Iskanje po katalogu digitalne knjižnice

Opis: Background/Objectives: Identifying and decomposing compound ingredients within meal plans presents meal customization and nutritional analysis challenges. It is essential for accurately identifying and replacing problematic ingredients linked to allergies or intolerances and helping nutritional evaluation. Methods: This study explored the effectiveness of three large language models (LLMs)—GPT-4o, Llama-3 (70B), and Mixtral (8x7B), in decomposing compound ingredients into basic ingredients within meal plans. GPT-4o was used to generate 15 structured meal plans, each containing compound ingredients. Each LLM then identified and decomposed these compound items into basic ingredients. The decomposed ingredients were matched to entries in a subset of the USDA FoodData Central repository using API-based search and mapping techniques. Nutritional values were retrieved and aggregated to evaluate accuracy of decomposition. Performance was assessed through manual review by nutritionists and quantified using accuracy and F1-score. Statistical significance was tested using paired t-tests or Wilcoxon signed-rank tests based on normality. Results: Results showed that large models—both Llama-3 (70B) and GPT-4o—outperformed Mixtral (8x7B), achieving average F1-scores of 0.894 (95% CI: 0.84–0.95) and 0.842 (95% CI: 0.79–0.89), respectively, compared to an F1-score of 0.690 (95% CI: 0.62–0.76) from Mixtral (8x7B). Conclusions: The open-source Llama-3 (70B) model achieved the best performance, outperforming the commercial GPT-4o model, showing its superior ability to consistently break down compound ingredients into precise quantities within meal plans and illustrating its potential to enhance meal customization and nutritional analysis. These findings underscore the potential role of advanced LLMs in precision nutrition and their application in promoting healthier dietary practices tailored to individual preferences and needs.
Ključne besede: artificial intelligence, food analysis, LLM, Ilama, GPT, mixtral, ingredient identification, ingredient decomposition, personalized nutrition, meal customization, nutritional analysis, dietary planning
Objavljeno v DKUM: 08.05.2025; Ogledov: 0; Prenosov: 1
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Opis: Mountain resilience is the ability of mountain regions to endure, adapt to, and recover from environmental, climatic, and anthropogenic stressors. Due to their steep topography, extreme weather conditions, and unique biodiversity, these areas are particularly vulnerable to climate change, natural hazards, and human activities. This paper examines how nature-based solutions (NbSs) can strengthen slope stability and geotechnical resilience, with a specific focus on Slovenia’s sub-Alpine regions as a case study representative of the Alps and similar mountain landscapes worldwide. The proposed Climate-Adaptive Resilience Evaluation (CARE) concept integrates geomechanical analysis with geotechnical planning, addressing the impacts of climate change through a systematic causal chain that connects climate hazards, their effects, and resulting consequences. Key factors such as water infiltration, soil permeability, and groundwater dynamics are identified as critical elements in designing timely and effective NbSs. In scenarios where natural solutions alone may be insufficient, hybrid solutions (HbSs) that combine nature-based and conventional engineering methods are highlighted as essential for managing unstable slopes and restoring collapsed geostructures. The paper provides practical examples, including slope stability analyses and reforestation initiatives, to illustrate how to use the CARE concept and how NbSs can mitigate geotechnical risks and promote sustainability. By aligning these approaches with regulatory frameworks and climate adaptation objectives, it underscores the potential for integrating NbSs and HbSs into comprehensive, long-term geotechnical strategies for enhancing mountain resilience.
Ključne besede: mountain resilience, climate change, nature-based solutions (NbSs), hybrid solutions (HbSs), geotechnical planning, slope stability, landslides
Objavljeno v DKUM: 31.03.2025; Ogledov: 0; Prenosov: 6
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Opis: Streets with an increasingly important place function play a significant role in the contemporary discourse on sustainable cities. The paper addresses urban streets that, observed from the urban planning perspective, have the potential to be transformed into either commercial or residential shared streets. After defining urban planning parameters identified as characteristic of shared streets, streets were quantified based on an analysis of the existing shared streets in Central Europe. By setting up distinctive scenarios that could help to detect specific types of streets, open spatial datasets were used for the mapping and identification of streets that could be transformed into shared streets. The methodology was tested on the example of the city of Maribor in Slovenia. The results of the research show that the selected urban planning parameters can help to identify streets with transformation potential, whereas the basic parameters, such as the building use and the length and width of the street, help us to better understand the urban fabric in which street spaces acquire new functions. The presented mapping method could serve as a testing tool for experts, planners, decision-makers, and the interested public to identify potential street transformations.
Ključne besede: street transformation potential, urban planning parameters, mapping, shared space, shared streets, open spatial datasets, GIS
Objavljeno v DKUM: 13.03.2025; Ogledov: 0; Prenosov: 4
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Opis: Prompt administration of radiotherapy (RT) is one of the most effective treatments against cancer. Eachday, the radiotherapy departments of large hospitals must plan numerous irradiation sessions, con-sidering the availability of human and material resources, such as healthcare professionals and linearaccelerators. With the increasing number of patients suffering from different types of cancers, manuallyestablishing schedules following each patient’s treatment protocols has become an extremely difficultand time-consuming task. We propose an optimization algorithm that automatically schedules andgenerates patient appointments. The model can rearrange fixed appointments to accommodate urgentcases, enabling hospitals to schedule appointments more efficiently. It respects the different treatment Prompt administration of radiotherapy (RT) is one of the most effective treatments against cancer. Eachday, the radiotherapy departments of large hospitals must plan numerous irradiation sessions, con-sidering the availability of human and material resources, such as healthcare professionals and linearaccelerators. With the increasing number of patients suffering from different types of cancers, manuallyestablishing schedules following each patient’s treatment protocols has become an extremely difficultand time-consuming task. We propose an optimization algorithm that automatically schedules andgenerates patient appointments. The model can rearrange fixed appointments to accommodate urgentcases, enabling hospitals to schedule appointments more efficiently. It respects the different treatment.
Ključne besede: appointments, hospital management, optimization algorithm, patient satisfaction, planning, radiotherapy
Objavljeno v DKUM: 25.02.2025; Ogledov: 0; Prenosov: 8
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Opis: There has been a global plummeting trend of failure in most manufacturing Small and Medium Enterprises (SMEs) due to purported supply chain inefficiency. It is imperative for clothing manufacturing SMEs in developing nations like Zimbabwe, with reference to Bulawayo Province, which lacks digitization to integrate Information and Communication Technology (ICT) solutions into their supply chain operations to improving efficiency and maintain competitiveness in the global market. Thus, the purpose of the study was to evaluate ICT and supply chain efficiency in the clothing manufacturing SMEs in Bulawayo Province. Employing the pragmatic approach, data were collected using semi-structured questionnaires from a sample of 107 from a total population of 147 that were triangulated with 15 interviews from clothing manufacturing SMEs in Bulawayo. A simple linear regression analysis through Ordinary Least Squares was conducted to test the relationship between ICT and supply chain efficiency. The results show that ICT has a positive and statistically significant effect on cost performance, agility and delivery performance in Bulawayo clothing manufacturing SMEs. By prioritizing ICT adoption, managers can achieve better cost management, increased responsiveness to market demands, and enhanced delivery capabilities. It is recommended that clothing manufacturing SMEs in Bulawayo should embrace the ICT. Further studies should examine the relationship between ICT and supply chain efficiency in manufacturing SMEs across different industries and nations.
Ključne besede: information and communication technology, supply chain efficiency, SMEs (small and medium enterprises), material requirement planning
Objavljeno v DKUM: 17.12.2024; Ogledov: 0; Prenosov: 5
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