Abstract: A signal processing device according to the present technology includes a feature quantity extraction unit including a neural network and trained to extract a feature quantity for a specific event with respect to an input signal from a sensor, and a correction unit that performs correction of the input signal on the basis of the feature quantity extracted by the feature quantity extraction unit.

Abstract: A signal processing device includes an approximate curved surface conversion unit that includes a first stacked autoencoder pretrained on the basis of learning input data constituted by coordinate data acquired for each of multiple elements of an object, and that obtains approximate curved surface data indicating an approximate curved surface of the object in an intermediate layer of the first stacked autoencoder, on the basis of input data constituted by the coordinate data acquired for each of the elements, and a geometric modulation processing unit that includes a second stacked autoencoder having learned by machine learning on the basis of learning input data constituted by the approximate curved surface data and on the basis of training data constituted by a result obtained by coordinate conversion for each of the elements in a geometric modulation process performed for the object, and performs the geometric modulation process.

Abstract: A signal transmission cable is provided with a conductor, an insulator covering around the conductor, a shield layer covering around the insulator, a sheath covering around the shield layer, and a plating base layer is provided between the insulator and the shield layer to cover around the insulator. The shield layer has a plating layer provided to cover the plating base layer to be in contact with an outer peripheral surface of the plating base layer. A surface roughness of an outer peripheral surface of the plating layer is less than a surface roughness of an inner peripheral surface of the plating layer.

Abstract: In a familiarity degree estimation apparatus, a first video process unit calculates a time while a hand being viewed, which is a time when a customer is viewing the hand. A second video process unit calculates a time while an item being held, which is a time when the customer is holding an item. A familiarity degree estimation unit calculates a time while the item being viewed based on the time while a hand being viewed and the time while the item being held, and estimates that the longer the time while the item being viewed, the lower the degree of familiarity of the customer with respect to the item.

Abstract: An item management apparatus manages the number of items displayed on an item shelf. An acquisition unit acquires an ideal quantity indicating an ideal number of items to be displayed, and a current quantity indicating the number of items being actually displayed on the item shelf. A detection unit detects the number of times of taking out and placing back an item with respect to the item shelf. An ideal quantity correction unit corrects the ideal quantity based on the current quantity and the number of times of taking out and placing back the item.

Abstract: A customer analysis apparatus (10) includes an image acquisition unit (110) and an image processing unit (120). The image acquisition unit (110) acquires a first image generated by a first image capture unit (22) and a second image generated by a second image capture unit (24). The image processing unit (120) processes the first image and the second image. More specifically, the image processing unit (120) generates product information indicating a product (50) taken out from a product shelf (40), by processing the first image and the second image. Further, the image processing unit (120) generates customer attribute information of a customer taking out the product (50), by processing the first image. Then, the image processing unit (120) causes a result storage unit (130) to store the product information and the customer attribute information in association with each other.

Abstract: In a familiarity degree estimation apparatus, a first video process unit calculates a time while a hand being viewed, which is a time when a customer is viewing the hand. A second video process unit calculates a time while an item being held, which is a time when the customer is holding an item. A familiarity degree estimation unit calculates a time while the item being viewed based on the time while a hand being viewed and the time while the item being held, and estimates that the longer the time while the item being viewed, the lower the degree of familiarity of the customer with respect to the item.

Abstract: A method of assessing a probe by measuring a known sample whose shape is known with the probe in an electronic microscope, the known sample having a projection part on a surface thereof, and the projection part having a shape tapered toward a vertex thereof, the method comprising a step of measuring circle equivalent radius of the projection part, a step of comparing the circle equivalent radius with a first threshold value, and a step of determining that the probe is satisfactory when the width is less than the first threshold value, and a step of determining that the probe is unsatisfactory when the width is equal to or greater than the first threshold value.

Abstract: To attain the object of providing a provider of a service with an environment in which service coordination allowing the provider to easily use user information in another service is carried out, included are: an identification unit that identifies a second service capable of providing user information to a provider of a first service; an inquiry unit that inquires, of a user who utilizes the first service, whether or not to consent to the provider of the first service using user information on the user in the second service at an opportunity of utilizing the first service; and a coordination unit that, in a case where information indicative of a consent of the user has been obtained, coordinates the first service and the second service by associating user information on the user in the first service and the user information on the user in the second service with each other.

Abstract: A signal processing device according to the present technology includes a stacked auto encoder that processes an input signal from a sensor, a control line associated learner including a neural network and subjected to control line associated learning for performing learning by associating different event aspects related to a specific event with values of different control lines with a feature quantity obtained in an intermediate layer of the stacked auto encoder after pretraining as an input, and a refactorer that obtains a difference between a first output that is an output of the control line associated learner when a first value is given to the control line, and a second output that is an output of the control line associated learner when a second value different from the first value is given to the control line.

