Abstract: A method and an integrated system for dyeing synthetic, natural, and blended textiles in the form of fabrics, yarns, and garments are provided. The integrated system includes a first pressurizing pump for pressurizing liquefied CO2 to supercritical CO2 (Sc—CO2); a second pressurizing pump for pressurizing CO2 to liquefied CO2; a liquefied CO2 storage vessel for storing the liquefied CO2 and the separated liquefied CO2 from the one or more cyclone separators; a heater for heating the Sc—CO2; a dyestuff vessel for mixing a dyestuff and the Sc—CO2 to obtain Sc—CO2-mixed dyestuff; a dyeing vessel for dyeing the textile by circulating the Sc—CO2 and the Sc—CO2-mixed dyestuff between the dyeing vessel and the dyestuff vessel; and one or more cyclone separators for removing the dyestuff from the Sc—CO2-mixed dyestuff to obtain separated liquefied CO2.

Abstract: A deep learning (DL) convolution neural network (CNN) reduces noise in positron emission tomography (PET) images, and is trained using a range of noise levels for the low-quality images having high noise in the training dataset to produce uniform high-quality images having low noise, independently of the noise level of the input image. The DL-CNN network can be implemented by slicing a three-dimensional (3D) PET image into 2D slices along transaxial, coronal, and sagittal planes, using three separate 2D CNN networks for each respective plane, and averaging the outputs from these three separate 2D CNN networks. Feature-oriented training can be implemented by segmenting each training image into lesion and background regions, and, in the loss function, applying greater weights to voxels in the lesion region. Other medical images (e.g. MRI and CT) can be used to enhance resolution of the PET images and provide partial volume corrections.

Abstract: A deep learning (DL) convolution neural network (CNN) reduces noise in positron emission tomography (PET) images, and is trained using a range of noise levels for the low-quality images having high noise in the training dataset to produceuniform high-quality images having low noise, independently of the noise level of the input image. The DL-CNN network can be implemented by slicing a three-dimensional (3D) PET image into 2D slices along transaxial, coronal, and sagittal planes, using three separate 2D CNN networks for each respective plane, and averaging the outputs from these three separate 2D CNN networks. Feature-oriented training can be implemented by segmenting each training image into lesion and background regions, and, in the loss function, applying greater weights to voxels in the lesion region. Other medical images (e.g. MRI and CT) can be used to enhance resolution of the PET images and provide partial volume corrections.

Abstract: A light-emitting apparatus including a circuit substrate and a light-emitting device is provided. The circuit substrate includes a first electrode and a second electrode. The light-emitting device is disposed on a first surface of the circuit substrate. The light-emitting device includes a first conductive terminal and a second conductive terminal. The first conductive terminal and the second conductive terminal are embedded between the first electrode and the second electrode. In a first direction, there is a first distance between an inner edge of the first electrode and an inner edge of the second electrode, there is a second distance between an outer edge of the first conductive terminal and an outer edge of the second conductive terminal, and the first distance is greater than or equal to the second distance.

Abstract: Systems and methods in which multi-dimensional metric monitoring is used with respect to multi-wavelength scattering for smoke detection are described. A multi-dimensional metric may dynamically track a slope of a relationship between scattered light of multiple wavelengths of scattered light being monitored. A multi-dimensional metric monitoring smoke detection algorithm may utilize multi-dimensional thresholds with respect to monitoring of the multi-dimensional metric for initiating a fire alarm and resetting the fire alarm. An optical measuring chamber utilized for providing multi-wavelength scattering signals utilized in deriving a multi-dimensional metric for smoke detection may be configured for wide-scattering-angle signal collection, such as using a light trapping sub-chamber having a light-guide diaphragm assembly configured for wide-scattering-angle signal collection.

