mhurhangee/patent-ind-claim-en huggingface dataset:
A method, comprising: providing, by a device and to a network device (220-1, ..., 220-N), a subscribe request that includes a request for sensor data based on an event; receiving, by the device and based on the subscribe request, sensor data packets, wherein each of the sensor data packets includes: the sensor data associated with one or more elements of the network device, and a header extension identifying a respective group identifier for a respective group of sensor data and final packet information indicating whether the sensor data packet is a final one for the respective group; storing, by the device, the sensor data packets until the final packet information of one of the sensor data packets indicates that the one of the sensor data packets is a final sensor data packet for the respective group of sensor data; identifying, by the device, a complete set of the sensor data packets when the final packet information of the one of the sensor data packets indicates that the one of the sensor data packets is the final sensor data packet for the respective group of sensor data; and performing, by the device, one or more actions based on the complete set of the sensor data packets. providing, by a device and to a network device (220-1, ..., 220-N), a subscribe request that includes a request for sensor data based on an event; receiving, by the device and based on the subscribe request, sensor data packets, wherein each of the sensor data packets includes: the sensor data associated with one or more elements of the network device, and a header extension identifying a respective group identifier for a respective group of sensor data and final packet information indicating whether the sensor data packet is a final one for the respective group; the sensor data associated with one or more elements of the network device, and a header extension identifying a respective group identifier for a respective group of sensor data and final packet information indicating whether the sensor data packet is a final one for the respective group; storing, by the device, the sensor data packets until the final packet information of one of the sensor data packets indicates that the one of the sensor data packets is a final sensor data packet for the respective group of sensor data; identifying, by the device, a complete set of the sensor data packets when the final packet information of the one of the sensor data packets indicates that the one of the sensor data packets is the final sensor data packet for the respective group of sensor data; and performing, by the device, one or more actions based on the complete set of the sensor data packets.
A method for determining a distance (h) to a surface of a product in a tank based on a time delay of electromagnetic signals propagating between a predefined reference and a surface of said product, said method comprising the steps of: i) generating a transmission signal (tx) in the form of a first pulse train having a predetermined pulse repetition frequency (PRF), said first pulse train comprising at least 5 pulses having a constant pulse repetition frequency; ii) generating a reference signal (rx) in the form of a second pulse train by generating a predefined and fixed time delay (T D )between said first and second pulse trains relative each other; wherein each pulse in said first and second pulse trains have essentially identical waveforms; wherein said first and second pulse trains have the same pulse repetition frequency (PRF); iii) guiding said transmission signal into the tank as electromagnetic signals, and allowing said signals to propagate towards said surface; iv) receiving a reflected signal (refl) reflected from the tank; v) forming a correlation value (corr) based on a time correlation between a pulse of the reference signal and the reflected signal, and storing said correlation value and the associated pulse repetition frequency; vi) carrying out steps i) to v) in sequence for at least three different pulse repetition frequencies (PRF 1-3 ), until at least three pairs of correlation values (cor n ) and associated pulse repetition frequencies (PRF n ) have been stored; vii) determining said distance based on said at least three pairs of correlation values and associated pulse repetition frequencies, and said fixed time delay between the reference signal and the transmission signal. i) generating a transmission signal (tx) in the form of a first pulse train having a predetermined pulse repetition frequency (PRF), said first pulse train comprising at least 5 pulses having a constant pulse repetition frequency; ii) generating a reference signal (rx) in the form of a second pulse train by generating a predefined and fixed time delay (T D )between said first and second pulse trains relative each other; iii) guiding said transmission signal into the tank as electromagnetic signals, and allowing said signals to propagate towards said surface; iv) receiving a reflected signal (refl) reflected from the tank; v) forming a correlation value (corr) based on a time correlation between a pulse of the reference signal and the reflected signal, and storing said correlation value and the associated pulse repetition frequency; vi) carrying out steps i) to v) in sequence for at least three different pulse repetition frequencies (PRF 1-3 ), until at least three pairs of correlation values (cor n ) and associated pulse repetition frequencies (PRF n ) have been stored; vii) determining said distance based on said at least three pairs of correlation values and associated pulse repetition frequencies, and said fixed time delay between the reference signal and the transmission signal.
