Background: A nationwide study was conducted to explore the short term association between daily individual meteorological parameters and the incidence of acute coronary syndrome (ACS) treated with coronary emergency catheter interventions in the Republic of Slovenia, a south-central European country. Method: We linked meteorological data with daily ACS incidence for the entire population of Slovenia, for the population over 65 years of age and for the population under 65 years of age. Data were collected daily for a period of 4 years from 1 January 2008 to 31 December 2011. In line with existing studies, we used a main effect generalized linear model with a log-link-function and a Poisson distribution of ACS. Results and Conclusions: Three of the studied meteorological factors (daily average temperature, atmospheric pressure and relative humidity) all have relevant and significant influences on ACS incidences for the entire population. However, the ACS incidence for the population over 65 is only affected by daily average temperature, while the ACS incidence for the population under 65 is affected by daily average pressure and humidity. In terms of ambient temperature, the overall findings of our study are in line with the findings of the majority of contemporary European studies, which also note a negative correlation. The results regarding atmospheric pressure and humidity are less in line, due to considerable variations in results. Additionally, the number of available European studies on atmospheric pressure and humidity is relatively low. The fourth studied variable—season—does not influence ACS incidence in a statistically significant way.

Companies often claim to follow specific software development methodologies (SDM) when performing their software development process. These methodologies are often supported by dedicated tools that keep track of work activities carried out by developers. The purpose of this paper is to provide a novel approach that integrates analytical insights from both the perceptions of SDM stakeholders and software development tools logs to provide SDM improvement recommendations. This paper develops a new process improvement approach that combines two significantly different sources of data on the same phenomenon. First, it uses a questionnaire to gather software development stakeholder SDM perceptions (managers and developers). Second, it leverages process mining to analyze software development tools logs to obtain additional information on software development activities. Finally, it develops recommendations based on concurrent analysis of both sources. Our novel process improvement approach is evaluated in three directions: Does the presented approach (RQ1) enable managers to gain additional insights into employees' performance, (RQ2) deliver additional insights into project performance, and (RQ3) enable development of additional SDM improvement recommendations? We find that integrated analysis of software development perception data and software development tools logs opens new possibilities to more precisely identify and improve specific SDM elements. The evaluation of our novel process improvement approach follows a single case study design. Our approach can only be used in enterprises in which software development tools logs are available. The study should be repeated in different cultural settings. We practically show how concurrently analyzing data about developer SDM perceptions and event log data from software development tools enables management to gain additional insights in the software development process regarding the performance of individual developers. The main theoretical contribution of our paper is a novel process improvement approach that effectively integrates data from management and developer perspectives and software development tools logs.

Users of information systems are the weakest link in information security. Considering their current information security performance is essential for improving information security training. User segmentation can help to improve information security training by dividing users into smaller groups based on their information security performance. In this paper, we present a segmented approach for information security training of users. To test the approach, we used data collected from students at a Slovenian university (N=165) with the Human Aspects of Information Security Questionnaire (HAIS-Q). HAIS-Q data was used to divide users into groups according to their information security performance via clustering. The proposed approach inherently balances adaptation of training to the needs of users and the efforts needed to achieve it which maximizes the key benefits of existing information security training approaches. With improved personalization, it mitigates the challenges related to training boringness and lack of user motivation which are emblematic for traditional information security training approaches. The proposed approach also offers some flexibility regarding the degree of personalization and the efforts related to information security training by fine-tuning the number of user groups. Finally, the proposed approach can help to identify beneficial software security requirements during development of new information systems.

This work reports on a cross-sectional study on device proficiency, support availability and cybersecurity competence of older adult users of smartphones and/or tablets. Results indicate that cybersecurity competence is associated with both device proficiency and support availability although the variance explained is relatively low. There were no differences in cybersecurity competence between users and non-users of either mobile devices. Users of both smartphones and tablets had significantly higher device proficiency than non-users. Users of tablets had significantly higher support availability than non-users while there were no significant differences between users and non-users of smartphones.