Abstract: A signal processing device includes an approximate curved surface conversion unit that includes a first stacked autoencoder pretrained on the basis of learning input data constituted by coordinate data acquired for each of multiple elements of an object, and that obtains approximate curved surface data indicating an approximate curved surface of the object in an intermediate layer of the first stacked autoencoder, on the basis of input data constituted by the coordinate data acquired for each of the elements, and a geometric modulation processing unit that includes a second stacked autoencoder having learned by machine learning on the basis of learning input data constituted by the approximate curved surface data and on the basis of training data constituted by a result obtained by coordinate conversion for each of the elements in a geometric modulation process performed for the object, and performs the geometric modulation process.

Abstract: An information processing apparatus according to the present invention includes: a first acquisition unit that acquires a first biometric information from a body of a user who requests an execution of a procedure; a second acquisition unit that acquires a second biometric information of the user from a passport presented by the user; a third acquisition unit that acquires qualification information of the user; a matching unit that performs a matching process between the first biometric information with the second biometric information; and a determination unit that determines whether or not the user is a target person of the procedure based on a result of the matching process and the qualification information.

Abstract: A signal processing device according to the present technology includes a feature quantity extraction unit including a neural network and trained to extract a feature quantity for a specific event with respect to an input signal from a sensor. and a correction unit that performs correction of the input signal on the basis of the feature quantity extracted by the feature quantity extraction unit.

Abstract: A signal processing device according to the present technology includes a stacked auto encoder that processes an input signal from a sensor, a control line associated learner including a neural network and subjected to control line associated learning for performing learning by associating different event aspects related to a specific event with values of different control lines with a feature quantity obtained in an intermediate layer of the stacked auto encoder after pretraining as an input, and a refactorer that obtains a difference between a first output that is an output of the control line associated learner when a first value is given to the control line, and a second output that is an output of the control line associated learner when a second value different from the first value is given to the control line.

Abstract: A signal processing apparatus includes: a data input unit to which image data is input; an output unit configured to output an output value based on the data input to the data input unit; an expectation feedback calculator configured to calculate a difference between an expectation based on the input data and the output value; and a Bayesian estimator to which information on the difference and information based on the image data are input and which is configured to perform machine learning in order to approximate the output value to the expectation based on the input information and to search for an optimum configuration.

Abstract: A medical information terminal for input and display of medical information of a patient comprises a position information obtaining unit that obtains position information of the medical information terminal, an information concealing level setting unit that sets an information concealing level for description contents of each item of the medical information, and an information concealing unit that determines an information display threshold value indicating a threshold value at which the description contents of each item are displayed according to the position information obtained by the position information obtaining unit and conceals the description contents of each item if the information concealing level of each item of the medical information is at the information display threshold value or more.

Abstract: Provided is a technique that makes a user analyze a sample without stressing the user as much as possible. An analyzer is provided with a display unit and a display control unit for controlling the display unit. The display control unit causes the display unit to display predetermined information in a step in which the user is waiting among steps of analyzing the sample.

Abstract: Provided is a technique for making a user analyze a sample while providing convenience to the user. An information providing system is provided with a determination unit configured to determine whether or not the part needs to be replaced, a display unit, and a display control unit configured to control the display unit. The display control unit causes the display unit to display supplier information on a supplier of the part when the part needs to be replaced.

Abstract: A cantilever has a probe at a tip end. An optical system emits laser light to the cantilever and detects the laser light reflected by the cantilever. A measurement unit measures characteristics of a sample based on a displacement of the cantilever obtained by a change in a position of the laser light detected by the optical system. The laser light adjustment unit adjusts, when adjusting the optical axis of the laser light, a spot diameter of the laser light to be larger than the spot diameter when measuring the characteristics of a sample. The imaging unit captures an image of a range including the position of the probe when adjusting the optical axis of the laser light. The display unit displays the captured image.

Abstract: A scanning probe microscope 1 is provided with a control unit 15. The control unit 15 includes a signal acquisition processing unit 151, an image acquisition processing unit 152, a scanning condition change processing unit 154, a scanning processing unit 155, and a noise determination processing unit 156. In the scanning probe microscope 1, when removing noise included in a surface image of a sample, the scanning condition change processing unit 154 changes a scanning condition. And, the signal acquisition processing unit 151 acquires an output signal from a detection unit 12. The image acquisition processing unit 152 acquires a surface image of a sample S based on the output signal. The noise determination processing unit 156 determines whether or not noise is inclined in the output signal contains noise based on the change in the output signal or the change in the surface image of the sample S when the scanning condition is changed by the scanning condition change processing unit 154.