Search results for: precision feed

Authors: Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung

Abstract:

Lightweight unmanned aerial vehicle (UAV) loading with novel sensors offers a low cost approach for data acquisition in complex environment. This study established a framework for applying UAV system in complex environment quick mapping and assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area Mai Po Inner Deep Bay Ramsar Site, Hong Kong. The study area was part of shallow bay with flat terrain and the major species including reedbed and four mangroves: Kandelia obovata, Aegiceras corniculatum, Acrostichum auerum and Acanthus ilicifolius. Other species involved in various graminaceous plants, tarbor, shrub and invasive species Mikania micrantha. In particular, invasive species climbed up to the mangrove canopy caused damage and morphology change which might increase species distinguishing difficulty. Hyperspectral images were acquired by Headwall Nano sensor with spectral range from 400nm to 1000nm and 0.06m spatial resolution image. A sequence of multi-view RGB images was captured with 0.02m spatial resolution and 75% overlap. Hyperspectral image was corrected for radiative and geometric distortion while high resolution RGB images were matched to generate maximum dense point clouds. Furtherly, a 5 cm grid digital surface model (DSM) was derived from dense point clouds. Multiple feature reduction methods were compared to identify the efficient method and to explore the significant spectral bands in distinguishing different species. Examined methods including stepwise discriminant analysis (DA), support vector machine (SVM) and minimum noise fraction (MNF) transformation. Subsequently, spectral subsets composed of the first 20 most importance bands extracted by SVM, DA and MNF, and multi-source subsets adding extra DSM to 20 spectrum bands were served as input in maximum likelihood classifier (MLC) and SVM classifier to compare the classification result. Classification results showed that feature reduction methods from best to worst are MNF transformation, DA and SVM. MNF transformation accuracy was even higher than all bands input result. Selected bands frequently laid along the green peak, red edge and near infrared. Additionally, DA found that chlorophyll absorption red band and yellow band were also important for species classification. In terms of 3D data, DSM enhanced the discriminant capacity among low plants, arbor and mangrove. Meanwhile, DSM largely reduced misclassification due to the shadow effect and morphological variation of inter-species. In respect to classifier, nonparametric SVM outperformed than MLC for high dimension and multi-source data in this study. SVM classifier tended to produce higher overall accuracy and reduce scattered patches although it costs more time than MLC. The best result was obtained by combining MNF components and DSM in SVM classifier. This study offered a precision species distribution survey solution for inaccessible wetland area with low cost of time and labour. In addition, findings relevant to the positive effect of DSM as well as spectral feature identification indicated that the utility of UAV-borne hyperspectral and photogrammetry deriving 3D data is promising in further research on wetland species such as bio-parameters modelling and biological invasion monitoring.

Keywords: digital surface model (DSM), feature reduction, hyperspectral, photogrammetric point cloud, species mapping, unmanned aerial vehicle (UAV)

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Authors: Riccardo Fratini, Riccardo Santini, Jacopo Serafini, Massimo Gennaretti, Stefano Panzieri

Abstract:

