An optimization device includes a processor configured to generate a first DFG corresponding to a first loop and a second DFG corresponding to a second loop for a program in which an incomplete nested loop in which a first arithmetic operation result for each loop of the first loop is sequentially used in an arithmetic operation for each loop of the second loop of a second layer included in the first loop of a first layer is present, and arrange a first data transfer node between an output portion of the first arithmetic operation result in the first DFG and an input portion of the first arithmetic operation result in the second DFG, connect the first DFG and the second DFG by the first data transfer node, and generate a third DFG of the program.
A non-transitory recording medium storing a plurality of instructions which, when executed by one or more processors on an information processing apparatus, causes the one or more processors to perform a method including: acquiring setting information related to an application that processes electronic data generated by an electronic device; identifying a program to be executed to use the application based on the setting information; and acquiring the identified program.
An optical waveguide substrate includes a support layer, and an optical waveguide forming layer including a core portion forming layer. The optical waveguide forming layer includes a first optical waveguide and a second optical waveguide. Each of the first and the second optical waveguides includes a core portion including a first core portion and a second core portion and extending along a light transmission direction in the core portion forming layer, and a side cladding portion. The second core portion is disposed along both side surfaces of the first core portion. The side cladding portion is disposed on a side surface of the second core portion. A refractive index of the second core portion is smaller than that of the first core portion, and a refractive index of the side cladding portion is smaller than that of the second core portion.
A processing unit causes a quantum computer to execute a quantum circuit including a first-polarity first control gate and a second-polarity second control gate, each controlled by an auxiliary qubit. The first control gate applies a first time-evolution operator corresponding to a Hamiltonian H(λ) to a qubit group corresponding to a quantum state |ψ>. The second control gate applies a second time-evolution operator corresponding to H(λ+δλ) to the qubit group. The processing unit acquires, from the quantum computer, a probability amplitude corresponding to an event that a result of applying the two types of time-evolution operators to the quantum state |ψ> matches |ψ>. The processing unit acquires a cumulative distribution function for an energy level difference between H(λ) and H(λ+δλ) by executing discrete Fourier transform using the probability amplitude, and estimates the difference based on the cumulative distribution function.
An arithmetic circuit including: multiple processing elements arranged in a lattice; a first bus connecting a second processing element located downstream in a column-direction data flow to a first processing element; a second bus connecting a third processing element located downstream in a row-direction data flow to the first processing element; a third bus connecting a fourth processing element positioned upstream in the same row as the second processing element to the first processing element; and a fourth bus connecting a fifth processing element positioned downstream in the same row as the second processing element to the first processing element.
G06F 7/483 - Calculs avec des nombres représentés par une combinaison non linéaire de nombres codés, p. ex. nombres rationnels, système de numération logarithmique ou nombres à virgule flottante
A computer-implemented method comprising: generating, based on input network packet data, a target flow summary comprising information relating to packet flow between two addresses during a target time period; generating, based on the target flow summary, a target latent space representation; identifying k reference latent space representations most similar to the target latent space representation, wherein the plurality of reference latent space representations correspond to a plurality of reference flow summaries; generating, using a first LLM and based on the target flow summary, a target flow report in natural language format and generating, using the first LLM and based on k reference flow summaries, k reference flow reports in natural language format; generating, using a second LLM and based on the target flow report and the k reference flow reports with their corresponding classifications, a classification of the packet flow as malicious or benign.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
7.
INFORMATION PROCESSING PROGRAM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING DEVICE
The present invention makes it possible to appropriately predict a structural change of a substance. An information processing device (10) sets, in a latent space (3) corresponding to possible structures of a subject, second points (5a, 5b) on a path (4) connecting a plurality of first points (3a, 3b) respectively corresponding to a plurality of first structures (2a, 2b) of the subject. The information processing device (10) also sets third points (6a-6f) on partial paths (4a-4c) obtained by dividing the path (4) at the positions of the second points (5a, 5b). On the basis of information relating to the positions of the second points (5a, 5b) and the positions of the third points (6a-6f), the information processing device (10) calculates an objective function relating to whether or not structures (2c-2j) corresponding to the second points (5a, 5b) and the third points (6a-6f) are obtained in a deformation process of the subject from one of the first structures (2a, 2b) to the other. Then, the information processing device (10) moves the second points (5a, 5b) in a direction in which the objective function is optimized.
G06N 99/00 - Matière non prévue dans les autres groupes de la présente sous-classe
G16B 15/00 - TIC spécialement adaptées à l’analyse de structures moléculaires bidimensionnelles ou tridimensionnelles, p. ex. relations structurelles ou fonctionnelles ou alignement de structures
8.
INFORMATION PROCESSING PROGRAM AND INFORMATION PROCESSING DEVICE
The present invention: extracts a method contained in a source code of a Web application; generates an application programming interface (API) end point set candidate containing one or more API end points using the extracted method; if the API end point set candidate does not satisfy a generation condition, performs at least one of splitting of an API code and combining of API codes with respect to an API contained in the API end point set candidate, thereby generating an API end point set that satisfies the generation condition; and outputs the API end point set that satisfies the generation condition. Thus, a Web API that satisfies the generation condition can be generated.
An information processing device (100) obtains a first intermediate representation (z1') by applying a prescribed editing operation to an intermediate representation (z1) obtained when first input data (x1) is input into a trained model (110). The information processing device (100) generates second input data (x2) in the same format as the first input data (x1) on the basis of the obtained first intermediate representation (z1'). The information processing device (100) generates output data (y2) corresponding to the generated second input data (x2) by inputting the second input data (x2) into the trained model (110).
G16B 15/00 - TIC spécialement adaptées à l’analyse de structures moléculaires bidimensionnelles ou tridimensionnelles, p. ex. relations structurelles ou fonctionnelles ou alignement de structures
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
10.
UNDERSEA OBJECT TYPE-IDENTIFICATION METHOD AND UNDERSEA OBJECT TYPE-IDENTIFICATION PROGRAM
An undersea object type-identification device (100): acquires a plurality of images (Dn) to be annotated that have been captured to include undersea objects and identifies the image to be annotated that has the shortest imaging distance (dm) to the objects among the imaging distances of the plurality of images (Dn) to be annotated; selects a reference image (Ir) that has a shorter imaging distance than the imaging distance (dm) of the identified image to be annotated from a pre-stored data set of a plurality of reference images (Rn) that include undersea objects; and uses the selected reference image (Ir) to identify the types of objects included in the images (Dn) to be annotated and outputs an image annotation results group (An).
G06V 10/70 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique
A control apparatus includes a digital processing circuit and a digital-to-analog converter (DAC). The digital processing circuit generates a first control command group including a plurality of first control commands for controlling a plurality of first qubits, and a second control command group including a plurality of second control commands for controlling a plurality of second qubits, each of the second control commands having the same frequency as that of a corresponding one of the first control commands. In addition, the digital processing circuit performs frequency-multiplexing on third and fourth control command groups of different frequency bands by adding offsets to the first and second control command groups, to generate a digital multiplexed signal. The DAC performs digital-to-analog conversion on the digital multiplexed signal, to generate an analog multiplexed signal.
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
H04J 1/05 - Dispositions à transposition de fréquence utilisant les techniques numériques
12.
RECORDING MEDIUM, INFORMATION PROCESSING METHOD, AND INFORMATION PROSSING DEVICE
An information processing device calculates an excited state to be calculated based on a predetermined parameter value. The information processing device generates a candidate representing sets of mutually orthogonal states Sx(i) based on the calculated excited state. The information processing device calculates a set of energies for each state Sx(i) in each generated candidate. The information processing device assigns a rank for set of energies of calculated states Sx(i) in each candidate. The information processing device updates each state Sx(i) with one of the candidates based on the assigned rank. The information processing device changes the values of the predetermined parameter Pn so that the rank of the set of the energies of each updated state Sx(i) becomes higher in the coordinate system.
G16C 10/00 - Chimie théorique computationnelle, c.-à-d. TIC spécialement adaptées aux aspects théoriques de la chimie quantique, de la mécanique moléculaire, de la dynamique moléculaire ou similaires
13.
INFORMATION PROCESSING PROGRAM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING DEVICE
When a computer trains an autoencoder that outputs the three-dimensional density structure of a molecule by inputting, into a decoder, a latent variable obtained by inputting a particle image of the molecule into an encoder, and three-dimensional information obtained from a value found by correcting azimuth information of the particle image of the molecule via a trainable parameter, this information processing device optimizes a parameter of the encoder, a parameter of the decoder, and the trainable parameter so that a loss function of the autoencoder is minimized.
G16B 15/00 - TIC spécialement adaptées à l’analyse de structures moléculaires bidimensionnelles ou tridimensionnelles, p. ex. relations structurelles ou fonctionnelles ou alignement de structures
An optical device(100) includes a substrate(10), a cantilever(20) that extends in a first direction on the substrate(10), includes diamond having a color center(21), and has an end which is a fixed end and another end which is a free end, an optical waveguide(30) that includes a first portion and a second portion that interpose the color center(21) therebetween in a second direction intersecting the first direction, extend in the second direction and are away from the cantilever(20), the first portion andthe second portion including diamonds, and a pair of electrodes(40,41) provided so as to interpose a part of the cantilever(20) located closer to the another end than the color center(21) therebetween.
G02F 1/01 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de l'intensité, de la phase, de la polarisation ou de la couleur
G02B 26/02 - Dispositifs ou dispositions optiques pour la commande de la lumière utilisant des éléments optiques mobiles ou déformables pour commander l'intensité de la lumière
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
15.
INFORMATION PROCESSING PROGRAM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING DEVICE
An information processing device (100) generates first information (111) explaining content related to persona information (140) among items of question information (150). The information processing device (100) generates second information (121) explaining the meaning of the question information (150). On the basis of the first information (111) and the second information (121), the information processing device (100) generates third information (131) explaining an answer to a question corresponding to information (141) regarding each of one or more items. The information processing device (100) generates answer information (160) with respect to the question information (150) on the basis of the third information (131).
