Reviewerly/exHarmony huggingface dataset:
Mathematical Analysis. Basis: Nomotex E-course

The paper describes the peculiarities of the development of the digital course “Mathematical Analysis. 1st semester” in the digital learning system Nomotex (DLS “NOMOTEX”) [1], developed at the Department of Computational Mathematics and Mathematical Physics, Bauman Moscow State Technical University. The features of innovative teaching methods using this course are also presented.
The video guides and social tagging with the methodology of video annotation

Teaching guides are mandatory for quality agencies to evaluate teaching programmes, just as institutions require teachers to comply with them. This teaching resource has been seen as a very effective tool for the information and orientation of students in university programmes. However, the reality may turn out to be different, as the current practices with these guides are often not the desirable ones, as they are not used, read and studied by students with the level of depth that teachers wish, and in some cases they may be a mere formality for students, thus losing all their potential and meaning. The communication we present aims to present the results of a teaching innovation project to break this problem by producing video guides as digital resources that are more motivating for students. In addition, to design and experiment with a new methodology for its application and analysis of these resources in teaching programmes of any kind (face-to-face, blended and online programmes) by means of multimedia annotation. In this work we present the objectives, methodologies and resources proposed in this project, as the main conclusions we have reached as it has been to check a greater participation in the understanding of the programmes by the students, as a more active and motivating methodology to work with these resources in the classroom for an online modality.
Content and methodological bases for studying global problems of humanity in the framework of the subject «Geography» based on the potential of extracurricular and extracurricular activities

Modern geographical education is undergoing a stage of updating its content. In the context of globalisation and constantly emerging problems and contradictions that have a universal character of manifestation, the key theme of school geographical education at the high school level can include global problems of humanity, the study of which will not only form a set of educational results, fixed by normative documents, but also help pupils to form a global type of thinking and behaviour, ensure the formation of a value attitude to the surrounding reality and understanding the significance of their own activities, aimed at ensuring the sustainability and balance of the development of all mankind. This article defines the content bases for studying global problems of humanity in six contexts that have a personal aspect for pupils. The article presents a methodological system for studying global problems of humanity in the process of both regular and extracurricular activities and represents a set of target (goal ideal and goal-means, correlated with the components of learning: cognitive, praxiological and axiological), content (contexts of studying global problems and levels of their consideration), procedural (forms, techniques, methods and technologies of learning that ensure the complex nature of the study of global problems of our time), performance-evaluation criteria, indicators and levels of mastering content about global problems of humanity) blocks.
Real Time Monitoring of Salinity Gradient and Solar Pond Temperatures

Electric energy is an important factor for human needs, functions as lighting, and various human activities. The large amount of electrical energy needs demands to create various alternative electrical energy. Alternative energy uses renewable energy sources to avoid crisis and energy scarcity. The National Energy Policy (KEN) has encouraged the government and the private sector and the public to use energy effectively and efficiently, and to utilize renewable energy. The direction of national energy policy includes reducing dependence on fossil fuels, specifically petroleum. Utilization of renewable energy is needed for the sustainability of national energy supply and reserves. Indonesia is called a maritime country, because 2/3 of Indonesia’s territory is the sea with the longest coastline in the world, which is ± 80,791. 42 Km and is also called an archipelagic country because it has thousands of islands. This natural situation is a great potential for the development of renewable energy, especially the energy sourced from the sea spread wide and very abundant, namely solar pond. One of the alternative sources of renewable energy sourced from the sea currently not developed in Indonesia is solar ponds, even though Indonesia has a huge geographical potential to develop this technology. There are at least two potential parameters for building a solar pond, first because Indonesia has a tropical climate with a large enough intensity of sun, second because Indonesia is a maritime country surrounded by sea, so the availability of raw water is very abundant. Solar pond is not a new power generation technology. In the history of electricity generation technology in Indonesia, this technology has never been tested and implemented at all. In this study, it has a long-term goal of generating electricity from solar ponds. Solar pond technology is a type of environmentally friendly power plant, based on seawater using sunlight to get the difference in heat in the solar pool so that the thermal layer can be converted into electrical energy. The specific targets, namely data salinity and temperature data on the prototype solar pond have been realized in the form of cylindrical with a height of 1. 05m and a diameter of 0. 8 meters. Solar pool research, in line with the goal of national transformation as a significant contributor to the benefit of the Indonesian Maritime Continent. In line with the development of electricity generation technology, solar pond technology has never been implemented in Indonesia, so this research is in accordance with the 2016-2020 National Strategic Plan number 51868 / UN4. 1 / PR. 04 / 2016.
Sequent Calculi for Modal Logics

