3. Producción

Browse

Settings

Access type: UnknownSubject: search.filters.subject.Artificial intelligence (AI)

Search Results

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Generating high-resolution climate data in the Andes using artificial intelligence: A lightweight alternative to the WRF model
    (Elsevier BV, 2025-12-01)
    In weather forecasting, generating atmospheric variables for regions with complex topography, such as the Andean regions with peaks reaching 6500 m above sea level, poses significant challenges. Traditional regional climate models often struggle to accurately represent the atmospheric behavior in such areas. Furthermore, the capability to produce high spatio-temporal resolution data (less than 27 km and hourly) is limited to a few institutions globally due to the substantial computational resources required. This study presents the results of atmospheric data generated using a new type of artificial intelligence (AI) models, aimed to reduce the computational cost of generating downscaled climate data using climate regional models like the Weather Research and Forecasting (WRF) model over the Andes. The WRF model was selected for this comparison due to its frequent use in simulating atmospheric variables in the Andes. Our results demonstrate a higher downscaling performance for the four target weather variables studied (temperature, relative humidity, zonal and meridional wind) over coastal, mountain, and jungle regions. Moreover, this AI model offers several advantages, including lower computational costs compared to dynamic models like WRF and continuous improvement potential with additional training data. • We propose an AI model to generate high-resolution climate data. • The model, based on ConvLSTM, predicts temperature, humidity, and wind accurately. • It runs up to 18× faster than WRF with lower memory and storage needs. • It shows promising accuracy across regions with varied topography and climate. • This approach offers an efficient alternative for climate modeling in low-resource areas.
      7
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Enabling women entrepreneurs through digital transformation: a business process technology perspective from emerging economies
    (Emerald Publishing Limited, 2026-01-01)
    This study examines how women entrepreneurs in emerging economies can optimize business processes through the adoption of digital technologies, using Business Process Technology (BPT) as a conceptual framework. It explores patterns of technology use, perceived barriers and opportunities that inform the design of differentiated training programs to foster inclusion and digital transformation. Design/methodology/approach A sequential exploratory mixed-method design was employed. Quantitative data were collected through a survey of 131 women entrepreneurs participating in the program Mujer, que tu negocio crezca más (Woman, Make Your Business Grow) across six regions of Peru. This phase enabled the identification of digital adoption profiles. Qualitative data from six focus groups complemented these findings by exploring how digital tools are embedded within administrative, commercial, and financial processes, as well as the contextual and gendered conditions shaping their adoption. Findings The findings reveal uneven digital maturity, characterized by (1) high adoption of social networks and digital communication channels, contrasted with limited use of financial and e-commerce platforms; (2) a higher level of digital maturity among entrepreneurs who operate a website; (3) the identification of two technology adoption profiles and (4) a comprehensive assessment of business processes that informed the design of a BPT-based training model grounded in the principles of integration, modeling and automation. Practical implications The results provide guidance for designing inclusive training programs that strengthen digital skills, promote gender equity, and contribute to achieving the Sustainable Development Goals. Originality/value The study integrates BPT theory with empirical evidence on women's entrepreneurship, proposing a process-oriented training model adaptable to similar contexts in emerging economies.