In an embodiment, a parameterized quantum circuit is initialized on a quantum computer for a Quantum Neural Network (QNN) with trainable parameters to learn a first conditional distribution of a training dataset. A marginal distribution is loaded on a first set of qubits and the first joint distribution on a second set of qubits. The QNN is operated on the marginal distribution to predict the first conditional distribution. The QNN is operated on the marginal distribution and first conditional distribution to generate a second conditional distribution for the input data and second output data. A second joint distribution is generated from the second conditional distribution and loaded onto a third set of qubits. Joint quantum measurements are extracted from the second and first joint distributions to train the QNN to learn the first conditional distribution.
An information processing apparatus acquires error data indicating an error of a first quantum gate. The information processing apparatus generates, using an approximation function that linearly approximates an influence of an additional quantum gate, which is to be added to the first quantum gate, on an operation of the first quantum gate, a linear equation which includes a variable corresponding to the additional quantum gate and indicates a relationship in which the error is canceled by the additional quantum gate. The information processing apparatus determines a second quantum gate corresponding to the additional quantum gate by solving the linear equation for the variable. The information processing apparatus determines a second quantum gate corresponding to the additional quantum gate by solving the linear equation for the variables.
A data array modification device modifies an array of data read from a memory to an array executable by a computational array including a plurality of computational elements arranged in a matrix, and includes an input data selector configured to select a data group including a predetermined number of first data to be input to the computational array in a single input, from among a plurality of data read from an area having consecutive addresses in the memory, and an array generator configured to generate data to be output to the computational array by inserting an interval between the predetermined number of first data of the data group selected by the input data selector and shifting the data group from a head position.
A non-transitory computer-readable recording medium has stored therein a program that causes a computer to execute a process including adding a shared parameter to parameters of a plurality of motion learning models that each predict a second state of a target from a first state of the target and a parameter of a language learning model that has been trained, the language learning model being related to a motion instruction for the target obtaining a training data set including a plurality of sets of training data each having the first state as input data and the second state as ground truth data and optimizing the shared parameter and a parameter of a motion learning model of the plurality of motion learning models, the motion learning model corresponding to the training data set, in a state where the parameter of the language learning model has been fixed.
A semiconductor device includes a barrier layer, a channel layer, an anode electrode making a Schottky contact with the channel layer, and a cathode electrode making an ohmic contact with the channel layer. The channel layer is located between the barrier layer and the anode electrode. The channel layer includes an n-type first region, an n-type second region located between the first region and the anode electrode and in contact with the first region and the anode electrode, and a p-type third region located between the first region and the anode electrode and in contact with the first region, the second region, and the anode electrode.
A processing unit converts a first learning image, which is for machine learning of a neural network configured to calculate authentication data for biometric authentication from an input biometric image, into first three-dimensional data by using a first conversion expression based on internal parameters of an imaging apparatus for capturing the biometric image; generates second three-dimensional data by varying a posture of a biological body part included in the first three-dimensional data; generates a second learning image by converting the second three-dimensional data by using a second conversion expression that performs inverse conversion of conversion performed by using the first conversion expression; and executes machine learning of the neural network by using at least the first learning image and the second learning image.
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/24 - Alignement, centrage, détection de l’orientation ou correction de l’image
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
A non-transitory computer-readable recording medium has stored therein a retrieval program that causes a computer to execute a process including dividing a set of structured documents related to external knowledge into a plurality of pieces of partial data for each predetermined unit generating a prompt including the pieces of partial data, designated input data, and an instruction to select the partial data relevant to the input data inputting the prompt to a large language model, thereby acquiring a selection result of the large language model and retrieving one piece of partial data from the pieces of partial data, based on the selection result, and outputting a retrieval result.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computers; computer servers; computer hardware for data
storage; computer peripheral devices; computer software;
microprocessors; digital signal processors; network servers;
communications servers [computer hardware]. Computer programming services; computer rental services;
server hosting; rental of web servers; optimization services
for computers, namely, computer networks and computer
software configuration; installation of computer software;
maintenance and upgrading of computer software, namely,
enhancing functions of computer software, changing or adding
functions of computer software, and providing information
thereon; software as a service [SaaS]; computer system
consulting and advisory services; providing temporary use of
non-downloadable cloud-based software; providing technical
information about computers, computer software and computer
networks; platform as a service [PaaS].
24.
Multi-Data Quantum Generative Network Learning and Inference
In an embodiment, a parameterized quantum circuit is initialized on a quantum computer for a Quantum Neural Network (QNN) with an ansatz architecture. Input data, which includes a quantum representation of a multi-dataset and an initial state of the QNN, and labels, is received. The quantum representation of the multi-datasets on the QNN is loaded and a first dataset of the multi-dataset is labelled. A label-controlled circuit associated with label-controlled input qubits of the ansatz architecture for the QNN is determined, based on the labelled first dataset. A universal circuit associated with the ansatz architecture for a prediction circuit associated with the QNN is determined, based on labelled first dataset. The prediction circuit is determined based on the label-controlled circuit and the universal circuit. The prediction circuit is trained and configured to generate predictions associated with the loaded fractionally weighted data portfolios.
Provided is an improvement proposal presentation method including estimating a dialogue stage for each dialogue of a plurality of dialogues included in a conversation based on the plurality of the dialogues and a first large language model, estimating a final dialogue stage among dialogue stages as a dropout stage of the conversation, and outputting an improvement proposal according to the dropout stage based on a dialogue content of the plurality of the dialogues, the dropout stage, and the first large language model.
G06Q 10/0637 - Gestion ou analyse stratégiques, p. ex. définition d’un objectif ou d’une cible pour une organisationPlanification des actions en fonction des objectifsAnalyse ou évaluation de l’efficacité des objectifs
26.
NON-TRANSITORY COMPUTER-READABLE RECORDING MEDIUM AND INFORMATION PROCESSING DEVICE
A non-transitory computer-readable recording medium has stored therein an inference program that causes a computer to execute a process including acquiring first image data captured in an environment that is different from an environment in pre-training of a machine learning model identifying a foreground area from the first image data generating composite image data based on the foreground area and second image data that is used in the pre-training of the machine learning model and acquiring an inference result by inputting the composite image data to the machine learning model.
A coefficient data generation device that executes calculation of a nonlinear function by a piecewise polynomial, the coefficient data generation device including a calculator configured to perform calculation of output values of respective segments of the nonlinear function based on an input value, and a generator configured to generate coefficient data used in the calculation of the nonlinear function based on the output values calculated by the calculator.
G06F 17/11 - Opérations mathématiques complexes pour la résolution d'équations
G06F 17/17 - Évaluation de fonctions par des procédés d'approximation, p. ex. par interpolation ou extrapolation, par lissage ou par le procédé des moindres carrés
28.
INFORMATION PROCESSING METHOD AND INFORMATION PROCESSING APPARATUS
An information processing apparatus performs, a plurality of times, an update process of updating a value of a first parameter, which is a variable included in a cost function applied to a variational quantum circuit used for variational quantum eigenvalue computation. The information processing apparatus determines a value of a second parameter representing a weight for an amount of change in the value of the first parameter in each update process, by adding a constant term and a variable term expressed using a ratio between the values of the cost function calculated through the variational quantum eigenvalue computation using the values of the first parameter obtained in the k-th and (k−1)-th update processes. The information processing apparatus performs the (k+1)-th update process using the amount of change weighted by the determined value of the second parameter.
An information processing apparatus acquires a coefficient matrix representing coefficients included in a linear system. The information processing apparatus generates a hypergraph including nodes corresponding to variables included in the linear system and edges corresponding to linear equations included in the linear system, each of the edges connecting nodes corresponding to positions of non-zero coefficients included in the coefficient matrix. The information processing apparatus transforms a plurality of first features associated with the plurality of nodes into a plurality of second features using a machine learning model including parameter values. The information processing apparatus computes a plurality of third features to be associated with the plurality of nodes, from the plurality of second features, based on the connection relationships between the nodes. The information processing apparatus updates the parameter value based on an error obtained from the plurality of third features.
An information processing device obtains a graph representing a structure of a molecule of interest, the graph including nodes representing respective atom groups of multiple atom groups and edges coupling different nodes. The information processing device refers to a basis function system, calculates, for each edge, an evaluation value representing the magnitude of interaction between atom groups represented by different nodes coupled by the edge, and sets the evaluation value as a weight for the edge. The information processing device divides the graph into portions by cutting edges so that a sum of the weights thereof is minimized and thereby divides the structure of the molecule of interest into fragments corresponding to the portions.
B.G. NEGEV TECHNOLOGIES AND APPLICATIONS LTD. (Israël)
Inventeur(s)
Otung, Andikan
Manor, Ofir
Schwartz, Tomer
Elovici, Yuval
Puzis, Rami
Abrégé
A computer implemented method for determining an origin of indication information in a networked connection between a client device and a server, comprising: receiving, at the server, the indication information of the client device, determining a client-server value based on a transmission time of a connection signal transmitted between the client device and the server, transmitting a tracing signal addressed to the indication information via a particular router in the networked connection between the client device and the server, determining a tracing value based on a transmission time of the tracing signal to the particular router, establishing whether the indication information originates from an intermediate connection in the networked connection or from the client device by comparing a difference value with a threshold value, the difference value being based on the client-server value and tracing value.
An information processing apparatus determines, based on target information regarding an imitation target, a first knowledge domain in which the imitation target has knowledge and a first knowledge level of the imitation target regarding the first knowledge domain. Upon receiving a first question, the information processing apparatus instructs an agent, which responds to a question by using a language model, to generate a response to the first question. In instructing the response, the information processing apparatus instructs a response generated by imitating thoughts of the imitation target that are referable to information restricted based on the first knowledge domain and the first knowledge level.
