Methods and metrics for studying interactions between automated vehicles and other road users in their vicinity, such as pedestrians, cyclists and non-automated vehicles, are not established yet. This workshop focuses on identifying the strengths and weaknesses of various methodologies that could potentially be used to study such interactions. The objective lies in determining the proper experimental design, sensitivity of metrics for measuring user behavior, ecological validity, generalizability of findings, extraction of insights regarding how findings can be translated into actionable requirements, and the alternatives for conducting longitudinal field studies. It will be of an interactive nature and involve hands-on activities. The workshop will consolidate existing knowledge, identify recurring issues, and explore the path towards resolving these issues. The outcome will be compiled into a paper to share this valuable knowledge with a broader research community.

Queuing systems (QS) represent everyday life in all business and economic systems. On the one hand, and there is a tendency for their time and cost optimization, but on the other hand, they have not been sufficiently explored. This especially applies to logistics systems, where a large number of transportation and storage units appear. Therefore, the aim of this paper is to develop an ANFIS (Adaptive neuro-fuzzy inference system) model in a warehouse system with two servers for defining QS optimization parameters. The research was conducted in a company for the manufacturing of brown paper located in the territory of Bosnia and Herzegovina, which represents a significant share of the total export production of the country. In this paper, the optimization criterion is the time spent in the system, which is important both from the aspect of all customers of the system, and from that of the owner of the company. The time criterion directly affects the efficiency of the system, but also the overall costs that this system causes. The developed ANFIS model was compared with a mathematical model through a sensitivity analysis. The mathematical model showed outstanding results, which justifies its development and application.

School of Medicine, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Department of Pathology, Clinical Center, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Department of Radiology, Clinical Center, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Department of Oncology, Clinical Center, University of Sarajevo, Sarajevo, Bosnia and Herzegovina College of Medicine, Qatar University, Doha, Qatar

This paper studies the behavior of singularly perturbed nonlinear differential equations with boundary-layer solutions that do not necessarily converge to an equilibrium. Using the average of the fast variable and assuming the boundary layer solutions converge to a bounded set, results on the closeness of solutions of the singularly perturbed system to the solutions of the reduced average and boundary layer systems over a finite time interval are presented. The closeness of solutions error is shown to be of order $\mathcal{O} (\sqrt{\varepsilon})$, where $\varepsilon$ is the perturbation parameter.

Organizations can improve efficiency of process execution through a correct resource allocation, as well as increase income, improve client satisfaction, and so on. This work presents a novel approach for solving problems of resource allocation in business processes which combines process mining, statistical techniques, and metaheuristic algorithms for optimization. In order to get more reliable results of the simulation, in this paper, we use process mining analysis and statistical techniques for building a simulation model. For finding optimal human resource allocation in business processes, we use the improved differential evolution algorithm with population adaptation. Because of the use of a stochastic simulation model, noise appears in the output of the model. The differential evolution algorithm is modified in order to include uncertainty in the fitness function. In the end, validation of the model was done on three different data sets in order to demonstrate the generality of the approach, and the comparison with the standard approach from the literature was done. The results have shown that this novel approach gives solutions which are better than the existing model from literature.

Grasping objects under uncertainty remains an open problem in robotics research. This uncertainty is often due to noisy or partial observations of the object pose or shape. To enable a robot to react appropriately to unforeseen effects, it is crucial that it continuously takes sensor feedback into account. While visual feedback is important for inferring a grasp pose and reaching for an object, contact feedback offers valuable information during manipulation and grasp acquisition. In this paper, we use model-free deep reinforcement learning to synthesize control policies that exploit contact sensing to generate robust grasping under uncertainty. We demonstrate our approach on a multi-fingered hand that exhibits more complex finger coordination than the commonly used two-fingered grippers. We conduct extensive experiments in order to assess the performance of the learned policies, with and without contact sensing. While it is possible to learn grasping policies without contact sensing, our results suggest that contact feedback allows for a significant improvement of grasping robustness under object pose uncertainty and for objects with a complex shape.

The aim of this research was to find the relationship between metals content and age of the sediment and to estimate the contamination level. For the research of sediment, samples were taken from the glacial Lake Prokosko. Concentrations of eight elements (Ca, Mg, Fe, Cd, Pb, Zn, Cu and Mn) were determined. The age was determined with usage of C14. For statistical evaluation of the results, we used basic statistical tools, correlation, and PCA. The results showed that all of investigated metals have natural origin. Sediment core from this research was around 18,000 years old and the results revealed characteristics of metals deposition in the process of sedimentation. Concentrations of metals were compared with age (depth) of sediment. Maximal concentrations for iron, calcium, magnesium and manganese are found in the period of Allerӧd oscilation. Differences in Mn/Fe ratio and organic matter content are showing changes through history. These results show metal deposition characteristics in different climate periods, and these characteristics could be used as another proof of climate change.

