The Internet of Things (IoT) has revolutionized our lives, but it has also introduced significant security and privacy challenges. The vast amount of data collected by these devices, often containing sensitive informa...
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Background: Epilepsy is a neurological disorder that leads to seizures. This occurs due to excessive electrical discharge by the brain cells. An effective seizure prediction model can aid in improving the lifestyle of...
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Colletotrichum kahawae(Coffee Berry Disease)spreads through spores that can be carried by wind,rain,and insects affecting coffee plantations,and causes 80%yield losses and poor-quality coffee *** deadly disease is har...
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Colletotrichum kahawae(Coffee Berry Disease)spreads through spores that can be carried by wind,rain,and insects affecting coffee plantations,and causes 80%yield losses and poor-quality coffee *** deadly disease is hard to control because wind,rain,and insects carry *** researchers utilized a deep learning system to identify CBD in coffee cherries at three growth stages and classify photographs of infected and uninfected cherries with 93%accuracy using a random forest *** the dataset is too small and noisy,the algorithm may not learn data patterns and generate accurate *** overcome the existing challenge,early detection of Colletotrichum Kahawae disease in coffee cherries requires automated processes,prompt recognition,and accurate *** proposed methodology selects CBD image datasets through four different stages for training and *** to train a model on datasets of coffee berries,with each image labeled as healthy or *** themodel is trained,SHAP algorithmto figure out which features were essential formaking predictions with the proposed *** of these characteristics were the cherry’s colour,whether it had spots or other damage,and how big the Lesions *** inception is important for classification to virtualize the relationship between the colour of the berry is correlated with the presence of *** evaluate themodel’s performance andmitigate excess fitting,a 10-fold cross-validation approach is *** involves partitioning the dataset into ten subsets,training the model on each subset,and evaluating its *** comparison to other contemporary methodologies,the model put forth achieved an accuracy of 98.56%.
The healthcare industry struggles with diagnosing health disorders and finding the right treatment for diseases at an earlier stage. Many diseases can be detected early and treated well. Thyroid malfunction is one suc...
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Early detection is vital in crop health, yet improvement in productivity faces time-consuming and inefficient challenges due to traditional manual techniques of plant disease detection. Thus, we present a deep learnin...
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Presently, when the Internet of Things (IoT) makes virtually everything smart by improving every aspect of our life, continuous development in this area is imperative. As IoT deals with the Low-Power Lossy Networks (L...
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Cloud computing has emerged as a viable alternative to traditional computing infrastructures,offering various ***,the adoption of cloud storage poses significant risks to data secrecy and *** article presents an effec...
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Cloud computing has emerged as a viable alternative to traditional computing infrastructures,offering various ***,the adoption of cloud storage poses significant risks to data secrecy and *** article presents an effective mechanism to preserve the secrecy and integrity of data stored on the public cloud by leveraging blockchain technology,smart contracts,and cryptographic *** proposed approach utilizes a Solidity-based smart contract as an auditor for maintaining and verifying the integrity of outsourced *** preserve data secrecy,symmetric encryption systems are employed to encrypt user data before outsourcing *** extensive performance analysis is conducted to illustrate the efficiency of the proposed ***,a rigorous assessment is conducted to ensure that the developed smart contract is free from vulnerabilities and to measure its associated running *** security analysis of the proposed system confirms that our approach can securely maintain the confidentiality and integrity of cloud storage,even in the presence of malicious *** proposed mechanism contributes to enhancing data security in cloud computing environments and can be used as a foundation for developing more secure cloud storage systems.
A visible light communication (VLC) provides potential and effective communication paradigm due to the demand of high data-rate applications. VLC networks, consisting of multiple light emitting diodes (LEDs) and it pr...
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The medical domain faces unique challenges in Information Retrieval (IR) due to the complexity of medical language and terminology discrepancies between user queries and documents. While traditional Keyword-Based Meth...
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Long-term urban traffic flow prediction is an important task in the field of intelligent transportation,as it can help optimize traffic management and improve travel *** improve prediction accuracy,a crucial issue is ...
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Long-term urban traffic flow prediction is an important task in the field of intelligent transportation,as it can help optimize traffic management and improve travel *** improve prediction accuracy,a crucial issue is how to model spatiotemporal dependency in urban traffic *** recent years,many studies have adopted spatiotemporal neural networks to extract key information from traffic ***,most models ignore the semantic spatial similarity between long-distance areas when mining spatial *** also ignore the impact of predicted time steps on the next unpredicted time step for making long-term ***,these models lack a comprehensive data embedding process to represent complex spatiotemporal *** paper proposes a multi-scale persistent spatiotemporal transformer(MSPSTT)model to perform accurate long-term traffic flow prediction in *** adopts an encoder-decoder structure and incorporates temporal,periodic,and spatial features to fully embed urban traffic data to address these *** model consists of a spatiotemporal encoder and a spatiotemporal decoder,which rely on temporal,geospatial,and semantic space multi-head attention modules to dynamically extract temporal,geospatial,and semantic *** spatiotemporal decoder combines the context information provided by the encoder,integrates the predicted time step information,and is iteratively updated to learn the correlation between different time steps in the broader time range to improve the model’s accuracy for long-term *** on four public transportation datasets demonstrate that MSPSTT outperforms the existing models by up to 9.5%on three common metrics.
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