Models for Managing Production Systems of Machine-Building Enterprises Based on the Development and Using of Their Digital Twins

The paper discusses the goals and objectives of creating digital twins of the production system of a machine-building enterprise. The data structure of the information model of the production system of a machine-building enterprise, which is the basis for building a digital twin, is presented. The paper shows the main approaches to managing a production system based on the construction of its digital twin. It is revealed that along with traditional approaches to PS management by forming recommendations in terms of PS engineering and its operation, the choice of the most rational PS management algorithms that take into account the peculiarities of the production process organization and ensure the formation of production schedules that take into account PS reliability indicators has a great potential. It is proposed to use a specialized language of DPML to describe the information model of the PS through the “product-process-resource” paradigm, which ensures the coordination of the processes of forming recommendations in terms of engineering and operation of the PS, as well as the choice of the most rational algorithm for managing the PS.

Rational perioperative antibiotic prophylaxis for open damages of brush in children

Introduction. Today, hand injuries are one of the most pressing and common problems in modern traumatology worldwide. Results obtained statistically indicate a fairly high frequency of hand injuries, including open ones. Often, an incorrect prescription of antibiotics in the form of unjustified antibiotic therapy in the absence of direct indications is done. Aim. This study aimed to develop a rational algorithm for perioperative antibiotic prophylaxis for open hand injuries in children based on experimental and clinical research. Materials and methods. The study was divided into two phases: experimental and clinical. The experiment was carried out on 60 sexually mature, outbred guinea pigs. During the experiment, the analysis of clinical signs of inflammation, complete blood count and biochemical blood analysis, spiral computed tomography, and morphological study of the consolidation zone were performed. The clinical part of the work is based on the analysis of surgical treatment results of 120 children with open hand injuries, which were divided into two groups: the main group that included 50 children receiving treatment according to the experimentally developed perioperative antibiotic prophylaxis (PAP) algorithm, and the comparison group included 70 children receiving a perioperative course of antibiotics from 0 to 7 days, without a well-defined algorithm. Results. In the analysis of clinical results, laboratory, radiation, and morphological methods of studying the experimental material, the absence of antibiotic prophylaxis in open fractures of small tubular bones with a 90% probability was found to entail pro-inflammatory complications in the area of postoperative wound; however, a one day short-term course of PAP will prevent complications and will not have statistically significant differences with a longer course of three days. Discussion. Results of a clinical study proved the effectiveness of the developed algorithm and showed better results in early and late postoperative period in comparison with the chaotic prescription of antibacterial drugs without a clear algorithm; however, no statistically significant differences in the level of postoperative complications were found. Conclusion. On the basis of an experimental model of an open fracture of the tubular bone, osteosynthesis and various courses of antibiotic prophylaxis has proven that a short-term course of PAP within 24 h is the most optimal one, and achieving minimal risks of inflammatory complications and better anatomical and functional outcomes in clinical practice.

Knowledge-based Algorithms for BDI-agents

Multiagent algorithm is a knowledge-based distributed algorithm that solves some problems by means of cooperative work of agents. From an individual agent's perspective, a multiagent algorithm is a reactive and proactive knowledge/believe-based rational algorithm aimed to achieve an agent's own desires. In the paper we study a couple of knowledge-based multiagent algorithms. One particular algorithm is for a system consisting of agents that arrive one by one (in a non-deterministic order) to a resource center to rent (for a while) one of available desired resources. Available resources are passive, they form a cloud; each of the available resources is lent on demand if there is no race for this resource and returns to the cloud after use. Agents also form a cloud but leave the cloud immediately when they rent a desired resource. The problem is to design a knowledge-based multiagent algorithm, which allows each arriving agent eventually to rent some of desired resources (without race for these resources).

