Modernization of waste processing through Waste-to-Energy has been a new trend to solve waste management and energy scarcity. This model however it may raise a conflict with recycling activities. This article establis...
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Nowadays,the production of consumer goods is based on the use of non-renewable raw materials,which in recent years has been performing as a problem for the *** the large number of available biofibers in nature,their ...
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Nowadays,the production of consumer goods is based on the use of non-renewable raw materials,which in recent years has been performing as a problem for the *** the large number of available biofibers in nature,their use in the development of polymeric composites has inevitably emerged,it is also necessary to take into account the countless discarded plastics that still have the potential to be *** this work,fibers were extracted from pineapple crown residues and utilized to compose sustainable composites using recycled polypropylene from cups discarded in the trash as a ***,it is known that for good performance,it is necessary to achieve a good chemical interaction between the fiber and the *** order to improve this interaction,alkaline mercerization treatment was carried out on the surface of the fibers removing some components incompatible with the *** this work,the effect of the mercerization treatment on the properties of the fibers was studied,as well as their interaction with the *** effect of fiber concentration on the mechanical and thermal properties of composites was also *** of 5 and 7 wt%were used for both natural and mercerized fibers.A decrease in the number of degradation stages was observed through thermogravimetry analyses(from four in natural fiber to two in mercerized fibers),showing that the mercerization performed on the fibers was *** increase in the degree of crystallinity of mercerized fibers was also observed through the results of X-ray *** techniques indicate that amorphous compounds,such as hemicellulose and lignin,were partially *** the tensile test,it could be noted that all composites presented higher values of de elastic modulus than recycled polypropylene without added load;however,there were no differences in the elastic modulus between the different types of fibers and load ***,it is interesting to use fibers as r
The energy control of a Wireless Sensor Network (WSN) often leads to an unbalanced state between the battery storage system, energy extraction through photovoltaic systems energy, and energy utilization in the WSN. Th...
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ISBN:
(数字)9798350364101
ISBN:
(纸本)9798350364118
The energy control of a Wireless Sensor Network (WSN) often leads to an unbalanced state between the battery storage system, energy extraction through photovoltaic systems energy, and energy utilization in the WSN. These disparities result in suboptimal wireless sensor network performance. The reliance on batteries is a major factor contributing to this problem. The Q-Learning Energy Management System (Q-EMS) is designed to address these challenges and improve energy management strategies. The Q-EMS algorithm used a learning process resulting in optimal actions for sensor nodes in different situations. The rewards or punishments nodes receive determine their decisions, which are determined by the Q-EMS algorithm. The Q-learning model approach is aimed at reducing energy consumption and supply in WSNs. Energy supply is categorized into battery-based, transfer-based, and harvesting, while energy consumption can be classified into task-cycle, mobility-based, and data-driven. The development of the Q Learning algorithm model has three scenarios: determining energy needs for WSN, effective energy harvesting strategy, and effective energy transfer. As a result, effective energy demand, harvesting and transfer using the Q-learning algorithm are balanced. However, it needs to be studied in more depth using real data in the field. In future research, I will use real data and optimize the use of the Q-Learning algorithm.
Interest in artificial intelligence (AI)-driven crowd work has increased during the last few years as a line of inquiry that expands upon prior research on microtasking to represent a means of scaling up complex tasks...
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ISBN:
(数字)9798331510886
ISBN:
(纸本)9798331510893
Interest in artificial intelligence (AI)-driven crowd work has increased during the last few years as a line of inquiry that expands upon prior research on microtasking to represent a means of scaling up complex tasks through AI mediation. Despite the increasing attention to the macrotask phenomenon in crowdsourcing, there is a need to understand the processes, elements, and constraints underlying the infrastructural and behavioral aspects in such form of crowd work when involving collaboration. To this end, this paper provides a first attempt to characterize some of the research conducted in this direction to identify important paths for an agenda comprising key drivers, challenges, and prospects for integrating human-centered AI in collaborative crowdsourcing environments.
The growing disparity between the high extraction of natural resources and low use of waste as alternative mineral resources will aggravate the scarcity of natural reserves. Therefore, the current linear economy model...
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The Fered-Fenton process is one of the proposed options across the set of electrochemical oxidation processes. The primacy of this process is in-situ production of oxidation factors such as the hydroxyl radical (OH•)....
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This study investigates the effectiveness of the Cu-doped Bi2O3 method for removing antibiotics. Cu at varying concentrations of 0%, 2%, 4%, 6%, and 8% was used to synthesize Bi2O3 material successfully. The optimal r...
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In electric vehicles (EVs), monitoring battery cells ensures safety and longevity. The Battery Management System (BMS) is responsible for this task, using variables such as State of Charge (SoC). This paper presents a...
In electric vehicles (EVs), monitoring battery cells ensures safety and longevity. The Battery Management System (BMS) is responsible for this task, using variables such as State of Charge (SoC). This paper presents a comparative study between the Unscented Kalman Filter (UFK) and Multilayer Perceptron Neural Network (PMC) methods applied to a pack using a simulation of a vehicle under the FTP-75 cycle with reference SoC using Coulomb Counting (CC). The Neural Network performed better with an RMSE value of 0.418 compared to 0.0593 for UFK.
This paper proposes a single-phase to three-phase drive system consisting of two parallel single-phase rectifiers, one three-phase inverter and an induction motor. It uses two parallel rectifiers without low frequency...
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