3. International Conference on New Research and Development in Technical and Natural Science, ICNRDTNS Slovenia, 20. December 2022 The organizers of the 3. International Conference on New Research and Development in Technology and Natural Sciences ICNRDTNS, dear participants and guests, are grateful for your contributions at another traditional meeting of all those interested in the use of mathematics, physics, chemistry, biology, medicine, computer science, electrical engineering, mechanical engineering , construction and geotechnics and all related high technologies in the fields of engineering and science. Presentation be only online. Assist. Prof. Dr. Matej Babič, Ph.D. International Program Committee General Chair 2 Organized by Complex System Company s.p. Editor: Assist. Prof. Dr. Matej Babič Publisher: Complex System Company s.p., Podgradje Circulation: Elektronic edition Date: december, 2022 icnrdtns.net Kataložni zapis o publikaciji (CIP) pripravili v Narodni in univerzitetni knjižnici v Ljubljani COBISS.SI-ID 137890051 ISBN 978-961-07-1446-0 (PDF) 3 International Organizing Committee Assist. Prof. Dr. Matej Babič, President, Faculty of Information Studies in Novo Mesto, Slovenia Prof. Dr. Gyula Varga, University of Miskolc, Hungary Prof. Dr. Cristiano Fragassa, University of Bologna, Italy Prof. Dr. Dragan Marinković, TU Berlin, Germany Prof. Dr. Michele Calì, University of Catania, Italy International Scientific Committee Prof. Dr. Borislav Savkovic, University of Novi Sad, Serbia Prof. Dr. Branko Mativić, Vinča Institute, Beograd, Serbia Dr. Kumar Dookhitram, University of Technology, Mauritius Prof. Dr. Bojan Đurin, University of North, Varaždin, Croatia Prof. Dr. Maja Ruzic Baf, University Juraj Dobrila of Pula, Croatia Prof. Dr. Karolj Skala, Ruđer Bošković Institute, Zagreb, Croatia Prof. Dr. Daniel Ghiculescu, Polyethnic University of Bucharest, Romania Dr. George Seritan, Polytechnic University of Bucharest, Romania Prof. Dr. Grzegorz Lesiuk, Wrocław University, Poland Dr. Michał Jakubowicz, Poznan University of Technology Dr. Abdulhamit Subasi, University of Turku, Finland Dr. Emilio Ramírez Juidías, University of Sevillie, Spain Prof. Dr. Rita Ambu, University of Cagliari, Cagliari, Italy Dr. Mirosław Rucki, University of Technology and Humanities in Radom, Poland 4 Programm 5 Assessment of 3D digital models of Madygenerpeton pustulatum holotype Yaroslav Garashchenko1), Ilja Kogan2), Mirosław Rucki3)*, Edwin Gevorkian3) 1) National Technical University, Kharkiv Polytechnic Institute, Department of Integrated Technologies of Mechanical Engineering, Ukraine 2) TU Bergakademie Freiberg, Geological Institute, Germany 3) Faculty of Mechanical Engineering, Kazimierz Pulaski University of Technology and Humanities in Radom, Poland *Corresponding author: m.rucki@uthrad.pl The range of possibilities for investigating, visualizing and replicating unique fossils has greatly widened due to the development of digital methods of surface and tomographic 3D scanning, virtual representation and 3D printing over the past two decades. This opens up a nearly unlimited field of applications including the creation of photorealistic 3D models that can be used for teaching and virtual exhibits, remote collaboration on specimens, anatomical studies, digital restoration, functional modelling or fabrication of analogue copies. At the same time, digital methods of investigation and reproduction involve only little contact and are genuinely non-destructive, which means that the risk of damaging the precious specimens is reduced to unlikely accidents during transport and manipulation while digitizing them. Despite the increasing use of digital techniques, only few comparative studies have attempted to assess fidelity of digitized or printed models obtained by various approaches and devices. Surprisingly little has been done especially on comparing models derived from computed tomography, which is a method designed to represent volumes, with models produced using the more accessible surface-based digitization methods. To fill in this gap, we are performing comparative analyses of digital and printed models of a complex fossil specimen on the example of the holotype of Madygenerpeton pustulatum, a „reptiliomorph amphibian‟ from the mid-Triassic fossil locality Madygen in Kyrgyzstan, Central Asia. The Madygen Formation has yielded a wealth of diverse and well-preserved remains of aquatic and terrestrial plants, invertebrates, vertebrates and trace fossils, giving an unparalleled insight into a 237 million years old continental ecosystem of the Northern hemisphere. This record justifies Madygen‟s status as one of world‟s most significant fossil lagerstätten of the Mesozoic, making it the center of a potential UNESCO global geopark. A late-surviving member of the predominantly Permian Chroniosuchia, Madygenerpeton is known from fragments of the dorsal carapace belonging to at least three individuals and one detached and slightly deformed skull lacking the lower jaw, which constitutes the holotype of the taxon. Skull roofing bones are covered by minute tubercles, which make both mechanical preparation and traditional replication using casts especially delicate. Furthermore, structures from the underside of the specimen and parts of the dentition are still covered by sediment, which cannot be removed without exposing the fossil to a high risk of breakage. Computed microtomography (µCT) offers a solution to this challenge, giving the possibility to differentiate between bone and sediment manually or, when the density contrast is sufficient, even automatically. However, for the sake of comparative analysis, the whole-surface model obtained from µCT scanning is needed. It has been produced by a custom-built YXLON µCT scanner at the Museum für Naturkunde Berlin and compared with several surface models obtained from different 3D scanning devices. An outstanding feature of µCT scanning is its ability to build a 3D model of Madygenerpeton skull free of the sedimentary additions, unable to be removed mechanically. Obviously, such a small, irregular details revealed by tomography and seen in Figure 1a, couldn‟t be extracted undamaged from the fossil. On the other hand, the analysis of the distances between the scanned surfaces from different devices showed that the tomography (point #8) provided the most distanced model from the reference one obtained with AR Strato. 