Disclosed is a method for improving affinity of an antibody for an antigen, comprising, in an unmodified antibody, improving affinity for an antigen as compared to the unmodified antibody, by changing 77th, 79th and 81st amino acid residues of a light chain defined by Kabat method to charged amino acid residues.

Systems and methods for tracking objects though a traffic control system include a plurality of sensors configured to capture data associated with a traffic location, and a logic device configured to detect one or more objects in the captured data, determine an object location within the captured data, transform each object location to world coordinates associated with one of the plurality of sensors; and track each object location using the world coordinates using prediction and occlusion-based processes. The plurality of sensors may include a visual image sensor, a thermal image sensor, a radar sensor, and/or another sensor. An object localization process includes a trained deep learning process configured to receive captured data from one of the sensors and determine a bounding box surrounding the detected object and output a classification of the detected object. The tracked objects are further transformed to three-dimensional objects in the world coordinates.

Systems and methods for tracking objects though a traffic control system include a plurality of sensors configured to capture data associated with a traffic location, and a logic device configured to detect one or more objects in the captured data, determine an object location within the captured data, transform each object location to world coordinates associated with one of the plurality of sensors; and track each object location using the world coordinates using prediction and occlusion-based processes. The plurality of sensors may include a visual image sensor, a thermal image sensor, a radar sensor, and/or another sensor. An object localization process includes a trained deep learning process configured to receive captured data from one of the sensors and determine a bounding box surrounding the detected object and output a classification of the detected object. The tracked objects are further transformed to three-dimensional objects in the world coordinates.

A millimeter wave radar apparatus determining a fall posture is applied to a human body. The millimeter wave radar apparatus includes a microprocessor and a millimeter wave radar. The millimeter wave radar is electrically connected to the microprocessor. The millimeter wave radar is configured to transmit a radar wave to the human body. The millimeter wave radar is configured to receive a reflected radar wave reflected from the human body based on the radar wave. The microprocessor is configured to obtain a point cloud information based on the reflected radar wave. The microprocessor is configured to utilize the point cloud information to determine whether the human body is in the fall posture.

A millimeter wave radar apparatus determining a fall posture is applied to a human body. The millimeter wave radar apparatus includes a microprocessor and a millimeter wave radar. The millimeter wave radar is electrically connected to the microprocessor. The millimeter wave radar is configured to transmit a radar wave to the human body. The millimeter wave radar is configured to receive a reflected radar wave reflected from the human body based on the radar wave. The microprocessor is configured to obtain a point cloud information based on the reflected radar wave. The microprocessor is configured to utilize the point cloud information to determine whether the human body is in the fall posture.

Perception sensors of a vehicle can be used for various operating functions of the vehicle. A computing device may receive sensor data from the perception sensors, and may calibrate the perception sensors using the sensor data, to enable effective operation of the vehicle. To calibrate the sensors, the computing device may project the sensor data into a voxel space, and determine a voxel score comprising an occupancy score and a residual value for each voxel. The computing device may then adjust an estimated position and/or orientation of the sensors, and associated sensor data, from at least one perception sensor to minimize the voxel score. The computing device may calibrate the sensor using the adjustments corresponding to the minimized voxel score. Additionally, the computing device may be configured to calculate an error in a position associated with the vehicle by calibrating data corresponding to a same point captured at different times.

This document describes techniques and systems for radar-based gesture-recognition with context-sensitive gating and other context-sensitive controls. Sensor data from a proximity sensor and/or a movement sensor produces a context of a user equipment. The techniques and systems enable the user equipment to recognize contexts when a radar system can be unreliable and should not be used for gesture-recognition, enabling the user equipment to automatically disable or “gate” the output from the radar system according to context. The user equipment prevents the radar system from transitioning to a high-power state to perform gesture-recognition in contexts where radar data detected by the radar system is likely due to unintentional input. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

This document describes techniques and systems for radar-based gesture-recognition with context-sensitive gating and other context-sensitive controls. Sensor data from a proximity sensor and/or a movement sensor produces a context of a user equipment. The techniques and systems enable the user equipment to recognize contexts when a radar system can be unreliable and should not be used for gesture-recognition, enabling the user equipment to automatically disable or “gate” the output from the radar system according to context. The user equipment prevents the radar system from transitioning to a high-power state to perform gesture-recognition in contexts where radar data detected by the radar system is likely due to unintentional input. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

A radar device includes a first radar and a second radar that are arranged at positions separated from each other, and of which detection ranges are at least partially overlapped; and a detection unit that detects at least one of a moving direction and a velocity vector of a reflection point existing in an overlapped portion of the detection ranges, based on a first detection result of the first radar and a second detection result of the second radar.

A radar device includes a first radar and a second radar that are arranged at positions separated from each other, and of which detection ranges are at least partially overlapped; and a detection unit that detects at least one of a moving direction and a velocity vector of a reflection point existing in an overlapped portion of the detection ranges, based on a first detection result of the first radar and a second detection result of the second radar.