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Keywords: environmentally friendly, mechanical properties, micro-structural analysis, sisal fibre
Published in DiRROS: 20.06.2025; Views: 489; Downloads: 264
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Keywords: nanofluids, silver nanoparticles, heat transfer, nanosphere/nanocube comparison, heat pipe optimization
Published in DiRROS: 19.06.2025; Views: 537; Downloads: 257
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Abstract: The article summarizes the research topics published in this special issue. The pa- pers in this issue are based on the selected and peer-reviewed papers from the 17th International Symposium on Operations Research in Slovenia – SOR’23, which took place in Bled, Slovenia (https://arhiv.fov.um.si/sor23/), September 20–22, 2023. In addition, we examined the 27 research papers in the last two SSI-SOR CEJOR special issues, 16 in the Cent Eur J Oper Res 31, issue 3, 2023, and 11 in this CEJOR special issue, and grouped them into clusters using keywords ac- cording to the methodology published by Kastrin et al. (2021) Methodologies and applications for resilient global development from the aspect of SDI-SOR. The clusters show the main and niche topics presented and, on the one hand, illustrate the European and international state of the art in the field of OR over the last five years and, on the other hand, can serve as a stimulus for further work on upcoming strategic OR topics.
Keywords: operations research, SOR conferences, Slovenia, cluster analysis
Published in DiRROS: 19.06.2025; Views: 426; Downloads: 272
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Abstract: Skin cancer is a severe and rapidly advancing condition that can be impacted by multiple factors, including alcohol and tobacco use, allergies, infections, physical activity, exposure to UV light, viral infections, and the effects of climate change. While the steep death tolls continue rising at an alarming rate, lack of symptoms recognition and its preventive measures further worsen the case. In this article, we employ the ISBI-2017 dataset to present an improved FrCN-based hybrid image segmentation method with U-Net to improve detection performance. This paper proposes a hybrid approach using the FrCN-(U-Net) image segmentation technique to enhance results compared to an advanced method for detecting skin cancer types, such as Benign or Melanoma. The classification phase is then handled using the R-CNN algorithm. Our model shows better performance in both training and testing accuracy than any other existing approaches. The results show that the combined method is effective in enhancing early disease diagnosis, which in turn improves treatment outcomes and prognosis. This paper presents an alternative technique for skin cancer detection, which can serve as a guide for clinical practices and public health strategies on how to lower skin-cancer-related deaths.
Keywords: skin tumors, cutaneous melanoma, lesions, imaging techniques, cancel detection and diagnosis, melanoma, preprocessing, melignant tumors
Published in DiRROS: 19.06.2025; Views: 470; Downloads: 272
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Abstract: This study investigates the influence of input values for building energy model parameters on simulation results, with the aim of improving the reliability and sustainability of energy performance assessments. Dynamic simulations were conducted in TRNSYS for three theoretical multi-residential buildings, varying parameters such as referent model dimensions, infiltration rates, envelope thermophysical properties, and interior thermal capacitance. The case study, based in Slovenia, demonstrates that glazing-related parameters, particularly the solar heat gain coefficient (g-value), exert the most significant influence—reducing the g-value from 0.62 to 0.22 decreased simulated heating (qH,nd) and cooling (qC,nd) demands by 25% and 95%, respectively. In contrast, referent dimensions for modeled floor area proved least influential. For Building III (BSF = 0.36), dimensional variations altered results by less than ±1%, whereas, for Building I (BSF = 0.62), variations reached up to ±20%. In general, lower shape factors yield more robust energy models that are less sensitive to input deviations. These findings are critical for promoting resource-efficient simulation practices and ensuring that energy modeling contributes effectively to sustainable building design. Understanding which inputs warrant detailed attention supports more targeted and meaningful simulation workflows, enabling more accurate and impactful strategies for building energy efficiency and long-term environmental performance.
Keywords: building energy modeling, dynamic simulation, TRNSYS, envelope modeling parameters, building energy performance
Published in DiRROS: 19.06.2025; Views: 486; Downloads: 309
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