Abstract: To automate time series forecasting machine learning pipeline generation, a data allocation size of time series data may be determined based on one or more characteristics of a time series data set. The time series data may be allocated for use by candidate machine learning pipelines based on the data allocation size. Features for the time series data may be determined and cached by the candidate machine learning pipelines. Predictions of each of the candidate machine learning pipelines using at least the one or more features may be evaluated. A ranked list of machine learning pipelines may be automatically generated from the candidate machine learning pipelines for time series forecasting based upon evaluating predictions of each of the one or more candidate machine learning pipelines.

Abstract: Single-electron devices useful as diodes, transistors or other electronic components are prepared by anodizing a metal substrate in sheet or foil form electrolytically in an acid bath, to deposit thereon an oxide film having axially disposed micropores of substantially uniform diameter in the range of from about 1 to about 500 nanometers and substantially uniform depth less than the thickness of the oxide film, leaving an ultra thin oxide layer between the bottom of each pore in the metal substrate. The conductive material is deposited in the pores to form nanowires contacting the oxide layer at the bottom of the pores. Macro metal is deposited over the ends of the nanowires for external electrical contact purposes. Devices can be made according to the present invention which are suitable to exhibit single-electron tunnelling effects and arrays of tunnel junction devices can be prepared having a density up to the order of 10.sup.10 per square cm.