A group migration apparatus, configured in a source donor device, includes a first receiver configured to receive a measurement report transmitted by a migrating IAB (integrated access and backhaul) node, a first transmitter configured to transmit a first migration request message to a target donor device, the first migration request message including context information on the migrating IAB node and its served child IAB-node or UE (user equipment), a second receiver configured to receive a first response message transmitted by the target donor device, the first response message including an RRC (radio resource control) reconfiguration message for the migrating IAB node and its served child IAB-node or UE, and a second transmitter configured to transmit the RRC reconfiguration message to the migrating IAB node and its served child IAB-node or UE.
An image processing device includes: a memory; and a processor coupled to the memory and configured to: determine whether or not overflow occurs in a virtual buffer when image data of each frame of moving image data is encoded; refer to recognition object information in a case where it is determined that the overflow occurs; and change a quantization value of a block at a position that corresponds to an area of an object to be recognized other than an object to be recognized specified by the recognition object information among objects to be recognized included in the image data to a quantization value higher than a quantization value that corresponds to a limit compression ratio.
H04N 19/176 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c. à d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une zone de l'image, p.ex. un objet la zone étant un bloc, p.ex. un macrobloc
H04N 19/136 - Caractéristiques ou propriétés du signal vidéo entrant
G06V 10/77 - Dispositions 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
H04N 19/152 - Débit ou quantité de données codées à la sortie du codeur par mesure de l’état de remplissage de la mémoire tampon de transmission
3.
COMPUTER-READABLE RECORDING MEDIUM HAVING STORED THEREIN PROGRAM FOR GENERATING MODEL, INFORMATION PROCESSING APPARATUS, AND METHOD FOR GENERATING MODEL
A computer-readable recording medium has stored therein a program for causing a computer to execute a process including: generating a voice processing model by executing machine learning using training data, the training data associating first training voice data obtained with a first microphone, second training voice data obtained with a second microphone different from the first microphone, and clarified training voice data with one another, the clarified training voice data being obtained by a clarifying process on voice contained at least one of the first training voice data and the second training voice data, the voice processing model generating clarified voice data in response to input of first inference voice data and second inference voice data.
G10L 21/057 - Compression ou expansion temporelles pour améliorer l'intelligibilité
G10L 21/0308 - Séparation du signal de voix caractérisée par le type de mesure du paramètre, p.ex. techniques de corrélation, techniques de passage par zéro ou techniques prédictives
4.
COMPUTER-READABLE RECORDING MEDIUM STORING SEARCH PROGRAM, SEARCH APPARATUS, AND METHOD OF SEARCHING
A non-transitory computer-readable recording medium storing a search program for causing a computer to execute processing including: obtaining a first cost value of a first potential that corresponds to interaction between coarse-grained particles, a second cost value of a second potential that corresponds to an angle and a dihedral angle between the particles, and a third cost value of a third potential that corresponds to repulsion and attraction between the particles; and instructing an Ising apparatus to search for a structure of a coarse-grained model with which a total sum of the first cost value, the second cost value, and the third cost value calculated for an entirety of the coarse-grained model that includes a plurality of particles satisfies a predetermined condition.
G16C 20/40 - Recherche de structures chimiques ou de données physicochimiques
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
G16C 20/30 - Prévision des propriétés des composés, des compositions ou des mélanges chimiques
5.
INFORMATION PROCESSING APPARATUS AND CORRECTION PROCESSING METHOD
An information processing apparatus includes: a memory configured to store correction information for performing distortion correction on an image; and a processor coupled to the memory and configured to: based on a characteristic of each imaging circuit of a plurality of imaging circuits that captures different images, group two or more imaging circuits for each of which determination is made that distortion correction is capable of being performed on an image based on the correction information among the plurality of imaging circuits; and perform distortion correction on an image captured by each imaging circuit of the two or more imaging circuits that are grouped, based on the correction information stored in the memory.
H04N 23/81 - Chaînes de traitement de la caméra; Leurs composants pour supprimer ou minimiser les perturbations lors de la génération de signaux d'image
A non-transitory computer-readable recording medium stores a calculation program for causing a computer to execute a process including: executing calculation of an iterative method for iterating update of a solution by using a plurality of processing circuits operating in parallel in one or each of a plurality of loop processing; executing the calculation of the iterative method by using the plurality of processing circuits in predetermined loop processing after the one or plurality of loop processing; and determining a timing of determination processing of determining update end in the calculation of the iterative method of the predetermined loop processing based on a number of times the solution is updated in the calculation of the iterative method of the one or each of the plurality of loop processing, wherein the determination processing includes processing of determining the update end based on a result of communication between the plurality of processing circuits.
An apparatus and method for transmitting data of vehicle communication (V2X) services and a communication system. The apparatus includes: a first generating unit configured in a media access control (MAC) layer of the terminal equipment and configured to generate at least one protocol data unit (PDU) in a mode identical to a transmission mode to which a service data unit (SDU) contained in a PDU corresponds; and a first transmitting unit configured in the MAC layer and configured to transmit the PDU to a physical layer of the terminal equipment, and notify the transmission mode to which the PDU corresponds to the physical layer. This disclosure facilitates the physical layer to transmit data in a corresponding transmission mode. The terminal equipment may determine the transmission mode or set the transmission mode according to the indication information, and layers of the terminal equipment perform corresponding processing.
H04W 28/02 - Gestion du trafic, p.ex. régulation de flux ou d'encombrement
H04W 4/40 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p.ex. communication véhicule-piétons
H04W 80/02 - Protocoles de couche liaison de données
8.
NON-TRANSITORY COMPUTER-READABLE RECORDING MEDIUM STORING INFORMATION PROCESSING PROGRAM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING APPARATUS
A non-transitory computer-readable recording medium storing an information processing program for causing a computer to execute processing including: extracting, for a plurality of pieces of combination data each of which is a combination of a plurality of feature amounts that includes an invariable feature amount and a variable feature amount that represent features of a target, combination data to be processed based on the plurality of pieces of combination data according to relation between the respective pieces of combination data; executing causal search processing for the variable feature amount according to the invariable feature amount by using the combination data to be processed; and selecting, based on a result of the causal search processing, a specific variable feature amount that corresponds to the specified invariable feature amount, to present the selected specific variable feature.
A semiconductor apparatus includes a substrate, a plurality of heat generating elements mounted on the substrate, a heat dissipation member fixed to the substrate and disposed such that the heat generating elements are interposed between the heat dissipation member and the substrate, at least one first heat conduction member provided on a first surface of the heat dissipation member, the first surface facing the heat generating elements, and a plurality of second heat conduction members each provided on a second surface of a corresponding one of the heat generating elements, the second surface facing the heat dissipation member, wherein the at least one first heat conduction member and the second heat conduction members are in contact with each other at an interface between opposing surfaces thereof.
A wireless communications device configured to perform wireless resource management at a base station that performs wireless communication with a plurality of terminals by a predetermined beam, includes a memory storing therein a plurality of beam tables set with the terminals accommodated by a plurality of beams, and a processor connected to the memory and configured to manage the beam tables. The processor, during system operation, determines a movable terminal that, of the terminals, is movable between the beam tables and determines another beam table that, of the beam tables, is capable of accommodating the movable terminal. The processor moves the moveable terminal to the other beam table and adjusts a number of the terminals accommodated by each of the beam tables.
An information processing apparatus generates a commitment by obfuscating item values, and generates zero-knowledge proof information for proving that a user has knowledge of the item values. The information processing apparatus sends an item value, the commitment, and the zero-knowledge proof information to an information processing apparatus. The information processing apparatus generates a commitment from the item value. The information processing apparatus verifies the authenticity of the received item value on the basis of the relationship between the commitments and a commitment registered in a database and the zero-knowledge proof information.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
A non-transitory computer-readable storage medium storing a machine learning program that causes at least one computer to execute a process, the process includes estimating a first label distribution of unlabeled training data based on a classification model and an initial value of a label distribution of a transfer target domain, the classification model being trained by using labeled training data which corresponds to a transfer source domain and unlabeled training data which corresponds to the transfer target domain; acquiring a second label distribution based on the labeled training data; acquiring a weight of each label included in the labeled training data and the unlabeled training data based on a difference between the first label distribution and the second label distribution; and re-training the classification model by the labeled training data and the unlabeled training data reflected the weight of each label.