Abstract: Various embodiments of a fall-detection system for detecting personal fall while preserving the privacy of a detected person are disclosed. This disclosed fall-detection system can begin by receiving a sequence of video images comprising a person being monitored. The disclosed fall-detection system then processes each video image in the sequence of video images by: detecting the person in the video image; and extracting a skeletal figure of the detected person by identifying a set of human keypoints from the detected person. Next, the disclosed fall-detection system processes the sequence of skeletal figures corresponding to the sequence of video images by labeling each skeletal figure in the sequence of skeletal figures with an action among a set of predetermined actions. The disclosed fall-detection system subsequently generates a fall/non-fall decision for the detected person based on the set of action labels corresponding to the sequence of video images.

Abstract: Systems and methods are described for extending a live range for a virtual scalar register during compiling of a program, comprising: receiving an intermediate representation (IR) of a source code configured for implementing single-instruction-multiple-thread (SIMT) execution, the IR representing the source code as control flow graph including a plurality of basic blocks (BB); and when a virtual scalar register defined in a first BB of the IR is last used in a second BB of the IR that is a divergent BB, modifying the IR to extend the live range of the virtual scalar register.

Abstract: A deep learning (DL) convolution neural network (CNN) reduces noise in positron emission tomography (PET) images, and is trained using a range of noise levels for the low-quality images having high noise in the training dataset to produceuniform high-quality images having low noise, independently of the noise level of the input image. The DL-CNN network can be implemented by slicing a three-dimensional (3D) PET image into 2D slices along transaxial, coronal, and sagittal planes, using three separate 2D CNN networks for each respective plane, and averaging the outputs from these three separate 2D CNN networks. Feature-oriented training can be implemented by segmenting each training image into lesion and background regions, and, in the loss function, applying greater weights to voxels in the lesion region. Other medical images (e.g. MRI and CT) can be used to enhance resolution of the PET images and provide partial volume corrections.

Abstract: An airport baggage recording system. The airport baggage recording system comprises a telescopic robotic arm that loads airport baggage. The robotic arm has one end connected to an upright by a pivot and a second end connected to a disc. A radio frequency identification (RFID) reader is located in the disc that reads RFID tags on the airport baggage when the airport baggage is placed on the disc during loading. Another RFID reader is located on the pivot that reads the RFID tags on the airport baggage when the airport baggage is placed on the disc during loading. The RFID reader in the disc and the RFID reader on the pivot both read the RFID tags on the airport baggage to prevent errors in reading the RFID tags on the airport baggage during loading.

Abstract: A display apparatus includes a driving substrate and a first light emitting diode element. The driving substrate has a plurality of driving structures. Each of the driving structures includes a first pad, a second pad, a third pad and a fourth pad. The plurality of driving structures include a first driving structure. The first light emitting diode element is electrically connected to a first pad and a second pad of the first driving structure, and the first light emitting diode element crosses a line connecting a third pad and a fourth pad of the first driving structure. A manufacturing method of the display apparatus is also provided.

Abstract: Various embodiments of a health-monitoring system are disclosed. In one aspect, this health-monitoring system includes a server and a set of health-monitoring sensors communicatively coupled to the server. In some embodiments, the server is configured to establish a new profile for a person to be monitored by: receiving a new profile request for establishing the new profile; generating a unique person-ID for the received new profile request; creating a new entry including the unique person-ID for the person in a profile database; and transmitting the unique person-ID along with the profile photos of the person to the set of health-monitoring sensors. Moreover, each health-monitoring sensor in the set of sensors is configured to establish the new profile by adding a new entry for the person in a person-ID dictionary of the health-monitoring sensor based on the received person-ID and the profile photos of the person.

Abstract: A display apparatus includes a driving substrate, a first light-emitting diode element, a first connection element, a second connection element, a first insulation pattern, and a reflective pattern. The driving substrate has a first pad, a second pad, a third pad, and a connection area. The first connection element is electrically connected to a first electrode of the first light-emitting diode element and the first pad of the driving substrate. The second connection element is electrically connected to a second electrode of the first light-emitting diode element and the second pad of the driving substrate. The first insulation pattern is disposed on the first light-emitting diode element, the first connection element, and the second connection element. The reflective pattern is disposed on the first insulation pattern.

