Abstract: Provided is a medical support arm system including a support arm that is a multilink structure having a plurality of links connected by a joint unit including an actuator, and supports a medical unit. The medical support arm system further includes a control device including an external force estimation unit to estimate an external force acting on the joint unit on the basis of a drive characteristic of the actuator, and a joint control unit to control drive of the joint unit on the basis of an external torque estimated by the external force estimation unit.

Abstract: An anti-vibration device is provided to enable improvement in a static spring constant of a bush in an axially perpendicular direction while suppressing an increase in a volume of the bush. A lower seat is formed to a position downward relative to a through hole on an axial end surface of a bush. The lower seat axially outwardly inclines downward to the outer circumferential surface of the bush. This lower seat enables suppression of an increase in a volume of the bush and improvement of a static spring constant of the bush relative to downward compressive deformation.

Abstract: A calculation scheme decision system includes a pre-calculation unit performing, in an execution environment in which calculation is performed, calculation for each of respective layers of the network structure using at least one of calculation schemes prepared in advance for the respective layers, a cost acquisition unit acquiring a calculation cost of at least one calculation scheme for each layer based on a result of the calculation by the pre-calculation unit, a decision unit selecting one calculation scheme for each layer based on the calculation cost from among at least one of the calculation schemes prepared in advance for the respective layers to associate the layer with the selected one calculation scheme, and a calculation unit performing the calculation for each of the respective layers of the network structure on input data in the execution environment using the calculation scheme associated with each layer.

Abstract: A training system comprises a training device, and a training data creation device for the training device. The training device trains a neural network by means of a backpropagation algorithm. The training data creation device acquires any one of a positive evaluation indicating that content of the input data coincides with the label, a negative evaluation indicating that content of the input data does not coincide with the label, and an ignorable evaluation indicating exclusion from a training target label, for each label regarding the input data to create training data.

Abstract: A training system comprises a training device, and a training data creation device. The training device trains a neural network. The training data creation device acquires any one of a positive evaluation indicating that content of the input data coincides with the label, a negative evaluation indicating that content of the input data does not coincide with the label, and an ignorable evaluation indicating exclusion from a training target label, for each label regarding the input data to create training data. In training the neural network for training, the training system adjusts the weight coefficient for the intermediate layer and makes the recognition score of the label with the ignorable evaluation not affect the adjustment of the weight coefficient for the intermediate layer.

Abstract: A calculation scheme decision system includes a pre-calculation unit performing, in an execution environment in which calculation is performed, calculation for each of respective layers of the network structure using at least one of calculation schemes prepared in advance for the respective layers, a cost acquisition unit acquiring a calculation cost of at least one calculation scheme for each layer based on a result of the calculation by the pre-calculation unit, a decision unit selecting one calculation scheme for each layer based on the calculation cost from among at least one of the calculation schemes prepared in advance for the respective layers to associate the layer with the selected one calculation scheme, and a calculation unit performing the calculation for each of the respective layers of the network structure on input data in the execution environment using the calculation scheme associated with each layer.

Abstract: An image processing device is provided. The image processing device includes: a tracking area setting section that sets a tracking area in a frame image of an original motion picture; a color information obtaining section that obtains color information of the tracking area set by the tracking area setting section; a tracking position estimating section that estimates a tracking position with reference to the tracking area with respect to each frame image of the original motion picture by using the color information obtained by the color information obtaining section; an output frame setting section that sets an output frame enclosing the tracking area set by the tracking area setting section and that updates the output frame based on the estimated tracking position; and a lock-on motion picture generating section that generates a motion picture that is based on the output frame.

Abstract: An object of the present invention is to provide an image processing device and the like that can generate a composite image in a desired focusing condition. In a smartphone 1, an edge detecting section 107 detects an edge as a feature from a plurality of input images taken with different focusing distances, and detects the intensity of the edge as a feature value. A depth estimating section 111 then estimates the depth of a target pixel, which is information representing which of the plurality of input images is in focus at the target pixel, by using the edge intensity detected by the edge detecting section 107. A depth map generating section 113 then generates a depth map based on the estimation results by the depth estimating section 111.

Abstract: A training system comprises a training device, and a training data creation device. The training device trains a neural network. The training data creation device acquires any one of a positive evaluation indicating that content of the input data coincides with the label, a negative evaluation indicating that content of the input data does not coincide with the label, and an ignorable evaluation indicating exclusion from a training target label, for each label regarding the input data to create training data. In training the neural network for training, the training system adjusts the weight coefficient for the intermediate layer and makes the recognition score of the label with the ignorable evaluation not affect the adjustment of the weight coefficient for the intermediate layer.

Abstract: An image processing device is provided. The image processing device includes: a tracking area setting section that sets a tracking area in a frame image of an original motion picture; a color information obtaining section that obtains color information of the tracking area set by the tracking area setting section; a tracking position estimating section that estimates a tracking position with reference to the tracking area with respect to each frame image of the original motion picture by using the color information obtained by the color information obtaining section; an output frame setting section that sets an output frame enclosing the tracking area set by the tracking area setting section and that updates the output frame based on the estimated tracking position; and a lock-on motion picture generating section that generates a motion picture that is based on the output frame.