A storage medium storing an information processing program that causes a computer to execute a process that includes acquiring a first candidate group that includes candidates of operating routes of each of a plurality of mobile bodies; acquiring a second candidate group that includes candidates of delivery routes of each of packages, the delivery routes being combinations of candidates of operating routes; setting a function that uses a first variable that indicates whether to select each of the candidates included in the first candidate group and a second variable that indicates whether to select each of the candidates included in the second candidate group; determining operation and delivery routes so as to minimize the value specified by the function under a constraint that candidates of operating routes included in the combination of selected candidates of the delivery routes according to the second variable, are selected according to the first variable.
An information processing apparatus generates, from a message including a public key of a user or an identifier associated with the public key and a random number, a commitment in which the message is concealed. The information processing apparatus generates signature information about a hash value of the random number by using a secret key associated with the public key. The information processing apparatus generates zero-knowledge proof information for proving that the user has knowledge of the random number, the message, and the public key. The information processing apparatus transmits the generated commitment, signature information, and zero-knowledge proof information to an information processing apparatus.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
A wireless communication device that transmits data to another wireless communication device that performs wireless connection using a packet including a transmission number, the wireless communication device includes, a controller configured to classify the data as first data when a transmission condition indicating a condition related to transmission of the data is a first transmission condition and classifies the data as second data when the transmission condition of the data is a second transmission condition different from the first transmission condition, and a transmitter configured to transmit the data in a first transmission mode in a layer related to the wireless connection when the data is the first data and transmits the data in a second transmission mode in a layer related to the wireless connection when the second data is second data.
H04W 72/542 - Critères d’affectation ou de planification des ressources sans fil sur la base de critères de qualité en utilisant la qualité mesurée ou perçue
H04W 76/10 - Gestion de la connexion Établissement de la connexion
H04W 28/02 - Gestion du trafic, p.ex. régulation de flux ou d'encombrement
16.
STORAGE MEDIUM, OUTPUT METHOD, AND INFORMATION PROCESSING DEVICE
A non-transitory computer-readable storage medium storing an output program that causes at least one computer to execute a process, the process includes analyzing first meaning representations of a target sentence to generate a first combination of subjects, verbs, and objects in the target sentence; searching for a second combination of subjects, verbs, and objects based on a knowledge base obtained by analyzing second meaning representations of input text, the knowledge base storing information that indicates a third combination of subjects, verbs, and objects in sentences, the third combination in the sentence having the cause-effect relationship with fourth combinations of subjects, verbs, and objects in each of sentences in the input text; and outputting the searched second combination.
A computer-implemented method of training an object detector, the method comprising: training an embedding neural network using, as an input, cropped images from an image dataset, wherein training the embedding neural network is performed using a self-supervised learning approach and the trained embedding neural network translates input images into a lower dimensional representation; and training an object detector neural network by, for images of the image dataset, repeatedly: passing an image through the object detector neural network to obtain proposed coordinates of an object within the image, cropping the image to the proposed coordinates to obtain a cropped image, passing the cropped image through the trained embedding neural network to obtain a cropped image representation, passing an exemplar through the trained embedding neural network to obtain an exemplar representation, wherein the exemplar is a cropped manually labelled image bounding a known object, computing a distance in embedding space between the cropped image representation and the exemplar representation, computing a gradient of the cropped image representation and the exemplar representation with respect to the distance, and passing the gradient into the object detector neural network for use in backpropagation to optimise the object detector neural network.
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
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 processing unit reads out design information about a highest hierarchical layer from a storage unit, divides the highest hierarchical layer into a plurality of segments (segments, etc.) based on the design information about the highest hierarchical layer, detects overlapping areas (optimum placement areas) in which segments at a corresponding location among a plurality of instances in a lowest hierarchical layer included in the highest hierarchical layer overlap with each other at least partly when the plurality of instances are overlapped with each other, sets, in each of the overlapping areas in the plurality of instances, a temporary placement location in which a test cell used for testing of manufacturing variation in critical dimension is temporarily placed, and outputs information indicating the overlapping areas and the temporary placement locations.
In an embodiment, multiple datasets related to multiple application domains are received. Further, feature dependency information associated with a first dataset is determined, based on a first user input. Also, feature difference information associated with the first dataset and a second dataset is determined, based on a second user input and a set of ethical requirements. A set of structural causal models (SCMs) associated with the first dataset are determined based on the feature dependency information and the feature difference information. A set of ethical coefficients associated with the set of ethical requirements are determined based on an application of a causal transportability model on the set of SCMs. A trust score associated with the first dataset is determined based on the set of ethical coefficients. The trust score is used to train a meta-learning model associated with the multiple application domains.
G06V 10/774 - Dispositions 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 10/772 - Détermination de motifs de référence représentatifs, p.ex. motifs de valeurs moyennes ou déformants; Génération de dictionnaires
20.
COMPUTER-READABLE RECORDING MEDIUM STORING ANALYSIS PROGRAM, ANALYSIS METHOD, AND INFORMATION PROCESSING SYSTEM
A recording medium stores a program for causing a computer to execute a process including: calculating a deviation degree between a first measurement value which represents an execution state in a period in which the problem does not occur and a second measurement value which represents the execution state in a period in which the problem occurs; calculating an involvement degree which indicates a degree of relevance to the problem based on a relationship between an occurrence location of the problem and each software element; calculating a single influence point which indicates a degree influenced by the problem based on the deviation degree and the involvement degree; and calculating a total influence point which indicates a degree to which a first software element is influenced by the problem, based on a single influence point of the first software element and a single influence point of a second software element.
An image processing device includes: a memory; and a processor coupled to the memory and configured to: acquire a first feature map output from a hidden layer by forward propagation of image data; acquire a plurality of second feature maps output from the hidden layer by forward propagation of each of a plurality of pieces of decoded data obtained by sequentially encoding the image data by using different quantization values and thereafter decoding the encoded image data; calculate a degree of influence of each block of the image data on a recognition result by backpropagating each error between the first feature map and the plurality of second feature maps; and determine a quantization value of each block when the image data is encoded.
G06V 10/77 - Dispositions 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
H04N 19/176 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c. à d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une zone de l'image, p.ex. un objet la zone étant un bloc, p.ex. un macrobloc
22.
ARITHMETIC PROCESSING DEVICE AND ARITHMETIC PROCESSING METHOD
An arithmetic processing device includes an instruction storage configured to store an arithmetic instruction and a data cache configured to cache a calculation result of the arithmetic instruction. A plurality of floating-point registers arranged on a side of the instruction storage is configured to store a register value used for executing the arithmetic instruction transferred from the instruction storage, and a plurality of floating point calculation circuits arranged on a side of the data cache is configured to perform a floating-point operation based on the arithmetic instruction, wherein a number of cycles is one when the register value is transferred from the instruction storage to one or more floating-point registers, among the plurality of floating point registers, arranged in positions closest in distance to the instruction storage.
A method may include obtaining a graph dataset that includes a plurality of nodes. The method may include specifying two or more clusters into which each node of the plurality of nodes is to be sorted. The method may include assigning each respective node of the plurality of nodes of the graph dataset into a respective cluster of the two or more clusters according to respective costs that are each associated with each of the respective clusters such that all of the costs are within a threshold value of each other. The respective cost associated with its respective cluster may be determined based on a number of external edges connecting the respective nodes in the respective cluster to the nodes in each other cluster. The method may include analyzing the plurality of nodes with respect to the respective cluster to which each of the respective nodes is assigned.
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06F 7/24 - Tri, c. à d. extraction de données d'un ou de plusieurs supports, nouveau rangement des données dans un ordre de succession numérique ou autre, et réinscription des données triées sur le support original ou sur un support différent ou sur une série d
24.
DETERMINATION METHOD, NON-TRANSITORY COMPUTER-READABLE RECORDING MEDIUM STORING DETERMINATION PROGRAM, AND INFORMATION PROCESSING DEVICE
In a determination method, a computer executes processing including: generating face image data from which noise is removed by a specific algorithm from face image data when the face image data is acquired; generating difference image data concerning difference between the face image data that has been acquired and the face image data that has been generated; determining whether or not the face image data that has been acquired is a composite image based on information included in the difference image data; and determining whether or not the face image data that has been acquired is a composite image based on information included in frequency data generated from the difference image data in a case where the face image data that has been acquired is not determined to be a composite image.
