Abstract: A brake (200) comprising a braking surface (202); a brake lever (206) arranged to move between a retracted position and an engaged position; a brake lining (210) and at least one non-contact sensor (212). The brake lining is disposed between the braking surface and the brake lever such that when the brake lever is in the engaged position the brake lining is in contact with the braking surface. The at least one non-contact sensor is arranged to output a signal dependent on the distance between the non-contact sensor and the braking surface.

Abstract: Disclosed is a data recognition model construction apparatus. The data recognition model construction apparatus includes a video inputter configured to receive a video, an image composition unit configured to, based on a common area included in each of a plurality of images that form at least a portion of the video, generate a composition image by overlaying at least a portion of the plurality of images, a learning data inputter configured to receive the generated composition image, a model learning unit configured to make a data recognition model learn using the generated composition image, and a model storage configured to store the learnt data recognition model.

Abstract: Disclosed are an artificial intelligence (AI) system using a machine learning algorithm such as deep learning, and an application thereof. The present disclosure provides an electronic device comprising: an input unit for receiving content data; a memory for storing information on the content data; an audio output unit for outputting the content data; and a processor, which acquires a plurality of data keywords by analyzing the inputted content data, matches and stores time stamps, of the content data, respectively corresponding to the plurality of acquired keywords, based on a user command being inputted, searches for a data keyword corresponding to the inputted user command among the stored data keywords, and plays the content data based on the time stamp corresponding to the searched data keyword.

Abstract: An electronic apparatus and an operating method are provided. The electronic apparatus includes a storage, at least one sensor, and at least one processor configured to execute stored instructions to while the electronic apparatus is moving, capture a surrounding image by using the at least one sensor, when an unable-to-move situation occurs while the electronic apparatus is moving, generate context data including a surrounding image captured within a predetermined time from a time when the unable-to-move situation has occurred, store, in the storage, the generated context data corresponding to the unable-to-move situation having occurred, and learn the stored context data by using one or more data recognition models.

Abstract: The disclosure relates to an artificial intelligence (AI) system using a machine learning algorithm such as deep learning, and an application thereof. In particular, an electronic apparatus, a document displaying method thereof, and a non-transitory computer readable recording medium are provided. An electronic apparatus according to an embodiment of the disclosure includes a display unit displaying a document, a microphone receiving a user voice, and a processor configured to acquire at least one topic from contents included in a plurality of pages constituting the document, recognize a voice input through the microphone, match the recognized voice with one of the acquired at least one topic, and control the display unit to display a page including the matched topic.

Abstract: An electronic device, a warning message providing method therefor, and a non-transitory computer-readable recording medium are provided. Disclosed is an artificial intelligence (AI) system using a machine learning algorithm such as deep learning and an application thereof.

Abstract: Provided is an Artificial Intelligence (AI) system for simulating a human brain's functions, such as recognition, decision, etc., by using a machine learning algorithm such as deep learning, etc. and applications of the AI system. Provided is an electronic device including: a camera configured to capture an outside image of a vehicle, and a processor configured to execute one or more instructions stored in a memory, wherein the processor executes the one or more instructions to: determine, from the captured image, at least one object for estimating lane information; estimate, from the image, lane information of a road on which the vehicle is traveling, based on a distance between the determined at least one object and the vehicle and a vanishing point of the image; and output guide information for guiding driving of the vehicle based on the estimated lane information.

Abstract: Disclosed are an artificial intelligence (AI) system using a machine learning algorithm such as deep learning, and an application thereof. The present disclosure provides an electronic device comprising: an input unit for receiving content data; a memory for storing information on the content data; an audio output unit for outputting the content data; and a processor, which acquires a plurality of data keywords by analyzing the inputted content data, matches and stores time stamps, of the content data, respectively corresponding to the plurality of acquired keywords, based on a user command being inputted, searches for a data keyword corresponding to the inputted user command among the stored data keywords, and plays the content data based on the time stamp corresponding to the searched data keyword.

Abstract: A passenger conveyance system (2, 102, 202) is provided which includes a first component (12, 112, 212) arranged to rotate about a first rotation axis A1 and a second component (16, 116, 216) arranged to rotate about a second rotation axis A2; at least one magnet (20,120, 220); and at least one sensor (24, 124, 224). Either the at least one sensor (24, 124, 224) or the at least one magnet (20, 120, 220) is fixed to the first component (12, 112, 212). The sensor (24, 124, 224) is arranged to measure a displacement to the at least one magnet (12, 112, 212), and the system (2, 102, 202) is arranged to use the measured displacement to determine information indicative of the alignment of the first and second components (12, 112, 212; 16, 116, 216).

Abstract: Disclosed are an artificial intelligence (AI) system using a machine learning algorithm such as deep learning, and an application thereof. The present disclosure provides an electronic device comprising: an input unit for receiving content data; a memory for storing information on the content data; an audio output unit for outputting the content data; and a processor, which acquires a plurality of data keywords by analyzing the inputted content data, matches and stores time stamps, of the content data, respectively corresponding to the plurality of acquired keywords, based on a user command being inputted, searches for a data keyword corresponding to the inputted user command among the stored data keywords, and plays the content data based on the time stamp corresponding to the searched data keyword.