A machine learning device includes a processor that executes a procedure. The procedure including: specifying, among a plurality of points that are present within a predetermined distance from a first point in a latent space of an autoencoder, a second point that satisfies a predetermined relationship with the first point; and updating at least a parameter of a decoder of the autoencoder by optimization of an objective function including a regularization term to reduce a difference between the first point and the second point in the latent space.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
A quantum device includes a first substrate; and a second substrate arranged on a same plane as the first substrate; and a diamond chiplet placed across the first substrate and the second substrate. The diamond chiplet includes a first optical waveguide portion and a second optical waveguide portion, and a first holding portion configured to hold the first optical waveguide portion and the second optical waveguide portion. The first optical waveguide portion includes a first region extending in a first direction and including a first color center, a second region extending in the first direction, and a third region bridging the first region and the second region. The second optical waveguide portion includes a fourth region extending in the first direction and including a second color center, a fifth region extending in the first direction, and a sixth region bridging the fourth region and the fifth region. The third region and the sixth region face each other to constitute a beam splitter.
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
In this determination method, a computer executes processes for: executing a first determination as to whether or not a first patch is an algae region, such determination performed for each first patch obtained by dividing an image into patches of a first patch size; and executing a second determination as to whether or not a second patch is an algae region, the second patch being obtained by dividing the periphery of a first patch, which was determined to be an algae region in the image in the first determination, into patches of a second patch size which is smaller than the first patch size.
An amplifier includes a rat-race coupler, a first peak amplifier configured to perform class C amplification, a second peak amplifier configured to perform class C amplification with a phase inverted relative to the first peak amplifier, a carrier amplifier configured to perform AB class amplification, a 180-degree hybrid circuit configured to invert a phase of either a signal transmitted from a third terminal to a second terminal or a signal transmitted from a fourth terminal to the second terminal and to output signals from the second terminal in phase with each other, a first transmission line having a quarter wavelength and coupled between a fourth port of the rat-race coupler and the first peak amplifier, and a transmission line having the quarter wavelength and coupled between the first peak amplifier and a terminal of the carrier amplifier.
H03F 1/02 - Modifications des amplificateurs pour augmenter leur rendement, p. ex. étages classe A à pente glissante, utilisation d'une oscillation auxiliaire
H03F 3/60 - Amplificateurs dans lesquels les réseaux de couplage ont des constantes réparties, p. ex. comportant des résonateurs de guides d'ondes
37.
METHOD AND APPARATUS FOR DETERMINING CARDIAC MOTION FEATURE
An apparatus to determine a cardiac motion feature and a method thereof. The method includes: acquiring wireless signals reflected by multiple body parts via a wireless sensing device; filtering the acquired wireless signals using a single-band filter or a multi-band filter, to obtain filtered time domain signals; calculating signal quality evaluation values for evaluating signal quality of the filtered time domain signals; selecting candidate signals from the filtered time domain signals according to the signal quality evaluation values; and determining a cardiac motion feature based on the candidate signals. The method is easy to implement and easy to operate, which can not only guarantee accuracy of the obtained cardiac motion feature, but also has a strong anti-noise capability and high privacy protectiveness.
A61B 5/11 - Mesure du mouvement du corps entier ou de parties de celui-ci, p. ex. tremblement de la tête ou des mains ou mobilité d'un membre
A61B 5/00 - Mesure servant à établir un diagnostic Identification des individus
A61B 5/0507 - Détection, mesure ou enregistrement pour établir un diagnostic au moyen de courants électriques ou de champs magnétiquesMesure utilisant des micro-ondes ou des ondes radio utilisant des micro-ondes ou des ondes térahertz
38.
NON-TRANSITORY COMPUTER-READABLE RECORDING MEDIUM, CALCULATION METHOD AND INFORMATION PROCESSING DEVICE
A non-transitory computer-readable recording medium that stores a program causing a computer to execute a process, the process including, repeating a search process to find a solution for an optimization target, generate a plurality of solutions by varying the solution, and calculate an average value and a variance value of an objective function for the plurality of solutions, and outputting a combination satisfying a predetermined condition among combinations of the average value and the variance value obtained in each search process.
This information processing device executes first training for training a feature converter that converts a first feature amount used for prediction in a trained first machine learning model having a first number of parameters into a second feature amount, and a predictor of a second machine learning model that includes a feature generator and a predictor and has a second number of parameters smaller than the first number of parameters, the training being performed by using an output result obtained by inputting the second feature amount converted by the feature converter into the predictor. The information processing device executes second training for training the feature generator on the basis of the conversion result converted by the trained feature converter and a generation result generated by the feature generator of the second machine learning model.
A computer obtains a causal relationship including a plurality of explanatory variables and a response variable by performing causal discovery using a subset extracted from a data aggregate including a value of each of the explanatory variables and a value of the response variable on the basis of each of a plurality of conditions related to ranges of the values of the explanatory variables. The computer obtains a causal effect of any explanatory variable of the explanatory variables on the response variable on the basis of the causal relationship obtained on the basis of each of the conditions. The computer obtains a determination result of similarity in the causal effects obtained on the basis of the respective conditions, by determining the similarity. The computer obtains an identified range of the value of each of the explanatory variables in which the causal effects have a predetermined sign on the basis of the determination result of the similarity and outputs range information indicating the identified range.
A load distribution device includes a memory and a controller coupled to the memory. The controller is configured to execute a control process including: monitoring a processing load of each of a plurality of processing devices configured to execute processing of a plurality of sub-models included in a machine learning model, and executing, when a first processing device having a processing load equal to or more than a first threshold is detected, first control for allocating a first sub-model to a second processing device to which a second sub-model different from the first sub-model is allocated, based on allocation of the plurality of sub-models and the plurality of processing devices, the second processing device being different from the first processing device to which the first sub-model is allocated and having the processing load less than the first threshold.
An information processing apparatus divides a quantum circuit into subcircuits each assigned to one of a plurality of quantum processors. The information processing apparatus predicts, for each of the subcircuits, fidelity when the subcircuit is executed by the quantum processor assigned thereto. The information processing apparatus repeats the process of dividing the quantum circuit into the subcircuits by increasing the number of subcircuits and the process of predicting the fidelity until the fidelity satisfies a predetermined criterion. When the criterion is satisfied, the information processing apparatus instructs a quantum computer to execute each of the subcircuits by the quantum processor assigned thereto. The information processing apparatus calculates, by classical computation, a computation result of the quantum circuit based on execution results of the subcircuits.
Under a production environment, an autonomous management system detects a change in a parameter file. In response to detection of the change in the parameter file, the autonomous management system updates a parameter file included in a DB container according to the change, and writes the contents of the change into a parameter table provided in a database included in the DB container. Under a disaster recovery environment, an autonomous management system detects a change in a parameter table in a database included in a DB container. In response to detection of the change in the parameter table, the autonomous management system updates a parameter file according to the change.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
44.
RECORDING MEDIUM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING DEVICE
An information processing device executes a quantum circuit multiple times and classifies combinations of determination results of first conditional branches in a first portion of the quantum circuit into multiple groups, based on the similarity of the combinations of the determination results of a second conditional branch in the second portion. The information processing device generates first information indicating a method of allocating physical qubits to the first portion, and generates and associates with each group, second information indicating a method of allocating physical qubits to the second portion. After executing the first portion according to the generated first information, the information processing device controls an executing unit to execute the second portion according to any of the second information, according to the current combination of the determination results of the first conditional branch.
G06N 10/20 - Modèles d’informatique quantique, p. ex. circuits quantiques ou ordinateurs quantiques universels
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
45.
INFORMATION PROCESSING APPARATUS, COMPUTER-READABLE RECORDING MEDIUM, AND INFORMATION PROCESSING METHOD
An information processing apparatus includes, a memory, and a processor coupled to the memory and configured to convert a first sentence and a second sentence into vector values using a sentence embedding model, calculate a first similarity of the first sentence to the second sentence based on the vector value of the first sentence and the vector value of the second sentence, extract feature values of the first sentence and the second sentence, and calculate a second similarity by correcting the first similarity by weighting based on a difference between the feature values of the first sentence and the second sentence.
An information processing device includes a processor configured to estimate, based on observation history data including a parameter of a machine training model that is sampled based on a probability measure on a parameter space and an observation result that is estimated in a case of setting the parameter to the machine training model, an optimum parameter and a function of the parameter that derives the observation result set an optimization problem for minimizing a false identification probability of falsely identifying, as an optimal solution, another parameter other than the optimum parameter on the parameter space based on the estimated function and the optimum parameter and search for a parameter to be an optimal solution to the machine training model by applying a projection subgradient method to the optimization problem.
A non-transitory computer-readable recording medium stores therein a program that causes a computer to execute a process including acquiring causal information representing a causal relationship among a plurality of variables, information representing a particular objective variable out of the variables, and information representing an intervention variable to be set out of the variables, generating a particular function representing a relationship between the particular objective variable and the intervention variable, based on the causal information, deciding, based on an objective function including the particular function, a value of the intervention variable that improves a value of the objective function, and outputting the value of the intervention variable.
A non-transitory computer-readable recording medium has stored therein a control program that causes a computer to execute a process including determining a first parallel number of nodes to execute computation for structural information of a polymer, based on a number of atoms contained in the polymer submitting a job to a plurality of nodes, the job associating the structural information of the polymer with the first parallel number allowing a number of nodes corresponding to the first parallel number for the structural information of the polymer to execute computation for the structural information of the polymer and when a computation time of the computation for the Structural information of the polymer reaches a reference time or more, allowing the nodes that have performed the computation to update a parallel number for the polymer from the first parallel number to a second parallel number.
G16B 15/00 - TIC spécialement adaptées à l’analyse de structures moléculaires bidimensionnelles ou tridimensionnelles, p. ex. relations structurelles ou fonctionnelles ou alignement de structures
49.
