Patents by Inventor Junjiang Li
Junjiang Li has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20250227835Abstract: An X-band small-focus accelerator for non-destructive testing is provided, including: a magnetron used to generate microwaves; an accelerating tube used to accelerate electrons, where the accelerating tube is an X-band accelerating tube; a microwave system connected between the magnetron and the accelerating tube, and used to feed the microwaves generated by the magnetron into the accelerating tube; an electron gun connected to the accelerating tube, and used to emit an electron beam into the accelerating tube; and an electron gun power supply used to supply power to the electron gun, where the accelerating tube, the microwave system, the magnetron and the electron gun power supply are arranged in sequence in a front-rear direction of the accelerator to determine a length of the accelerator.Type: ApplicationFiled: June 30, 2023Publication date: July 10, 2025Inventors: Yaohong LIU, Huaibi CHEN, Wei JIA, Hao ZHA, Yu HE, Jian LI, Weiqiang GUAN, Ming JIN, Qing YE, Junjiang LI, Yan XU
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Patent number: 11995796Abstract: A method of reconstruction of super-resolution of video frame includes inputting a first video frame with a first resolution and a plurality of consecutive frames thereof into a pre-trained super-resolution reconstruction network, and outputting, by the pre-trained super-resolution reconstruction network, a second video frame with a second resolution corresponding to the first video frame. The second resolution is higher than the first resolution. The super-resolution reconstruction network includes a feature extraction subnetwork, a spatial-temporal non-local alignment subnetwork, an attention progressive fusion subnetwork, and an up-sampling subnetwork which are connected in sequence.Type: GrantFiled: November 17, 2021Date of Patent: May 28, 2024Inventors: Dengyin Zhang, Chao Zhou, Can Chen, Junjiang Li, Zijie Liu, Yi Cheng
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Patent number: 11983562Abstract: A multidimensional resource scheduling method in a Kubernetes cluster architecture system is provided. For a computing-intensive service, each server node in the cluster is scored according to CPU idleness and memory idleness; for an ordinary service, each server node in the cluster is scored according to resource requirements of a scheduling task, a resource priority of each server node and resource balance of each server node. The pod scheduling task is bound to a server node with a highest score for execution. This scheduling method meets diverse resource requests of various services, thereby enhancing the flexibility and expandability of the system.Type: GrantFiled: August 6, 2021Date of Patent: May 14, 2024Assignee: NANJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONSInventors: Dengyin Zhang, Lin Zhu, Junjiang Li, Zijie Liu, Chengwan Ai
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Patent number: 11868944Abstract: A container image management system for distributed clusters, the system including at least one master node and at least one worker node. The at least one master node includes a container image database, a request input module and a container image management module. The container image management module is responsive when the container image management module establishes the connection to the container image database, then it is configured to perform a read/write operation on the container image database. The container image database is a distributed database configured to store node information of the at least one master node and the at least one worker node in the container image management system. The request input module is configured to receive request content including a request destination and command execution content. The command execution content includes an execution operation field and an executed container image list.Type: GrantFiled: December 10, 2020Date of Patent: January 9, 2024Inventors: Dengyin Zhang, Junjiang Li, Can Chen, Chao Zhou, Zijie Liu
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Patent number: 11734152Abstract: A method for detecting comprehensive GPU-related factors of a distributed cluster, the method including: (1): checking whether there is a configuration file content of an operating node; (2): reading a mode parameter in an environment variable of the operating node, and correspondingly switching an operating mode according to the mode parameter; (3): reading a timer frequency value from the environment variable of the operating node so as to set a time period for reading a GPU information parameter according to the timer frequency value; (4): calculating the maximum value of the GPU information parameter of the operating node, and storing the maximum value into the GPU information list cache; and (5): initializing the transmitted information; determining whether there is a GPU in the GPU information list cache of the operating node.Type: GrantFiled: July 7, 2021Date of Patent: August 22, 2023Assignee: Nanjing University of Posts and TelecommunicationsInventors: Dengyin Zhang, Junjiang Li, Yi Cheng, Yingjie Kou, Zheng Zhou, Wensheng Han, Shibo Kang