In this chapter we focus on standard and generalised sequent calculi for some modal logics. In general, the application of SC apparatus to non-classical logics showed several limitations of the Gentzen’s approach. In sections 4.2 - 4.4 we describe extensions of LK and G3 to modal logics. In particular, we provide proofs of cut elimination/admissibility for logics T and S4, and discuss the problem of proof search and decidability for these logic. The remaining sections are devoted to problems with obtaining a cut-free formalization of S5. On this occassion we introduce several nonstandard and generalised forms of SC. In section 4.5 we survey some proposals based either on possible translation into other cut-free logics, or restrictions put on cut, or introducing additional nonstandard rules. As a different way of overcoming this problem we will present some generalised SC for S5 in the remaining sections. First we present practically the simplest one based on the application of labelled formulae. Then we focus on the family of solutions introduced in the framework of hypersequent calculus. Eventually we describe a simplified solution based on the application of bisequents which are numerically restricted hypersequents.
Improving The Training Of Teachers In The Digital Transformation Of Education

The article explores the core techniques of improving the professional training of teachers of the future in the digital transformation of education. The aim of the article is to identify activities that are intended to ensure the quality training of teachers of the future in the digital transformation of education. It is proposed to develop the human resource potential of future teachers who are ready to carry out pedagogical activities in a digital environment. The steps are taken to create the conditions for the vocational training of the teacher of the future in terms of the development of new educational programs and the inclusion in existing educational programs of new subjects related to the formation of the digital competences of the teacher, Modernizing the content of educational subjects, introducing new models of teaching, and integrating mass open online courses (MOOC) into educational programs. Special attention is paid to the digital transformation of the university, the digital transformation of the teacher, the peculiarities of the students of the new generation - generation «Z», the need to introduce the discipline «Digital didactics» into the content of educational programs, Institutionalization of the mentoring system as an important resource for the development of the professionalism of educators, the development of new basic and complementary educational programs aimed at preparing teachers of the future and filling professional deficits. Skills have been identified within the framework of the digital competence of the teacher, which are proposed to be developed during the implementation of new educational programs.
Camera Re-localization by Training Multi-dataset Simultaneously via Convolutional Neural Network

With the advances of Convolutional Neural Networks (CNN) in computer vision, rapid progresses have been taken in camera re-localization. In this paper we propose a new network, a multi-dataset simultaneously training network (MdNet) to relocate camera pose from an RGB image. Moreover, we propose to construct new loss functions to learn camera pose, image segmentation and images depth maps from the multi-datasets. Compared with PoseNet Geometric Loss in street dataset, position and orientation accuracy are increased by 52% and 35% respectively. Experiment shows that our method outperforms other prior similar works in large-scale scenarios and is more robust under different season or time conditions.
Research on Behavior of Blocking Internet Advertising Regulated by Economic Law

With the advent of big data and Internet era, the scale of network economy is getting larger and larger. Blocking online advertisements is practical for users, but it also does harm to certain interests of advertisers. The antagonistic relationship has led to the debate on the regulations of Economic Law concerning blocking the internet advertisements between relevant circles of theory and practice.
Breast cancer diagnosis method based on multitask learning and BI-RADS assessments

Breast cancer is the most common cancer in women, and ultrasound diagnosis is one of the most common diagnostic methods. This paper used the deep transfer learning network to classify breast ultrasound images as benign and malignant. To improve diagnosis performance, we designed a multitask deep learning classification network for breast tumours and integrated the BI-RADS label information of breast ultrasound images during the training process. In BI-RADS classification accuracy, the multitask deep learning network reached the AUC value of 0.836, superior to the single-task network of 0.826. In terms of benign and malignant tumours, the classification accuracy reached 90.7%, which was 2.9% higher than that of a single-task network. In the combined diagnosis, the model prediction results combined with the BI-RADS category reviewed by the Reader achieved a classification accuracy of 93.4%, which was improved by 2.7% compared with the multitask model the AUC value reached 0.982, achieving an excellent diagnostic effect. Our results show that the multitask deep learning network combined with the BI-RADS assessments can improve the training accuracy. The strategy of deep learning model combined with Reader's assessment of BI-RADS labels can significantly improve the diagnostic accuracy.
Adaptive Context Learning Network for Crowd Counting

