Abstract: According to one embodiment, a transport device includes a main part, a wheel, and a reader. The main part supports or pulls an object. The wheel is mounted to the main part, and rolls over a traveling surface. The reader is fixed with respect to the main part, and reads an identifier in a direction tilted with respect to a first direction and a second direction. The first direction is along the traveling surface, and the second direction is perpendicular to the traveling surface. The identifier is mounted to a surface, which crosses the first direction, of the object. A position of an area of the surface read by the reader changes along the second direction as the transport device moves in the first direction.

Abstract: A method for producing a polytetrafluoroethylene powder, which includes subjecting tetrafluoroethylene to suspension polymerization in an aqueous medium to prepare a suspension-polymerized particle of non melt-processible polytetrafluoroethylene, drying the suspension-polymerized particle to prepare a dry particle, subjecting the dry particle to fluorine radical treatment to prepare a fluorine radical-treated particle, and crushing the fluorine radical-treated particle to produce a polytetrafluoroethylene powder. Also disclosed is a polytetrafluoroethylene formed article obtained by forming the polytetrafluoroethylene powder, as well as a polytetrafluoroethylene compression-molded article obtained by compression molding the polytetrafluoroethylene powder.

Abstract: A method for producing a polytetrafluoroethylene particle, which includes subjecting tetrafluoroethylene to suspension polymerization in an aqueous medium to prepare a suspension-polymerized particle of polytetrafluoroethylene, washing and then crushing the suspension-polymerized particle or crushing the suspension-polymerized particle with washing to prepare a crushed particle, dehydrating the crushed particle to prepare a crushed particle having a water content of 40% by mass or less, and subjecting the dehydrated crushed particle to heat treatment to produce a polytetrafluoroethylene particle.

Abstract: A power generation element includes a magnetic member that produces a large Barkhausen effect and magnetism collection members including an insertion part having the magnetic member inserted therethrough. The magnetism collection member includes a first component on an opposite side of a boundary plane to a magnetic field generation unit and a second component on the same side of the boundary plane as the magnetic field generation unit, the boundary plane passing through a center of an imaginary circle inscribed in the insertion part and having a diameter equal to a length of the insertion part in a third direction perpendicular to first and second directions, the first direction is a direction of the insertion of the magnetic member, and the second direction is a direction in which the magnetic field generation unit is disposed. A volume of the second component is larger than a volume of the first component.

Abstract: An interference determination device includes a controller that determines interference between a robot and an object. The controller obtains a plurality of vertices of at least one object within a motion range of the robot in a real space and positional information regarding the plurality of vertices. The controller determines interference between the robot and the object in the real space on a basis of the plurality of vertices and the positional information.

Abstract: A sheet identification device includes a light irradiation portion. When forming an identification image, the light irradiation portion projects first pattern light (P11) and second pattern light (P12) having different dependences on a fiber direction of a surface of a sheet on an identification region (R1). The identification image is an image of the identification region (R1) of the surface of the sheet on which image formation or image reading is performed, which is used for identifying the fiber direction of the surface of the sheet.

Abstract: An object of the present invention is to determine the cause of an image defect that occurs in an image forming device with high accuracy while suppressing the amount of calculation at a processor. A processor (80) determines the cause of an image defect on the basis of a test image read from an output sheet of an image forming device (2). The processor (80) generates a plurality of feature images by executing a feature extraction process on the test image. Further, the processor (80) uses each of the plurality of feature images as an input image and determines which of a plurality of cause candidates corresponding to the image defect the input image corresponds to by pattern recognition of the input image.

Abstract: According to an embodiment, a transfer system comprises a mobile body, a detection object, and a first detecting part. The mobile body is configured to travel and to transfer an object. The detection object is mounted to the object. The detection object is located at a higher position than the object when referenced to a surface on which the mobile body travels. The first detecting part is located at a higher position than the object when referenced to the surface. The first detecting part detects the detection object.

Abstract: A processor determines an image defect in a test image obtained through an image reading process performed on an output sheet output by an image forming apparatus. The processor derives a vertical data string that is composed of data about horizontal representative values serving as representative values of a plurality of pixel values in each line in a horizontal direction in the test image. Moreover, the processor determines the presence or absence of at least one periodicity set in advance in the vertical data string by performing frequency analysis on the vertical data string. Furthermore, the processor determines the occurrence or non-occurrence and the cause of periodic density unevenness serving as a type of the image defect according to the determination result on the periodicity.

Abstract: An object of the present invention is to extract image defects from a test image for each type by a simple process. A processor (80) generates a first preprocessed image and a second preprocessed image by executing a main filter process with each of a horizontal direction and a vertical direction of the test image used as a processing direction. The main filter process is a process of converting the pixel value of each pixel of interest sequentially selected from the test image into a converted value obtained by a process of emphasizing the difference between the pixel values of an area of interest and the pixel values of two adjacent areas. The processor (80) extracts, as the image defects, a first singular part that is present in the first preprocessed image and is not common to both images, a second singular part that is present in the second preprocessed image and is not common to both images, and a third singular part that is common to both images.