A non-transitory computer-readable storage medium storing an information processing program that causes at least one computer to execute a process, the process includes training a model based on training data that defines a relationship between a vector that corresponds to a program and a vector that corresponds to each of subprograms that corresponds to the program; and when receiving a first program to be analyzed, acquiring first vectors of first subprograms that corresponds to the first program by inputting the first program to the training model.
A data converting device includes a processor that executes a procedure. The procedure includes: for each of plural conversion rules, specifying a difference between pre-conversion data and post-conversion data generated by applying the plural conversion rules respectively to the pre-conversion data; determining application probabilities of the plural conversion rules respectively, in accordance with deviations in first plural data based on a first attribute of the first plural data and the differences for the plurality conversion rules; and generating second plural data by applying the plural conversion rules to the first plural data based on the application probabilities.
Inter-University Research Institute Corporation Research Organization of Information and Systems (Japon)
Inventeur(s)
Goshima, Masahiro
Ge, Yi
Abrégé
A processor includes a queue configured to hold a memory access instruction including one or more addresses, a contracted address generator configured to generate a contracted address by contracting bits of multiple addresses in a case where the memory access instruction includes the multiple addresses, a conflict detector configured to detect a conflict between the contracted address and the address held in the queue, and an access controller configured to control processes of the memory access instruction held in the queue, based on a detection result of the conflict detector.
G06F 12/02 - Adressage ou affectation; Réadressage
G06F 12/0875 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p.ex. mémoires cache avec mémoire cache dédiée, p.ex. instruction ou pile
28.
COMPUTER-READABLE RECORDING MEDIUM STORING IMAGE PROCESSING PROGRAM, IMAGE PROCESSING METHOD, AND INFORMATION PROCESSING APPARATUS
A non-transitory computer-readable recording medium stores an image processing program for causing a computer to execute a process including: obtaining a plurality of images consecutively captured in a time series manner; calculating a probability that a type of an object present in each of the plurality of images is one type using a trained classification model; determining whether or not the probability that the type of the object is the one type periodically changes in consecutive images among the plurality of images; and in a case of determining that the probability periodically changes, saving one image within a period in which the probability that the type of the object is the one type periodically changes as training data.
G06V 10/774 - Dispositions 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 10/764 - 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 10/74 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
29.
SEMICONDUCTOR STORAGE DEVICE AND CONTROL METHOD OF SEMICONDUCTOR STORAGE DEVICE
A semiconductor storage device includes: a storage element that holds data; a bit line that is coupled to the storage element and in which step-down to reference voltage causes data held in the storage element to be inverted, a first step-down circuit that steps down bit line voltage to a first predetermined value equal to or below the reference voltage, the bit line voltage being voltage applied to the bit line; and a control circuit that detects a first voltage change based on a first output from a first inverter which has a voltage dependence of an occurring delay and a second output from a second inverter in which a voltage dependence of an occurring delay is larger than that of the first inverter, and that controls a step-down amount of the bit line voltage by the first step-down circuit depending on an amount of the detected first voltage change.
G11C 7/14 - Gestion de cellules factices; Générateurs de tension de référence de lecture
G11C 7/12 - Circuits de commande de lignes de bits, p.ex. circuits d'attaque, de puissance, de tirage vers le haut, d'abaissement, circuits de précharge, circuits d'égalisation, pour lignes de bits
G11C 29/12 - Dispositions intégrées pour les tests, p.ex. auto-test intégré [BIST]
An object detection device includes a processor that executes a procedure. The procedure includes: converting an input image into a first vector such that information related to an area of an object in the image is contained in the first vector; converting input text into a second vector such that information related to an order of appearance in the text of one or more word strings each indicating a detection target object included in the text is contained in the second vector; generating a third vector in which the first vector and the second vector have been reflected in a vector of initial values corresponding to detection target objects; and estimating whether or not a feature indicated by the third vector corresponds to a detection target object that appears at which number place in the text, and estimating a position of the detection target object in the image.
G06V 10/22 - Prétraitement de l’image par la sélection d’une région spécifique contenant ou référençant une forme; Localisation ou traitement de régions spécifiques visant à guider la détection ou la reconnaissance
G06V 10/75 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexte; Sélection des dictionnaires
31.
NON-TRANSITORY RECORDING MEDIUM, INFORMATION PROCESSING DEVICE AND INFORMATION PROCESSING METHOD
An information processing method comprising: for a classification model for classifying input data into one or another of plural classes that was trained using a first data set, identifying, in a second data set that is different from the first data set one or more items of data having a specific datum of which a degree of contribution to a change in a classification criterion is greater than a predetermined threshold, the classification criterion being a classification criterion of the classification model during re-training based on the second data set; and, from among the one or more items of data, detecting an item of data, for which a loss reduces for the classification model by change to the classification criterion by re-training based on the second data set, as an item of data of an unknown class not contained in the plural classes.
A non-transitory computer-readable storage medium storing a search program that causes at least one computer to execute a process, the process includes generating, when search text is received, a first vector that indicates the search text based on a vector that indicates a word included in the search text; generating, when a word that indicates negation is included in the search text, a second vector obtained by rotating the first vector by a certain angle; executing text search processing by using the second vector when the second vector is generated; and executing the text search processing by using the first vector when the second vector is not generated.
A non-transitory computer-readable recording medium has stored therein an information processing program causes a computer to execute a process comprising, dividing input data including a plurality of items related to data to be estimated that is a target of an estimation process using a machine learning model into a plurality of groups based on a predetermined condition; acquiring, for each of the plurality of groups, a first estimation result by a machine learning model that has already been trained, based on the input data included in the each of the plurality of groups; and outputting estimation result information indicating a basis for estimation of a second estimation result that is an estimation result of the data to be estimated, based on the first estimation result of each of the plurality of groups and the second estimation result.
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 10/776 - Dispositions 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 Évaluation des performances
G06V 10/774 - Dispositions 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 10/771 - Sélection de caractéristiques, p.ex. sélection des caractéristiques représentatives à partir d’un espace multidimensionnel de caractéristiques
34.
COMPUTER-READABLE RECORDING MEDIUM STORING INFORMATION PROCESSING PROGRAM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING APPARATUS
A non-transitory computer-readable recording medium storing an information processing program for causing a processor to execute processing including: classifying input data into one or more groups based on a weight of output of each neural network module in a case where data input in training by machine learning is performed for a plurality of neural network modules; and generating, in machine learning processing after the classification, a mini-batch of the input data such that pieces of the input data included in the same group are included in the same mini-batch.
G06F 18/2413 - Techniques de classification relatives au modèle de classification, p.ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
35.
COMPUTER-READABLE RECORDING MEDIUM STORING POWER CONTROL PROGRAM, INFORMATION PROCESSING DEVICE, AND POWER CONTROL METHOD
A non-transitory computer-readable recording medium stores a power control program for causing a computer to execute processing including: monitoring an integrated value of energy consumption consumed by a memory for every predetermined period counted by an interrupt counter; and performing control to increase an operating frequency and a voltage of a memory system at timing of receiving an interrupt that occurs in a case where the interrupt counter overflows on a basis of an upper limit threshold of power consumption per predetermined period set in advance in the interrupt counter.
G06F 1/3234 - Gestion de l’alimentation, c. à d. passage en mode d’économie d’énergie amorcé par événements Économie d’énergie caractérisée par l'action entreprise
G06F 1/3296 - Gestion de l’alimentation, c. à d. passage en mode d’économie d’énergie amorcé par événements Économie d’énergie caractérisée par l'action entreprise par diminution de la tension d’alimentation ou de la tension de fonctionnement
36.
COMPUTER-READABLE RECORDING MEDIUM STORING DETERMINATION PROGRAM, DETERMINATION METHOD, AND INFORMATION PROCESSING DEVICE
A program for causing a computer to execute processing including: generating division candidate datasets divided in accordance with different criteria from each other, from a combined dataset obtained by combining training data and validation data in a divided dataset that has been divided into the training data and the validation data used for machine learning; generating respective machine learning pipelines that execute machine learning, separately for each of the divided dataset and the division candidate datasets; using each of the divided dataset and the division candidate datasets to calculate respective prediction performances when the respective machine learning pipelines are executed; identifying division candidate datasets that have the prediction performances closest to the respective prediction performances calculated using the divided dataset, from among the division candidate datasets; and determining division criteria used for the identified division candidate dataset to be the division criteria used for the divided dataset.
