Reviewerly/exHarmony huggingface dataset:
Sleepwalking into Disaster? Requirements Engineering for Digital Cash (Position Paper)

Digital cash seems inevitable. But it’s not going to be bitcoin or the like, which will be regulated out of existence rather than being allowed to become mainstream currency. Central Bank Digital Currencies promise to eliminate crime but come with many of the problems that bitcoin set out to avoid. What do we actually need from digital cash? We had better figure it out before building and deploying unsuitable systems.
Exploratory studies on total reflection X-ray fluorescence spectrometry combined with slurry sampling for the multi-element analysis of copper-nickel sulfide ore

Major and trace elements in polymetallic minerals are crucial subjects of study in ore geology.
Learning to Select the Relevant History Turns in Conversational Question Answering

The increasing demand for web-based digital assistants has given a rapid rise in the interest of the Information Retrieval (IR) community towards the field of conversational question answering (ConvQA). However, one of the critical aspects of ConvQA is the effective selection of conversational history turns to answer the question at hand. The dependency between relevant history selection and correct answer prediction is an intriguing but under-explored area. The selected relevant context can better guide the system so as to where exactly in the passage to look for an answer. Irrelevant context, on the other hand, brings noise to the system, thereby resulting in a decline in the model’s performance. In this paper, we propose a framework, DHS-onvQA (Dynamic History Selection in Conversational Question Answering), that first generates the context and question entities for all the history turns, which are then pruned on the basis of similarity they share in common with the question at hand. We also propose an attention-based mechanism to re-rank the pruned terms based on their calculated weights of how useful they are in answering the question. In the end, we further aid the model by highlighting the terms in the re-ranked conversational history using a binary classification task and keeping the useful terms (predicted as 1) and ignoring the irrelevant terms (predicted as 0). We demonstrate the efficacy of our proposed framework with extensive experimental results on CANARD and QuAC – the two popularly utilized datasets in ConvQA. We demonstrate that selecting relevant turns works better than rewriting the original question. We also investigate how adding the irrelevant history turns negatively impacts the model’s performance and discuss the research challenges that demand more attention from the IR community.
A Web Service Oriented Integration Solution for Capital Facilities Information Handover

The potential to obtain the correct information, manage and interchange it are some of the keys to the success of a project. In the Oil and Gas industry context, the Capital Facilities Information Handover Specifications (CFIHOS) represents an initiative to improve how information is exchanged between companies that own, operate, and build equipment for the process and energy sectors. In that sense, CFIHOS proposes a data model and a library (Reference Data Library - RDL) with standard terms for data interchange. This work presents an implementation using a subset of the CFIHOS data model in the scope of Construction of Engineering Procurement (EPC) contracts. The use case was implemented over the INSIDE system, allowing dynamic integration between heterogeneous databases using an architecture based on web services. The knowledge of extracting the information from databases and generating a spreadsheet in the CFIHOS data model was encoded in INSIDE by defining data services in the knowledge base. There are no tools that verify how much the information contained in a file complies with the CFIHOS data model and RDL information. For this reason, a prototype of a validator was implemented to verify the challenges of using CFIHOS. The developed CFIHOS Validator complements the data extraction and data verification flows according to this standard.
Counterfactual Explanations for Sequential Recommendation with Temporal Dependencies

Explanations can substantially enhance users’ trust and satisfaction with recommender systems. Counterfactual explanations have demonstrated remarkable effectiveness in enhancing the performance of explainable sequential recommendation. However, existing counterfactual explanation models for sequential recommendation ignore temporal dependencies in a user’s historical behavior sequence. Moreover, counterfactual histories must be as close as possible to the real history; otherwise, they will violate the user’s real behavioral preferences. In this paper, we propose Counterfactual Explanations with Temporal Dependencies (CETD), a counterfactual explanation model based on a Variational Autoencoder (VAE) for sequential recommendation that handles temporal dependencies. When generating counterfactual histories, CETD uses a Recurrent Neural Network (RNN) to capture both long-term preferences and short-term behavior in the user’s real behavioral history, which can enhance explainability. Meanwhile, CETD fits the distribution of reconstructed data in a latent space, and then uses the variance obtained from learning to make counterfactual sequences closer to the original sequence, which will reduce the proximity of counterfactual histories. Extensive experiments on two real-world datasets show that the proposed CETD consistently outperforms state-of-the-art methods.
Path-KGE: Preference-Aware Knowledge Graph Embedding with Path Semantics for Link Prediction

