Reviewerly/exHarmony huggingface dataset:
Taxy.io@FinTOC-2020: Multilingual Document Structure Extraction using Transfer Learning

In this paper we describe our system submitted to the FinTOC-2020 shared task on financial doc- ument structure extraction. We propose a two-step approach to identify titles in financial docu- ments and to extract their table of contents (TOC). First, we identify text blocks as candidates for titles using unsupervised learning based on character-level information of each document. Then, we apply supervised learning on a self-constructed regression task to predict the depth of each text block in the document structure hierarchy using transfer learning combined with document features and layout features. It is noteworthy that our single multilingual model performs well on both tasks and on different languages, which indicates the usefulness of transfer learning for title detection and TOC generation. Moreover, our approach is independent of the presence of actual TOC pages in the documents. It is also one of the few submissions to the FinTOC-2020 shared task addressing both subtasks in both languages, English and French, with one single model.
DIRECTIONS AND TRENDS IN THE DEVELOPMENT OF NEURODIDACTICS

In this article the main directions for the development of neurodidactics are identified. The author highlights individual and typological differences in the organization of the brain, motivation for learning, the emotional-motivational component of learning, neurodidactic principles of designing a modern educational environment, diagnostics of the initial level and others. These promising areas of neurodidactics development are constantly being supplemented due to the intensive development of this pedagogical branch.
Syntax Device and Unit Disorder in Children with Mental Retardation: A Neurolinguistic Perpspective on Language Learning Innovations and Progressive Education

This study aimed at obtaining information from neurolinguistic perspective about how children with mental retardation experience language learning by focusing on syntax device and unit disorder. With a qualitative paradigm, this study involved three children with mental retardation aged 17, 12, and 13 years at a special school in East Jakarta. Data in the form of utterances from three children with mental retardation through communication interactions were collected and produced 12 recordings which were then analyzed by apply-ing content analysis technique. The results of this study indicated that there were 151 errors in the form of syntax unit disorder, and the most errors were in the form of the phrase unit, amounting to 61 errors. In terms of syntax device disorder, 37 errors were found, of which the most errors were in intonation defects, amounting to 12 errors. The conclusion of the study is that children with mental retardation experience language disorders in the form of syntax defects because they are influenced by neurological disorders. How-ever, we see that these findings should not be standard benchmarks for mental and neurological disorders, so we argue that the defects in the syntax devices and units exhibited by children with mental retardation should be seen as a componential model of language issue on which their language development should be more focused on the meaning they get from information. In other words, we cannot just stick to the results which state that children with mental retardation have language difficulties but we must focus more on what they can understand as meaningful language to them. Therefore, we recommend trying to approach it with the concept of componential model of language that may be applicable with some technologies as innovative teaching and learning for teachers as well as progressive education for the children with mental retardation for their language learning experiences.
Synthetic aperture phase-shifting interferometry for high-numerical-aperture spherical surface measurement

In testing of high-numerical-aperture spherical lenses, conventional Fizeau interferometry with a mechanical phase modulator suffers from spatial nonuniformity of the phase steps within the observation aperture. The amount of phase modulation decreases rapidly in the marginal region of the aperture due to a geometrical effect, which results in a systematic error of several nanometers in the measured object profile. We propose a synthesis of phase-shifting algorithms in which several algorithms designed for different phase steps operate on the same set of interference fringes recorded in a single phase-shift sequence. Then, the object phase is determined from each of the algorithms for each aperture division. The resultant phase distribution showed minimal systematic errors.
Initiatives of the Polish Librarians’ Association for Libraries and Readers in the First Phase of the Pandemic

Thesis / Purpose of the article ‒ The aim of the article is to present the activities undertaken by the Polish Librarians’ Association in the first period of the pandemic, which supported librarians in two areas: maintaining communication with readers and self-improvement and improving competences in the field of remote reader service. Research methods ‒ The article uses the method of analyzing available sources, i.e., reports presenting activities undertaken by the SBP and libraries until the end of June 2020, including: reports, reports posted on websites, in social media, articles in industry magazines, surveys of training preferences of librarians and online training evaluation. Results / conclusions – Showed the effects of the pandemic with regard to the services offered by libraries, the impact of SBP on increasing the dissemination of digital resources and electronic services, as well as increasing the competence of librarians in the use of tools to work with the reader in the virtual space, through online training.
Foreign software on Russian archival soil: two projects

