Reviewerly/exHarmony huggingface dataset:
Digital intelligence of a modern economist: an exploratory case study

In the current context of digitalization of various spheres of life, an important characteristic of participants in a digital society is the level of their digital intelligence. The level at which future economists develop their digital intelligence skills during university depends on their successful employment and career development. The presented article analyses the concept of digital intelligence of an economist on the basis of the Digital Quotient framework developed by the Digital Intelligence Institute, characterizing the levels of “Digital Citizen”, “Digital Creator”, “Digital Entrepreneur” for such components of digital intelligence as: Digital Changemaker Identity, Digital Use, Safety Digital, Digital Security, Digital Emotional Intelligence, Digital Communication, Digital Literacy, Digital Rights. For the first time, the contents of an academic discipline of a university training programme for future economists have been proposed, in the course of which digital intelligence skills can be developed. The authors demonstrate the stages of formation, indicators for different levels of formation, content and examples of educational representation of material. They offer the stages of Digital intelligence development in the framework of studying the course modules, the implementation of project work and the solution of the real case studies during academic training. The results of the pilot study for achieving all three levels of digital intelligence. A statistical analysis of the results of the experiment was carried out and their relevance proved.
Digital directions: Curricular goals relating to digital literacy and digital competences in the Gymnasium (stx) in Denmark.

Digital literacy and digital competences are increasingly being formulated as important educational goals.In that regard, the precision, clarity and topicality of curricular guidelines relating to these concepts become vital, and this calls for research that investigates how digital literacy and digital competences are represented in curricular documents.This study makes a contribution to knowledge in this field by investigating the general curriculum for the Gymnasium in Denmark, with a specific focus on differences between the subjects.The article provides a qualitative analysis of 150 paragraphs containing between 4 and 175 words.The findings suggest that aspects relating to digital literacy and digital competences are broadly covered, but also that the different curricula formulate and organize these in very different ways.The article furthermore identifies a clear division of labour between the subjects, where the subjects within the educational field of Natural Science and Technology especially focus on ICT as a neutral learning tool and on ICT-operational competences.The challenges relating to these findings are discussed.
Designing locally maximally entangled quantum states with arbitrary local symmetries

One of the key ingredients of many LOCC protocols in quantum information is a multiparticle (locally) maximally entangled quantum state, aka a critical state, that possesses local symmetries. We show how to design critical states with arbitrarily large local unitary symmetry. We explain that such states can be realised in a quantum system of distinguishable traps with bosons or fermions occupying a finite number of modes. Then, local symmetries of the designed quantum state are equal to the unitary group of local mode operations acting diagonally on all traps. Therefore, such a group of symmetries is naturally protected against errors that occur in a physical realisation of mode operators. We also link our results with the existence of so-called strictly semistable states with particular asymptotic diagonal symmetries. Our main technical result states that the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>N</mml:mi></mml:math>th tensor power of any irreducible representation of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow class="MJX-TeXAtom-ORD"><mml:mi mathvariant="normal">S</mml:mi><mml:mi mathvariant="normal">U</mml:mi></mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mi>N</mml:mi><mml:mo stretchy="false">)</mml:mo></mml:math> contains a copy of the trivial representation. This is established via a direct combinatorial analysis of Littlewood-Richardson rules utilising certain combinatorial objects which we call telescopes.
La gestión ágil de proyectos de software en la formación Académica Universitaria: Una revisión sistemática de la literatura

Agile project management is an iterative approach that allows you to plan and guide project processes that require special speed and flexibility to achieve project success. It is for this reason that today professionals must master the basic concepts of this work as disciplinary or professionalizing competence. The objective of the study lies mainly in compiling recent research, including the last three years, in relation to Agile Software Project Management, its current situation and its application in practice. The study shows the implementation of the methodology proposed by Kitchenham for the systematic literature review (RSL) analyzing 40 scientific publications, concluding that the agile management of software projects allows efficient and effective management with the application of a standard o priority methodology and with the unavoidable use of software tools of specific use for it.
Ontology Modelling and Standardized Information Exchange with Content Delivery Applications in Technical Communication

