Abstract: A secure authorization method and system. The method includes providing, an XFA authorization backend having registered therein a user that wants to protect access or protect the performance of an operation on an Internet-connected asset having a service backend computer where the asset is assigned to the user through an identifying element; receiving, by the XFA backend, one or more user-configurable security factors that are linked to a producer service and provide information about the user. When the user wants to access the asset or the performance of an operation on the asset, the XFA backend receives a checking enquire for at least one of the user-configurable security factors, and in response to the checking enquire, the XFA backend checks if the user fulfils the enquired user-configurable security factor/s using the identifying element, and authorizes or denies the access or the performance of the operation based on the checking.

Abstract: In some embodiments, a computer-implemented method for predicting agronomic field property data for one or more agronomic fields using a trained machine learning model is disclosed. The method comprises receiving, at an agricultural intelligence computer system, agronomic training data; training a machine learning model, at the agricultural intelligence computer system, using the agronomic training data; in response to receiving a request from a client computing device for agronomic field property data for one or more agronomic fields, automatically predicting the agronomic field property data for the one or more agronomic fields using the machine learning model configured to predict agronomic field property data; based on the agronomic field property data, automatically generating a first graphical representation; and causing to display the first graphical representation on the client computing device.

Abstract: A method and an orchestration server for packet data network service slicing over a network infrastructure for real-time IP services are provided. The method comprises providing an orchestration server that has knowledge of a whole connectivity status of a network infrastructure and that is configured to manage service nodes. The server receives a session request for a real-time IP service from a UE device located in a given region and requests to one or more service nodes of said given region whether it has/they have network resources. Each of the one or more service nodes compute a QoS measurement thereof in terms of KPIs including latency, jitter and bandwidth, the QoS measurement being computed by a software module that is implemented on a virtual machine deployed on the service node; and tag a plurality of interfaces. The orchestration server selects a given service node in view of said QoS measurement.

Abstract: Systems and methods for identifying clouds and cloud shadows in satellite imagery are described herein. In an embodiment, a system receives a plurality of images of agronomic fields produced using one or more frequency bands. The system also receives corresponding data identifying cloud and cloud shadow locations in the images. The system trains. a machine learning system to identify at least cloud locations using the images as inputs and at least data identifying pixels as cloud pixels or non-cloud pixels as outputs. When the system receives one or more particular images of a particular agronomic field produced using the one or more frequency bands, the system uses the one or more particular images as inputs into the machine learning system to identify a plurality of pixels in the one or more particular images as particular cloud locations.

Abstract: The disclosed technology is generally directed to downlink prioritization of on-orbit spaceborne data. In one example of the technology, image metadata and raw image data obtained from sensors on the constrained-environment device are stored. The raw image data includes a plurality of images. A plurality of images tiles is provided such that the plurality of images tiles includes, for each image of the plurality of images, evenly-spaced portions of the image. Via an embedding-generation model, a plurality of embeddings is generated based on the plurality of image tiles. The plurality of embeddings is used to perform a prioritization of image tiles among the plurality of image tiles. During a downlink session from the constrained-environment device, image tiles from among the plurality of image tiles are downlinked based, at least in part, on the prioritization.

Abstract: A method and a system for multi-factor authentication for blockchain services are proposed.

Abstract: A method and a system for multi-factor authentication for blockchain services, the method comprising holding, by an authentication server, an account of an end-user identifiable via an accountID; establishing, by the end-user, a multi-factor approval status in the server; and in response to an operation to be performed in a customer smart contract, the latter interacting with the server to confirm the established multi-factor approval status.

Abstract: A method and system for multi-factor authenticating users in Web3 services includes a multi-factor authentication (e.g., 2FA) provider configured to validate that an end-user owns a public key in a blockchain based on a cryptocurrency or a NFT transference, the public key used as a first factor for the authentication. The authentication provider interacts with a smart contract to perform the multi-factor authentication in an operation in a smart contract by using off-chain data as the other factor(s) required for the multi-factor authentication. The off-chain data are received in a user terminal, e.g., a smartphone via SMS or a mobile application, associated with the account created in the authentication provider. The authentication result is read by each node executing the smart contract and, when a consensus is reached among nodes, a new block representing the result is generated in the blockchain.