A non-transitory computer-readable storage medium storing an information processing program that causes at least one computer to execute a process, the process includes acquiring an update amount of a classification criterion of a classification model in retraining, the classification model being trained by using a first dataset, the classification model classifying input data into one of a plurality of classes, the retraining being performed by using a second dataset; and detecting data with a largest change amount among the second dataset when changing each piece of data included in the second dataset so as to decrease the update amount.
A storage medium storing an image diagnosis support program for causing a computer to execute process that includes inputting input images to a first model that outputs, according to input images obtained by imaging a subject under the plurality of imaging conditions, an estimation result of a disease name of the, and a degree of contribution to estimation of each of input images for each of the imaging conditions; selecting, among input images, an image imaged under an imaging condition for estimation selected based on the degree of contribution; inputting the image imaged under the imaging condition for estimation to a second model that outputs an estimation result of a lesion part in the image according to the input image; and outputting the estimation result of the lesion part specified based on an output result of the second model.
A computer-readable recording medium storing a program for causing a computer to execute processing including: acquiring browsing feature information indicating a feature of a browsed sentence from browsed data indicating the browsed sentence browsed by a user; acquiring posting feature information indicating a feature of a posted sentence from posted data indicating the posted sentence posted by the user; acquiring target feature information indicating a feature of a target sentence from each target sentence as a processing target; calculating a similarity degree of the target feature information to a set of the browsing feature information and the posting feature information by assigning a larger weight to the posting feature information than to the browsing feature information for each target sentence; and determining a priority of each target sentence to be presented to the user as the processing target, based on the similarity degree of each target sentence.
A non-transitory computer-readable recording medium stores a determination program for causing a computer to execute processing including: re-training a classification model that has been trained by using a first data set and that classifies input data into any one of a plurality of classes by using a loss calculatable based on a second data set that is different from the first data set; and determining, in a case where a change in a classification standard of the classification model based on the loss is a predetermined standard or more before and after re-training, that unknown data that is not classified into any one of the plurality of classes is included in the second data set.
G06F 18/2415 - Techniques de classification relatives au modèle de classification, p.ex. approches paramétriques ou non paramétriques basées sur des modèles paramétriques ou probabilistes, p.ex. basées sur un rapport de vraisemblance ou un taux de faux positifs par rapport à un taux de faux négatifs
A non-transitory computer-readable recording medium stores a program for causing a computer to execute a process that includes adding identification information of each of a plurality of libraries to be installed, to a determination target list one by one, performing, every time the identification information of each of the plurality of libraries is added to the determination target list, a determination process that determines compatibility between a plurality of determination target libraries that include first libraries indicated by first identification information included in the determination target list and depended libraries on which the first libraries depend, when incompatibility regarding a second library indicated by the added identification information is detected, deleting the added identification information from the determination target list, and when the incompatibility regarding the second library is not detected, generating a library list that contains the first identification information and identification information of the depended libraries.
A computer-readable recording medium stores an information processing program. The program is for causing a computer to execute a process including: generating data in which, to each piece of word information included in a graph that represents a plurality of target objects in image data and a relationship between the plurality of target objects, information that indicates a relationship to which the piece of word information belongs and information that indicates a role of the piece of word information in the relationship are added; acquiring, through machine learning in which the generated data serves as input data to an autoencoder, a feature quantity for the input data; and performing classification of the image data, based on the acquired feature quantity.
G06V 20/70 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène 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
43.
BEAM MANAGEMENT METHOD, APPARATUS THEREOF AND BEAM MANAGEMENT DEVICE
A beam management method, an apparatus thereof and an intelligent beam management device. The method includes querying a database according to position information (x0, y0, z0) of a terminal equipment, the database including multiple entries, each entry containing beam measurement related information of a point (xi, yi, zi), selecting entries corresponding to points in a predetermined range of the terminal equipment from the database; selecting no more than a first number of IDs of base station transmitter beams with the highest number of occurrences from all the selected entries; and determining a base station transmitter beam serving the terminal equipment according to whether beams corresponding to the no more than a first number of IDs of base station transmitter beams belong to a serving base station or another base station.
H04W 16/28 - Structures des cellules utilisant l'orientation du faisceau
H04B 7/08 - Systèmes de diversité; Systèmes à plusieurs antennes, c. à d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station de réception
H04B 7/06 - Systèmes de diversité; Systèmes à plusieurs antennes, c. à d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
G06F 16/29 - Bases de données d’informations géographiques
A method of manufacturing a quantum circuit, the method includes forming, in a diamond layer that includes a color center, an optical waveguide optically coupled the color center, the diamond layer having a first principal surface and a second principal surface, wherein the optical waveguide includes: a core region that includes the color center; and an optical confinement region provided around the core region, a refractive index of the optical confinement region is lower than the refractive index of the core region.
A wireless communication system includes a first wireless communication device, and a second wireless communication device. The first wireless communication device includes: a communicator that delivers, to the second wireless communication device, data addressed to a third wireless communication device and receives, from the second wireless communication device, information on communication quality according to failed data of which delivery fails among the data delivered from the second wireless communication device to the third wireless communication device; and a controller that controls delivery of the data in accordance with the information on the communication quality.
According to an aspect of an embodiment, operations may include obtaining a respective target temperature for each respective segment of multiple segments of a Highly Non-Linear optical Fiber (HNLF). Each respective target temperature may be based on a respective Zero-Dispersion Wavelength (ZDW) distribution of its corresponding segment and may be based on a target ZDW of the HNLF. The operations may also include adjusting a respective temperature of each respective segment that may be based on the respective target temperature of each respective segment such that each respective segment has a respective ZDW that is within a threshold of the target ZDW.
H01S 3/30 - Lasers, c. à d. dispositifs utilisant l'émission stimulée de rayonnement électromagnétique dans la gamme de l’infrarouge, du visible ou de l’ultraviolet utilisant des effets de diffusion, p.ex. l'effet Brillouin ou Raman stimulé
H01S 3/10 - Commande de l'intensité, de la fréquence, de la phase, de la polarisation ou de la direction du rayonnement, p.ex. commutation, ouverture de porte, modulation ou démodulation
47.
COMMUNICATION SYSTEM AND COMMUNICATION CONTROL DEVICE
A communication system includes a plurality of first communication control devices that are arranged in association with a plurality of operators, and a second communication control device that is connected to the first communication control devices. The first communication control device calculates an effect evaluation value in a case where bands used by an operator of subject are increased and reduced and transmits information containing the effect evaluation value to the second communication control device. The second communication control device specifies a combination of radio devices and a combination of operators that maximize a value of change in a case where each operator changes the used bands of the radio devices and instructs the first communication control devices corresponding to the operators of the specified combination to increase and reduce the used bands of the radio devices of the specified combination.
A non-transitory computer-readable recording medium stores therein a simulation program that causes a computer to execute a process including acquiring coordinates of particles disposed in a virtual space, moving, in a first coordinate axis direction among coordinate axes that define the coordinates on the virtual space, a window with a width of a cutoff radius used for cutoff of calculation of an interaction between two particles, determining whether first particles that enter the window by the moving and second particles that exist in the window are within the cutoff radius and, when the first particles and the second particles exist, generating a particle pair, and iterating the moving of the window and the generating of the particle pair.
An information processing device acquires output image data that is acquired by inputting image data indicating a pseudo-shadow area to an auto-encoder that is generated by machine learning using label image data contained in training data, the label image data indicating a shadow area in ultrasound image data of a captured target. The information processing device generates augmented data corresponding to the training data by combining the acquired output image data with the ultrasound image data.
G06V 10/75 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexte; Sélection des dictionnaires
50.
