Abstract: A catalyst composition for converting an alcohol to olefins, the catalyst composition comprising the following components: (a) beta zeolite; (b) at least one element selected from the group consisting of zinc, magnesium, calcium, strontium, sodium, and potassium; and (c) at least one element selected from the group consisting of hafnium, yttrium, zirconium, tantalum, niobium, and tin; wherein the components (b) and (c) are independently within or on a surface of said beta zeolite. The catalyst may also further include component (d), which is copper or silver. Also described herein is a method for converting an alcohol to one or more olefinic compounds, the method comprising contacting the alcohol with a catalyst at a temperature of at least 100° C. and up to 500° C. to result in the alcohol being converted to the one or more olefinic compounds.

Abstract: A method for converting an alcohol to a jet-diesel hydrocarbon fraction, comprising contacting the alcohol with a pillared two-dimensional zeolite catalyst at a temperature of at least 200° C. and up to 500° C. to convert the alcohol to hydrocarbons comprising: (a) a first mixed olefin fraction containing a mixture of C2-C5 olefins; (b) a first paraffin fraction containing C3-C5 paraffins; and (c) a gasoline fraction containing C6+ hydrocarbons; and the conversion of the alcohol is energy neutral or exothermic. The first mixed olefin fraction may be subjected to an oligomerization process to result in a second paraffin fraction containing C3-C6 paraffins along with a C7+ partially unsaturated fraction, and the first and second paraffin fractions combined into a total C3-C6 paraffin fraction, which can in turn be subjected to a dehydrogenation or aromatization process with hydrogen gas as byproduct, and the hydrogen gas recycled for use in producing the jet-diesel fraction.

Abstract: The present disclosure provides a method and an apparatus for detecting a 3D image, an electronic device, and a computer-readable medium. The method for detecting a 3D image includes layering a 3D image to obtain at least one 3D subimage. The 3D subimage contains a plurality of 2D images. The method includes performing an intra-layer clustering on the 3D subimage to obtain a superpixel grid. The method includes inputting the superpixel grid into a neural network for detecting. The method includes detecting, in response to detecting an object in the superpixel grid, the 3D subimage forming the superpixel grid containing the object to obtain and output a detection result.

Abstract: The present disclosure discloses a method and device for image encoding and a method and device for image decoding. The encoding method comprises steps of: downscaling an input high resolution HR image into a low resolution LR image by a downscaler; compressing the LR image using a first compression method; extracting an index value from at least one of the HR image and the LR image; determining a parameter from a parameter database using the index value; compressing the parameter using a second compression method different from the first compression method; and obtaining a data stream by merging the compressed parameter and the compressed LR image.

Abstract: A method and an electronic device for positioning an eyeball in a retinopathy image are disclosed. The method includes: using retinopathy image data with corresponding labeled data to train a deep learning network based on a loss function, so as to obtain a trained deep learning network; and processing retinopathy image data to be tested by using the trained deep learning network to obtain corresponding eyeball center coordinates and/or an eyeball diameter.

Abstract: A resolving method and a system, the method includes: creating a sample library by utilization of an original high-resolution (HR) image set; training a convolutional structural network by utilization of the sample library; and obtaining an HR output signal by processing a low-resolution (LR) input signal by utilization of the trained convolutional structural network. In the resolving method and system according to this disclosure, data after expansion may be processed by simple expansion hardware, without a large change algorithm; and complex algorithms are allocated into parallelizing design, and different servers operate mutually independent; and also, due to the modular design, the design proposals of functional modules may be modified by latter optimization.

Abstract: A method for converting an alcohol to a hydrocarbon fraction reduced in gaseous hydrocarbon content, the method comprising: (i) contacting said alcohol with a metal-loaded zeolite catalyst under conditions suitable for converting said alcohol to a first hydrocarbon fraction containing liquid hydrocarbons having at least five carbon atoms along with gaseous hydrocarbons having less than five carbon atoms, wherein said metal-loaded zeolite catalyst is catalytically active for converting said alcohol to said first hydrocarbon fraction; and (ii) selectively removing said gaseous hydrocarbons from the first hydrocarbon fraction and contacting said gaseous hydrocarbons with a metal-loaded zeolite catalyst under conditions suitable for converting said gaseous hydrocarbons into liquid hydrocarbons having at least five carbon atoms to produce a second hydrocarbon fraction reduced in gaseous hydrocarbon content, wherein the metal-loaded zeolite catalyst in steps (i) and (ii) are the same or different.

Abstract: The present disclosure relates to an image processing method and a device, wherein the image processing method includes: acquiring a first image, the first image including an image formed with respect to a skin part of a patient to be diagnosed which needs diagnosis; inputting the first image into a neural network, to acquire position information of a pathologic change area in the first image; acquiring a boundary of the pathologic change area in the first image, acquiring an original image and a mask image which include the pathologic change area from the first image; fusing the mask image and the original image, obtaining a target image corresponding to the pathologic change area; wherein the target image is an image for diagnosing the pathologic change area, pixel points in the target image correspond to those in the original image and the mask image one by one.

Abstract: The present application discloses a facial image processing apparatus. The facial image processing apparatus includes a memory; and one or more processor. The memory and the at least one processor are communicatively connected with each other. The memory stores computer-executable instructions for controlling the one or more processors to automatically identify a facial feature from a facial image; automatically extract an image portion defining the facial feature from the facial image; perform a detail enhancement process on the image portion to obtain a detail-enhanced image portion corresponding to the image portion; and perform an image composition process to compose the detail-enhanced image portion and the facial image to obtain an enhanced facial image.