The task of crowd counting is to estimate the accurate number of people in photos taken from unconstrained surveillance scenes. It is in general a challenging problem due to the input scale variations and perspective distortions. Previous methods make efforts to enhance the representation ability by using multi-scale features of the scene pictures. However, most of these methods directly add or fuse the features, in which the influences of different feature sizes are equally considered. In this paper, we propose a novel architecture called adaptive context learning network (ACLNet) to incorporate context of features in multiple levels. In this architecture, the original image features are enhanced by a multi-level feature generating module, and then the multi-level features are up-sampled to the same size and re-weighted for fusing. The ACLNet incorporates the context information existed in sub-regions of various scales adaptively, thus it is able to enhance the representative ability of multi-level features. We perform several experiments on public ShanghaiTech (A and B), UCF_CC_50 and NWPU-crowd datasets. Our proposed ACLNet achieves the state-of-the-art results compared with existing methods.
Accuracy Analysis Transliteration Balinese Script-to-Latin Text Using Hexadecimal Labeling Method

Balinese script is a collection of symbols used to communicate via text messages used by Balinese. Since the 804s or 9th century until now, the use of the Balinese script has been intensified by the Bali Provincial Government. The government has made various innovations to using the Balinese script in daily activities. Currently, technology has started to be applied in the Balinese script learning process, especially in the transliteration Latin characters into Balinese characters. This makes it easier to learn the Balinese script for all circles. However, behind the rapid development of Latin transliteration application technology to Balinese script, the reverse transliteration process from Balinese script to Latin script has become an interesting topic to be researched. In this study, the optimized string replacement method with the hexadecimal number format was used to improve the string replacement algorithm to translate Balinese script sentences into understandable Latin sentences. The optimization of this method resultedin an accuracy of 95.1 % from 464 test data.
Web Saturation with Libraries of Machin Learning Modules

The paper presents the result of Web resources cursory review (45 sources, through to December 2019) containing software libraries that implement models and algorithms of artificial intelligence (Machine Learning - ML). The purpose of the review is to provide a set of developments in the field of ML for students and developers of digital technologies in all fields of activities compactly. The ML Libraries (MLL) have been classifying by languages implementation and by basic methods specificity. The table “MLL-Features” has been compiling. The features characterize a set of methods, a technique and a task orientation of each library. In total, there are more than 40 such libraries for developing server-side and client-side of knowledge-based Information Systems (KBIS), deep Artificial Neuron Network (ANN), and Natural Language Processing. Most of them are new but are ready for use by developers. As the review one result, it became clear that ML libraries are quite accessible to students and even high school students. The advantage of Web languages is that they are useful both for understanding ready projects and for direct use: only a web browser and development environment are required to run an ML project in JavaScript. The review is useful for undergraduates, graduates, postgraduates and novice developers of artificial intelligence systems and KBIS.
Experience in Engineers Training on Multiple Integrals in the Nomotex DLS

The paper discusses a new approach to teaching the discipline “Multiple and curvilinear integrals, series” for engineers, using a new digital information and educational environment “NOMOTEX”, developed at the Department of Computational Mathematics and Mathematical Physics, Bauman Moscow State Technical University. A new methodology for conducting lectures and practical classes for the Multiple Integrals course using Nomotex DLS is presented. The article analysed to the experience of training engineers at the Bauman Moscow State Technical University course on Multiple Integrals, including the advantages of learning using interactive computer visualization of mathematical concepts.
D-colSimulation: A Distributed Approach for Frequent Graph Pattern Mining based on colSimulation in a Single Large Graph

Frequent pattern mining in graph data is a hot topic in recent years. At present, most frequent graph pattern mining methods use the concept of subgraph isomorphism for the matching of candidate graph pattern in data graph. However, in some applications where the accuracy of matching is not so strict, the topology constraints of subgraph isomorphism may lose some meaningful frequent patterns. Simulation matching plays an important role in graph pattern matching. However, in frequent graph pattern mining, it may lead to the matching between the connected candidate pattern and the disconnected substructure in the data graph. The topology of matching results can not be guaranteed, which greatly affects the quality of mining, and may lead to mining a large number of redundant graphics patterns with repeated structure. Therefore, this paper proposes a new concept of simulation matching - colSimulation, which can ensure the point-to-point matching between pattern graph and data graph, effectively avoid redundant mining results and improve the mining speed. The D-colSimulation proposed in this paper is a distributed frequent graph pattern mining method based on colSimulation for large-scale graph data. Experiments on datasets show that our method not only improves the mining efficiency, but also performs well on data sets with poor performance of subgraph isomorphism.
Development of an Ambisonic Guitar System