Knowledge graph embedding (KGE) aims to transfer entities and relations into low-dimensional vector space while preserving underlying semantics in knowledge graph (KG). Some existing models directly learn embeddings based on original triples, while others integrate external information to enhance the limited semantic information in KG. However, most of them ignore latent user preferences in their interactions with real-world KG applications, not even considering the relational semantics implied in historical interaction data, which are practical and essential for many downstream tasks like link prediction. To address these issues, we propose a novel preference-aware knowledge graph embedding with path semantics model Path-KGE, which learns semantic information of relation paths and integrates it into embedding process. First, we mine multi-hop relations with frequent and temporal characteristics as semantic relation paths in user interaction data, to obtain implicit user preference features. Second, we design a path importance function to distinguish the semantic impacts of user preferences on distinct relation paths. Finally, we utilize weight scores as long-term constraints to learn preference-aware embeddings, so that the representation vectors of entity pairs connected by preferred relation paths can remain close distances in vector space as in reality. The experimental results show that our model outperforms state-of-the-art translation-based models on link prediction and triple classification tasks.
METHODOLOGICAL FOUNDATIONS OF THE STUDY OF NEUROSOCIAL INTELLIGENCE OF STUDENTS USING DIGITAL TECHNOLOGIES

The article analyzes and explores the methodological foundations and semantic approaches of the described neurosocial intelligence of students of the Financial University under the Government of the Russian Federation. Socially active youth manifests themselves and is represented both in the real world (university) and in the virtual space of education and Internet communications (digital educational environment). The most significant is the study of satisfaction and dissatisfaction with information and educational needs, as well as ideas about digital technologies. The leading methodological principle of analyzing the influence of neurosocial intelligence on behavior in educational systems is the performance of research works, which in fact are the decision-making on the further educational track and the features of individual learning. In this study difficulties in using digital platforms were reported by a relatively small number of respondents in the total sample. In general, it was revealed that the attitude of students and teachers to work in the digital educational environment is positive, also the tendency to perceive digitalization and changes in human intelligence as an opportunity for development was indicated.
UNIVERSITY PROJECT IN THE ANCIENT CITY: THE HISTORY OF DEVELOPMENT OF CULTURE, EDUCATION AND ENLIGHTENMENT IN VELIKY NOVGOROD

The article describes the experience of creating Novgorod State University within the framework of the integration concept as an innovative project. The historical and cultural context of the development of the ancient Novgorod region is presented, which gives grounds to believe that the formation of the Novgorod University of the classical type is a historically predetermined and natural phenomenon. At the same time, it is shown that the implementation of such university project requires special conditions, prerequisites and huge efforts from university teams, understanding the need for change, support for power structures and the formation of a powerful leadership team – a team of like-minded people. It is also important that in the system of spiritual and moral values of Veliky Novgorod, bookishness and enlightenment have always occupied one of the leading places. From here new trends of worldview, science and culture spread in Russia. Currently, the university with full responsibility implements its mission of the federal-regional center for science, culture, education, is the main methodological and scientific-methodical regional center for continuing pedagogical education and educational, scientific and innovative complex with a developed infrastructure.
SYNERGETIC APPROACH TO ANALYSIS AND IMPLEMENTATION OF SOCIO-PEDAGOGICAL PRACTICES

The article is devoted to the urgent problem of identifying potential possibilities of synergetic methodology for the study of socio-pedagogical activity as a special system that is transformed under the influence of unstable conditions of society. It is emphasized that the subject area of socio-pedagogical activity is currently being transformed, characterized by an increasing trend of spontaneous socialization of children, that its spatial and temporal characteristics are changing, as the space of children&amp;apos;s problems is expanding, the time required for scientific understanding of problems and the search for solutions to them is decreasing. The appeal to the synergetic approach is due to the fact that it is focused on the analysis of system processes that are in a nonlinear, non-equilibrium state, in the &amp;quot;order – chaos - order&amp;quot; movement. The article uses the following concepts to describe the process of organization and self-organization of socio-pedagogical activity: &amp;quot;attractor&amp;quot; (an ordered process), &amp;quot;fluctuation&amp;quot; (the presence of potential opportunities in the process both to maintain the system and to destroy it), &amp;quot;bifurcation&amp;quot; (a chaotic state of the process). At the institutional level, the movement of socio-pedagogical activity through the stages of &amp;quot;order - chaos - order&amp;quot; is determined by the value orientations of its subjects. They are the center of attraction for specialists of helping professions and keep the system in a state of stable attractor. Violation of the value bases of socio-pedagogical activity disorganizes the system, leads it into a state of chaos (bifurcation). At the individual level of teacher–child interaction, a sense of stability (attractor) is formed if the practices used to solve the child&amp;apos;s problems give a positive result. Otherwise, the teacher plunges into reflection, looking for ways of self-organization that contributes to solving problems.
Building Correct-by-Construction Systems with Formal Patterns

