https://analecta.hu/index.php/analecta/issue/feedAnalecta Technica Szegedinensia2024-12-12T13:49:46+01:00Prof. Livia Cveticanineditor@analecta.huOpen Journal Systems<p>The Analecta Technica Szegedinensia (Anal. Tech. Szeged.), is an international journal dedicated to the latest advancements in engineering related sciences. The aim of the Journal is to offer scientists and engineering specialists all over the world an international forum to promote, share, and discuss various new issues and developments in different areas of engineering science.</p>https://analecta.hu/index.php/analecta/article/view/45848Augmented Reality Based Industrial Digitalization and Logistics2024-07-01T11:57:06+02:00János Simonsimon@mk.u-szeged.hu<p class="MK06AbstractText"><span lang="EN-GB">The virtualization systems enable the examination of the system's virtual elements by manufacturers, thus allowing them to be analysed and designed where real-world changes are necessary. Unnecessary planning is reduced by virtual reality, which allows engineers to experiment with changes before the final solution is created. Realistic and risky simulations occurring in the manufacturing environment, such as chemical spills, hazardous machinery, and noisy surroundings, can be simulated through virtual reality training programs without exposing workers to actual danger. In the event of an inevitable occurrence, employees will have usable experience and are more likely to respond appropriately to the situation. The paper presents and describes some of the most important Logistics 4.0 technologies: Internet of Things, robotics and automation, augmented reality, 3D printing and automatic guided vehicles. The aim of this paper is to describe the concept of Logistics 4.0, define its significance, components and technologies using augmented reality.</span></p>2024-12-12T00:00:00+01:00Copyright (c) 2024 János Simonhttps://analecta.hu/index.php/analecta/article/view/45844The Relationship Between Supplementation and Sport2024-06-16T21:13:38+02:00Gréta Újváriujvarigreti@gmail.comBrigitta Zsótérzsoterb@mk.u-szeged.huZoltán Veresveres.zoltan@gtk.uni-pannon.hu<p>Nowadays, the fitness industry has become a growing industry alongside the nutritional supplements industry within the food industry. Small and large companies are fighting for consumers. They offer products tailored to different training goals, whether sold online or offline. Companies are developing their marketing strategies by observing consumer preferences and habits. But do we need supplementation? Are the products on the market safe? What do we even mean by a food supplement? Is it a good idea to buy supplements that are in line with the latest trends? In this study we will show whether or not supplementation is really necessary for athletes and what determines whether it is.</p>2024-12-12T00:00:00+01:00Copyright (c) 2024 Gréta Újvári, Brigitta Zsótér, Zoltán Vereshttps://analecta.hu/index.php/analecta/article/view/45841Modelling Hysteresis with Memristors2024-07-01T11:59:09+02:00Sándor Csikóscsikos-s@mk.u-szeged.huÁdám Bálintbalint-a@mk.u-szeged.huJózsef Sárosisarosi@mk.u-szeged.hu<p class="MK06AbstractText"><span lang="EN-GB">In the realm of electronics, the foundational passive components—resistors, inductors, and capacitors—are well-established. However, in 1971, Leon Chua introduced a theoretical fourth element, the memristor, identified by its distinctive characteristic of memristance and its manifestation in a pinched hysteresis loop. This intriguing property suggests potential applications beyond conventional electronics, particularly in modelling hysteresis phenomena across various domains. This paper delves into the exploration of memristance as a mathematical framework for simulating hysteresis in electrical and mechanical systems. We commence by elucidating the theoretical underpinnings of memristance and its hysteresis behaviour, followed by a comprehensive overview of existing hysteresis models. Subsequently, we propose a novel approach that leverages the memristor model to offer enhanced insights and predictive capabilities for hysteresis in these systems. Through analytical examination and simulation studies, we demonstrate the versatility and applicability of the memristor model, underscoring its potential as a universal tool for hysteresis modelling. This research not only broadens the understanding of memristive properties but also opens new avenues for cross-disciplinary applications, ranging from electronic circuit design to mechanical system analysis.