Mobile technology use in education is changing, much like in the business and health sectors. Research is now conducted on designing user-centric platforms that allow people to engage in teaching and learning activiti...
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Data recovery from flash memory in the mobile device can effectively reduce the loss caused by data corruption. Type recognition of data fragment is an essential prerequisite to the low-level data recovery. Previous w...
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Data recovery from flash memory in the mobile device can effectively reduce the loss caused by data corruption. Type recognition of data fragment is an essential prerequisite to the low-level data recovery. Previous works in this field classify data fragment based on its file type. Still, the classification efficiency is low, especially when the data fragment is a part of a composite *** propose a fine-grained approach to classifying data fragment from the low-level flash memory to improve the classification accuracy and efficiency. The proposed method redefines flash-memory-page data recognition problem based on the encoding format of the data segment, and applies a hybrid machine learning algorithm to detect the data type of the flash page. The hybrid algorithm can significantly decompose the given data space and reduce the cost of training. The experimental results show that our method achieves better classification accuracy and higher time performance than the existing methods.
The medical services industry is on the cusp of another period driven by the union of distributed computing, man-made consciousness (simulated intelligence), and the Ayushman Bharat Wellbeing Record (ABHA) card drive....
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Classification of the patterns is a crucial structure of research and applications. Using fuzzy set theory, classifying the patterns has become of great interest because of its ability to understand the parameters. ...
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Classification of the patterns is a crucial structure of research and applications. Using fuzzy set theory, classifying the patterns has become of great interest because of its ability to understand the parameters. One of the problemsobserved in the fuzzification of an unknown pattern is that importance is givenonly to the known patterns but not to their features. In contrast, features of thepatterns play an essential role when their respective patterns overlap. In this paper,an optimal fuzzy nearest neighbor model has been introduced in which a fuzzifi-cation process has been carried out for the unknown pattern using k nearest neighbor. With the help of the fuzzification process, the membership matrix has beenformed. In this membership matrix, fuzzification has been carried out of the features of the unknown pattern. Classification results are verified on a completelyllabelled Telugu vowel data set, and the accuracy is compared with the differentmodels and the fuzzy k nearest neighbor algorithm. The proposed model gives84.86% accuracy on 50% training data set and 89.35% accuracy on 80% trainingdata set. The proposed classifier learns well enough with a small amount of training data, resulting in an efficient and faster approach.
The emergence of COVID-19 has underscored the urgency of accurate medical diagnosis, particularly in the context of chest X-ray image classification for various lung conditions, including COVID-19, normal cases, viral...
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Weeds refer to plants that a farmer does not intentionally cultivate because they interfere with or limit the growth and yield of crops. Due to their fast reproduction and spreading, weeds are well-known for quickly i...
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Strong protection against cyber threats is ensured by forensic analysis and cloud environment security being reinforced by the use of real-time threat detection and advanced encryption *** existing approach struggles ...
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ISBN:
(纸本)9798331508845
Strong protection against cyber threats is ensured by forensic analysis and cloud environment security being reinforced by the use of real-time threat detection and advanced encryption *** existing approach struggles to keep up with changing cyber threats and lack the strategic thinking skills necessary to address new security issues. To overcome these drawbacks, this work presents a novel method that maximizes security and forensic analysis in cloud-based settings by fusing blockchain technology, the game theory, and recursive Gated Recurrent Unit (GRU) models. The behavioral analytic capabilities of the recursive GRU models are especially helpful for detecting patterns and anomalies in security-related cloud logs, as evidenced by the UNW-NB15 dataset. Its flexibility is essential for identifying changing cyber threats and identifying anomalous user behavior. Using blockchain technology to create a decentralized, immutable ledger helps to mitigate data integrity issues that may arise from forensic investigation in cloud environments. This ledger guarantees the accuracy of data for forensic examinations, and smart contracts which come with built-in security features automate access controls and security issue remedies. Because blockchain is decentralized, it reduces individual points of failure, which improves the security of cloud infrastructure as a whole. By synchronizing security occurrences in real-time with the blockchain, the proposed connection creates a reliable and unchangeable record. Programmed intelligent agreements respond quickly to security incidents by issuing alerts or executing specified actions, as detected by the recursive GRU model. Through the use of continuous learning techniques, the model continuously adjusts to new data, improving its comprehension of both common and uncommon tendencies based on security incidents recorded on the blockchain. In cloud environments, this approach seeks to improve safety, openness, and effectiven
The use of social media is widespread in modern culture. People are making purchases on social media sites. Compared to more conventional approaches, digital marketing has shown to be successful. Both academics and re...
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Ancient texts are important because they connect us with ancient civilizations, through which gain cultural, religious, and scientific knowledge, but these texts are often damaged over time due to environmental factor...
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In today's time several deadly tumors are present like breast cancer, liver cancer, oral cancer, etc. Brain tumor is also one such disease. It is a biological condition in which the brain's normal functioning ...
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