Today, a lot of people use the Internet of Things (IoT) in organizations, businesses, and daily life. Attackers have taken advantage of this potential for IoT devices to expose the integrity and security of user data....
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The aim of this study is to improve the efficiency of software testing and/or review by predicting modules that are likely to contain a bug. In cross-version bug prediction, which uses bug data from a previous version...
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Integrating multiple omics data can significantly improve the accuracy of cancer subclassification, a challenging task due to the high dimensionality and limited sample sizes. The integration of these data sets can en...
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Cyberspace is extremely dynamic,with new attacks arising *** cybersecurity controls is vital for network *** Learning(DL)models find widespread use across various fields,with cybersecurity being one of the most crucia...
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Cyberspace is extremely dynamic,with new attacks arising *** cybersecurity controls is vital for network *** Learning(DL)models find widespread use across various fields,with cybersecurity being one of the most crucial due to their rapid cyberattack detection capabilities on networks and *** capabilities of DL in feature learning and analyzing extensive data volumes lead to the recognition of network traffic *** study presents novel lightweight DL models,known as Cybernet models,for the detection and recognition of various cyber Distributed Denial of Service(DDoS)*** models were constructed to have a reasonable number of learnable parameters,i.e.,less than 225,000,hence the name“lightweight.”This not only helps reduce the number of computations required but also results in faster training and inference ***,these models were designed to extract features in parallel from 1D Convolutional Neural Networks(CNN)and Long Short-Term Memory(LSTM),which makes them unique compared to earlier existing architectures and results in better performance *** validate their robustness and effectiveness,they were tested on the CIC-DDoS2019 dataset,which is an imbalanced and large dataset that contains different types of DDoS *** results revealed that bothmodels yielded promising results,with 99.99% for the detectionmodel and 99.76% for the recognition model in terms of accuracy,precision,recall,and F1 ***,they outperformed the existing state-of-the-art models proposed for the same ***,the proposed models can be used in cyber security research domains to successfully identify different types of attacks with a high detection and recognition rate.
Insurance companies worldwide are concerned about financial losses due to false claims. Automobile insurance fraud (AIF) has become more sophisticated, causing the yearly loss of trillions of dollars. AIF is tough to ...
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Lung cancer is the most dangerous and death-causing disease indicated by the presence of pulmonary nodules in the *** is mostly caused by the instinctive growth of cells in the *** nodule detection has a significant r...
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Lung cancer is the most dangerous and death-causing disease indicated by the presence of pulmonary nodules in the *** is mostly caused by the instinctive growth of cells in the *** nodule detection has a significant role in detecting and screening lung cancer in Computed tomography(CT)scan *** detection plays an important role in the survival rate and treatment of lung cancer ***,pulmonary nodule classification techniques based on the convolutional neural network can be used for the accurate and efficient detection of lung *** work proposed an automatic nodule detection method in CT images based on modified AlexNet architecture and Support vector machine(SVM)algorithm namely *** proposed model consists of seven convolutional layers,three pooling layers,and two fully connected layers used to extract *** vector machine classifier is applied for the binary classification of nodules into benign *** experimental analysis is performed by using the publicly available benchmark dataset Lung nodule analysis 2016(LUNA16).The proposed model has achieved 97.64%of accuracy,96.37%of sensitivity,and 99.08%of specificity.A comparative analysis has been carried out between the proposed LungNet-SVM model and existing stateof-the-art approaches for the classification of lung *** experimental results indicate that the proposed LungNet-SVM model achieved remarkable performance on a LUNA16 dataset in terms of accuracy.
An image can convey a thousand words. This statement emphasizes the importance of illustrating ideas visually rather than writing them down. Although detailed image representation is typically instructive, there are s...
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The utilization of thermal images has become widespread in various applications, particularly for thermal examination and night surveillance systems. Although many details associated with thermal imaging are virtually...
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Context-awareness is a pivotal trend within the Internet of Things research area, facilitating the near real-time processing and interpretation of relevant sensor data to enhance data processing efficiency. Context Ma...
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The Latent Dirichlet Allocation (LDA) model has two important hyperparameters that control the document-topic distribution known as alpha (α), and topic-word distribution known as beta (β). It is important to find t...
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