

The paper proposes a type of block cipher algorithm based on cryptographic hash function and public key cryptography. The algorithm proposed here is capable of verifying the origin and integrity of the encrypted message. On the other hand, establishing a shared secret key between the sender/encryptor and the receiver/decryptor can be done for each message separately.
Research and Analysis of Factors Influencing the Passing Rate of CET-4 in Local Universities

With the rapid development of social information and economic globalization, English has become widely prevalent worldwide. As a "global language," English significantly influences language teaching policies and practices globally, particularly in China, where a national College English Test Band-4 has been established. Since its inception, the College English Test Band-4 has evolved into one of the most crucial assessments for evaluating college students’ foreign language proficiency. Recently, a growing number of local university students in China are grappling with the challenge of failing to pass this exam. Therefore, this study examines the influencing factors on the passing rate of the College English Test Band-4, based on surveys conducted among undergraduate students in 2020 and 2021 at Hulunbuir College. The paper employs cross-analysis and regression tests to analyze the factors affecting the passing rate of CET-4 among local undergraduate college students, drawing relevant conclusions. Additionally, the study proposes suggestions for English learning strategies tailored to the needs of local undergraduate college students. Factors such as gender, English scores in the college entrance examination, and daily English learning methods are identified as having a significant impact on the passing rate of CET-4.&#x0D;
Comparative Study of Face-to-Face and Online Teaching Outcomes in Biology

Since the introduction of the Internet in China in 2000, the number of Internet users has consistently grown (TITC, 2010). Amidst the global pandemic, electronic applications have proven advantageous in delivering education. In this study, we designed a progress test involving 60 students who covered the same content in the biology course at the Vocational Education College of China's Ministry of Education and Culture, both through online and inclass formats. There was no significant difference in the overall results for the first semester between students who studied biology online and those in the traditional classroom setting. However, the test scores of online students were found to be slightly lower than those of their counterparts in the classroom. The reliability of the evaluation task developed in this study is deemed good, and improvement is needed, particularly in terms of the discrimination index, which stands at 54.4%. About 32.1% of the tasks were rated as good or very good, with the majority (78.8%) being categorized as relatively easy based on the difficulty index. Based on our research findings, it is plausible to consider conducting biology lessons in the future through online or hybrid courses in addition to traditional classroom settings.&#x0D; Биологийн хичээлийн цахим болон танхимын сургалтын үр дүнг харьцуулсан судалгаа&#x0D; БНХАУ-д 2000 оноос цахим сүлжээ нэвтэрч жилээс жилд цахим хэрэглэгчдийн тоо өссөөр байна. Дэлхий нийтийг хамарсан цар тахлын үед энэхүү цахим хэрэглээ нь боловсролын салбарт тулгамдсан сургалтыг явуулахад давуу тал болсон юм. Бидний судалгаа БНХАУ-ын ӨМӨЗО-ны мэргэжлийн боловсрол олгох коллежийн Биологийн хичээлийн ижил агуулгыг цахим болон танхимаар судалсан нийт 60 суралцагсдаас явцын шалгалтын даалгавар боловсруулж авсан. Энэхүү даалгаврын найдвартай байдал, хүндрэлийн болон ялгах чадварын индексийг тооцож, цахим болон танхимын сургалтын талаар асуулга судалгаа авав. Биологийн хичээлийг цахим болон танхимаар судалсан суралцагсдын нэгдүгээр улирлын ерөнхий дүнг харьцуулахад ялгаагүй, цахимаар судалсан суралцагсдын шалгалтын оноо танхимаар судалсан суралцагсдаас бага байв. Бидний боловсруулсан үнэлгээний даалгаврын найдвартай байдал сайн, ялгах чадварын индексээр даалгаврыг засаж сайжруулах шаардлагатай даалгавар 67.9%; сайн, маш сайн даалгавар 32.1% гарсан бол хүндрэлийн индексээр даалгаврын ихэнх хувийг (78.8%) хөнгөн даалгавар эзэлж байв. Судалгааны асуулгын үр дүнгээр биологийн хичээлийг танхимаас гадна хосолсон сургалтаар явуулах боломжтойг харуулж байна. Түлхүүр үг: Биологийн хичээл, Цахим, Танхим
The ICE Model: Evaluating In-Cockpit Child-Centric Interaction Solutions

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Effective smart cockpit interaction design can address the specific needs of children, offering ample entertainment and educational resources to enhance their on-board experience. Currently, substantial attention is focused on smart cockpit design to enrich the overall travel engagement for children. Recognizing the contrasts between children and adults in areas such as physical health, cognitive development, and emotional psychology, it becomes imperative to meticulously customize the design and optimization processes to cater explicitly to their individual requirements. However, a noticeable gap persists in both research methodologies and product offerings within this domain. This study employs user survey to delve into children’s on-board experiences and utilization of current child-centric in-cockpit interaction solutions (C-SI Solutions), that over 50% of the interviewees (children) got on-board at least several times per week and over half of the parents would pay for C-SI Solutions, but less than 8% of the interviewees reported actual usage. By employing an interdisciplinary approach that harmonizes Design Thinking and Developmental Psychology, this research reveals that the traditional cockpit is actually a liminal space for children, and introduces the ICE Model (Evaluation Model for In-Cockpit Child-Centric Interaction Solutions) for providing insights into C-SI solution design. This model is consisted of two modules: IPO-Based Structured Module and I&amp;amp;C (Intelligence &amp;amp; Consciousness) Evaluation Module. IPO-Based Structured Module is based on the IPO (Input-Process-Output) Model and for interpreting C-SI Solution’s structure, so that to realize the paradigm shift in Design Thinking. I&amp;amp;C Evaluation Module, the second one, is for analyzing C-SI Solution’s psychological developmental function. The ICE model is then applied to conduct market research, aiming to identify challenges and shortcomings with current C-SI Solutions. Subsequently, this research offers recommendations and possibilities for the improvement of designing C-SI Solutions, that it requires not only seamless cooperation between designers and engineers, but also interdisciplinary collaboration.&lt;/div&gt;&lt;/div&gt;
Lane Changing Comfort Trajectory Planning of Intelligent Vehicle Based on Particle Swarm Optimization Improved Bezier Curve

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;This paper focuses on lane-changing trajectory planning and trajectory tracking control in autonomous vehicle technology. Aiming at the lane-changing behavior of autonomous vehicles, this paper proposes a new lane-changing trajectory planning method based on particle swarm optimization (PSO) improved third-order Bezier curve path planning and polynomial curve speed planning. The position of Bezier curve control points is optimized by the particle swarm optimization algorithm, and the lane-changing trajectory is optimized to improve the comfort of lane changing process. Under the constraints of no-collision and vehicle dynamics, the proposed method can ensure that the optimal lane-changing trajectory can be found in different lane-changing scenarios. To verify the feasibility of the above planning algorithm, this paper designs the lateral and longitudinal controllers for trajectory tracking control based on the vehicle dynamic tracking error model. The simulation is carried out in the Carsim-Simulink co-simulation platform. The simulation results show that the trajectory planning method proposed in this paper can ensure the safety and efficiency of lane changing of the vehicle in the process of lane changing, and has better performance in ride comfort.&lt;/div&gt;&lt;/div&gt;
Addressing Governance Challenges of Digitalisation and Sustainability: A Perspective of Central Bank Digital Currency

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