EQUILIBRIUM SOLUTION SEARCHING METHOD AND INFORMATION PROCESSING APPARATUS
An information processing apparatus determines a group, which includes at least two nodes, based on similarity between a plurality of first behavior sets using node information which indicates the plurality of first behavior sets corresponding to the plurality of nodes. The information processing apparatus assigns a second behavior set to the group. The information processing apparatus calculates an evaluation value for each behavior included in the second behavior set without calculating evaluation values for behaviors included in the at least two first behavior sets corresponding to the at least two nodes. The information processing apparatus calculates a probability distribution of the behaviors included in the second behavior set based on the evaluation values.
A non-transitory computer-readable recording medium storing an information processing program for causing a computer to execute a procedure, the procedure includes acquiring a start time and an end time of an event processed by a process forming software in which a fault has occurred from a storage, detecting any event in which a processing time is unusual, the any event being processed by any process forming the software, and identifying, when the any event is detected, a type of data related to the any process corresponding to cause of an unusual processing time of the detected any event, based on a state of the any process.
A storage apparatus comprises a controller. Another storage apparatus including a first communication port is coupled to a network, and a first identification number with which a server accesses a first storage area is set in the first communication port. A second communication port in the storage apparatus is closed when the storage apparatus is in a standby state. The controller controls access to the second storage area by opening the second communication port in a case where an operation of the other storage apparatus stops and the storage apparatus transitions to the active state, using the first identification number, and execute diagnosis of the second communication port by changing the first identification number to a second identification number and opening the second communication port in a case where the diagnosis is executed when the storage apparatus is in the standby state.
A computer-implemented method comprising: obtaining an output from each of a plurality of kernels in an extraction layer of a first trained convolutional neural network, wherein the first convolutional neural network is configured to identify one or more features in an image; aggregating the outputs corresponding to at least some input samples of a first domain to generate an aggregate map corresponding to that kernel; resizing the aggregate maps to a lower resolution to generate a plurality of region maps corresponding to the aggregate maps, respectively; clustering the region maps to generate clusters of region maps, each cluster comprising region maps having similar regions; and training, using input samples of a second domain, a second convolutional neural network with a kernel weight of at least one of the kernels which corresponds to at least one of the image regions of at least one of the clusters.
G06V 10/762 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant le regroupement, p.ex. de visages similaires sur les réseaux sociaux
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
54.
INFORMATION PROCESSING APPARATUS AND MEMORY ACCESS CONTROL METHOD
An information processing apparatus includes: calculation circuits that each executes deep learning; a shared memory that is shared by the calculation circuits; an access information memory that holds, for each of the calculation circuits, a write request for writing data generated in forward propagation processing by the calculation circuits to the shared memory, a read request for reading the data used in backward propagation processing by the calculation circuits from the shared memory, and a start time of backward propagation processing; and a processor that schedules data transfer between the calculation circuits and the shared memory based on the write request, the read request, and the start time of backward propagation processing such that the data is transferred from the shared memory to a calculation circuit that executes backward propagation processing by the start time of backward propagation processing, and accesses the shared memory based on a scheduling result.
A packet processing apparatus includes: a gate provided for each service and configured to open and close an output of a packet in a unit of a time slot; and a processor configured to: decide open/close information of a corresponding gate in a first time slot at a current time point by using a set operation parameter; control opening and closing of each gate based on the open/close information in the first time slot; decide open/close information of the corresponding gate in a second time slot after a predetermined timing from the current time point by using the operation parameter; detect a timing conflict between the services in the open/close information in the second time slot; change contents of the operation parameter set based on a priority order; reset the changed operation parameter; and decide open/close information in a new first time slot by using the set changed operation parameter.
H04W 72/1263 - Jumelage du trafic à la planification, p.ex. affectation planifiée ou multiplexage de flux
H04W 72/566 - Critères d’affectation ou de planification des ressources sans fil sur la base de critères de priorité de l’information, de la source d’information ou du destinataire
56.
COMPUTER-READABLE RECORDING MEDIUM STORING TRANSMISSION PROGRAM, TRANSMISSION APPARATUS, AND TRANSMISSION METHOD
A non-transitory computer-readable recording medium storing a transmission program causing a computer of a first transmission apparatus to execute a procedure, the procedure includes detecting a collision between a transmission timing of an intra-coded video frame in first video data transmitted from the first transmission apparatus and a transmission timing of an intra-coded video frame in second video data transmitted from a second transmission apparatus, changing, when the collision is detected at a first time, a frame type of the first video data to one of a forward predictive coded video frame and a bi-directional predictive coded video frame, and transmitting the first video data of which the frame type is changed, at a second time at which the intra-coded video frame in the first video data is scheduled to be transmitted.
H04N 19/593 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage prédictif mettant en œuvre des techniques de prédiction spatiale
H04N 19/177 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c. à d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant un groupe d’images [GOP]
57.
RECORDING MEDIUM AND INFORMATION PROCESSING METHOD
A computer-readable recording medium stores therein an information processing program executable by a computer, the information processing program includes: an instruction for obtaining a matrix to be subject to a calculation for a matrix vector multiplication; an instruction for generating a first matrix in a first format, the first matrix representing a first element group that includes non-zero elements among elements on a part of diagonals, among a main diagonal and sub-diagonals parallel to the main diagonal in the obtained matrix; and an instruction for generating a second matrix in a second format different from the first format, the second matrix representing a second element group that includes the non-zero elements, among the elements in at least a part of rows or columns that form the obtained matrix, other than the elements on the part of the diagonals.
A non-transitory computer-readable recording medium stores a program for causing a computer to execute a process, the process includes extracting a plurality of candidates for an entity in a knowledge graph based on a word in text, collecting related images related to the extracted candidates, generating image clusters of the collected related images for the respective candidates, calculating degrees of similarity between the generated image clusters, and determining, as the entity, a candidate of which the image cluster indicates a higher degree of similarity among the candidates.
A resource allocation apparatus includes a memory, and a processor coupled to the memory and configured to select, based on template information of each of a plurality of containers to be deployed, from among the containers, a first candidate container to be deployed to an information processing apparatus of a first cluster coupled to a second cluster via an external network, determine, based on flow information of communication between the containers, whether a communication band in a case where the selected container is deployed to a gateway of the second cluster coupled to the external network satisfies traffic of a second candidate container to be deployed to an information processing apparatus of the second cluster, and determine a deployment destination of each container, based on a result of the determination of whether the communication band satisfies the traffic.
An access control method is performed by a computer. The method includes: when detecting generation of a process in any of one or more containers, registering an association relationship between the generated process and an address for network communication in the container having the generated process in management information; when detecting an output of an access request to a database, identifying a transmission source process using a transmission source port number of the access request from among one or more processes associated with a transmission source address of the access request in the management information; identifying transmission source software executed by the identified transmission source process; and determining whether access to the database according to the access request from the identified transmission source software is permitted.
A non-transitory computer-readable recording medium stores a program for causing a computer to execute a process, the process includes obtaining first change information, which indicates a change in a feature of a first dataset when first preprocessing is performed on the first dataset, inputting the first change information to a trained machine learning model that outputs an inference result regarding preprocessing information that identifies each piece of second preprocessing for a second dataset, the trained machine learning model being trained by using training data in which the preprocessing information is associated with second change information that indicates a change in a feature of the second dataset when each piece of second preprocessing is performed, and identifying one or more pieces of recommended preprocessing that correspond to the first preprocessing based on the inference result that is output in response to the input of the first change information.
A method of training a model, a device of training a model, and an information processing method is provided. The method of training a model comprises: determining a subsample set sequence composed of N subsample sets of a total training sample set; and iteratively training the model in sequence of N stages based on the subsample set sequence; wherein a stage training sample set of a y-th stage from a second stage to a N-th stage of the N stages comprises a y-th subsample set in the subsample set sequence and a downsampled pre-subsample set of a pre-subsample set composed of all subsample sets before the y-th subsample set; and each single class sample quantity of the downsampled pre-subsample set is close to or falls into a single class sample quantity distribution interval of the y-th subsample set.
G06V 10/774 - Dispositions 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 10/82 - 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
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 10/762 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant le regroupement, p.ex. de visages similaires sur les réseaux sociaux
63.
ARITHMETIC PROCESSING APPARATUS AND METHOD FOR MEMORY ACCESS
An arithmetic processing apparatus includes a controlling unit that refers to an attribute of a compressing scheme on data on a main memory when the data is transferred between the main memory and a memory controller, and that transfers the data by switching the compressing scheme based on the referred attribute.