6 Fig. 1. Analysis of the µCT model: a) details of the skull hidden in sedimentary rock, b) distances between 3D surfaces obtained from different scanners (1 – AICON; 2 – AR Crysta; 3 – AR Strato; 4 – ARTEC; 5 – CREAFORM GoScan; 6 – CREAFORM HandyScan; 7 – EinScan Pro; 8 – Yxlon µCT) The distances from µCT model were the largest for each reference. Apart from that, the calculated volume of µCT model was the smallest, while its surface was one of the largest. Moreover, it had the largest number of polygons. This demonstrates that µCT model represents the Madygenerpeton skull in a much more detailed way. Comparative analysis of two models – one included the sedimentary rocks, and the other excluded them – enabled the assessment of the dimensions of the unwanted additions. Statistically, thickness of sediments ts can be described by maximal value { ts} max = 8.2 mm, statistical mean 𝑡 𝑠 = 0.69 mm, and square root deviation ts} = 1.18 mm. Since the models had different geometry and differed from one another in respect of the number of triangles, statistical parameters appeared to be different depending on which of the two models was tested, and which one was used as a reference. Table 1 shows the results of comparative analysis of two models in terms of distance between the respective triangles. Table 1. Results of initial statistical analysis of the distances between two 3D models Reference model Test model Distance statistics maximum average ∆𝑑 standard deviation positive negative all positive negative 𝜎 ∆𝑑 AR Strato YXLON µCT 2.000 -2.000 -0.0860 0.2664 -0.3006 0.5762 YXLON µCT AR Strato 1.9899 -1.9981 0.0210 0.0772 -0.0676 0.1191 Comparative analysis of the statistical parameters revealed that µCT model differed the most from all other ones, showing the largest ∆𝑑 and 𝜎 ∆𝑑 . It can be explained from the perspective of the radical differences between the scanning principles. The average distance, however, is below 0.12 mm with standard deviation below 0.6 mm. Since these values are close to the accuracy of 3D printing technologies, it is possible to use the MCT model for further additive manufacturing of the Madygenerpeton pustulatum skull. Acknowledgement: The paper was prepared thanks to Erasmus+ mobility. 7 Mechanical Performance of Structural Rebars subjected to several Mechanical tests Authors: Kayode Olaleye1, Zielonka Pawel1, Duda Szymon1, Cristine Caroline Campos Lopes2, Bruno Pedrosa3, Lesiuk Grzegorz1, Katarzyna Żołyńska1, Wojciech Błażejewski1 1 Wroclaw University of Science and Technology, Wroclaw, Poland 2 Federal University of Minas Gerais, Belo Horizonte, Brazil 3 University of Coimbra, Coimbra, Portugal Abstract Due to their numerous benefits, such as their high tensile and fatigue strengths, high corrosion resistance, light weight, ease of handling, thermal and electrical insulating properties, and insensitivity to magnetic fields, fiber-reinforced polymer (FRP) bars have been used more and more in the field of structural engineering [1,2,3]. FRP reinforcing bars, on the other hand, have several significant drawbacks, such as creep failure, limited commercial availability, high production costs, anisotropic material properties, limited ductility, low elastic modulus, intolerance to bending (for use as stirrups), and low transverse and lateral strength values in comparison to longitudinal tensile strength [4,5,6]. Another restriction on the usage of FRP bars for structural purposes is the absence or constrained scope of the restrictions in the existing FRP reinforced concrete (RC) norms and regulations. Researchers are working to come up with solutions to the problems associated with the structural usage of FRP bars and are pushing its use as concrete reinforcement due to the multiple positive effects of FRP bars on the service life of structures, the national economy, and the environment. The mutual adhesion, surface friction, and shear interlock bond mechanisms of FRP bars in concrete are comparable to those of steel bars. However, compared to steel bars, FRP bars have entirely different mechanical properties [7,8]. As a result, the evaluation of the flexural behavior of FRP RC members cannot be based on the flexural behavior of RC members with steel reinforcement. Due to the above pros and cons, this research will investigate the mechanical characteristic our homemade composite rebars and they could be utilized as reinforcing phase in concrete and soil. Acknowledgements: The research was financed by the National Center for Research and Development of Poland (NCBiR) grant number LIDER/40/0219/L-10/18/NCBR/2019. References 1. Tomasz, M., Szymon, D., Bartosz, B., Joanna, W., Paweł, Z., & Grzegorz, L. (2022). Flexural and compressive residual strength of composite bars subjected to harsh environments. Engineering Failure Analysis, 133, 105958. 2. Barcikowski, M., Lesiuk, G., Czechowski, K., & Duda, S. (2021). Static and flexural fatigue behavior of GFRP pultruded rebars. Materials, 14(2), 297. 3. Nanni, A., De Luca, A., & Zadeh, H. (2014). Reinforced concrete with FRP bars. Mechanics and design, international standard book no-13, 978-0. 4. GangaRao, H. V., Taly, N., & Vijay, P. V. (2006). Reinforced concrete design with FRP composites. CRC press. 5. ACI Committee. (2015). Guide for the design and construction of structural concrete reinforced with fiber-reinforced polymer (FRP) bars (ACI 440. 1R-15). Farmington Hills, Michigan: American Concrete Institute. 6. Mufti, A. A., & Neale, K. W. (2007). State-of-the-art of FRP and SHM applications in bridge structures in Canada. Proc., Composites & Polycon 2007. 7. FIB (Fédération Internationale du Béton). (2000). Bond of reinforcement in concrete. FIB Bulletin 10. 8. Bond, A. C. I. (2003). Development of Straight Reinforcing Bars in Tension. ACI 408R-03. 8 Analysis of the Deceleration Methods of Fatigue Crack Growth Rates under Mode I Loading Type in Pearlitic Rail Steel Authors: Szymon Dziuba1, Kayode Olaleye1, Bruno Pedrosa3, Lesiuk Grzegorz1, Jose A.F.O. Correia3, Abilio M.P. De Jesus3, H. Nykyforchyn4, Olha Zvirko4 1 Wroclaw University of Science and Technology, Wroclaw, Poland 2 University of Coimbra, Coimbra, Portugal 3 University of Porto, Porto, Portugal 4 Karpenko Physico-Mechanical Institute of the NAS, Lviv, Ukraine The main goal of this paper is to compare different (physically) approaches in crack growth rate deceleration in pearlitic steel commonly used for rail manufacturing [1]. The paper presents a comparison of fatigue crack growth rates from raw rail steel with steel reinforced with composite patches, the implementation of the stop-hole technique, and the application of an “anti-crack growth fluid”. All these methods are widely used as deceleration methods of fatigue crack growth. Carbon fiber-reinforced polymer (CFRP) patches are still of particular interest in various applications in civil engineering [2-5]. The fatigue crack growth process is strongly associated with the crack driving force and its local condition. In [6-8], authors explained crack growth rate decreasing with an