This paper presents a nonlinear differential model, for a three-bladed horizontal axis wind turbine (HAWT) suited for control applications. It is based on a 8-dofs, lumped parameters structural dynamics coupled with a quasi-steady sectional aerodynamics. In particular, using the Euler-Lagrange Equation (Energetic Variation approach), the authors derive, and successively validate, such model. For the derivation of the aerodynamic model, the Greenbergs theory, an extension of the theory proposed by Theodorsen to the case of thin airfoils undergoing pulsating flows, is used. Specifically, in this work, the authors restricted that theory under the hypothesis of low perturbation reduced frequency k, which causes the lift deficiency function C(k) to be real and equal to 1. Furthermore, the expressions of the aerodynamic loads are obtained using the quasi-steady strip theory (Hodges and Ormiston), as a function of the chordwise and normal components of relative velocity between flow and airfoil Ut, Up, their derivatives, and section angular velocity ε˙. For the validation of the proposed model, the authors carried out open and closed-loop simulations of a 5 MW HAWT, characterized by radius R =61.5 m and by mean chord c = 3 m, with a nominal angular velocity Ωn = 1.266rad/sec. The first analysis performed is the steady state solution, where a uniform wind Vw = 11.4 m/s is considered and a collective pitch angle θ = 0.88◦ is imposed. During this step, the authors noticed that the proposed model is intrinsically periodic due to the effect of the wind and of the gravitational force. In order to reject this periodic trend in the model dynamics, the authors propose a collective repetitive control algorithm coupled with a PD controller. In particular, when the reference command to be tracked and/or the disturbance to be rejected are periodic signals with a fixed period, the repetitive control strategies can be applied due to their high precision, simple implementation and little performance dependency on system parameters. The functional scheme of a repetitive controller is quite simple and, given a periodic reference command, is composed of a control block Crc(s) usually added to an existing feedback control system. The control block contains and a free time-delay system eτs in a positive feedback loop, and a low-pass filter q(s). It should be noticed that, while the time delay term reduces the stability margin, on the other hand the low pass filter is added to ensure stability. It is worth noting that, in this work, the authors propose a phase shifting for the controller and the delay system has been modified as e^(−(T−γk)), where T is the period of the signal and γk is a phase shifting of k samples of the same periodic signal. It should be noticed that, the phase shifting technique is particularly useful in non-minimum phase systems, such as flexible structures. In fact, using the phase shifting, the iterative algorithm could reach the convergence also at high frequencies. Notice that, in our case study, the shifting of k samples depends both on the rotor angular velocity Ω and on the rotor azimuth angle Ψ: we refer to this controller as a spatial repetitive controller. The collective repetitive controller has also been coupled with a C(s) = PD(s), in order to dampen oscillations of the blades. The performance of the spatial repetitive controller is compared with an industrial PI controller. In particular, starting from wind speed velocity Vw = 11.4 m/s the controller is asked to maintain the nominal angular velocity Ωn = 1.266rad/s after an instantaneous increase of wind speed (Vw = 15 m/s). Then, a purely periodic external disturbance is introduced in order to stress the capabilities of the repetitive controller. The results of the simulations show that, contrary to a simple PI controller, the spatial repetitive-PD controller has the capability to reject both external disturbances and periodic trend in the model dynamics. Finally, the nominal value of the angular velocity is reached, in accordance with results obtained with commercial software for a turbine of the same type.

Keywords: wind turbines, aeroelasticity, repetitive control, periodic systems

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Authors: Ali Kazemi

Abstract:

Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: C. M. Kalleshwaraswamy, G. S. Sathisha, A. S. Vidyashree, H. B. Pavithra

