Abstract: A semiconductor chip package is described. The semiconductor chip package has a substrate. The substrate has side I/Os on the additional surface area of the substrate. The side I/Os are coupled to I/Os of a semiconductor chip within the semiconductor chip package. A cooling assembly has also been described. The cooling assembly has a passageway to guide a cable to connect to a semiconductor chip's side I/Os that are located between a base of a cooling mass and an electronic circuit board that is between a bolster plate and a back plate and that is coupled to second I/Os of the semiconductor chip through a socket that the semiconductor chip's package is plugged into.

Abstract: A method and an equipment for comprehensive utilization of niobite is disclosed. The method includes the following steps: S1. adding and uniformly mixing a coal-based reducing agent to the niobite, and subsequently reducing the mixture in a reduction furnace to obtain the selective reduction product; S2. adding the selective reduction product to a super-gravity reactor where the ambient temperature is controlled to be lower than the temperature at which the niobium oxide is reduced; driven by super-gravity, reverse migrating and collecting the metal iron and the niobium-rich slag at different locations in the reactor; discharging the metallic iron tightly attached to the wall of the reactor through an iron discharging port, and discharging the niobium-rich slag enriched to the inner layer of the reactor through a slag discharging port, so that the separation of the metallic iron and the niobium-rich slag is realized in the super-gravity field.

Abstract: Disclosed is an infrared thermal image classification and hot spot positioning method of a photovoltaic panel, comprising following steps: constructing a photovoltaic panel infrared thermal image data set, preprocessing the image data set, and dividing into a training set and a testing set according to a preset proportion; training an auxiliary generating countermeasure network based on the training set to obtain a trained generator and a trained discriminator, training an encoder by combining the image data in the training set with the generator, and fixing the parameters of a trained encoder; inputting the image data in the test set into a trained discriminator to obtain a photovoltaic image classification result; inputting images in the test set into the trained encoder, and then inputting the images into the generator for a reconstruction; comparing pixels of the input images with the reconstructed infrared thermal images, and positioning hot spots.