Reviewerly/exHarmony huggingface dataset:
Direct distortion prediction method for AR-HUD dynamic distortion correction

Dynamic distortion is one of the most critical factors affecting the experience of automotive augmented reality head-up displays (AR-HUDs). A wide range of views and the extensive display area result in extraordinarily complex distortions. Existing methods based on the neural network first obtain distorted images and then get the predistorted data for training mostly. This paper proposes a distortion prediction framework based on the neural network. It directly trains the network with the distorted data, realizing dynamic adaptation for AR-HUD distortion correction and avoiding errors in coordinate interpolation. Additionally, we predict the distortion offsets instead of the distortion coordinates and present a field of view (FOV)-weighted loss function based on the spatial-variance characteristic to further improve the prediction accuracy of distortion. Experiments show that our methods improve the prediction accuracy of AR-HUD dynamic distortion without increasing the network complexity or data processing overhead.
Improving Quality of Service for Users of Leaderless DAG-Based Distributed Ledgers

Usability of distributed ledgers is crucial to their mainstream adoption, especially for enterprise applications in which most users do not wish to operate full-node infrastructure. Some attempts have been made to solve the problem of user-node interaction for blockchains in which leaders assemble users’ transactions into blocks, but in the case of leaderless DAG-based ledgers such as IOTA, many of these solutions cannot be applied due to the absence of a shared mempool and the ability of nodes to issue blocks in parallel. In this work, we propose a user-node interaction mechanism for ledgers of this kind that is designed to balance user traffic across nodes and ensure the risk of a user experiencing a poor quality of service is low. Our mechanism involves users selecting nodes to issue their transactions to the ledger based on quality of service indicators advertised by the nodes. Simulation results are presented to illustrate the efficacy of the proposed policies.
Impact of Digitalization on Social Entrepreneurship

This research work demonstrates the method of examining the influence of digitalization in social entrepreneurial perspectives. For this purpose, three major digital transformation domains, namely, blockchain, artificial intelligence (AI) and cloud services were considered. For all three domains, their adoption over time is studied and further analyzed. Consequently, it is observed that all three have a noteworthy positive influence to improve the business performance, trade, supply chain and similar disciplines. For the blockchain, their user activity like addition of new wallets, transactions made and the market price for bitcoins over time was used. For AI, data from tech fundings prior to the year 2020–2021 were obtained and AI adoption in several regions was analyzed. Finally, for cloud services, cloud computing adoption data (2009–2019) at both the individual and organizational level were studied. This research is useful for business entities to further support the fact that digitalization has modernized legacy processes, enabled rapid innovation, strengthened security and increased profitability.
Employees’ training to master digital tools in the process of modeling pedagogical design for work programs in the disciplines’ psychological cycle

Objectives of the training program “Pedagogical design tools digital learning content” are: the training program’s development and testing of digital educational technology instructional design for the teaching staff of the university in the blended learning; system formation of knowledge about digital literacy and digital competence; learning the digital learning technologies’ use in the work programs of the psychological disciplines’ unit in the context of a hybrid learning. Before conducting the teaching, the author conducted a survey of the participants, which demonstrated that 77 % of respondents are willing to learn new skills; 74 % view learning as a question of personal responsibility; 80 % sure that they can adapt to new technologies in the teaching of their subject. 72 % of respondents said that they had not used digital tools before. The results also showed that the motivation for the training of teachers was an inner desire to be a professional (35,8 %); the striving for new knowledge (42,9 %). The requirement for mandatory training is important for one third of the members. The basis of training is founded on the Model 6D (6 disciplines) developed by Roy Pollock with colleagues. To help our teachers the author was developed guidelines for the development of digital skills among teachers and recorded online course (use the following tools: “Mentimetr” for training and development of personnel in the organization in the competence management system; “SessionLab” – for training of employees in the company; “Kahoot” to check the students’ knowledge on the employees’ development in the company and for online interaction; “WhenSpeak” – for analysis the performance of a corporate university, alternative methods of training and personnel development; Board “Lino” was used as an example of work on social learning within the team).
The distance learning impact on the quality of the educational process (according to the study results conducted at the State University of Management)

