K-DSM uses per-feature kurtosis to set noise scales in DSM, enabling effective single-scale anomaly detection on tabular benchmarks in both semi-supervised and unsupervised settings.
Quantum Confinement and Negative Heat Capacity
4 Pith papers cite this work. Polarity classification is still indexing.
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abstract
Thermodynamics dictates that the specific heat of a system is strictly non-negative. However, in finite classical systems there are well known theoretical and experimental cases where this rule is violated, in particular finite atomic clusters. Here, we show for the first time that negative heat capacity can also occur in finite quantum systems. The physical scenario on which this effect might be experimentally observed is discussed. Observing such an effect might lead to the design of new light harvesting nano devices, in particular a solar nano refrigerator.
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Random forest regression trained on clustered 3D-current VIV experiments predicts riser response statistics and is compared against the VIVANA-FD semi-empirical tool.
AVVA is a new framework adapting verbal analysis for classroom discourse with triangulation across ten steps and a four-criterion validation scheme for temporal stability, applied to 23 hours of recordings.
Empirical tests on 148 images show that the best colorspace for k-means quantization depends on the image and the target number of colors k, with RGB winning in roughly half the cases.
citing papers explorer
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Kurtosis-Guided Denoising Score Matching for Tabular Anomaly Detection
K-DSM uses per-feature kurtosis to set noise scales in DSM, enabling effective single-scale anomaly detection on tabular benchmarks in both semi-supervised and unsupervised settings.
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Data-driven prediction of vortex-induced vibration response of marine risers subjected to three-dimensional current
Random forest regression trained on clustered 3D-current VIV experiments predicts riser response statistics and is compared against the VIVANA-FD semi-empirical tool.
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Audio Video Verbal Analysis (AVVA) for Capturing Classroom Dialogues
AVVA is a new framework adapting verbal analysis for classroom discourse with triangulation across ten steps and a four-criterion validation scheme for temporal stability, applied to 23 hours of recordings.
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Optimized $k$-means color quantization of digital images in machine-based and human perception-based colorspaces
Empirical tests on 148 images show that the best colorspace for k-means quantization depends on the image and the target number of colors k, with RGB winning in roughly half the cases.