Abstract: An embodiment packet capture device comprises: a packet receiver configured to receive a packet from a network; a packet retainer configured to store the received packet in a memory to temporarily retain the received packet; a failure detector configured to determine a communication failure is present in the network; a capture controller configured to determine an operation stop address such that retention of packets from the network in time periods before and after a detection time point of the communication failure is ensured when the communication failure is detected by the failure detector; and a capture data generator configured to output the packet stored in the memory as capture data when a storage destination address of the packet stored in the memory has reached the operation stop address or when at least a predetermined waiting time period has elapsed from the detection time point of the communication failure.

Abstract: A traffic monitoring apparatus that monitors traffic of a monitoring target network and includes a statistical information processor that acquires statistical information per specific flow of the traffic, and a packet capture unit that captures a packet of the specific flow, in which the statistical information processor includes a statistical information aggregation unit that aggregates the pieces of statistical information, and a statistical information file generation unit that generates a statistical information file based on the pieces of aggregated statistical information.

Abstract: A recognition loss calculation unit of a learning device calculates a recognition loss using: a recognition result with respect to recognition object data in a learning data set that is a set of a pair of the recognition object data and a weak label; a mixing matrix calculated based on the learning data set; and the weak label attached to the recognition object data. The recognition loss calculation unit includes: a difference calculation unit that calculates a difference between a mixing matrix and the recognition result; and a sum of squares calculation unit that calculates the recognition loss by calculating a sum of a square of the difference.

Abstract: A recognition loss calculation unit of a learning device calculates a recognition loss using a recognition result with respect to recognition object data in a dataset for learning that is a set of pairs of the recognition object data and a weak label, a mixing matrix calculated based on the dataset for learning, and a weak label attached to the recognition object data. The recognition loss calculation unit includes a conversion unit that converts the recognition result into a conjugate vector, a mixing matrix product calculation unit that calculates a product of the conjugate vector and the mixing matrix, a normalization term calculation unit that calculates a normalization term from the conjugate vector, and a total sum calculation unit.

Abstract: Provided is a propylene oxide production apparatus including a switching mechanism that is capable of switching a state of each reactor between an operating state where reaction raw materials are supplied and an epoxidation reaction is performed and a non-operating state where the supply of the reaction raw materials is shut off. The propylene oxide production apparatus is capable of changing a reactor in the non-operating state one by one, and performs switching in such a way that only reactors in the operating state are connected fluidically in series or in parallel, thereby enabling supplying the reaction raw materials to the reactors in the operating state. A sampling mechanism is also provided that samples part of the reaction mixture from each discharge line that is connected to each reactor.

Abstract: A battery diagnostic system includes a superimposed current applying unit, a current value acquiring unit, a voltage value acquiring unit, an impedance calculating unit, and a diagnostic unit. The superimposed current applying unit configured to apply a superimposed current formed by superimposing a plurality of frequency components to a battery. The current value acquiring unit acquires the current value of the superimposed current applied to the battery. The voltage value acquiring unit acquires a battery voltage of the battery to which the superimposed current is applied. The impedance calculating unit calculates impedance for each of a plurality of frequency components using discrete Fourier transform from the superimposed current and the battery voltage. The diagnostic unit diagnoses the battery based on the impedance.

Abstract: A battery monitoring system includes a data acquiring unit and a failure determining unit. The data acquiring unit acquires a plurality of types of monitoring data to monitor a state of a secondary battery. The failure determining unit determines whether the secondary battery has failed. The failure determining unit performs sparsity regularization using the monitoring data as variables and calculates a partial correlation coefficient matrix of the monitoring data. The failure determining unit calculates, as an abnormality level, an amount of change in a partial correlation coefficient, which is a component of the partial correlation coefficient matrix, between two partial correlation coefficient matrices calculated at different periods. The failure determining unit determines that the secondary battery has failed when the calculated abnormality level exceeds a predetermined threshold.

Abstract: An image processing device includes a division circuit that divides an input image and outputs a plurality of divided images, a first processor that performs computation of an object detection model and acquires attribute information including an attribute value of an object included in each of the divided images and a first quadrangular frame surrounding the object as first metadata, a scaling circuit that output an overall image obtained by shrinking the input image, a second processor that performs computation of the object detection model and acquires attribute information including an attribute value of an object included in the overall image and a second quadrangular frame as second metadata, and a third processor that generates third metadata of the input image by combining pieces of the attribute information of the second metadata and pieces of attribute information that are not held in common by the first and second metadata.

Abstract: In the battery deterioration prediction system, a polarization calculation unit calculates negative and positive electrode polarizations from negative and positive electrode resistances, and an electrical current value flowing through the secondary battery. A CCP calculation unit calculates a negative electrode closed-circuit potential on the secondary battery negative electrode open circuit potential and the negative electrode polarization calculated by the polarization calculation unit, and calculates a positive electrode closed-circuit potential based on the secondary battery positive electrode open circuit potential and the positive electrode polarization calculated by the polarization calculation unit.

