Abstract: A semiconductor with 3D flash memory storing cells includes a stack structure in each storing cell, a blocking layer, at least one floating gate layer, a tunnel dielectric layer, and a channel layer. The stack structure includes at least one control gate layer, at least one dielectric layer, and at least one erasing layer. The blocking layer is coplanar with the control gate layer. The floating layer is received in the blocking layer, and insulates the control gate layer by the blocking layers. The tunnel dielectric layer covers sides of the blocking layer and the floating gate layer. The channel layer is placed on a side of the tunnel electric layer. When the storing cell executes a data reading and writing process, a voltage is applied on the erasing layer to reduce a series resistance of the channel layer for rapid conduction by the semiconductor.

Abstract: A method for detecting defects in product applied in a computer device inputs an image of a product under test to an automatic encoder to obtain a reconstructed image, and the image is segmented into N image blocks and the reconstructed image is segmented into N image blocks. The computer device associates each of the N testing blocks with one reconstructed blocks according to positions of the N testing blocks in the image and positions of the N reconstructed blocks in the reconstructed image. The computer device further calculates mean square errors between each of the N testing blocks and each of the N reconstructed blocks, and associates each mean square error with each of the N testing blocks, whether the product has defects being determined based on the mean square errors corresponding to each of the N testing blocks.

Abstract: A method of detecting defects revealed in images of products obtains sample image training data. An underlying feature dimension of an autoencoder is selected and a score is obtained. By comparing the score with a standard score, an optimal underlying feature dimension is confirmed. A test image is inputted into the autoencoder with the optimal underlying feature dimension to obtain a reconstruction image. A reconstruction error between the test image and the reconstruction image is computed. By comparing the reconstruction error with the predefined threshold a result of analysis of the test image is outputted. An image defect detection apparatus and a computer readable storage medium applying the method are also provided.

Abstract: A method for detecting defects in multi-scale images and a computing device applying the method acquires a to-be-detected image and converts the to-be-detected image into a plurality of target images of preset sizes. Feature extraction is performed on each target image by using a pre-trained encoder to obtain a latent vector, the latent vector of each target image is inputted into a decoder corresponding to the encoder to obtain a reconstructed image and then into a pre-trained Gaussian mixture model to obtain an estimated probability. Reconstruction error is calculated according to each target image and the corresponding reconstructed image. A total error is calculated according to the reconstruction error of each target image and the corresponding estimated probability, and a detection result is determined according to the total error of each target image and a corresponding preset threshold, thereby improving an accuracy of defect detection.

Abstract: A scalp monitoring method applied to a smart hair dryer is provided. The method includes obtaining a plurality of head photos by photographing a head of a user using a photographing device. A head region corresponding to each of the plurality of head photos is identified. Once related parameters of each head region is identified based on the head photos corresponding to the each head region, a condition of a scalp of the each head region is analyzed based on the related parameters of the each head region and historical related parameters corresponding to the each head region.

Abstract: A block operation method, an electronic device, and a storage medium are provided. A plurality of clusters are calculated according to computing power and rewards of each blockchain node, a node computing power and reward carried by each broadcast block being determined when a blockchain node receives a broadcast block. A target cluster to which a blockchain node belongs is determined, and a target difficulty weighting is determined, corresponding to the target cluster. A target difficulty of the target blockchain node is determined according to the node power and reward and the target difficulty weighting. A block is generated after the blockchain calculations are processed according to the target difficulty, the method improves decentralization of the blockchain.

Abstract: A waterproof connecting structure includes a first housing, a second housing employs a waterproof adhesive layer between the two. The first housing includes a first mounting member with a first groove, the first groove includes a first recessed area. The second housing includes a second recessed area and a protrusion of a certain shape. The second recessed area surrounds an edge of the second housing, the protrusion is disposed close to the second recessed area, and penetrates into the first recessed area. The waterproof adhesive layer is disposed between the first housing and the second housing, and is accommodated in the first groove and the second recessed area. An electronic device including the waterproof connecting structure is also provided.

Abstract: A system and method for controlling multi-party communication during video conferences communicatively connects with at least two participating terminals, each manned by one participant in the conference. A voice acquisition module acquires speech and video at each participating terminal. A recognition module acquires information as to an action state of a participant in the video and audio of what participant is saying, and determines whether the action of participant includes speaking movements and whether the audio includes what is being said by the participant. A control module can control the volume of other participating terminals and adjust the volumes of microphones of simultaneous speakers, to be louder, fainter, or muted, depending on assigned priority of each participant, for orderly control of conferences and as an overall recording.

Abstract: A method for processing data, applied in an electronic device, obtains dimensions of a target data set by dimensionality reduction processing, and creates a search index based on the target data set. A denominator d of a noise ratio is set. An unlabeled data point P is selected from the target data set, and neighbors of the data point P are searched for according to the search index to obtain a neighbor data set. A number of data in the neighbor data set of a type which is different from type of the data point P is calculated, the calculated number is set to be a numerator c of the noise ratio. The noise ratio A=c/d is calculated, and if greater than a preset noise ratio, the data point P is labeled as noise data. The present disclosure shortens the time of processing training data.