The article is devoted to two international projects with the participation of Russian archives, in which foreign software was used. The first project is the Russian-American project for entering fond descriptions of four Russian archives (GARF, RtSHIDNI, GATO, TtSDNI) into the RLIN database. The second project is the Computerization of the Comintern Archive. The characteristics of software, goals and results of the projects are considered.
Discussion on the Reform of Mixed-English Teaching Mode of Higher Vocational English Based on “Internet +”

In today’s society, English has become a core competency that everyone needs. How to use the development advantages of “Internet +” and to develop a hybrid teaching method is the main research content of this paper. Based on this, this paper firstly summarizes the problems existing in the mixed teaching mode of vocational English from the aspects of single multimedia teaching form and the utilization rate of modern information teaching tools. Subsequently, combining traditional classroom teaching with flipped classes based on microlecture, developing mixed-English teaching, establishing a self-learning environment for students under the network platform, and proposing suggestions are the guidance for students to use the online platform for independent learning, in order to be able to provides new ideas for higher vocational English mixed teaching reform.
A Digital Quantum Algorithm for Jet Clustering in High-Energy Physics

Experimental High-Energy Physics (HEP), especially the Large Hadron Collider (LHC) programme at the European Organization for Nuclear Research (CERN), is one of the most computationally intensive activities in the world. This demand is set to increase significantly with the upcoming High-Luminosity LHC (HL-LHC), and even more in future machines, such as the Future Circular Collider (FCC). As a consequence, event reconstruction, and in particular jet clustering, is bound to become an even more daunting problem, thus challenging present day computing resources. In this work, we present the first digital quantum algorithm to tackle jet clustering, opening the way for digital quantum processors to address this challenging problem. Furthermore, we show that, at present and future collider energies, our algorithm has comparable, yet generally lower complexity relative to the classical state-of-the-art $k_t$ clustering algorithm.
DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning

The need for robust, secure and private machine learning is an important goal for realizing the full potential of the Internet of Things (IoT). Federated learning has proven to help protect against privacy violations and information leakage. However, it introduces new risk vectors which make machine learning models more difficult to defend against adversarial samples. In this study, we examine the role of differential privacy and self-normalization in mitigating the risk of adversarial samples specifically in a federated learning environment. We introduce DiPSeN, a Differentially Private Self-normalizing Neural Network which combines elements of differential privacy noise with self-normalizing techniques. Our empirical results on three publicly available datasets show that DiPSeN successfully improves the adversarial robustness of a deep learning classifier in a federated learning environment based on several evaluation metrics.
Translation of Quantum Circuits into Quantum Turing Machines for Deutsch and Deutsch-Jozsa Problems

We want in this article to show the usefulness of Quantum Turing Machine (QTM) in a high-level didactic context as well as in theoretical studies.We use QTM to show its equivalence with quantum circuit model for Deutsch and Deutsch-Jozsa algorithms.Further we introduce a strategy of translation from Quantum Circuit to Quantum Turing models by these examples.Moreover we illustrate some features of Quantum Computing such as superposition from a QTM point of view and starting with few simple examples very known in Quantum Circuit form.
Psychological Evaluation for Images/Videos Displayed Using Large LED Display and Projector

Display of images/videos on a big screen/display, such as digital signage, projection mapping, etc., is becoming popular in the area of entertainment, advertisement, and so on. A comparison of the usage of an LED display and a projector is important for such applications. We have prepared an experimental environment where two types of projection/display using a 200 inch LED display and a 200-inch screen and a projector. Also, two brightness conditions, light-on and light-off, and two types of contents, art content and text content were used for the experiment. Under a total of eight types of environments, we carried out a psychological experiment using 24 participants. Each subject filled a questionnaire based on a five-point semantic differential scale. Based on the analysis of the result, it was revealed that the combination of art content, light-off, and LED display gives far better results than other combinations.
Problems of Appointment and Production of Forensic Computer-Technical Expertise

