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The major cause of under-capacity or overcapacity at smaller airports is seasonality. Such airports are finding it difficult to determine the capacity to meet the demand and adequately handle passengers in both high and low season. If the capacity is not optimally defined, excessive congestions and waiting times occur, resulting in lower service quality. Airports greatly benefit from capacity utilization analysis in terms of more accurate planning, designing, and adjusting capacity to the current demand in order to encourage further development as well as to reduce additional costs. Using queuing theory, this paper aims to answer the following question: is the passenger capacity at Rijeka International Airport (Croatia) optimally determined to meet the demand promptly, both in high and low season, without causing excessive congestions and waiting times. The results obtained indicate the occurrence of overcapacity since high season demand can be well served, even with reduced capacity used in the low season when demand is significantly lower.

Berth occupancy sensors are used to monitor and determine the presence of vessels at a berth on a daily basis to improve port management and make a port more efficient and competitive. This paper presents an evaluation of wireless ultrasonic berth occupancy sensors by analyzing the accurate and inaccurate detection of berth occupancy and the efficiency of the sensors under different berth status conditions, highlighting the main causes of false detections. Results revealed that sensors' accuracy for berth status detection range from 35% to 92%. The most common causes of inaccurate berth occupancy detection are sea currents, inadequate sensor positioning, damage to the sensor, exceeding boat-to-sensor distance, ropes from adjoining berths, and surrounding vegetation.

In moderately developed cities, the realization of mobility desires today still depends heavily on the private transport system. Transitional cities, where demand for private transport modes is currently highest, face a number of problems. These problems are typically related to the level of traffic congestion, which leads to unacceptable travel times, fuel waste, lower operational efficiency, poor air quality, high driver stress levels, and safety concerns. Therefore, the need for effective short- and medium-term traffic flow forecasting is becoming increasingly important for the development of decision-support systems and the implementation of low-error operational procedures in traffic management. This paper evaluates the performance of advanced time series forecasting algorithms that ensure accurate future input data for traffic management decision making. The algorithms were trained, validated, and tested on a dataset of hourly traffic flow on a divided multilane highway (urban bypass) in 2021 (Rijeka, Croatia). The dataset consists of traffic flow data collected from inductive loop detectors on 10 highway sections (two detectors per driving direction ; one detector on the right driving lane and one detector on the overtaking lane). The accuracy of the evaluated algorithms is assessed using performance metrics such as Mean Square Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). All tested algorithms meet the application criteria for detecting diurnal trends in traffic flow and are suitable for implementation in traffic management decisions.

U radu je analiziranpostojeći sustav reda čekanja u Zračnoj luci Rijeka, kako bi povećanjem kvalitete usluge ista postala konkurentnija.Određeni su pokazatelji funkcioniranjareda čekanjau svrhuispitivanja zagušenja sustava. Istraživanjem su definirana potencijalna „uska grla“, a dobiveni rezultati uspoređeni su sa smjernicama IATA-e o maksimalno dozvoljenom vremenučekanja. Ponašanje sustavaispitanoje kakou zimskom tako i u ljetnom periodu.Ovim radom nastoji se ocijeniti učinkovitost postojećeg stanja u cilju poboljšanja sustava reda čekanja u zračnoj luci, budući da se u sljedećih nekoliko godina očekuje rekordan broj putnika.Rad sustava simuliran je u softverskompaketu FlexSim. Rezultati simulacije se u potpunosti podudaraju s provedenim izračunima.