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Isoptera are an interesting group of social insects with different castes and division of labour. They are primarily wood-feeders, but also feed on a variety of other organic substrates, such as living trees, leaf litter, soil, lichens and animal faeces. The number of species and their biomass are especially large in tropics. In natural ecosystems, they perform a beneficial role in nutrient cycles by accelerating decomposition. The magnitude and dimension of ecological role played by termites is a function of their diversity, population density, and biomass. Termite assemblage composition has a strong response to habitat disturbance and may be indicative of quantitative changes in the decomposition process. Many previous studies in Western Ghat region of India suggest increased anthropogenic activities that adversely affect the soil macrofauna and diversity. Shivamogga district provides a good opportunity to study the effect of topography, cropping pattern, human disturbance on the termite fauna, thereby acquiring accurate baseline information for conservation decision making. The district has 3 distinct agro-ecological areas such as maidan area, semi-malnad and Western Ghat region. Thus, the district provides a unique opportunity to study the effect of varied climate and anthropogenic disturbance on the termite diversity. The standard protocol of belt transects method developed by Eggleton et al. (1997) was used for sampling termites. Sampling was done at monthly interval from September-2014 to August-2015 in Western Ghats, semi-malnad and maidan habitats. The transect was 100m long and 2m wide and divided into 20 contiguous sections, each 5 x 2m in each habitat. Within each section, all the probable microhabitats of termites were searched, which include dead logs, fallen tree, branch, sticks, leaf litter, vegetation etc.,. All the castes collected were labelled, preserved in 80% alcohol, counted and identified to species level. The number of encounters of a species in the transect was used as an indicator of relative abundance of species. The species diversity, species richness, density were compared in three different habitats such as Western Ghats, semi-malnad and maidan region. The study indicated differences in the species composition in the three different habitats. A total of 15 species were recorded which belonging to four sub family and five genera in three habitats. Eleven species viz., Odontotermes obesus, O. feae, O. anamallensis, O. bellahunisensis, O. adampurensis, O. boveni, Microcerotermes fletcheri, M. pakistanicus, Nasutitermes anamalaiensis, N. indicola, N. krishna were recorded in Western Ghat region. Similarly, 11 species viz., Odontotermes obesus, O. feae, O. anamallensis, O. bellahunisensis, O. hornii, O. bhagwathi, Microtermes obesi, Microcerotermes fletcheri, M. pakistanicus, Nasutitermes indicola and Pericapritermes sp. were recorded in semi-malnad habitat. However, only four species viz., O. obesus, O. feae, Microtemes obesi and Pericapritermes sp. species were recorded in maidan area. Shannon’s wiener diversity index (H) showed that Western Ghats had more species dominance (1.56) followed by semi- malnad (1.36) and lowest in maidan (0.89) habitats. Highest value of simpson’s index (D) was observed in Western Ghats habitat (0.70) with more diverse species followed by semi-malnad (0.58) and lowest in maidan (0.53). Similarly, evenness was highest (0.65) in Western Ghats followed by maidan (0.64) and least in semi-malnad habitat (0.54). Menhinick’s index (Dmn) value was ranging from 0.03 to 0.06 in different habitats in the study area. Highest index was observed in Western Ghats (0.06) followed by semi-malnad (0.05) and lowest in maidan (0.03). The study conclusively demonstrated that Western Ghat had highest species diversity compared to semi-malnad and maidan habitat indicating these two habitats are continuously subjected to anthropogenic disturbances. Efforts are needed to conserve the uncommon species which otherwise may become extinct due to human activities.

Keywords: anthropogenic disturbance, isoptera, termite species diversity, Western ghats

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Authors: Krystian Szczepanski, Sylwia Łaba

Abstract:

