Reviewerly/exHarmony huggingface dataset:
Learning Theory of Distribution Regression with Neural Networks

In this paper, we aim at establishing an approximation theory and a learning theory of distribution regression via a fully connected neural network (FNN). In contrast to the classical regression methods, the input variables of distribution regression are probability measures. Then we often need to perform a second-stage sampling process to approximate the actual information of the distribution. On the other hand, the classical neural network structure requires the input variable to be a vector. When the input samples are probability distributions, the traditional deep neural network method cannot be directly used and the difficulty arises for distribution regression. A well-defined neural network structure for distribution inputs is intensively desirable. There is no mathematical model and theoretical analysis on neural network realization of distribution regression. To overcome technical difficulties and address this issue, we establish a novel fully connected neural network framework to realize an approximation theory of functionals defined on the space of Borel probability measures. Furthermore, based on the established functional approximation results, in the hypothesis space induced by the novel FNN structure with distribution inputs, almost optimal learning rates for the proposed distribution regression model up to logarithmic terms are derived via a novel two-stage error decomposition technique.
Derivative Free Weight-space Ensembling

Recent work suggests that interpolating between the weights of two specialized language models can transfer knowledge between tasks in a way that multi-task learning cannot. However, very few have explored interpolation between more than two models, where each has a distinct knowledge base. In this paper, we introduce Derivative Free Weight-space Ensembling (DFWE), a new few-sample task transfer approach for open-domain dialogue. Our framework creates a set of diverse expert language models trained using a predefined set of source tasks. Next, we finetune each of the expert models on the target task, approaching the target task from several distinct knowledge bases. Finally, we linearly interpolate between the model weights using a gradient-free-optimization algorithm, to efficiently find a good interpolation weighting. We demonstrate the effectiveness of the method on FETA-Friends outperforming the standard pretrain-finetune approach.
Random Number Generators and Seeding for Differential Privacy

Differential Privacy (DP) relies on random numbers to preserve privacy, typically utilising Pseudorandom Number Generators (PRNGs) as a source of randomness. In order to allow for consistent reproducibility, testing and bug-fixing in DP algorithms and results, it is important to allow for the seeding of the PRNGs used therein. In this work, we examine the landscape of Random Number Generators (RNGs), and the considerations software engineers should make when choosing and seeding a PRNG for DP. We hope it serves as a suitable guide for DP practitioners, and includes many lessons learned when implementing seeding for diffprivlib.
Physics-Constrained Hardware-Efficient Ansatz on Quantum Computers that is Universal, Systematically Improvable, and Size-consistent

Variational wavefunction ans\"{a}tze are at the heart of solving quantum many-body problems in physics and chemistry. Previous designs of hardware-efficient ansatz (HEA) on quantum computers are largely based on heuristics and lack rigorous theoretical foundations. In this work, we introduce a physics-constrained approach for designing HEA with rigorous theoretical guarantees by imposing a few fundamental constraints. Specifically, we require that the target HEA to be universal, systematically improvable, and size-consistent, which is an important concept in quantum many-body theories for scalability, but has been overlooked in previous designs of HEA. We extend the notion of size-consistency to HEA, and present a concrete realization of HEA that satisfies all these fundamental constraints while only requiring linear qubit connectivity. The developed physics-constrained HEA is superior to other heuristically designed HEA in terms of both accuracy and scalability, as demonstrated numerically for the Heisenberg model and some typical molecules. In particular, we find that restoring size-consistency can significantly reduce the number of layers needed to reach certain accuracy. In contrast, the failure of other HEA to satisfy these constraints severely limits their scalability to larger systems with more than ten qubits. Our work highlights the importance of incorporating physical constraints into the design of HEA for efficiently solving many-body problems on quantum computers.
We, Vertiport 6, are temporarily closed: Interactional Ontological Methods for Changing the Destination

