Abstract: A ventilation fan is disclosure and includes a housing, a grille support, a fan module, a base, plural connecting columns and a function module. The grille support and the base form a grille structure mounted under a ceiling. The fan module disposed within the housing forms an airflow flowing. The base and the grille support are connected through the plural connecting columns and spaced apart from each other. An inlet radially formed between the base and the grille support is in communication with the outlet through the grille opening. The base includes a holder having a holding opening axially downward and faced away from the housing. The function module is disposed within the holder through the holding opening.

Abstract: A computer-implemented method includes capturing visual data of an environment using an image sensor of an electronic device and non-visual data of the environment using one or more non-image sensors of the electronic device. Feature descriptors of one or more objects in the environment are generated using the visual data of the environment and the non-visual data of the environment. A map of the environment is generated using the feature descriptors of the one or more objects. One or more virtual objects are anchored to at least one of the objects using the map. The visual data, the non-visual data, and the map are combined in a digital multimedia container file. The digital multimedia container file is stored on the electronic device or on another electronic device connected to the electronic device.

Abstract: A circuit protection apparatus (100) is used to protect an LED drive circuit (200), and the circuit protection apparatus (100) includes a first switch unit (1) and a snubber circuit (3). The first switch unit (1) provides an electrical connection between an input terminal (100A) and the LED drive circuit (200) according to the normality of an input current (Iin) flowing through the input terminal (100A). The snubber circuit (3) provides a first delay time period (Td1) according to an input power (Vin). The snubber circuit (3) provides a start signal (Ss) to the LED drive circuit (200) according to the end of the first delay time period (Td1), and controls a first ground point (G1) of the snubber circuit (3) to be coupled to a second ground point (G2) of the LED drive circuit (200).

Abstract: A ventilation fan includes a fan module provided in a housing attached to an opening in a ceiling, a grille support mounted under the ceiling to correspond to the opening, a lighting module having base and an LED element provided in the base and configured to project light axial and radially, a plurality of columns connecting the grill support and the base to define an inlet facing radially, and a function module provided in a holding opening of the base.

Abstract: A computer-implemented method includes capturing visual data of an environment using an image sensor of an electronic device and non-visual data of the environment using one or more non-image sensors of the electronic device. Feature descriptors of one or more objects in the environment are generated using the visual data of the environment and the non-visual data of the environment. A map of the environment is generated using the feature descriptors of the one or more objects. One or more virtual objects are anchored to at least one of the objects using the map. The visual data, the non-visual data, and the map are combined in a digital multimedia container file. The digital multimedia container file is stored on the electronic device or on another electronic device connected to the electronic device.

Abstract: Systems and methods are described for implementing a coordinator within a coordinated environment, which environment includes set of coordinated devices managed by the coordinator. The coordinator can be provisioned with a set of tasks, each task corresponding to a segment of code that can be executed by the coordinator, such as to manage the coordinated devices. The coordinator can further be provisioned with event flow information designating a routing of inputs to the coordinator computing device to destinations, such as task executions or coordinated devices. On receiving input, the coordinator can reference the event flow information to pass the input to an appropriate destination.

Abstract: The present invention discloses an image enlarging method having super resolution enlarging mechanism that includes the steps outlined below. An enlarging module of a neural network system receives an input image to generate an enlarged image. A front end convolutional path included in a neural network module of the neural network system receives the input image to perform convolution to generate a front end operation output result. Branching convolutional paths included in the neural network module respectively receive the front end operation output result to perform convolution to generate groups of output image residues. A mixing module of the neural network system weights the output image residues according to weighing settings related to image regions of the input image and mixes the weighted output image residues to generate a group of final output image residue such that an enhancement module enhances the enlarged image to generate an output enlarged image.

Abstract: A current transmission assembly and a current transmission system are provided. The current transmission system includes the current transmission assembly and a circuit board structure. The current transmission assembly includes a pluggable component, at least one conductor component, and at least one electrically connecting component. The pluggable component includes a housing, two sets of electrically conductive arms, and two connecting members. Each of the two sets of electrically conductive arms is disposed inside the housing. Each of the conductor components includes an electrical insulator and a wire main body. The electrical insulator encircles the wire main body, so that a first terminal and a second terminal are exposed from the wire main body, and the first terminal is connected to one of the two connecting members. Each of the electrically connecting components includes a connecting portion, to which the second terminal of the wire main body is fixed.

Abstract: A system for image scaling and enhancement is provided. The system includes a scaling processing unit, a deep-learning residue network unit and a combination unit. The filter scaling processing unit is configured to upscale a low-resolution image to output a high-resolution image. The deep-learning residue network unit is operated based on a deep-learning result, and configured to output a high-resolution residue image corresponding to the low-resolution image. The combination unit is configured to adjust the high-resolution residue image according to a weighting factor and combine an adjusted high-resolution residue image and the high-resolution image, in order to output an enhanced image, wherein the weighting factor is different from a reference weighting factor being used in a deep-learning procedure for training the deep-learning residue network unit.

Abstract: A Lamb wave resonator includes a piezoelectric material layer, a first finger electrode, a second finger electrode, at least two floating electrodes, and at least two gaps. The first finger electrode is disposed on one side of the piezoelectric material layer and includes a first main portion and first fingers. The second finger electrode is disposed on the side of the piezoelectric material layer and includes a second main portion and second fingers. The first fingers are parallel to and alternately arranged with the second fingers. The floating electrodes are disposed between each first finger and each second finger, and the gaps are disposed at two ends of each floating electrode, respectively.

