Abstract: A vibration detection device is used to execute a vibration detection method for detecting a vibrating touch pad. The vibration detection device includes a first detection module which has a first moving plate, a circuit board and a plurality of acceleration sensors. The first moving plate is movable relative to the vibrating touch pad. The circuit board is disposed on the first moving plate. The plurality of acceleration sensors is disposed on the circuit board as an array, and can abut against a plurality of measuring points on the vibrating touch pad when the first moving plate is moved close to the vibrating touch pad, so as to simultaneously detect a vibration feedback parameter generated from each of the plurality of acceleration sensors.

Abstract: This application provides a motor drive system, a power system, and an electric vehicle, and relates to the field of power electronic technologies. The drive system is configured to drive a motor that uses a power battery pack as a power supply. The power battery pack includes at least two battery modules that are independent of each other, the drive system includes at least two direct current-alternating current DC-AC circuits, and the battery modules one-to-one correspond to the DC-AC circuits. Each battery module is correspondingly connected to an input end of one DC-AC circuit, and an output end of each DC-AC circuit is connected to a corresponding winding of the motor. The DC-AC circuit is configured to convert a direct current provided by the corresponding battery module into an alternating current to drive the corresponding winding of the motor.

Abstract: Provided herein is technology relating to automated driving and particularly, but not exclusively, to an intelligent information conversion system and related methods for providing collaborative automatic driving to intelligent transportation systems, vehicle networking systems, collaborative management control systems, vehicle-road collaborative systems, automated driving systems, and the like.

Abstract: A direct current charging apparatus, a powertrain, and an electric vehicle. The direct current charging apparatus which includes a direct current charging interface, a switch module, and a direct current voltage conversion module is configured to charge power battery of the electric vehicle. The direct current charging interface is configured to connect a positive electrode and a negative electrode of a power supply apparatus and a positive electrode and a negative electrode of the power battery to form a charging loop. The switch module is configured to connect or disconnect the charging loop. The direct current voltage conversion module is configured to output a preset direct current voltage to the positive electrode and the negative electrode of the power supply apparatus. When the charging loop between the power battery and a charging pile is connected again, charging can be resumed without re-swiping card/re-scanning QR code.

Abstract: The present invention discloses a multi-header pipe distributing annular printed circuit heat exchanger, and pertains to the technical field of heat exchangers, the heat exchanger includes: a front head configured to achieve same side entry and exit of a cold fluid; a core body with one end thereof connected with the front head and configured to achieve distributing of cold fluid entry and exit; a hot fluid inlet cavity provided in a middle portion of the core body and configured to achieve entry of a hot fluid; a shell sheathed outside the core body, and the shell and the core body provided with a gap for collecting the hot fluid; and a lower cover plate connected with one end of the core body and configured to block the hot fluid inlet cavity. The present invention can improve compactness and power density of the heat exchanger, reduce volume and weight.

Abstract: A wearable device an intelligent health promotion service system (IHPSS) is disclosed. One embodiment of the wearable device (10) is configured to interface plurality groups of skin-mounted sensor pads (130) over a body part (140) of a wearer, and comprises: a modular brace (110) structurally separated from the sensor pads, and a plurality of sensor modules (120). The modular bracing is provided with a plurality groups of orienting slots (111) arranged thereon configured to maintain intra-group orientation between the sensor pads, and is configured to allow inter-group distance adjustment between the groups of the sensor pads over the body part of the wearer. The plurality of sensor modules is configured to be detachably coupled to the groups of sensor pads through the orienting slots in the modular bracing member. The sensor modules are provided with physiological sensing circuits wirelessly communicative with the intelligent health system.

Abstract: Provided are a sound gathering device for voiceprint monitoring and a preparation method. The sound gathering device is a cone structure and includes a front end portion (1) and a rear end portion (2), the front end portion (1) is trumpet-shaped, an inner wall surface of the front end portion (1) is present a pattern array of a microstructure (3), and the microstructure (3) presenting the pattern array is formed through laser etching. A sound wave frequency monitored by the sound gathering device is 50 Hz˜10 kHz, and a sound wave enters the sound gathering device from an entrance of the front end portion (1), is reflected through the pattern array of the microstructure (3) on the inner wall surface of the front end portion (1), and is transmitted from an exit of the rear end portion (2), and a sound pressure of the exit of the rear end portion (2) is 4 times˜8 times a sound pressure of the entrance of the front end portion (1).