Ontologies are a technology recently used in technical communication (TC) to model information into a multidimensional net. They expand the modelling by taxonomy of metadata in TC. Any kind of relation between multiple classes and instances can be established. These ontologies can appear in the form of semantic correlation rules (SCR), which represent the connection between the metadata of the objects. SCR are used in connection with component content management systems (CCMS), semantic modelling systems (SMS) and content delivery portals (CDP) to deliver the appropriate amount of content in a more precise manner to the end user. In general, Ontology tools, CCMS and CDP are not based on the same ecosystem and therefore, they do not always work together effortlessly. A solution to this problem are exchange formats like the intelligent information Request and Delivery Standard (iiRDS), which enable a standardized information exchange between supported systems. Another solution would be compound information systems (CIS) like ONTOLIS, which combine a CCMS, CDP and SMS all in one. This paper aims to investigate the effect of SCR in the CDP of a CIS like ONTOLIS and to evaluate the use of exchange formats like iiRDS.
Covert Anti-Jamming Communication Based on Gaussian Coded Modulation

In several wireless communication systems, robustness against jammers and covertness against eavesdroppers are required simultaneously. In this paper, we propose a novel covert anti-jamming communication system. The properties of both anti-jamming and covertness are achieved through the Gaussian-coded time-frequency modulation scheme. We propose two receiver algorithms based on the sparse signal recovery framework. The receiver algorithms estimate and remove the jamming signal from the received signal. In addition, it is difficult to distinguish the proposed signal from the actual Gaussian noise in both the time and frequency domains. We compare the covertness of the proposed communication system with that of a conventional digital modulation system in terms of the probability of detection. We numerically evaluated the bit error rate of the proposed system to demonstrate its anti-jamming performance.
A Semi-Automatic Semantic Consistency-Checking Method for Learning Ontology from Relational Database

To tackle the issues of semantic collision and inconsistencies between ontologies and the original data model while learning ontology from relational database (RDB), a semi-automatic semantic consistency checking method based on graph intermediate representation and model checking is presented. Initially, the W-Graph, as an intermediate model between databases and ontologies, was utilized to formalize the semantic correspondences between databases and ontologies, which were then transformed into the Kripke structure and eventually encoded with the SMV program. Meanwhile, description logics (DLs) were employed to formalize the semantic specifications of the learned ontologies, since the OWL DL showed good semantic compatibility and the DLs presented an excellent expressivity. Thereafter, the specifications were converted into a computer tree logic (CTL) formula to improve machine readability. Furthermore, the task of checking semantic consistency could be converted into a global model checking problem that could be solved automatically by the symbolic model checker. Moreover, an example is given to demonstrate the specific process of formalizing and checking the semantic consistency between learned ontologies and RDB, and a verification experiment was conducted to verify the feasibility of the presented method. The results showed that the presented method could correctly check and identify the different kinds of inconsistencies between learned ontologies and its original data model.
Open Relation Extraction in Patent Claims with a Hybrid Network

Research on relation extraction from patent documents, a high-priority topic of natural language process in recent years, is of great significance to a series of patent downstream applications, such as patent content mining, patent retrieval, and patent knowledge base constructions. Due to lengthy sentences, crossdomain technical terms, and complex structure of patent claims, it is extremely difficult to extract open triples with traditional methods of Natural Language Processing (NLP) parsers. In this paper, we propose an Open Relation Extraction (ORE) approach with transforming relation extraction problem into sequence labeling problem in patent claims, which extract none predefined relationship triples from patent claims with a hybrid neural network architecture based on multihead attention mechanism. The hybrid neural network framework combined with Bi-LSTM and CNN is proposed to extract argument phrase features and relation phrase features simultaneously. The Bi-LSTM network gains long distance dependency features, and the CNN obtains local content feature; then, multihead attention mechanism is applied to get potential dependency relationship for time series of RNN model; the result of neural network proposed above applied to our constructed open patent relation dataset shows that our method outperforms both traditional classification algorithms of machine learning and the-state-of-art neural network classification models in the measures of Precision, Recall, and F1.
DEVELOPMENT AND IMPROVING STUDENTS' EXPERIMENTAL SKILLS THROUGH STEM ACTIVITIES

