Abstract: A system and method for detecting rider impairment based on image or audio input is implemented in a rental fleet of lightweight vehicles. The system comprises a mobile device, a backend server, and one or more lightweight vehicles. Access to fleet vehicles is controlled by the mobile application based on results of data collected about the prospective driver.

Abstract: The present disclosure relates to a system and method for automatic vehicle recognition, based on a smart device. The system mainly includes an image capturing device integrated in the smart device, a data storage to store the images captured by the image capturing device and known identity aspects related to a vehicle allotted to a user, and a License plate processing and matching (LPPM) component to perform recognition process. LPPM component includes an identity aspect detector to detect a portion representing the identity aspect, an image processor to enhance the portion and perform Optical Characters Recognition (OCR) to extract character strings from the portion. The character string is compared against a character string of the known identity aspect to verify the vehicle.

Abstract: A method includes obtaining video content and associated substantially mono audio content. The method also includes determining at least one of a position or a motion trajectory of each of one or more objects detected in the video content and classifying each of the one or more objects into one of multiple object classes. The method further includes separating audio streams within the audio content based on the video content. Each of the audio streams is associated with one of multiple audio sources. The method also includes classifying each of the audio sources into one of the object classes. In addition, the method includes, for each audio source classified into the same object class as one of the one or more objects, distributing the audio stream associated with that audio source into multiple audio channels based on at least one of the position or the motion trajectory of that object.

Abstract: An image classification system and method are used to determine the status of equipment completeness of the rental two-wheeled vehicles, such as electric scooters. The system and method use deep learning models to analyze and classify ambiguous states of the rental vehicle when the user finishes the ride. These states are likely to be encountered by rental vehicles, to protect helmets, trunks or other equipment from loss or damage.

Abstract: An XR helmet collects user data and environmental data using onboard sensors. The collected data is used to train a model for predicting safe rides in a rental fleet of lightweight vehicles. The XR helmet is configured to selectively take control of the lightweight vehicle when driver biofeedback or environmental data are predictive of unsafe driving conditions. Access and control of fleet vehicles is controlled by a predictive machine learning model trained by data indicative of safe and unsafe driving conditions.

Abstract: A burst mode time division multiple access (TDMA) data processing system can determine burst time plans (BTPs). The burst mode TDMA data processing system can receive burst mode time division multiple access (TDMA) data. The burst mode TDMA data can be distributed among processors based on the BTPs. The distributed burst mode TDMA data can be demodulated and decoded the using the processors and the demodulated and decoded burst mode TDMA data can be output.

Abstract: A system and method for rider profiling for lightweight vehicles is disclosed herein. The system comprises a lightweight vehicle actuating unit. Load-cells are configured on a deck of the lightweight vehicle for sensing and measuring load acting thereupon for generating a measurement signal. A pressure-pattern collection unit receives the measurement signal to identify and process a load pattern acting on the deck to generate a pressure-pattern signal. A learning model receives the pressure-pattern signal for processing to obtain information associated with a pose of the rider. A riding control is coupled to a riding control database and configured to unit receive the information associated with the pose from the learning model for determining at least one instance of rule violation and computing a decision based on the at least one instance of rule violation.

Abstract: A smart system for detecting the presence of a helmet in a vehicle is disclosed herein. The system comprises a first transceiver configured within a trunk of the vehicle. The first transceiver is configured to transmit a first detection signal on detecting the opening of the trunk of the vehicle. At least one second transceiver corresponds to at least one helmet provided on the body of the helmet. The second transceiver is configured to respond to the first detection signal with a response signal, wherein the response signal includes a unique identity marker corresponding to the helmet. A transmission device is configured to detect opening and closing of trunk to activate the first transceiver, subsequent to which the first detection signal is sent, and the transmission device is further configured to transmit information associated with the response signal to a base controller.

Abstract: The present invention discloses a Double Metal Cyanide (DMC) catalyst(s) useful for the production of polyether polyols (PEPO) and a less energy intensive room temperature method for the synthesis thereof. The catalyst(s) comprises of a DMC complex, an organic complexing agent, i.e., ethylenediaminetetraacetic acid (EDTA) and other co-complexing organic agents, e.g., t-BuOH, PEPO of composition ranging from about 1 to 10 wt %, wherein the average molecular weight of PEPO used ranged from 200 to 1000. A method of preparing a series of DMC catalyst(s) at room temperature with varying compositional ratios of the complexing and co-complexing agents targeting a wide range of PEPO of varying kinematic viscosity range is also disclosed. These DMC catalyst(s) are amorphous, highly active, and easily separable from product PEPO with recyclability/recoverability, making the product PEPO better industrially applicable and DMC catalyst more cost-effective.

Abstract: A 3D printing and assembly system includes a 3D printer having a build volume; a robotic arm configured to access both within the build volume and outside of the printer. The printing and assembly system and a 3D computer hardware system are connected to both the printer and the robotic arm. An assistive object outside of build volume and accessible by robotic arm is identified. A 3D object assembly to be generated by the printer is identified. The assistive object and the object assembly is real-time analyzed, using the computer hardware system, to generate interdependent sequential instructions for the printer and the robotic arm. The already-generated object is positioned within the build volume using the robotic arm with the sequential instructions for the robotic arm. The object assembly is 3D printed by 3D printing around the already-generated object using the sequential instructions for the 3D printer.