Formal patterns are formally specified generic solutions to commonly occurring computational problems. A formal pattern applies to a typically infinite class of systems that satisfy specified semantic requirements. Application of a formal pattern to a system satisfying the formal pattern’s input requirements results in a new system with new functionality that is correct by construction and enjoys specific formal properties. This paper explains the semantics of formal patterns and illustrates their usefulness from the software engineering, programming methodology, and formal methods perspectives by means of specific formal patterns in several application areas.
GAMIFICATION AS A CONDITION FOR DEVELOPING HIGH SCHOOL STUDENTS’ ABILITY TO COOPERATE

The article deals with the current trend of modern education – gamification. The authors analyze the reason for the increased interest in the problem of developing communicative skills of high school students in face-to-face and distant communication. The efficiency of the gamification approach as a promising one for the construction of games is substantiated. An algorithm for the development of communicative games is proposed, which can be used by teachers in extracurricular work with senior students. The communicative game is considered as a system consisting of 14 elements. For organizing efforts to develop the cooperation ability the three-component structure of this ability is described, the criteria for its development are indicated in accordance with the selected components. The results of the study of the use of gamification for the development of senior adolescents’ ability to cooperate based on their participation in remote team games, online gatherings and online tournaments are presented
K.D. USHINSKY: NEW COMPREHENSION OF LIFE STAGES AND PEDAGOGICAL ACTIVITY (FOR THE 200TH ANNIVERSARY OF THE BIRTH)

K.D. Ushinsky lived a short but eventful life, each stage of which had a certain significance for the formation of his personality, worldview, scientific and practical pedagogical activity. Based on the biographical method, using little-known letters and other documents and pre-revolutionary materials, a phased analysis of the objective conditions and circumstances that determined the life and professional path of K.D. Ushinsky. Particular emphasis is placed on the mention of those people who had a direct and indirect positive impact in the process of his formation as a person, teacher and scientist.
Correct and Efficient Policy Monitoring, a Retrospective

The MonPoly project started over a decade ago to build effective tools for monitoring trace properties, including functional correctness, security, and compliance policies. The original MonPoly tool supported monitoring specifications given in metric first-order temporal logic, an expressive specification language. It handled both the online case, where system events are monitored as they occur, and the offline case, monitoring logs. Our tool has evolved over time into a family of tools and supporting infrastructure to make monitoring both scalable and suitable for high assurance applications. We survey this evolution which includes: (1) developing more expressive monitors, e.g., adding aggregation operators, regular expressions, and limited forms of recursion; (2) delimiting efficiently monitorable fragments and designing new monitoring algorithms for them; (3) supporting parallel and distributed monitoring; (4) using theorem proving to verify monitoring algorithms and explore extensions; and (5) carrying out ambitious case studies.
International Criminal Assessment of the Risks Associated with the Use of Digital Technologies for Criminal Purposes

The chapter reveals the international legal framework for countering crimes in the digital sphere. The growth of digital crimes has led to an appeal to the problem of countering digital crimes at both supranational and domestic levels. Meanwhile, there is no unity in the issues under consideration today. The purpose of this study is: to consider global and national approaches to countering digital crime, and to identify the main reference points. The study of the provisions of criminal legislation, as well as national plans for countering IT crimes in Western Europe, the USA, and the CIS countries allowed us to form a unified picture of countering digital crimes on the world stage. The research is based on a wide range of international sources, as well as data from international organizations, national legislation, and scientific literature. The methodology of the research comprises historical, comparative, legal and functional methods and a systemic approach.
The Efficiency of Distance and Traditional Academic Activities in Teaching English Language to Students of International Economic Relations