This paper presents a continuation of the previous research on the interaction between a human traffic manager and the UATMS. In particular, we focus on the automation of the process of handling a vertiport outage, which was partially covered in the previous work. Once the manager reports that a vertiport is out of service, which means landings for all corresponding agents are prohibited, the air traffic system automates what it has to handle for this event. The entire process is simulated through knowledge representation and reasoning. Moreover, two distinct perspectives are respected for the human supervisor and the management system, and the related ontologies and rules address their interactions. We believe that applying non-monotonic reasoning can verify each step of the process and explain how the system works. After a short introduction with related works, this paper continues with problem formulation, primary solution, discussion, and conclusions.
Guideline for Trustworthy Artificial Intelligence -- AI Assessment Catalog

Artificial Intelligence (AI) has made impressive progress in recent years and represents a key technology that has a crucial impact on the economy and society. However, it is clear that AI and business models based on it can only reach their full potential if AI applications are developed according to high quality standards and are effectively protected against new AI risks. For instance, AI bears the risk of unfair treatment of individuals when processing personal data e.g., to support credit lending or staff recruitment decisions. The emergence of these new risks is closely linked to the fact that the behavior of AI applications, particularly those based on Machine Learning (ML), is essentially learned from large volumes of data and is not predetermined by fixed programmed rules. Thus, the issue of the trustworthiness of AI applications is crucial and is the subject of numerous major publications by stakeholders in politics, business and society. In addition, there is mutual agreement that the requirements for trustworthy AI, which are often described in an abstract way, must now be made clear and tangible. One challenge to overcome here relates to the fact that the specific quality criteria for an AI application depend heavily on the application context and possible measures to fulfill them in turn depend heavily on the AI technology used. Lastly, practical assessment procedures are needed to evaluate whether specific AI applications have been developed according to adequate quality standards. This AI assessment catalog addresses exactly this point and is intended for two target groups: Firstly, it provides developers with a guideline for systematically making their AI applications trustworthy. Secondly, it guides assessors and auditors on how to examine AI applications for trustworthiness in a structured way.
Error-tolerant quantum convolutional neural networks for symmetry-protected topological phases

The analysis of noisy quantum states prepared on current quantum computers is getting beyond the capabilities of classical computing. Quantum neural networks based on parametrized quantum circuits, measurements and feed-forward can process large amounts of quantum data to reduce measurement and computational costs of detecting non-local quantum correlations. The tolerance of errors due to decoherence and gate infidelities is a key requirement for the application of quantum neural networks on near-term quantum computers. Here we construct quantum convolutional neural networks (QCNNs) that can, in the presence of incoherent errors, recognize different symmetry-protected topological phases of generalized cluster-Ising Hamiltonians from one another as well as from topologically trivial phases. Using matrix product state simulations, we show that the QCNN output is robust against symmetry-breaking errors below a threshold error probability and against all symmetry-preserving errors provided the error channel is invertible. This is in contrast to string order parameters and the output of previously designed QCNNs, which vanish in the presence of any symmetry-breaking errors. To facilitate the implementation of the QCNNs on near-term quantum computers, the QCNN circuits can be shortened from logarithmic to constant depth in system size by performing a large part of the computation in classical post-processing. These constant-depth QCNNs reduce sample complexity exponentially with system size in comparison to the direct sampling using local Pauli measurements.
Pengaruh Penggunaan Video Animasi Terhadap Minat Belajar Siswa Pada Tema Organ Gerakan Hewan Di Kelas V Sekolah Dasar

Student involvement and participation in the learning process has not shown student activity. Students tend to be less enthusiastic and proactive in participating in learning. This study aims to determine the effect of animated videos on increasing interest in learning and student perceptions. This type of research is experimental research with a research design using a non-equivalent control group design. The subjects of this study were fifth grade elementary school students as the population and sample. The sampling technique used purposive sampling. The research instrument used test and lift. The data analysis used was hypothesis testing on students' interests and perceptions. The results showed that there was no difference between the students' initial abilities before the application of animated video media between the experimental and control classes. Meanwhile, the final ability and interest in student learning after the application of animated video media experienced a significant difference. Perceptions of experimental class students towards animated video media showed a very good attitude. It can be concluded that animated videos are proven to have a significant influence on students' interests and perceptions
Elementary Algorithms – Prefix Sum