There are some trends currently being monitored in the country: interest in science studies and related professions is decreasing; unsatisfactory results of international student achievement research (PISA, TIMSS). In order to make students more interested in natural sciences and to motivate them to relate their life to STEAM activities, it is appropriate to encourage students to engage in independent research and to discover the joy of discovery. One of the ways to solve this problem is the students' practical experimental activity in the laboratories of University. In this way, students not only get to know the laws of science, new technologies, but also carry out experiments, research and projects. The research analyses the usage of STEAM program “Cognition of Energy and Thermal Processes” for students of ninth (1st Gymnasium) grades in order to deepen and broaden the knowledge of natural science education, develop practical abilities of students and their scientific researcher's competence. Students are advised to do five experimental works in this field. The program engages a basic educational method – inquiry-based learning. The results of the pedagogical experiment and the questionnaire survey are discussed. It can be stated that educational experimental activities are necessary and useful for students. By using these experimental activities, students can be provided with educational material in an attractive form, which stimulates the interest in the subject. Program participants have deepened and expanded their knowledge of energy and thermal processes in nature. Students improved their competence in natural science research. They learned how to plan and perform experiments, acquired the ability to formulate hypotheses, to make assumptions, to analyse and explain results, and to formulate reasoned conclusions. Students acquired practical skills to work properly and safely with devices and tools (computer systems Nova 5000 and Xplorer GLX, temperature, humidity sensors, caliper, scales, etc.) Students liked to be young researchers; they felt the joy of discovery by practically experimenting and independently exploring natural phenomena. Keywords: experimental skills, science learning system, inquiry-based learning, STEAM education.
The impact of the development of information technology tools of communication on digital culture and Internet slang

A digital culture is such a vast and complex concept that is often difficult to define. However, using just a definition does not answer the question: what are digital culture and Internet slang? To gain a deeper understanding of а digital culture, you need to understand what makes a digital culture as it is. It is becoming increasingly clear that this area can be successfully explored only through the joint efforts of humanitarian, social, cultural and technical scientists, and therefore the integration and structuring of existing disciplinary approaches and results are necessary. Our research does not consider digital culture in terms of professional subculture, understanding of modern information technologies, their functioning, and professional language. In our research, the digital culture is considered in the range of the Internet user’s personality. The topicality of the research is that digital culture and Internet slang are «interdisciplinary categories, with the help of which it is possible to analyze problems of cultural identity», mutual influence of culture and slang in the system of unified computer networks.
Reachable sets of classifiers and regression models: (non-)robustness analysis and robust training

Abstract Neural networks achieve outstanding accuracy in classification and regression tasks. However, understanding their behavior still remains an open challenge that requires questions to be addressed on the robustness, explainability and reliability of predictions. We answer these questions by computing reachable sets of neural networks, i.e. sets of outputs resulting from continuous sets of inputs. We provide two efficient approaches that lead to over- and under-approximations of the reachable set. This principle is highly versatile, as we show. First, we use it to analyze and enhance the robustness properties of both classifiers and regression models. This is in contrast to existing works, which are mainly focused on classification. Specifically, we verify (non-)robustness, propose a robust training procedure, and show that our approach outperforms adversarial attacks as well as state-of-the-art methods of verifying classifiers for non-norm bound perturbations. Second, we provide techniques to distinguish between reliable and non-reliable predictions for unlabeled inputs, to quantify the influence of each feature on a prediction, and compute a feature ranking.
Training future primary school teachers for the formation of students' skills to cooperate in a team

The model of training future primary school teachers for the formation of students' skills to cooperate in a team is developed and experimentally tested in the article. There are the following components of this model: goals, methodological approaches, content (the structure of the ability to work in a team is considered), the main stages, forms, methods, means, diagnostic tools and the result of the studied training. The skills to cooperate in a team are explored in the article as a complex formation and as one of the soft skills. At higher education institutions, the future teachers training for the formation at primary school students' skills to collaborate in a team takes place mainly during the implementation of interactive, game and project methods. However, this training needs to be improved. The developed experimental model implies systematic work on the basis of Pedagogy of the Heart and Pedagogy of Success, as a methodological basis of the researched process; equivalence of tendencies of using group work to improve learning outcomes and group work as a means of formation of students' ability to interact. Experimental verification proved the effectiveness of the designed model: the number of representatives at a high level of readiness to develop primary schoolchildren' ability to work in a team significantly increased and there were no low-level representatives.
Designing and implementing a Big Data benchmark in a financial context: application to a cash management use case