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Patent number: 11656902Abstract: Disclosed in the present invention are a distributed container image construction scheduling system and method. The system includes a construction node and a management node. The construction node includes an image constructor for executing a construction task issued by the management node. The management node includes a console and a scheduler. The console is responsible for acquiring the relevant parameters such as a development dependency library and system configuration required by a user, and generating tasks with these parameters and sending same to the scheduler. The scheduler is used for receiving the tasks sent by the console, detecting the legitimacy of the tasks, and sending the tasks to the corresponding construction node to be run.Type: GrantFiled: January 6, 2021Date of Patent: May 23, 2023Inventors: Dengyin Zhang, Junjiang Li, Zijie Liu, Lin Zhu, Yi Cheng, Yingying Zhou, Zhaoxi Shi
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Patent number: 11490128Abstract: The present disclosure provides a deep neural network (DNN)-based reconstruction method and apparatus for compressive video sensing (CVS). The method divides a video signal into a key frame and a non-key frame. The key frame is reconstructed by using an existing image reconstruction method. The non-key frame is reconstructed by using a special DNN according to the present disclosure. The neural network includes an adaptive sampling module, a multi-hypothesis prediction module, and a residual reconstruction module. The neural network makes full use of a spatio-temporal correlation of the video signal to sample and reconstruct the video signal. This ensures low time complexity of an algorithm while improving reconstruction quality. Therefore, the method in the present disclosure is applicable to a video sensing system with limited resources on a sampling side and high requirements for reconstruction quality and real-time performance.Type: GrantFiled: August 17, 2020Date of Patent: November 1, 2022Inventors: Dengyin Zhang, Chao Zhou, Can Chen, Junjiang Li, Zijie Liu
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Publication number: 20220291956Abstract: A distributed container scheduling method includes: monitoring a container creation event in a Kubernetes API-Server in real time, and validating a container created once a new container creation event is detected; updating a container scheduling queue with containers passing the validation; when the container scheduling queue is empty, performing no operation until the containers passing the validation are added to the queue; when the container scheduling queue is not empty, reading the containers to be scheduled from the container scheduling queue in sequence, and selecting, from a Kubernetes cluster, an optimal node corresponding to the containers to be scheduled to generate a container scheduling two-tuple; and scheduling, based on the container scheduling two-tuple, the containers to be scheduled to the optimal node to finish the distributed container scheduling operation.Type: ApplicationFiled: March 22, 2022Publication date: September 15, 2022Inventors: Dengyin ZHANG, Junjiang LI, Zijie LIU, Yi CHENG, Yingjie KOU, Hong ZHU, Weidan YAN
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Publication number: 20220261959Abstract: A method of reconstruction of super-resolution of video frame includes inputting a first video frame with a first resolution and a plurality of consecutive frames thereof into a pre-trained super-resolution reconstruction network, and outputting, by the pre-trained super-resolution reconstruction network, a second video frame with a second resolution corresponding to the first video frame. The second resolution is higher than the first resolution. The super-resolution reconstruction network includes a feature extraction subnetwork, a spatial-temporal non-local alignment subnetwork, an attention progressive fusion subnetwork, and an up-sampling subnetwork which are connected in sequence.Type: ApplicationFiled: November 17, 2021Publication date: August 18, 2022Inventors: Dengyin ZHANG, Chao ZHOU, Can CHEN, Junjiang LI, Zijie LIU, Yi CHENG
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Publication number: 20220171652Abstract: Disclosed in the present invention are a distributed container image construction scheduling system and method. The system includes a construction node and a management node. The construction node includes an image constructor for executing a construction task issued by the management node. The management node include, a console and a scheduler. The console is responsible for acquiring the relevant parameters such as a development dependency library and system configuration required by a user, and generating tasks with these parameters and sending same to the scheduler. The scheduler is used for receiving the tasks sent by the console, detecting the legitimacy of the tasks, and sending the tasks to the corresponding construction node to be run.Type: ApplicationFiled: January 6, 2021Publication date: June 2, 2022Inventors: Dengyin ZHANG, Junjiang LI, Zijie LIU, Lin ZHU, Yi CHENG, Yingying ZHOU, Zhaoxi SHI