Process for manufacturing a nanocomposite polymer by means of a single screw extruder or twin-screw comprising a sleeve, characterized in that it comprises the following steps of : - addition of inorganic or inorganic / organic hybrid precursors of nanofillers to a thermoplastic polymer or to a prepolymer for thermosetting resin in the extruder; - dispersion in the thermoplastic polymer or the thermosetting resin prepolymer in the molten state of the inorganic or inorganic / organic hybrid precursors of nanofillers ; - inorganic condensation under the action of microwaves ; and - Obtaining a thermoplastic or thermosetting nano composite polymer. - addition of inorganic or inorganic / organic hybrid precursors of nanofillers to a thermoplastic polymer or to a prepolymer for thermosetting resin in the extruder; - dispersion in the thermoplastic polymer or the thermosetting resin prepolymer in the molten state of the inorganic or inorganic / organic hybrid precursors of nanofillers ; - inorganic condensation under the action of microwaves ; and - Obtaining a thermoplastic or thermosetting nano composite polymer.
A method for the optical characterization of at least one particle present in a sample , comprising: - the illumination of said sample using a light beam, the sample being positioned in the object space of an optical system ; - the acquisition of at least one phase image and at least one intensity image of said at least one particle illuminated by the light beam, the acquisition being carried out in an analysis plane arranged in the image space of the optical system ; - the calculation of a combined image from said at least one phase image and said at least one intensity image, said combined image being obtained from the normalized complex transmission, the real part of the normalized complex transmission or the imaginary part of the normalized complex transmission; wherein the method is characterized in that it further comprises: - the summation of points of said combined image over a given field of the combined image comprising an image of said at least one particle; - the determination of at least one optical property of said at least one particle from said sum, said at least one optical property comprising at least one of the complex dipolar polarizability, the effective absorption cross section, the effective scattering cross section, the effective extinction cross section. - the illumination of said sample using a light beam, the sample being positioned in the object space of an optical system ; - the acquisition of at least one phase image and at least one intensity image of said at least one particle illuminated by the light beam, the acquisition being carried out in an analysis plane arranged in the image space of the optical system ; - the calculation of a combined image from said at least one phase image and said at least one intensity image, said combined image being obtained from the normalized complex transmission, the real part of the normalized complex transmission or the imaginary part of the normalized complex transmission; wherein the method is characterized in that it further comprises: - the summation of points of said combined image over a given field of the combined image comprising an image of said at least one particle; - the determination of at least one optical property of said at least one particle from said sum, said at least one optical property comprising at least one of the complex dipolar polarizability, the effective absorption cross section, the effective scattering cross section, the effective extinction cross section. - the summation of points of said combined image over a given field of the combined image comprising an image of said at least one particle; - the determination of at least one optical property of said at least one particle from said sum, said at least one optical property comprising at least one of the complex dipolar polarizability, the effective absorption cross section, the effective scattering cross section, the effective extinction cross section.