This paper details the steps followed to benchmark a cash management platform of an investment bank using a generic benchmarking solution called BABEL. We highlight the modular design of BABEL, and present an evaluation methodology and best practices for its application on real world systems. The performance results collected with BABEL for the cash management use case enables to define the right tradeoffs in terms of consistency and availability, in a way that respects the service level agreements defined by the clients. On the other hand, we show that the overhead caused by BABEL’s integration with the platform at runtime is very negligible.
FedProto: Federated Prototype Learning over Heterogeneous Devices.

The heterogeneity across devices usually hinders the optimization convergence and generalization performance of federated learning (FL) when the aggregation of devices' knowledge occurs in the gradient space. For example, devices may differ in terms of data distribution, network latency, input/output space, and/or model architecture, which can easily lead to the misalignment of their local gradients. To improve the tolerance to heterogeneity, we propose a novel federated prototype learning (FedProto) framework in which the devices and server communicate the class prototypes instead of the gradients. FedProto aggregates the local prototypes collected from different devices, and then sends the global prototypes back to all devices to regularize the training of local models. The training on each device aims to minimize the classification error on the local data while keeping the resulting local prototypes sufficiently close to the corresponding global ones. Through experiments, we propose a benchmark setting tailored for heterogeneous FL, with FedProto outperforming several recent FL approaches on multiple datasets.
The formation of a professionally-oriented communicative competence of foreign students-economists by means of distance technologies

The article deals with the use of foreign language distance learning for first-year foreign students of economic specialties. The implementation of distance learning is one of the ways to modernize the education in Ukraine in the context of globalization and the intensive development of information technologies. Distance technologies are now widely used in many fields of education, especially when teaching a foreign language to inophones. Creating an effective learning system, based on information technology, is an urgent task at all levels of education. One of the systems focused on the professional development of future specialists is the system of teaching students a foreign language using information technology. The possibilities of organizing the educational process are not limited to traditional and distance learning. There is a significant educational sector in which distance learning cannot be fully applied, but individual elements of e-learning can be used (in particular, distance learning technologies). It is referred to full-time and part-time (1-2 courses) forms of higher education. The mixed learning has become a special role as a more perfect model of the educational process organization, which takes the advantage of distance learning and compensates for these disadvantages. To improve the organization of the educational process for the language training of foreign students, we consider appropriate to use the materials of distance courses in the models of mixed learning. The options for integrating distance learning into the traditional system of language training for foreigners in the mixed learning models have been analyzed. When integrating the model into a traditional educational process at this stage of foreigners' training, it is suggested to use the distance course developed by us with the prevailing classroom component, because the degree of students' independent work in learning the teaching material of the discipline in the first year is not high. The structure and content of the distance course «Foreign Language» (educational-professional sphere of communication connection), designed on the Moodle platform, are considered in the article. The importance of using distance technologies in the process of organizing language training for foreign students is noted. It contributes to the formation of professional competence of future specialists in the field of economics.
Fooling LiDAR Perception via Adversarial Trajectory Perturbation

LiDAR point clouds collected from a moving vehicle are functions of its trajectories, because the sensor motion needs to be compensated to avoid distortions. When autonomous vehicles are sending LiDAR point clouds to deep networks for perception and planning, could the motion compensation consequently become a wide-open backdoor in those networks, due to both the adversarial vulnerability of deep learning and GPS-based vehicle trajectory estimation that is susceptible to wireless spoofing? We demonstrate such possibilities for the first time: instead of directly attacking point cloud coordinates which requires tampering with the raw LiDAR readings, only adversarial spoofing of a self-driving car's trajectory with small perturbations is enough to make safety-critical objects undetectable or detected with incorrect positions. Moreover, polynomial trajectory perturbation is developed to achieve a temporally-smooth and highly-imperceptible attack. Extensive experiments on 3D object detection have shown that such attacks not only lower the performance of the state-of-the-art detectors effectively, but also transfer to other detectors, raising a red flag for the community. The code is available on https://ai4ce.github.io/FLAT/.