Abstract: An information calculation system acquires a battery load history of a secondary battery that has been used. The information calculation system calculates first degradation states of a plurality of battery constituent elements of the secondary battery, based on the battery load history acquired and a plurality of degradation factors related to each of the battery constituent elements. The information calculation system acquires estimated load information on a load that is estimated to act on the secondary battery when the secondary battery is used in a future application. The information calculation system calculates future second degradation states of the plurality of battery constituent elements of the secondary battery when the secondary battery is used in the future application, based on the first degradation states related to the battery constituent elements calculated, the estimated load information acquired, and the plurality of degradation factors related to the battery constituent elements.

Abstract: An object of the present invention is to provide a carbon fiber which exhibits excellent strength development rate when used in a composite material. The present invention that solves the problems is a carbon fiber which simultaneously satisfies the following formulae (1) and (2): Lc/d?3??(1) TS×d×Lc>6.0×105??(2) wherein: Lc is an X-ray crystallite size (?), d is a filament diameter (?m), and TS is a strand tensile strength (MPa).

Abstract: An object of the present invention is to provide a carbon fiber which exhibits excellent strength development rate when used in a composite material. The present invention that solves the problems is a carbon fiber which simultaneously satisfies the following formulae (1) and (2): Lc/d?3??(1) TS×d×Lc>6.0×105??(2) wherein: Lc is an X-ray crystallite size (?), d is a filament diameter (?m), and TS is a strand tensile strength (MPa).

Abstract: An embodiment is a data sequence correction method. The data sequence correction method including temporarily saving data with sequence information imparted thereto in a ring buffer, the ring buffer having a predetermined number of storage regions corresponding to the sequence information, and being provided with a monitoring section made up of one, or two or more consecutive sequence numbers, and an acceptance section in which a start or a second sequence number of the monitoring section is a start sequence number, and the sequence number ahead by a count of storage regions of the ring buffer including the start of the monitoring section is an end sequence number.

Abstract: A traffic monitoring apparatus includes: a header analysis circuit configured to acquire one or more identifiers from a header of a received packet; a rule registration circuit configured to convert a rule table including rules in which one or more rule elements are registered for each of the rules into a predetermined format and register the rule table in a rule matching circuit; and the rule matching circuit configured to search for rules to be matched with the acquired identifiers.

Abstract: A state detection circuit compares a target connection with an immediate previous connection based on an identifier of an incoming packet and detects a post-transitional state of the target connection based on a control flag of the incoming packet and on a pre-transitional state of the target connection detected just before if the target connection is identical with the immediate previous connection; and a connection counting circuit increments or decrements the number of target connections only when the detected post-transitional state indicates a start or end of the target connection.

Abstract: A network load balancing apparatus has a data buffer for each communication path of a received packet's transfer destinations, calculates a first hash value using a field value contained in the packet, determines, based on the field value of the packet or the first hash value, a communication path of a transfer destination of the packet subject to external transfer control for transmission to a predetermined external server, determines, based on the first hash value, a communication path of a transfer destination of the packet to be subject to priority control, determines, based on a second hash value based on the first hash value, a communication path of a transfer destination of the packet to be subject to load balancing control, to match a preset load balancing situation of the data buffer, and transmits the packet to a data buffer corresponding to the communication path of the transfer destination.

Abstract: The dataset supply unit supplies a learning dataset. The recognition unit outputs the recognition result for the recognition object data in the supplied learning dataset. Further, the intersection matrix computation unit computes the intersection matrix based on the learning dataset. The recognition loss computation unit computes the recognition loss using the recognition result, the intersection matrix, and the correct answer data given to the recognition object data. Then, the updating unit updates the parameters of the recognition unit based on the recognition loss.

Abstract: To provide a battery service life estimation system capable of improving estimation accuracy, a new battery service life estimation system includes an intersection time estimation unit and a service life estimation unit. In view of a relation between a cumulative usage period and a capacity retention0 rate of a secondary battery containing a non-aqueous electrolyte, the intersection time estimation unit estimates a prediction line intersection time tx when an anode service life prediction line intersects with a cathode service life prediction line on a plane coordinate system. The service life estimation unit estimates a battery service life by using the anode service life prediction formula before a point of the prediction line intersection time tx and the cathode service life prediction formula described the prediction line intersection time tx.

Abstract: A burst traffic detection device includes a packet receiver configured to receive packets from a network, a flow specification device configured to specify, in accordance with header information of the packets, flow rules, a flow information storage device configured to store flow information of the specified flow rules, a statistical information storage device configured to store statistical information including the total number of packets for each flow rule and/or the total number of bytes for each flow rule, a burst detection device configured to detect the occurrence of burst traffic in accordance with the statistical information, and a detection count storage device configured to store the number of times of the occurrence of burst traffic.

Abstract: A data sequence correction method for temporarily saving data with sequence information in a ring buffer and performing sequence correction is provided. The ring buffer includes a number of storage regions, a monitoring section having one or more continuous sequence numbers, and an acceptance section having a first or second sequence number of the monitoring section as a start sequence number and a sequence number immediately preceding the start sequence number of the monitoring section as an end sequence number. The method includes, when a value determined based on a remainder obtained by dividing a sequence number of received data by the number of storage regions is inside the acceptance section, writing the received data in a position of the storage region corresponding to the determined value, and when data are written in the entire monitoring section, reading out all the data in the monitoring section.