QUANTUM CIRCUIT TRANSFORMATION METHOD AND INFORMATION PROCESSING APPARATUS
A quantum circuit includes a rotation gate representing a gate operation for an arbitrary rotation that rotates a state of a qubit to be operated about an axis different from the coordinate axes. An information processing apparatus transforms the rotation gate for the arbitrary rotation into a sub-circuit that performs a rotation gate operation in which a rotation about a Z-axis is insufficient by a predetermined angle relative to the arbitrary rotation. The information processing apparatus changes, in the quantum circuit, a gate operation of one or a plurality of quantum gates following the rotation gate, which acts on the qubit to be operated, to a gate operation that performs an additional rotation about the Z-axis by the predetermined angle.
G06N 10/20 - Modèles d’informatique quantique, p. ex. circuits quantiques ou ordinateurs quantiques universels
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
50.
ACCESS CONTROL DEVICE, ACCESS CONTROL SYSTEM, AND COMPUTER-READABLE RECORDING MEDIUM
An access control device includes, a memory that stores data associated with an NFT on a blockchain and stores disclosure destination information indicating a disclosure destination of the data in association with identification information of the NFT; and a processor coupled to the memory and the processor configured to, determine whether or not to disclose the data to a disclosure requester based on the disclosure destination information stored in the memory in a case where a disclosure request of the data is received from the disclosure requester, the disclosure request being based on an access destination of the data indicated by the NFT.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
51.
COMPUTER-READABLE RECORDING MEDIUM, MACHINE LEARNING METHOD, AND MACHINE LEARNING DEVICE
A non-transitory computer-readable recording medium has stored therein a machine learning program causing a computer to execute a process including, estimating a first intensity estimation value that indicates an intensity of a data change in data after change, performing a first update, by using an intensity adjustment learning device, on a learning device such that the data change of the intensity indicated by the first intensity estimation value is added to data before change, generating post-change data by adding the data change to the data before change by using the learning device that has been subjected to the first update, estimating a second intensity estimation value that indicates the intensity of the data change in the post-change data by using the intensity estimation AT, and, causing the intensity adjustment learning device to perform first learning such that the second intensity estimation value approaches the first intensity estimation value.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Cash registers; automated teller machines [ATM]; fire
alarms; gas alarms; anti-theft warning apparatus; electric
buzzers; laboratory apparatus and instruments; photographic
machines and apparatus; cinematographic machines and
apparatus; optical machines and apparatus; measuring or
testing machines and instruments; power distribution or
control machines and apparatus; batteries, electric; fuel
cells; electric or magnetic meters and testers; electric
wires and cables; telecommunication machines and apparatus;
radio machines and apparatus; radio beacon machines and
apparatus; computers; computer programs; computers; computer
peripheral devices; computer hardware; data processing
apparatus; tablet computers; electronic control apparatus;
industrial x-ray machines and apparatus, not for medical
use; magnetic object detectors; ultrasonic flaw detectors;
ultrasonic sensors; wearable computers; wearable video
display monitors; smartglasses; smart rings; personal
digital assistants in the shape of a watch; virtual reality
headsets; humanoid robots with artificial intelligence for
use in scientific research; humanoid robots with artificial
intelligence for educational support; game programs for home
video game machines; electronic circuits and CD-ROMs
recorded with programs for hand-held games with liquid
crystal displays; electronic circuits and CD-ROMs recorded
with automatic performance programs for electronic musical
instruments; phonograph records; downloadable music files;
recorded video discs, video tapes, and other recorded media;
downloadable image files, video files and movie files;
electronic publications, downloadable; computer software
using artificial intelligence [recorded]; computer programs
using artificial intelligence [recorded]; recorded or
downloadable computer software platforms using artificial
intelligence; image files, video files and movie files
relating to artificial intelligence, downloadable via the
internet. Computer-based information processing; computer-based data
processing; information processing using artificial
intelligence. Design of computers, electronic applied machines and
telecommunication apparatus, and consultancy relating to the
design thereof; designing of machines, apparatus,
instruments [including their parts] or systems composed of
such machines, apparatus and instruments; providing
information relating to computer design; design services
[excluding those relating to advertising]; computer software
design, computer programming, or maintenance of computer
software; providing information relating to computer
software design, computer programming, or maintenance of
computer software; design and development of computer
systems; maintenance of software for computer systems;
consultancy relating to software for computer systems;
monitoring of computer system operation by remote access;
configuration, installation, expansion, modification,
addition and other optimization of computer software, and
providing information relating thereto; design, programming,
configuration, installation, expansion, modification,
addition, maintenance and other optimization of computer
software, and providing information relating thereto;
consultancy relating to computer software design,
programming or maintenance; design and planning of
telecommunication network systems; maintenance of
telecommunication network systems being software;
consultancy relating to design and planning of
telecommunication network systems; consultancy relating to
maintenance of telecommunication network systems being
software; diagnosis or consulting relating to security
measures for telecommunication network systems; user
authentication services using technology for e-commerce
transactions; data encryption services; conversion
processing of electronic data for embedding or removing
digital watermarks using computers; fault diagnosis and
virus scanning of computer software; conversion of computer
programs and data, other than physical conversion;
duplication of computer programs; internet security
consultancy; computer security consultancy; data security
consultancy; design and development of computer systems and
consultancy relating thereto; maintenance of software for
computer systems and consultancy relating thereto;
consultancy relating to cloud computing; creating or
maintaining websites for others; providing search engines
for the internet; technological advice relating to
computers, automobiles and industrial machines; testing,
inspection or research of pharmaceuticals, chemicals,
cosmetics or foodstuffs, and consultancy and providing
information relating thereto; research on building
construction or city planning, and consultancy relating
thereto; consultancy relating to testing, data analysis or
measurement in the field of civil engineering and building
construction; testing, inspection or research on
agriculture, livestock breeding or fisheries, and
consultancy, guidance and providing information relating
thereto; testing or research on computers and computer
programs; testing or research on telecommunication machines
and apparatus and their peripherals; testing or research on
semiconductors; testing or research on semiconductor
manufacturing equipment and semiconductor measuring
instruments; testing or research on machines, apparatus and
instruments, or consultancy relating thereto; research in
the field of artificial intelligence technology; rental of
computers; providing computer programs on data networks;
electronic data storage; rental of web servers; server
hosting; providing virtual computer systems through cloud
computing; software as a service [SaaS]; platform as a
service [PaaS]; preparation of technical manuals relating to
computers and computer programs; preparation of technical
manuals for computer operation and use of computer programs;
hosting of digital content on the internet; technological
consultancy services for digital transformation; rental of
memory space for storage of electronic data of digital
images; hosting of digital content relating to artificial
intelligence on the internet; rental of memory space for
storage of electronic data of digital images relating to
artificial intelligence; design of artificial
intelligence-based products; technological consultancy in
the field of artificial intelligence; research in the field
of artificial intelligence technology; artificial
intelligence consultancy; development of computer platforms
using artificial intelligence; design and development of
computer software using artificial intelligence; maintenance
of computer software using artificial intelligence;
providing computer software platforms using artificial
intelligence as a service [PaaS]; development of computer
platforms using artificial intelligence; design, programming
or maintenance of computer platforms using artificial
intelligence; providing computer programs using artificial
intelligence on data networks; preparation of technical
manuals for computers and computer programs that utilize
artificial intelligence; creation or maintenance of websites
for information exchange in the field of artificial
intelligence; technological consultancy services for digital
transformation using artificial intelligence; providing
computer programs for information exchange in the field of
artificial intelligence on data networks; rental of memory
space on servers for websites for information exchange in
the field of artificial intelligence.
An imaging apparatus includes a conveying path inclined downward toward downstream in a medium conveying direction, a first imager to image a medium conveyed, a circuit board located below the conveying path, multiple electronic components mounted on the circuit board and having different heights, and a first shield located above the multiple electronic components to attenuate a radio wave generated by the first imager. The multiple electronic components include a first electronic component mounted on an upstream portion of the circuit board located below an upstream position in the medium conveying direction, and a second electronic component smaller in height than the first electronic component and mounted on a downstream portion of the circuit board located below a position downstream from the upstream position. The first shield is inclined downward from the first electronic component toward the second electronic component and covers an upper side of the multiple components.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Cash registers; automated banking machines; Fire alarms; gas alarms; anti-theft warning apparatus; laboratory apparatus and instruments; photographic machines and apparatus; cinematographic machines and apparatus; optical machines and apparatus; measuring or testing machines and instruments; power distribution or control machines and apparatus; batteries, electric; Electrochemical generators including fuel cells; electric or magnetic meters and testers; electric wires and cables; telecommunication machines and apparatus; radio machines and apparatus; radio beacon machines and apparatus; computers; computer programs; Electronic machines and apparatus, and parts therefor; industrial X-ray machines and apparatus, not for medical use; magnetic object detectors; ultrasonic flaw detectors; ultrasonic sensors; Wearable mobile information terminals; Wearable displays; smartglasses; smart rings; personal digital assistants in the shape of a watch; virtual reality headsets; humanoid robots with artificial intelligence for use in scientific research; humanoid robots with artificial intelligence for use in educational support; game programs for home video game machines; electronic circuits and CD-ROMs recorded with programs for hand-held games with liquid crystal displays; electronic circuits and CD-ROMs recorded with automatic performance programs for electronic musical instruments; phonograph records; Downloadable music files; Prerecorded video discs and video tapes, and other prerecorded recording media; Downloadable image files, video files and motion picture files; Publications (Electronic -), downloadable. (1) Advertising and publicity services; promoting the goods and services of others through the administration of sales and promotional incentive schemes involving trading stamps; advertising provided via the Internet and mobile phones, and advertising agency services; Providing advertising space on websites on the Internet and providing information relating thereto; website traffic optimisation; presentation of goods on communication media, for retail purposes; Advertising and marketing, and providing advice and information relating thereto; business management analysis or business consultancy; business management; marketing research or analysis; providing information concerning commercial sales; organizing and conducting trade fairs, events and exhibitions for commercial or advertising purposes; conducting virtual trade show exhibitions online; business consultancy services relating to data processing; providing consulting services in the area of global sustainable business solutions; business consultancy services for digital transformation; Business research, analysis, guidance and advisory services relating to new business ventures; Providing consumer information relating to artificial intelligence (AI)-related products and services for business support of others; Business guidance and advisory services in the field of pharmaceuticals; Providing information relating to the sale of pharmaceuticals; Business management and operation relating to information processing and information and communication networks; Business management and operation relating to the operation of information processing and information and communication networks; Advisory and assistance services relating to business management and operation; Business management consultancy relating to the implementation of information technology (IT); Analysis of customer trend information and providing information relating to the results of such analysis; Employment agency services for engineers specializing in the design, development or maintenance of computers and computer programs; employment agency services; auctioneering; import-export agency services; office functions, namely filing, in particular documents or magnetic tapes; document reproduction; computerized file management; Administrative processing of sales orders and purchase orders for mail-order sales for others; compilation of information into computer databases; Compilation and systemization of information into computer databases and editing of information in computer databases, and advisory services relating thereto; data search in computer files for others; providing business assistance to others in the operation of data processing apparatus namely, computers, typewriters, telex machines and other similar office machines; Providing information relating to the operation of computers, typewriters, telex machines or other office machines and equipment equivalent thereto; Office machines and equipment rental; providing commercial information and advice for consumers in the choice of products and services; providing information about newspaper articles being news clipping services; Mediation or intermediation of subscription contracts for telecommunications by telephone, mobile telephone or computer terminals; retail services or wholesale services for electrical machinery and apparatuses; retail services or wholesale services for printed matter; retail services or wholesale services for paper and stationery.
