Input data can come from variety of form (structured, semi-structured, or unstructured). 4 Data might not be immediately available for retrieval due to site restriction. 5 Data might not always be updated on a regular interval.Related works Traffic prediction analysis is typically done in a cro...
Traditional ML approaches are based on creating features and segmentation, and DL techniques are based on learning from data in its raw form. Using pre-trained CNNs like GoogleNet and AlexNet could classify twenty-six pests and diseases within fourteen plant species [7]; 99.34% was obtained ...
A comprehensive evaluation method, incorporating fuzzy evaluation model, is developed to synthetically evaluate the data quality, based on the score value of each dimension. This method focuses on interactions of dimensions to achieve the dynamic balance. Furthermore, the adoption of fuzzy evaluation mo...
All the data processes of MINI are the same as BENCH except for removing the pairs showing pair-wise sequence identity≥ 40% because MINI did not have enough scale to eliminate redundancy. To avoid the contingency of negative sample selection, we repeated the above processes 5 times to form ...
This was the first type of models [30, 31] that made use of pre-trained word embeddings. Although the results improved the best current systems, one disadvantage is that using this approach each word form is assigned a single vector containing its representation independent from its context. (...
For both testing and training scenarios using the 20 participants (i) LOPOCV and (ii) 70% training and 30% testing data, classification results are represented in form of confusion matrices and the F1-score. The confusion matrix reports the number of false-positive (incorrectly identified), ...
and these indicators record the status of different services in time series form [3]. Therefore, closely monitoring and analyzing various key performance indicators collected from each service instance, such as CPU load and network usage, has become the mainstream method for detecting and locating fa...
[40] used millions of well-known good and bad network connections to model network traffic in the form of a time series, specifically TCP/IP packets within a predetermined time range. To do this, a multilayer perceptron must be used, in addition to CNN, CNN-RNN, CNN-long, CNN-LSTM, ...
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including VGG19 and the second form of Google MobileNet [40]. DenseNet and VGG19 networks were seen to detect COVID-19 automatically. Furthermore, Khan proposed CoroNet, a DCNN model with a similar goal [41]. Similarly, Li proposed Covid-MobileXpert, a mobile-based DL network framework [...