Abstract: Chain tension monitoring device (40) is configured for monitoring a chain tension force (FC) of a drive chain (27) extending in a longitudinal direction forming closed loop between two sprockets (26, 28). The chain tension monitoring device (40) comprises a sensor device (41) configured for mechanically contacting the drive chain (27), detecting movement of the drive chain (27) transversely, in particular orthogonally, to the longitudinal direction of the drive chain (27), and providing a detection signal indicating the detected movement of the drive chain (27); and an evaluator (50) configured for receiving the detection signal provided by the sensor device (41) and determining a chain tension force (FC) of the drive chain (27) from said detection signal.

Abstract: Disclosed is a data recognition model construction apparatus. The data recognition model construction apparatus includes a video inputter configured to receive a video, an image composition unit configured to, based on a common area included in each of a plurality of images that form at least a portion of the video, generate a composition image by overlaying at least a portion of the plurality of images, a learning data inputter configured to receive the generated composition image, a model learning unit configured to make a data recognition model learn using the generated composition image, and a model storage configured to store the learnt data recognition model.

Abstract: An anti-fuse device includes an anti-fuse array and a biasing circuit. The anti-fuse array includes an anti-fuse cell that has a gate node, a gate oxide layer and a source-drain node. The biasing circuit is coupled to the anti-fuse array and is configured to bias the gate node of the anti-fuse cell with a first bias voltage during a program operation, and bias the source-drain node of the anti-fuse with a second bias voltage during the program operation. A voltage level of the first bias voltage is lower than a voltage level of the second bias voltage, and a voltage difference between the first bias voltage and the second bias voltage is higher than a gate oxide breakdown voltage of the gate oxide layer.

Abstract: A passenger conveyance system (2, 102, 202) is provided which includes a first component (12, 112, 212) arranged to rotate about a first rotation axis A1 and a second component (16, 116, 216) arranged to rotate about a second rotation axis A2; at least one magnet (20,120, 220); and at least one sensor (24, 124, 224). Either the at least one sensor (24, 124, 224) or the at least one magnet (20, 120, 220) is fixed to the first component (12, 112, 212). The sensor (24, 124, 224) is arranged to measure a displacement to the at least one magnet (12, 112, 212), and the system (2, 102, 202) is arranged to use the measured displacement to determine information indicative of the alignment of the first and second components (12, 112, 212; 16, 116, 216).

Abstract: Disclosed is a data recognition model construction apparatus. The data recognition model construction apparatus includes a video inputter configured to receive a video, an image composition unit configured to, based on a common area included in each of a plurality of images that form at least a portion of the video, generate a composition image by overlaying at least a portion of the plurality of images, a learning data inputter configured to receive the generated composition image, a model learning unit configured to make a data recognition model learn using the generated composition image, and a model storage configured to store the learnt data recognition model.

Abstract: A people conveyor (2), which is configured for conveying passengers by at least one conveyance band (8) travelling along a closed loop, comprises at least one handrail element (6) which is configured for moving parallel to the at least one conveyance band (8) along a travel path forming a closed loop; and at least one force sensor (18a, 18b), which is configured for detecting a force (FS1, FS2) exerted by the at least one handrail element (6) in a direction transverse to the direction of movement of the at least one handrail element (6) and for providing a corresponding force signal.

Abstract: A people conveyor (1) comprises a band (12) of conveyance elements (13) connected to and driven by at least one drive chain (15, 27) comprising a plurality of chain links (34, 36). The people conveyor (1) further comprises at least one inductive sensor (40, 41) arranged laterally next to the at least one drive chain (15, 27) and configured for monitoring the chain links (34, 36) passing by the at least one inductive sensor (40, 41).

Abstract: A people conveyor (1) comprises a truss (2) extending between two landing portions (20, 21); a band (12) of conveyance elements (13) forming a closed loop extending in a conveyance direction between the two landing portions (20, 21); a drive machine (25) configured for driving the band (12) of conveyance elements (13); and at least two magneto-inductive sensors (36a, 36b, 36c) mounted to the truss (2). The at least two magneto-inductive sensors (36a, 36b, 36c) are configured for providing sensor signals which allow determining the position and orientation of the drive machine (25) with respect to the truss (2).

Abstract: The disclosure relates to an artificial intelligence (AI) system using a machine learning algorithm such as deep learning, and an application thereof. In particular, an electronic apparatus, a document displaying method thereof, and a non-transitory computer readable recording medium are provided. An electronic apparatus according to an embodiment of the disclosure includes a display unit displaying a document, a microphone receiving a user voice, and a processor configured to acquire at least one topic from contents included in a plurality of pages constituting the document, recognize a voice input through the microphone, match the recognized voice with one of the acquired at least one topic, and control the display unit to display a page including the matched topic.

Abstract: A brake (200) comprising a braking surface (202); a brake lever (206) arranged to move between a retracted position and an engaged position; a brake lining (210) and at least one non-contact sensor (212). The brake lining is disposed between the braking surface and the brake lever such that when the brake lever is in the engaged position the brake lining is in contact with the braking surface. The at least one non-contact sensor is arranged to output a signal dependent on the distance between the non-contact sensor and the braking surface.