Abstract: An embodiment for dynamically displaying images based on textual content is provided. The embodiment may include receiving real-time textual content from a sender and a recipient. The embodiment may also include deriving a topic of the real-time textual content and a context associated with the real-time textual content. The embodiment may further include identifying a medium in which the real-time textual content is entered. The embodiment may also include predicting a digital image to be displayed to the sender. The embodiment may further include in response to determining the digital image is available in a digital library, selecting the digital image from the digital library and displaying the selected digital image to the sender. The embodiment may also include validating the selected digital image and displaying the validated selected digital image to the recipient.

Abstract: Disclosed is an Augmented Reality (AR) optical waveguide. The AR optical waveguide includes a transparent substrate including a user proximate surface and a user distal surface. The AR optical waveguide also includes a slant etched diffractive grating included on the user distal surface of the transparent substrate. The slant etched diffractive grating includes a refractive index of greater than or equal to 2.0.

Abstract: An apparatus and method for expanded cohort application of machine-learning classifier methods based on a seed data set. The apparatus comprises at least a processor configured to receive at least a labeled seed set, train an embedding model based on the seed data, determine a plurality of vector representations for both the seed set and the target data, identify commonalities between the seed vector representation and the target vector, and provide the vector training data to a supervised machine-learning application for subsequent classifications.

Abstract: According to one embodiment, a method, computer system, and computer program product for static balancing of a cargo transport through digital twin simulation is provided. The embodiment may include capturing a plurality of property data related to a transport. The embodiment may further include capturing a plurality of property data related to a plurality of cargo items. The embodiment may also include generating a digital twin simulation of the transport and each cargo item. The embodiment may further include generating a loading plan of each cargo item onto the transport based on the generated digital twin simulation.

Abstract: According to one aspect, an adaptive driving style system may include a set of two or more sensors, a memory, and a processor. The set of two or more sensors may receive two or more sensor signals. The memory may store one or more instructions. The processor may execute one or more of the instructions stored on the memory to perform one or more acts, actions, or steps, including training a trust model using two or more of the sensor signals as input, training a preference model using the trust model and two or more of the sensor signals as input, and generating a driving style preference based on an adaptive driving style model including the trust model and the preference model.

Abstract: Embodiments herein describe techniques for a semiconductor device including a substrate. A first capacitor includes a first top plate and a first bottom plate above the substrate. The first top plate is coupled to a first metal electrode within an inter-level dielectric (ILD) layer to access the first capacitor. A second capacitor includes a second top plate and a second bottom plate, where the second top plate is coupled to a second metal electrode within the ILD layer to access the second capacitor. The second metal electrode is disjoint from the first metal electrode. The first capacitor is accessed through the first metal electrode without accessing the second capacitor through the second metal electrode. Other embodiments may be described and/or claimed.

Abstract: An embodiment for decontaminating transportation vehicles is provided. The embodiment may include receiving GPS data and real-time and historical data relating to contamination. The embodiment may also include identifying a route and location of the transportation vehicle. The embodiment may further include predicting one or more target areas to decontaminate. The embodiment may also include placing one or more decontamination devices at the target areas. The embodiment may further include identifying one or more parts of the transportation vehicle requiring decontamination. The embodiment may also include in response to determining at least one type of contamination is airborne, activating the one or more decontamination devices to increase air pressure inside the transportation vehicle and releasing the air pressure when a door is opened.

Abstract: An interactive voice response system is provided that includes an interactive voice recognition module, an image collection module, and a data extraction module. The image collection module communicates with the voice recognition module and the user device. The extraction module communicates with the image collection module. The voice recognition module collects speech data from a user of the user device and provides an indication to the image collection module when the speech data includes complex data. The image collection module, in response to the indication, communicates with the user device in a text message. The text message includes a link that, when activated, opens a camera on the user device. The image collection module, in response to receiving an image having the complex data from the camera, communicates the image to the extraction module, which extracts the complex data from the image as textual data.

Abstract: An apparatus may include a database and a processor in communication with at least one network. The processor may be configured to instantiate an application stack comprising a data missing detector, a data source router, and a response handler. The data missing detector may be configured to receive a request for data and determine whether the data is available from the database. The data source router may be configured to identify an alternate database from which to obtain the data when the data is not available from the database and route the request for data through the at least one network to an alternate processor associated with the alternate database. The response handler may be configured identify responsive data to a routed response received from another processor in the database and send the responsive data to a requesting device. Multiple apparatuses may form a distributed system.

Abstract: Distributed data sampling, including: receiving a sampling target; generating, based on one or more sensors, sampled data; determining, based on the sampling target, a value for the sampled data; and determining, based on the value for the sampled data, whether to provide the sampled data to a remotely disposed computing device.