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Wang [39] showed the effectiveness of using logistic regression modeling to detect multi-attack types.

We used Box-Jenkins modeling to detect and model autocorrelation in our independent and, after adjusting for covariates, dependent variable (Box et al. 1994).

Currently, methods are missing that use replicate information as the basis for data-driven error modeling to detect consistent peaks and to statistically infer changes in contact frequencies between different conditions.

Another approach determines the modulation mode of the signal through a T-F method with autoregressive modeling to detect phase shifts, frequency shifts and amplitude shifts [61].

The physiological and computational approaches, such as percutaneous coronary intervention and stent design modeling, to detect, evaluate and mitigate this malicious progression were also discussed.

Together, they provided the opportunity for using multilevel modeling to detect and evaluate interactions over time (change for change analysis), a technique that is substantially more robust than simple cross-sectional association or regression.

Similar(54)

Sensor nodes use binary detection model to detect target.

The technology uses deep learning models to detect, normalize, validate, match and identify faces.

Scales big data projects, developing complex models to detect patterns in social data.

To develop and validate a prediction model to detect sensitization to wheat allergens in bakery workers.

Kvaale proposed an artificial neural network model to detect emotions [11].

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