Alibaba Group Holding Limited

Hangzhou City University

Kai Xu

Fei Sun

Yen-kuang Chen

Minghai Qin

Yuan Xie

Yuhao Wang

Jianjun Fan

Chao Chen

Tong Zhu

Yunliang Cui

Weijie Yan

Shuangfeng Li

Zidong He

Qunchao Ma

Huiming Li

Zhipeng Liu

Junshuai Zhang

A vacuum-flocculation-solidification integrated apparatus for waste mud and a using method thereof are provided, and the apparatus includes an outer support truss, a vacuum barrel wall, a flocculation stirring device, and a rotary spraying solidification device. The using method of the apparatus includes: flattening a site and installing a support truss and a vacuum barrel wall; assembling a flocculation stirring device and then hoisting and installing to a top of the vacuum barrel wall; checking an air tightness; adding an APAM flocculant, starting the flocculation stirring device and a vacuum pump; starting an air compressor; and squeezing solidified soil from soil outlets. Beneficial effects of apparatus are that: multiple procedures of flocculation, vacuum drainage, solidification and discharging soil for the waste mud are continuously performed; a solidification agent is fully mixed with solidified soil through rotary spraying; and the apparatus is convenient to be disassembled, reassembled, and reused.

Vacuum-flocculation-solidification integrated apparatus for waste mud and using method thereof

Methods and systems are provided for implementing preprocessing operations and augmentation operations upon image datasets transformed to frequency domain representations, including decoding images of an image dataset to generate a frequency domain representation of the image dataset; performing a resizing operation based on resizing factors on the image dataset in a frequency domain representation; performing a reshaping operation based on reshaping factors on the image dataset in a frequency domain representation; and performing a cropping operation on the image dataset in a frequency domain representation. The methods and systems may further include performing an augmentation operation on the image dataset in a frequency domain representation. Methods and systems of the present disclosure may free learning models from computational overhead caused by transforming image datasets into frequency domain representations. Furthermore, computational overhead caused by inverse transformation operations is also alleviated.

Data preprocessing and data augmentation in frequency domain

Methods and systems are provided for implementing static channel filtering operations upon image datasets transformed to frequency domain representations, including decoding images of an image dataset to generate a frequency domain representation of the image dataset; discarding coefficient values of one or more particular frequency channels of each image of the image dataset in a frequency domain representation; and transporting the image dataset in a frequency domain representation to one or more special-purpose processor(s). Methods and systems of the present disclosure may enable a filtered image dataset to be input to a second layer of a learning model, bypassing a first layer, or may enable a learning model to be designed with a reduced-size first layer. This may achieve benefits such as reducing computational overhead and time of machine learning training and inference computations, reducing volume of image data input into the learning model, and reducing convergence time.

Static channel filtering in frequency domain

A system for processing encoded image components for artificial intelligence tasks. The system can include one or more compute units, one or more controllers and memory. The one or more controllers can include one or more micro-op schedulers and one or more channel switches. The one or more compute units can be configured to process components of the transformed domain image data according to one or more micro-operations for an artificial intelligence task. The one or more channel switches can be configured to selectively control the transfer of the components of transformed domain image data to the one or more compute units based on one or more gating flags. The one or more channel switches can also be configured to selectively control generation of the one or more micro-operations by the one or more micro-op schedulers based on the one or more gating flags.

Techniques to dynamically gate encoded image components for artificial intelligence tasks

A system for determining the importance of encoded image components for artificial intelligence tasks includes an image capture or storage unit, a processor and a communication interface. The processor can receive components of transformed domain image data from the one or more image capture or storage units across the communication interface. The processor can be configured to determine the relative importance of the components of the transformed domain image data for an artificial intelligence task.

Techniques for determining importance of encoded image components for artificial intelligence tasks

A service processing device and method include receiving a service processing request including data interaction processing mode information and account information, and determining, based on the service processing request, one or more data interaction processing mode candidates for executing the service processing request. The data interaction processing mode candidates are determined from a plurality of data interaction processing modes. Each of the data interaction processing modes includes processing parameters, and at least one of the processing parameters is different between different data interaction processing modes. Each of the one or more data interaction processing mode candidates has an associated processing success rate based on a historical processing record of the data interaction processing modes. The method also includes determining, based on the processing success rates, a data interaction processing mode candidate as a data interaction processing mode for executing the service processing request.

Method and device for selecting a service processing mode based on historical success rates

Device for connecting a television with an external signaling source

Television set top box

Growing community of inventors

Hangzhou, China

Kai Xu