Identification of heat exchange process in the evaporators of absorption refrigerating units under conditions of uncertainty

Проведено аналіз функціонування випарників абсорбційно-холодильних установок блоку вторинної конденсації типового для України агрегату синтезу аміаку. Обґрунтована необхідність мінімізації температури вторинної конденсації за рахунок створення автоматизованої адаптивної системи оптимального програмного управління. Встановлені рівняння для чисельної оцінки невизначеності теплового навантаження випарника та коефіцієнту теплопередачі. Розроблено алгоритмічне забезпечення щодо розв’язання задач ідентифікації та створення математичної моделі. Визначена технічна структура автоматизованої системи для їх реалізації

Improving the Representation and Conversion of Mathematical Formulae by Considering their Textual Context

Mathematical formulae represent complex semantic information in a concise form. Especially in Science, Technology, Engineering, and Mathematics, mathematical formulae are crucial to communicate information, e.g., in scientific papers, and to perform computations using computer algebra systems. Enabling computers to access the information encoded in mathematical formulae requires machine-readable formats that can represent both the presentation and content, i.e., the semantics, of formulae. Exchanging such information between systems additionally requires conversion methods for mathematical representation formats. We analyze how the semantic enrichment of formulae improves the format conversion process and show that considering the textual context of formulae reduces the error rate of such conversions. Our main contributions are: (1) providing an openly available benchmark dataset for the mathematical format conversion task consisting of a newly created test collection, an extensive, manually curated gold standard and task-specific evaluation metrics; (2) performing a quantitative evaluation of state-of-the-art tools for mathematical format conversions; (3) presenting a new approach that considers the textual context of formulae to reduce the error rate for mathematical format conversions. Our benchmark dataset facilitates future research on mathematical format conversions as well as research on many problems in mathematical information retrieval. Because we annotated and linked all components of formulae, e.g., identifiers, operators and other entities, to Wikidata entries, the gold standard can, for instance, be used to train methods for formula concept discovery and recognition. Such methods can then be applied to improve mathematical information retrieval systems, e.g., for semantic formula search, recommendation of mathematical content, or detection of mathematical plagiarism.Comment: 10 pages, 4 figure

Adversarial Attack and Defense on Graph Data: A Survey

Deep neural networks (DNNs) have been widely applied to various applications including image classification, text generation, audio recognition, and graph data analysis. However, recent studies have shown that DNNs are vulnerable to adversarial attacks. Though there are several works studying adversarial attack and defense strategies on domains such as images and natural language processing, it is still difficult to directly transfer the learned knowledge to graph structure data due to its representation challenges. Given the importance of graph analysis, an increasing number of works start to analyze the robustness of machine learning models on graph data. Nevertheless, current studies considering adversarial behaviors on graph data usually focus on specific types of attacks with certain assumptions. In addition, each work proposes its own mathematical formulation which makes the comparison among different methods difficult. Therefore, in this paper, we aim to survey existing adversarial learning strategies on graph data and first provide a unified formulation for adversarial learning on graph data which covers most adversarial learning studies on graph. Moreover, we also compare different attacks and defenses on graph data and discuss their corresponding contributions and limitations. In this work, we systemically organize the considered works based on the features of each topic. This survey not only serves as a reference for the research community, but also brings a clear image researchers outside this research domain. Besides, we also create an online resource and keep updating the relevant papers during the last two years. More details of the comparisons of various studies based on this survey are open-sourced at https://github.com/YingtongDou/graph-adversarial-learning-literature.Comment: In submission to Journal. For more open-source and up-to-date information, please check our Github repository: https://github.com/YingtongDou/graph-adversarial-learning-literatur

Finnish pupils’ success in mathematics: factors that contribute to Finnish pupils’ success in mathematics

This report focuses on the factors that contribute positively to Finnish pupils’ success in mathematics and considers the implications for policy and practice in England. Includes examples of items from the PISA and TIMSS test

The Principles Of Developing A Management Decision Support System For Scientific Employees

Employees engaged in mental work have become the most valuable assets of any organization in the 21st century. The satisfaction of those involved in mental work requires the provision of objectivity and transparency in their decision-making. This, in turn, entails the development of scientifically motivated decision making mechanisms and scientific-methodological approaches to evaluate their performance based on innovative technologies.The main goal of this article is in development of the scientific and methodological framework for the establishment of a decision support system to manage the employees engaged in mental work and operating in uncertainty. In this regard, initially, the question of evaluating the activities of scientific workers is examined, its characteristic features are determined, and the fuzzy relation model is proposed as a multi-criterion issue formed in uncertainty. Taking into consideration the hierarchical structure of the criteria that allows evaluating the activities of scientific workers, a phased solution method based on an additive aggregation method is proposed. In accordance with the methodology, a functional scheme of the decision support system to manage the scientific personnel is developed. The working principle of each block and the interaction of the blocks are described. The rules for the employees\u27 management decisions are shown by referring to the knowledge production model.Based on the proposed methodological approach, the implementation phases of the decision support system for the management of the scientific workers of the Institute of Information Technology of ANAS are described. To evaluate the employees\u27 performance, the tools to collect initial information, evaluate the system of criteria, define their importance coefficients and mathematical descriptions are provided. Some results of the system software are presented. The opportunities of the system based on the proposed methodology to support enterprise mangers to make scientifically justified decisions are provided