Due to the specifics of crimes committed on the Internet and the need to involve competent persons with special knowledge in the field of information and computing technologies and information and computer technology in criminal proceedings, the appointment of computer and technical expertise is relevant in the investigation of most online crimes. Electronic (digital) information that is the subject of criminal encroachment or a means of committing a socially dangerous act on the Internet can be correctly collected, examined and examined only by specialists or with their assistance. In scientific research on computer-technical expertise, the definition of its concept is not formulated, the distinctive features of this type of expertise are analyzed exclusively through the description of specific objects of such expertise. The article proves that the name "computer-technical expertise" is the most optimal term that semantically combines the study of both the device itself, that is, hardware, and its components, as well as system software, information data that includes various types of text and graphic documents. The problems of performing forensic computer-technical examinations are based on objective and subjective reasons. Problems that do not depend on the expert's professional competence (objective) appear even before the start of production of the type of expertise under consideration. For example, failure to comply with the requirements of the criminal procedure form when collecting electronic documents or computer equipment during investigative actions prevents the expert from preparing a reliable, respectively, and acceptable conclusion. It is also important to take into account the continuous improvement of software and hardware used in criminal activities, which inevitably causes the need to modify and optimize the methods of conducting examinations. The article defines the concept, principles of forensic computer-technical expertise, its types, objects of research and opportunities in the investigation and detection of crimes. Almost any handling of computer information requires the use of special knowledge. Therefore, the authors emphasize the possibilities of forensic computer- technical expertise in solving diagnostic and identification problems, analyze the problems of assigning and producing computer-technical expertise.
Remote Sensing Applications in Mapping Salt Affected Soils

The aim of this review paper is to provide a comprehensive overview of remote sensing-based mapping of salt affected soils. By providing multispectral and multi-temporal low cost data at various resolutions, remote sensing plays an important role for identifying and mapping the distribution of salt affected soils. Different bands of the multispectral data and the indices and transforms derived from them have been found useful in delineating salt affected soils. The various approaches to map salt affected soils involving remote sensing data, from visual interpretation to supervised and unsupervised classifications have been discussed. Quantitative mapping of soil salinity with remote sensing and other environmental variables have also been discussed.
Digital music art through the prism of interdisciplinarity

&amp;nbsp; The processes taking place in modern science tend to integrate various scientific disciplines in studying any scientific phenomenon. This explains the search of methodology based on the techniques of different sciences involved in formation of the subject of research, which in this article is represented by the digital music art. Interpreted as a branch of music art with digital specificity, digital music art incorporates electronic music presented by specific, algorithmic, and electronic music. A signature characteristic of digital music art consists in its interdisciplinarity, which suggests the combined effect of separate parts of the system and leads to self-organization, which corresponds with the scientific tasks of synergetics. This substantiates the relevance for elaboration of interdisciplinary methodology for studying digital music art in the context of research mechanisms developed within synergetics. The scientific lies in the analysis of digital art through the prism of the qualities inherent to synergetics. The disciplines united by digital art (mathematics, set theory, probability theory, information theory, combinatorics, game theory, cybernetics, computer science, acoustics, sociology, communication, and biology) are interdisciplinary, which means that in ensemble with other disciplines they form a complex interdisciplinary knowledge of structure of digital music art. At the same time, the disciplines that comprise scientific framework of digital music art are attributed to different sciences: humanities, natural sciences, mathematics, social sciences, and technical sciences. In this context, the research of digital music art is simultaneously of interdisciplinary and multiscientific nature. The author established a peculiar impact of interdisciplinarity upon digital art, which generates the qualities inherent to synergetics &amp;ndash; nonlinearity, disequilibrium, openness, chaotic nature, entropy, indeterminacy, and dissipation. &amp;nbsp;
Bayesian Non-Parametric Factor Analysis for Longitudinal Spatial Surfaces

We introduce a Bayesian non-parametric spatial factor analysis model with spatial dependency induced through a prior on factor loadings.For each column of the loadings matrix, spatial dependency is encoded using a probit stickbreaking process (PSBP) and a multiplicative gamma process shrinkage prior is used across columns to adaptively determine the number of latent factors.By encoding spatial information into the loadings matrix, meaningful factors are learned that respect the observed neighborhood dependencies, making them useful for assessing rates over space.Furthermore, the spatial PSBP prior can be used for clustering temporal trends, allowing users to identify regions within the spatial domain with similar temporal trajectories, an important task in many applied settings.In the manuscript, we illustrate the model's performance in simulated data, but also in two real-world examples: longitudinal monitoring of glaucoma and malaria surveillance across the Peruvian Amazon.The R package spBFA, available on CRAN, implements the method.
An improved method for Rotation Estimation Using Photometric Spherical Moments

