156 research outputs found

    Greenfield FDI attractiveness index: a machine learning approach

    Get PDF
    This study aims to propose a comprehensive greenfield foreign direct investment (FDI) attractiveness index using exploratory factor analysis and automated machine learning (AML). We offer offer a robust empirical measurement of location-choice factors identified in the FDI literature through a novel method and provide a tool for assessing the countries' investment potential.publishedVersionPaid open acces

    Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

    Get PDF
    Smart networks such as active distribution network (ADN) and microgrid (MG) play an important role in power system operation. The design and implementation of appropriate protection systems for MG and ADN must be addressed, which imposes new technical challenges. This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks (NNs) and multiple sampling points for ADN and MG. The solution is implemented on an edge device. NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure. Multiple sampling points are used to derive a data-driven model, which allows the generalization considering the implementation in physical systems. The adaptive fault detector model is implemented on a Jetson Nano system, which is a single-board computer (SBC) with a small graphic processing unit (GPU) intended to run machine learning loads at the edge. The proposed method is tested in a physical, real-life, low-voltage network located at Universidad del Norte, Colombia. This testing network is based on the IEEE 13-node test feeder scaled down to 220 V. The validation in a simulation environment shows the accuracy and dependability above 99.6%, while the real-time tests show the accuracy and dependability of 95.5% and 100%, respectively. Without hard-to-derive parameters, the easy-to-implement embedded model highlights the potential for real-life applications. © 2013 State Grid Electric Power Research Institute

    Flexural strength of high-performance soil-cement: a new, alternative, sustainable construction material

    Get PDF
    Soil-cement is a building material that is considered low-cost and has a low environmental impact. Despite its benefits, performance optimisation studies are scarce compared to other materials such as concrete. The possibility of obtaining soil-cement with improved characteristics, such as flexural strength, would enable the increased use of this product in new applications in construction. The aim of this study is to produce high-performance soil-cement (HPSC) specimens and to evaluate and compare this new material with high-performance concrete (HPC) in terms of flexural strength. A total of 12 specimens were produced with a mixture of 23.5% (by mass) of cement with the application of 10 MPa of pressure for its compaction. The results show that, at 28 days, the specimens reached an average strength of 6.73 MPa and, at 240 days, 12.34 MPa. This means that the HPSC reached a flexural strength resistance equivalent to HPC without the need for mined materials, such as sand and gravel, or the additives adopted in some doses of HPC, such as superplasticisers. Therefore, when using local soil, HPSC can be considered an environmentally preferable alternative to HPC for many construction applications where flexural strength is a requirement.Peer ReviewedPostprint (published version

    A Novel Technique to Label Cover Crop Biomass Using Stable Isotopes

    Get PDF
    Stable isotopes can be used as tracers for carbon and nitrogen pathways being a great tool to track nutrients in integrated systems. The objective of this experiment was to understand the partitioning of 15N and 13C within cover crop plants when they were labeled with stable isotopes, using chambers under field conditions. Cover crops were planted at the University of Florida, North Florida Research and Education Center-Marianna, located in Marianna, FL. Treatments were four cover crops, in which one was considered a typical cover crop system and the other three consisted of an integrated crop-livestock system with or without the inclusion of legume or different nitrogen fertilizer rates grazed every two weeks. All treatments were replicated three times in a randomized complete block design. Two chambers were built and placed in each plot to label the cover crop plants. For the 15N labeling, 15N2-labeled urea (98 atom% 15N) was applied at a rate of 0.5 kg N ha-1 only once. The target amount of 13CO2 (99 atom% 13C) was determined considering a 20% enrichment of the CO2 concentration present inside the chamber’s volume. The 13CO2 labeling was performed for 28 consecutive days. The labeling technique using chambers and stable isotopes to enrich cover crop species worked under field conditions for both, grass and legume species. Moving forward, this labeling technique can be a useful tool to track nutrient pathways, especially litter decomposition in diversified integrated crop and livestock systems under different management practices

    Evaluation of a long-established silvopastoral Brachiaria decumbens system: plant characteristics and feeding value for cattle.

