InGraph Platform: a new resource of scientific works with an expanded scientometrics tool

The paper presents a scientific and practical development of an information technology product – the InGraph Platform. The logic, structure, and information technology implementation of this Platform provide a practically useful service for all subjects of scientific activity who create scientific works and use them: authors, reviewers, and end users from science and practice. The Platform mechanisms, which ensure interaction between all its users, form a technology of scientific and practical communications based on the principle of “everyone gets what they need with minimal waste of time”. The InGraph Platform concept implements the transition from the one-dimensional model of “scientist for scientist” or “science for science” to the two-dimensional model of “science for improving human well-being”, setting as a priority for science the provision of practical needs for the results of scientific research, rather than the number of citations or the h-index. At the same time, the use of the platform completely eliminates the intermediary in the form of a publisher, preserving the copyright of the author and ensuring honest and transparent communications between authors and users of scientific work

The role of social networks in students’ learning experiences

The aim of this research is to investigate the role of social networks in computer science education. The Internet shows great potential for enhancing collaboration between people and the role of social software has become increasingly relevant in recent years. This research focuses on analyzing the role that social networks play in students’ learning experiences. The construction of students’ social networks, the evolution of these networks, and their effects on the students’ learning experience in a university environment are examined

Mapping for maximum performance on FPGA DSP blocks

The digital signal processing (DSP) blocks on modern field programmable gate arrays (FPGAs) are highly capable and support a variety of different datapath configurations. Unfortunately, inference in synthesis tools can fail to result in circuits that reach maximum DSP block throughput. We have developed a tool that maps graphs of add/sub/mult nodes to DSP blocks on Xilinx FPGAs, ensuring maximum throughput. This is done by delaying scheduling until after the graph has been partitioned onto DSP blocks and scheduled based on their pipeline structure, resulting in a throughput optimized implementation. Our tool prepares equivalent implementations in a variety of other methods, including high-level synthesis (HLS) for comparison. We show that the proposed approach offers an improvement in frequency of 100% over standard pipelined code, and 23% over Vivado HLS synthesis implementation, while retaining code portability, at the cost of a modest increase in logic resource usage

National Analytical Scientific Base of Ukraine as a resource of quality scientific publications for Web of Science and Scopus: conceptual solution and information and mathematical support

The object of research: scientific quality of periodical scientific publications in terms of national and international requirements. Investigated problem: imperfect evaluation of the quality of scientific publications of Ukraine, which does not allow at the state level to adequately represent the scientific heritage of the country in the form of high-quality scientific periodicals. Instead, such an acquisition may be of interest to Web of Science and Scopus, which is interested in quality scientific publications in order to realize its commercial interest in expanding the circle of subscribers. Because of this, each Ukrainian publication must independently prove its ability to index in Web of Science and Scopus, and these resources do not have the opportunity to obtain a potentially large cluster of high-quality scientific publications with a theoretical horizon of more than 2,000 publications. Accordingly, the large-scale presentation of scientific periodicals of Ukraine in Web of Science and Scopus will make it possible to increase the ratings of Ukrainian science, which is represented by the universities of the Ministry of Education and Science of Ukraine and the structures of the National Academy of Sciences of Ukraine. The main scientific results: the proposed general structure of the National Analytical Scientific Base of Ukraine (NASB), which takes into account international quality requirements and scientometric indices, and is supplemented with analytical quality evaluation tools. The proposed informational and mathematical support includes four components of the Integral Quality index (QI) vector, which takes into account the relative indices of the quality of a scientific publication, its demand among authors, citations and demand among readers. This allows comprehensive, objective and transparent evaluation of the quality of scientific publications on four quantitative scales, which minimizes possible manipulations and increases trust in scientific publications on the part of users. The area of practical use of the results of the study: a system for evaluating the quality of scientific publications, scientific activity of individual scientists, collectives, institutions of Ukraine, as well as, in a potential perspective, scientometric databases Web of Science and Scopus as integrated sub-databases. Innovative technological product: the concept and informational and mathematical support of a database of scientific periodicals, which has the potential for practical implementation under the conditions of investment in development and implementation. The scope of the innovative technological product: NASB as a fully functional independent scientific resource that can be used in the system of evaluating scientific activity in Ukraine, or as part of other global resources of scientific periodicals, in particular Web of Science and Scopus

