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In this paper we deal with the problem of creating an online environment for taking written exams during the lockdown caused by the COVID-19 pandemic. We have taken an approach that combines Microsoft Teams and an e-learning system. Before the exam begins all students join a Microsoft Teams meeting together with the teachers. This provides a simple way for teachers to check and monitor students' activity during the exam. Also, any student can immediately contact the teachers if they encounter technical problems. Online exam is accessed through an e-learning system. In our e-learning system exam questions can be parameterized, so that each student gets different variants of questions of the same difficulty. Furthermore, the order of the questions is randomized, so that students get different permutations of the questions. In smaller courses this can ensure that each student takes a unique variant of the exam which can discourage and minimize cheating. To answer questions students must upload scans or photos of their handwritten solutions. After the written online exam is manually evaluated, students must also take an oral exam through a Microsoft Teams meeting with the teachers. The described online exam procedure was used on the course Fundamentals of electrical engineering in the Fall semester of 2020/2021.

Background: Lung ultrasound (LUS) is a useful imaging method for identifying COVID-19 pneumonia. The aim of this study was to explore the role of LUS in predicting the severity of the disease and fatality in patients with COVID-19. Methods: This was a single-center, follow-up study, conducted from 1 November 2020, to 22 March 2021. The LUS protocol was based on the assessment of 14 lung zones with a total score up to 42, which was compared to the disease severity and fatality. Results: A total of 133 patients with COVID-19 pneumonia confirmed by RT-PCR were enrolled, with a median time from hospital admission to lung ultrasound of one day. The LUS score was correlated with clinical severity at hospital admission (Spearman’s rho 0.40, 95% CI 0.24 to 0.53, p &lt, 0.001). Patients with higher LUS scores were experiencing greater disease severity, a high flow nasal cannula had an odds ratio of 1.43 (5% CI 1.17–1.74) in patients with LUS score &gt, 29, the same score also predicted the need for mechanical ventilation (1.25, [1.07–1.48]). An LUS score &gt, 30 (1.41 [1.18–1.68]) and age over 68 (1.26 [1.11–1.43]) were significant predictors of fatality. Conclusions: LUS at hospital admission is shown to have a high predictive power of the severity and fatality of COVID-19 pneumonia.

In this paper, we research the use of software combinatorial testing techniques and the Formal Concept Analysis method for preparing sets of questions for student assessment in e-learning systems. Utilizing these techniques and methods, we ensure that the selected questions optimally cover the course material and that each question combines multiple topics. Therefore, in this paper we introduce our method for preparing student assessments that performs automated combinatorial testing and selection of questions, as well as automated generation of appropriate sequences of questions. The input for our method is a set of questions labelled with attributes or features. This set of questions is pre-processed using the Formal Concept Analysis method, and then the combinatorial testing of question features is performed, which generates a concise list of test-cases covering all pairs or triples of question features. Correspondingly, our method helps in identifying and selecting a subset of questions that covers all generated test-cases. Afterwards, the Formal Concept Analysis method automatically generates suitable sequences of selected questions for formative student assessments in e-learning systems. In this paper we implemented the proposed combinatorial testing method, and also demonstrated the feasibility of the proposed method on a use-case from an actual e-learning system.

One of the biggest challenges in the process of establishing modern e-learning systems is figuring out ways to leverage legacy course materials and integrating them in the new information systems. Existing exam query repositories in particular are a very valuable data source, but one which usually lacks enough metadata to help establish relationships between exam questions and corresponding learning concepts whose adoption is being evaluated. In this paper we present the continuation of our research regarding the usage of educational data mining methods able to automatically annotate pre-existing exam queries with information about learning concepts they relate to. In our novel approach we leverage both textual and visual information contained in the queries. By combining the power of natural language processing which focuses on the text of the question, and annotated data extracted from figures accompanying the questions, we are able to further refine our classification methods and achieve noticeably improved results. By identifying learning concepts more accurately we further facilitate automatic creation of exams as well as even better insight into learning concept adoption. Our approach is again applied on data gathered from a large scale university course, and the results were validated in consultation with educational domain experts.

