Fish classification and object detection are crucial tasks in the fishery industry. The use of computer vision and deep learning techniques can help automate these tasks and improve the efficiency of the fishery indus...
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Forest fires, one of the most pernicious and devastating disasters, cause deforestation, wildlife extinction, global warming, and climate change. Early fire detection is critical before it reaches catastrophic dimensi...
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Forest fires, one of the most pernicious and devastating disasters, cause deforestation, wildlife extinction, global warming, and climate change. Early fire detection is critical before it reaches catastrophic dimensions. Artificial intelligence-based systems that detect forest fires accurately and quickly are needed for early intervention. Delayed extinguishing efforts without such systems cause tremendous damage and losses. An effective monitoring system allows for the reduction of fire damage and hence prevents forest loss. This study aims to develop a successful artificial intelligence model to detect fire from forest landscape images. In this context, this work is new as it provides new insights into robust and scientific modeling for forest fire detection by analyzing feature maps based on fused transformer architectures using Deep Neural Networks. The experimental models were validated using accuracy, sensitivity, precision, and area under the receiver operating characteristic curve measures. The validation findings reveal that the proposed hybrid model performs the best while all models yield reasonable results. To summarize, satisfactory accuracy values of 99.58% and 96.79% for both datasets, respectively, strongly support the proposed hybrid model's fire detection achievement with the 5-fold cross-validation. Furthermore, the high sensitivity and high precision measures imply that the model has few false negatives and false positives. Considering the obtained accuracies, the proposed hybrid model could be used for comprehensive fire detection modeling. To the author's best knowledge, this study is the first to use transformer architectures and Deep Neural Networks for forest fire detection and is therefore important for the relevant literature. In this context, this study presents a new approach to distinguishing landscape images of forest fires and further developing fire detection strategies by the role of transformer architectures in feature extraction.
Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder that affects millions worldwide. Early and accurate diagnosis is crucial for timely intervention and management, as it can significantly improve p...
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In just one and half minutes,more than fifty thousand died due to the 7.7 and 7.6 magnitude earthquakes that struck Turkey’s southeast on February 6,2023;thousands of families who barely escaped struggled to survive ...
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In just one and half minutes,more than fifty thousand died due to the 7.7 and 7.6 magnitude earthquakes that struck Turkey’s southeast on February 6,2023;thousands of families who barely escaped struggled to survive in the freezing weather.A warm shelter was the most basic requirement of these *** buildings are a rapid and easy solution to this ***,there is a need for a more effective and safe heating option than a wood fire for these *** this study,cabin heaters,which allow truck drivers to warm up when they park their vehicles to sleep,are specially optimized for emergency shelters after an *** optimized fuzzy controller was developed to use in such buildings,which allows an air–fuel ratio in the combustion chamber of the cabin heater to be controlled adaptively based on system dynamics to get lower carbon emissions and fuel *** TRNSYS software was used to establish the transient simulation model of a cabin heater with a capacity of 4 kW for a typical 21 m^(2) shelter building in Turkey’s cold *** developed fuzzy controller carried out the heating process of this shelter from the 15th of November to the 15th of *** of using expert knowledge,the Gray Wolf Optimization(GWO)method was applied to optimize the fuzzy controller parameters developed for the cabin *** the optimized fuzzy controller,the fuel consumption at the end of the heating season was reduced by an average of 0.2 L/h,and the cabin heater’s efficiency increased by more than 13%.Our simulation results show that the intelligent controller we developed could improve diesel fuel combustion efficiency by up to 85%.
Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the ***,the abundance of reviews and the risk of encounte...
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Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the ***,the abundance of reviews and the risk of encountering spoilers pose challenges for efcient sentiment analysis,particularly in Arabic *** study proposed a Stochastic Gradient Descent(SGD)machine learning(ML)model tailored for sentiment analysis in Arabic and English movie *** allows for fexible model complexity adjustments,which can adapt well to the Involvement of Arabic language *** adaptability ensures that the model can capture the nuances and specifc local patterns of Arabic text,leading to better *** distinct language datasets were utilized,and extensive pre-processing steps were employed to optimize the datasets for *** proposed SGD model,designed to accommodate the nuances of each language,aims to surpass existing models in terms of accuracy and *** SGD model achieves an accuracy of 84.89 on the Arabic dataset and 87.44 on the English dataset,making it the top-performing model in terms of accuracy on both *** indicates that the SGD model consistently demonstrates high accuracy levels across Arabic and English *** study helps deepen the understanding of sentiments across various linguistic *** many studies that focus solely on movie reviews,the Arabic dataset utilized here includes hotel reviews,ofering a broader perspective.
This paper presents a novel approach of establishing a multichannel optical communication link, combining optical fiber cable (OFC) and free space optics (FSO) technology. By leveraging multiple lengths of optical fib...
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In recent years, especially children and adolescents have shown increased interest in social media, making them a potential risk group for cyberbullying. Cyberbullying posts spread very quickly, often taking a long ti...
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People may now receive and share information more quickly and easily than ever due to the widespread use of mobile networked devices. However, this can occasionally lead to the spread of false information. Such inform...
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This study investigates a safe reinforcement learning algorithm for grid-forming(GFM)inverter based frequency *** guarantee the stability of the inverter-based resource(IBR)system under the learned control policy,a mo...
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This study investigates a safe reinforcement learning algorithm for grid-forming(GFM)inverter based frequency *** guarantee the stability of the inverter-based resource(IBR)system under the learned control policy,a modelbased reinforcement learning(MBRL)algorithm is combined with Lyapunov approach,which determines the safe region of states and *** obtain near optimal control policy,the control performance is safely improved by approximate dynamic programming(ADP)using data sampled from the region of attraction(ROA).Moreover,to enhance the control robustness against parameter uncertainty in the inverter,a Gaussian process(GP)model is adopted by the proposed algorithm to effectively learn system dynamics from *** simulations validate the effectiveness of the proposed algorithm.
In the enormous field of Natural Language Processing (NLP), deciphering the intended significance of a word among a multitude of possibilities is referred to as word sense disambiguation. This process is essential for...
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