A mesterséges intelligencia az oktatásban: kihívások és lehetőségek

Összefoglalás. A mesterséges intelligencia (továbbiakban: MI) fogalma az egyik napról a másikra robbant be a tudományos világból a nemzetközi és a hazai köztudatba. Az MI számos formában jelen van életünkben és az elkövetkező pár évtizeden belül pedig olyan megkerülhetetlen és hétköznapi technológiai megoldássá válik, mint ma az internet. Ezért érdemes megvizsgálni, hogy mit mondanak a kutatások az automatizáció hatásairól, mit gondolnak erről a munkáltatók, valamint a jövő munkavállalói. Létfontosságú, hogy megmutassuk az MI-ben rejlő társadalmi és piaci lehetőségeket, biztonsági veszélyeket, ezáltal növelve a magyar vállalkozók versenyképességét és a munkavállalók karrierlehetőségeit. Ennek egyik kezdőlépése a társadalom tudatosítása, valamint az MI oktatásban történő bevezetése, mely kiterjed a technológia iskolákban történő alkalmazásától, egészen használatának, fejlesztésének, biztonsági kockázatainak az oktatásáig. Summary. The concept of artificial intelligence (hereinafter: AI) has exploded overnight from the scientific world into international and domestic public consciousness. AI is present in many forms in our lives, and over the next few decades it is set to become as an essential and everyday tech solution as the Internet today. Therefore, it is worth examining what research says about the effects of automation and what employers and future employees think about it. It is therefore of critical importance to demonstrate the social and market potentials and dangers for safety of AI, thereby increasing the competitiveness of Hungarian entrepreneurs and the career opportunities of the employees. One of the first steps in this is to raise public awareness and introduce AI into education, ranging from the use of technology in schools to the education of its use, safety risk and development. Is it worth thinking about what the distant future can bring to humanity? There are various professional predictions as to when we will invent the “real” AI, the master algorithm that controls each process, when we will achieve the singularity, from which AI will be able to program itself beyond human intelligence. Never, according to pessimists, between 2040–2100, according to optimists. Moreover, in the meantime, genetic engineering or a brain amplified with nanorobots may precede machine intelligence. What is certain is that cooperation and coexistence will be the cornerstone, so technical, philosophical, social, ethical and legal responses must be developed as long as the decision is in the hands of the US and not the AI. However, all this is a complex task, as logical contradictions in national regulations and political opinions, for example, are very difficult to handle for a rational algorithm. (Lovászy 2019) Regulation is needed that does not hinder economic development, but strengthens transparency and security. The opportunities inherent in AI will be decisive for both Hungary’s competitiveness and the success of the individual in the coming decades. In my study, I pointed out that the conscious use and development of AI by education, the knowledge of security risks can be a breaking point for broad strata of our nation. So, I first examined the impact of the use of AI on the labor market, what new generations of workers think and want, and how it all affects the educator, the content and tools of education, the methodology, and what are the benefits and risks. Then I flashed a couple of possible visions in which, whether we achieve singularity in the near or distant future or not, AI will be a crucial part of our everyday lives. The pillars, technological and sectoral focuses, and transformative projects of the newly adopted Artificial Intelligence Strategy Foundation will crucially determine how much we will be able to exploit the opportunities of the decades ahead at the individual and state levels. In order to increase Hungary’s competitiveness, it calls for further research and wide-ranging professional consultations on the conditions (infrastructure, competencies, etc.) and modern methods for the successful integration of AI, the awareness of society and the education of different age groups.

Theoretical Virtues in Science

A theoretical virtue in science is a property of a scientific theory that is considered desirable. Standard theoretical virtues include testability, empirical accuracy, simplicity, unification, consistency, coherence, and fertility. First highlighted by Thomas S. Kuhn in a seminal paper in 1977, theoretical virtues have come to play an important role in a number of philosophical debates. A central bone of contention in many of these debates is whether theoretical virtues are epistemic, i.e., whether they are indicative of a theory’s correctness, or whether they are just pragmatic, concerning only the convenient use of a theory. Particularly contested virtues are simplicity and unifying power. In the scientific realism debate, in which philosophers argue about whether or not scientific theories allow us to uncover the reality behind the phenomena, scientific realists have argued that virtuous theories are more likely to be correct than a less virtuous ones, even when they accommodate the same data. In the closely related debate about the so-called Inference to the Best Explanation, realists have argued that not only can we determine the best explanation on the basis of its virtues, but we can also determine which explanation is the true one. In discussions about “theory choice” or “theory appraisal,” philosophers discuss which virtues might be most decisive in scientists’ deliberations about which theory they should adopt. Here a theory’s successful novel predictions, or novel successes for short, have been a particular focus. Philosophers have also discussed possible trade-offs between various virtues and the difficulties which these may pose for theory choice. Samir Okasha has argued recently that there cannot be any rational algorithm for theory choice. Theoretical virtues also play a role in philosophical accounts of the laws of nature. One extremely prominent account, namely David Lewis’ Best System Analysis, appeals to simplicity and unifying power to determine what generalizations qualify as genuine laws of nature (rather than just accidentally true generalizations). Even in philosophical theorizing about science, theoretical virtues have been appealed to: Rudolf Carnap believed that simplicity and fruitfulness were important desiderata guiding the explication of scientific concepts. Finally, psychologists have started to investigate the role of theoretical virtues in picking explanations. There is work that appears to show that children and adults have preferences for simple and broad theories.