Abstract: A method and system for optimizing indoor wireless coverage are proposed. A user device and computer program are also proposed. The method comprises connecting, by a mobile device, to a wireless router via a first wireless network, the wireless router being located at a customer premises; computing a coverage metric for a plurality of subpoints within at least a first point and a second point of the customer premises, obtaining a plurality of coverage metrics as a result, each coverage metric comprising a position of the mobile device and a quality indicator of the wireless connection of the mobile device in that position; generating a wireless coverage map using the plurality of coverage metrics; determining whether a wireless signal repeater has to be installed based on the generated wireless coverage map; and showing a new wireless coverage map considering the installation of the wireless signal repeater.

Abstract: A method and system for multi-factor authenticating a user wearing a VR headset (120) comprising a multi-factor authentication application programming interface to interact with a multi-factor authentication provider server (110) and enable the user to create an account in the provider server (110) associated with a secondary device (130). Each one-time code generated by the provider server (110) is received in the secondary device (130) through a secondary communication channel. The one-time code is entered, through a graphical interface (1000) of the VR headset (120), while the user is wearing it, by hearing or seeing the code, received in the secondary device (130), through the VR headset (120). The entered code is sent from the VR headset (120) to the provider server (110) to verify it and determines whether the user is enabled to access the VR application, the access is disabled or the user is asked for another entry of code through the VR headset (120).

Abstract: Systems and methods for identifying clouds and cloud shadows in satellite imagery are described herein. In an embodiment, a system receives a plurality of images of agronomic fields produced using one or more frequency bands. The system also receives corresponding data identifying cloud and cloud shadow locations in the images. The system trains. a machine learning system to identify at least cloud locations using the images as inputs and at least data identifying pixels as cloud pixels or non-cloud pixels as outputs. When the system receives one or more particular images of a particular agronomic field produced using the one or more frequency bands, the system uses the one or more particular images as inputs into the machine learning system to identify a plurality of pixels in the one or more particular images as particular cloud locations.

Abstract: A conjugate for active targeted therapy of tumors is obtained by coupling a hydrophilic affibody with an active tumor targeting function and a hydrophobic anti-tumor cytotoxin through a small molecule linker. The affibody has a specific binding activity and a high affinity to receptors overexpressed on surfaces of various tumor cells. The cytotoxin is a highly effective anti-tumor drug. The affibody-cytotoxin conjugate can self-assemble in water to form the nanoparticle with the affinity body as a shell and the cytotoxin as an inner core. Since the affibody can specifically recognize and bind to receptors overexpressed on the surfaces of the tumor cells, the nanoparticle can be efficiently enriched at tumor sites and biodegraded through the linker to release the cytotoxin and reach effective therapeutic concentrations for inhibiting the growth of the tumors while reducing toxic and side effects to normal organs and tissues.

Abstract: Systems and methods for identifying clouds and cloud shadows in satellite imagery are described herein. In an embodiment, a system receives a plurality of images of agronomic fields produced using one or more frequency bands. The system also receives corresponding data identifying cloud and cloud shadow locations in the images. The system trains. a machine learning system to identify at least cloud locations using the images as inputs and at least data identifying pixels as cloud pixels or non-cloud pixels as outputs. When the system receives one or more particular images of a particular agronomic field produced using the one or more frequency bands, the system uses the one or more particular images as inputs into the machine learning system to identify a plurality of pixels in the one or more particular images as particular cloud locations.