Posidonia oceanica (L.) Delile endemska je vrsta u Mediteranu, čija naselja zbog velike primarne produkcije i biomase predstavljaju jedan od najproduktivnijih ekosistema mora. Ona naseljava infralitoralna područja toplih tropskih i umjerenih mora gdje stvara gusta naselja koja predstavljaju sklonište, dom i izvor hrane za mnoge bentičke organizme. Cilj ovog istraživanja bio je utvrditi osnovna obilježja naselja morske cvjetnice Posidonia oceanica (L.) Delile u plitkom moru na tri lokacije u okolici Zadra. Uzorci posidonije sakupljeni su u travnju 2011. godine na 2 m dubine na postaji Ženski Banj (Zadarski kanal), te na 3 m dubine u uvali Brbišćica (Dugi otok) i uvali Zaglav (Dugi otok). Sakupljena su ukupno 64 uzorka posidonije, te je obrađeno 147 izdanaka. Određena je i gustoća naselja prebrojavanjem izdanaka in situ u deset kvadrata površine 40x40 cm na sve tri lokacije. Na uzorcima posidonije napravljena je biometrija listova, lepidokronološka analiza, te je procijenjena biomasa i primarna produkcija. Rezultati su pokazali razlike u gustoći naselja, biometriji listova, te biomasi i primarnoj produkciji na istraživanim postajama. Najveća gustoća naselja zabilježena je na postaji Ženski Banj (1013±353 izdanaka po m2), a najmanja na postaji Brbišćica (402±32 izdanka po m2). Indeks lisne površine najveći je na postaji Ženski Banj (116586,17 cm2/m2), a najmanji na postaji Zaglav (66690,30 cm2/m2). Biomasa po m2 najveća je za naselje na Ženskom Banju (295,41 g suhe mase po m2), a najmanja za naselje u uvali Zaglav (86,69 g suhe mase po m2). Najveća primarna produkcija procijenjena je za naselje na postaji Ženski Banj i iznosi 1409,48 g suhe mase po m2/god (2008. god.), dok je najmanja procjena za naselje u uvali Zaglav i iznosi 158,16 g suhe mase po m2/god (2005). S obzirom na gustoću i primarnu produkciju, naselje posidonije na postaji Ženski Banj u Zadarskom kanalu najbolje je razvijeno, dok je naselje u uvali Zaglav najslabije razvijeno. Posidonia oceanica (L.) Delile is an endemic species in the Mediterranean, whose meadows, due to the high primary production and biomass, represent one of the most productive ecosystems of the sea. It inhabits subtidal areas of warm tropical and temperate seas where it forms dense meadows that represent shelter, home and source of food for many benthic organisms. The goal of this research was to determine the main characteristics of Posidonia meadows in three locations in wider Zadar area. Posidonia samples were collected in April 2011 at 2 m of depth at station Ženski Banj (Zadar channel), and at 3 m of depth at Brbišćica bay (Dugi otok) and Zaglav bay (Dugi otok). A total of 64 samples of seagrass were collected, and a total of 147 shoots were processed. Density was estimated in situ at all three locations in ten squares with 40x40 cm surface area. Leaf biometry and lepidochronological analysis were performed and the biomass and primary production were estimated for the collected Posidonia samples. The highest density was observed at station Ženski Banj (1013±353 shoots per m2), and lowest at station Brbišćica (402±32 shoots per m2). Leaf area index was the largest on Ženski Banj (116586,17 cm2/m2) and lowest at Zaglav (66690,30 cm2/m2). Biomass per m2 was the largest for the meadow on Ženski Banj (295,41 g DW per m2), and the lowest in Zaglav bay (86,69 g DW per m2). The maximum value of primary production was obtained for the station Ženski Banj (1409,48 g DW per m2/y; 2008), while the lowest value was in Zaglav bay (158,16 g DW per m2/y; 2005). Given the density and primary productivity, the Posidonia bed at station Ženski Banj in Zadar channel is the best developed, while the one at station Zaglav is the least developed.

In maritime navigation, the Vessel Traffic Service (VTS) represents a sea traffic organisation and surveillance system for the particular sea area. Its most important services are the information support and traffic management with the aim of safety of navigation improvement and the marine environment protection. In pace with the increasing market, and related increase of the maritime transport and traffic in the Adriatic region, the risks of maritime accidents are increasing as well. Although, as per respective standards and official VTS guidelines, the legislative and operational traffic control measures are established, the number of accidents still represents a significant threat to the safety of navigation. In order to cope with this challenge, the Sea Traffic Management system (STM) represents a new means for improvement of the vessels’ surveillance and management. The proposed paper elaborates the STM from the organisational, safety and operational point of view, as well as analysing its establishment feasibility in terms of integration with other related services. Further, the advantages of the system and its features are analysed with regards to existing means of surveillance and sea traffic organisation. For the purpose of the research on existing services as well as potential improvement options, the structured interviews and surveys were conducted among VTS operators. The results indicate that the further usage of the STM represents a significant progress towards sea traffic monitoring and VTS services’ organisation in the area in terms of integration and mutual communication between all related stakeholders.

