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Abstract: Reporting the empirical results of swarm and evolutionary computation algorithms is a challenging task with many possible difficulties. These difficulties stem from the stochastic nature of such algorithms, as well as their inability to guarantee an optimal solution in polynomial time. This research deals with measuring the performance of stochastic optimization algorithms, as well as the confidence intervals of the empirically obtained statistics. Traditionally, the arithmetic mean is used for measuring average performance, but we propose quantiles for measuring average, peak and bad-case performance, and give their interpretations in a relevant context for measuring the performance of the metaheuristics. In order to investigate the differences between arithmetic mean and quantiles, and to confirm possible benefits, we conducted experiments with 7 stochastic algorithms and 20 unconstrained continuous variable optimization problems. The experiments showed that median was a better measure of average performance than arithmetic mean, based on the observed solution quality. Out of 20 problem instances, a discrepancy between the arithmetic mean and median happened in 6 instances, out of which 5 were resolved in favor of median and 1 instance remained unresolved as a near tie. The arithmetic mean was completely inadequate for measuring average performance based on the observed number of function evaluations, while the 0.5 quantile (median) was suitable for that task. The quantiles also showed to be adequate for assessing peak performance and bad-case performance. In this paper, we also proposed a bootstrap method to calculate the confidence intervals of the probability of the empirically obtained quantiles. Considering the many advantages of using quantiles, including the ability to calculate probabilities of success in the case of multiple executions of the algorithm and the practically useful method of calculating confidence intervals, we recommend quantiles as the standard measure of peak, average and bad-case performance of stochastic optimization algorithms.
Keywords: algorithmic performance, experimental evaluation, metaheuristics, quantile, confidence interval, stochastic algorithms, evolutionary computation, swarm intelligence, experimental methodology
Published in DKUM: 28.03.2025; Views: 0; Downloads: 7
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Abstract: Purpose – The purpose of this paper is to develop a methodology for shaping the tourist spatial identity of the city and to take advantage of it to discover alternative urban outdoor spaces. As the number of indoor visitors has been limited due to the COVID-19 pandemic, open urban areas such as streets, squares and parks have become more important tourist locations. Design/methodology/approach – The assessment methodology consists of two basic steps. In the first step, the authors look for places or points that are carriers of spatial identity. For this purpose, the method of mental mapping is used. In the second step, statistical methods are used to evaluate the spatial suitability for the most common tourist activities. To obtain a holistic picture, a temporal component is included. Findings – The application of the methodology is presented in the form of a case study. The obtained research results provide an insight into the spatial situation of the city of Maribor (Slovenia, Europe). Tourist spatial identity of a city depends on time. Based on the value of spatial sensitivity indicator and the suitability of activities, it is possible to adapt the tourist offer to the temporal component. Originality/value – To the best of the authors’ knowledge, this is an original perspective on the spatial identity of tourists. The presented approach could be integrated as a good practice in any other city worldwide. It supports the identification of suitable outdoor tourist places that are memorable, cosy, multifunctional and can be recommended by city guides (mobile or printed books). Every city has many hidden gems that tourists have yet to discover
Keywords: urban tourism, evaluation methodology, image of the city, mental mapping, spatial identity
Published in DKUM: 12.03.2025; Views: 0; Downloads: 5
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Abstract: Introduction: The development of a family history (FH) questionnaire (FHQ) provides an insight into a patient's familiarity of a trait and helps to identify individuals at increased risk of disease. A critical aspect of developing a new tool is exploring users' experience. Objective: The objective of this study was to examine users' experience, obstacles and challenges, and their views and concerns in the applicability of a new tool for determining genetic risk in Slovenia's primary care. Methods: We used a qualitative approach. The participants completed a risk assessment software questionnaire that calculates users' likelihood of developing familial diseases. Audio-taped semi-structured telephone interviews were conducted to evaluate their experience. There were 21 participants, and analyses using the constant comparative method were employed. Results: We identified 3 main themes: obstacles/key issues, suggestions for improvements, and coping. The participants were poorly satisfied with the clarity of instructions, technical usability problems, and issues with the entry of relatives' data. They expressed satisfaction with some of the characteristics of the FHQ (e.g., straightforward and friendly format, easy entry, and comprehension). They suggested simpler language, that the disease risk should be targeted toward the disease, that the FHQ should include patient-specific recommendations, and that it should be part of the electronic medical records. When discussing what would they do with the results of the FHQ, the participants used different coping strategies: active (e.g., seeking information) or passive (e.g., avoidance). Discussion/conclusion: User experience was shown to be a synthesis of obstacles, overcoming them with suggestions for improvements, and exploration of various coping mechanisms that may emerge from dealing with the stressor of "being at risk."