effective stress intensity factor (crack closure concept [9]) based on ∆Keff concept. This assumption allows us to explain, simply using a closure parameter, the role of crack closure in analytical formulas. Recently, the concept of crack closure triggering due to the application of fluid [10] into the crack was successfully validated for low-carbon steel [6]. The material from which all the samples presented in the study were prepared was taken from the rail that had previously been withdrawn from use, and its profile conformed to UIC60 [11]. In addition to the samples made from the base material, samples were also reinforced with a carbon fiber material. CFRP polymer is an extremely strong and light fiber-reinforced plastic. The tests were carried out on five types of samples, which are listed below:  raw steel material,  raw steel material with stop-hole technique,  raw steel material with a wide CFRP patch (full face),  raw steel material with a narrow CFRP patch (strip),  raw steel material with the “anti-crack growth fluid” [10]. For the experimental campaign, compact tension (CT) specimens were prepared in accordance with ASTM E647 [12] standard. All specimens were tested using constant load amplitude methods with a maximum loading Fmax = 8 kN and stress ratio R = σ /σ min max = 0.1 to analyse the efficiency of different strategies of fatigue crack growth rate deceleration. 9 Figure 1. Fatigue crack growth curves for all tested specimens Results had shown that the fastes fatigue crack grow is obtained with the raw material and the slowest is obtained when the “anti-crack growth fluid” is applied. Additionally, the study on fatigue fracture surfaces using light and scanning electron (SEM) microscopy to analyse the crack growth mechanism was carried out. As a result of fluid activity, fatigue crack closure occurred leading to a significant decrease in the crack driving force which resulted in lower fatigue crack growth. Figure 1 presents fatigue lifetime curves for all specimens tested in the same loading conditions. As it is noticeable, comparable effect is obtained for the designed stop hole technique and composite CFRP patches. Similar frack growth was found using one strip or full patch of CFRP which is in accordance with the results presented in Lesiuk et al. [13]. Authors implemented a numerical analysis focus on the CFRP effect on the stress intensity factor showing the same reduction level when using a strip or a full patch CFRP. For direct comparison of the fluid activation effect on the crack deceleration for metallic specimens (without CFRP) kinetic fatigue fracture diagram (KFFD) was constructed, as shown in Figure 2. Figure 2. Comparison of fatigue crack growth rates for pure metallic specimens (stop hole, CT specimen with injected fluid). Keywords: pearlitic steel; CFRP patches; crack retardation; fatigue crack growth; failure analysis 10 References 1. Lesiuk, G.; Smolnicki, M.; Mech, R.; Ziety, A.; Fragassa, C. Analysis of fatigue crack growth under mixed mode (I+ II) loading conditions in rail steel using CTS specimen. Eng. Fail. Anal. 2020, 109, 104354. 2. Lesiuk, G.; Katkowski, M.; Correia, J.; de Jesus, A.M.; Blazejewski, W. Fatigue crack growth rate in CFRP reinforced constructional old steel. Int. J. Struct. Integr. 2018, 9, 381–395. 3. Yu, Q.Q.; Wu, Y.F. Fatigue retrofitting of cracked steel beams with CFRP laminates. Compos. Struct. 2018, 192, 232–244. 4. Emdad, R.; Al-Mahaidi, R. Effect of prestressed CFRP patches on crack growth of centre-notched steel plates. Compos. Struct. 2015, 123, 109–122. 5. Hosseini, A.; Ghafoori, E.; Motavalli, M.; Nussbaumer, A.; Zhao, X.L. Mode I fatigue crack arrest in tensile steel members using prestressed CFRP plates. Compos. Struct. 2017, 178, 119–134. 6. Khaburskyi, Y.; Slobodyan, Z.; Hredil, M.; Nykyforchyn, H. Effective method for fatigue crack arrest in structural steels based on artificial creation of crack closure effect. Int. J. Fatigue 2019, 127, 217–221. 7. Borrego, L.P.; Ferreira, J.M.; Da Cruz, J.P.; Costa, J.M. Evaluation of overload effects on fatigue crack growth and closure. Eng. Fract. Mech. 2003, 70, 1379–1397. Metals 2021, 11, 584 13 of 13 8. Maierhofer, J.; Simunek, D.; Gänser, H.P.; Pippan, R. Oxide induced crack closure in the near threshold regime: The effect of oxide debris release. Int. J. Fatigue 2018, 117, 21–26. 9. Elber, W. Fatigue crack closure under cyclic tension. Eng. Fract. Mech. 1970, 2, 37–45 10. Nykyforchyn, H.; Pustovyi, V.; Slobodyan, Z.; Khaburskyi, Y.; Barna, R.; Zvirko, O.; Kret, N. The Method of Fatigue Crack Growth Arrest. Patent of Ukraine No.128514, 15 September 2018. (In Ukrainian). 11. Lesiuk, G.; Smolnicki, M.; Mech, R.; Ziety, A.; Fragassa, C. Analysis of fatigue crack growth under mixed mode (I+ II) loading conditions in rail steel using CTS specimen. Eng. Fail. Anal. 2020, 109, 104354. 12. Lesiuk, G.; Pedrosa, B.A.; Ziety, A.; Błazejewski, W.; Correia, J.A.; De Jesus, A.M.; Fragassa, C. Minimal invasive diagnostic ˙ capabilities and effectiveness of CFRP-Patches repairs in long-term operated metals. Metals 2020, 10, 984. 13. Lesiuk, G.; Pedrosa, B.A.; Ziety, A.; Błazejewski, W.; Correia, J.A.; De Jesus, A.M.; Fragassa, C. Minimal invasive diagnostic ˙ capabilities and effectiveness of CFRP-Patches repairs in long-term operated metals. Metals 2020, 10, 984. 11 A graphical approach based on slipping to evaluate necking phenomena during tensile stress Michele Calì, Mario Grasso Electric, Electronics and Computer Engineering Department, University of Catania, Catania, Italy, michele.cali@unict.it What are the characteristics in the tensile test that determine the shrinkage and collapse in the centerline? The experimental results reported in the book 'Construction Science, Vol. 2, p. 370, Fig. 264', by S. Timoshenko', show that for a tensile rod, a passing limiting force can be evaluated (Figs. 1/a, 1/b) between: negligible elongations of the specimen, at the beginning highly sensitive elongations, and that by analogy to the instability limiting force for compressive load (peak load), is referred to here as 'F lim traction limit force'. d S= scorrimento F= forza applicata Some cases related to different patterns of applied forces are reported. With reference to Fig. 2, we have: F = Applied impulsive force; ta = to/4 = Duration of application force; to = Rod time length. Fig. 2 shows: a) the following frames highlighting the position of the pressure waves oscillating back and forth along the rod; (b) how the initial rod with free ends and on which the 'F' forces act, is equivalent to a rod of length 'to/2' and embedded in the corresponding centreline; c) the pressure in some sections over time. Pressure that varies cyclically with period T = 2To. 