Abstract: A machine learning model training method includes receiving a problem type to be processed, determining a machine learning model corresponding to the problem type, receiving sample data to train the determined machine learning model, analyzing training results of the determined machine learning model obtained after training is completed and displaying the training results that meet preset conditions, and providing a machine learning model corresponding to the training result that meets the preset conditions.

Abstract: A support assembly and a chassis structure for positioning and support of large and heavy computer cards. The chassis structure includes a housing, a main board in the housing, and a graphics card slot on the main board. The housing includes a positioning frame on the main board and the support assembly on the frame. The support assembly is detachable. The support assembly includes positioning base plate, positioning member, and adjusting member. The positioning member is on a base which is detachable from the positioning frame. The adjusting member is moveable. The positioning member includes a first support portion, the adjusting member includes a second support portion. Depending on card size, either the first support portion or the second support portion abuts against an end side of a graphics card away from the graphics card slot, to position and firmly hold in place graphics cards of different sizes.

Abstract: An image defect detection method is used in an electronic device. The electronic device determines a training image feature set, and trains a Gaussian mixture model by using the feature set to obtain an image defect detection model and a reference error value. An image for analysis is input into the autoencoder to obtain a second implicit vector and a second reconstructed image, and to calculate a second reconstruction error. The electronic device obtains a test image feature of the image for analysis according to the second reconstruction error and the second implicit vector, and inputs the test image feature into the image defect detection model to obtain a prediction score. The image for analysis is determined to reveal a defect when the prediction score is less than or equal to the reference error value.

Abstract: An optical lens utilizing individual lenses which are, all but one, made from plastic materials but with an optical clarity unaffected by temperature swings, includes first to sixth lenses. The first to sixth lenses of the optical lens meets conditions of composite formula 4.55<|EFL2|/|EFL1|<4.95, 1.91<(N1?N3)/(N2?N3)<1.93, 0.16<(V1?V3)/(V2?V3)<0.20, 0.95<(N4?N6)/(N5?N6)<1.05 and 0.95<(V4?V6)/(V5?V6)<1.05. EFL1 is a focal length of the first to third lenses, and EFL2 is a focal length of the fourth to sixth lenses. N1, N2, N3, N4, N5, and N6 are respective refractive indexes of the first to sixth lenses, and V1, V2, V3, V4, V5, and V6 are their respective Abbe numbers.

Abstract: A memory chip includes a memory cell circuit, a periphery circuit, an interconnect structure, and a control logic circuit. The periphery circuit is positioned under the memory cell circuit and electrically connected to the memory cell circuit. The interconnect structure is positioned on a side surface of the memory cell circuit. The control logic circuit is positioned under the interconnect structure. The control logic circuit is electrically connected to the interconnect structure and the periphery circuit and includes a dynamic random-access memory.

Abstract: A comment management method applied to a server is provided. The method includes detecting comment parameters of an article. Whether or not to activate a comment management mechanism for the article is determined according to the comment parameters of the article. All comments of the article are managed by activating the comment management mechanism. Once an activation duration of the comment management mechanism is activated, the comment management mechanism is canceled when the activation duration reaches a preset duration.

Abstract: A well cover assembly includes a monitoring device and a well cover. The well cover includes a first protrusion and a second protrusion. A through hole is defined on the well cover and surrounded by the second protrusion. The monitoring device can be installed on the well cover. The monitoring device includes a monitoring terminal and a fixing bracket. The fixing bracket includes a first bracket and a second bracket. One end of the first bracket is fixed to the monitoring terminal, and another end can protrude from the through hole. The second bracket is connected to the end of the first bracket protruding from the through hole, the second bracket can extend from the end of the first bracket toward an edge of the second protrusion and toward the first protrusion. The second bracket further can clamp with each of the second protrusion and the first protrusion.

Abstract: A method for automatically generating news event of a certain topic applied in an electronic device analyzes text of the news event by a topic model to obtain topics, a probability distribution of keywords in each topic is established, and a time interval distribution of the keywords in each topic is calculated. Keywords within a preset probability distribution range are selected to reduce the size of a word bag relating to the topic, and a time interval range of the reduced word bag of the topic is determined. A calculation of text similarities of the text in a database is made to obtain a news article corresponding to each topic according to the time interval range of the reduced word bag, and a title of the news article as a target topic of the text of the news event is determined.

Abstract: A method for marking defects of products implemented in an electronic device is provided. The method includes obtaining at least one detection image of a product to be marked; recognizing a position and a type of at least one defect on the product according to the at least one detection image; transmit the position and the type of the at least one apparent defect to a robot arm; controlling the robot arm to mark the at least one defect on an adhesive film according to the position and the type of the at least one defect; and controlling a film coating unit to apply the adhesive film which is marked to the product.

Abstract: A method for classifying cells densities by cell images being input into artificial computer intelligence obtains positional information of all central points of all groups of first encoding features generated when training a model of convolutional neural network and ranges of densities of images of biological cells represented by different central points. The method inputs a test image of the biological cells into a trained model of the convolutional neural network to encode the test image, to obtain a second encoding feature. The method also determines a central point nearest to the second encoding feature according to the positional information. The method determines a range of densities of the test image according to the ranges of densities of the images represented by different central points and the central point nearest to the second encoding feature. An electronic device and a non-transitory storage medium are also disclosed.