Nokia Solutions and Networks Oy

International Business Machines Corporation

Chinese Academy of Sciences

Nokia Technologies Oy

Yi Zhi Yao

Yu Xin Zhao

Bing Xin Wang

Martin Kollar

Jian Zhang

Anatoly Andrianov

Tian Ji Yang

Yibo Wang

Ming Zhao

Xue Feng Gao

Malgorzata Tomala

Bernhard Wegmann

Guo Kang Fu

Yikang Zheng

Mu Dan Cao

Qingfeng Xue

Da Wei Zhang

Shun Zi Chen

Ingo Viering

Wei Peng Huang

Huan Wang

Hong Yu Chen

Xue Yong Zhang

Krzysztof Kordybach

Richard Waldhauser

Kun Yan Yin

He Li

Gyula Bodog

Hong Bing Zhang

Clemens Suerbaum

Xin Tang

Guang Qing Zhong

Qing Y Meng

Shaojiang Wu

Fan Teng

Embodiments of the present disclosure provide a real-time microseismic magnitude calculation method based on deep learning and a corresponding device. The method includes: constructing a DAS-based horizontal well microseismic monitoring system; constructing a training data set; constructing a magnitude calculation module, wherein the magnitude calculation module comprises two input branches of frequency spectrum and time waveform, the two input branches use a 3-layer convolution structure to extract frequency characteristic and waveform characteristic of a microseismic event, and then a model fusion is performed, and then 2 fully connected layers are used, and finally a calculated magnitude is outputted; training the magnitude calculation module; and analyzing and processing field data. The microseismic magnitude calculation method in the present disclosure improves the ability to quickly estimate the microseismic magnitude, without the need for converting the strain data, and improves the accuracy of the microseismic magnitude estimation.

Real-time microseismic magnitude calculation method and device based on deep learning

Systems, methods, apparatuses, and computer program products for virtualized network function (VNF) component (VNFC) level performance management are provided. One method includes collecting virtualized resources measurements, identifying virtualized network function components that the virtualized resources measurements belong to, and associating the collected virtualized resources measurements with an application function (MF).

Methods and apparatuses for virtualized network function component level virtualized resources performance management collection

The application discloses an AI real-time microseism monitoring node, which includes a processor and a data acquisition device, an AI calculation device, and a communication device connected to the processor, wherein the AI calculation device is provided with pre-trained microseism data analysis Device, and the processor is configured to perform the following operations: controlling the data acquisition equipment to acquire microseism data; turning on the AI calculation device to calculate the acquired microseism data by means of the microseism data analysis device to determine the valid event data associated with the microseism; and sending the valid event data to the remote data center through the communication device.

Artificial intelligence real-time microseism monitoring node

An artificial intelligence calculation method and apparatus for monitoring an earthquake in real time based on edge cloud cooperation is applied to a micro-earthquake data processing system. The micro-earthquake data processing system includes an edge calculation device and a remote server in communication connection with the edge calculation device. The remote server deploys a micro-earthquake data analyzing model based on an artificial intelligence to the edge calculation device in advance. The method includes steps of receiving, by the remote server, effective event data related to the micro-earthquake from the edge calculation device; performing a transfer training to the micro-earthquake data analyzing model by the remote server according to the effective event data; and updating the model after the micro-earthquake data analyzing model that has been transfer-trained is transmitted to the edge calculation device by the remote server.

Artificial intelligence calculation method and apparatus for monitoring earthquake in real time based on edge cloud cooperation, and storage medium

In an approach for JAVA Virtual Machine (JVM) heap memory tuning, one or more computer processors obtain a feature vector of an application running on the JVM. The one or more computer processors input the feature vector to a predictive model trained with historical application data collected in one or more production environments. The one or more computer processors receive an output of the predictive model based on the feature vector with at least one memory tuning recommendation for the JVM. The one or more computer processors tune the memory of the JVM based on the at least one memory tuning recommendation.

Machine-learning based heap memory tuning

A method and apparatus may include transmitting a scaling request. The scaling request comprises a request for virtualized network function expansion or virtualized network function contraction. The scaling request is transmitted to a second network node. A first domain is directed to application level details. A second domain is directed to virtualization level details. The scaling request comprises: (1) a relative target capacity that is generic to both the first domain and the second domain, (2) an absolute target capacity that is specific to the first domain, or (3) a relative target capacity that is specific to virtualized network function level targets. The method may also include receiving a notification that a virtualization network function has been updated based on the transmitted scaling request.

Method and apparatus for virtualized network function scaling that is initiated by network management and/or element management

A user reading statistic data set relating to a natural language document is received. The user reading statistic data set includes information indicative of at least one of a set of user reading statistic types. A set of machine logic rules is applied to the user reading statistic data set to generate, as reading assistance to the reader with reading the natural language document, a user reading comprehension data set including information indicative of reading comprehension with respect to content of the natural language document.

Generating a structured document guiding view

The present disclosure provides, in part, methods, computer program products, systems, for providing a method. In one embodiment a method can include for example applying tags to a first document according to a tagging map; and applying tags to a second document according to the tagging map. In one embodiment a method can include parsing first content of a first document and second content of a second document using a tagging map; and generating an output document using the tagging map, wherein the generating included presenting in first and second different areas defining the output document the first content and the second content. In one embodiment, a method can include providing a custom tagging map based on one or more user defined input; and applying tags to a document using the custom tagging map.

Mapping of documents with global tagging map

A method and system for improving a shared memory file transfer setup and usage is provided. The method includes configuring network links connected between hardware nodes. For every shared storage link, each hardware node includes a command section and a data storage section. A storage capacity for a hardware disk drive is determined based on a number of the hardware nodes and the hardware disk drive is connected to the hardware nodes. A software agent is installed within each of the hardware nodes and properties for the network links are configured. Each software agent is enabled and a connectivity status, bandwidth, and loading condition are tested for each of the network links. Each hardware node is registered with the hardware disk drive and communications between the hardware disk drive and the hardware nodes are enabled via the network links.

Shared memory device

There are provided measures for inactivity timer evaluation. Such measures exemplarily comprise monitoring a communication related state, determining, upon a first state change indicative of a start of a communication, a duration amount of a period between said first state change and a preceding second state change indicative of an end of a preceding communication, and adjusting a control value based on a distribution of a plurality of determined duration amounts.

Inactivity timer evaluation

A physical computer keyboard which includes: a circuit board having touchpoints; physical programmable, pluggable keys such that each of the keys is programmable to provide the function of each of the keys, each of the keys having interlocking elements to join with an adjoining key, each key having connectors on a bottom surface of each key to make electrical contact with the touchpoints; and display panels with one display panel on a top surface of each key, the function of each key being displayed on the display panel of each key.

Programmatic, pluggable keyboard

Feedback is collected from a user during log-on to a system. The feedback from the user can be used to enhance a knowledge base. The feedback is required from the user in order for the user to gain access to the system.

Collecting user feedback through logon questions

A method of energy saving is applied to a mobile communications network comprising at least two radio access technology systems () having a plurality of base stations (-). The method comprises the steps of: assigning () respective priorities to the radio access technology systems; and an energy saving server () instructing, on the basis of the priorities, a selected radio access technology system to reduce the operational state cells in a group of cells. This reduction occurs if the selected radio access technology system and/or another radio access technology system is able to maintain service to served mobile terminals.

Energy saving in a communications network

Growing community of inventors

Beijing, China

Yi Zhi Yao