Descriptive data mining techniques offer a way of extracting useful information out of large datasets and presenting it in an interpretable fashion to be used as a basis for future decisions. Since users interpret information most easily through visual means, techniques which produce concise, visually attractive results are usually preferred. We define a method, which converts transactional data into tree-like data structures, which depict important relationships between items contained in this data. The new approach we propose is offering a way to mitigate the loss of information present in previously developed algorithms, which use mined frequent itemsets and construct tree structures. We transfer the problem to the domain of graph theory and through minimal spanning tree construction achieve more informative visualizations. We highlight the new approach with comparison to previous ones by applying it on a real-life datasets – one connected to market basket data and the other from the educational domain.

In this paper we interpret constraint satisfaction problem (CSP) with model checker Spin and bounded model checkers from satisfiability modulo theories (SMT) solvers. Our previous experience shows that single example modelled in different ways and interpreted with the same solver can have different space and time consumption. The goal is to find a feasible translation from of CSP problem to model checker and SMT solver. For that purpose we build Promela models for Spin model checker and Z3 models for SMT solver. Domain problem used in examples is graph colouring applied to Sudoku puzzle. In the beginning we briefly introduce CSP, model checking, graph colouring and Sudoku puzzle. The central part of this paper deals with various modelling efforts of Sudoku puzzle. After that results are analysed and compared. The main benefits of this paper are twofold, as we use them for educational purposes within Formal Methods in System Design course and as a solution to industrial scale problems like wavelength assignment in photonic networks respectively. At the end we give a conclusion and propose future research directions.

Objective Chronic post-traumatic arteriovenous fistula (AVF) is a late complication of vascular injury and can be presented with symptoms of congestive heart failure, venous hypertension and distal ischaemia. We present an unusual case of chronic ischaemic leg ulcer in young adult caused by post-traumatic AVF. Case report A 29-year-old male patient was admitted to our hospital with symptoms of chronic ulcer located on the lateral side of the lower left leg. Arterial pulses distally from the groin were absent. His medical history revealed him to have sustained gunshot injury of the left thigh in the war conflict 18 years before. Angiography showed a large AVF between superficial femoral artery and femoral vein. The patient underwent surgical repair of AVF with reconstruction of superficial femoral artery by saphenous vein interposition under spinal anaesthesia. Completion angiography confirmed AVF exclusion. Leg ulcer healed within a month. Conclusion Chronic leg ulcer may be the only symptom of large post-traumatic AVF in young adults.

Internal carotid artery (ICA) aneurysms are rare. The symptoms are related to cerebral embolization, local compression and rupture. Options for treatment include open surgery or endovascular treatment with a covered stent. We report a case of a 67 year old woman with bilateral idiopathic internal carotid artery aneurysms, found during the diagnostic evaluation for an episode of syncope. The right ICA aneurysm was treated with resection and end-to-end anastomosis of the ICA. There were no perioperative complications. Six months later the patient underwent endovascular repair of left carotid artery aneurysm with a covered stent. There were no complications in postoperative period. Treatment options for ICA aneurysms are surgical or endovascular, depending of size, location and anatomic relation to surrounding structures.

This paper deals with the problem of automated generation of questions for basic electrical engineering education in e-learning systems. One of the main challenges in developing e- learning systems is to create an effective knowledge testing module. In most of e-learning systems teachers need to manually compose test questions, prepare the correct and wrong answers, and added feedback information. The process is time-consuming and prone to errors. We have focused on problems in basic electrical engineering education, specifically series – parallel DC circuits, and we propose a solution for automated generation of template based questions of various degrees of similarity and complexity. Our prototype Web application dynamically generates text of the question and its circuit diagram image, solves the problem, and as a feedback provides correct results and a step-by-step solution. The interface is bilingual, available in Croatian and English. We have used standard Web technologies, such as JavaScript, jQuery and SVG, together with MathJax for mathematical notation. We will recommend our students on the course Fundamentals of Electrical Engineering to use this Web Application for self-assessment and practice. In future work we plan to advance our Web application and to fully integrate it into our developing e-learning system.

Social learning is a natural way of acquiring knowledge and approaching various problems. In high education, students widely use social learning which is to a large extent facilitated by todays' popular social network applications. However, as of yet high education systems typically do not recognise the value of the data produced by or embedded within these social network applications. In this paper we present survey results through which we examine certain recent learning habits among students in Croatia. We predominantly investigated their usage of Facebook, today's leading social network application, specifically for the purposes of learning. Based on these findings, and taking into account common communication problems we perceive in our work, we propose a framework for University Social Network construction. We presume various usages of it by different stakeholders, propose node construction within the network compliant with educational and research processes and recommend flexible privacy levels for communication units.