Mobility analysis is used to determine how people change travel behavior, and traffic safety analysis focuses on how traffic safety can change from before to after an event. Today, the wide availability of mobile sensors has given us the opportunity to be able to assess changes in human mobility in near real time. The platforms produce aggregated daily mobility metrics and the integration of mobility and safety data related to COVID-19 is expected to provide valuable results. Data collected on the impact of COVID-19 on human mobility using public location data of mobile devices available to many companies such as Google and Apple which is very useful to show the change of human mobility according to a different control policy. With different control policies from local and state government, the outbreak of COVID-19 dramatically changed the behavior in the Republic of Croatia. In this study, we collected timelines of public policies issued by the local and state government. The different levels of control policies during the outbreak of COVID-19 are closely related to safety awareness, driving and travel behavior, and thus an indirect impact on collision frequency. Based on set of data of people involved in traffic accidents and mobility data from mobile devices, the impact of COVID-19 on traffic safety was analyzed. Based on collected set of data of mobility and traffic accidents in the Republic of Croatia from the beginning of the pandemic, this study specifically aims to assess road safety in view of the change in control policies for COVID-19. This paper explores the impact of human mobility and control policies, including declaring emergencies, banning gatherings of certain sizes, closing schools, business restrictions and home stays on the number of people involved in accidents in the Republic of Croatia during the COVID-19 pandemic.

Great part of mechanics is involved with derivation of some kind, e.g., differential equations. In the long history of mechanics, a lot of mathematical and numerical methods have been developed for their solution. However, today we have an additional component that strongly influences approach to the solution of problems in mechanics. Namely, existence of data allows us to use solution methods that would otherwise be inapplicable. A significant tool towards formalization of the solution process is use of derivation matrices that reduce the derivation operation and solution of differential equations to linear algebra operations [1]. Derivation matrices are formulated by applying numerical methods in matrix notation, like finite difference schemes. Here we are developing a novel formulation based on Lagrange polynomials. The main advantage of the approach is straightforward formulation, clear engineering insight into the process and (almost) arbitrary precision through choice of the interpolation order. Prerequisite for application of derivation matrices is availability of data, recorded displacements or velocities or accelerations. Let us assume quadratic function interpolation and interpolation of the function value in some point 'j' is represented using the equation p_j (x)=u_l L_l (x)+u_j L_j (x)+u_d L_d (x) where 'u's are unknown function values in discretization points, 'L's are Lagrange interpolation polynomials, and indices 'l' and 'd' represent the left and the right point in the adopted discretization scheme. Value of the derivative in point 'j' is w_j (x)=u_l L_l (x) that gives the equation 〖p'〗_j (x). It is clear that we only have to differentiate the Lagrange polynomials, which is straightforward. Special care should be taken at boundary points. In order to preserve a uniform precision, usually an extra point is added at the boundary. The result of this procedure is the derivation matrix of the dimension [n×n], where 'n' is the number of data points. The resulting matrix is singular (of rank 'n-1') until boundary/initial conditions are introduced. However, that does not prevent us to successfully differentiate our unknown function represented with the recorded data points. Derivation matrix approach is easily applicable to a wide range of engineering problems. This methodology could be extended to dynamic systems with multiple degrees of freedom and adapted when velocities or accelerations are recorded instead of displacements. Additional adjustments are needed when one records a reduced set of parameters (less then one set of data for each degree of freedom). It is also possible to determine the initial conditions and damping at the same time. Acknowledgment: This work has been supported through project HRZZ 7926 ”Separation of parameter influence in engineering modelling and parameter identification” and project KK.01.1.1.04.0056 ”Structure integrity in energy and transportation”, which is gratefully acknowledged.