G06F 7/556 - Méthodes ou dispositions pour effectuer des calculs en utilisant exclusivement une représentation numérique codée, p.ex. en utilisant une représentation binaire, ternaire, décimale utilisant des dispositifs non spécifiés pour l'évaluation de fonctions par calcul de fonctions logarithmiques ou exponentielles
G06F 7/57 - Unités arithmétiques et logiques [UAL], c. à d. dispositions ou dispositifs pour accomplir plusieurs des opérations couvertes par les groupes ou pour accomplir des opérations logiques
64.
METHOD AND APPARATUS FOR REPORTING BEAM FAILURE INFORMATION
The embodiments of the present disclosure provide a method and an apparatus for reporting beam failure information. The method includes: determining, by a terminal equipment, that it has completed candidate beam detection based on a synchronization signal block (SSB) or a channel state information reference signal (CSI-RS) in a secondary cell in which a beam failure occurs; and reporting to a network device that a beam failure occurs in the secondary cell.
A computer acquires training data including first text, first class information indicating a class mapped to a single word contained in the first text, first position information indicating a position of the single word in the first text, and first range information indicating a range of a first named entity that includes the single word in the first text. The computer executes, based on the training data, machine learning of a machine learning model which is used to estimate, from text, class information, and position information, range information of a named entity included in the text.
An information processing apparatus calculates a plurality of first evaluation values respectively corresponding to a plurality of actions on the basis of probability distribution information indicating the selection probability of each of the plurality of actions. When the plurality of first evaluation values include a negative evaluation value, the information processing apparatus converts the plurality of first evaluation values to a plurality of second evaluation values that are non-negative, using a negative reference value. The information processing apparatus updates the selection probability of each of the plurality of actions on the basis of the plurality of second evaluation values.
A method including: obtaining a reduction ratio of each element of layers in a trained model of a neural network; when the neural network includes a process that outputs a tensor as a result of a given calculation on tensors and when tensors from first layers preceding the process are inputted, inserting a second layer that performs a zero padding between the first layers and the process, the first layers including a preceding layer of the process and including one or more layers preceding the preceding layer and being shortcut-connected to the process; and padding tensors inputted into second layers associated one with each first layer with one or more zero matrices such that a number of elements of each tensor inputted into the process from the first layers after reducing of elements of each first layer in accordance with the reduction ratio comes to be a first number.
A computer-implemented method comprising: obtaining, based on an input image, a first activation map of a labelled filter of a first convolutional neural network, the first convolutional neural network being configured to identify one or more first features in the input image; obtaining, based on the input image, a second activation map of a filter of a second convolutional neural network, the second convolutional neural network being configured to identify one or more second features in the input image; calculating a similarity measure between the first activation map and the second activation map; and labelling, when the similarity measure is equal to or above a threshold similarity, the filter of the second convolutional neural network with a label of the labelled filter of the first convolutional neural network.
A determination method implemented by a computer, the determination method including: in response to acquiring a primary image captured by a camera, calculating, based on a size of a region of the subject, an estimated value of a distance to a subject that is specified and included in the primary image; acquiring a secondary image captured by the camera focused on a position according to the calculated estimated value; and determining, based on the acquired secondary image, whether the subject is a display object.
H04N 23/67 - Commande de la mise au point basée sur les signaux électroniques du capteur d'image
H04N 23/611 - Commande des caméras ou des modules de caméras en fonction des objets reconnus les objets reconnus comprenant des parties du corps humain
70.
COMPUTER-READABLE RECORDING MEDIUM STORING INFORMATION PROCESSING PROGRAM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING SYSTEM
A non-transitory computer-readable recording medium stores an information processing program for causing a computer to execute processing includes: acquiring a first condition of an execution environment to which a first job is deployed with reference to first information that makes it possible to specify, for each job, a condition of an execution environment to which the job is deployed; creating a first execution environment to which the first job is deployed based on the acquired first condition; deploying the first job to the created first execution environment; executing the first job; and deleting, in response to completion of the first job, the created first execution environment to which the first job is deployed in a case where a deletion condition that corresponds to the first job is satisfied.
G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
G06F 9/455 - Dispositions pour exécuter des programmes spécifiques Émulation; Interprétation; Simulation de logiciel, p.ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
71.
INFORMATION PROCESSING METHOD AND INFORMATION PROCESSING DEVICE
A non-transitory computer-readable recording medium stores an information processing program for causing a computer to execute a process including generating a representative scenario representing a plurality of forecast scenarios, generating a representative model enabling to calculate a future value of a third variable by using a value of a first variable defined by the representative scenario and a value of a second variable, generating a deviation model representing a deviation between the representative model and a prediction model, identifying a mathematical expression enabling to calculate an analytical solution for a deviation of the second variable so as to optimize a value of a first objective variable, calculating a reference solution for the value of the second variable so as to optimize a value of a second objective variable, and calculating a numerical value solution for the value of the second variable, based on the reference solution and the analytical solution.
G16H 70/40 - TIC spécialement adaptées au maniement ou au traitement de références médicales concernant des médicaments, p.ex. leurs effets secondaires ou leur usage prévu
72.
STORAGE MEDIUM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING DEVICE
A non-transitory computer-readable storage medium storing an information processing program that causes at least one computer to execute a process, the process includes acquiring first trail data to be registered in a traceability system; registering a first identifier that correspond to the first trail data in a first memory to which organizations of the traceability system refer; and registering the first identifier and first information regarding a certain data included in the first trail data, in a second memory to which certain organizations of the organizations refer.
A semiconductor device includes a source electrode and a drain electrode located over a surface of a semiconductor layer including an electron transit layer and an electron supply layer. A gate electrode is located between the source electrode and the drain electrode. A first diamond layer is located between the source electrode and the drain electrode over the surface with an insulating film therebetween. A second diamond layer is located directly on the surface between the gate electrode and the drain electrode. Of heat generated by the semiconductor layer of the semiconductor device in operation, heat on the side of the electrode on which a relatively strong electric field is applied is efficiently transferred to the second diamond layer. The semiconductor device achieves an excellent heat dissipation property from the semiconductor layer and effectively suppresses overheating and a failure and degradation of the characteristics due to the overheating.
H01L 23/373 - Refroidissement facilité par l'emploi de matériaux particuliers pour le dispositif
H01L 29/778 - Transistors à effet de champ avec un canal à gaz de porteurs de charge à deux dimensions, p.ex. transistors à effet de champ à haute mobilité électronique HEMT
H01L 29/423 - Electrodes caractérisées par leur forme, leurs dimensions relatives ou leur disposition relative ne transportant pas le courant à redresser, à amplifier ou à commuter
H01L 29/417 - Electrodes caractérisées par leur forme, leurs dimensions relatives ou leur disposition relative transportant le courant à redresser, à amplifier ou à commuter
H01L 29/66 - Types de dispositifs semi-conducteurs
74.
COMMUNICATION DEVICE, RADIO COMMUNICATION SYSTEM, AND SYNCHRONIZATION SIGNAL TRANSMISSION METHOD
A communication device includes a communication interface that communicates with a plurality of radio units, and a processor that is connected to the communication interface, wherein the processor executes a process of determining a maximum number of beams that indicates an upper limit of the number of beams formed by each of the plurality of radio units such that a sum total of the number of beams formed by the plurality of radio units is equal to or less than the number of synchronization signals that are able to be transmitted within a predetermined time unit, and notifying the plurality of radio units of the determined maximum number of beams.
A method may include directing transmission of a first optical noise signal along a frequency channel of an optical network at a first power level. The first optical noise signal may include a notch at a frequency in the frequency channel. The method may also include while transmission of the first optical noise signal occurs along the frequency channel, obtaining a measurement of a first noise level at the frequency and obtaining a measurement of a second noise level at the frequency. The frequency channel may include a second power level when the measurement of the second noise level is obtained and the second power level may be different than the first power level. The method may further include estimating a noise level of an optical data signal transmitted along the frequency channel based on the first noise level and the second noise level.
H04B 10/079 - Dispositions pour la surveillance ou le test de systèmes de transmission; Dispositions pour la mesure des défauts de systèmes de transmission utilisant un signal en service utilisant des mesures du signal de données
H04B 10/077 - Dispositions pour la surveillance ou le test de systèmes de transmission; Dispositions pour la mesure des défauts de systèmes de transmission utilisant un signal en service utilisant un signal de surveillance ou un signal supplémentaire
76.