12 In such circumstances, on each section of the rod there is a tensile stress σ1 constant (Fig. 3). From this configuration, apply a further impulsive action ∆F2 to the rod. in traction and such that it is ∆σ2=∆F2A<(∆σ1=∆F1A) or from eq. (3) σ1+∆σ2=σlim-∆σ1+∆σ2<σlim (4) which is: F1+2 ∆F2>Flim or σ1+2 ∆σ2>σlim (5) Considering the previous analysis Fig. 2/c, in which the tensile impulse at both ends generates a tensile stress trend such that on average in the centerline it doubles compared to the ends Fig. 4, we have: 13 Fig. 4 Average tensile stress diagram along the pulse rod ∆F1. Summing the effects due to the initial force F1 and those due to ∆F2, that is, adding up the graphs Fig. 3 + Fig. 4, we get Fig5 Fig. 4 Average tensile stress diagram along the pulse rod ∆F1. Summing the effects due to the initial force F1 and those due to ∆F2, that is, adding up the graphs Fig. 3 + Fig. 4, we get Fig5 Fig. 5 Total tension tensile diagram rod. By choosing appropriately the values of F1, ∆F1, ∆F2, we can make sure that it results: σ1+2 ∆σ2>σlim>σ1+∆σ2 (6) Therefore, it turns out that the centerline zone exceeds the tension limit tension of tensile instability and therefore zone of ignition of restriction.σlim 14 MAPPING OF TOURIST DIVING ATTRACTIONS IN THE ADRIATIC SEA Vlatka Davidović1, Viktor Medakov2, Matej Pogarčić3 1Polytechnic of Rijeka, Croatia, vlatka.davidovic@veleri.hr 2University Juraj Dobrila of Pula, Croatia, viktor.medakov@gmail.com 3Vodogradnja d.o.o, Rijeka, Croatia, matej.pogarcic@gmail.com ABSTRACT Applied geography in the form of maps and spatial data has served discovery, planning, collaboration and conflict through many years of mankind. Like many other aspects of life, in the last five decades the way we collect and use spatial information has been deeply influenced by modern technology, and GIS software and hardware are the results of these advances. GIS becomes an increasingly important tool in environmental management, marketing, tourism and many other components of our daily lives. The aim of this paper is to show the possibilities that this technology provides us theoretically and through an independent project - mapping and cadaster of sunken ships and other attractions in the Adriatic Sea. Keywords: GIS, mapping, attractions, Adriatic Sea 1. INTRODUCTION The term GIS has been attempted to be defined many times and for this reason there is no single concluding definition that we can use. The diversity of these definitions is explained by Pickles [1] by saying that the definition of a GIS system varies depending on who defines GIS and also states that the definition of a GIS is very likely to change with future developments in technology [2]. In general, the definitions of GIS systems cover three main components: GIS is a computer system, it uses spatial data and it performs various analyses over these spatial data. It can be said that GIS is a tool for creating and using spatial information with added value. GIS can exist as a generic framework if the specific application is not considered. In that case, any meaningful process/system that requires spatial data and/or its analysis can be applied. As each information system is the basis for the processes of management and decision-making, GIS expands these properties and gives them a new appearance and a new value. Of course, data and information in GIS are of great importance for specific users, because only with the existence of users any G(IS) becomes a reality with concrete goals and a concrete purpose. 2. DATA IN GIS Data in GIS systems represent a simplified view of the world and simplified view of physical entities in the world. They include information on the spatial position and scope of the object and information on its non-spatial properties. Spatial data defines the location and shape of each spatial object or phenomenon in two or three-dimensional space [3]. Attribute data is used to record non-spatial characteristics of entities. When it comes to geographic information systems, the purpose of the spatial data model is to enable the display and management of spatially referenced information [3]. Spatial data structures provide the necessary information to the computer so that it ca n reconstruct the spatial data model into a digital form. Two data models were used in geographic information systems: raster and vector. Raster is one of the oldest and most widely used models. It is most commonly used in writing, analyzing and visualizing data of a continuous nature such as elevations, temperatures or for example electromagnetic radiation [4]. A vector data model uses a set of coordinates and associated attribute data to specify discrete objects. Coordinate groups determine the location and boundaries of 15 discrete objects and, together with attribute data, create vector objects that we use to display real entities [3]. Triangulated irregular network (TIN) is a data model that is most often used to display terrain height, i.e. it has x, y and z spatial values. TIN, as its name suggests, creates a network of irregular triangles. This model uses indexing shapes to connect adjacent points. Each edge of the triangle is connected to two points which are then connect to other edges. These joins continue recursively until the entire network has been created [3]. 3. COLLECTION AND VISUALIZATION OF SPATIAL DATA Collecting spatial data is one of the most time-consuming and financially expensive GIS tasks. There are various sources of geographic data and also a lot of methods by which they can be entered into GIS. The two main methods of data collection are data retrieval and data transfer. It is important to understand the difference between primary (direct measurements) and secondary (taking data from other sources) data retrieval, which also applies to vector and raster data [5] Primary retrieval of geographic data includes direct measurements of objects. Digital data obtained by measurement can be entered directly into the GIS database or stored in a temporary file before entering. The most common method for raster data retrieval is remote sensing. The term remote sensing encompasses the areas of satellite imaging and aero photography. In vector data retrieval, there are two main branches that are divided into field measurements and GPS. Secondary retrieval of geographic data is the process of creating raster and vector files and databases from existing maps, photographs and other documents [5]. Visualization of spatial data is extremely important in understanding their locations, shapes and surfaces and comes from the need to better understand the nature of these data. Visualization can be done through various software systems, programming languages, their libraries and tools. Spatial data visualization uses and combines different layers obtained using different libraries and plugins. 