Digitalization is gaining momentum at a rapid pace, affecting all spheres of society, including education, where, as a result of the global Covid-19 pandemic, a forced transition from full-time to distance learning, digital format was carried out. However, the quality of educational activities during this transition has significantly decreased, as evidenced by numerous studies in 2020-2023. Therefore, it is necessary to comprehend the main problems associated with the reduction of traditional classroom educational practices and the transition from offline learning format to online format. The study purpose is to clarify the students’ opinion about the quality of educational activities in the distance learning format; to identify difficulties encountered by participants in the educational process in connection with the emergency transition to online learning; to determine the prospects of the developed online learning system at the higher education level. To achieve this goal, theoretical and empirical research methods were used, as well as qualitative and quantitative analysis of the data obtained. The sample consisted of the responses of 100 1 st -year students of the State University of Management who receive professional education in various fields of training. As a result of processing the students’ responses, a generally positive attitude towards distance education was noted, however, forced digitalization revealed the negative sides of this transition. In this regard, it is proposed to form recommendations on the need to develop the principles of an educational process combined system, providing for a combination of online and offline formats. In addition, the author’s task is to offer modern interactive techniques that will be used on online platforms in order to increase interest in learning and improve the quality of the educational process.
Neuro-explicit semantic segmentation of the diffusion cloud chamber

For decades, in diffusion cloud chambers, different types of subatomic particle tracks from radioactive sources or cosmic radiation had to be identified with the naked eye which limited the amount of data that could be processed. In order to allow these classical particle detectors to enter the digital era, we successfully developed a neuro-explicit artificial intelligence model that, given an image from the cloud chamber, automatically annotates most of the particle tracks visible in the image according to the type of particle or process that created it. To achieve this goal, we combined the attention U-Net neural network architecture with methods that model the shape of the detected particle tracks. Our experiments show that the model effectively detects particle tracks and that the neuro-explicit approach decreases the misclassification rate of rare particles by 73% compared with solely using the attention U-Net.
Medoid based semi-supervised fuzzy clustering algorithms for multi-view relational data

In this paper we present two novel families of semi-supervised multi-view clustering algorithms for relational data, providing relevance weights for views and cluster representatives. The families differ by their cluster representative approach: set-medoids and vector set-medoids. Each family possesses four models, referred to as variants, differing by their weighting approach and the constraints imposed on those weights. Semi-supervision is attained through the use of must-link and cannot-link pairwise constraints. The algorithms perform the clustering task through the minimisation of an objective function; such minimisation is achieved through the iteration of three steps until convergence, namely: search for the best representatives, computation of the best relevance weights, and computation of the best fuzzy partition. Experiments performed on several real datasets show that those algorithms have greater robustness than other semi-supervised multi-view fuzzy clustering algorithms when handling the pairwise constraints and provide better interpretability of the results. Moreover, those experiments reveal that one family may perform better than the other depending on the data being considered; this can also be observed for the variants within each family. Furthermore, the proposed algorithms were tested in a real multi-view dataset where a synthetic noise view was added; it was observed that those algorithms managed to maintain a good level of quality in the resulting partition as well as discriminating the noise view by assigning it a lower relevance weight.
Robustness of Classification Algorithm in the Face of Label Noise

Label noise is an important part in the process of machine learning. Transition matrix provides an effective way to reduce the impact of label noise on classification algorithm. In this experiment, we study logistic regression algorithm and random forest algorithm. We use the known real transition matrix to evaluate the robustness of the algorithm on two datasets. We also design a transition matrix estimator to estimate the transition matrix of three datasets and evaluate the robustness of the two algorithms. We use average error to evaluate the effectiveness of the transition matrix estimator and the top-1 accuracy to evaluate our method.
Advancing Internationalization Agenda Amidst the War in Ukraine: Kindness and Trauma-Informed Teaching Project in Teacher Education

The paper aims to describe and analyze graduate students' collaborative online learning project between Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University, Vinnytsia [VSPU] Ukraine, and Worcester State University [WSU], Massachusetts, USA, as one of the outcomes of the internationalization agenda in Ukraine. Since the war in Ukraine and the increased acts of violence in the U.S. require immediate action, the “Kindness and Trauma-Informed Teaching” project is essential. Based on a one-semester interaction for the case study, research, and project work, it is a novel practice at both educational institutions. Graduate students engaged in asynchronous and synchronous activities utilizing Zoom, Google Classroom, and Google Documents. The project was carried out under the auspices of Education USA, the American Council in Ukraine, and SUNY COIL Foundation in the USA. The findings highlight the significance of such partnerships and persuade that this project promotes further collaborative research in teacher education.
An algorithm for solving the principal ideal problem with subfields