In this paper, we investigate the bandwidth and power allocation problem in remote radio head cluster (RRHC)-based millimeter wave (mm-wave) massive MIMO heterogeneous cloud radio access networks with limited fronthaul capacity. The coordinated multipoint transmission is applied in each RRHC for cancelling the intra-cluster interference. To avoid the inter-tier interference, distinct bandwidths are allocated to macro base station and RRHs. Following this, we formulate a bandwidth and power allocation optimization problem to maximize the downlink weighted sum rate of the system subject to per-RRHC power and fronthaul capacity constraints, which is a non-convex optimization problem and is difficult to directly solve. Next, we fix the bandwidth allocation and the original problem can be divided into two independent optimization problems, i.e., the weighted sum rate maximization problems of MUs and RRH users, respectively. For the former, the convex optimization technique can be used to solve it. As for the latter, a two-loop iterative algorithm is proposed to deal with it. Specifically, we propose the price-based outer iteration to control the fronthaul capacity and the weighted minimum mean square error-based inner iteration to obtain the power allocation. To this end, a 1-D search method is adopted to find the optimal bandwidth allocation. Finally, numerical results are conducted to verify the effectiveness of the proposed algorithms under different parameters.

Biodizel je naziv za gorivo dobiveno iz obnovljivih izvora koje se može upotrebljavati u nemodificiranim dizelskim motorima umjesto uobičajenog fosilnog dizelskog goriva. Biodizel je ustvari komercijalni naziv za smjesu metilnog estera, koja se danas može naći na tržištu tekućih goriva, prije svega u EU-u, gdje se i prodaje krajnjim korisnicima. Globalna proizvodnja biodizela u 2014. godini premašila je 30 milijardi litara od čega oko 39 % otpada na EU.1 Kao osnovna sirovina za dobivanje biodizela mogu poslužiti svi izvori biomase bogati triacilglicerolima. U prvom redu tu spadaju jestiva biljna ulja, zatim nejestiva, otpadna i upotrijebljena ulja, kao i životinjske masti. Metanoliza biljnih ulja može biti podijeljena na osnovu prisutnosti i vrste katalizatora ili topljivosti katalizatora u reakcijskoj smjesi. Ovisno o tome odvija li se reakcija metanolize s ili bez prisutnosti katalizatora, metanoliza može biti katalizirana i nekatalizirana. Kemijski katalizatori metanolize razlikuju se kako po svojoj prirodi tako i na osnovi njihove topljivosti u reakcijskoj smjesi. Ovisno o tome je li katalizator u reakcijskoj smjesi topljiv ili nije, kemijski katalizirana metanoliza može biti podijeljena na homogeno, heterogeno i homogeno-heterogeno kataliziranu metanolizu. Osnovna karakteristika homogeno katalizirane metanolize je otopljen katalizator u reakcijskoj smjesi. Homogeni katalizatori metanolize mogu biti lužine i kiseline. Najčešće istraživan i u komercijalnim procesima najčešće primjenjivan način dobivanja biodizela je metanoliza katalizirana lužinama. Proces transesterifikacije s lužnatim katalizatorom uobičajen je način proizvodnje biodizela iz rafiniranih biljnih ulja. Kao lužnati katalizatori najčešće se upotrebljavaju kalijev hidroksid (KOH), natrijev hidroksid (NaOH) i natrijev metoksid (NaOCH3). Unatoč brojnim prednostima homogeno katalizirane metanolize, glavni nedostatak joj je nemogućnost ponovne uporabe katalizatora. Pored toga, katalizator zaostaje u esterskoj frakciji, odakle ga je potrebno ukloniti, što se najčešće provodi višestrukim ispiranjem s vodom, a otpadna voda čini značajan problem za okoliš.2,3 Uporabom katalizatora koji se ne otapaju u reakcijskoj smjesi, pojednostavljuje se način izdvajanja i rafiniranja proizvoda, smanjuju okolišni problemi i omogućava ponovna uporaba katalizatora. Uporabom heterogenih katalizatora dobiva se kvalitetniji i čišći biodizel kao i glicerol, a zbog jednostavnijeg postupka i mogućnosti višestruke uporabe katalizatora danas se homogena kataliza sve više nastoji zamijeniti heterogenom.3,4,5 U posljednje vrijeme heterogeno katalizirana metanoliza vrlo se intenzivno istražuje. U različitim laboratorijskim istraživanjima heterogeno katalizirane metanolize upotrebljavan je velik broj različitih spojeva u funkciji katalizatora.6 Pri tome je mnogo pozornosti posvećeno istraživanju vrste, načina pripreme i količine heterogenog katalizatora, kao i uvjetima pri kojima se izvodi reakcija metanolize. Katalitička aktivnost heterogenih katalizatora ovisi o mnogo čimbenika, prije svega o njihovoj prirodi, veličini i specifičnoj površini čestica te primijenjenim uvjetima u kojima se reakcija izvodi.7 Između objavljenih rezultata ovih istraživanja postoje razlike oko optimalnih uvjeta procesa, pa čak i oko postojanja katalitičke aktivnosti nekih spojeva. Najveći broj istraživanja heterogeno katalizirane metanolize odnosi se na primjenu zemnoalkalijskih metala, točnije njihovih oksida kao katalizatora reakcije.3 Katalitička aktivnost oksida zemnoalkalijskih metala raste s povećanjem njihove bazičnosti i to redoslijedom;