CSR Training and Financial Statement “Disclosure”: The Case of Italy

The objective of the chapter is to analyse the impact that CSR (corporate social responsibility) training had on non-financial information that is contained in financial statements following the EU directive 2014/95/EU and the Italian law: 254/2016. Literature review is based on institutional theory and social and environmental accounting as emancipatory tool to ameliorate the quality of life. The case analysed is the territory of Rimini, Italy. The case has been chosen because Rimini represents one of the most important concentrations within the hospitality and tourism industry in Europe. Another reason is that in the area of Rimini, 13 years ago, CSR training courses had been promoted for profit-making enterprises by the Chamber of Commerce along with public and private organisations. These training courses created a very important background for collocating the new EU directive regarding non-financial information that must necessarily be contained within the financial statements of enterprises. The objective of the chapter is to analyse the impact that the CSR training had on non-financial information that is contained in financial statements following the EU directive 2014/95/EU and Italian law: 254/2016

Model-driven engineering of an openCypher engine: using graph queries to compile graph queries

Graph database systems are increasingly adapted for storing and processing heterogeneous network-like datasets. Many challenging applications with near real-time requirements - such as financial fraud detection, on-the-fly model validation and root cause analysis - can be formalised as graph problems and tackled with graph databases efficiently. However, as no standard graph query language has yet emerged, users are subjected to the possibility of vendor lock-in. The openCypher group aims to define an open specification for a declarative graph query language. However, creating an openCypher-compatible query engine requires significant research and engineering efforts. Meanwhile, model-driven language workbenches support the creation of domain-specific languages by providing high-level tools to create parsers, editors and compilers. In this paper, we present an approach to build a compiler and optimizer for openCypher using model-driven technologies, which allows developers to define declarative optimization rules

Towards Extreme and Sustainable Graph Processing for Urgent Societal Challenges in Europe

The Graph-Massivizer project, funded by the Horizon Europe research and innovation program, researches and develops a high-performance, scalable, and sustainable platform for information processing and reasoning based on the massive graph (MG) representation of extreme data. It delivers a toolkit of five open-source software tools and FAIR graph datasets covering the sustainable lifecycle of processing extreme data as MGs. The tools focus on holistic usability (from extreme data ingestion and MG creation), automated intelligence (through analytics and reasoning), performance modelling, and environmental sustainability tradeoffs, supported by credible data-driven evidence across the computing continuum. The automated operation uses the emerging serverless computing paradigm for efficiency and event responsiveness. Thus, it supports experienced and novice stakeholders from a broad group of large and small organisations to capitalise on extreme data through MG programming and processing. Graph-Massivizer validates its innovation on four complementary use cases considering their extreme data properties and coverage of the three sustainability pillars (economy, society, and environment): sustainable green finance, global environment protection foresight, green AI for the sustainable automotive industry, and data centre digital twin for exascale computing. Graph-Massivizer promises 70% more efficient analytics than AliGraph, and 30 % improved energy awareness for extract, transform and load storage operations than Amazon Redshift. Furthermore, it aims to demonstrate a possible two-fold improvement in data centre energy efficiency and over 25 % lower greenhouse gas emissions for basic graph operations.</p

Benchmarking communicative reinforcement learning frameworks on multi-robot cooperative tasks

Industry 4.0 warehousing is characterised by autonomous multi-robot collaboration systems (MRSs) along with other technologies such as digital communication capabilities and the Internet of Things. These MRSs need to behave coherently for the efficient completion of the assigned cooperative tasks. Multi-agent reinforcement learning (MARL) frameworks are currently considered state-of-the-art to control the behaviour of autonomous MRSs. These MARL frameworks can be with learnable or predefined communication. Current works lack any worthwhile evaluation of communicative MARL frameworks on multi-robot cooperative tasks. This work empirically evaluates current state-of-the-art seminal learnable communicative MARL frameworks by comparing their performance against non-communicative MARL frameworks on multi-robot coop-erative tasks in the context of Industry 4.0 warehousing with the assumptions of partial observability and reward sparsity. The results demonstrate that communicative MARL frameworks outperform their counterparts by a fair margin in training (average returns between 11 and 6 against 8 and 4 for highest and lowest values respectively) and execution performances (average returns between 1.24 and 0.29 against 0.49 and 0.19 for highest and lowest values respectively). This leads to the conclusion that communicative MARL is better suited to multi-robot cooperative tasks under the above-mentioned assumptions.ye

Economical representation of spatial networks

Network visualization is essential for many scientific, societal, technological and artistic domains. The primary goal is to highlight patterns out of nodes interconnected by edges that are easy to understand, facilitate communication and support decision-making. This is typically achieved by rearranging the nodes to minimize the edge crossings responsible of unintelligible and often unaesthetic trends. But when the nodes cannot be moved, as in spatial and physical networks, this procedure is not viable. Here, we overcome this situation by turning the edge crossing problem into a graph filtering optimization. We demonstrate that the presence of longer connections prompt the optimal solution to yield sparser networks, thereby limiting the number of intersections and getting more readable layouts. This theoretical result matches human behavior and provides an ecologically-inspired criterion to visualize and model real-world interconnected systems