The principal ideal principal (PIP) is the problem of deciding whether a given ideal of a number field is principal and, if it is, of finding a generator.Solving the PIP applies to solving major computational tasks in number theory.It is also connected to the search of approximate short vectors in the so-called ideal lattices which is a crucial problem in cryptography.In this paper, we present a novel application of norm relations to utilize information from subfields to solve the PIP in fields of degree larger than 1800.
Achieving a Leap in Expertise in Interpreting - Research on a Learning Platform for Network Oriented Collaborative Interpretation Expertise Based on Deliberate Practice Strategy

The improvement of interpretation expertise has gone through the development stage from novice to expert. In the developmental process of expert interpreters, the key is to enhance the interpretation expertise through deliberate practice. Deliberate practice is a concept firstly put forward by Ericsson to answer the question of how genius excels. This paper discusses how to better the mental representation and adaptive mechanism of novice by introducing the IPTAM system, a collab·orative interpretation learning platform. IPTAM (Interpreter Professional Training and Acquisition Module) for short. It is a modular interactive Online interpreting learning platform.
The reform of the training mode of building intelligent engineering technology professionals based on the Internet of Things smart home 1 + X certificate

As the third batch of “1+X” certificate pilots, the integration and application of the Internet of Things smart home system is of great significance to the reform of talent training programs for building intelligent engineering technology majors in higher vocational colleges. Integrate the standard of “educational certificate + vocational skill certificate” into the training plan for building intelligent engineering technology professionals, and reform the teaching of “project penetration and module progression” by reconstructing the “platform foundation + course certificate integration” curriculum Methods and methods such as building a “trinity” functional teaching team, to achieve the integration of courses and certificates , and to cultivate compound talents majoring in building intelligent engineering technology.
Research on the Path of Improving the Quality of Education Funded by Universities under the Perspective of Five Education

With the overall victory of the battle against poverty in China, the funding work of colleges and universities is also facing new opportunities and challenges, and the funding work is gradually changing from economic funding to development-oriented funding. In this paper, “five education simultaneously” as the background, the current funding education work significance and problems, from moral education, intellectual education, physical education, aesthetic education, labor education perspective, module put forward the current funding education quality improvement path in colleges and universities, in order to establish a long-term mechanism for funding education work, build multi-level education platform to provide new ideas and suggestions.
Convergence Rates of the Stochastic Alternating Algorithm for Bi-Objective Optimization

Stochastic alternating algorithms for bi-objective optimization are considered when optimizing two conflicting functions for which optimization steps have to be applied separately for each function. Such algorithms consist of applying a certain number of steps of gradient or subgradient descent on each single objective at each iteration. In this paper, we show that stochastic alternating algorithms achieve a sublinear convergence rate of $${\mathcal {O}}(1/T)$$ , under strong convexity, for the determination of a minimizer of a weighted-sum of the two functions, parameterized by the number of steps applied on each of them. An extension to the convex case is presented for which the rate weakens to $${\mathcal {O}}(1/\sqrt{T})$$ . These rates are valid also in the non-smooth case. Importantly, by varying the proportion of steps applied to each function, one can determine an approximation to the Pareto front.
The Path of Cultivating English Core Literacy in Higher Vocational Education in the Context of New Curriculum Standard

Higher vocational students have problems such as weak English language foundation, poor independent learning, weak awareness of multicultural communication, and insufficient communication skills in the foreign-related workplace. In view of these problems, according to the requirements of English Curriculum Standard for Higher Vocational Education (2021 Edition) for cultivating English core literacy in higher vocational education, this paper has proposed the strategies of reforming the curriculum, implementing mixed teaching, constructing typical foreign-related workplace scenarios and strengthening off-campus internship practice to integrate the concept of cultivating English core literacy into the whole process of curriculum teaching, in which way the humanity and instrumentality of vocational English curriculum can be achieved.
Interpretation of Cultural Conflict in The Joy Luck Club from Perspective of High-context and Low-context Cultures