Abstract: According to the embodiments of the present disclosure, there is provided a method for detecting feature points in an image. The method comprises: processing data of the image using a first type of convolutional layers in a Convolutional Neural Network (CNN) to generate first processed data, wherein the first type of convolutional layers comprise convolution kernels having non-shared weights; processing the first processed data using a second type of convolutional layers in the CNN to generate second processed data, wherein the second type of convolutional layers comprise convolution kernels having shared weights; and determining the feature points in the image based on the second processed data. In addition, the embodiments of the present disclosure further provide a corresponding device and a corresponding computer readable storage medium.

Abstract: A catalyst composition for converting an alcohol to olefins, the catalyst composition comprising the following components: (a) beta zeolite; (b) at least one element selected from the group consisting of zinc, magnesium, calcium, strontium, sodium, and potassium; and (c) at least one element selected from the group consisting of hafnium, yttrium, zirconium, tantalum, niobium, and tin; wherein the components (b) and (c) are independently within or on a surface of said beta zeolite. The catalyst may also further include component (d), which is copper or silver. Also described herein is a method for converting an alcohol to one or more olefinic compounds, the method comprising contacting the alcohol with a catalyst at a temperature of at least 100° C. and up to 500° C. to result in the alcohol being converted to the one or more olefinic compounds.

Abstract: According to embodiments of the present disclosure, a method for processing an adaptive media service at an encoder includes a first acquisition step of acquiring a first data stream including first image encoding data obtained by encoding a first image sequence, a second acquisition step of acquiring at least one second data stream, each second data steam including second image encoding data obtained by encoding a second image sequence and a target optimization parameter corresponding to the second image encoding data, a first selection step of selecting one data stream from a first data stream set in accordance with a condition of the receiver, the first data stream set at least including the first data stream and the at least one second data stream, and a first transmission step of transmitting the selected data stream to the receiver.

Abstract: The present application discloses a microphone. The microphone includes a voice sensor configured to collect an audio signal; a converter connected to the voice sensor and configured to convert the audio signal into a digital audio signal; a signal transceiver connected to the converter and configured to transmit the digital audio signal and receive a voice status determination signal generated based on the digital audio signal; and an indicator configured to generate one or more indication signals based on the voice status determination signal. The voice status determination signal includes one or a combination of an acoustic quality determination signal and a health status determination signal. The one or more indication signals includes one or a combination of an acoustic quality indication signal and a health status indication signal.

Abstract: The present disclosure provides a method and an apparatus for detecting a 3D image, an electronic device, and a computer-readable medium. The method for detecting a 3D image includes layering a 3D image to obtain at least one 3D subimage. The 3D subimage contains a plurality of 2D images. The method includes performing an intra-layer clustering on the 3D subimage to obtain a superpixel grid. The method includes inputting the superpixel grid into a neural network for detecting. The method includes detecting, in response to detecting an object in the superpixel grid, the 3D subimage forming the superpixel grid containing the object to obtain and output a detection result.

Abstract: The present application discloses an apparatus for protecting a user's eye from blue light radiation, the apparatus includes a radiation detector configured to convert blue light from a light source into a photo voltage having a voltage value; a processor coupled to the radiation detector and configured to calculate a cumulative radiation intensity based on the voltage value cumulated over a time interval, and to compare the cumulative radiation intensity with a threshold value; and a controller coupled to the processor, configured to adjustably control blocking of at least a portion of blue light from the user's eye when the cumulative radiation intensity exceeds the threshold value.

Abstract: According to the embodiments of the present disclosure, there is provided a method for detecting feature points in an image. The method comprises: processing data of the image using a first type of convolutional layers in a Convolutional Neural Network (CNN) to generate first processed data, wherein the first type of convolutional layers comprise convolution kernels having non-shared weights; processing the first processed data using a second type of convolutional layers in the CNN to generate second processed data, wherein the second type of convolutional layers comprise convolution kernels having shared weights; and determining the feature points in the image based on the second processed data. In addition, the embodiments of the present disclosure further provide a corresponding device and a corresponding computer readable storage medium.

Abstract: The present disclosure provides a data processing method, a data processing device, and a computer readable storage medium. The data processing method includes: determining an encryption key according to first data; encrypting second data with the encryption key; and storing the first data in association with the encrypted second data.

Abstract: The present disclosure discloses a method and device for image encoding and a method and device for image decoding. The encoding method comprises steps of: downscaling an input high resolution HR image into a low resolution LR image by a downscaler; compressing the LR image using a first compression method; extracting an index value from at least one of the HR image and the LR image; determining a parameter from a parameter database using the index value; compressing the parameter using a second compression method different from the first compression method; and obtaining a data stream by merging the compressed parameter and the compressed LR image.

Abstract: A method for producing one or more hydrocarbon compounds from at least one of 2,3-butanediol, acetoin, and ethanol, the method comprising contacting said at least one of 2,3-butanediol, acetoin, and ethanol with a catalyst at a temperature of at least 100° C. and up to 500° C. to result in said 2,3-butanediol, acetoin, and/or ethanol being converted to said one or more hydrocarbon compounds, wherein said catalyst is either: (i) a catalyst comprising nanoparticles composed of (a) a first metal oxide selected from the group consisting of zirconium oxide, cerium oxide, titanium oxide, and lanthanum oxide, and (b) a main group metal oxide; or (ii) a catalyst comprising a zeolite loaded with at least one metal selected from the group consisting of copper, silver, nickel, palladium, platinum, rhodium, and ruthenium in an amount of 1-30 wt % by weight of the zeolite.

Abstract: The embodiments of the present disclosure disclose an image processing method and device. The image processing method comprises transforming a first image to obtain a plurality of second images; obtaining feature maps of each of the second images by performing feature extraction on the second images using a first machine learning unit selected from a group including at least one first machine learning unit; and inputting the feature maps of each of the second images to a second machine learning unit to obtain a processing result of the first image.