In this paper we present a special problem, named as prefix sum, and its variations. We analyse the base problem more detailed and compare the possible solutions. Our students solved simi-lar problems in competitions, so we have statistics about their solutions. We offer this article for those readers who are interested in programming methodology, or who are teachers, and their students will be participated in competitions.
Secondary School Programming Olympiads in Gomel Region

This article describes the content of programming competitions for students in grades 5–8 of the Gomel region. A general idea of the content of the tasks and examples of tasks by topic are given. The methodology for teaching and preparing schoolchildren for such Olympiads is also briefly described. A serious technical basis is the instrumental system of distance learning developed under the supervision of the author (http://dl.gsu.by).
ANALYSIS OF THE DETERMINING FACTORS OF UNEMPLOYMENT IN THE CITY OF NAMPULA

Economic theories point to variables such as inflation, age and level of education as some of the determining factors for the occurrence of unemployment.Therefore, this research was designed with the objective of analyzing the factors that determine unemployment in the city of Nampula, in the period between 2020 and 2022.To achieve this objective, it was necessary to design a regression model of the variables that determine unemployment as well as the use of univariate, bivariate and multivariate analyses.For the research, statistical methods were used, that is, the Ordinary Least Squares Method (OLS), with a quantitative methodology, through data from secondary sources and the use of the STATA 12.0 software, based on which it was possible to estimate the regression.The research results show that the determining variables of the unemployment rate in the city of Nampula during the period under analysis were the level of education and gender.
Optimization design of electronic commerce system based on the basic principles of software engineering

Based on the basic principles of software engineering, this paper optimizes the design of e-commerce system from the aspects of demand analysis, system design, coding, implementation, testing and maintenance. Specifically, this paper adopts the object-oriented software development method, using the UML modeling tools to model the system, adopted the MVC architecture mode to realize the stratification of the system, using the front-end technology such as HTML, CSS, JavaScript to realize the user interface design of the system, combined with the back-end technology such as Java, JSP, the Servlet system. Through the system test and the use of code quality control tools, the system is accepted, and the maintenance of the system is planned and designed. Finally, this paper realizes an easy-to-use, stable, safe and efficient e-commerce system.
Deepening research on the construction thought of intelligent substation aerial survey auxiliary system

In the construction and development of modern society, the rational use of intelligent system is the inevitable trend of the development of the world's electric power, and the comprehensive promotion of smart grid is the basic consensus of the world's innovation. Substation intelligentization belongs to a gradual in-depth development process, which will change from traditional substation to integrated automation station, and then to digital substation, and finally become smart substation. Nowadays, Chinese power grid enterprises have already realized the large-scale construction and management of digital substations, and put forward the development goals and basic plans for the construction of smart substations. In 2020, the intelligent development probability of important substations has reached 100%. Therefore, after understanding the construction scheme and development status of smart substation system, this paper mainly discusses the construction ideas and main structure of the new generation of smart substation line measurement auxiliary system, and then defines the future development direction of smart substation auxiliary system, in order to provide effective basis for the construction and operation of power system in the new era.
GAMIFICATION TECHNOLOGIES IN THE EDUCATIONAL PROCESS OF SMART-TNPU IN THE COMPUTER SCIENCE TEACHING

The article describes the features of the gamification technologies used in the educational process of SMART-TNPU, based on the work experience of researchers of Ternopil Volodymyr Hnatiuk National Pedagogical University (TNPU). An analysis of the game technologies implementation in the process of learning computer science at the university and general secondary education institutions was conducted. In the conditions of martial law, the situation with gamification of education is considered, the role of gamification in the educational process is determined. Significant achievements of the teachers of the Department of Computer Science in the study of problems related to the game technologies used in classes with different age groups of pupils and students are described. The conducted research helped to identify the main playgrounds and platforms that contribute to the development of digital competences of the participants of the educational process, help them create their own game projects. Approaches to the stages of implementing gamification in the SMART-TNPU system have been analyzed. The specifics of each stage of gamification are defined, the analysis of game project creation services and their use is presented. The main types of gamification in the educational process are outlined. The examples of student game projects and tasks are provided. The spheres of positive influence of gamification technologies using a Likert scale are substantiated, and caveats regarding their mass use are indicated. Gamification is an example of the use of innovative technologies, which contributes to increasing the efficiency of the organization of the educational process and achieving high results in the training of a modern computer science teacher.
STUDY GUIDE FOR PRIMARY SCHOOL STUDENTS: SCIENTIFIC APPROACHES TO DEVELOPMENT AND DESIGN