WIRELESS COMMUNICATION METHOD AND APPARATUS AND SYSTEM
A wireless communication apparatus, configured in a terminal equipment, includes a receiver configured to receive control information, the control information triggering a physical downlink shared channel, reception or monitoring of the control information being related to two TCI states, and a DCI format corresponding to the control information including no TCI field, and a processor configured to transmit or receive the physical downlink shared channel according to the two TCI states or according to one of the two TCI states.
H04W 72/232 - Canaux de commande ou signalisation pour la gestion des ressources dans le sens descendant de la liaison sans fil, c. à d. en direction du terminal les données de commande provenant de la couche physique, p.ex. signalisation DCI
77.
METHOD, APPARATUS AND SYSTEM FOR MEASURING NONLINEAR RELATED PARAMETERS OF NONLINEAR DEVICE
A method, an apparatus and a system to measure nonlinear related parameters of a nonlinear device. The apparatus comprises a memory and a processor coupled to the memory to control execution of a process to: generate a first signal according to a signal to be measured, the first signal and the signal to be measured having a signal probability distribution that is same, and the first signal having at least one notch frequency; and calculate, according to an output signal of the nonlinear device when the first signal is input into the nonlinear device, nonlinear related parameters of the nonlinear device when the signal to be measured is transmitted.
Operations may include obtaining a dataset that includes a plurality of unique values and obtaining a plurality of permutations with respect to the plurality of unique values. Additionally, the operations may include, for each respective permutation, obtaining a respective overall permutation probability for the respective permutation based on masked value probabilities determined by a masked language model (MLM). Each masked value probability may be determined with respect to a respective masked version of a plurality of masked versions of the respective permutation. The operations may also include selecting a particular permutation from the plurality of permutations based on a comparison between the respective overall permutation probabilities of the plurality of permutations. In addition, the operations may include determining a semantic order of the unique values of the plurality of unique values based on the particular permutation in which the semantic order is related to respective meanings of the unique values.
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
G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
79.
COMPUTER-READABLE RECORDING MEDIUM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING APPARATUS
A non-transitory computer-readable recording medium stores therein an information processing program that causes a computer to execute a process including, acquiring a video image in which an inside of a store in which each commodity product is arranged is captured, specifying a relationship between a plurality of persons who visit the inside of the store by analyzing the acquired video image in which the inside of the store is captured, grouping the plurality of persons when the specified relationship between the plurality of persons satisfies a predetermined condition, specifying, by analyzing the acquired video image in which the inside of the store is captured, a behavior exhibited with respect to the commodity product by each of the plurality of grouped persons, and associating the behavior exhibited with respect to the commodity product with a group to which the person who exhibits the behavior with respect to the commodity product belongs.
A non-transitory computer-readable recording medium has stored therein a setting program that causes a computer to execute a process, the process including acquiring a video from a camera, identifying a depth indicating a distance from the camera to each of constituent elements of the video acquired from the camera, generating a three-dimensional in-store model, generating skeleton information on a person who moves inside the store from the video acquired from the camera, setting a range and a direction of an aisle in the store in the generated three-dimensional in-store model based on a change in the generated skeleton information and setting a detection line in the storage based on the range and the direction of the aisle in the store, the detection line for detecting that the person has extended a hand to a product.
A computer-readable recording medium storing a program for causing a computer of searching for a solution for a combinatorial optimization problem represented by an energy function including state variables, to execute processing including: executing search processing of searching for the solution by performing determination whether or not to accept a change of each value of a plurality of first state variables, for the plurality of first state variables selected from among the state variables in parallel and executing processing of changing the value of one state variable of which the change of the value is determined to be accepted while changing the plurality of selected first state variables; and specifying the number of the plurality of selected first state variables, based on a search status of the search processing or search information that indicates a search record of another combinatorial optimization problem and repeating the search processing.
A non-transitory computer-readable recording medium stores a management program for causing a computer to execute processing including: acquiring information regarding a usage status of a first memory for data transfer included in a measurement target from each of a plurality of the measurement targets; calculating priority of data transfer of each of the plurality of measurement targets, based on the acquired information regarding the usage status of the first memory; collecting measurement data from the first memory of any one of the plurality of measurement targets, based on the calculated priority; and storing the collected measurement data in a second memory that stores measurement data output to a data processing unit that processes the measurement data of each of the plurality of measurement targets.
An information processing system includes an edge computer that implements a preceding stage of a learning model, and a cloud computer that implements a subsequent stage of the learning model, wherein the edge computer includes a first processor configured to calculate a first feature amount by inputting a first image to the preceding stage, identify an area of interest in the first image based on the first feature amount, generate a second image obtained by masking the area of interest in the first image, calculate a second feature amount by inputting the second image to the preceding stage, and transmit the second feature amount to the cloud computer, and the cloud computer includes a second processor configured to infer an object included in the second image by inputting the second feature amount to the subsequent stage.
G06V 10/771 - Sélection de caractéristiques, p.ex. sélection des caractéristiques représentatives à partir d’un espace multidimensionnel de caractéristiques
G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
G06V 10/77 - Dispositions 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
84.
INFORMATION PROCESSING DEVICE AND FUNCTION GENERATION METHOD
A non-transitory computer-readable recording medium stores a function generation program for causing a computer to execute a process, the process includes acquiring manipulation data generated based on manipulated variable distribution information that represents distribution of values of manipulated variables, and measurement data measured when a control object device is controlled based on the manipulation data, and by performing inverse reinforcement learning by using the manipulation data and the measurement data, generating a reward function that includes evaluation indices for the manipulated variable distribution information and coefficient distribution information that represents distribution of the values of coefficients of the evaluation indices.
G05B 13/02 - Systèmes de commande adaptatifs, c. à d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
85.
VERIFICATION METHOD AND INFORMATION PROCESSING APPARATUS
An information processing apparatus acquires a first verifiable credential (VC) that proves the validity of attribute information of a holder by a first signature verifiable by verification procedures of a first decentralized identifiers (DID) infrastructure and a second VC that proves the validity of the attribute information of the holder by a second signature verifiable by verification procedures of a second DID infrastructure. Next, the information processing apparatus verifies the second signature contained in the second VC by the verification procedures of the second DID infrastructure. Further, the information processing apparatus transmits a verification request for verifying the first signature contained in the first VC to a verification device capable of verifying the first signature contained in the first VC by the verification procedures of the first DID infrastructure, and then acquires, from the verification device, verification results of the first signature contained in the first VC.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
86.
INFORMATION PROCESSING DEVICE AND INFORMATION PROCESSING METHOD
An information processing device coupled to a first switch among a plurality of switches and included in a plurality of information processing devices includes: a memory; and a processor coupled to the memory and configured to: store, in the memory, communication destination information based on a plurality of bit strings related to communication destinations of collective communication; and communicate with an information processing device connected to a second switch among the plurality of switches on a basis of the communication destination information. Some information processing devices that include the information processing device among the plurality of information processing devices participate in the collective communication, and the plurality of bit strings is selected from a bit string set related to the communication destinations of the plurality of information processing devices on a basis of the number of the some information processing devices.
H03M 13/00 - Codage, décodage ou conversion de code pour détecter ou corriger des erreurs; Hypothèses de base sur la théorie du codage; Limites de codage; Méthodes d'évaluation de la probabilité d'erreur; Modèles de canaux; Simulation ou test des codes
G06F 11/10 - Détection ou correction d'erreur par introduction de redondance dans la représentation des données, p.ex. en utilisant des codes de contrôle en ajoutant des chiffres binaires ou des symboles particuliers aux données exprimées suivant un code, p.ex. contrôle de parité, exclusion des 9 ou des 11
87.
NON-TRANSITORY COMPUTER READABLE RECORDING MEDIUM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING APPARATUS
A non-transitory computer-readable recording medium has stored therein an information processing program that causes a computer to execute a process, the process including, identifying an action of a specific user picking up a piece of merchandise from the shelf and from a video of an area including an accounting machine in the store, each of the specific user and the accounting machine, storing information, receiving a purchase history, identifying one or more pieces of merchandise included in the purchase history from the accounting machine and identifying a merchandise item to be associated with the shelf, such that a difference between a predicted value and an observed value is minimized, the predicted value being for the number of pieces of merchandise purchased and being based on the action of picking up a piece of merchandise.
