Abstract: The present invention relates to antibody-drug conjugates (ADCs) wherein a plurality of active agents are conjugated to an antibody through at least one branched linker. The branched linker may comprise a branching unit, and two active agents are coupled to the branching unit through a secondary linker and the branching unit is coupled to the antibody by a primary linker. The active agents may be the same or different. In certain such embodiments, two or more such branched linkers are conjugated to the antibody, e.g., 2-4 branched linkers, which may each be coupled to a different C-terminal cysteine of a heavy or light chain of the antibody. The branched linker may comprise one active agent coupled to the branching unit by a first branch and a second branch that comprises a polyethylene glycol moiety coupled to the branching unit. In certain such embodiments, two or more such branched linkers are conjugated to the antibody, e.g.

Abstract: The present specification relates to a composition for preventing, alleviating or treating burnout syndrome, containing a natural extract as an active ingredient. According to one aspect of the present invention, the composition contains a ginseng fruit extract, and thus is useful for preventing, treating and alleviating burnout syndrome. In addition, according to one aspect of the present invention, the composition further contains ginseng fruit and one or more selected from the group consisting of red ginseng, Angelica gigas, Cornus officinalis, Cervi parvum corni, and Nigella sativa, so as to maximize the synergistic effect among two or more ingredients, thereby exhibiting excellent effects on the prevention, treatment and alleviation of burnout syndrome. Therefore, there is an advantage of making individuals and society mentally and physically healthy since burnout syndrome can be prevented, treated and alleviated, by using the composition of the present invention.

Abstract: A battery includes an electrode assembly including a first electrode, a second electrode and a separator between the first electrode and the second electrode, the first electrode, the second electrode and the separator being wound around a winding axis to define a core and an outer peripheral surface. The first electrode and the second electrode include a first uncoated region and a second uncoated region along a winding direction, respectively, and an active material layer coating is absent in the first uncoated region and the second uncoated region. The battery further includes a housing receiving the electrode assembly through an opening formed at a bottom, a first current collector coupled to the first uncoated region and disposed within the housing, a cap covering the opening, a spacer interposed between the cap and the electrode assembly to fix the electrode assembly and seal the housing, and a terminal electrically connected to the second uncoated region.

Abstract: Disclosed is an electrode assembly, a battery, and a battery pack and a vehicle including the same. In the electrode assembly, a first electrode, a second electrode, and a separator interposed therebetween are wound based on an axis to define a core and an outer circumference. The first electrode includes an uncoated portion at a long side end thereof and exposed out of the separator along a winding axis direction of the electrode assembly. A part of the uncoated portion is bent in a radial direction of the electrode assembly to form a bending surface region that includes overlapping layers of the uncoated portion, and in a partial region of the bending surface region, the number of stacked layers of the uncoated portion is 10 or more in the winding axis direction of the electrode assembly.

Abstract: A battery includes an electrode assembly including a first uncoated region and a second uncoated region; a battery housing accommodating the electrode assembly and electrically connected to the second uncoated region; a cap to cover an open portion on bottom of the battery housing; a first electrode terminal passing through a partially closed portion of the battery housing and being electrically isolated from the battery housing; and a first current collector coupled to the first uncoated region and connected to the first electrode terminal.

Abstract: A display device includes a substrate, a first conductive layer on the substrate, the first conductive layer including a data signal line, a first insulating layer on the first conductive layer, a semiconductor layer on the first insulating layer, the semiconductor layer including a first semiconductor pattern, a second insulating layer on the semiconductor layer, and a second conductive layer on the second insulating layer, the second conductive layer including a gate electrode disposed to overlap the first semiconductor pattern, a transistor first electrode disposed to overlap a part of the first semiconductor pattern, wherein the transistor first electrode is electrically connected to the data signal line through a contact hole that penetrates the first and second insulating layers, and a transistor second electrode disposed to overlap another part of the first semiconductor pattern.

Abstract: Disclosed are a deep neural network lightweight device based on batch normalization, and a method thereof. The deep neural network lightweight device based on batch normalization includes a memory that stores at least one data and at least one processor that executes a network lightweight module. When executing the network lightweight module, the processor performs learning on an input neural network based on sparsity regularization to adaptively determine at least one parameter of the sparsity regularization, performs pruning on the learning result, and performs fine tuning on the pruning result.

Abstract: The present invention relates to an apparatus and method for drawing, the method comprising: inputting a drawing image; recognizing a component in the input drawing image; inferring a structure of an object based on the recognized component; and drawing the inferred structure of the object.

Abstract: Disclosed is a method for manufacturing an MSO coil, comprising: a pressing step of forming a bent surface on a part of a unit coil layer, which has a ring shape such that both ends thereof face each other, thereby endowing both ends of the unit coil layer with a height difference; a fixing step of connecting and fixing a plurality of unit coil layers to each other, each unit coil layer having the bent surface formed thereon, such that the first end of both ends of a unit coil layer having the bent surface formed thereon contacts the second end of both ends of another unit coil layer having the bent surface formed thereon; and a bonding step of bonding connection parts defined by contact of the first and second ends of each of the plurality of unit coil layers that are connected and fixed to each other.

