*.avi; *.csv; *.txt
The rocket nose-cone shapes have been generated by blending few conic sections together (two conic sections in one) and the simulated against mach number regime from subsonic through transonic to supersonic. The aerodynamic drag coefficients have been recoded for each shape for each mach number.
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456 Views
A comparative, empirical study of state-of-the-art contrastive and generative graph learning models applied to source and binary software fragments drawn from the National Vulnerability Database (NVD) reveals that Graph Masked Auto-Encoders show exceptional promise for detecting security vulnerabilities, outperforming all other baseline models in the study.
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3 Views
In traditional schemes, obtaining a robust topology requires high connectivity. We chose random undirected and directed network topologies for comparison to showcase the
advantages of entropy and connectivity.
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84 Views
This is a fictional data set, provided by the IBM. These data set contains atmost 30 features of categorical and discreet data. These data are kind of both numerical and text values which help in analysing the employee data from hiring to firing and on boarding to attrition.
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4899 Views
The accuracy and reliability of an Ultra- WideBand (UWB) Indoor Positioning System (IPS) are compromised owing to the positioning error caused by the Non-Line-of-Sight (NLoS) signals. To address this, Machine Learning (ML) has been employed to classify Line-of-Sight (LoS) and NLoS components. However, the performance of ML algorithms degrades due to the disproportion of the number of LoS and NLoS signal components. A Weighted Naive Bayes (WNB) algorithm is proposed in this paper to mitigate this issue.
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312 Views
The data refer to times of payment from a hospital billing (HB) data set. The source data were collected from a hospital in the Netherlands over three years provided by Felix Mannhardt, Massimiliano de Leoni, Hajo A. Reijers and Wil M. P. van der Aalst in the paper with the title "Data-Driven Process Discovery - Revealing Conditional Infrequent Behavior from Event Logs". Based on the original data, duration data in four tasks are extracted for the analysis of patient patterns from a time perspective.
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121 Views
<p>Two-electrode straight open magnetic source (TSOMS) has been widely used on the magnetic minesweeper and magnetic decoy. Fast-forward modeling and obtaining the high-precision magnetic field in the air are the prerequisites for real-time inversion and positioning of the TSOMS. In this paper, we propose an algorithm to calculate the magnetic field of the two-electrode straight open magnetic source (MFTSOMS) by previous theoretical research. And a classical algorithm of electric dipole magnetic field is used to verify the correctness of our algorithm.
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81 Views
This dataset contains one month of the binary activity of the 4060 urban IoT nodes. Each record in the dataset presents the node ID, the time stamp, the location of the IoT node in latitude and longitude, and also the binary activity of the IoT node. The main purpose of this dataset is to be used as part of distributed denial of service (DDoS) attack research.
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583 Views
Data preprocessing is a fundamental stage in deep learning modeling and serves as the cornerstone of reliable data analytics. These deep learning models require significant amounts of training data to be effective, with small datasets often resulting in overfitting and poor performance on large datasets. One solution to this problem is parallelization in data modeling, which allows the model to fit the training data more effectively, leading to higher accuracy on large data sets and higher performance overall.
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100 Views
Most machine learning (ML) proposals in the Internet of Things (IoT) space are designed and evaluated on pre-processed datasets, where the data acquisition and cleaning steps are often considered a black box. Therefore, the data acquisition stage requires additional data cleaning/anomaly techniques, which translate to additional resources, energy, and storage.
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1473 Views