A non-transitory computer-readable recording medium stores therein an information processing program that causes a computer to execute a process including, extracting a person and a commodity product from a video image in which an inside of a store is captured, tracking the extracted person, specifying a behavior exhibited by the tracked person with respect to the commodity product, specifying a first behavior type that is reached by a first behavior exhibited by the tracked person with respect to the commodity product from among a plurality of behavior types in each of which a transition of processes of the behaviors exhibited between a behavior of entering the inside of the store and a behavior of purchasing the commodity product in the inside of the store is defined, and specifying, based on the first behavior type, content of a customer service provided with respect to the tracked person.
A non-transitory computer-readable recording medium stores therein an information processing program that causes a computer to execute a process, the process including, identifying relationships between a plurality of customers and a sales clerk by analyzing a video in which an inside of a store is captured, identifying customers who received customer services from the sales clerk among the plurality of customers based on the identified relationships between the sales clerk and the plurality of customers, classifying each of the customers into a certain group such that the customers who received the services from the sales clerk belong to different groups, and associating the classified group with behaviors of the customers who belong to the group.
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 20/40 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène dans le contenu vidéo
G06V 40/20 - Mouvements ou comportement, p.ex. reconnaissance des gestes
90.
NON-TRANSITORY COMPUTER READABLE RECORDING MEDIUM, DISTRIBUTION METHOD, AND INFORMATION PROCESSING APPARATUS
A non-transitory computer-readable recording medium has stored therein a distribution program that causes a computer to execute a process, the process including, extracting a person and a product from a video of an inside of a store, tracking the extracted person, identifying a behavior that is performed by the tracked person with respect to a product in the store, identifying a first behavior type that is led by the behavior that is performed by the tracked person with respect to the product among a plurality of behavior types that define transition of a process of the behavior since entrance into the store until purchase of a product in the store, and distributing information on a product indicating the first behavior type to the tracked person when the identified first behavior type is at a predetermined level or higher and the tracked person has not yet purchased the product.
Rules for explaining the output of an ANN are derived by: creating decision trees trained to approximate the ANN and optimize a defined criterion, a threshold value for the criterion being calculated to determine for which node of the ANN the input activations should be split between branches of the decision tree; obtaining threshold value combinations each comprising a threshold value obtained for respective nodes of the ANN; for each combination, using the combination to perform a rule extraction algorithm to extract a rule explaining the output of the ANN and to obtain a fidelity metric indicating the accuracy of the rule with respect to predictions of the ANN; determining which combination yields the best fidelity metric; and using the rule extraction algorithm with the combination of threshold values determined to yield the best fidelity metric to extract at least one rule for explaining the output of the ANN.
An apparatus for selecting sidelink resources includes determining processer circuitry configured to determine a first monitoring time period at least according to a service periodicity, a last time unit of a sensing time period and a selection time period, a monitor configured to monitor sidelink control information in the first monitoring time period, and excluding processor circuitry configured to exclude one or more candidate resources in the selection time period according to the received sidelink control information.
H04W 72/02 - Sélection de ressources sans fil par un utilisateur ou un terminal
H04W 72/25 - Canaux de commande ou signalisation pour la gestion des ressources entre terminaux au moyen d’une liaison sans fil, p.ex. liaison secondaire
93.
STORAGE MEDIUM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING DEVICE
A non-transitory computer-readable storage medium storing an information processing program that causes at least one computer to execute a process, the process includes acquiring first trail data to be registered in a traceability system; registering a first identifier that correspond to the first trail data in a first memory to which organizations of the traceability system refer; and registering the first identifier and first information regarding the first trail data, in a second memory.
A non-transitory computer-readable storage medium storing an estimation program that causes at least one computer to execute a process, the process includes inputting training data that includes a vector of graph data, a vector of ontology, and a label; training a machine learning model based on a loss function acquired by the label and a value obtained by merging a value of an activation function acquired with the vector of the graph data and a value of the activation function acquired with the vector of the ontology.
A non-transitory computer-readable storage medium storing an arrangement specifying program that causes at least one computer to execute a process, the process includes acquiring a shape of a container that has a first surface and a second surface orthogonal to the first surface; acquiring a shape of a plurality of articles; and specifying an arrangement position and an arrangement posture of each of the plurality of articles when the plurality of articles is arranged in the container in an arrangement order, by using a bottom left algorithm.
B65B 57/10 - Dispositifs de commande automatique, de vérification, d'alarme ou de sécurité sensibles à l'absence, à la présence, à l'alimentation anormale ou au mauvais positionnement des objets ou matériaux à emballer
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
G05B 15/02 - Systèmes commandés par un calculateur électriques
B65B 5/06 - Emballage de groupes d'objets, chaque groupe étant traité comme un seul objet
96.
LEARNING METHOD AND INFORMATION PROCESSING APPARATUS
An information processing apparatus deletes specific types of characters from each of multiple sentences and generates multiple word strings which do not include the specific types of characters and correspond to the multiple sentences. The information processing apparatus divides the multiple word strings into multiple groups, each including two or more word strings. The information processing apparatus performs, for each of the multiple groups, padding to equalize the number of words among the two or more word strings based on the maximum number of words in the two or more word strings. The information processing apparatus updates, using each of the multiple padded groups, parameter values included in a natural language processing model that calculates an estimate value from a word string input thereto.
G06F 40/40 - Traitement ou traduction du langage naturel
G06F 40/166 - Traitement de texte Édition, p.ex. insertion ou suppression
97.
COMPUTER-READABLE RECORDING MEDIUM STORING RECOGNITION-RELATED DATA PROCESSING PROGRAM, METHOD OF PROCESSING RECOGNITION-RELATED DATA, AND INFORMATION PROCESSING SYSTEM
A computer-readable recording medium storing a recognition-related data processing program for causing a computer of a user terminal to be used by a user to execute processing including: accepting an audit demand for an audit of recognition-related data received from a terminal; transmitting, in response to the audit demand, an audit request to a first terminal that is different from the user terminal, and obtaining audit information on the recognition-related data transmitted from the first terminal; and transmitting the audit information to a second terminal that is able to verify correctness of the audit information and that executes a return, to the user, a consideration corresponding to the recognition-related data, and demanding that the second terminal return, to the user, the consideration which corresponds to the recognition-related data associated with the transmitted audit information.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
98.
MONITORING SYSTEM, MONITORING METHOD, AND COMPUTER-READABLE RECORDING MEDIUM STORING MONITORING PROGRAM
A recording medium stores a monitoring program that cause a computer to execute processes including: determining a learning range, used in learning of messages, for each of monitoring target systems based on time-series information of each of past message groups and on keyword information that suggests a forwarding destination; generating a learning model, used to infer information on the forwarding destination, by using the determined learning range as a parameter and by using the time-series information, the information on the forwarding destination, and the keyword information included in each of the messages in the case where the message is the error message as training data; and selecting the learning model to be applied to the new system based on a degree of similarity between the keyword information used in the learning of each of the monitoring target systems and the keyword information of the error message of the new system.
An information processing apparatus generates a data set including a plurality of records each of which indicates one out of a plurality of behaviors. The information processing apparatus calculates a first evaluation value for a first behavior that appears in the data set, based on a distribution of appearance frequency of first behaviors in the data set. The information processing apparatus updates at least a part of the records so that the appearance frequency of a first behavior whose first evaluation value exceeds a threshold increases. The information processing apparatus calculates a second evaluation value for a second behavior that appears in the updated data set based on a distribution of the appearance frequency of second behaviors in the updated data set.
A generation method includes extracting, by a computer, a tendency of topics shared by a group to which a user of a social networking service belongs; and generating information that indicates, based on the tendency of topics, a probability of the user spreading posted fake information.
G06Q 50/00 - Systèmes ou procédés spécialement adaptés à un secteur particulier d’activité économique, p.ex. aux services d’utilité publique ou au tourisme
G06F 16/9536 - Personnalisation de la recherche basée sur le filtrage social ou collaboratif
brevets