Abstract: A method for wafer treatment is disclosed. A wafer is provided with a main surface, a surface layer, and a base layer. The surface layer is disposed between the main surface and the base layer, and the surface layer covers the base layer and exposes the main surface. Then, at least one laser process is performed to fully irradiate the main surface and the surface layer with a first laser to generate a plurality of optimized regions in the main surface and the surface layer, so that the optimized regions form at least one stress-relieving array.

Abstract: A method for a wafer treatment includes providing a wafer including a main surface, a surface layer and a base layer; and performing at least one laser process to irradiate the whole surface layer with laser to thereby generate a plurality of defect regions in the surface layer, and the defect regions form at least one array of defect regions.

Abstract: Provided herein is technology relating to a function allocation system (FAS) that deploys artificial intelligence models for a connected automated highway (CAH) system and a connected automated vehicle (CAV) system to distribute driving intelligence between the CAV system and the CAH system. The FAS comprises a communication module, a data module, and a computing module. The computing module is configured to analyse scenes using sensing data, determine automated driving function requirements, deploy function allocation methods, and analyse CAH system and CAV system functions. The function allocation methods provide analysis, guidance, and optimization capabilities for sensing, decision-making, and control functions. The FAS allocates automated driving functions to the CAV system and the CAH system based on their respective intelligence levels.

Abstract: The invention provides a roadside computing system (RCS), or an edge computing system, for an autonomous vehicle. The RCS comprises a hierarchy of roadside unit (RSU) and an onboard unit (OBU) in an individual vehicle. The RSU comprises a data processing module and a communication module, and is capable of generating guidance information and targeted instructions for individual vehicle. The data processing module of the RSU comprises two processors: an External Object Calculating Module (EOCM) and an AI processing unit. Thus, the RCS utilizes roadside edge computing power and AI models to support autonomous driving for the vehicle. The OBU comprises a data processing module, a communication module, and a vehicle control module, and is capable of generating vehicle-specific targeted instruction for the vehicle based on guidance information and targeted instructions received from RSUs, and controlling the vehicle based on vehicle-specific targeted instruction.

Abstract: A hardware-based fan controller for controlling fan modules in a computer system having multiple computer nodes is disclosed. Each of the computer nodes has a service processor. The fan controller includes a slave module that receives fan speed commands from each of the service processors. A fan speed generator is coupled to the slave module and a subset of the fan modules. The fan speed generator receives fan speed commands from the slave module and fan speed outputs from the subset of fan modules. The fan speed generator is configured to output a speed command to each of the fan modules in the subset.

Abstract: Provided herein is an artificial intelligence-based mobile roadside intelligent unit (MRIU) for providing, supplementing, and/or enhancing the control and operation of autonomous vehicles in normal and long-tail scenarios. The MRIU comprises a computing module configured to provide supplemental computation capability for autonomous driving. The MRIU comprises a communication module to communicate and exchange data with a vehicle or a cloud. The MRIU provides prediction, decision-making, and/or control functions for autonomous driving. The MRIU provides edge computing capability for autonomous vehicles to train and operate artificial intelligence-based intelligent driving models in a distributed fashion. Specifically, an edge computing unit conducts data fusion and data feature extraction, provides prediction, formulates control strategies, generates vehicle control instructions, and/or distributes vehicle control information and/or instructions for an autonomous vehicle.

Abstract: The invention provides an autonomous vehicle and center guidance system (AVCGS) for drone/tele driving or digital twins by sending guidance instructions to an autonomous vehicle (AV) or a connected automated vehicle (CAV). The AVCGS is a component of a Connected Automated Vehicle Highway (CAVH) system. This AVCGS is configured to operate AVs or CAVs using a hierarchy of traffic control centers/units (TCCs/TCUs). The AVCGS comprises automatic or semi-automated computational modules, a TCC/TCU communication module, and/or an onboard unit (OBU) communication module and a vehicle control module. The AVCGS communicates with one or more entities. The vehicle-specific guidance instructions and information comprise vehicle maneuver, safety maintenance, traffic control/road condition, and special information. The AVCGS provides backup in case of any errors or failures. Specifically, through the AVCGS, AVs or CAVs can be effectively and efficiently operated.