Abstract: An object of the present invention is to provide an image processing device and the like that can generate a composite image in a desired focusing condition. In a smartphone 1, an edge detecting section 107 detects an edge as a feature from a plurality of input images taken with different focusing distances, and detects the intensity of the edge as a feature value. A depth estimating section 111 then estimates the depth of a target pixel, which is information representing which of the plurality of input images is in focus at the target pixel, by using the edge intensity detected by the edge detecting section 107. A depth map generating section 113 then generates a depth map based on the estimation results by the depth estimating section 111.

Abstract: An object of the present invention is to provide an image processing device and the like that can generate a composite image in a desired focusing condition. In a smartphone 1, an edge detecting section 107 detects an edge as a feature from a plurality of input images taken with different focusing distances, and detects the intensity of the edge as a feature value. A depth estimating section 111 then estimates the depth of a target pixel, which is information representing which of the plurality of input images is in focus at the target pixel, by using the edge intensity detected by the edge detecting section 107. A depth map generating section 113 then generates a depth map based on the estimation results by the depth estimating section 111.

Abstract: To provide a method for producing sepiapterin, lactoylpterin or tetrahydrolactoylpterin. Sepiapterin, lactoylpterin and tetrahydrolactoylpterin are produced at high yield through the following reaction scheme.

Abstract: To provide a method for producing sepiapterin, lactoylpterin or tetrahydrolactoylpterin. Sepiapterin, lactoylpterin and tetrahydrolactoylpterin are produced at high yield through the following reaction scheme.

Abstract: An object of the present invention is to provide an image processing device and the like that can generate a composite image in a desired focusing condition. In a smartphone 1, an edge detecting section 107 detects an edge as a feature from a plurality of input images taken with different focusing distances, and detects the intensity of the edge as a feature value. A depth estimating section 111 then estimates the depth of a target pixel, which is information representing which of the plurality of input images is in focus at the target pixel, by using the edge intensity detected by the edge detecting section 107. A depth map generating section 113 then generates a depth map based on the estimation results by the depth estimating section 111.

Abstract: According to an aspect of an embodiment, a server system includes a service processor, a plurality of system boards and a plurality of crossbar boards connecting the system boards. The service processor includes a first notifier that notifies each of the crossbar boards of a crossbar board subjected to maintenance. The crossbar boards each include a first transmitter that, when notified by the service processor that the crossbar board subjected to maintenance is another crossbar board, generates a suspension packet for suspending packet transmission to the another crossbar board and transmits the suspension packet to each of the system boards. The system boards each include a suspender that, when receiving the suspension packet from the crossbar board, suspends packet transmission to the crossbar board subjected to maintenance.

Abstract: According to an aspect of an embodiment, a server system includes a service processor, a plurality of system boards and a plurality of crossbar boards connecting the system boards. The service processor includes a first notifier that notifies each of the crossbar boards of a crossbar board subjected to maintenance. The crossbar boards each include a first transmitter that, when notified by the service processor that the crossbar board subjected to maintenance is another crossbar board, generates a suspension packet for suspending packet transmission to the another crossbar board and transmits the suspension packet to each of the system boards. The system boards each include a suspender that, when receiving the suspension packet from the crossbar board, suspends packet transmission to the crossbar board subjected to maintenance.

Abstract: When an uncorrectable error (UE) occurs in data read out from a second tag memory corresponding to a first tag memory of an arithmetic processing unit, a system controller issues a notification of WAY information of the second tag memory in which the UE has occurred to the arithmetic processing unit. The arithmetic processing unit degenerates a WAY of the corresponding first tag memory based on the received WAY information and issues a notification of completion of the degeneration process to the system controller. The system controller degenerates the WAY of the second tag memory in which the UE has occurred and re-issues a request relating to the UE after a notification that the degeneration process of the first tag memory is completed is received from the arithmetic processing unit.

Abstract: Cross bar control circuits are connected to each other by two buses, which are a broadcast bus for transmitting a broadcast packet from a system board to all system boards other than the system board and a point-to-point bus for transmitting a unicast packet from a system board to another system board. When unicast packets passing through the point-to-point bus are too many, the unicast packets are output by using the broadcast bus in addition to the point-to-point bus if the broadcast bus is not used. In this way, the unicast packets can be output quickly and efficiently, so that use efficiency of the broadcast bus and the point-to-point bus can be increased as a whole.

Abstract: An information processing device includes SBs; an XBB for executing data transfer between the SBs; and an SCF for managing and controlling the SBs and the XBB. The SB includes a transmitting/receiving unit for transmitting a notification packet indicating occurrence of an error via the XBB when detecting the occurrence of the error. The SCF includes an executing unit for executing a configuration change process corresponding to an instruction when detecting the instruction related to the SB, a suspending unit for suspending acceptance of an error report from the SB in which the error occurs during execution of the configuration change process and an XBB controller for controlling the XBB to destroy the notification packet received from the SB of which configuration change process is being executed and controlling the XBB to inhibit transfer of the notification packet to the SB of which configuration change process is being executed.