The article deals with the essence and requirements for developing and creating a new type of educational publication – a study guide for students of grades 1-2 of general secondary education institutions, designed to replace current textbooks on the Ukrainian language and Reading, and Mathematics. This study guide will implement the functions of a textbook and a workbook. Based on the analysis of the purpose of the specified publication as a textbook and workbook, there have been formulated the generalized requirements for this type of educational literature. Firstly, a study guide is to comply with the educational program of the specified educational subject or integrated course. Secondly, the study guide has to be developed taking into account the principles of national orientation, child-centeredness, forming the subject and key competencies, motivational support, and developmental orientation. Thirdly, it should be developed on basis of Ukrainian studies and include a combination of universal and national values. Fourthly, it should diversify the activities of schoolchildren on educational material, in particular, provide for work in pairs and groups.&#x0D; There have been outlined the requirements for illustrating such books. They include the general ones, which relate to the illustration of educational publications in general (requirements for the connection of illustrative material with the text and other structural components of a study guide. Here also belong the special ones (adaptation of the visual series of a study guide to the age characteristics of primary school students, a set of hygienic requirements for the illustrative material of study guides for primary school, a number of artistic and aesthetic requirements, as well as additional recommendations for the use of illustrative material. The article highlights the peculiarities of illustrating textbooks / study guides for certain educational subjects (primers, language and mathematics textbooks).
SCIENTIFIC APPROACHES TO FORMING READINESS FOR PROFESSIONAL SELF-IMPROVEMENT OF FUTURE SPECIALISTS IN MUSICAL ART

The article is devoted to the substantiation of the leading scientific approaches to the problem of forming the readiness of future music specialists for professional self-improvement. The role and place of the scientific approach in the structure of methodology as a teaching is determined, and its definition is defined. The analysis of such scientific approaches as: acmeological, synergistic, person-oriented, cultural, axiological, activity, environmental, from the standpoint of which the leading aspects of the problem of professional self-improvement in the professional training of future teachers were investigated and certain features of the implementation of the process of forming the readiness of future teachers-musicians for the specified activity. It was determined that the acmeological approach in the context of the research problem acts as a process of conscious development of potential opportunities, qualities and properties of the individual; the cultural approach involves the formation of the professional worldview of future specialists, their personal and professional values, orientations, guidelines and is based on the desire to independently master and deepen the level of professional knowledge, skills and abilities; the synergistic approach involves a clear structuring of the process of professional self-improvement and its activation by ensuring the process of self-organization and self-development of the individual; the axiological approach is based on the emergence of the need and value orientations for professional self-improvement, awareness of the importance of professional activity and, accordingly, provides opportunities for its analysis and regulation in order to improve it; the activity approach is based on personal activity in the process of educational activity, which involves self-organization of the individual, implementation of systematic self-control and self-analysis of one's own activities, orientation towards self-transformation and transformation of the surrounding world; the environmental approach constitutes a system of opportunities for managing the process of self-change of the individual, determining the optimal ways of its implementation and aiming at achieving high results. Based on the results of the analysis, it was concluded that the specified scientific approaches in their interaction and integrity serve as a conceptual basis for the effective construction of the process of preparing future music specialists for professional self-improvement, become the basis for determining the structure and characteristics of the relevant structural components of readiness for professional self-improvement of future music specialists and justification of certain organizational and pedagogical conditions of its formation. As a result of the research, a conclusion was made regarding the role and significance of the implementation of selected scientific approaches in the process of forming the personality of a student of higher education as a future professional teacher.