Abstract: In at least some implementations, a charge forming device includes a main body having a throttle bore, a throttle valve, a housing and a circuit board including a throttle position sensor and a pressure sensor. The throttle valve is received at least partially within the valve bore, is rotatable between an idle position and a second position, and includes a magnet that is rotated when the throttle valve rotates. The housing is carried by the main body, and the circuit board is carried by the housing. A signal path is defined leading from the pressure sensor to a pressure source, the signal path includes a liquid collection area located below a gaseous area with respect to gravity.

Abstract: An etching method includes providing a substrate including an etching target layer including a silicon-containing layer, and a mask located on the etching target layer, comprising a metal, and having an opening defined by a side wall of the mask, supplying a process gas including a metal-containing gas, and etching, with plasma generated from the process gas, the etching target layer through the opening while forming a protective layer comprising a metal on a top of the mask and on the side wall of the mask.

Abstract: A non-aqueous electrolyte secondary battery according to one embodiment, wherein a mixture layer of an electrode has a first layer formed on a core body, and second and third layers formed on the first layer. The first, second, and third layers contain a binding agent, and the third layer is formed on at least a part of an end of the electrode. The content of the binding agent in the third layer is higher than the content of the binding agent in the first layer, and is greater than 0.8 mass % and less than 2.0 mass %.

Abstract: The function input means 71 accepts input of a cost function that calculates a cost incurred in at least one of a selection of a candidate relay point and a design of a route, the cost function being represented as a linear sum of terms weighted by degree of importance attached to each of the features that an expert is assumed to intend when selecting the candidate relay point and design of the route. The learning means 72 learns the cost function by inverse reinforcement learning using training data that includes relay point information which is data that maps information indicating a relay point with surrounding information of the relay point and usage information of the relay point, and route result information which is result data of a route that pass through each relay point.

Abstract: A tampering detection device includes tampering detection circuitry configured to acquire an access pattern of a monitoring target file, extract a time-series pattern of access for each monitoring target file from the access pattern acquired, and determine a scan pattern on a basis of the time-series pattern of access extracted.

Abstract: An input unit 81 receives inputs of pre-change performance data acquired by a device before a change and post-change performance data acquired by the device after having undergone the change, through control using a first cost function. An update unit 82 generates a second cost function obtained by updating the first cost function in such a way as to reduce a difference between the pre-change performance data and the post-change performance data. In the process, the update unit 82 generates the second cost function obtained by updating the first cost function by estimating an error that occurs in an output value of the device included in the first cost function before and after the change to the device.

Abstract: A classification apparatus according to the present disclosure includes an input unit configured to receive an operation performed by a user, an extraction unit configured to extract moving image data by using a predetermined rule, a display control unit configured to display an icon corresponding to the extracted moving image data on a screen of a display unit, a movement detection unit configured to detect a movement of the icon on the screen caused by the operation performed by the user, and a specifying unit configured to specify a classification of the moving image data corresponding to the icon based on a position of the icon on the screen.

Abstract: A focus adjustment method for a charged particle beam device having a magnetic field lens used for focus adjustment and an astigmatism corrector includes: acquiring a plurality of first images by varying an excitation current of the magnetic field lens within a focus search range, and determining a reference value of the excitation current; removing hysteresis from the magnetic field lens by setting the excitation current of the magnetic field lens outside the focus search range before and after varying the excitation current of the magnetic field lens within the focus search range; and acquiring a plurality of second images by varying the excitation current of the magnetic field lens using the reference value as a reference and varying a stigma correction value of the astigmatism corrector at each excitation current, and then determining optimum values of the excitation current and the stigma correction value.

Abstract: The present invention provides a processing apparatus (10) including: a determination unit (12) determining a predetermined vehicle state and a predetermined ambient environment, based on user vehicle data indicating a vehicle state and an ambient environment when a user uses a vehicle; a computation unit (13) computing a degree of similarity between the predetermined vehicle state and the predetermined ambient environment, and a vehicle state and an ambient environment indicated by a vehicle running test scenario; and an output unit (14) outputting a computation result by the computation unit (13).

Abstract: A comfort determination model learning unit 81 learns a comfort determination model, by using comfortable activity data where a comfort indicator, which is an indicator measuring whether an individual is comfortable or not when an activity classified as a comfortable activity is performed, is associated with a teacher label indicating comfort, and uncomfortable activity data where the comfort indicator when an activity classified as an uncomfortable activity is performed, is associated with a teacher label indicating discomfort, as first training data, taking an objective variable for a comfort value indicating a degree of comfort, and taking an explanatory variable for each of the comfort indicators. An individual data generation unit 82 generates individual data including explanatory variables, which are used in the comfort determination model, generated based on the comfort indicators of the subject during riding on a vehicle, and driving situations of the vehicle when the comfort indicators are obtained.

