Abstract: Properly parking personal mobility vehicles (PMVs) is an important for safety and public satisfaction. The large number of daily rides of ride-share PMVs makes it impossible to verify manually that each PMV is properly parked. Aspects of this disclosure include systems and methods for verifying that PMVs are properly parked. These systems and methods can include training a machine learning model on a server. The system can request that users submit images to the server, such that the server can verify that the user properly parked the PMV. The server can transmit a finished indication when it determines that the user properly parked the vehicle. The server can transmit instructions to the user to take various actions when it determines that the user improperly parked the vehicle or when the image is insufficient to determine whether the user properly parked the vehicle.

Abstract: Properly parking personal mobility vehicles (PMVs) is an important for safety and public satisfaction. The large number of daily rides of ride-share PMVs makes it impossible to verify manually that each PMV is properly parked. Aspects of this disclosure include systems and methods for verifying that PMVs are properly parked. These systems and methods can include training a machine learning model on a server. The system can request that users submit images to the server, such that the server can verify that the user properly parked the PMV. The server can transmit a finished indication when it determines that the user properly parked the vehicle. The server can transmit instructions to the user to take various actions when it determines that the user improperly parked the vehicle or when the image is insufficient to determine whether the user properly parked the vehicle.

Abstract: The disclosed embodiments relate to detecting sidewalk riding by a personal mobility vehicle (e.g., an electric scooter). For example, a method includes collecting sensor data (e.g., vibration data of an accelerometer) generated by the scooter while traveling on a surface of a travel pathway. The method further includes identifying a surface type by processing the collected sensor data with a computer model that can distinguish among different surface types, and determining that the travel pathway is unsuitable (e.g., a sidewalk) for the scooter based at least in part on the identified surface type (e.g., a pattern of concrete sections). In response to determining that the travel pathway is a sidewalk, causing the personal mobility vehicle to assist the user in navigating the personal mobility vehicle, alter a mobility operation of the personal mobility vehicle, or notify a surrounding area of a presence of the personal mobility vehicle.

Abstract: Properly parking personal mobility vehicles (PMVs) is an important for safety and public satisfaction. The large number of daily rides of ride-share PMVs makes it impossible to verify manually that each PMV is properly parked. Aspects of this disclosure include systems and methods for verifying that PMVs are properly parked. These systems and methods can include training a machine learning model on a server. The system can request that users submit images to the server, such that the server can verify that the user properly parked the PMV. The server can transmit a finished indication when it determines that the user properly parked the vehicle. The server can transmit instructions to the user to take various actions when it determines that the user improperly parked the vehicle or when the image is insufficient to determine whether the user properly parked the vehicle.

Abstract: Properly parking personal mobility vehicles (PMVs) is an important for safety and public satisfaction. The large number of daily rides of ride-share PMVs makes it impossible to verify manually that each PMV is properly parked. Aspects of this disclosure include systems and methods for verifying that PMVs are properly parked. These systems and methods can include training a machine learning model on a server. The system can request that users submit images to the server, such that the server can verify that the user properly parked the PMV. The server can transmit a finished indication when it determines that the user properly parked the vehicle. The server can transmit instructions to the user to take various actions when it determines that the user improperly parked the vehicle or when the image is insufficient to determine whether the user properly parked the vehicle.

Abstract: Properly parking personal mobility vehicles (PMVs) is an important for safety and public satisfaction. The large number of daily rides of ride-share PMVs makes it impossible to verify manually that each PMV is properly parked. Aspects of this disclosure include systems and methods for verifying that PMVs are properly parked. These systems and methods can include training a machine learning model on a server. The system can request that users submit images to the server, such that the server can verify that the user properly parked the PMV. The server can transmit a finished indication when it determines that the user properly parked the vehicle. The server can transmit instructions to the user to take various actions when it determines that the user improperly parked the vehicle or when the image is insufficient to determine whether the user properly parked the vehicle.

Abstract: The disclosed embodiments relate to detecting sidewalk riding by a personal mobility vehicle (e.g., an electric scooter). For example, a method includes collecting sensor data (e.g., vibration data of an accelerometer) generated by the scooter while traveling on a surface of a travel pathway. The method further includes identifying a surface type by processing the collected sensor data with a computer model that can distinguish among different surface types, and determining that the travel pathway is unsuitable (e.g., a sidewalk) for the scooter based at least in part on the identified surface type (e.g., a pattern of concrete sections). In response to determining that the travel pathway is a sidewalk, causing the personal mobility vehicle to assist the user in navigating the personal mobility vehicle, alter a mobility operation of the personal mobility vehicle, or notify a surrounding area of a presence of the personal mobility vehicle.

Abstract: A pressure reducing system for fuel gas and a natural gas dewaxing vehicle are provided. The pressure reducing system includes fuel gas pipelines which consist of successively connected a high pressure pipeline, a medium pressure pipeline and a low pressure pipeline in the flow direction of fuel gas. The tail end of the low pressure pipeline connects with a combustion apparatus. A high pressure relief valve, a high pressure air feed valve, a heat exchanger and a primary pressure reducing valve subassembly are connected on the high pressure pipeline. The heat exchanger is provided with a hot fluid inlet and a hot fluid outlet, where the hot fluid inlet connects with a hot water apparatus, and the hot fluid outlet connects with a water storage apparatus. The medium pressure pipeline is equipped with a medium pressure relief valve and a secondary pressure reducing valve.

Abstract: A pressure reducing system for fuel gas and a natural gas dewaxing vehicle are disclosed. The pressure reducing system (6) comprises fuel gas pipelines which consist of successively connected a high pressure pipeline (41), a medium pressure pipeline (42) and a low pressure pipeline (43) in the flow direction of fuel gas. The tail end of the low pressure pipeline (43) connects with an combustion apparatus (7). A high pressure relief valve (17), a high pressure air feed valve (21), a heat exchanger (24) and a primary pressure reducing valve subassembly are connected on the high pressure pipeline (41). The heat exchanger (24) is provided with a hot fluid inlet (24A) and a hot fluid outlet (24B), wherein the hot fluid inlet (24A) connects with an hot water apparatus (12), and the hot fluid outlet (24B) connects with an water storage apparatus. The medium pressure pipeline (42) is equipped with a medium pressure relief valve (27) and a secondary pressure reducing valve (29).

Abstract: An auction format may be selected pursuant to analyzing and identifying certain statistical patterns in historical data. For example, the choice of auction format may be based on whether bids and quality exhibit correlation, which can be identified in the historical data. By identifying the statistical patterns in the data, one can choose an auction format that can achieve generation of higher revenue. Such techniques allow an auctioneer, such as a search engine, to generate higher revenue than using a fixed auction format. For example, in the context of sponsored search auction, if the value of a click and the probability of a click are positively correlated, the auctioneer generates higher revenue by ranking the advertisers by bids rather than by bids multiplied by quality.