Abstract: The invention relates to a method for judging risk of suffering kidney cancer. The method includes detecting a PSMB9 protein concentration value from a test sample. And a risk factor value is obtained after processing the PSMB9 protein concentration value with an age. When the score of the risk factor value is greater than a defined threshold value of the risk factor threshold value, then the test sample is classified as a high risk sample of a of potential kidney cancer patient.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an image embedding model. In one aspect, a method comprises: obtaining training data comprising a plurality of training examples, wherein each training example comprises: an image pair comprising a first image and a second image; and selection data indicating one or more of: (i) a co-click rate of the image pair, and (ii) a similar-image click rate of the image pair; and using the training data to train an image embedding model having a plurality of image embedding model parameters.

Abstract: Systems and techniques for target object retrieval may include or utilize an image capture device, and a task planner. The image capture device may receive an image of an environment including identified objects. The task planner may determine potential actions, calculate a probability of success of achieving a desired goal for each of the potential actions based on an action prediction model, the corresponding potential action, a current state of the environment, any previously taken action, and the desired goal, select a potential action associated with the highest calculated probability of success, and simulate a subsequent state based on the selected potential action and a dynamic prediction model. The potential actions may be associated with an identified object of the identified objects and an operation to be performed on the identified object.

Abstract: According to one aspect, intersection scenario description may be implemented by receiving a video stream of a surrounding environment of an ego-vehicle, extracting tracklets and appearance features associated with dynamic objects from the surrounding environment, extracting motion features associated with dynamic objects from the surrounding environment based on the corresponding tracklets, passing the appearance features through an appearance neural network to generate an appearance model, passing the motion features through a motion neural network to generate a motion model, passing the appearance model and the motion model through a fusion network to generate a fusion output, passing the fusion output through a classifier to generate a classifier output, and passing the classifier output through a loss function to generate a multi-label classification output associated with the ego-vehicle, dynamic objects, and corresponding motion paths.

Abstract: A method includes steps of: based on protein structure data, selecting a residue pair that includes a specific residue and a paired residue respectively of two wild-type protein chains of a protein complex; determining a mutant residue to substitute for the specific residue; for a target interface between the mutant residue and the paired residue, calculating an atomic distance and an atomic interaction force based on the protein structure data and amino acid structure data; and estimating binding free energy of the target interface by feeding the atomic distance, the atomic interaction force, and physicochemical information related to the specific residue and the mutant residue into a deep neural network.

Abstract: An antenna structure of reduced size but operating at multiple frequencies, applied to an electronic device, includes a housing, a system ground plane, and a first feed point. The housing has at least one portion made of metal material and defines a first gap and a second gap. The housing between the first gap and the second gap forms a first radiation portion. The system ground plane is positioned in the housing and defines a first slit. The first slit corresponds to the first radiation portion and communicates with the second gap. The first feed point is positioned on the first radiation portion and is electrically connected to a first feed source for feeding current and signal to the first radiation portion.

Abstract: A method includes: determining a mutation frequency for each residue in a wild-type spike protein of a specific virus; for each residue in the protein, counting a total number of contact residues related to said each residue and P antibodies based on P entries of protein structure data; for each residue in the protein, for a condition that said each residue mutates into one common amino acid residue, determining a normalized binding free energy value using a pre-established model based on the protein structure data, and determining a mutation effect score based on the mutation frequency, the total number of contact residues and the normalized binding free energy value; generating a mutation effect epitope map related to the mutation effect scores determined for all residues in the protein and all common amino acid residues; and determining, based on the map, a region in the protein as a target epitope.

Abstract: A phase interpolator capable of preventing a glitch from being generated during a clock signal switching operation and a clock signal selector thereof are provided. The clock signal selector includes a selector and a selection signal generator. The selector receives multiple clock signals with different phases. The selector selects one of the clock signals according to a selection signal to generate a selected clock signal. The selection signal generator is coupled to the selector and generates the selection signal. When the selector switches from selecting a first clock signal to selecting a second clock signal as the selected clock signal, the selection signal generator generates a set time point according to a transition point of one of the first clock signal and the second clock signal whose phase lags behind a phase of the other, and generates the selection signal according to the set time point.

Abstract: An image object classification method and system are disclosed. The method is executed by a processor coupled to a memory. The method includes: providing an image file including at least one image object, performing a process of extracting multiple binary-classified characteristics on the image object to obtain a plurality of first results independent of each other in categories, combining the plurality of first results in a manner of dimensionality reduction based on concatenation, performing a process of characteristics abstraction on the combined first results to obtain a second result, and performing a process of characteristics integration on the plurality of first results and the second result in a manner of dot product of matrices to obtain a classification result.

Abstract: A system and method for learning naturalistic driving behavior based on vehicle dynamic data that include receiving vehicle dynamic data and image data and analyzing the vehicle dynamic data and the image data to detect a plurality of behavioral events. The system and method also include classifying at least one behavioral event as a stimulus-driven action and building a naturalistic driving behavior data set that includes annotations that are based on the at least one behavioral event that is classified as the stimulus-driven action. The system and method further include controlling a vehicle to be autonomously driven based on the naturalistic driving behavior data set.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an image embedding model. In one aspect, a method comprises: obtaining training data comprising a plurality of training examples, wherein each training example comprises: an image pair comprising a first image and a second image; and selection data indicating one or more of: (i) a co-click rate of the image pair, and (ii) a similar-image click rate of the image pair; and using the training data to train an image embedding model having a plurality of image embedding model parameters.