The Joy Luck Club , a masterpiece by Amy Tan, tells the story of the mother-daughter conflicts, focusing on the differences between Chinese culture and American culture. According to the theory of high-context and low-context cultures put forward by Eward T. Hall, Chinese culture can be classified as a high-context culture, while American culture is classified as a low-context culture. In light of high-context and low-context cultures theory, this paper deeply analyzes mother-daughter conflicts in The Joy Luck Club , aiming to provide reference for exploring the right way to resolve cultural conflict. In this paper, the author introduces the main differences of high and low-context cultures, on the basis of which the cultural conflict between Chinese and American reflected in The Joy Luck Club were summarized and analyzed. The conflicts can be divided into three aspects: different ways of language expression, different understandings of the relationship between parents and children and different ways of emotional expression.
Research on the Teaching Path of Integrating Excellent Traditional Chinese Culture into the Course of “Spoken Language for Preschool Teachers”

Teaching in universities should not only meet the development needs of students’ professional skills, but also focus on imparting classroom ideological and political elements. As the core course of preschool education, “ Spoken Language for Preschool Teachers “ aims to deeply explore the connotation of traditional Chinese culture, strengthen the power, consolidate the platform, and innovate the mode of education, lead students to inherit the Chinese spirit. On the basis of analyzing the characteristics of the course “ Spoken Language for Preschool Teachers”, this article proposes specific construction plans and implementation strategies.
Spatial-Aware Multi-Directional Autoencoder For Pre-Training

Abstract Vision Transformers for pre-trained models explore semantic context and spatial relationships for images, which heavily depend on how you select image patches. In this paper, we propose a novel Spatial-aware Multi-directional Patches Multi-cycle Autoencoder (SMPMA) for a pre-trained model that brings the following benefits: (1) Spatial-aware Multi-directional (SM) patches are created with multi-directional spatial locations, transforming a whole image autoencoder problem into a short-span image patches autoencoder problem; (2) SM patches admit a self-cycle autoencoder alignment learning for the first stage and a cross-cycle interaction learning for the second stage, which makes patches align and interact for optimization; (3) SM patches enable to explore local object features and correlation distribution of adjacent pixels by taking arbitrary sampled patches as inputs. Experimental results on four downstream tasks show that our model can achieve state-of-the-art performance over the tasks of image generation, image classification and semantic segmentation.
Design of 4P-BL Teaching Mode with Four Integration

In view of the Ministry of Education “one degree for both sexes” and the new engineering construction objectives, cultivating applied undergraduate talent initiative, initiative and solve practical engineering problems become the focus. Taking the Introduction to Big Data Technology course of Geely University as an example, this paper studies the innovative design of 4P-BL teaching mode based on four-integration and the five-step teaching method.
Research on the design and practice of a blended teaching model for Chinese Language and Literature majors based on “Rain Classroom”

With the arrival of the “Internet plus” era, students’ thinking ability and way of thinking have changed, making modern teaching reform imminent. As a smart teaching tool, Rain Classroom aims to improve the overall classroom teaching experience, making teacher-student interaction and teaching more convenient. This paper conducts an in-depth study of the Chinese Language and Literature course based on the Rain Classroom, using comparative experiments to study the impact of this teaching mode on students’ learning outcomes. The results of the comparative experiment showed that the final examination results of the students in the experimental class were significantly higher than those of the control class; the results of the questionnaire survey showed that the motivation, study habits, independent learning and collaborative learning ability of the students in the experimental class had significantly improved compared with those in the control class; at the same time, more than 90% of the students approved and endorsed the “Rain Classroom” learning The overall satisfaction rate of the blended teaching mode was 92.05%.
Study on the Feasibility and Necessity of Setting Up Student Learning Center in Private Higher Education Institution

In view of the rapid development of private higher education institution in China and the differences between instructors and students composition and public universities, some students have some problems in learning methods and learning initiative. Setting up special guidance and improving students’ learning and development ability is an important measure to improve the teaching quality of private universities, which is also feasible and necessary. Learning from the successful experience of “Learning Guidance and Development Centers” of universities at domestic and abroad, this paper explores a student learning support system in accordance with the characteristics of private universities, and improves students’ independent learning ability by setting up learning guidance courses, consultation, discussion and peer assistance.