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Self-service car returning method in car sharing process and car sharing method based on self-service car returning

A self-service car returning method in the car sharing process and a car sharing method based on self-service car returning belong to the field of car sharing. The methods are disclosed in order to solve the problem that the procedure of car returning is complicated for car sharing as a car user needs to return a car to a car owner and the car owner needs to check the car face to face. The self-service car returning method is characterized by comprising the following steps: S1, a car user parks a car at an agreed location at the end of car sharing; the car user submits a car returning application through the APP client thereof, and takes an image of the car using an APP and uploads the image to a cloud platform server as the car checking basis for car returning, and the cloud platform server automatically adds a timestamp when the APP client of the car user uploads the image, carries out backup and image processing and comparing, makes out new damaged points generated after the car user picks up the car, and pushes the new damaged points to the APP client of a car sharer; and S3, the car sharer receives the car returning application, checks the car based on the image pushed by the APP client of the car user, and / or checks the car at the car location, and / or does not check the car.
Owner:DALIAN ROILAND SCI & TECH CO LTD

On-line continuous environmental air quality automatic monitoring system and peculiar smell source tracing method

ActiveCN105424840AReal-time air odor concentration distributionRapid Fingerprinting AnalysisComponent separationTerrainGas phase
The invention discloses an on-line continuous environmental air quality automatic monitoring base station, an automatic monitoring network system composed of a plurality of non-point source grid base stations and a data processing center, and a method of tracing with the system. The base station consists of an automatic sampling module, a sensor module and a meteorological monitoring module that are connected to a data transmission module. The data processing center monitoring the network system is equipped with databases, terrain data and a meteorological diffusion model. Once sampling occurs to the base station disposed in a protection zone of the system due to the deterioration of air quality, the data processing center runs the meteorological diffusion model according to real time data, calculates the occurring source that can affect the protection zone in the monitoring zone, and starts the base station set nearby the occurring source to perform sampling, a fast gas phase electronic nose is utilized to perform gas sample fingerprint analysis on the collected sample and compare fingerprint technology similarity, and the source can be traced according to the similarity. The system and the method have the characteristics of high precision, fast analysis speed and real-time grabbing of air samples, and provide sample guarantee for tracing positioning.
Owner:周俊杰

Deep learning based smart safe community management system

The invention relates to the field of community management, and particularly relates to a deep learning based smart safe community management system. The deep learning based smart safe community management system comprises a video monitoring module, a face recognition module, a vehicle information recognition module, a personnel hotspot distribution module, a vehicle trajectory analysis module, GIS electronic map and a big data cloud platform, and is characterized in that the video monitoring module, the face recognition module, the vehicle information recognition module, the personnel hotspot distribution module, the vehicle trajectory analysis module and the GIS electronic map are connected with the big data cloud platform through a network framework VPN channel. The beneficial effects are that the smart safe community management system combines a high-definition camera, extracts effective structured information from unstructured video information based on a deep learning algorithm, accurately recognizes face and vehicle information characteristics, quickly compares the face and vehicle information characteristics, integrates and links systems of a community and improves the management decision-making ability.
Owner:深圳火眼智能有限公司

Detection method for rapid change in multi-source navigation electronic map vector road network

The invention discloses a detection method for rapid change in a multi-source navigation electronic map vector road network. The detection method comprises the following steps: I. reading two groups of road networks to be matched, wherein one group is marked as a reference road network and the other group is marked as a target road network, acquiring topological relation between road network node and arc, and constructing a spatial index of node elements; II. for each road node in the reference road network, searching candidate matching node from the target road network, determining matching relation of the road node, and determining corresponding relation of road arcs by calculating an included angle cosine matrix; III. depending on the obtained node matching relation and arc corresponding relation, finally obtaining possible m-to-n matching relation between the road arcs, wherein if the matching relation can exist, both m and n are not changed; and IV. on the basis of result of the determined road arc matching relation, further deducing and judging possible matching relation. Through the detection method disclosed by the invention, a matching result with relatively high accuracy rate is obtained, and efficiency is comparatively high as well.
Owner:NORTH CHINA UNIV OF WATER RESOURCES & ELECTRIC POWER

Modular animal digestive tract in-vitro simulation system and human intestinal tract simulation method thereof

The invention discloses a modular animal digestive tract in-vitro simulation system and a human intestinal tract simulation method thereof. The modular animal digestive tract in-vitro simulation system comprises at least one animal digestive tract in-vitro simulation unit. Each animal digestive tract in-vitro simulation unit includes a frame, a reaction tank used for simulating a specific digestive tract cavity, and multiple function modules which can complete a specific and relatively independent task of intestinal tract simulation. Each frame is provided with multiple installation positions for installing the function modules and the reaction tank, and the function modules and the reaction tank are installed on the frame detachably. Each function module includes a sensor or a moving part, or includes both the sensor and the moving part. Each function module uses a separate Arduino nano 328 as a control chip, and is connected with an upper computer through a USB serial port. Each frame is equipped with a USB active hub. A USB is responsible for power supply to single chip microcomputers in the function modules and instruction transmission between upper and lower computers. Multiple function modules are integrated in one frame, so that the lab space is saved, the modules can be replaced rapidly, and a faulty module can be checked and replaced without shutdown.
Owner:JINAN UNIVERSITY

Hardware Trojan horse test system

ActiveCN103954904AImprove the level of automated testingEasy to handleDigital circuit testingElectrical resistance and conductanceFpga chip
The invention discloses a hardware Trojan horse test system. The hardware Trojan horse test system comprises a PC, an NI high-speed digital I/O board and a test circuit, wherein the PC is used for generating a test vector, conducting programming on an FPGA chip, controlling the NI high-speed digital I/O board, an oscilloscope and the FPGA chip and receiving signals sent by the NI high-speed digital I/O board and the oscilloscope; the NI high-speed digital I/O board is used for outputting the test vector to the FPGA chip, collecting an FPGA response signal and sending back the FPGA response signal to the PC; the testing circuit comprises the FPGA chip and receives the test vector output by the NI high-speed digital I/O board. The hardware Trojan horse test system further comprises a precise resistor R1, a precise resistor R2, the oscilloscope and a precise voltage-stabilized source, wherein the precise resistor R1 and the precise resistor R2 monitor the power consumption change of the kernel voltage and the auxiliary voltage of the FPGA chip, the oscilloscope is used for automatically triggering and collecting signals of power consumption change of the kernel voltage and the auxiliary voltage of the FPGA chip and sending the signals to the PC; the precise voltage-stabilized source is used for supplying power to the test circuit. The hardware Trojan horse test system conducts automatic tests, improves the precision of logic testing and bypass analysis and is high in application value.
Owner:FIFTH ELECTRONICS RES INST OF MINIST OF IND & INFORMATION TECH
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