The term sound spatialisation indicates a group of techniques for organising and manipulating the spatial projection and movement of sound in a physical or virtual listening environment. An Ambisonic Guitar System has been devised and realised, with the project name GASP: 'Guitars with Ambisonic Spatial Performance'. GASP is an ongoing University of Derby research project, where our interest in Ambisonic algorithmic research and guitar sound production is combined with off-the-shelf hardware and bespoke software to create an Ambisonic based immersive guitar sound system. It is an innovative audio project, fusing the musical with the technical, combining individual string timbralisation with Ambisonic immersive sound. The GASP guitars have multichannel pickups (aka hex, hexaphonic or divided pickups) installed. The arpeggiation effect can be blended with the output from the other mono guitar pickups such that a sustained strummed chord can be output from the mono pickup output, whilst the MIDI sequence picks out and enhances the selected programmed rhythmic notes.
Abstracted Visualization of Halo Topologies in Dark Matter Simulations

This work focuses on particle-based ΛCDM (cold dark matter) simulations. The features of interest are clusters of dark matter particles, called halos. Halos are governed by the laws of motion and gravitation, and they may, consequently, merge over time. In this paper, we present visualization methods for the topology of the resulting tree-like accumulation history of the halos, as well as for the underlying halo data. We combine direct visualization methods of merger trees, in which trajectories over time are depicted in 3D space, with novel visual topological abstracts that are obtained by mapping time to one spatial axis while projecting halo positions on the remaining two axes. The user can explore and analyze both halos and merger trees through our unified visualization interface, which uses linked views complementing each other. All of our methods pay special attention to the periodic boundary conditions that are typically used during the underlying physical simulation.
Acquiring New Definitions of Entities

We focus on understanding natural language (NL) definitions of new entities via the ones available in the current version of an ontology. Once a definition is acquired from a user or from documents, this and other users can rely on the newly defined entity to formulate new questions. We first explore how to automatically build a taxonomy from a corpus of documents or from the web, and use this taxonomy to filter out irrelevant answers. We then develop a logical form approach to building definitions from text and outline an algorithm to build a step-by-step definition representation that is consistent with the current ontology. A nonmonotonic reasoning-based method is also proposed to correct semantic representations of a query. In addition, we focus on a special case of definitions such as NL descriptions of algorithm for the NL programming paradigm. Finally, search relevance improvement is evaluated based on acquired taxonomy and ontology.
A Digital Watermark Introduction in Image with Partial Turning Resistance

The proposed algorithm is used to obtain partial turning resistance. The traditional method of implementation of the watermark is described. The proposed method for the implementation of the watermark is described. In the proposed method, the Arnold transform is excluded and the coefficients at which the watermark are applied are changed. The Arnold transform and the coefficients in the traditional method are non-invariant. The results of the comparison of the traditional and the proposed methods for the introduction of watermark are presented. The cross-correlation coefficient (between two square matrices) was calculated. The proposed method has characteristics in terms of resistance to turns and reflections higher than the traditional one.
Controlled AutoEncoders to Generate Faces from Voices

Multiple studies in the past have shown that there is a strong correlation between human vocal characteristics and facial features. However, existing approaches generate faces simply from voice, without exploring the set of features that contribute to these observed correlations. A computational methodology to explore this can be devised by rephrasing the question to: “how much would a target face have to change in order to be perceived as the originator of a source voice?” With this in perspective, we propose a framework to morph a target face in response to a given voice in a way that facial features are implicitly guided by learned voice-face correlation in this paper. Our framework includes a guided autoencoder that converts one face to another, controlled by a unique model-conditioning component called a gating controller which modifies the reconstructed face based on input voice recordings. We evaluate the framework on VoxCelab and VGGFace datasets through human subjects and face retrieval. Various experiments demonstrate the effectiveness of our proposed model.
Using computer data processing in schoolchildren’s cross-cultural collaborative research

This Research to Practice Full Paper aims to illustrate how the introducing of basic computerbased data processing instruments to gifted senior school students may engage them in cross-cultural humanitarian research practice intensively. The authors of the article suggest using a cross-cultural approach to humanitarian research to develop the research competence and computer skills of adolescents. The article contains a detailed description of the case on the use of computer technology for the development of students' research efficiency. Analysis of the project results allows the authors to identify specific deficiencies in the existent Russian school IT-practice and propose a multi-purpose method for their compensation.