Abstract: A dangerous scene prediction device 80 for predicting a dangerous scene occurring during driving of a vehicle includes a learning model selection/synthesis unit 81 and a dangerous scene prediction unit 82. The learning model selection/synthesis unit 81 selects, from two or more learning models, a learning model used for predicting the dangerous scene, depending on a scene determined based on information obtained during the driving of the vehicle. The dangerous scene prediction unit 82 predicts the dangerous scene occurring during the driving of the vehicle, using the selected learning model.

Abstract: An apparatus that extracts an explanatory variable used as a condition from a classification model classified by the condition for selecting a component used for prediction, displays the explanatory variable in association with any of dimensional axes of a multi-dimensional space in which a prediction value is displayed, specifies the component that corresponds to a position in the multi-dimensional space specified by each of the explanatory variables associated with the dimensional axis, displays the prediction value calculated based on the specified component, on the same position and displays the multi-dimensional space that corresponds to the position in which the prediction value is displayed, in a mode that corresponds to the component used for calculating the prediction value.

Abstract: A focus adjustment method for a charged particle beam device having a magnetic field lens used for focus adjustment and an astigmatism corrector includes: acquiring a plurality of first images by varying an excitation current of the magnetic field lens within a focus search range, and determining a reference value of the excitation current; removing hysteresis from the magnetic field lens by setting the excitation current of the magnetic field lens outside the focus search range before and after varying the excitation current of the magnetic field lens within the focus search range; and acquiring a plurality of second images by varying the excitation current of the magnetic field lens using the reference value as a reference and varying a stigma correction value of the astigmatism corrector at each excitation current, and then determining optimum values of the excitation current and the stigma correction value.

Abstract: An explanatory variable display means 81 extracts an explanatory variable used as a condition from a classification model classified by the condition for selecting a component used for prediction and displays the explanatory variable in association with any of dimensional axes of a multi-dimensional space in which a prediction value is displayed. A prediction value display means 82 specifies the component that corresponds to a position in the multi-dimensional space specified by each of the explanatory variables associated with the dimensional axis, and then, displays the prediction value calculated on the basis of the specified component, on the same position. A space display means 83 displays the multi-dimensional space that corresponds to the position in which the prediction value is displayed, in a mode that corresponds to the component used for calculating the prediction value.

Abstract: An estimation data input unit 90 inputs estimation data including one or more explanatory variables which are information that may influence deterioration of an object. A component determination unit 91 determines a component to be used for estimation of deterioration of the object based on a hierarchical latent structure, which is a structure in which latent variables are represented by a tree structure and each of the components representing a probability model is assigned to each node at the lowest level of the tree structure, a gate function to determine a branch direction at each node of the hierarchical latent structure, and the estimation data. A deterioration estimation unit 92 estimates the deterioration of the object based on the component determined by the component determination unit 91 and the estimation data.

Abstract: Provided are a motion recognition apparatus, a motion recognition system and a motion recognition method that enable ‘event motions’ to be recognized with a small number of calculations. The motion recognition system, which recognizes user motions by using sensor data, is configured to be provided with: a cyclical loss detection means for detecting cyclical losses of sensor data when a user is moving; and a recognition processing means for setting data intervals to be used for recognizing motions in accordance with the cyclical losses of sensor data that were detected, and for recognizing user motions on the basis of sensor data for the data intervals that have been set.

Abstract: An information terminal includes the following: an extraction unit that extracts, as change frequency information, at least one of the change frequency of index data and the change frequency of the movement state of a user, which are indicated by acquired index data; a setting unit that, based on the extracted change frequency information, sets a rule for controlling the sleep state of an estimation unit that estimates the movement state of the user; and a control unit that, based on the set rule, controls the sleep state of the estimation unit.

Abstract: A position information providing apparatus includes a sensor data acquiring unit acquiring sensor data, a feature amount calculating unit calculating a feature amount from the sensor data, and a confidence level calculating unit calculating a confidence level using the feature amount, wherein the sensor data is more than one, and the feature amount includes a statistical amount of more than one piece of the sensor data and an amount showing a form of the sensor data.

Abstract: An upper structure for a sports shoe is provided that can not only enhance holdability as an upper but also improve wearer's touch on a foot. In the upper structure for the sports shoe, the upper is formed of a knitted fabric having thermally fusible yarn and another knitted fabric having no thermally fusible yarn. In the knitted fabric having the thermally fusible yarn, the thermally fusible yarn is disposed on an outer surface side of the upper, and on an inner surface side of the upper, a front yarn and a back yarn are arranged in a parallel relationship. The thermally fusible yarn is fusion-bonded and cured in the knitted fabric by heat treatment and the outer surface side of the upper 1 is thus hardened than the inner surface side of the upper.

Abstract: There are provided: a demand forecasting section that calculates a demand forecast value of the power system as a whole; a supply planning section that calculates a planned supply value of the power system as a whole; a difference extraction section that finds the difference between said demand forecast value and planned supply value; an economic load allocation section of a distribution system that allocates the difference obtained by the difference extraction section with respect to control subjects provided in the distribution system, in accordance with a cost optimization technique; and a control section that outputs control amounts based on the allocated amounts obtained by the economic load allocation section of said distribution system to the control subjects.