    Get PDF
    Abstract One of the main challenges of using a silvopastoral system (SPS) is maintaining pasture and animal productivity over time. Our objective was to compare the productive characteristics and nutritive value of signal grass (Brachiaria decumbens cv. Basilisk) and the liveweight gain of dairy heifers in a SPS and open pasture (OP, signal grass under full sunlight) during the rainy seasons of four experiments between 2003 and 2016, which characterised systems from their 6th to 19th years after establishment in south-eastern Brazil when analysed together. The experimental design was a randomised complete block in a 2 4 factorial scheme (two production systems (SPS and OP) and four experiments (2003?2004, 2004?2007, 2011?2014 and 2014?2016)). From the 7th year onwards, the progressive reduction of photosynthetically active radiation negatively impacted the productive characteristics of the SPS pasture. Total forage mass was reduced by 19% in SPS compared with the OP in 2004?2007, 38% in 2011?2014 and 31% in 2014?2016. Crude protein content was 23%and30%higher in theSPSthan in theOPin 2011?2014 and 2014?2016, respectively. However, during the study period (until the 19th year), the liveweight gain of heifers was similar between systems since the higher crude protein content available in SPS contributed to improved forage nutritional value. From the 17th to the 19th year, weight gain per area was lower in the SPS compared with the OP (169 vs 199 kg ha?1), although the difference between systems was small. Signal grass presents a high degree of phenotypic plasticity in response to changes in shade levels, which gives this species a high potential for use in SPS

    Masonry dams : analysis of the historical profiles of Sazilly, Delocre and Rankine

    Get PDF
    The significant advances in masonry dam design that took place in the second half of the 19th century are analyzed and discussed within the context of the historical development of dam construction. Particular reference is made to the gravity dam profiles proposed by Sazilly, Delocre and Rankine, who pioneered the application of engineering concepts to dam design, basing the dam profile on the allowable stresses for the conditions of empty and full reservoir. These historical profiles are analyzed taking into consideration the present safety assessment procedures, by means of a numerical application developed for this purpose, based on limit analysis equilibrium methods, which considers the sliding failure mechanisms, the most critical for these structures. The study underlines the key role of uplift pressures, which was only addressed by Lévy after the accident of Bouzey dam, and provides a critical understanding of the original design concepts, which is essential for the rehabilitation of these historical structures.This work has been funded by FCT (Portuguese Foundation for Science and Technology) through the PhD grant SFRH/BD/43585/2008, for which the first author is grateful

    Prediction of aboveground biomass and dry-matter content in brachiaria pastures by combining meteorological data and satellite imagery.

    Get PDF
    Aboveground biomass (AGB) data are important for profitable and sustainable pasture management. In this study, we hypothesized that vegetation indexes (VIs) obtained through analysis of moderate spatial resolution satellite data (Landsat-8 and Sentinel-2) and meteorological data can accurately predict the AGB of Brachiaria (syn. Urochloa) pastures in Brazil. We used AGB field data obtained from pastures between 2015 and 2019 in four distinct regions of Brazil to evaluate (i) the relationship between three different VIs?normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2) and optimized soil adjusted vegetation index (OSAVI)?and meteorological data with pasture aboveground fresh biomass (AFB), aboveground dry biomass (ADB) and dry-matter content (DMC); and (ii) the performance of simple linear regression (SLR), multiple linear regression (MLR) and random forest (RF) algorithms for the prediction of pasture AGB based on VIs obtained through satellite imagery combined with meteorological data. The results highlight a strong correlation (r) between VIs and AGB, particularly NDVI (r = 0.52 to 0.84). The MLR and RF algorithms demonstrated high potential to predict AFB (R2 = 0.76 to 0.85) and DMC (R2 = 0.78 to 0.85). We conclude that both MLR and RF algorithms improved the biomass prediction accuracy using satellite imagery combined with meteorological data to determine AFB and DMC, and can be used for Brachiaria (syn. Urochloa) AGB prediction. Additional research on tropical grasses is needed to evaluate different VIs to improve the accuracy of ADB prediction, thereby supporting pasture management in Brazil
    corecore