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Publication number: 20220030281Abstract: The present disclosure provides a deep neural network (DNN)-based reconstruction method and apparatus for compressive video sensing (CVS). The method divides a video signal into a key frame and a non-key frame. The key frame is reconstructed by using an existing image reconstruction method. The non-key frame is reconstructed by using a special DNN according to the present disclosure. The neural network includes an adaptive sampling module, a multi-hypothesis prediction module, and a residual reconstruction module. The neural network makes full use of a spatio-temporal correlation of the video signal to sample and reconstruct the video signal. This ensures low time complexity of an algorithm while improving reconstruction quality. Therefore, the method in the present disclosure is applicable to a video sensing system with limited resources on a sampling side and high requirements for reconstruction quality and real-time performance.Type: ApplicationFiled: August 17, 2020Publication date: January 27, 2022Inventors: Dengyin ZHANG, Chao ZHOU, Can CHEN, Junjiang LI, Zijie LIU
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Publication number: 20210382808Abstract: A method for detecting comprehensive GPU-related factors of a distributed cluster, the method including: (1): checking whether there is a configuration file content of an operating node; (2): reading a mode parameter in an environment variable of the operating node, and correspondingly switching an operating mode according to the mode parameter; (3): reading a timer frequency value from the environment variable of the operating node so as to set a time period for reading a GPU information parameter according to the timer frequency value; (4): calculating the maximum value of the GPU information parameter of the operating node, and storing the maximum value into the GPU information list cache; and (5): initializing the transmitted information; determining whether there is a GPU in the GPU information list cache of the operating node.Type: ApplicationFiled: July 7, 2021Publication date: December 9, 2021Inventors: Dengyin ZHANG, Junjiang LI, Yi CHENG, Yingjie KOU, Zheng ZHOU, Wensheng HAN, Shibo KANG
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Publication number: 20210365290Abstract: A multidimensional resource scheduling method in a Kubernetes cluster architecture system is provided. For a computing-intensive service, each server node in the cluster is scored according to CPU idleness and memory idleness; for an ordinary service, each server node in the cluster is scored according to resource requirements of a scheduling task, a resource priority of each server node and resource balance of each server node. The pod scheduling task is bound to a server node with a highest score for execution. This scheduling method meets diverse resource requests of various services, thereby enhancing the flexibility and expandability of the system.Type: ApplicationFiled: August 6, 2021Publication date: November 25, 2021Inventors: Dengyin ZHANG, Lin ZHU, Junjiang LI, Zijie LIU, Chengwan AI
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Publication number: 20210097477Abstract: A container image management system for distributed clusters, the system including at least one master node and at least one worker node. The at least one master node includes a container image database, a request input module and a container image management module. The container image management module is responsive when the container image management module establishes the connection to the container image database, then it is configured to perform a read/write operation on the container image database. The container image database is a distributed database configured to store node information of the at least one master node and the at least one worker node in the container image management system. The request input module is configured to receive request content including a request destination and command execution content. The command execution content includes an execution operation field and an executed container image list.Type: ApplicationFiled: December 10, 2020Publication date: April 1, 2021Inventors: Dengyin ZHANG, Junjiang LI, Can CHEN, Chao ZHOU, Zijie LIU
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Publication number: 20160259762Abstract: The disclosure provides a webpage layout method and apparatus, a computer storage medium and a terminal. The webpage layout method includes steps as follows: it is determined whether a current webpage belongs to pre-counted webpages frequently accessed by a user, and a determining result is obtained; when the determining result is YES, a user preference value of each channel in the current webpage is counted, and the current webpage starts to be rendered; and during rendering the current webpage, if the user preference value of a detected channel is determined to be greater than a set basic preference value, all pieces of sub-link information in the channel are rendered; otherwise, if the user preference value of the detected channel is determined to be smaller than or equal to the basic preference value, all pieces of sub-link information in the channel are rendered in an additionally initiated thread.Type: ApplicationFiled: November 21, 2013Publication date: September 8, 2016Inventor: Junjiang Li
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Patent number: D1038190Type: GrantFiled: May 17, 2024Date of Patent: August 6, 2024Inventor: Junjiang Li
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Patent number: D1069491Type: GrantFiled: October 12, 2024Date of Patent: April 8, 2025Inventor: Junjiang Li