Keywords: primary healthcare, family history, qualitative methodology
Published in DKUM: 01.10.2024; Views: 0; Downloads: 4
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Abstract: The manuscript discusses the investigation of vehicle flow in a predesignated junction byan appropriate traffic flow management with an effort to minimize fuel consumption, the productionof CO2, an essential greenhouse gas (hereinafter referred to as GHG), and related transport costs.The particular research study was undertaken in a frequented junction in the city of Celje, located in the eastern part of Slovenia. The results obtained summarize data on consumed fuel and produced CO2 amounts depending on the type of vehicle, traffic flow mixture, traffic light signal plan, andactual vehicle velocity. These values were calculated separately for three different conditions of traffic flow management. Amounts of fuel consumed were experimentally investigated in real traffic situations, whereas CO2 production was calculated by applying the actual European standardentitled EN 16258:2012 associated with a guideline for measuring emission values, as well as by examining specific traffic flow parameters. The key objective of the manuscript is to present multiple scenarios towards striving to minimize environmental impacts and improve transport operation's economic consequences when implementing proper traffic flow management. As for crucial findings, we quantified fuel consumption and CO2 emissions based on real data on the number and type of vehicles crossing the examined intersection and traffic light switching intervals. The results show that most of the CO2 was produced while waiting and in the accelerating phase in front of traffic lights, whereby in the running phase through the intersection, significantly less fuel was used. This study represents a mosaic fragment of research addressing endeavors to reduce CO2 production in urban transport. Following the experiments conducted, we can see a notable contribution towards reducing CO2 production with known and tested interventions in the existing transport infrastructure. A procedure embracing individual research steps may be deemed as an approach methodology dealing with traffic flow management with an aim to decrease the environmental and economic impacts oftraffic and transport operation; this is where the novelty of the research lies.
Keywords: traffic flow management, urban transport, CO2 production, greenhouse gas, fuel consumption, methodology, logistics, crossroads
Published in DKUM: 19.08.2024; Views: 82; Downloads: 9
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Abstract: Three different and very small amounts of alumina (0.2, 0.3 and 0.5 wt. %) in two sizes (approx. 25 and 100 nm) were used to enhance the wear characteristics of ZA-27 alloy-based nanocomposites. Production was realised through mechanical alloying in pre-processing and compocasting processes. Wear tests were under lubricated sliding conditions on a block-on-disc tribometer, at two sliding speeds (0.25 and 1 m/s), two normal loads (40 and 100 N) and a sliding distance of 1000 m. Experimental results were analysed by applying the response surface methodology (RSM) and a suitable mathematical model for the wear rate of tested nanocomposites was developed. Appropriate wear maps were constructed and the wear mechanism is discussed in this paper. The accuracy of the prediction was evaluated with the use of an artificial neural network (ANN). The architecture of the used ANN was 4-5-1 and the obtained overall regression coefficient was 0.98729. The comparison of the predicting methods showed that ANN is more efficient in predicting wear.
Keywords: ZA-27 alloy, Al2O3 nanoparticles, nanocomposites, wear, response surface methodology, artificial neural network
Published in DKUM: 20.03.2024; Views: 239; Downloads: 13
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