4. PROJECT OF MAPPING TOURIST DIVING ATTRACTIONS IN THE ADRIATIC SEA The first step in mapping tourist diving attractions in the Adriatic Sea is data collection. These data are structured and prepared for input into GIS. Then follows the visualization of the data, and after the visualization, cartographic expressions, i.e. the final product, are created. 4.1. DATA COLLECTION The project began with research and data collection for 4 categories of tourist diving attractions in the Adriatic, namely: shipwrecks, aircraft wrecks, reefs and caves. Data was recorded and processed in Microsoft Excel 2010 version 14.0 as part of the Microsof Office Professional Plus 2010 package. To collect data on shipwrecks, a book entitled Wrecks of modern ships in the Adriatic Sea ( Adriatic Wrecks) was used as the starting point of the research. The author of the book is Danijel Frka, B.Sc., independent underwater researcher, photographer and historian [6]. Additional literature was also used to collect data on shipwrecks and other categories. Book The underwater story of Istria has contributed in the research of the area of Istria [7]. The book Austro-Hungarian destroyers was used to find information on Austro-Hungarian destroyers [8]. The literature entitled Crash of an Allied Bristol Beaufighter (NT997) near Senj in October 1944 was also used to check and find missing information [9]. Of course, along with books and professional articles, some websites are used, such as:  https://h2oglobe.com/  http://www.ronjenjehrvatska.com/hr/home  https://www.diving-shark.hr/en/  https://krnica.com/index.php 16 Shipwreck attributes A total of 42 shipwrecks were recorded, all from the territory of the Republic of Croatia, and they were described with 17 attributes. The first and main attribute is the ID that is the primary key and identifier in the database. This is followed by attributes indicating the name of the ship and the minimum and maximum depth expressed in the meters on which the wreck is located. The most important attributes, those without which it is not possible to map the locations of wrecks, are latitude and longitude that are expressed in decimal values. These attributes were the most demanding to find because a lot of literature omits the location of the shipwreck. To find the location of each wreck, more detailed and deeper research was needed, and specifically from different sources (Figures 1 and 2). Information about the dates when the ship sank and when it was built and/or launched was also saved. Information about the type of ship was also recorded, for example whether it was a steamship or a motor propulsion, whether it was a cargo or a war cruiser, and of course, an attribute was added to indicate whether the ship was civilian or belonged to the navy. Very interesting attributes are also the flag under which the ship sailed and why it sank. Later it will be shown that the most ships sank from hitting an underwater mine. The literature used for the research provided information about the length and width of the wreck. Data were also added on the area of sinking, which represents the region or the nearest settlement or island where the ship sank, and generally in which part of the Adriatic the ship sank (north, middle or south). At the very end, we can read what is the minimum diving category required to access the wreck (R1, R2 and R3) where R1 indicates the initial and R3 the most experienced category and the visibility score of the wreck of 1-5, where 1 is the worst and 5 is excellent visibility. Of course, some fields in the table will be remain empty because the data for that attribute could not be found or was different from various sources. Figure 1 Shipwreck Dataset Attributes Part 1 17 Figure 2 Shipwreck Dataset Attributes Part 2 Figure 3 The wreck of the steamship Vis, which sank in 1946 near Cape Mašnjak at the entrance to Plomin Bay [6] Attributes of aircraft wreckages In the research is shown that currently only 4 aircraft wreckage has been discovered in the Adriatic Sea, all during the Second World War between 1941 and 1944. They are described with 15 attributes, most of which are the same as for the previous dataset on shipwrecks with minor differences. Differences are categories of wrecks (Figures 4 and 5). Some attributes from the previous dataset were thrown out, such as visibility and the date when the aircraft was built. These data were mostly not available or were contradictory. 18 Figure 4 Attributes of the aircraft wreckage dataset Part 1 Figure 5 Attributes of the aircraft wreckage dataset Part 2 Figure 6 The B-17 flying fortress near Vis lies at a depth of 72 meters [6] Attributes of the reefs Data were collected on 14 reefs across Croatia that can be visited and described with 12 attributes. Compared to earlier datasets, there were two new attributes added, which did not appear in previous datasets. The attribute of flora and fauna that categorizes the flora and fauna of the reef into three classes: poor, rich and exist. Current attribute is described with current strength in the reef area: weak, medium and strong. The current attribute directly affects the attribute of the minimum diving category. It is not recommended for beginner diver category R1 to access the location with strong current. 19 Attributes of the caves It is important to emphasize that the caves that can be visited are also located in the same locations as some reefs in the previous dataset. In this data set, only caves that are not part any of the reefs are recorded. A total of 37 caves were recorded in this project and it can be said that the southern Adriatic is the richest in this category. The attributes of this data set are exactly the same as the set for reefs. After collecting and entering the data into the tables, it is necessary to convert the data into a CSV ( Comma separated values) file so that the data from the table can be entered into the QGIS project. A single .csv file is imported into the project as a layer. 