Abstract: A self-emissive element includes a light-emitting diode (LED) and an auxiliary structure. The LED includes a first type semiconductor, a second type semiconductor, a first pad, and a second pad. The second type semiconductor is overlapped with the first type semiconductor in a vertical direction perpendicular. The auxiliary structure includes a cover portion, a protection portion and a first anchor portion. The cover portion is overlapped with the LED in the vertical direction. The protection portion is not overlapped with the LED in the vertical direction. An orthographic projection area of the protection portion in the vertical direction is greater than or equal to an orthographic projection area of the LED in the vertical direction. The first anchor portion and the protection portion are respectively located at different sides of the LED.

Abstract: An adjustable head angle bicycle assembly includes a steerer tube; a head tube that includes a first annular surface protruding radially inward from an inner wall at the upper end, and a second annular surface protruding radially inward from the inner wall at the lower end; an upper cup that includes a third annular surface engaged with the first annular surface of the head tube; and a lower cup that includes a fourth annular surface engaged with the second annular surface of the head tube.

Abstract: Various embodiments of a vision-based privacy-preserving embedded fall-detection system are disclosed. This embedded fall-detection system can include one or more cameras for capturing video images of one or more persons. Moreover, this embedded fall-detection system can include various fall-detection modules for processing the captured video images including: a pose-estimation module, an action-recognition module, and a fall-detection module, all of which can perform the intended fall-detection functionalities within the embedded system environment in real-time in order to detect falls of the one or more persons. When a fall is detected, instead of sending the original captured images, the embedded fall-detection system can transmit sanitized video images to the server, wherein each detected person is represented by a skeleton figure in place of the actual person images, thereby preserving the privacy of the detected person.

Abstract: A display apparatus includes a driving substrate and a first light emitting diode element. The driving substrate has a plurality of driving structures. Each of the driving structures includes a first pad, a second pad, a third pad and a fourth pad. The plurality of driving structures include a first driving structure. The first light emitting diode element is electrically connected to a first pad and a second pad of the first driving structure, and the first light emitting diode element crosses a line connecting a third pad and a fourth pad of the first driving structure. A manufacturing method of the display apparatus is also provided.

Abstract: To reduce the effect(s) caused by patient breathing and movement during PET data acquisition, an unsupervised non-rigid image registration framework using deep learning is used to produce motion vectors for motion correction. In one embodiment, a differentiable spatial transformer layer is used to warp the moving image to the fixed image and use a stacked structure for deformation field refinement. Estimated deformation fields can be incorporated into an iterative image reconstruction process to perform motion compensated PET image reconstruction. The described method and system, using simulation and clinical data, provide reduced error compared to at least one iterative image registration process.

Abstract: A display panel including an array substrate, a first sub-pixel, a second sub-pixel, and a first light-emitting diode is provided. The array substrate includes a first connection pad and a second connection pad. The first sub-pixel includes a first driving unit electrically connected to the first connection pad. The second sub-pixel includes a second driving unit electrically connected to the second connection pad. The first light-emitting diode completely overlaps and is physically isolated from the second connection pad. The first light-emitting diode is not completely overlapped and is electrically connected to the first connection pad. A manufacturing method of a display panel is also provided.

Abstract: A method for estimating a state of charge of a battery includes obtaining a discharge voltage and discharge capacity curve of a battery under a preset discharge current, in responding to an order for estimating the state of charge of the battery; matching the discharge voltage and discharge capacity curve with a plurality of standard curves in a database, thereby obtaining an optimal matching curve with respect to the discharge voltage and discharge capacity curve; and calculating the state of charge of the battery according to the optimal matching curve, under a preset discharge stage. The present method can accurately calculate the state of charge of the battery with simple calculation manners.

Abstract: An electronic component includes a circuit substrate, a connecting electrode, a micro-element, and a solder. The connecting electrode is located on the circuit substrate. The connecting electrode has a first transparent conductive layer. A surface of the first transparent conductive layer is located opposite the circuit substrate, and has a plurality of micrometers or nanometer particles. The micro-element is electrically connected to the connecting electrode. The solder is located between the connecting electrode and the micro-element, and fixes the micro-element on the connecting electrode.