(2) Design of computers, electronic apparatus and telecommunication apparatus, and advisory services relating to such design; designing of machines, apparatus, instruments [including their parts] or systems composed of such machines, apparatus and instruments; Providing information relating to the design of computers; Designing, other than for advertising purposes; computer software design, computer programming, or maintenance of computer software; provision of information relating to computer programs; Computerized information processing; Computerized data processing; Design, development or maintenance of computer systems; Advisory services relating to computer systems; Remote monitoring of computer systems; Configuration, installation, expansion, modification, addition or other optimization of computers, and providing information relating thereto; Design, development, configuration, installation, expansion, modification, addition, maintenance or other optimization of computer programs, and providing information relating thereto; Advisory services relating to the design, development or maintenance of computer programs; Design, planning or maintenance of telecommunication network systems; Advisory services relating to the design, planning or maintenance of telecommunication network systems; Security assessment or consultancy relating to telecommunication network systems; Authentication of users in electronic commerce; data encryption services; Computerized conversion of electronic data for embedding or removing digital watermarks; Diagnosis of faults in computer programs and computer virus detection; Conversion of computer programs and computer data; Duplication of computer programs; internet security consultancy; computer security consultancy; data security consultancy; Design, development or maintenance of computer systems, and advisory services relating thereto; Consulting services in the field of cloud computing; creating or maintaining web sites for others; Providing search engines for the Internet; technological advice relating to computers, automobiles and industrial machines; Testing, inspection or research of pharmaceuticals, chemicals, cosmetics or foodstuffs, and advisory and information services relating thereto; Research relating to civil engineering, architecture or urban planning, and advisory services relating thereto; Advisory services relating to testing, data analysis or measurement in the fields of civil engineering, architecture and related fields; Testing, inspection or research relating to agriculture, livestock farming or fisheries, and advisory, guidance and information services relating thereto; Testing or research relating to computers and computer programs; Testing or research relating to telecommunication apparatus and peripheral equipment therefor; Testing or research relating to semiconductors; Testing or research relating to semiconductor manufacturing equipment and semiconductor measuring apparatus; Testing or research relating to machinery and apparatus, or advisory services relating thereto; research in the field of artificial intelligence technology; rental of computers; providing computer programs on data networks; Rental of storage space on computers; rental of web servers; server hosting; Cloud computing; software as a service [SaaS]; platform as a service [PaaS]; Preparation of manuals relating to computers and computer programs; Preparation of manuals for the operation of computers and the use of computer programs.
55.
QUANTUM DEVICE AND METHOD OF MANUFACTURING QUANTUM DEVICE
A quantum device includes a quantum chip including a substrate, a quantum bit, and an electrode electrically connected to the quantum bit, a mounter having a mounting surface on which a peripheral edge of the quantum chip is mounted, the mounter having a linear expansion coefficient different from that of the substrate, a conductor pin having a tip end in contact with the electrode, and a holder fixed to the mounter, holding the conductor pin, and having a linear expansion coefficient different from that of the substrate. The electrode has a shape having a longitudinal direction in a direction radially extending from a center of the substrate, and the quantum chip is mounted on the mounting surface by inserting a protrusion provided on one of the substrate and the mounting surface into a hole provided on another thereof, the hole having a longitudinal direction in a direction extending radially.
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
A processor includes a memory access controller that accesses a memory based on a memory access request, a storage that stores a plurality of limit values of an access bandwidth of the memory in association with a plurality of power consumption values of the memory, respectively, a power capping controller that acquires a limit value corresponding to a specified power consumption value from the storage and controls the memory access controller so that the access bandwidth is the acquired limit value or less, and an initial setting circuit that repeatedly accesses the memory during an initialization mode, monitors a power consumption value for a case where the access bandwidth is not limited and a plurality of the power consumption values when the limit value is gradually varied, and stores the plurality of limit values in the storage in association with the plurality of monitored power consumption values, respectively.
A machine learning method includes for each of a predetermined number of slices divided from point cloud data including a target of gait recognition, determining whether a corresponding slice includes a point out of a distribution that deviates from the distribution of the target, maintaining a point slice determined not to include the point out of the distribution, obtaining a filtered slice by filtering the corresponding slice determined to include the point out of the distribution to remove the point out of the distribution, and merging the point slice determined not to include the point out of the distribution and the filtered slice with each other to reconstitute the point cloud data and generate disentanglement data.
Provided is a medium conveying apparatus which is prevented from being used with a roller cover open. A medium conveying apparatus includes a housing, a loading tray provided to be attachable and detachable relative to the housing and be movable between a fixed position where the loading tray is fixed to the housing to place a medium and an inclined position inclined relative to the fixed position for mounting the loading tray to the housing, a roller to separate the medium, and a cover provided to be openable and closable relative to the housing and be swingable between a closed position where the cover covers the roller and forms part of a guide surface of a medium and an open position for attaching and detaching the roller. The loading tray includes a contact part to come into contact with the cover and push the cover toward the closed position when the loading tray is located at the inclined position or when the loading tray moves from the inclined position to the fixed position with the cover located at the open position.
B65H 1/26 - Supports ou magasins pour les piles dans lesquelles on prélève des articles avec supports auxiliaires pour faciliter l'introduction ou le remplacement de la pile
B65H 1/04 - Supports ou magasins pour les piles dans lesquelles on prélève des articles adaptés pour supporter les articles en position sensiblement horizontale, p. ex. pour les enlever en partant du haut de la pile
B65H 3/06 - Rouleaux ou séparateurs rotatifs analogues
B65H 3/68 - Guides ou lissoirs pour articles, p. ex. déplaçables pendant le travail fixes pendant le travail
B65H 5/38 - Guides ou lissoirs pour articles, p. ex. mobiles pendant le travail fixes pendant le travail
59.
SYSTEMS AND METHODS FOR GIBBS STATE GENERATION IN QUANTUM CIRCUITS
There is provided a computer-implemented hybrid variational method of training a parametrised quantum circuit configuration to perform Gibbs state generation of a parametrised Hamiltonian.
G06N 10/60 - Algorithmes quantiques, p. ex. fondés sur l'optimisation quantique ou les transformées quantiques de Fourier ou de Hadamard
G06N 10/20 - Modèles d’informatique quantique, p. ex. circuits quantiques ou ordinateurs quantiques universels
G06N 10/80 - Programmation quantique, p. ex. interfaces, langages ou boîtes à outils de développement logiciel pour la création ou la manipulation de programmes capables de fonctionner sur des ordinateurs quantiquesPlate-formes pour la simulation ou l’accès aux ordinateurs quantiques, p. ex. informatique quantique en nuage
G06N 7/01 - Modèles graphiques probabilistes, p. ex. réseaux probabilistes
60.
RECORDING MEDIUM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING DEVICE
A computer-readable recording medium stores therein an information processing program for causing a computer to execute a process, the process includes: obtaining a decomposition number of a Trotter decomposition approximating a quantum unitary corresponding to an Ising model; and setting a quantum circuit expressing a formula of the Trotter decomposition by one or more first partial circuits and a second partial circuit, the one or more first partial circuits being of a first count one less than the obtained decomposition number and each including an Rz gate that represents a rotation action about a Z-axis on a qubit, the second partial circuit being free of the Rz gate and coupled to a rear of the one or more first partial circuits.
An information processing apparatus acquires a message including a job name of a job in which a trouble has occurred and type information indicating a type of the trouble. The information processing apparatus determines an impact level of the trouble on a system executing the job, based on a combination of the job name and the type information. The information processing apparatus determines an attribute of information to be acquired, based on the determined impact level. Then, the information processing apparatus acquires, from first information relating to the job, second information having the determined attribute.
A processing unit groups a plurality of sequences to be aligned in a multiple sequence alignment problem into a plurality of groups, selects a representative sequence from each of the plurality of groups, and causes an Ising machine to perform a first alignment process among the representative sequences of the plurality of groups. The processing unit replaces the representative sequence before the first alignment process with the corresponding representative sequence obtained through the first alignment process in each of the plurality of groups, and causes the Ising machine to perform a second alignment process within each of the plurality of groups after the replacement of the representative sequences.
