Abstract: Provided herein is an apparatus. The apparatus can include a battery cell. The battery cell can include a vent. The vent can be coupled with the battery cell. The apparatus can include a channel coupled with the vent. The apparatus can include a porous component. The porous component can be disposed in the channel. The porous component can include one or more pores each having a width less than a width of the channel.

Abstract: Disclosed are techniques for estimating a 3D bounding box (3DBB) from a 2D bounding box (2DBB). Conventional techniques to estimate 3DBB from 2DBB rely upon classifying target vehicles within the 2DBB. When the target vehicle is misclassified, the projected bounding box from the estimated 3DBB is inaccurate. To address such issues, it is proposed to estimate the 3DBB without relying upon classifying the target vehicle.

Abstract: Disclosed is a disc-shaped sample chamber for collecting molten metal, the chamber comprising: a chamber body having a left body and a right body bonded to each other to define a disc-shaped sample space therebetween; an inlet extending upward from the chamber body and connecting the sample space with the outside; and a welded bonding portion disposed on at least one lateral face of the chamber body for bonding the left body and the right body to each other. Further, a probe having the chamber is disclosed.

Abstract: Disclosed are techniques for estimating a 3D bounding box (3DBB) from a 2D bounding box (2DBB). Conventional techniques to estimate 3DBB from 2DBB rely upon classifying target vehicles within the 2DBB. When the target vehicle is misclassified, the projected bounding box from the estimated 3DBB is inaccurate. To address such issues, it is proposed to estimate the 3DBB without relying upon classifying the target vehicle.

Abstract: Disclosed are techniques for determining a motion state of a target object. In an aspect, an on-board computer of an ego vehicle detects the target object in one or more images, determines one or more first attributes of the target object based on measurements of the one or more images, determines one or more second attributes of the target object based on measurements of a map of a roadway on which the target object is travelling, and determines the motion state of the target object based on the one or more first attributes and the one or more second attributes of the target object.

Abstract: Disclosed are techniques for estimating a 3D bounding box (3DBB) from a 2D bounding box (2DBB). Conventional techniques to estimate 3DBB from 2DBB rely upon classifying target vehicles within the 2DBB. When the target vehicle is misclassified, the projected bounding box from the estimated 3DBB is inaccurate. To address such issues, it is proposed to estimate the 3DBB without relying upon classifying the target vehicle.

Abstract: Disclosed is a disc-shaped sample chamber for collecting molten metal, the chamber comprising: a chamber body having a left body and a right body bonded to each other to define a disc-shaped sample space therebetween; an inlet extending upward from the chamber body and connecting the sample space with the outside; and a welded bonding portion disposed on at least one lateral face of the chamber body for bonding the left body and the right body to each other. Further, a probe having the chamber is disclosed.

Abstract: Disclosed are techniques for lane estimation. In aspects, a method includes receiving a plurality of camera frames captured by a camera sensor of a vehicle, assigning a first subset of the plurality of camera frames to a deep learning (DL) detector and a second subset of the plurality of camera frames to a computer vision (CV) detector based on availability of the DL and CV detectors, identifying a first set of lane boundary lines in a first camera frame processed by the DL detector, identifying a second set of lane boundary lines in a second camera frame processed by the CV detector, generating first and second sets of lane models based on the first and second sets of lane boundary lines, and updating a set of previously identified lane models based on the first set of lane models and/or the second set of lane models.

Abstract: Disclosed are techniques for estimating a 3D bounding box (3DBB) from a 2D bounding box (2DBB). Conventional techniques to estimate 3DBB from 2DBB rely upon classifying target vehicles within the 2DBB. When the target vehicle is misclassified, the projected bounding box from the estimated 3DBB is inaccurate. To address such issues, it is proposed to estimate the 3DBB without relying upon classifying the target vehicle.

Abstract: Disclosed are techniques for estimating a 3D bounding box (3DBB) from a 2D bounding box (2DBB). Conventional techniques to estimate 3DBB from 2DBB rely upon classifying target vehicles within the 2DBB. When the target vehicle is misclassified, the projected bounding box from the estimated 3DBB is inaccurate. To address such issues, it is proposed to estimate the 3DBB without relying upon classifying the target vehicle.