4.2 CREATING A MAP OF THE ADRIATIC SEA For the purpose of this project, our own map of the Adriatic Sea was created from a set of 20 Landsat 8 satellite images collected from the website: https://earthexplorer.usgs.gov/ The satellite images were saved in .TIFF format and transferred as such to the QGIS program. They are grouped into one raster layer and form a map that can be seen in Figure 7. In this project is used WGS84 ( World geodetic system) with identifier EPSG:4326 was used. WGS84 is the standard in GPS and Google Maps service works on this coordinate reference system. It was required because each exact location was obtained and verified from Google Maps service. Figure 7 Set of satellite images from the territory of the Republic of Croatia and Italy 20 4.3 DATA VISUALIZATION In order to make the displayed data more understandable to the user, a visible name of the wreck or other feature is added above the symbol, In the project, the table with attributes was additionally modified. A new image attribute was added, which contains the path to the directory where the image is located. After adding a new field to the table, for each feature it was necessary to load an image from the directory in which it is located. The appearance of visualized data can be seen in Figure 8, which shows the southern Adriatic. Figure 8 Mapped data of the southern Adriatic islands The map is exported through the qgis2web plugin. Map can be displayed in a web browser so that it is not necessary to have QGIS software installed to view the map (Figure 9). Figure 9 Image display as part of attributes in a Web browser 21 It is possible to additionally modify the map in such a way as to set the scale, the rotation of the map and the size of the space on which the map is located, as well as the background, frame and grid of the map. By itself, this map doesn't mean much without some context, so it's necessary to add a map legend. The map legend can be further edited by changing the font, spacing and style of the text, and other additional settings. In addition to the legend, a smaller map was added, showing on a larger scale which area it is about. By adding a graphic scale, it is presented the ratio between the distance of the features on the map and in the real world. In the settings, the unit of measurement, segments, width, height and line style can be adjusted if necessary. Figure 10 Adding a legend and a smaller map After completing the creation of the map, it is necessary to export it in the desired format. Some of the formats are JPG, JPEG, TIFF, SVG, PDF. It is also possible to export the data to a table or CSV file in the selected desired resolution, height and width of the page. 5. CONCLUSION The paper is guided by the idea that such a project can be made as a separate system with the possibility of inclusion in wider and more robust GIS systems. The advantages and benefits of its use are multiple. It can be included in the tourist offer, for example, organized diving activities. Such objects have a significant attraction value. Then, most of these objects have historical significance because they are tied to a particular historical event. And even when the object cannot be tied exactly to a certain date, the possibility of archaeological treatment remains. From the aspect of geodesy as the G part of GIS, such objects are of interest because their location helps to monitor and maintain both objects and locations. It is clear that the sea affects both the location and the integrity of the object. This is intended to emphasize the dynamism of the system in terms of the possibility of intentional or unintentional dislocations of the observed objects. From the aspect of informatics as well as part of GIS, such projects are grateful topics when creating a database, especially in an object-oriented software environment. Vector data is easily arranged as a relational database of Cartesian coordinates and associated attributes, while rasterization can be performed by storing other than primitive data and object-type data such as digitized images. The authors consider the project open for refinement of each targeted and useful type and remains open for possible useful connection or inclusion in wider projects. In this sense, the authors also remain open to all forms of cooperation. 22 REFERENCES [1] Pickles, J. (1995.) Representations in an Electronic Age: Geography, GIS, and Democracy, New York: The Guilford Press [2] Heywood, I., Cornelius, S. and Carver, S. (2006.) An introduction to geographical information systems, 3rd Edition, Harlow: Pearson Education Limited [3] Bolstad, P. (2016.) GIS fundamentals: A first text on geographic information systems. Eider (PressMinnesota). [4] Pingel, T. (2018.) The raster data model. Geographic Information Science & Technology Body of Knowledge. [5] Longley, P.A., Goodchild, M.F., Maguire, D.J. and Rhind, D.W. (2005.) Geographic information systems and science. John Wiley & Sons. [6] Frka, D. (2012.) Olupine (nalazi) novovjekih brodova u Jadranskom podmorju, IV. međunarodna konferencija o Industrijskoj baštini, Zbornik radova, Rijeka, Pro Torpedo Rijeka, 2012., http://protorpedo-rijeka.hr/wp/wp-content/uploads/2018/04/62.pdf [7] Iveša, N., Vojnić, N., Komšo, D. (2015.) Istarska podvodna priča - karta podvodnih arheoloških lokaliteta, (Underwater Story of Istria - map of the underwater archaeological sites), 2015. [8] Veperdi A., Az Osztrák-Magyar Flotta Tengeralattjárói (Austro-Hungarian Destroyers), https://adoc.pub/az-osztrak-magyar-flotta-tengeralattjaroi-sszeallitotta-vepe.html [9] Domines Peter, P. (2019.) Pad savezničkog zrakoplova Bristol Beaufightera (nt 997) kod Senja u listopadu 1944. godine, Senjski zbornik, 46(1), str. 297-324. https://doi.org/10.31953/sz.46.1.11 Web sources: H2O Globe [Online] https://h2oglobe.com/ [Accesed: 31.05.2022.] Ronjenje u Hrvatskoj [Online] http://www.ronjenjehrvatska.com/hr/home [Accesed: 31.05.2022.] Diving Shark ronilački klub [Online] https://www.diving-shark.hr/en/ [Accesed: 31.05.2022.] Krnica ronilački klub [Online] https://krnica.com/index.php [Accesed: 31.05.2022.] 23 Parking system simulation model using CNN Matej Babič Faculty of Information Studies, Novo mesto, Slovenia Abstract The article shows a possibility of applying graph theory to solving problems in the field of wireless sensor networks. The modernization of the infocommunication infrastructure of the regional data transmission network is presented to increase the maximum transmission speed of existing transport routes, ensure quality of service and reliability. We research one of the fundamental issues in such networks in which we would like to determine whether an area of interest is sufficiently covered by a given set of sensors. The dynamics of car parking is modelled with cellular neural networks that predict the occupancy of a parking lot regards on weather conditional. 