G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
G06F 7/08 - Tri, c.-à-d. rangement des supports d'enregistrement dans un ordre de succession numérique ou autre, selon la classification d'au moins certaines informations portées sur les supports
63.
COMPUTER-READABLE RECORDING MEDIUM HAVING STORED THEREIN INFORMATION PROCESSING PROGRAM, INFORMATION PROCESSING DEVICE, AND INFORMATION PROCESSING METHOD
A non-transitory computer-readable recording medium having stored therein an information processing program causing a computer to perform a process including: in classification processing on input graph structure data using a machine learning model, acquiring a contribution degree in the classification processing for each of a plurality of partial regions included in graph structure data; and determining an evaluation for the machine learning model based on similarity between the contribution degree and designation information for the partial region of the graph structure data.
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16B 15/00 - TIC spécialement adaptées à l’analyse de structures moléculaires bidimensionnelles ou tridimensionnelles, p. ex. relations structurelles ou fonctionnelles ou alignement de structures
09 - Appareils et instruments scientifiques et électriques
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Computers; computer programs; computer software; electronic machines and apparatus, and parts therefor; telecommunication machines and apparatus; measuring or testing machines and instruments; fire alarms; gas alarms; anti-theft warning apparatus; laboratory apparatus and instruments; photographic machines and apparatus; cinematographic machines and apparatus; optical machines and apparatus; power distribution or control machines and apparatus; batteries, electric; electric or magnetic meters and testers; electric wires and cables; radio machines and apparatus; personal digital assistants [PDAs]; game programs for home video game machines; electronic circuits and CD-ROMs recorded with programs for hand-held games with liquid crystal displays; electronic circuits and CD-ROMs recorded with automatic performance programs for electronic musical instruments; phonograph records; game programs for arcade video game machines; downloadable music files; prerecorded video discs and video tapes, and other prerecorded recording media; downloadable image files and video files; electronic publications, downloadable. (1) Design, creation, development or maintenance of computer software; providing information relating to computer software design; providing computer software; software as a service [SaaS]; upgrading and rental of computer software; platform as a service [PaaS]; computer software design, computer programming, or maintenance of computer software; advisory and information services relating to the design, development or maintenance of computer programs; design of computers, electronic apparatus and telecommunication apparatus, and advisory services relating to such design; designing of machines, apparatus, instruments [including their parts] or systems composed of such machines, apparatus and instruments; providing information relating to the design of computers; designing, other than for advertising purposes; computerized information processing; computerized data processing; design, development or maintenance of computer systems; advisory services relating to computer systems; remote monitoring of computer systems; configuration, installation, expansion, modification, addition or other optimization of computers, and providing information relating thereto; configuration, installation, expansion, modification, addition, maintenance or other optimization of computer programs, and providing information relating thereto; design, planning or maintenance of telecommunication network systems; advisory services relating to the design, planning or maintenance of telecommunication network systems; security assessment or consultancy relating to telecommunication network systems; authentication of users in electronic commerce; data encryption services; computerized conversion of electronic data for embedding or removing digital watermarks; diagnosis of faults in computer programs and computer virus detection; conversion of computer programs and computer data; duplication of computer programs; design, development or maintenance of computer systems, and advisory services relating thereto; consulting services in the field of cloud computing; creating or maintaining web sites for others; providing search engines for the Internet; technological advice relating to computers, automobiles and industrial machines; testing, inspection or research of pharmaceuticals, chemicals, cosmetics or foodstuffs, and advisory and information services relating thereto; research relating to civil engineering, architecture or urban planning, and advisory services relating thereto; advisory services relating to testing, data analysis or measurement in the fields of civil engineering, architecture and related fields; testing, inspection or research relating to agriculture, livestock farming or fisheries, and advisory, guidance and information services relating thereto; testing or research relating to computers and computer programs; testing or research relating to telecommunication apparatus and peripheral equipment therefor testing or research relating to semiconductors; testing or research relating to semiconductor manufacturing equipment and semiconductor measuring apparatus; testing or research relating to machinery and apparatus, or advisory services relating thereto; research in the field of artificial intelligence technology; rental of computers; providing computer programs on data networks; rental of storage space on computers; rental of web servers; server hosting; cloud computing; preparation of manuals relating to computers and computer programs; preparation of manuals for the operation of computers and the use of computer programs.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computers; computer programs; computer software; electronic machines and apparatus, and parts therefor; telecommunication machines and apparatus; measuring or testing machines and instruments; fire alarms; gas alarms; anti-theft warning apparatus; laboratory apparatus and instruments; photographic machines and apparatus; cinematographic machines and apparatus; optical machines and apparatus; power distribution or control machines and apparatus; electric batteries; electric or magnetic meters and testers; electric wires and cables; radio machines and apparatus; game programs for home video game machines; electronic circuits and CD-ROMs recorded with programs for hand-held games with liquid crystal displays; electronic circuits and CD-ROMs recorded with automatic performance programs for electronic musical instruments; phonograph records; game programs for arcade video game machines; downloadable music files; prerecorded video discs and video tapes, and other prerecorded recording media; downloadable image files and video files; downloadable electronic publications; personal digital assistants [PDAs] providing information relating to computer software design; providing computer software; software as a service (SaaS); upgrading and rental of computer software; platform as a service (PaaS); advisory and information services relating to the design, development or maintenance of computer programs; design of computers, electronic apparatus and telecommunication apparatus, and advisory services relating to such design; designing of machines, apparatus, instruments [including their parts] or systems composed of such machines, apparatus and instruments; providing information relating to the design of computers; designing, other than for advertising purposes; computerized information processing; computerized data processing; design, development or maintenance of computer systems; advisory services relating to computer systems; remote monitoring of computer systems; configuration, installation, expansion, modification, addition or other optimization of computers, and providing information relating thereto; configuration, installation, expansion, modification, addition, maintenance or other optimization of computer programs, and providing information relating thereto; design, planning or maintenance of telecommunication network systems; advisory services relating to the design, planning or maintenance of telecommunication network systems; security assessment or consultancy relating to telecommunication network systems; authentication of users in electronic commerce; data encryption services; computerized conversion of electronic data for embedding or removing digital watermarks; diagnosis of faults in computer programs and computer virus detection; conversion of computer programs and computer data; duplication of computer programs; design, development or maintenance of computer systems, and advisory services relating thereto; consulting services in the field of cloud computing; creating or maintaining websites for others; providing search engines for the Internet; technological advice relating to computers, automobiles and industrial machines; testing, inspection or research of pharmaceuticals, chemicals, cosmetics and foodstuffs, and advisory and information services relating thereto; research relating to civil engineering, architecture or urban planning, and advisory services relating thereto; advisory services relating to testing, data analysis or measurement in the fields of civil engineering, architecture and related fields; testing, inspection or research relating to agriculture, livestock farming or fisheries, and advisory, guidance and information services relating thereto; testing or research relating to computers and computer programs; testing or research relating to telecommunication apparatus and peripheral equipment therefor; testing or research relating to semiconductors; testing or research relating to semiconductor manufacturing equipment and semiconductor measuring apparatus; testing or research relating to machinery and apparatus, or advisory services relating thereto; research in the field of artificial intelligence technology; rental of computers; providing computer programs on data networks; rental of storage space on computers; rental of web servers; server hosting; cloud computing; preparation of manuals relating to computers and computer programs; preparation of manuals for the operation of computers and the use of computer programs; Design, creation, development or maintenance of computer software; computer software design, computer programming or maintenance of computer software
A Majorana quantum bit includes: a first topological insulator layer including a first edge; a first s-wave superconductor layer; and a first layer provided between the first edge and the first s-wave superconductor layer and which allows cooper pairs to enter the first edge from the first s-wave superconductor layer.
A processor chip having a plurality of processor cores, the processor chip including a phase-locked loop circuit configured to input a common oscillation value common to each of the plurality of processor cores, a first frequency change circuit configured to, in a first processor core of the plurality of processor cores, perform a given clock pulse skipping from the common oscillation value according to a first oscillation value set for the first processor core, and to operate the first processor core at the first oscillation value, and a second frequency change circuit configured to, in a second processor core of the plurality of processor cores, perform a given clock pulse skipping from the common oscillation value according to a second oscillation value set for the second processor core, and to operate the second processor core at the second oscillation value.
H03L 7/183 - Synthèse de fréquence indirecte, c.-à-d. production d'une fréquence désirée parmi un certain nombre de fréquences prédéterminées en utilisant une boucle verrouillée en fréquence ou en phase en utilisant un diviseur de fréquence ou un compteur dans la boucle une différence de temps étant utilisée pour verrouiller la boucle, le compteur entre des nombres fixes ou le diviseur de fréquence divisant par un nombre fixe
H03L 7/085 - Détails de la boucle verrouillée en phase concernant principalement l'agencement de détection de phase ou de fréquence, y compris le filtrage ou l'amplification de son signal de sortie
68.
RECORDING MEDIUM, INFORMATION PROCESSING METHOD, INFORMATION PROCESSING DEVICE
A computer-readable recording medium storing therein an information processing program for causing a computer to execute a process including: setting first and second functions, for a quantum circuit used when solving a combinatorial optimization problem and including, for each layer, a first partial circuit representing an action of a mixer unitary operator and a second partial circuit representing an action of a cost unitary operator, the first function representing a first variational parameter of the first partial circuit, the second function representing a second variational parameter of the second partial circuit; and calculating a solution to the combinatorial optimization problem by updating a value of a first transformation parameter related to the first function and a value of a second transformation parameter related to the second function so as to optimize an expected value of a cost function corresponding to the combinatorial optimization problem by using the quantum circuit after setting the first function and the second function.
G06N 5/01 - Techniques de recherche dynamiqueHeuristiquesArbres dynamiquesSéparation et évaluation
69.