Digitalized transformational processes that have affected the sphere of education due to the COVID-19 pandemic have caused fundamental changes in approaches to teaching. While most courses implied training in a traditional format with direct face-to-face contact between a teacher and students, digital technologies had to be applied on a large scale to various types of educational activities and tasks to achieve the stated goals of completing the courses as part of the curriculum. Two years after the global switch to online learning, most universities now have traditional offline classes, which makes it possible to analyze the efficiency of the two different modes. The following questions thus arise: How successful has the introduction of online learning technologies been? And what types of activities and tasks performed remotely can be incorporated into the regular educational process? This article highlights the main problems brought about by the transition to distance learning in the spring of 2020 due to the spread of COVID-19, analyzes whether teaching staff has managed to adapt efficiently to working online, and identifies the most productive kinds of language development activities applied within the framework of teaching English for special purposes (ESP) to students at the School of International Economic Relations at MGIMO University during the distance learning period. This paper relies on data collected from empirical studies and employs the methods of descriptive and comparative analysis. Conclusions summing up the potential of integrating some online learning techniques and activities into the traditional face-to-face educational process on a regular basis determine the practical significance of the study.
Enhancing Speaking Skills in a Foreign Language Using Virtual Reality. A Study in a Portuguese Higher Education Institution

Fear of public speaking is a problem shared by many people, which means it is also experienced by many students. However, given the circumstances of a student’s life, they gradually discover that they must frequently deal with this fear whenever the need to engage in oral presentations arises. This fear ends up being considerably worse when public speaking is not done in their mother tongue, as is the case in foreign language disciplines. In this regard, and to better prepare students for public speaking, a virtual reality study was conducted with 41 students from a Portuguese higher education institution. The study’s objectives were to ascertain whether virtual reality makes it possible to design an environment that is more comfortable for practicing oral presentations and whether the tool’s performance feedback may potentially have an impact on students’ subsequent performances. It was concluded that, in fact, the use of virtual reality is able to provide clear insights regarding the students’ performance, giving specific instructions on how to change certain aspects, such as voice volume or speech pace, among others.
Evaluation method of intelligent classroom teaching effect based on fuzzy set change algorithm

In order to solve the problems of low evaluation accuracy, large quantitative error of indicators, and long evaluation time in traditional teaching effect evaluation methods, evaluation method of intelligent classroom teaching effect based on fuzzy set change algorithm was designed for college students' English reading teaching courses. Firstly, determine the evaluation indicators for the effect of English reading teaching for college students in intelligent classrooms. Secondly, the feature vector corresponding to the largest feature of the index is calculated, and the feature vector is quantised. Finally, based on the fuzzy set change algorithm, a fuzzy evaluation matrix is constructed to determine the grade of intelligent classroom teaching quality, construct an intelligent classroom teaching effect evaluation model, and obtain the evaluation results. The experimental results show that using this method can effectively improve the accuracy of intelligent classroom teaching evaluation.
Virtual Classroom and the Impact of E-Skills on the Performance of Peruvian University Students

The objective of the study is to explore the experiences of students in the virtual classroom and the impact of digital competencies on the performance of students. Participants were 363 university students enrolled in the School of Communication at a private university in Peru. The instrument used was a 10-question questionnaire, based on a Likert scale. According to the results, the participants concluded that they were not entirely satisfied with the virtual classrooms, as they found it difficult to have a precise anchorage in the learning process. In addition, there are gaps related to the contents elaborated by teachers for asynchronous classes and synchronous lessons, finding advantages in the synchronic lessons, being valued by the student, because they can interact live and feel that they have a tutor supporting them. For this reason, information should be distributed in a straightforward and creative approach, avoiding long online periods and allowing long content in digestible and downloadable formats.
A BiLSTM-attention-based point-of-interest recommendation algorithm

Abstract Aiming at the problem that users’ check-in interest preferences in social networks have complex time dependences, which leads to inaccurate point-of-interest (POI) recommendations, a location-based POI recommendation model using deep learning for social network big data is proposed. First, the original data are fed into an embedding layer of the model for dense vector representation and to obtain the user’s check-in sequence (UCS) and space-time interval information. Then, the UCS and spatiotemporal interval information are sent into a bidirectional long-term memory model for detailed analysis, where the UCS and location sequence representation are updated using a self-attention mechanism. Finally, candidate POIs are compared with the user’s preferences, and a POI sequence with three consecutive recommended locations is generated. The experimental analysis shows that the model performs best when the Huber loss function is used and the number of training iterations is set to 200. In the Foursquare dataset, Recall@20 and NDCG@20 reach 0.418 and 0.143, and in the Gowalla dataset, the corresponding values are 0.387 and 0.148.