Abstract: A compression unit of a rotary compressor includes a cylinder, an upper end plate that closes the upper side of the cylinder, a lower end plate that closes the lower side of the cylinder, and a piston that is fitted to a rotating shaft, revolves along an inner peripheral surface of the cylinder, and forms a cylinder chamber in the cylinder. At least one of an end face of the piston in the axial direction of the rotating shaft, a sliding surface of the upper end plate that slides with the end face of the piston, and a sliding surface of the lower end plate that slides with the end face of the piston, has formed therein an oil-film retention region having an array of a plurality of recessed portions that retain lubricating oil.

Abstract: An air conditioner includes an adapter including a control unit that controls the air conditioner using a learning model and a communication unit that communicates with a server device that generates the learning model on the basis of operation history data of the air conditioner. The adapter includes an acquisition unit, a determination unit, an erasing unit, and a transmission unit. The acquisition unit acquires the data every predetermined cycle from the air conditioner. The determination unit determines whether or not an amount of change between temporally continuous data of the data acquired by the acquisition unit is within a predetermined range. The erasing unit leaves at least one of the continuous data and deletes the other data in a case where the amount of change between the continuous data is within the predetermined range. The transmission unit transmits the data after being deleted to the server device.

Abstract: According to an aspect of an embodiment operations may include receiving, by a server, message shares. The operations may also include generating, by the server, an aggregate hash share of the message shares. In addition, the operations may include receiving, by the server, a verification vector iteration from another server and generating another verification vector iteration based on: the received verification vector iteration, a permutation that corresponds to the server, and a masking vector that corresponds to the server. The operations may also include obtaining a verification hash that is based on the verification vector and participating in a multiparty computation to determine an aggregate hash. The operations may also include determining, as part of the multiparty computation, whether one or more of the servers is operating in an adverse manner based on whether the verification hash is equal to the aggregate hash.

Abstract: Disclosed system specifies, based on measurement results of communication times taken for accessing a plurality of external databases, relation between the communication times taken for accessing the plurality of external databases, calculates, when accepting an instruction to execute processing using at least one of the plurality of external databases, a processing load when accessing the at least one of the external databases, based on the relation between the communication times, and controls an access to data included in the at least one of the external databases according to the calculated processing load.

Abstract: A non-transitory computer-readable storage medium storing a pattern search program that causes a computer to execute a process, the process includes designating priority ranks of each of attributes included in a plurality of attribute patterns that indicate one or more attributes, based on an inclusion relationship between occurrence sets of a plurality of samples with respect to each of the attributes included in the plurality of attribute patterns; and determining whether each of the plurality of attribute patterns is an emerging pattern according to a search order based on the priority ranks, when a frequency of occurrence of the plurality of samples in a first attribute pattern is less than the frequency of occurrence of the plurality of samples in a second attribute pattern that has all the attributes except one of the attributes with lowest one of the priority ranks among the attributes included in the first attribute pattern.

Abstract: A method and apparatus for transmitting and receiving uplink control information. The method includes: determining a channel access type of an uplink control channel used for transmitting uplink control information by a terminal equipment; and detecting a channel according to the channel access type and transmitting the uplink control information to a network device after the channel is detected as being idle, or not detecting a channel according to the channel access type and transmitting the uplink control information to the network device. Hence, in some scenarios, uplink control information may be transmitted without detecting a channel, which may lower latency and improve transmission efficiency; and in some other scenarios, uplink control information may be transmitted after the channel is detected as being idle, which may avoid or lower interference and improve reliability of transmission.

Abstract: A blower includes a cross flow fan, a mechanism configured to rotate the cross flow fan about a rotation axis, a front tongue part that is arranged in front of the cross flow fan, and a back tongue part that is arranged in back of the cross flow fan, wherein a front fan facing surface of the front tongue part faces the cross flow fan, and includes a plurality of front non-flat portions on which non-flatness is formed, and a plurality of front flat portions on which no non-flatness formed, a back fan facing surface of the back tongue part faces the cross flow fan, and includes a plurality of back non-flat portions on which non-flatness formed, and a plurality of back flat portions on which no non-flatness is formed, and the back non-flat portions respectively face the front flat portions and the back flat portions respectively face the front non-flat portions.

Abstract: A non-transitory computer-readable recording medium storing a machine learning program for causing a computer to execute a process to train a machine learning model constructed by combining a plurality of modules configured by a neural network, the process includes parsing dependency between words for a plurality of words included in a question sentence of training data that forms a set of an image and the question sentence related to the image, determining a weight to be applied to each of the plurality of modules, based on a result of the parsing, and controlling selection of a combination of modules to be used in the machine learning model from the plurality of modules, based on the weight to be applied to each of the plurality of modules.

Abstract: A method includes calculating a plurality of first index values indicating access loads from one or more first virtual storage devices accessing a first physical storage device of a plurality of physical storage devices, to the first physical storage device, in a case where access loads from the one or more first virtual storage devices to a plurality of second physical storage devices including the first physical storage device are equalized across the second physical storage devices, the plurality of second physical storage devices being associated with the one or more first virtual storage devices; and outputting a plurality of second index values indicating access loads from a plurality of virtual machines to the first physical storage device, the second index values being obtained by summing the calculated first index values for each virtual machine associated with each of the one or more first virtual storage devices.

Abstract: A processor includes an operation executer configured to execute pipeline processing of an operation instruction, wherein the operation executer includes a first register configured to hold data to be used for an operation; a pre-processor configured to pre-process data held in the first register; a second register configured to hold the data pre-processed by the pre-processor; an operator configured to execute an operation on the data held in the first register or the data held in the second register; and a selector configured to connect an output of the first register or an output of the second register to an input of the operator.