1. Introduction One of the areas of development of the Internet of Things (IoT) is the construction of all-pervasive sensor networks, based on self-organizing wireless networks. WiFi is the industrial name of the technology of wireless data exchange, which belongs to the group of standards for the organization of wireless networks IEEE 802.11. Wireless, all-penetrating sensor networks (BSNs) are self-organizing networks consisting of multiple wireless sensor units distributed in space and designed to monitor and control the characteristics of the environment or objects located in it. The space that is covered by the sensor network is called the sensory field. Wireless sensor nodes are miniaturized devices with limited resources: battery charge, memory capacity, computational capabilities, etc. In wireless communication we have inexpensive wireless nodes capable of sensing, storing, processing, and communicating data. So they are becoming increasingly common and readily available. However, combining a large number of these elements into the network due to the effect of the roving intelligence provides an opportunity to get a real picture of the events and processes occurring within the framework of a sensory field. The graph theory finds applications, for example, in geoinformation systems. Existing or newly designed houses, structures, quarters, etc. are considered as peaks, and the connecting roads, engineering networks, transmission lines, etc., are like ribs. The application of various calculations made on such a graph allows, for example, to find the shortest bypass or the nearest grocery store, to plan the optimal route. The theory of graphs contains a large number of unresolved problems and not yet proven hypotheses. Know the content of the discipline "Graph Theory" and have a fairly complete idea of its possibilities in other sections of mathematics and in applications; have an idea of the structures of graph theory and the basic combinatorial methods of proof and be able to apply these methods, including in wireless networks. When graphs are depicted in the drawings, the following notation is most often used: the vertices of the graph are represented by dots or, when the vertex's meaning is specified, rectangles, ovals, etc., where the meaning of the vertex (graphs of flowcharts of algorithms) is revealed inside the figure. Cellular automata provide useful models for many studies in natural and computational sciences and combinatorial mathematics; in particular, they represent a natural way of studying the evolution of large physical systems. Cellular automata also form a common parallel computing paradigm, just as Turing machines do for sequential computing . The popularity of cellular automata is based on their comparative simplicity combined 24 with great potential for modeling a set of interconnected homogeneous objects. Each cell represent a finite state machine, whose state is determined by the states of neighboring cells and, possibly, by its own. Changes in the values of all cells occur simultaneously after calculating the new state of each lattice cell. When a lattice is homogeneous, all the cells have the same rule. However, many dynamical systems have continuous cell states and simply cannot use binary values of states. In such cases an extension of cellular automata can be used, cellular neural networks (CNN). In this article, we use cellular neural networks to model the dynamics of a parking lot. 2. Data preparation In the city Novo mesto, Slovenia, it is parking system with 38 park places. One parking place is reserved for the disabled (yellow circle in Fig. 1) and two places for gas auto. Fig. 5 represent geometry of parking system in the city Novo mesto, Slovenia. Each parking place have magnetic sensor. So, we used data from magnetic sensors. We calculating average degree of occupancy of each of 38 park places for 30 days. Then, we transform this data to matrix with different colors Fig. 2. Table 1 represent weather data for 30 days. Figure 2: The occupancy of the parking lot and its prediction by CNN, taking also the weather into consideration 25 3. Results and discussion There are P = 38 parking spaces in the parking lot. The data is available for D = 30 days. For each day, only data of the average occupancy (in percent) for each parking space is given. Therefore, a proper cellular automaton (CA) cannot be used, as it operates above a finite number of states; typically binary states (0 and 1, i.e. unoccupied and occupied). Therefore, s cellular neural network (CNN) is applied here, which, based on the average occupancy of the parking space or cell and the average occupancy of adjacent cells, attempts to predict the average occupancy of the parking space for the next day, as shown in Figure 3. When the rule is the same for all cells, we speak of a homogeneous cellular automaton or homogeneous cellular neural network. 26 In our case, the mean squared error (MSE) is 0.02625. The RMSE (root MSE) is 0.16, i.e. a 16% error in the occupancy prediction. In CNN training and prediction testing, 10-fold cross-validation was used, meaning that the data set was divided into 10 parts; each time, 90% of the data was used to train the CNN model and 10% (one of 10 subsets) was used for testing. In addition, 10 different experiments with 10-fold cross-validation were done for each model, in order to reduce the effects of random initial weights and of the training procedure. All the models had one output neuron, but differed in the number of hidden layers and hidden neurons. For example, 10-5-1 means 10 neurons in the first hidden layer, 5 in the second, and one in the output layer. 27 Three different adjacencies are taken: 0, 1 and 2. Adjacency (radius) 2 means that in addition to a cell, we also consider two neighbors on each side. In such a case, two edge cells are not predicted. The spaces in the parking lot were divided into two groups: those that are closer to the entrance / exit of the parking lot, and the others. The two groups are differentiated using an additional input (0 or 1) that can influence the network to implicitly build at least a partially different model. It was found that this helps a little. Another factor that helped in the prediction was the weather data: average dayly values of temperature, wind speed, relative humidity, dew point, air pressure, and weather (qualitatively). Therefore, the actual CNN model included also these additional data, so the CNN function was extended as 28 29 The results show that it is possible to get much better prediction than the naive one (16%): the best MSE was 0.0019, which yields RMSE of 0.0436, that is below 5%. Acknowledgement The investment is co-financed by the Republic of Slovenia and the European Union from the European Regional Development Fund and supported by the Slovenian Research Agency (ARRS). References [1] Zhou, Honbo. The Internet of Things in the Cloud: A Middleware Perspective. Boca Raton: CRC Press, Taylor & Francis Group, 2013. [2] Golbon-Haghighi, M.H. (2016). Beamforming in Wireless Networks (PDF). InTech Open. pp. 163–199. doi : 10.5772/66.399 . ISBN 9781466557529 . 