My First Conference is an annual conference for doctoral students of engineering and technology studying at University of Rijeka. It is a joint initiative of Faculty of Engineering, Faculty of Maritime Studies and Faculty of Civil Engineering of the University of Rijeka. Doctoral students from other institutions and graduate students with ambitions in scientific research are also welcome to participate in this annual event. The goals for the participants of this conference are: - To provide the feedback for the ongoing student's research ; the presented work should not be only the completed research, but also the research that is still not finished. - Improvement of the presentation skills in English at a scientific conference at no cost. - Development of the possibility for the interdisciplinary research projects between doctoral students from different institutions. - Public presentation of the research results required within the doctoral study obligations (this presentation can serve for this purpose if the person in charge of the institution's doctoral study approves it). The conference was held at University of Rijeka, Faculty of Maritime Studies on September 23, 2021. For the fifth edition of My First Conference, 30 abstracts were submitted along with 3 plenary and one keynote lecture.

Numerous technological innovations that provide clear benefits that society sorely needs require new and advanced materials with their superior properties. The unique mechanical behaviour of these materials is inadequately described by conventional models and therefore poorly understood. Consequently, machine learning approaches appear to be a potential tool for characterizing complex material properties. The stiffness matrix contains information on the mechanical properties of the material whose key component is the strain-displacement matrix. In this research, we utilized deep learning methods to generate a strain-displacement matrix at Gauss points. The intrinsic coordinate system-based isoparametric formulation was employed to derive the element stiffness matrix and equations. The proposed method is utilized to develop quadratic 1D linear elastic and functionally graded rod finite elements with varying Young’s modulus. The dataset included nodal coordinates, nodal displacements, and strain of the finite element. Several sets of data including training data, test data, and validation data were employed to obtain the best feasible prediction model. The numerical tests indicated a satisfying model's performance.

In order to realistically describe the behaviour of a heterogeneous material and capture the phenomena that the classical (Cauchy) theory cannot, several alternative theories have been developed, one of which is the micropolar (Cosserat) continuum theory. Unlike the classical theory, where the static interaction between two particles of a body is described only by a force vector, in the micropolar theory there exists an additional moment vector field [1]. Consequently, there is an additional couple-stress tensor and both stress tensors are non-symmetric in general. The existence of a couple-stress tensor causes an additional kinematic field (microrotation), which gives an orientation to each material point and it is completely independent of the skew-symmetric part of the displacement gradient at the observed point (macrorotation). To describe a linear centrosymmetric isotropic micropolar continuum, it is necessary to know six independent material parameters [2]. The theory itself is well known, but reliable experimental methods for determining the material parameters are still not established, which prevents wider application of the theory. Alternatively, the material parameters may be obtained from experiments with the help of numerical analysis in an inversely posed problem. The development of high-quality micropolar finite elements is thus very important and for this reason, we present a detailed linear analysis of the micropolar continuum within the finite-element method using a novel interpolation based on the fixed-pole concept. The concept was first introduced in [3] where authors applied it to the geometrically nonlinear 3D beams which has proven to be particularly useful in dynamics, but so far, no attempts have been made to apply it in linear analysis, where some advantages of the concept can be expected. The new family of micropolar finite elements will be tested through patch tests and compared with existing elements [4].

Unmanned aerial vehicles (UAVs) have been used for coastal research in Croatia since 2012. SfM-MVS photogrammetry is mostly used for analysis of changes on beaches, which increasingly requires high resolution and precision of three-dimensional point clouds resulting from photogrammetric technique [1]. In this paper, this technology was used to study coastal processes on Ploče beach in Rijeka. The beach was surveyed 19 times with a drone in 2020 and 2021, and two 3D scans of the beach area were performed to determine the accuracy of the point clouds. The defined point cloud precision for the emerged beach is better than ± 5 cm. The point cloud representing the submerged beach was compared to the multibeam echo sounder data, and the results showed significantly greater discrepancies than for the emerged beach. The accuracy of the submerged point cloud data was increased by depth correction using the light refractive index, but more accurate corrections are one of the ultimate goals of this research. The CloudCompare software has also proven to be a useful tool for identifying and describing beach surface changes. Successive beach surveys were compared and digital models of the differences (DoDs) were created as a result. The comparisons showed that the greatest changes on the beach are caused by waves from southern and southeastern directions, and when storm events are accompanied by higher rainfall, runoff from coastal springs enhances the coastal process on the beach body. UAV photogrammetry has proven to be a simple, fast, and cost-effective tool for describing and visualising changes on beaches, considering that the morphological changes under the influence of waves and precipitation are much greater than the accuracy achieved.