Abstract: A non-transitory computer-readable recording medium stores a program for causing a computer to execute a process, the process includes in repeat calculation of electron density of a substance by a self-consistent field method that uses a specific number of wave functions according to cutoff energy, executing a second electron density calculation at an (N+1)-th time (N is an integer greater than or equal to 1) by applying second cutoff energy of a value smaller than first cutoff energy applied to an first electron density calculation at an N-th time, determining whether the electron density obtained by the second electron density calculation at the (N+1)-th time satisfies a predetermined condition, and outputting the value of the second cutoff energy in a case where the condition is not satisfied.

Abstract: A recording medium stores a program for causing a computer to execute a process including: accepting selection of one or more atoms among a plurality of atoms that form a target molecule that exists in a predetermined coordinate space; and altering coordinates of each atom of the one or more atoms from first coordinates to second coordinates in the coordinate space based on: a unit vector between the coordinates of a first atom and a second atom of which a bond length is to be changed; a normal vector with respect to a plane formed by a first bond axis and a second bond axis of which a bond angle is to be changed; or a rotation matrix of the second atom of which a rotation angle is to be changed; or any combination of the unit vector, the normal vector, or the rotation matrix, in the coordinate space.

Abstract: A Doherty amplification device includes a distributor to distribute, into first and second signals, an input signal after distortion-compensation, first and second amplifiers, a combiner to combine the amplified first and second signals, and an adjuster between the distributor and the first or second amplifiers and to include a first calculation circuit to obtain a first-characteristic indicating a relationship of a gain of an output signal with respect to reference-power of the input signal, based on the output signal and the input signal, a classification circuit to classify the first-characteristic into regions according to the reference-power, a second calculation circuit to obtain a statistical-value of the gain for each regions, and a determination circuit to set, in the adjuster, a phase-delay at which distortion to be generated in the output signal is minimized, based on the statistical-value, wherein the adjuster adjusts the phase-delay of the first or second signals.

Abstract: An optical transmission system includes: a WDM transmission device configured to output WDM signal light including rays of a plurality of wavelengths; a wavelength converter configured to convert the WDM signal light into converted light in a different wavelength band; and a processor configured to control a signal level of the WDM signal light incident on the wavelength converter, wherein the processor controls the signal level of the WDM signal light so as to make the signal level of the WDM signal light decrease in a direction away from a wavelength of pump light used in the wavelength converter.

Abstract: An optical transmitter includes: an optical modulator of a Mach-Zehnder type using an InP-based material; a bias controller configured to control a DC bias applied to the optical modulator; a monitor configured to monitor output light of the optical modulator to generate a monitor signal; and a corrector configured to correct a gain of the monitor signal in a direction in which wavelength dependency of insertion loss of the optical modulator is compensated according to a wavelength at a preceding stage of bias control by the bias controller.

Abstract: A process includes obtaining, according to a predetermined update order of a policy parameter of each agent, a degree of influence on a constraint specific to a first agent and a degree of influence on a system-wide constraint in which a degree of influence by an updated policy parameter of a second agent previous to the first agent in the update order is shared, and in a case where an update width of the policy parameter of the first agent exists in both ranges respectively determined depending on the degree of influence on the constraint specific to the first agent and the degree of influence on the system-wide constraint, updating the policy parameter of the first agent and causing the degree of influence on the system-wide constraints by the updated policy parameter to be shared with a third agent next to the first agent in the update order.

Abstract: A computer-readable recording medium has stored therein a machine learning program executable by one or more computers, the machine learning program including: an instruction for comparing a first plurality of relationship information pieces with a second plurality of relationship information pieces, the first plurality of relationship information pieces being determined in terms of an inputted configuration of a first Artificial Intelligence (AI) system and each including a plurality of attributes, the second plurality of relationship information pieces being determined in terms of a second AI system; an instruction for determining priorities of the first plurality of relationship information pieces, the priorities being based on a result of the comparing; and an instruction for outputting, as a checklist of the first AI system, one or more check items selected in accordance with the determined priorities from among a plurality of check items associated with the plurality of attributes.

Abstract: A non-transitory computer-readable recording medium storing a machine learning program for causing a computer to execute a process, the process includes inputting moving image data that includes at least a first frame image and a second frame image to a first machine learning model trained by using training data, and training an encoder by detecting a first object and a second object from the first frame image and the second frame image, respectively, based on an inference result by the first machine learning model, determining identity between the first object and the second object that have been detected, and inputting, to the encoder, first data in a first image area that includes the first object and second data in a second image area that includes the second object, the first object and the second object having been determined to have the identity.

Abstract: An arithmetic processing device executes instructions by pipeline processing. In the arithmetic processing device, a branch predictor includes a prediction holder holding a prediction value of a consecutively taken branch count, a current taken branch count, and a prediction value of a remaining taken branch count for conditional branch instructions. A branch instruction issuance scheduler outputs an instruction refetch request upon a branch prediction miss of a conditional branch instruction held at an entry other than a head of a branch instruction completion queue holding branch instructions to be completed, and a repair request to the branch predictor for conditional branch instructions held between the entry and the head of the queue. In response to the requests, the branch predictor updates the prediction value of the remaining taken branch count for the conditional branch instructions corresponding to the repair request.

Abstract: A non-transitory computer-readable recording medium stores a program for causing a computer to execute a sampling process including: converting first data in a latent space into second data in a data space by using a machine learning model that has the latent space transformable into an isometric space with same probability distribution as the data space according to a predetermined transformation rule; determining whether or not to accept the second data as a transition state in a Markov chain Monte Carlo method from an accepted first sample in the data space with an acceptance probability based on the transformation rule; and outputting the second data as a second sample of the transition state from the first sample when the second data is determined to be accepted.