30 PPT bicycle rental in the GoNM system using Descriptive statistics Matej Babič Faculty of Information Studies, Novo mesto, Slovenia Abstract This study proposes a descriptive statistics for PPT bicycle rental in the GoNM system in the town of Novo mesto, Slovenia. Public passenger transport (PPT) is important for every municipality, as the current transport system faces well-known problems such as congestion, environmental impact, lack of parking areas, increased safety risks and high energy consumption. Urban transport is crucial for the functionality of any city. High-quality and usable urban transport not only affects the functionality of the city as an economic and social center, but also reduces the number of passenger cars on the streets. The wider Novo mesto region, with about 30,000 inhabitants, is an important industrial center and is heavily dependent on urban traffic. Unfortunately, the urban traffic of Novo mesto still has a relatively weak influence on the transport connectivity of the wider area. The aim of the research is to analyze and model bicycle rentals. Descriptive statistics for PPT bicycle rental in the GoNM system in the town of Novo mesto, Slovenia are used to predict bicycle traffic over 30 weeks. Our approach will also be useful for other Slovenian and foreign cities with similar needs. Data preparation Bicycle data The bicycle rental data was obtained for 14 stations for 35 weeks between 25.3.2019 and 25.11.2019 from the municipality of Novo mesto, Slovenia. The Microsoft Excel software is used to analyze the data, by using the pivot tables. Table 1 presents the numbers of bike rentals for 14 stations for the 13th week. Table 2 presents number of bike rentals for all 35 weeks. In Table 2 the first column present number of week. Second column present number of rent a bike. S 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 3 4 3 0 3 2 0 1 2 1 2 5 0 3 2 3 1 2 8 2 2 0 5 4 0 0 1 1 1 3 4 1 4 0 3 1 7 2 0 0 1 3 0 0 4 3 6 1 5 3 0 2 1 3 1 0 2 2 4 5 1 3 7 1 13 13 0 3 1 1 1 11 0 1 6 1 2 2 0 14 7 3 2 3 0 1 5 1 2 7 0 0 6 3 1 3 4 0 0 0 1 0 0 0 8 5 2 1 4 2 0 0 8 3 1 0 3 5 3 9 1 1 0 5 0 1 1 3 7 1 0 2 0 3 10 1 1 0 1 2 1 0 0 1 2 0 0 0 0 11 2 0 1 0 0 2 0 0 1 0 26 0 1 0 12 10 2 4 1 10 2 0 1 3 1 0 11 0 0 13 0 1 1 1 0 2 0 6 0 0 0 0 5 4 14 6 0 0 0 2 3 3 1 3 0 0 1 5 4 Table 2: Numbers of bike rentals for 14 stations for the 13th week 31 # week 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 # rent a bike 18 13 88 142 193 27 106 78 252 190 353 413 432 367 361 291 301 241 # week 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 # rent a bike 204 238 189 267 249 256 256 226 221 293 280 184 275 86 58 63 31 Table 2: Number of rent a bike for 35 weeks Weather data The weather data were obtained, such as temperature (T), rainfall (R), wind speed (W), and relative humidity (H), from Weather Society Zeus, Slovenia, for each day. The averages of all data were calculated for 35 weeks. Table 3 shows the weather data. The first column (n) contains the number of the week, the second column average temperature [C], the third column average rainfall [mm], the fourth column average wind speed [m/s] and the fifth column average relative humidity [%]. n T R W H 1 11.3 0.0 4.6 55.3 2 10.2 0.1 8.3 63.3 3 12.3 1.1 5.5 72.8 4 9.3 3.7 4.7 86.2 5 14.0 0.0 6.1 55.9 6 15.9 2.1 6.3 69.6 7 13.1 1.6 4.7 73.7 8 13.2 0.6 4.1 71.9 9 10.8 6.7 4.7 83.8 10 18.4 0.0 3.9 67.9 11 16.9 8.3 1.9 82.3 12 24.4 0.0 3.9 60.5 13 26.8 0.0 3.7 61.4 14 23.0 3.5 3.2 76.9 15 26.6 0.1 4.3 60.7 16 25.7 2.1 4.4 65.8 17 20.1 0.7 3.9 73.5 18 24.1 0.1 2.5 61.0 19 26.5 3.6 2.6 68.2 20 23.6 2.0 2.0 75.7 21 26.1 0.1 3.9 67.1 22 22.4 3.2 3.0 71.5 23 23.1 0.8 4.1 75.7 24 24.9 0.1 2.0 78.1 25 18.1 1.7 4.5 80.7 26 18.3 1.3 2.4 77.4 32 27 15.3 1.9 4.1 75.3 28 16.5 1.7 2.1 84.7 29 15.4 1.7 3.0 77.3 30 13.7 3.0 4.9 80.3 31 16.6 0.4 3.0 79.9 32 16.6 0.2 1.6 79.4 33 9.7 1.3 4.6 89.0 34 9.3 4.0 2.3 92.8 35 9.0 3.3 3.1 91.5 Table 3: Weather conditions parameters Results 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 Conclusion In this research I present statistical methods of GoNM system. Acknowledgements This work is co-financed by the Republic of Slovenia and the European Union from the European Regional Development Fund, by the Slovenian Research Agency (ARRS). Reference Babbie, Earl R. (2009). The Practice of Social Research (12th ed.). Wadsworth. pp. 436–440. ISBN 978-0-495-59841-1. 59 Scientific error since 1785 Mihelič Janko, Domžale, Slovenija mihelic.jani72@gmail.com • Basic rule of trigonometry. Very old, nameless physical law. If we assume a field source, a point source of light with radius r, light strength decreases with distance. • The same relation applies for electric and magnetic field strength. The rule explains that the field‟s strength weakens with distance and that it has the shape of the sphere. • We must read the equation from both sides! The distance decreases depending on the field strength. The field determines the length measures and the velocities. • Coulomb„s (inverse square) law is fundamental physical law of electromagnetism, first published in 1785. This well known relation must be interpreted as „field dependent length contraction“ when assuming that the sphere„s radius r, as well as all other dimensions and velocities affected by a field are determined by it. In this way, all kinds of attractive forces, including gravity must be understood as field effects occurring when one body is located within another„s field of influence and vice versa. 60 Goldfish problem Problem of the inverse square law is the physical measurements that we observe within the system, but we cannot observe and measure them outside the system. The fish is in fishbowl, but it can't physically take a look at itself and take measurements from the outside on the inside. The energy sent by the transmitter to the receiver is expanded both during the signal transmission and during the bouncing return throughout the space (which means geometrically over the surface of the sphere), so the inverse square for both paths means that the transmitter will receive energy according to the inverse fourth power of range. Well, modern physics is a false theory. Are we lawbreakers when we apply the gravitational force instead of the field in our environment, which is capable of doing the same thing? The speed (m/s) also depends on the field strength and is therefore not fixed! We and our measuring devices cannot detect this as we are also in this field, our solar system. The speed of light is proportional to the measurement path. The result at all events is a constant value. Speed of light is a constant of measurement and not a constant of nature. References: Prof. Dr. Konstantin Meyl, author of Unified Field Theory: Potential vortex Vol. 5 page 13,14 Potential Vortex Vol.4 page 59,60. 61