Abstract: A steam trap comprises: a main body having a flow path between an inlet and an outlet; an opening and closing unit, installed at an outlet of the main body, and an operation unit, installed in the flow path between the inlet and the outlet, wherein the opening and closing unit is provided with a nozzle that has a discharge hole, and includes an opening and closing member which is in close contact with the nozzle at the inlet side of the flow path for blocking or opening the discharge hole while linearly moving, and an operating rod for connecting the operating unit and the opening and closing member to linearly move the opening and closing member to the operating unit.

Abstract: Techniques and systems are provided for determining features of one or more objects in one or more images. For example, an image of an object and a three-dimensional model associated with the object can be obtained. From the image, a sample point on the object can be determined. A depth and an angle of the sample point of the object can be determined. A pose and a shape of the three-dimensional model associated with the object can be determined based on the depth and the angle.

Abstract: A steam trap comprises: a main body having a flow path between an inlet and an outlet; an opening and closing unit, installed at an outlet of the main body, and an operation unit, installed in the flow path between the inlet and the outlet, wherein the opening and closing unit is provided with a nozzle that has a discharge hole, and includes an opening and closing member which is in close contact with the nozzle at the inlet side of the flow path for blocking or opening the discharge hole while linearly moving, and an operating rod for connecting the operating unit and the opening and closing member to linearly move the opening and closing member to the operating unit.

Abstract: Provided is a fluid container including: a container main body, of which one side is open, configured to store a fluid; a housing having an outlet provided at one side and in which the container main body slides in a longitudinal direction; and a pump module coupled to the open one side of the container main body and configured to discharge the fluid to the outlet by sliding the container main body.

Abstract: Disclosed are techniques for estimating multiple lane boundaries through simultaneous detection of lane markers (LM) and raised pavement markers (RPM). Conventional techniques for lane marker detection (LMD) comprises extracting and clustering line segments from a camera image, fitting the clustered lines to a geometric model, and selecting the multiple lanes using heuristic approaches. Unfortunately, in the conventional technique, an error from each step is sequentially propagated to the next step. Also there are no techniques to estimate both LMs and RPMs. A technique to simultaneously detect in real time both LM and RPMs is proposed. This enables optimal estimation of multiple lane boundaries.

Abstract: Techniques and systems are provided for determining features of one or more objects in one or more images. For example, an image of an object and a three-dimensional model associated with the object can be obtained. From the image, a sample point on the object can be determined. A depth and an angle of the sample point of the object can be determined. A pose and a shape of the three-dimensional model associated with the object can be determined based on the depth and the angle.

Abstract: Provided is a fluid container including: a container main body, of which one side is open, configured to store a fluid; a housing having an outlet provided at one side and in which the container main body slides in a longitudinal direction; and a pump module coupled to the open one side of the container main body and configured to discharge the fluid to the outlet by sliding the container main body.

Abstract: Disclosed are techniques for estimating a 3D bounding box (3DBB) from a 2D bounding box (2DBB). Conventional techniques to estimate 3DBB from 2DBB rely upon classifying target vehicles within the 2DBB. When the target vehicle is misclassified, the projected bounding box from the estimated 3DBB is inaccurate. To address such issues, it is proposed to estimate the 3DBB without relying upon classifying the target vehicle.

Abstract: Disclosed are techniques for estimating a 3D bounding box (3DBB) from a 2D bounding box (2DBB). Conventional techniques to estimate 3DBB from 2DBB rely upon classifying target vehicles within the 2DBB. When the target vehicle is misclassified, the projected bounding box from the estimated 3DBB is inaccurate. To address such issues, it is proposed to estimate the 3DBB without relying upon classifying the target vehicle.

Abstract: Disclosed are techniques for determining a motion state of a target object. In an aspect, an on-board computer of an ego vehicle detects the target object in one or more images, determines one or more first attributes of the target object based on measurements of the one or more images, determines one or more second attributes of the target object based on measurements of a map of a roadway on which the target object is travelling, and determines the motion state of the target object based on the one or more first attributes and the one or more second attributes of the target object.