A two-part tissue thickness compensator assembly can include a first tissue thickness compensator configured to be positioned relative to an anvil of a surgical stapler, a second tissue thickness compensator configured to be positioned relative to a staple cartridge of the surgical stapler, and a hinge connecting the first tissue thickness compensator to the second tissue thickness compensator. The first and/or second tissue thickness compensators may include additional engagement features, such as a raised ridge that engages a slot in the anvil and/or the staple cartridge. In certain embodiments, the first and/or second tissue thickness compensators may include an encasement that contains a suitable biologic agent. An end effector assembly may be provided for attachment to a surgical instrument that includes, for example, a staple cartridge, an anvil, a first tissue thickness compensator positioned on the anvil, and a second tissue thickness compensator positioned on the staple cartridge.

Tissue thickness compensators

There is provided an information processing device including a display section configured to display a first object in a virtual three-dimensional space having a depth direction of a display screen, an operation section configured to acquire an operation for moving the first object in at least the depth direction, and a controller configured to move the first object on the display screen in accordance with the acquired operation, to execute, when a region of the first object overlaps a first overlap determination region, a first process to one or both of the first and second objects, and to execute, when the region of the first object overlaps a second overlap determination region, a second process to one or both of the first and second objects. The first overlap determination region may be a region obtained by extending the second overlap determination region in at least the depth direction.

Information processing device, information processing method, and program

A processing system includes methods to promote sleep. The system may include a monitor such as a non-contact motion sensor from which sleep information may be determined. User sleep information, such as sleep stages, hypnograms, sleep scores, mind recharge scores and body scores, may be recorded, evaluated and/or displayed for a user. The system may further monitor ambient and/or environmental conditions corresponding to sleep sessions. Sleep advice may be generated based on the sleep information, user queries and/or environmental conditions from one or more sleep sessions. Communicated sleep advice may include content to promote good sleep habits and/or detect risky sleep conditions. In some versions of the system, any one or more of a bedside unit 3000 sensor module, a smart processing device, such as a smart phone or smart device 3002, and network servers may be implemented to perform the methodologies of the system.

Methods and systems for sleep management

An image sensor of an electronic camera photoelectrically converts a subject image obtained by a shooting optical system to generate an image signal. A image processing section generates face registration image data and moving image data. A face detecting section detects a face area inside a shooting screen based on the moving image data. A controlling section adjusts shooting parameters of the shooting optical system, depending on a position detected at the face area. A face image generating section cuts out an image of the face area to generate face image data. A face recognizing data generating section extracts feature points of the face of a captured person from a part of the face area of the face registration image data and generates face recognizing data. A recording section records the face recognizing data or face image data.

Electronic Camera and Image Processing Device

A drive assist device allows a driver to favorably check space for opening a back door along with an image of a periphery of a vehicle. The drive assist device is configured: to perform a viewpoint conversion that converts an image captured by a vehicle-mounted camera, which image is of a scene in the periphery of the vehicle including at least an area rearward of the vehicle, into an overhead image showing the vehicle from above; to superimpose on the overhead image a graphic image showing a flip-up back door in an open state from the same viewpoint as that of the overhead image; and to allow the superimposed image to be displayed on a monitor device in a vehicle compartment.

Drive assist device

Provided are a physiological condition estimation device and a vehicle control device capable of preventing an error in the operation of an apparatus, such as a vehicle, and improving the safety of the operation of the apparatus. The physiological condition estimation device includes an eye-open time acquiring unit that acquires the eye-open time of the driver, a variation calculating unit that acquires a variation in the eye-open time acquired by the eye-open time acquiring unit, and a drowsiness predicting unit that determines the physiological condition of the driver on the basis of the variation in the eye-open time acquired by the variation calculating unit. In this way, since the physiological condition is determined on the basis of the variation in the eye-open time, it is possible to detect a slight reduction in the arousal level and estimate a significant reduction in the arousal level to a value that will cause an error in the driving of the vehicle in the future.

Physiological condition estimation device and vehicle control device

PROBLEM TO BE SOLVED: To automatically recognize the scene of a picture and the action intention of a person in the picture. SOLUTION: A picture processing part 12 extracts an object in a picture obtained by a photographing part 10. A recognizing part 14 decides the attribute of the extracted object (that is, whether or not the object is a person, and the action of a person when the object is a person, and the designation of a body when the object is a body). A scene recognizing part 18 selects the most certain scene based on the attribute of the object from among scene candidates. An estimating part 22 specifies the most matched action intention of the person from among the plural possible action intentions based on the action attribute of the person object in the recognized scene.

Scene recognizing device

A driving assistance apparatus includes a plurality of model candidates that define a correspondence relationship between a driving operation performed by a driver and information indicating relative positions of a moving body detected on a periphery of a host vehicle and the host vehicle. The driving assistance apparatus determines a model to be used from among the plurality of model candidates on the basis of information relating to the detected moving body, and executes driving assistance on the basis of the determined model and a driving operation performed by the driver following detection of the moving body. Preferably, the determined model can be updated on the basis of the determined model and the driving operation performed by the driver following detection of the moving body.

Driving assistance apparatus

A drowsiness level detection section (6) detects a drowsiness level of an individual person. A sleep depth level control section (11) controls the sleep depth of the individual person based on the detected drowsiness level. The sleep depth level control section executes a first sleep control (4, s7), in which the sleep depth level of the individual person is maintained at a predetermined sleep depth level below a maximum sleep depth level (4, s6), if the detected drowsiness level is equal to or below a predetermined threshold.

Sleep control device and control method therefor

PROBLEM TO BE SOLVED: To speedily evaluate a design. SOLUTION: Concerning this design evaluating device, the design prepared by a user is inputted from an input part 10. An element required for evaluating the design is extracted from the input design by an analytic part 12 and evaluated by an evaluation part 14. The evaluation part 14 is composed of a neural network or data base learnt based on the evaluation value of a teacher designer to the sample design, and the evaluation value of the input design is calculated and outputted to an output part 16. The evaluation value of the color balance or form balance of the design can include a function value as well.

Hiroki Okamura

Papers

Physiological condition estimation device and vehicle control device

Scene recognizing device

Driving assistance apparatus

Sleep control device and control method therefor

Design evaluating device and design preparing device and method