NON-TRANSITORY COMPUTER-READABLE RECORDING MEDIUM, INFORMATION PROCESSING METHOD, INFORMATION PROCESSING DEVICE, DETECTION METHOD, AND DETECTION DEVICE
B. G. NEGEV TECHNOLOGIES AND APPLICATIONS LTD., at Ben-Gurion University (Israël)
Inventeur(s)
Shams, Jacob
Nassi, Ben
Koda, Satoru
Shabtai, Asaf
Elovici, Yuval
Abrégé
A non-transitory computer-readable medium stores an information processing program that causes a computer to detect bounding boxes of an object in multiple frames captured by a camera installed at a fixed location. The program determines reliability for each detected bounding box and generates a heat map representing average reliability at each coordinate within the camera's field of view. By aggregating reliability values across frames, the system produces a spatial representation useful for analyzing detection performance within the monitored area.
G06V 20/70 - Étiquetage du contenu de scène, p. ex. en tirant des représentations syntaxiques ou sémantiques
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 20/52 - Activités de surveillance ou de suivi, p. ex. pour la reconnaissance d’objets suspects
G06V 40/10 - Corps d’êtres humains ou d’animaux, p. ex. occupants de véhicules automobiles ou piétonsParties du corps, p. ex. mains
70.
MEDIUM FEED APPARATUS TO ADVANCE SUCCEEDING SHEET OF MEDIUM WHEN PRECEDING SHEET OF MEDIUM PASSES PICK ROLLER
A medium feed apparatus includes a stacking tray, a pick roller located at an upstream side from a feed roller and separation roller in the medium conveyance direction, a first sensor located at an upstream side from the pick roller in the medium conveyance direction, a second sensor located at a downstream side from the feed roller and the separation roller in the medium conveyance direction, and a processor to rotate the pick roller and the feed roller in a medium feed direction to feed a plurality of sheets of the medium stacked on the stacking. The processor stops the pick roller when the second sensor detects a front end of a preceding sheet of the medium and rotates the pick roller again to advance a succeeding sheet of the medium when the first sensor detects a back end of the preceding sheet of the medium.
B65H 7/12 - Commande de l'alimentation en articles, de l'enlèvement des articles, de l'avance des piles ou d'appareils associés permettant de tenir compte d'une alimentation incorrecte, de la non présence d'articles ou de la présence d'articles défectueux par palpeurs ou détecteurs sensibles à la présence d'articles défectueux ou à l'enlèvement ou à une alimentation incorrecte sensibles à une alimentation ou enlèvement en double
B65H 3/06 - Rouleaux ou séparateurs rotatifs analogues
B65H 3/52 - Dispositifs de retenue à friction agissant sur les côtés inférieur ou arrière des articles à enlever
B65H 7/06 - Commande de l'alimentation en articles, de l'enlèvement des articles, de l'avance des piles ou d'appareils associés permettant de tenir compte d'une alimentation incorrecte, de la non présence d'articles ou de la présence d'articles défectueux par palpeurs ou détecteurs sensibles à la présence d'articles défectueux ou à l'enlèvement ou à une alimentation incorrecte
B65H 7/18 - Modification ou arrêt de la manœuvre des séparateurs
An information processing device according to the present invention displays, in a first region of a display unit, information defining a legal procedure required for introducing an AI system to be introduced into a market to which a law defining regulations and legal requirements regarding AI is applied, on the basis of a compliance result indicating whether or not the AI system satisfies each of a plurality of legal requirements of the applied law. The information processing device acquires a request that is detected by an agent which generates information in response to input information and that relates to a legal requirement or a legal procedure in audit trail work for a regulatory authority. The information processing device causes the agent which has received an input of the request to generate response information in response to the request, the response information being an explanation related to audit trail work for the regulatory authority, displays the response information in a second region of the display unit, and, after the information and the response information have been displayed on the display unit, registers an audit trail for the regulatory authority.
A processing unit acquires the data of first and second classical shadows corresponding to first and second quantum data represented by qubits, and geometric structure information indicating the geometric structure of a space including lattice points associated with the qubits. The first and second classical shadows include first and second data elements, respectively, corresponding to the qubits. The processing unit sets local subspaces each including a set of local lattice points in the space, based on the geometric structure information. The processing unit calculates, for each local subspace, a value of a first kernel function based on first and second data elements of the first and second classical shadows corresponding to the lattice points of that local subspace, and calculates a value of a second kernel function corresponding to the first and second classical shadows, based on the values of the first kernel function corresponding to the local subspaces.
G06N 10/60 - Algorithmes quantiques, p. ex. fondés sur l'optimisation quantique ou les transformées quantiques de Fourier ou de Hadamard
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
73.
METHOD OF MANUFACTURING JOSEPHSON JUNCTION ELEMENT AND JOSEPHSON JUNCTION ELEMENT
A method of manufacturing a Josephson junction element includes forming a lower electrode on a substrate by using a superconducting material, depositing a first insulating film on the substrate to cover the lower electrode, depositing a superconducting film on the first insulating film, and forming an upper electrode by etching the superconducting film, the upper electrode covering an entire lower electrode in plan view and having an outer peripheral edge located outside an outer peripheral edge of the lower electrode.
A non-transitory computer-readable recording medium stores therein a program that causes a computer to execute a process including calculating, for a machine learning model having a plurality of mechanisms that each of the mechanisms generate attention information, cosine similarity of the attention information generated by each of the mechanisms, calculating an entropy of an aggregate of the attention information generated by the mechanisms, and training the machine learning model by minimizing the cosine similarity and maximizing the entropy.
A non-transitory computer-readable recording medium that stores a program causing a computer to execute a process, the process including, when converting an analysis target into an evaluation function and searching for a solution, generating a plurality of evaluation functions by reflecting variations in at least any element of the evaluation function, generating an objective function by combining the plurality of evaluation functions, and searching for a solution in the objective function.
A computer is configured to acquire first region information indicating a region of an object in an input image, the first region information being output from a first object detection model used by a first object detection device, acquire an attribute of the object, cause the first object detection device to output output data including second region information obtained by changing the first region information by a predetermined amount for a trigger object having the attribute satisfying a condition defined as a trigger, and makes it difficult for a cloner to notice and suppressing a loss of functionality in object detection.
G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
G06T 3/40 - Changement d'échelle d’images complètes ou de parties d’image, p. ex. agrandissement ou rétrécissement
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
A method may include obtaining a configuration of a quantum circuit comprising n qubits and k quantum gates. The k quantum gates include at least a single-qubit gate or a two-qubit control gate. The method may include constructing a neural network representing the quantum circuit, wherein the neural network includes k+1 layers that include k pairs of adjacent layers, with each pair of the adjacent layers corresponding to one of the k quantum gates. The method may include connecting one or more nodes in each pair of the adjacent layers based on a representation of a corresponding quantum gate of the k quantum gates. The method may include training the neural network using machine learning techniques to obtain an output. The method may include applying the output to the quantum circuit.
An information processing apparatus includes a control unit. The control unit acquires target analysis information indicating physical and chemical analysis results corresponding to an inspection target by inputting an inspection image from a nondestructive inspection on the inspection target to a first machine learning model trained by machine learning using a first data set of training data that associates an inspection image from a nondestructive inspection on first food with first analysis information indicating physical and chemical analysis results for the first food. The control unit infers sensory evaluation results corresponding to the inspection target by inputting the acquired target analysis information to a second machine learning model trained by machine learning using a second data set of training data that associates second analysis information indicating physical and chemical analysis results for second food with sensory evaluation results for the second food.
G06Q 50/26 - Services gouvernementaux ou services publics
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
Provided in the embodiments of the present application is a method for determining power control parameters, which is applied to a terminal device. The method comprises: before applying a transmission configuration indicator state (TCI state), transmitting a physical uplink shared channel (PUSCH) on a non-subband full duplex (SBFD) symbol and/or SBFD symbol; and on the basis of at least one of a first parameter preambleReceivedTargetPower, a second parameter msg3-DeltaPreamble and a third parameter deltaPreamble, determining a target receiving power for the PUSCH transmitted on the non-SBFD symbol, and on the basis of at least one of a fourth parameter preambleReceivedTargetPower-SBFD, a fifth parameter msg3-DeltaPreamble-SBFD and a sixth parameter deltaPreamble-SBFD, determining a target receiving power for the PUSCH transmitted on the SBFD symbol; and/or, on the basis of a seventh parameter msg3-Alpha, determining a path loss compensation factor for the PUSCH transmitted on the non-SBFD symbol, and on the basis of an eighth parameter msg3-Alpha-SBFD, determining a path loss compensation factor for the PUSCH transmitted on the SBFD symbol.
A non-transitory computer-readable recording medium stores therein an output program that causes a computer to execute a process including receiving information related to a policy, identifying a policy model by using the received information related to the policy, the policy model being composed of a plurality of components defining a detail related to the policy in a hierarchical structure, generating a policy model in which one or more components corresponding to the information related to the policy among the components of the identified policy model are changed, and , outputting the generated policy model.
There is provided a non-transitory computer-readable medium storing a calculation program for causing a computer to execute a process. The process includes, training a model by using a loss term corresponding to a degree of continuity or discreteness of a variable to be optimized as a cost function in a search process that incorporates continuous relaxation into a discrete optimization problem, and changing the loss term as the search process progresses.
This information processing device, when allocating a sample to each of a plurality of processors and processing the plurality of samples in the training stage of a machine learning model, calculates a calculation cost, in which the time required for processing is estimated, for each of the plurality of samples. The information processing device allocates the plurality of samples to the plurality of processors on the basis of the calculation costs such that the difference between the total values of the calculation costs of the samples allocated to the respective processors falls below a threshold value.