Abstract: The invention provides systems and methods for an autonomous vehicle and center control system (AVCCS), which is a component of a Connected Automated Vehicle Highway (CAVH) system. The AVCCS is configured to realize drone/tele driving or digital twins by providing automated vehicles (AVs) or connected automated vehicles (CAVs) with vehicle-specific control instructions comprising instructions for vehicle longitudinal and lateral position, speed, and steering and control. Specifically, through the system, AVs or CAVs can be effectively and efficiently controlled by the AVCCS. In addition, the AVCCS is configured to provide vehicle-specific control instructions to AVs or CAVs and control them through a hierarchy of traffic control centers/units (TCCs/TCUs) or the combination of TCCs/TCUs and the onboard units (OBUs) with a vehicle control module, wherein said TCCs/TCUs are configured to fulfill vehicle maneuver tasks, monitor safety maintenance tasks, and take over if the system fails.

Abstract: The invention provides an autonomous vehicle and intelligent control (AVIC) system with distributed AI computing, which is a component of a Connected Automated Vehicle Highway (CAVH) system. This AVIC system is configured to realize training and application for distributed AI computing by providing automated vehicles (AVs) and/or connected automated vehicles (CAVs) with vehicle-specific control instructions comprising instructions for vehicle longitudinal and lateral position, speed, and steering and control. Detailed and time-sensitive vehicle-specific control instructions comprise control instructions for speed, spacing, lane designation, vehicle following, lane changing, and/or route guidance. Specifically, through the system, CAVs can be effectively and efficiently controlled by the AVIC system.

Abstract: This invention presents a function allocation system for an autonomous vehicle (AV). During the operations of the AV, some or all of its automated driving capabilities or functions could be downgraded due to long-tail events or malfunctioning. The roadside intelligent infrastructure, or the cloud platform, could supplement some or all of AV's automated driving functions, including sensing, prediction and decision-making, and/or control functions. The function allocation system dynamically allocates these functions between AV and intelligent infrastructure, achieving a higher system intelligence level S than the downgraded vehicle intelligence level V. In addition, a function allocation system could dynamically allocate sensing, prediction and decision-making, and/or control functions between AV and a cloud platform. This invention also presents a function integration system or a fusion system for an AV.

Abstract: This invention presents an automated driving system with distributed computing (ADS-DC). During the operation of a connected automated vehicle (CAV), some or all of its automated driving capabilities for sensing, prediction, planning, decision-making, or control may be downgraded due to long-tail events or malfunctions. The intelligent roadside toolbox (IRT) functions as an edge server or a cloud, and can supplement CAV's sensing functions, prediction and management functions, planning and decision-making functions, and vehicle control functions by providing customized, on-demand, and dynamic computing resources and functions to the CAV. In addition, the IRT computing functions provide the computation support for sensing, prediction, planning, decision-making, and/or control functions of said CAV. Namely, the IRT functions as an edge server or a cloud to provide processing, training or optimization of CAV driving models as well as facilitate the implementation of the driving models in the CAV.

Abstract: An example device is described for facilitating polygon localization. In various aspects, the device can comprise a processor. In various instances, the device can comprise a non-transitory machine-readable memory that can store machine-readable instructions. In various cases, the processor can execute the machine-readable instructions, which can cause the processor to localize a polygon depicted in an image, based on execution of a deep learning pipeline. In various aspects, the deep learning pipeline can comprise a circular-softmax block.

Abstract: The present invention discloses a method of preparing procollagen from freshwater fish. The method comprises the following steps: pressure treatment, physical crushing, mixing and emulsification, homogenization, refrigeration, cleaning, extraction, homogenization, inactivation, homogenization, and filtration. In the mixing and emulsification step, freshwater fish tissue containing collagen is mixed with a surfactant to remove endotoxins to below 0.25 EU/ml. The procollagen is extracted following the step of adding enzymes and an acid solution of pH 3 to 6 to the pretreated tissue. The pretreatment of freshwater fish tissue in this invention can effectively reduce the endotoxins to below 0.25 EU/ml. The extraction technique of this invention can extract and retain greater amounts of procollagen while increasing its denaturation temperature and preserving the intact, tightly twisted triple-helix bonds of type I procollagen.