Abstract: A traffic condition prediction system and a traffic condition prediction method are disclosed. The method includes: determining a center of circle in a surveillance image of a target traffic scene; determining a first circle based on the center of circle and a first radius; extracting a plurality of first feature points along the circumference of the first circle according to a first preset sampling frequency; generating a scene feature of the target traffic scene at least based on the first feature points; determining whether the scene feature and a scene feature of another traffic scene are similar; and when determining that they are similar, predicting traffic condition of the target traffic scene through a prediction model used for predicting traffic condition of the other traffic scene. The scene feature of the target traffic scene and that of the other traffic scene are generated in a same way.

Abstract: The present invention provides an object position determination circuit including a receiving circuit and a detecting circuit. In operations of the object position determination circuit, the receiving circuit receives an image signal; and the detecting circuit detects a position of an object in an Nth frame of the image signal, determines a partial region within an (N+M)th frame of the image signal according to the position of the object in the Nth frame, and only detects the partial region within the (N+M)th frame to determine a position of the object in the (N+M)th frame, wherein N and M are positive integers.

Abstract: A lighting ventilation fan is disclosure and includes a housing, a grille support, a fan module, a lighting base, plural connecting columns, a lighting module and a function module. The grille support, the lighting base and the lighting module form a grille structure mounted under a ceiling. The fan module disposed within the housing forms an airflow flowing. The lighting base and the grille support are connected through the plural connecting columns and spaced apart from each other. An inlet radially formed between the lighting base and the grille support is in communication with the outlet through the grille opening. The lighting base includes a holder having a holding opening axially downward and faced away from the housing. The lighting module is disposed in the lighting base and has a light-emitting surface emitting light axially and radially. The function module is disposed within the holder through the holding opening.

Abstract: The present disclosure provides a plug connector adapted to insert into a receptacle connector, the receptacle connector includes a cage having an opening. The plug connector includes a metal shell and a conductive elastic member. The metal shell is provided with a recessed groove. The conductive elastic member includes a conductive elastic body, the conductive elastic body has a holding portion held in the recessed groove and a first electromagnetic shielding portion extending out of the recessed groove from the holding portion, when the plug connector is inserted forwardly into the receptacle connector, the first electromagnetic shielding portion enters into the opening of the cage of the receptacle connector and mechanically and electrically contacts the cage and the metal shell. However, some embodiments may not include a holding portion or recessed groove.

Abstract: A computing device divides a training image into a plurality of training blocks, and the training image includes a training object. The computing device calculates, for each of the training blocks, a correct confidence score of the training object covering the training block according to an image-marking data and a confidence-score-translating function, and the image-marking data includes a piece of location information of the training object in the training image. Then, the computing device trains a deep-learning model with the training image, the correct confidence scores and the image-marking data to generate the object-detecting model.

Abstract: A traffic condition prediction system and a traffic condition prediction method are disclosed. The method includes: determining a center of circle in a surveillance image of a target traffic scene; determining a first circle based on the center of circle and a first radius; extracting a plurality of first feature points along the circumference of the first circle according to a first preset sampling frequency; generating a scene feature of the target traffic scene at least based on the first feature points; determining whether the scene feature and a scene feature of another traffic scene are similar; and when determining that they are similar, predicting traffic condition of the target traffic scene through a prediction model used for predicting traffic condition of the other traffic scene. The scene feature of the target traffic scene and that of the other traffic scene are generated in a same way.

Abstract: Systems and methods are described for implementing a framework for testing on-demand code execution that is configured to be executed on coordinated devices. The testing framework allows the execution of tasks in a network based on-demand system. The resulting generation of an I/O file for accessing local resources can be intercepted and either processed via a handler process or transmitted to the local resource.

Abstract: A system for image scaling and enhancement is provided. The system includes a scaling processing unit, a deep-learning residue network unit and a combination unit. The filter scaling processing unit is configured to upscale a low-resolution image to output a high-resolution image. The deep-learning residue network unit is operated based on a deep-learning result, and configured to output a high-resolution residue image corresponding to the low-resolution image. The combination unit is configured to adjust the high-resolution residue image according to a weighting factor and combine an adjusted high-resolution residue image and the high-resolution image, in order to output an enhanced image, wherein the weighting factor is different from a reference weighting factor being used in a deep-learning procedure for training the deep-learning residue network unit.

Abstract: A feature determination apparatus and method adapted to multiple object sizes are provided. The apparatus individually supplies each of the object images to a convolution neural network having several convolution layers to generate multiple feature maps corresponding to each object image. The apparatus calculates a feature amount of each feature image of each object image. The apparatus determines an invalid layer start number of each object image according to a preset threshold and the feature amount corresponding to each object image. The apparatus determines a feature map extraction recommendation for each of a plurality of object sizes according to a size of each object image and the invalid layer start number of each object image.

Abstract: A computing device divides a training image into a plurality of training blocks, and the training image includes a training object. The computing device calculates, for each of the training blocks, a correct confidence score of the training object covering the training block according to an image-marking data and a confidence-score-translating function, and the image-marking data includes a piece of location information of the training object in the training image. Then, the computing device trains a deep-learning model with the training image, the correct confidence scores and the image-marking data to generate the object-detecting model.