</span></p>2024-12-12T00:00:00+01:00Copyright (c) 2024 Sándor Csikós, Ádám Bálint, József Sárosihttps://analecta.hu/index.php/analecta/article/view/45836Examination of Xanthan Production on Biodiesel Industry Effluent-based Medium in Lab-scale Bioreactor2024-06-14T19:18:44+02:00Ida Zahovićida.zahovic@uns.ac.rsJelena Dodićklik@uns.ac.rsDamjan Vučurovićdvdamjan@uns.ac.rsBojana Bajićbaj@uns.ac.rsSiniša Dodićdod@uns.ac.rsZorana Trivunovićron@uns.ac.rs<p>Xanthan is microbial polysaccharide with outstanding rheological properties, non-toxic nature, biodegradability, and biocompatibility. This biopolymer is widely used in food, biomedical, pharmaceutical, petrochemical, chemical and textile industry. Industrial xanthan production is generally conducted by aerobic submerged cultivation of <em>Xanthomonas campestris</em> strains on the media with glucose or sucrose under optimal conditions. Results from previous research indicate that xanthan can be successfully produced on media containing crude glycerol from biodiesel industry by different <em>Xanthomonas</em> species. The aim of this study was to examine the course of xanthan biosynthesis by the reference strain <em>X. campestris</em> ATCC 13951 in lab-scale bioreactor on medium containing crude glycerol generated in domestic biodiesel factory. The bioprocess was monitored by the analysis of cultivation medium samples taken in predetermined time intervals, and its success was estimated based on the xanthan concentration in the medium, separated biopolymer average molecular weight and degree of nutrients conversion. At the end of bioprocess, cultivation medium contained 12.34 g/L of xanthan with the average molecular weight of 3.04∙10<sup>5</sup> g/mol. Within this study, the achieved degree of glycerol, total nitrogen and total phosphorous conversion were 75.91%, 53.27% and 38.96%, respectively.</p>2024-12-12T00:00:00+01:00Copyright (c) 2024 Ida Zahović, Jelena Dodić, Damjan Vučurović, Bojana Bajić, Siniša Dodić, Zorana Trivunovićhttps://analecta.hu/index.php/analecta/article/view/45827The Risks of AI in Agriculture2024-06-06T17:03:17+02:00György Hampelhampel@mk.u-szeged.huZoltán Fabulyafabulya@mk.u-szeged.hu<p class="MK06AbstractText"><span lang="EN-GB">Integration of artificial intelligence (AI) into agriculture has the potential to revolutionise agriculture, but it also presents challenges and risks that must be carefully managed. AI can improve planning, streamline work processes, and improve decision making in crop cultivation and animal husbandry, ultimately leading to higher returns for farmers. However, lack of training and high implementation costs can make it difficult for some farmers to adopt AI, creating a competitive disadvantage and concentrating agricultural resources. Additionally, AI may contribute to unemployment among those with lower skill levels and poses cybersecurity risks that need continuous monitoring. Legal concerns also arise with respect to data ownership and usage rights, with questions about who can access and utilise collected data. Farmers often have to rely on AI systems as "black boxes", with limited understanding of how they work. If these systems fail and cause damage, accountability becomes an important issue. It is crucial to assess the drawbacks and risks of AI implementation in agriculture and educate farmers about these risks to prevent significant damage. Managing these risks effectively and ensuring data accuracy and security are essential in the global adoption of AI in agriculture.</span></p>2024-12-17T00:00:00+01:00Copyright (c) 2024 György Hampel, Zoltán Fabulyahttps://analecta.hu/index.php/analecta/article/view/46034Contribution to the Petrographic Study of the Geological Formations of the Mbanga Sector and its Headwaters in the Tshela Territory (Central Kongo, DRC)2024-11-08T18:10:54+01:00Djonive Munenedjonive.munene@unikin.ac.cdRaphael Matamba Jibikilaraphael.matamba@unikin.ac.beJoel Lohad Etshekodi joellohadje@gmail.comRavely Lusakueno Nsietoravely.nsieto@unikin.ac.beHugues Kasongo Kanyindadjonive.munene@unikin.ac.cdEmmanuel Kalemba Ngungiemmanuelkn01@gmail.comAudrey Katakanga N’kembo katakangaaudrey@gmail.comRaphael Palata Kadjengdjonive.munene@unikin.ac.cdVanshok Ekoko Bolua Mpengedjonive.munene@unikin.ac.cdGertrude Mbumbu Luswamudjonive.munene@unikin.ac.cd<p>In order to fill the glaring gaps in the geological data for the Mbanga region and surrounding area, in the Province of Kongo-Central in DR Congo, geological investigations were carried out in the field over a three-week period. The results obtained, coupled with those from the laboratory, led to the identification of eight different lithofacies in the study area, namely: metaryolites, sericite schists and biotitose schists, all with grey to greenish grey facies. This work consists of a detailed petrographic study to identify the different facies of the West Congo Supergroup belonging to the Mayumbian Group and the Zadinian Group. The geology of the Mbanga sector and its surroundings is made up of metamorphic layers of volcanic and sedimentary origin. The various rock formations in our study area are grouped into two West Congo Supergroup groups; the metarhyolite formation belongs to the Tshela/Seke-Banza Group (Mayumbian) and the others belong to the Matadi Group (Zadinian).</p>2024-12-12T00:00:00+01:00Copyright (c) 2024 Djonive Munene, Raphael Matamba Jibikila, Joel Lohad Etshekodi , Ravely Lusakueno Nsieto, Hugues Kasongo Kanyinda, Emmanuel Kalemba Ngungi, Audrey Katakanga N’kembo , Raphael Palata Kadjeng, Vanshok Ekoko Bolua Mpenge, Gertrude Mbumbu Luswamu