Abstract: A computer-implemented technique is described herein for interpolating input data that includes image and/or audio content. The technique identifies plural sizes associated with different respective phenomena exhibited by the input data. The technique then interpolates the input data in a pipeline that includes plural passes. The plural passes are controlled using plural respective parameter values. The plural respective parameter values, in turn, are selected based on the plural respective sizes, arranged from largest to smallest. In other implementations, the technique chooses pass-specific algorithmic changes to be applied by the interpolation algorithms used by the different passes. In other implementations, the technique chooses its configurations without regard to sizes of phenomena that may be exhibited in the input data. The technique is advantageous because it reduces the presence of artifacts in output data produced by the computer-implemented technique.

Abstract: In an embodiment, a computer-implemented method for predicting subfield soil properties for an agricultural field comprises: receiving satellite remote sensing data that includes a plurality of images capturing imagery of an agricultural field in a plurality of optical domains; receiving a plurality of environmental characteristics for the agricultural field; generating a plurality of preprocessed images based on the plurality of satellite remote sensing data and the plurality of environmental characteristics; identifying, based on the plurality preprocessed images, a plurality of features of the agricultural field; generating a subfield soil property prediction for the agricultural field by executing one or more machine learning models on the plurality of features; transmitting the subfield soil property prediction to an agricultural computer system.

Abstract: Systems and methods for identifying clouds and cloud shadows in satellite imagery are described herein. In an embodiment, a system receives a plurality of images of agronomic fields produced using one or more frequency bands. The system also receives corresponding data identifying cloud and cloud shadow locations in the images. The system trains. a machine learning system to identify at least cloud locations using the images as inputs and at least data identifying pixels as cloud pixels or non-cloud pixels as outputs. When the system receives one or more particular images of a particular agronomic field produced using the one or more frequency bands, the system uses the one or more particular images as inputs into the machine learning system to identify a plurality of pixels in the one or more particular images as particular cloud locations.

Abstract: A method and an orchestration server for packet data network service slicing over a network infrastructure for real-time IP services are provided. The method comprises providing an orchestration server that has knowledge of a whole connectivity status of a network infrastructure and that is configured to manage service nodes. The server receives a session request for a real-time IP service from a UE device located in a given region and requests to one or more service nodes of said given region whether it has/they have network resources. Each of the one or more service nodes compute a QoS measurement thereof in terms of KPIs including latency, jitter and bandwidth, the QoS measurement being computed by a software module that is implemented on a virtual machine deployed on the service node; and tag a plurality of interfaces. The orchestration server selects a given service node in view of said QoS measurement.

Abstract: Systems and methods for identifying clouds and cloud shadows in satellite imagery are described herein. In an embodiment, a system receives a plurality of images of agronomic fields produced using one or more frequency bands. The system also receives corresponding data identifying cloud and cloud shadow locations in the images. The system trains a machine learning system to identify at least cloud locations using the images as inputs and at least data identifying pixels as cloud pixels or non-cloud pixels as outputs. When the system receives one or more particular images of a particular agronomic field produced using the one or more frequency bands, the system uses the one or more particular images as inputs into the machine learning system to identify a plurality of pixels in the one or more particular images as particular cloud locations.

Abstract: In some embodiments, a computer-implemented method for predicting agronomic field property data for one or more agronomic fields using a trained machine learning model is disclosed. The method comprises receiving, at an agricultural intelligence computer system, agronomic training data; training a machine learning model, at the agricultural intelligence computer system, using the agronomic training data; in response to receiving a request from a client computing device for agronomic field property data for one or more agronomic fields, automatically predicting the agronomic field property data for the one or more agronomic fields using the machine learning model configured to predict agronomic field property data; based on the agronomic field property data, automatically generating a first graphical representation; and causing to display the first graphical representation on the client computing device.

Abstract: A control function configuration method includes broadcasting a control function message in a control system through a narrow-band communication network, and receiving a function-configured notification message sent by a target secondary control device in the control system through the narrow-band communication network. The function-configured notification message indicates that a control function of the target secondary control device has been configured to be a target control function. The method further includes broadcasting a function-configured status message in the control system through the narrow-band communication network. The function-configured status message indicates that the control function of the target secondary control device has been configured to be the target control function.