Abstract: Provided are a method and system for training a dynamic deep neural network. The method for training a dynamic deep neural network includes receiving an output of a last layer of the deep neural network and outputting a first loss, receiving an output of a routing module according to an input class of the deep neural network and outputting a second loss, calculating a third loss based on the first loss and the second loss, and updating a weight of the deep neural network by using the third loss.

Abstract: A data learning device in a deep learning network characterized by a high image resolution and a thin channel at an input stage and an output stage and a low image resolution and a thick channel in an intermediate deep layer includes a feature information extraction unit configured to extract global feature information considering an association between all elements of data when generating an initial estimate in the deep layer; a direct channel-to-image conversion unit configured to generate expanded data having the same resolution as a final output from the generated initial estimate of the global feature information or intermediate outputs sequentially generated in subsequent layers; and a comparison and learning unit configured to calculate a difference between the expanded data generated by the direct channel-to-image conversion unit and a prepared ground truth value and update network parameters such that the difference is decreased.

Abstract: A fast object detection method and a fast object detection apparatus using an artificial neural network. The fast object detection method includes obtaining an input image; inputting the obtained input image into an object detection neural network using a plurality of preset bounding boxes; and detecting an object included in the input image by acquiring output data of the object detection neural network.

Abstract: An apparatus and method for searching a neural network architecture may be disclosed. The apparatus may include an architecture searcher and an architecture evaluator. The architecture searcher may search for a topology between nodes included in a basic cell of a network, search for an operation to be applied between the nodes after searching for the topology, and determine the basic cell. The architecture evaluator may evaluate performance of the determined basic cell.

Abstract: A fast object detection method and a fast object detection apparatus using an artificial neural network. The fast object detection method includes obtaining an input image; inputting the obtained input image into an object detection neural network using a plurality of preset bounding boxes; and detecting an object included in the input image by acquiring output data of the object detection neural network.

Abstract: The present invention relates to an apparatus and method for providing personalized adaptive e-learning, and more specifically, to an apparatus and method for estimating a learner's proficiency to each attribute and providing adaptive e-learning by taking into consideration an item answering result of an individual learner in a personalized learning environment.

Abstract: Disclosed is a method for manufacturing an MSO coil, comprising: a pressing step of forming a bent surface on a part of a unit coil layer, which has a ring shape such that both ends thereof face each other, thereby endowing both ends of the unit coil layer with a height difference; a fixing step of connecting and fixing a plurality of unit coil layers to each other, each unit coil layer having the bent surface formed thereon, such that the first end of both ends of a unit coil layer having the bent surface formed thereon contacts the second end of both ends of another unit coil layer having the bent surface formed thereon; and a bonding step of bonding connection parts defined by contact of the first and second ends of each of the plurality of unit coil layers that are connected and fixed to each other.

Abstract: Provided are an apparatus and method for learner diagnosis using reliability of a cognitive diagnostic model, which estimates the reliability of the cognitive diagnostic model that estimates a concept vector (?) of a learner through a Q-matrix regarding a question and an R-matrix regarding a response to a question, the method including assuming a probability (P(X|?)) of a learner response (X) when a concept vector (?) of a learner is given; obtaining a concept pattern-specific probability (P(?|X)) of the learner from the assumed concept vector and learner response of the learner; obtaining an information entropy (H) value of the learner from the concept pattern-specific probability (P(?|X)) of the learner; and obtaining reliability (?) of an estimated result of a learner-specific concept understanding using the information entropy value of the learner and a number of concepts.

Abstract: The present invention relates to an apparatus and method for providing personalized adaptive e-learning, and more specifically, to an apparatus and method for estimating a learner's proficiency to each attribute and providing adaptive e-learning by taking into consideration an item answering result of an individual learner in a personalized learning environment.

Abstract: The present invention relates to a learning diagnosis apparatus, a method of diagnosing a learner's learning ability, and an adaptive learning system for providing adaptive learning using the diagnosis result. The learning diagnosis apparatus includes a database (DB) configured to store and manage adaptive learning data and store a program for estimating a learner's proficiency to each attribute and recommending learning content and a processor configured to execute the program, wherein the processor calculates a attribute proficiency vector estimation result of a specific learner using information about a solution to a personalized item together with group test solution information.

Abstract: Provided is a system for detecting an object from a depth image. The system includes a communication module, a memory, and a processor. By executing the object detection program, the processor extracts a first object area and a second object area from the depth image, based on a predetermined floor plane and an outer plane which is set with respect to the predetermined floor plane. The processor extracts a target area including pixels of the second object area which are spaced apart from the first object area by a predetermined interval. The processor samples a pixel, which is not included in the target area, to extract a floor area from the second object area, calculates a boundary value of an object and a floor, based on the floor area and the target area, and extracts a foreground pixel from the target area, based on the calculated boundary value.