A method performed by at least one processor for analyzing and clustering botnets that share a same seed and Domain Generation Algorithms (DGAs) with embedded DGA representations, comprising: a) selecting, by a DGA classifier model, DGA-generated domain names from DNS records; b) representing said DGA-generated domain names as numerical feature vectors; c) learning embeddings of the selected domain names by training an autoencoder Neural Network (NN) with said selected domain names, wherein said autoencoder is a deep convolutional autoencoder that has a bi-directional Long-Term Short-Term embedding layer in the middle, and wherein all autoencoders of said Neural Network are configured with a same input and output layer; and d) performing cluster analysis on said DGA-generated domain names for obtaining DGA family analysis and determining whether a detected DGA is malicious or not, and for detecting active botnets that share a same seed by examining only the domain name, using said embeddings, wherein said method further comprises a step of: e) applying the model to a real-world dataset from an upper level DNS of said DNS records to detect previously unknown DGA families and distinguishing between different domains from a same DGA that were generated by a different seed. a) selecting, by a DGA classifier model, DGA-generated domain names from DNS records; b) representing said DGA-generated domain names as numerical feature vectors; c) learning embeddings of the selected domain names by training an autoencoder Neural Network (NN) with said selected domain names, wherein said autoencoder is a deep convolutional autoencoder that has a bi-directional Long-Term Short-Term embedding layer in the middle, and wherein all autoencoders of said Neural Network are configured with a same input and output layer; and d) performing cluster analysis on said DGA-generated domain names for obtaining DGA family analysis and determining whether a detected DGA is malicious or not, and for detecting active botnets that share a same seed by examining only the domain name, using said embeddings,
Hammer device , preferably hand-guided hammer device , comprising a striking mechanism which is designed to be able to act on a tool , preferably on a chisel , in a striking manner along the longitudinal axis (X), and comprising at least one striking force storage element which is designed to at least partly store a striking force (D) of the striking mechanism in the axial direction (A) along the longitudinal axis (X) and to deliver it, at least partly, back to the tool in the counter-axial direction (B) along the longitudinal axis (X) as a striking force (D') of the striking mechanism , characterized by a striking force deflection element which is designed and can be arranged in the flow of force between the striking mechanism and the striking force storage element so that the striking force (D) of the striking mechanism can be delivered, at least partly, for storage to the striking force storage element in the axial direction (A) along the longitudinal axis (X) by at least partly, preferably completely, circumventing the tool .
A positive active material for a nonaqueous electrolyte secondary battery, the positive active material containing a lithium-transition metal composite oxide, wherein the lithium-transition metal composite oxide has an α-NaFeO 2 -type crystal structure, and the following conditions are met: the lithium-transition metal composite oxide is represented by the general formula Li 1+α Me 1-α O 2 (0 < α, Me is a transition metal element containing Ni and Mn, or containing Ni, Mn, and Co, a molar ratio Mn/Me of Mn to Me meets Mn/Me ≥ 0.45), and the positive active material has a ratio a/b of 17 ≤ a/b ≤ 25 between a discharge capacity (a) from 4.35 V (vs. Li/Li + ) to 3.0 V (vs. Li/Li + ) and a discharge capacity (b) from 3.0 V (vs. Li/Li + ) to 2.0 V (vs. Li/Li + ) ; or the lithium-transition metal composite oxide is represented by the general formula Li 1+α Me 1-α O 2 (0 < α, Me is a transition metal element containing Ni and Mn, or containing Ni, Mn, and Co, a molar ratio Mn/Me of Mn to Me meets 0.3 ≤ Mn/Me < 0.55), and a ratio (I 490 /I 600 ) of a maximum value I 490 in a range of 450 cm -1 or more and 520 cm -1 or less to a maximum value I 600 in a range of 550 cm -1 or more and 650 cm -1 or less is 0.45 or more in a Raman spectrum. the lithium-transition metal composite oxide is represented by the general formula Li 1+α Me 1-α O 2 (0 < α, Me is a transition metal element containing Ni and Mn, or containing Ni, Mn, and Co, a molar ratio Mn/Me of Mn to Me meets Mn/Me ≥ 0.45), and the positive active material has a ratio a/b of 17 ≤ a/b ≤ 25 between a discharge capacity (a) from 4.35 V (vs. Li/Li + ) to 3.0 V (vs. Li/Li + ) and a discharge capacity (b) from 3.0 V (vs. Li/Li + ) to 2.0 V (vs. Li/Li + ) ; or the lithium-transition metal composite oxide is represented by the general formula Li 1+α Me 1-α O 2 (0 < α, Me is a transition metal element containing Ni and Mn, or containing Ni, Mn, and Co, a molar ratio Mn/Me of Mn to Me meets 0.3 ≤ Mn/Me < 0.55), and
A method comprising: providing a first executable environment, the first executable environment for execution within an operating system environment of a host computer system ; providing a software application in a form for installation and execution within the operating system environment absent the first executable environment; characterized in that the method comprises installing the software application within the first executable environment, the software application installed within a removable peripheral memory storage device for execution within the first executable environment which, during execution, interrogates the host computer system to determine its capabilities, both software and hardware; wherein an installation process for the software application interrogates the first executable environment and installs the software application within that environment, wherein the first executable environment intercepts application specific system library calls and translates the application specific system