Production of fruit and vegetables, food cereals or oilseeds affects the natural environment via intake of nutrients being contained in the soil, use of the resources of water, fertilizers and food protection products, and energy. The limitation of the mentioned effects requires the introduction of techniques and methods for cultivation being friendly to the environment and counteracting losses and waste of agricultural raw materials as well as the appropriate management of food waste in every stage of the agri-food supply chain. The link to basic production includes obtaining a vegetal raw material and its storage in agricultural farm and transport to a collecting point. When the plants are ready to be harvested is the initial point; the stage before harvesting is not considered in the system of measuring and monitoring the food losses. The moment at which the raw material enters the stage of processing, i.e., its receipt at the gate of the processing plant, is considered as a final point of basic production. According to the Regulation (EC) No 178/2002 of the European Parliament and of the Council of 28 January 2002, Art. 2, “food” means any substance or product, intended to be, or reasonably expected to be consumed by humans. For the needs of the studies and their analysis, it was determined when raw material is considered as food – the plants (fruit, vegetables, cereals, oilseeds), after being harvested, arrive at storehouses. The aim of the studies was to determine the reasons for loss generation and to analyze the directions of their management in basic vegetal production in Poland in the years 2017 and 2018. The studies on food losses and waste in basic vegetal production were carried out in three sectors – fruit and vegetables, cereals and oilseeds. The studies of the basic production were conducted during the period of March-May 2019 at the territory of the whole country on a representative trail of 250 farms in each sector. The surveys were carried out using the questionnaires by the PAP method; the pollsters conducted the direct questionnaire interviews. From the conducted studies, it is followed that in 19% of the examined farms, any losses were not recorded during preparation, loading, and transport of the raw material to the manufacturing plant. In the farms, where the losses were indicated, the main reason in production of fruit and vegetables was rotting and it constituted more than 20% of the reported reasons, while in the case of cereals and oilseeds’ production, the respondents identified damages, moisture and pests as the most frequent reason. The losses and waste, generated in vegetal production as well as in processing and trade of fruit and vegetables, or cereal products should be appropriately managed or recovered. The respondents indicated composting (more than 60%) as the main direction of waste management in all categories. Animal feed and landfill sites were the other indicated directions of management. Prevention and minimization of loss generation are important in every stage of production as well as in basic production. When possessing the knowledge on the reasons for loss generation, we may introduce the preventive measures, mainly connected with the appropriate conditions and methods of the storage. Production of fruit and vegetables, food cereals or oilseeds affects the natural environment via intake of nutrients being contained in the soil, use of the resources of water, fertilizers and food protection products, and energy. The limitation of the mentioned effects requires the introduction of techniques and methods for cultivation being friendly to the environment and counteracting losses and waste of agricultural raw materials as well as the appropriate management of food waste in every stage of the agri-food supply chain. The link to basic production includes obtaining a vegetal raw material and its storage in agricultural farm and transport to a collecting point. The starting point is when the plants are ready to be harvested; the stage before harvesting is not considered in the system of measuring and monitoring the food losses. The successive stage is the transport of the collected crops to the collecting point or its storage and transport. The moment, at which the raw material enters the stage of processing, i.e. its receipt at the gate of the processing plant, is considered as a final point of basic production. Processing is understood as the change of the raw material into food products. According to the Regulation (EC) No 178/2002 of the European Parliament and of the Council of 28 January 2002, Art. 2, “food” means any substance or product, intended to be, or reasonably expected to be consumed by humans. It was determined (for the needs of the present studies) when raw material is considered as a food; it is the moment when the plants (fruit, vegetables, cereals, oilseeds), after being harvested, arrive at storehouses. The aim of the studies was to determine the reasons for loss generation and to analyze the directions of their management in basic vegetal production in Poland in the years 2017 and 2018. The studies on food losses and waste in basic vegetal production were carried out in three sectors – fruit and vegetables, cereals and oilseeds. The studies of the basic production were conducted during the period of March-May 2019 at the territory of the whole country on a representative trail of 250 farms in each sector. The surveys were carried out using the questionnaires by the PAPI (Paper & Pen Personal Interview) method; the pollsters conducted the direct questionnaire interviews. From the conducted studies, it is followed that in 19% of the examined farms, any losses were not recorded during preparation, loading, and transport of the raw material to the manufacturing plant. In the farms, where the losses were indicated, the main reason in production of fruit and vegetables was rotting and it constituted more than 20% of the reported reasons, while in the case of cereals and oilseeds’ production, the respondents identified damages, moisture, and pests as the most frequent reason. The losses and waste, generated in vegetal production as well as in processing and trade of fruit and vegetables, or cereal products should be appropriately managed or recovered. The respondents indicated composting (more than 60%) as the main direction of waste management in all categories. Animal feed and landfill sites were the other indicated directions of management. Prevention and minimization of loss generation are important in every stage of production as well as in basic production. When possessing the knowledge on the reasons for loss generation, we may introduce the preventive measures, mainly connected with the appropriate conditions and methods of the storage. ACKNOWLEDGEMENT The article was prepared within the project: "Development of a waste food monitoring system and an effective program to rationalize losses and reduce food waste", acronym PROM implemented under the STRATEGIC SCIENTIFIC AND LEARNING PROGRAM - GOSPOSTRATEG financed by the National Center for Research and Development in accordance with the provisions of Gospostrateg1 / 385753/1/2018

Keywords: food losses, food waste, PAP method, vegetal production

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