A computer-readable recording medium stores therein a training program that causes a computer to execute a process including first inputting a first image capturing a target compound to an encoder of an auto-encoder including a latent space that is isometric with respect to an input space, second inputting a latent variable output by the encoder and a typical compound model corresponding to a typical case of a three-dimensional structure of the target compound to a decoder of the auto-encoder, and updating parameters of the encoder and the decoder, based on a reconfiguration error between a second image reconfigured based on an output of the encoder and the first image.
In an embodiment, a set of hash functions and a set of data streams to be hashed may be received. Each of a first hash function and a second hash function may be selected from the received set of hash functions by using a hash selector in an encoder system. The first hash function is applied on a first set of data streams to generate a first hashed data stream. The second hash function is applied on a second set of data streams to generate a second hashed data stream. An encoded data stream associated with the set of data streams is generated. The generated encoded data stream is transmitted to a decoder system associated with the encoder system, wherein the decoder system is configured to determine the set of data streams from the transmitted encoded data streams, based on both the first hash function and the second hash function.
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
According to an aspect of an embodiment, a method may include obtaining a tabular dataset. The tabular dataset may be converted into a first dataset having a first data type using a first converter. The tabular dataset may be converted into a second dataset having a second data type using a second converter. The method may further include generating, using a first encoder, a first set of embeddings in a first dimensional space based on the first dataset and generating, using a second encoder, a second set of embeddings in a second dimensional space based on the second dataset. The method may further include training one or both of the first encoder and the second encoder based on the first set of embeddings and the second set of embeddings.
A quantum device includes a quantum bit having a Josephson junction element; a signal source connected to the quantum bit; and a resistive element connected between a signal path between the signal source and the quantum bit, and a ground line.
The present invention evaluates the reliability of the response of a machine learning model to a prompt. An information processing device (10) inputs, to a machine learning model (13), a prompt (14) including first instructions that dictate the output of information related to first information and second instructions that dictate the output of the first information, acquires second information which was outputted from the machine learning model (13) in response to the second instructions, calculates the similarity between the first information and the second information, and determines a storage condition of the first information in the machine learning model (13) on the basis of the similarity.
This spatiotemporal inference device is configured to: convert spatiotemporal information that includes the position of an object in a real space at each time, said object being detected from an image of each frame of a video, into log data in a table format; and execute spatiotemporal inference on the video on the basis of the log data and a question in a natural language sentence.
G06V 10/62 - Extraction de caractéristiques d’images ou de vidéos relative à une dimension temporelle, p. ex. extraction de caractéristiques axées sur le tempsSuivi de modèle
89.
INFORMATION PROCESSING PROGRAM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING DEVICE
This information processing device acquires a video including a person to be detected. The information processing device acquires object information that is outputted by a predetermined video analysis technique, the attribute information and behavior information of a person being associated with the person included in the video. The information processing device generates work assistance information for the person on the basis of the object information. The information processing device verifies the influence on the person when the person has changed an action on the basis of the generated work assistance information. The information processing device outputs the work assistance information when the verification result satisfies a prescribed condition.
The present invention improves the accuracy of fake detection. A processing unit (12) acquires an image pair from among a plurality of images. The processing unit (12) generates a composite image (40) by replacing low frequency components (21a) that correspond to frequencies lower than a first frequency and that are among the frequency components contained in a first partial image (21), which is a portion of a first image (20) belonging to the pair, with low frequency components of a second partial image (31) that is included in a second image (30) belonging to the pair and that corresponds to the first partial image (21). The processing unit (12) assigns, to the composite image (40), a label that is based on a first label indicating whether or not the first image (20) is a fake and a second label indicating whether or not the second image (30) is a fake. By machine learning using a composite image generated for each pair acquired from among the plurality of images and the label for the composite image, the processing unit (12) generates a machine learning model that outputs an indicator indicating the likelihood that a third image is a fake upon input of the third image.
5 A computer-implemented method of training a filter for large language model, LLM, outputs, the method comprising: accepting input of a plurality of training prompts, the plurality of training prompts comprising labels identifying each prompt as a safe prompt or an unsafe prompt; for each training prompt, obtaining a plurality of LLM parameter gradients by passing the training prompt through an LLM selecting a subset of the plurality of LLM 0 parameter gradients, and quantizing the subset to obtain quantized gradient information; and training a classifier using the quantized gradient information and the training prompt labels, the trained classifier being configured to act as the filter for LLM outputs and classify prompts as safe or unsafe.
A computer-implemented method comprising: generating, based on log data, a first knowledge hypergraph; extracting from the log data information related to a set of keywords and generating, based on the extracted information, a set of second knowledge hypergraphs; generating a combined hypergraph; extracting, from among nodes of the combined hypergraph, query-specific seed nodes based on similarity between the nodes of the combined hypergraph and named entities in a received query; detecting communities in the combined hypergraph and computing a community weight for each community; and ranking hyperedges in the combined hypergraph, wherein the ranking of each hyperedge is based on weights of the nodes which the hyperedge connects, and using a first LLM to generate, based on the query and the ranked hyperedges, an answer to the query.
A method may include discretizing a partial differential equation with an initial value condition to obtain a linear equation. The method may also include scaling at least one discretization parameter of the linear equation to obtain a scaled linear equation. The method may include applying a quantum algorithm to the scaled linear equation to obtain a linear system with a preconditioned matrix. The method may further include performing a quantum singular value transformation to apply an inverse of the preconditioned matrix to obtain a solution. The method may include extracting an integral probability from the solution using an integral interpolation.
G06N 10/20 - Modèles d’informatique quantique, p. ex. circuits quantiques ou ordinateurs quantiques universels
94.
COMPUTER-READABLE RECORDING MEDIUM HAVING STORED THEREIN DATA SELECTION PROGRAM, INFORMATION PROCESSING APPARATUS, AND COMPUTER-IMPLEMENTED DATA SELECTION METHOD
A non-transitory computer-readable recording medium having stored therein a data selection program that causes a computer to execute a process including determining, for each of a plurality of pieces of graph structure data, a weight in data selection based on the number of adjacent nodes shared by two nodes for a set of the two nodes included in the graph structure data, and selecting training data to be used for training a neural network that predicts a presence or absence of a link between nodes included in the graph structure data input as input data from among the plurality of pieces of graph structure data based on the determined weight and information indicating a presence or absence of a link between nodes for each of one or more sets of two nodes.
An information processing apparatus includes circuitry to receive a selection of an integration destination for imaging data from among a plurality of integration destination candidates, using settings information that includes imaging settings and an integration destination setting, determine whether a usage frequency of the integration destination meets a predetermined condition, create additional settings information that includes the integration destination specified in the integration destination setting when a usage frequency of the integration destination meets a predetermined condition, and display, on a display, the additional settings information as available.
An information processing device (100) acquires first structure information representing the structure of each sentence of a plurality of sentences. The information processing device (100) generates a first prompt (120) that is to be input into a first language model (110) and that requests aggregation of two or more sentences having same or similar structures among the plurality of sentences. The first prompt (120) includes each sentence and the acquired first structure information representing the structure of the sentence, in association with each other. This enables the information processing device (100) to generate an appropriate first prompt (120) that makes it easier for the first language model (110) to aggregate the plurality of sentences as intended by the user. The information processing device (100) can, for example, make it easier to aggregate a plurality of sentences based on a contract. Therefore, the information processing device (100) can be used, for example, to make it easier for users to understand contract contents, thus preventing contract violations.
The present invention improves the accuracy of distance measurement. A housing (20) incorporates an irradiation unit (21) that emits a laser beam, a mirror (22) configured such that the angle at which the mirror reflects the laser beam can be changed, and a light-receiving unit (23) that receives a laser beam. A processing unit (12) acquires a first round-trip time of the laser beam emitted from the irradiation unit (21) to an object (30) via the mirror (22) and received by the light-receiving unit (23), and a first angle of rotation of the mirror (22). On the basis of in-housing flight time information (11a) that specifies the in-housing flight time of the laser beam for each angle of rotation of the mirror (22), the processing unit (12) performs correction for subtracting a first in-housing flight time corresponding to the first angle from the first round-trip time.
An information processing apparatus generates error patterns each indicating one or more first data qubits to which errors are introduced among a plurality of data qubits in a two-dimensional lattice where the data qubits and a plurality of ancilla qubits are alternately arranged in each of a row and a column direction; determines whether the first data qubits indicated by the error patterns satisfy a predetermined determination criterion; determines, when the criterion is satisfied, that a logical error does not occur in the error patterns; and determines, when the criterion is not satisfied, whether the logical error occurs based on error detection information where ancilla qubits adjacent, in the row or column direction, to the first data qubits indicated in the error patterns have flipped states.
G06N 10/70 - Correction, détection ou prévention d’erreur quantique, p. ex. codes de surface ou distillation d’état magique
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
G06N 10/80 - Programmation quantique, p. ex. interfaces, langages ou boîtes à outils de développement logiciel pour la création ou la manipulation de programmes capables de fonctionner sur des ordinateurs quantiquesPlate-formes pour la simulation ou l’accès aux ordinateurs quantiques, p. ex. informatique quantique en nuage
99.
MEMORY CIRCUIT AND INFORMATION PROCESSING APPARATUS
A memory circuit including a word line driver configured to set a potential of a word line signal input to a selected memory cell to a second value lower than a first value by a certain amount until a stable operation of the memory cell is ensured, a timing adjustment circuit configured to determine a time at which the potential of the word line signal is set to the second value, and a pull-up circuit configured to boost the potential of the word line signal from the second value to the first value according to the determined time.
An information processing device generates a first data group that is before transformation at an a-th diffusion stage. The information processing device obtains a third data group that is generated by a second quantum circuit according to a second data group that is before transformation at a b-th reverse diffusion stage. The information processing device trains the first quantum circuit to discriminate the first data group as true and to discriminate the third data group as false. The information processing device trains the second quantum circuit so that the trained first quantum circuit discriminates the third data group as true. The information processing device sets the trained second quantum circuit as a variational quantum circuit expressing an operation of the b-th reverse diffusion stage.