Using spherical moments to estimate the rotation of camera is an effective method. However, after the camera rotates, the scene in the captured image will change, which will cause a certain error. This paper proposes a method to reduce this error by removing the non-common part between the two images during rotation. Through multiple iterations, the error caused by scene changing will become very small. The experimental results using manual generated image are provided to show the efficiency of this proposed method.
Construction Strategy of Smart English Teaching Platform from the Perspective of “Internet + Education”

The advent of the “Internet + Education” era has brought smart education into a higher stage of development. Teachers’ intelligent learning is not only a technological change, but more importantly, integrating network thinking into the teacher’s learning. The concept of intelligent teaching allows students to learn more scientifically. English education is an important part of school education, which lays a good foundation for improving the overall quality of students. With the development of Internet technology, it provides a new platform for school English teaching. It provides favorable conditions for teacher-student interaction and improves the educational effect of school English and student learning. The purpose of this article is to study the construction strategy of smart English education platform from the perspective of “Internet + Education”. In terms of methods, this paper proposes the coexistence of multiple learning modes to improve the original learning mode, build a personalized, experiential teaching ecosystem, and realize two-way interaction between online and offline to better improve learning efficiency. And establish a teacher-student interaction communication platform, teachers can adjust their own teaching progress, content, methods, etc. based on the feedback of students in the discussion group. Install assisted composition correction software to reduce the burden on teachers, thereby spending more time and energy to educate students. In terms of experiments, through the establishment of experimental classes and control classes, teaching is carried out separately, and the examinations are conducted before and after teaching. Send a questionnaire at the end of the period to see its satisfaction. It is found that the teaching platform of Internet + Education proposed in this paper is superior to traditional teaching in terms of learning effect and students’ satisfaction with learning.
Modeling the Kinematics of Two Robots with Denavit–Hartenberg Notation

Abstract This article presents a description and methodology for building a kinematics model for the formation of two-wheeled mobile robots transporting a beam using Denavit–Hartenberg notation. The simple and inverse kinematics tasks of this formation were solved. Solutions of kinematics tasks are presented in junction coordinates and global coordinates. The obtained results were simulated using the Matlab–Simulink package together with animation of the solution using a programmed emulator of robot work.
Knowledge Sharing, Organizational Capabilities, and Innovation Management to Sustain Competitive Advantage: A Qualitative Multi-Case Study

The importance of new product development (NPD) and innovative capabilities in marketing, innovation, and business strategy has been recognized by management and researchers. Knowledge management and organizational capabilities are also explored and evaluated by researchers and practitioners. However, the current literature shows a lack of connection between NPD, innovative capabilities, integrated shared knowledge, and organizational capabilities. Also, there is limited knowledge on the impact and the contribution of the integrated shared knowledge and the organizational capabilities to the firm's success, performance, and sustainability. This study aims to determine if there is a link between NPD and innovative capabilities and the integrated shared knowledge and the organization's capability and explore how shared knowledge and the organization's capabilities influence and contribute to NPD, innovative capabilities, and innovative management. A qualitative, multi-site case study through one-on-one, in-depth interviews with primary decision-makers from technology and innovative companies in Jordan is employed. The primary research question is, how do shared knowledge and the organizational capabilities that influence NPD and innovative capability contribute to the firm's success, performance, and sustainability? Respondent interviews are imported and analyzed through NVivo qualitative data analytics software. Findings are also determined using NVivo 11 through theme analysis. A key finding is that shared knowledge and the organization's capabilities are linked and critical for NPD's success and innovative capabilities.
Identification of Bots in Social Networks based on Data Mining Technologies

This article solves the problem of intelligent models constructing and their accuracy evaluating for identifying bots in social networks.The relevance of solving this problem is noted.The construction and accuracy assessment of the neural network model, decision tree and linear regression are performed.The initial data source was Twitter social network.To collect the initial data, we used our own database, consisted of 3428 users, about half of which contained characteristic features of bots.The initial data were randomly divided into the training and testing sets, each of them included approximately 50% of the records.15 attributes were used as the model's input parameters, in particular, the number of symbols in the username, the user's number of tweets, the number of readers, etc.The models construction and study was carried out on the Deductor analytical platform base.Each model was tested on data set consisted of 1719 records.For all models, the corresponding classification matrices were constructed and the first, second kind errors and the general model's error were calculated.In terms of minimizing these errors, the neural network model showed the best results, and the linear regression model showed the worst.This allowed us to conclude, that in order to minimize classification errors, it is advisable to use a neural network model.This indicates its effectiveness and the possibility of practical use in intelligent decision-making support systems for bots identifying in social networks.