The estimation of the CO2 concentration variations due to plants photosynthesis has become a topic of outstanding interest in view of evaluating the carbon footprint of greenhouses and farms. In this context, distribu...
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ISBN:
(纸本)9798350380903;9798350380910
The estimation of the CO2 concentration variations due to plants photosynthesis has become a topic of outstanding interest in view of evaluating the carbon footprint of greenhouses and farms. In this context, distributed sensing solutions can be an alternative to expensive gas analyzers. However, gas sensing can be prone to several criticalities linked to accuracy, stability, and temperature effect. In this paper, a thorough study for the conditioning, the calibration, and the acquisition of an optical sensor for CO2 monitoring is presented. The sensor is integrated in a node thought for greenhouse monitoring and the whole system is tested during measurement campaigns in free air and in a closed chamber housing some plants. The results of calibration and tests prove that the device can detect the CO2 variation due to plants photosynthesis with a resolution of 10 ppm and satisfactory measurement accuracy, paving the way for CO2 fluxes monitoring even with low-cost and low-power embedded solutions.
To reduce carbon emission levels, an in-grid energy system combining photovoltaic (PV) and electric energy storage applicable to distributed parks has been modeled and evaluated. The configuration of PV and battery is...
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An innovative Seagull Optimization Term Memory (SOTM) model comes into being in the study of computer virtual reality technology applied to power system training and simulation. The model effectively integrates the st...
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ISBN:
(纸本)9798350373646
An innovative Seagull Optimization Term Memory (SOTM) model comes into being in the study of computer virtual reality technology applied to power system training and simulation. The model effectively integrates the strengths of both the Long Short-Term Memory (LSTM) network and the Seagull Optimization Algorithm (SOA), resulting in the creation of the SOTM model. This innovative design aims to augment the precision and effectiveness of power system training and simulation platforms, furnishing power engineering professionals with advanced, highly-realistic training utilities and more dependable power system simulation outcomes. LSTM networks are very suitable for simulating dynamic behavior and trend changes of power systems because of their ability to capture and remember long-term dependencies when processing time series data. In the power system training and simulation system, LSTM can learn and predict the state change of the power system based on the historical operation data, so as to realize the accurate simulation of the complex behavior of the power system. However, the selection and optimization of LSTM model parameters are crucial to the performance of the model, especially in the face of high-dimensional, nonlinear and dynamically changing complex systems such as power systems, which may be difficult to find the optimal solution by traditional training methods. To this end, the researchers introduced the seagull optimization algorithm. As an optimization algorithm derived from natural phenomena, SOA draws on the efficient search strategy shown by seagulls when they forage for food, and has strong global search capability and fast convergence speed. In the context of the SOTM model, the Seagull Optimization Algorithm (SOA) is employed to refine and optimize the parameters within the LSTM model, thereby enabling it to align more precisely with the operational principles of the power system. By integrating the dual advantages of LSTM and SOA, SOTM model not
The main focus of this project is to extend battery life and recharge the battery using external renewable resources. The objective is to bring a new technology at a low cost while also lowering the amount of pressure...
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We provide a novel approach to predicting the deterioration in the response state of patients suffering from neurological movement disorders, which include hand tremors and involuntary motions, similar to the symptoms...
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This paper introduces a novel approach to criminal identification and activity tracking using Python and APIs. It outlines a method for extracting email addresses and phone numbers associated with individuals, followe...
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One of the services that LinkedIn offers is a job recommendation system that helps users find job opportunities that match their interests and skills. This paper investigates the recommender system for LinkedIn user p...
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This study offers a thorough analysis of bottom-up parsing techniques, necessary for the creation and execution of compilers. Parsers such as SLR (Simple LR), LR (Canonical LR), LR(k) and LALR (Look-Ahead LR) are bott...
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Diabetic Retinopathy (DR) is a leading cause of vision loss worldwide. Early detection and timely intervention are crucial for preventing vision impairment. This research aims to develop an AI-powered system for the e...
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Personalized medicine is driving the need for new and customized biopharmaceuticals using proteins that have been changed. As such, it is critical to evaluate these items for allergenicity before introducing them as t...
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