Abstract: A reactor for nanoparticle production comprising a main chamber including a first nozzle to which raw material gas is supplied, a lens housing connected to the main chamber in a fluidly movable manner and including a second nozzle for supplying flushing gas to the lens housing, a lens mounted on the lens housing, a light source for irradiating a laser, which passes through the lens to reach the raw material gas in the main chamber, and a hood for discharging nanoparticles generated in the main chamber. A cross-sectional area of at least a part of the lens housing decreases along a direction facing the main chamber.

Abstract: Method and apparatus for etching a thin layer including silicon nitride formed on a substrate are disclosed. Etchant including phosphoric acid and water is supplied on the substrate so that a liquid layer is formed on the substrate. The thin layer is etched by reaction between the thin layer and the etchant. Thickness of the liquid layer is measured to detect variation in the thickness of the liquid layer while etching the thin layer. Variation in the concentration of the phosphoric acid and the water is calculated based on the variation in the thickness of the liquid layer. Water is supplied on the substrate based on the variation in the concentration of the phosphoric acid and the water so that the concentration of the phosphoric acid and the water becomes a predetermined value.

Abstract: Provided is a feed spacer, in which angles of strands are differently formed in one feed spacer according to a flow direction of raw water, so that a differential pressure decrease region and a recovery increase region are separated to perform multiple functions, and a reverse osmosis filter module including the feed spacer.

Abstract: Disclosed herein is an asymmetric rolling joint device of a surgical instrument which increases traction force by asymmetrically forming rolling contact surfaces of joint links facing each other. The asymmetric rolling joint device includes: a first joint link part which forms a joint of the surgical instrument; and a second joint link part coming into rolling contact with the first joint link part, wherein rolling contact surfaces where the first joint link part and the second joint link part come into rolling contact with each other are formed asymmetrically so as to increase traction force more than rolling contact surfaces which are formed symmetrically.

Abstract: A flexible drive manipulator according to an example embodiment may include a proximal portion, a plurality of joint portions drivably connected from an end of the proximal portion with respect to a longitudinal axis, a distal portion connected to an end of the plurality of joint portions, a pair of drive wires passing through the plurality of joint portions in parallel along the longitudinal axis, the pair of drive wires configured to drive the plurality of joint portions in a rotational direction of rotation with respect to a transverse axis perpendicular to the longitudinal axis, and a fixing wire passing through the plurality of joint portions in a shape of converging along the longitudinal axis, the fixing wire configured to adjust rigidity of the plurality of joint portions.

Abstract: Provided is a welding apparatus having a fume elimination function. The welding apparatus efficiently eliminates fume generated while a welding object is being welded using a laser.

Abstract: An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm. When estimating a region of interest by using an AI algorithm, the image processing apparatus may estimate a region of interest by using a machine learning algorithm, a neural network algorithm, or a deep learning algorithm.

Abstract: An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm. When estimating a region of interest by using an AI algorithm, the image processing apparatus may estimate a region of interest by using a machine learning algorithm, a neural network algorithm, or a deep learning algorithm.

Abstract: An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.

Abstract: An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.

Abstract: The present disclosure relates to an artificial intelligence (AI) system utilizing a machine learning algorithm such as deep learning, and application of the same. In particular, a method for controlling an electronic device of the present disclosure comprises the steps of: obtaining image data and supplementary data including data on a user from an external terminal connected to the electronic device; generating feature data for determining the user's actual emotion by using the image data and the supplementary data; and determining the user's actual emotion by inputting the feature data into an emotion recognition model.

Abstract: Disclosed is a user interface which enables mark based interaction for images. The present disclosure relates to a user interface which enables mark based interaction for images, the images comprising a volume which is a three-dimensional image and slices which are two-dimensional images, each of which represents a cross section of the volume. At least two of the images each include the same visual mark for identifying at least one common region of interest. The user interface comprises: an input unit for receiving a user input associated with the same visual mark included in one of the images; and at least one component for enabling the interaction for the images including the same visual mark associated with the user input.

Abstract: There is provided an apparatus for interpolating a lesion area when diagnosis is performed in a Computer Aided Diagnosis (CAD) system using consecutive images. According to an example, the apparatus includes: an image receiver configured to receive images sequentially; an image matcher configured to match a current image with reference images, and to determine whether to interpolate a lesion area in the current image based on a matching result; and a lesion area acquirer configured to interpolate or acquire the lesion area in the current image according to a result of the determination.

Abstract: A method of visualizing anatomical elements in a medical includes receiving a medical image; detecting a plurality of anatomical elements from the medical image; verifying a location of each of the plurality of anatomical elements based on anatomical context information including location relationships between the plurality of anatomical elements; adjusting the location relationships between the plurality of anatomical elements; and combining the verified and adjusted information of the plurality of anatomical elements with the medical image.

Abstract: An apparatus includes an interface unit configured to provide, to a terminal, an interface supporting one or more modes, and display, on the interface, an image including a contour of a region of interest. The apparatus further includes a contour modification unit configured to modify the contour based on a mode selected by a user from the one or more modes, and an operation performed by the user.

Abstract: An apparatus and method for medical diagnostics includes receiving three-dimensional (3D) volume data of a part of a patient's body, and generating two-dimensional (2D) slices including cross-sections of the 3D volume data cut from a cross-section cutting direction. The apparatus and the method also determine whether a lesion in each of the 2D slices is benign or malignant and output results indicative thereof, select a number of the 2D slices based on the results, and make a final determination whether the lesion is benign or malignant based on the selected 2D slices.

Abstract: A method of visualizing anatomical elements in a medical includes receiving a medical image; detecting a plurality of anatomical elements from the medical image; verifying a location of each of the plurality of anatomical elements based on anatomical context information including location relationships between the plurality of anatomical elements; adjusting the location relationships between the plurality of anatomical elements; and combining the verified and adjusted information of the plurality of anatomical elements with the medical image.

Abstract: A method and an apparatus for modifying a contour line of an object are provided. The method involves displaying a contour line of an object on a screen, receiving a plurality of touch points, matching each of the plurality of the received touch points with corresponding contour line points on the contour line, generating touch point movement data by tracing a movement path of each of the plurality of the received touch points, determining a curvature variation of the contour line based on the touch point movement data, and modifying the contour line by moving each of the corresponding contour line points based on the touch point movement data and applying the curvature variation to a section connected between each of the moved corresponding contour line points to generate the section.

Abstract: An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm.

Abstract: An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.