This paper gives an overview of relevant research in the area of process mining. Process mining techniques are able to extract knowledge from event logs. The major objective of process mining is to discover, monitor and improve real processes. Process mining aims to exploit event data in a meaningful way to identify and anticipate problems, and recommend countermeasures. Additionally, process mining places the existing massive volumes of data in the context of processes. Since extracting data is an integral part of any process mining procedure, data preparation or data pre- processing requires certain efforts. Examples have been given to indicate how the chosen process mining technique deals with incompleteness in the event log data. Experiments have been made on the real data collected from information system for accommodation services.

Imaging the pregnant patient presents a unique challenge to radiologist due to the risk of radiation to the conceptus (embryo/fetus). A rare case of a successfully recognized and treated pseudoaneurysm (PA) of the abdominal aorta is to be presented. The pseudoaneurysm occurred in the third trimester and had a favorable outcome for the mother and the baby. Emergent abdominal ultrasound (US) is the first modality in diagnostic algorithm for the rupture of aortic aneurysm in a pregnant woman. It provides the most rapid diagnostic information, although intestinal gas and abdominal tenderness may limit its accuracy. To confirm the findings, magnetic resonance angiography (MRA) or CT angiography (CTA) can be used. In our case, the diagnosis was established using a color Doppler ultrasonography of the abdomen and was later confirmed by a low dose CT scan of the abdominal aorta. MRA in such cases have some disadvantages. At many health centers, the monitoring of patients with acute ruptures is more difficult in the MR suite than at the CT scanner. MRA angiographic images are also subject to degradation by multiple artifacts and the visualization of the distal vasculature is suboptimal and inferior to the one done by CTA. Due to fetal movements, a small quantity of fresh blood can be overlooked by MR. MRA is often not available on a 24-hours basis, and the time required for making a diagnosis can preclude the use of MRA in an unstable patient. For this reason, we used a low dose CTA protocol to confirm the diagnosis. Low dose scanning protocols in CT can obtain sufficient diagnostic information while reducing the risk of radiation. A particular focus is put on the outline of new concepts for dose management and optimization. We used new approaches based on tube current modulation. The birth was induced by an urgent Caesarean section followed by a resection of a pseudoaneurysm and a reconstruction of the aorta with an end-to- end vascular prosthesis.

We describe our web-based system for the analysis of students' results on the course Fundamentals of Electrical Engineering by applying the method of Formal Concept Analysis. We have focused on the students' answers and constructed their concept lattices or taxonomies of the subject matter. Finally, we have shown that this approach corresponds well with the actual students' overall results and final grades.

To examine the mechanisms contributing to pain genesis in diabetic neuropathy, we investigated epidermal thickness and number of intraepidermal nerve fibers in rat foot pad of the animal model of diabetes type 1 and type 2 in relation to pain- related behavior. Male Sprague-Dawley rats were used. Diabetes type 1 was induced with intraperitoneal injection of streptozotocin (STZ) and diabetes type 2 was induced with a combination of STZ and high-fat diet. Control group for diabetes type 1 was fed with regular laboratory chow, while control group for diabetes type 2 received high-fat diet. Body weights and blood glucose levels were monitored to confirm induction of diabetes. Pain-related behavior was analyzed using thermal (hot, cold) and mechanical stimuli (von Frey fibers, number of hyperalgesic responses). Two months after induction of diabetes, glabrous skin samples from plantar surface of the both hind paws were collected. Epidermal thickness was evaluated with hematoxylin and eosin staining. Intraepidermal nerve fibers quantification was performed after staining skin with polyclonal antiserum against protein gene product 9.5. We found that induction of diabetes type 1 and type 2 causes significant epidermal thinning and loss of intraepidermal nerve fibers in a rat model, and both changes were more pronounced in diabetes type 1 model. Significant increase of pain-related behavior two months after induction of diabetes was observed only in a model of diabetes type 1. In conclusion, animal models of diabetes type 1 and diabetes type 2 could be used in pharmacological studies, where cutaneous changes could be used as outcome measures for predegenerative markers of neuropathies.