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IEEE/ICACT20260142 Slide.22        [Big Slide]	Oral Presentation
	For pattern detection experiments, we generated 4000 synthetic time series — 100 points each, 30-second intervals — stored in Victoria Metrics, a high-performance metric database. Each series includes a baseline + Gaussian noise (Eq. 14), then one injected pattern: spikes/dips, level shifts, or trends (Eq. 15–17). Parameters are listed in Table II (baseline x_i, deviation ¥ä, changepoint j, slope ¥â, shift ¥Ä, etc.). We use binary classification metrics: True Positive Rate and False Positive Rate, to evaluate detection accuracy and false alarm rates across pattern types.

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