Abstract: A method for analyzing a viewing direction of an electronic component includes inputting a package type and a file image of an electronic component, with the file image having at least one engineering drawing image, and the at least one engineering drawing image being a view of the electronic component in at least one viewing direction; querying and acquiring a viewing direction detection model meeting the package type from a database, with the database storing respective viewing direction detection models of different package types of electronic components; inputting the file image into the viewing direction detection model of the package type to identify the viewing direction of the at least one engineering drawing image; and outputting the viewing direction of the at least one engineering drawing image of the electronic component.

Abstract: A method for analyzing a specification parameter of an electronic component includes inputting a package type and at least one engineering drawing image of an electronic component; acquiring a probability value that in each view of the different viewing directions each of the plurality of specification parameter of the electronic component is labeled; taking the view of each of the plurality of specification parameters in the view direction with a highest probability value as a recommended view; performing a box selection on the plurality of specification parameters for at least one engineering drawing image with the same viewing direction as that of the recommended view by an object detection model; and identifying box-selected specification parameters to acquire a size value of identified specification parameters from the at least one engineering drawing image, and converting the size value into a corresponding editable text for output.

Abstract: A system and method for providing unsupervised domain adaption for spatio-temporal action localization that includes receiving video data associated with a source domain and a target domain that are associated with a surrounding environment of a vehicle. The system and method also include analyzing the video data associated with the source domain and the target domain and determining a key frame of the source domain and a key frame of the target domain. The system and method additionally include completing an action localization model to model a temporal context of actions occurring within the key frame of the source domain and the key frame of the target domain and completing an action adaption model to localize individuals and their actions and to classify the actions based on the video data. The system and method further include combining losses to complete spatio-temporal action localization of individuals and actions.

Abstract: A system and method for risk object identification via causal inference that includes receiving at least one image of a driving scene of an ego vehicle and analyzing the at least one image to detect and track dynamic objects within the driving scene of the ego vehicle. The system and method also include implementing a mask to remove each of the dynamic objects captured within the at least one image. The system and method further include analyzing a level of change associated with a driving behavior with respect to a removal of each of the dynamic objects. At least one dynamic object is identified as a risk object that has a highest level of influence with respect to the driving behavior.

Abstract: Systems and methods for bird's eye view (BEV) segmentation are provided. In one embodiment, a method includes receiving an input image from an image sensor on an agent. The input image is a perspective space image defined relative to the position and viewing direction of the agent. The method includes extracting features from the input image. The method includes estimating a depth map that includes depth values for pixels of the plurality of pixels of the input image. The method includes generating a 3D point map including points corresponding to the pixels of the input image. The method includes generating a voxel grid by voxelizing the 3D point map into a plurality voxels. The method includes generating a feature map by extracting feature vectors for pixels based on the points included in the voxels of the plurality of voxels and generating a BEV segmentation based on the feature map.

Abstract: A method includes: forming first, second, and third NWs; forming form first to fourth transistors in corresponding first to fourth groups of active regions, connecting selected transistors amongst the first and second transistors to form first and second input circuits respectively receiving a first input signal in a first domain and a second input signal in the first domain; connecting selected transistors amongst the first and third transistors and amongst the first and fourth transistors to respectively form a first single bit level shifter (SBLS) and a second SBLS; each SBLS operates in the second domain and receives correspondingly versions of the first and second input signals; and connecting selected transistors amongst the first and third transistors to form a control circuit for toggling the first and second SBLSs between a normal and a standby state, a portion of the control circuit and the first SBLS sharing the second NW.

Abstract: A foldable electronic device is disclosed and includes a first body, a second body, a hinge mechanism, and a cover. The hinge mechanism includes a first rack plate disposed to the first body, a second rack plate disposed to the second body, a first gear shaft meshed with the first rack plate, and a second gear shaft meshed with the second rack plate and the first gear shaft. The cover is movably disposed on the hinge mechanism and covers the hinge mechanism. When the second body rotates relative to the first body, the second rack plate, the second gear shaft, the first gear shaft and the first rack plate rotate in sequence, the first rack plate and the second rack plate abut against the cover, so the cover is away from the hinge mechanism and separated from the first body and the second body.

Abstract: An all-in-one (AIO) computer is provided. The AIO computer includes a main body, a first display, and a second display. The main body includes a front surface and a rear surface. The rear surface includes an inclined region. An angle of the inclined region with respective to the front surface is greater than 0 degree. The first display is disposed on the front surface. The second display is disposed in the inclined region.

Abstract: A display control method applicable to an all-in-one (AIO) computer is provided. The AIO computer includes a first monitor and a second monitor. The display control method includes: receiving a control instruction from the first monitor; projecting a display content on the second monitor according to the control instruction; and selectively enabling a touch control function of the second monitor according to the control instruction.