library calls into at least one of system library calls and instruction codes compatible with the operating system, such that the software application does not need modifications to install properly within the first executable environment, and wherein the first executable environment is designed for supporting a plurality of software applications for execution therein without modifications to the plurality of software applications from their form configured for installation and execution within the operation system environment, absent the first executable environment. providing a first executable environment, the first executable environment for execution within an operating system environment of a host computer system ; providing a software application in a form for installation and execution within the operating system environment absent the first executable environment; characterized in that the method comprises installing the software application within the first executable environment, the software application installed within a removable peripheral memory storage device for execution within the first executable environment which, during execution, interrogates the host computer system to determine its capabilities, both software and hardware; wherein an installation process for the software application interrogates the first executable environment and installs the software application within that environment, wherein the first executable environment intercepts application specific system library calls and translates the application specific system library calls into at least one of system library calls and instruction codes compatible with the operating system, such that the software application does not need modifications to install properly within the first executable environment, and wherein the first executable environment is designed for supporting a plurality of software applications for execution therein without modifications to the plurality of software applications from their form configured for installation and execution within the operation system environment, absent the first executable environment.
An image forming apparatus comprising: an image forming device configured to form an image on a recording medium (P), based on image forming conditions (Cd); an image position determination unit configured to determine a position of the image formed on the recording medium (P) by the image forming device , by generating correction data (Ps1) that is used to correct the positional deviation of the image based on detection signals (Dt) of a correction pattern formed on the recording medium (P) by the image forming device and reference position information (Ps2) of the correction pattern on the recording medium (P); and characterized by : a reference position determination unit configured to determine a reference position of the correction pattern formed on the recording medium (P) differently depending on the image forming conditions (Cd), wherein the image forming conditions (Cd) include at least one of resolution information of the image formed by the image forming device, and size information of the recording medium. an image forming device configured to form an image on a recording medium (P), based on image forming conditions (Cd); an image position determination unit configured to determine a position of the image formed on the recording medium (P) by the image forming device , by generating correction data (Ps1) that is used to correct the positional deviation of the image based on detection signals (Dt) of a correction pattern formed on the recording medium (P) by the image forming device and reference position information (Ps2) of the correction pattern on the recording medium (P); and characterized by : a reference position determination unit configured to determine a reference position of the correction pattern formed on the recording medium (P) differently depending on the image forming conditions (Cd), wherein the image forming conditions (Cd) include at least one of resolution information of the image formed by the image forming device, and size information of the recording medium.
A computer-implemented method for generating a digital model of an individual intraoral component from a digital model of a patient's dentition, the method comprising: obtaining (S110, S120) a 3-D digital polygon mesh model of the patient's dentition; performing (S130; S202, S204) automatic tooth component segmentation on the obtained polygon mesh model and displaying automated segmentation results; performing interactive tooth segmentation of the automated segmentation results by adding, by an operator instruction, one or more geometric primitives to aid interactive tooth segmentation on the displayed automated segmentation results, causing a further automated segmentation to be executed using the added geometric primitives and displaying the further automated segmentation result; wherein the interactive tooth segmentation is performed for further segmentation refinement to improve, correct and/or clean up observed errors and inconsistencies in the automated segmentation results; and displaying (S220) and storing the segmentation results after the refinement. obtaining (S110, S120) a 3-D digital polygon mesh model of the patient's dentition; performing (S130; S202, S204) automatic tooth component segmentation on the obtained polygon mesh model and displaying automated segmentation results; performing interactive tooth segmentation of the automated segmentation results by adding, by an operator instruction, one or more geometric primitives to aid interactive tooth segmentation on the displayed automated segmentation results, causing a further automated segmentation to be executed using the added geometric primitives and displaying the further automated segmentation result; wherein the interactive tooth segmentation is performed for further segmentation refinement to improve, correct and/or clean up observed errors and inconsistencies in the automated segmentation results; and displaying (S220) and storing the segmentation results after the refinement.