Abstract: A moving body includes processing circuitry. The processing circuitry is configured to collect an external image of the moving body from an external sensor and collect information associated with an inner state of the moving body from an internal sensor. The processing circuitry is configured to determine whether or not to adopt the external image collected by the external sensor as a first image for estimating a position of the moving body, based on the information associated with the inner state of the moving body collected by the internal sensor. The processing circuitry is configured to estimate a position of the moving body by comparing the first image and a second image associated with a collection position of the first image.

Abstract: A processor identifies an original drawing part that is originally drawn in a test image. Furthermore, the processor identifies a noise point in the test image. Furthermore, the processor determines which of predetermined two types of cause candidates is a cause of the noise point by determining a degree of overlapping between the original drawing part and the noise point. The two types of cause candidates are: waste toner dropping in which waste toner that has adhered to a transfer body that transfers a toner image to a sheet, is transferred to the sheet in the image forming device; and carrier developing in which magnetic carrier that has been mixed with toner is transferred to a sheet.

Abstract: A vector generation unit derives a reference feature vector and a document feature vector. A feature quantity extraction unit performs a dimensionality reduction process on the reference feature vector and the document feature vector so as to set a dimensional value as a first feature quantity and derives a cosine similarity between the reference feature vector and the document feature vector as a second feature quantity. A grid division unit classifies documents into first partial regions obtained by dividing a feature quantity space of the first feature quantity, and classifies the documents into second partial regions obtained by dividing a range of the second feature quantity. A training data extraction unit selects, for each combination of a first partial region and a second partial region, a document classified in both the partial regions and sets documents selected with respect to all combinations as training data.

Abstract: A position estimating apparatus includes a memory that stores a reference image, an interface circuit configured to communicate with a movable apparatus, and a processor. The processor is configured to, upon receipt of at least one image captured by the movable apparatus via the interface circuit, calculate an evaluation value for each of a plurality of regions of the image, and determine a current position of the movable apparatus by comparing the regions of the captured image where the calculated evaluation value exceeds a first threshold with the reference image.

Abstract: A processor selects a target sheet from a plurality of predetermined sheet candidates in accordance with selection information that is input via an input device. Furthermore, the processor derives feature information regarding a noise point from a target image that is obtained through an image reading process performed on an output sheet output from an image forming device, the noise point being a dot-like noise image included in the target image. Furthermore, the processor determines whether or not the noise point is a dot-like sheet noise by applying the feature information to a determination algorithm that corresponds to the target sheet, the sheet noise being included in a sheet of the output sheet itself, the determination algorithm being one of a plurality of determination algorithms that respectively correspond to the plurality of sheet candidates.

Abstract: A vector generation unit derives a reference feature vector and a document feature vector. A feature quantity extraction unit performs a dimensionality reduction process on the reference feature vector and the document feature vector so as to set a dimensional value as a first feature quantity and derives a cosine similarity between the reference feature vector and the document feature vector as a second feature quantity. A grid division unit classifies documents into first partial regions obtained by dividing a feature quantity space of the first feature quantity, and classifies the documents into second partial regions obtained by dividing a range of the second feature quantity. A training data extraction unit selects, for each combination of a first partial region and a second partial region, a document classified in both the partial regions and sets documents selected with respect to all combinations as training data.

Abstract: A vector generation unit derives a feature vector of a reference document and a feature vector of a population document. A feature quantity extraction unit performs a dimensionality reduction process to reduce dimensionality of the above feature vectors and sets a dimensional value obtained by the dimensionality reduction process as a first feature quantity, and derives a cosine similarity between the feature vector of the reference document and the feature vector of the population document as a second feature quantity. A retrieval range control unit extracts a specific number of population documents, starting from the population document with the shortest distance to the reference document in a feature quantity space of the first feature quantity, so as to limit a retrieval range. A training data extraction unit extracts, as training data, a specific number of documents from the extracted documents, starting from the document with the lowest cosine similarity.

Abstract: A feature-amount extraction unit generates a base feature-map group constituted by a plurality of base feature maps from an input image, applies a plurality of statistic calculations to the base feature maps in the base feature-map group, and generates a plurality of types of statistic maps. The inference unit derives inference results of segmentation for inference inputs based on the plurality of statistic maps. Each of the plurality of types of statistic calculations described above is processing of calculating a statistic with a specific window size and a specific calculation formula, and the plurality of types of statistic calculations are different from each other in at least either one of the window size and the calculation formula.

Abstract: A detection system includes an acquisition portion scanning light to acquire point-cloud information corresponding to a plurality of positions of a detection target object; an estimation portion using consistency with an outer shape model of the detection target object to estimate a location and attitude of the detection target object based on the point-cloud information; and an output portion outputting information relating to a movement target location based on an estimation result, wherein the estimation portion fits an outer shape model indicating an outer shape of the detection target object to a point cloud according to the point-cloud information, and uses point-cloud information existing outside the outer shape model to estimate the location and the attitude of the detection target object.

Abstract: A processor generates an extraction image by extracting, from a test image, a target specific part that is a horizontal stripe extending in a horizontal direction or a noise point. The processor derives a vertical data sequence from a target area in the extraction image and converts the vertical data sequence to primary conversion data of a frequency domain. The processor converts, to secondary conversion data of a space domain, correction data that is obtained by removing, from the primary conversion data, data of frequency bands other than a particular frequency band corresponding to a target specific part that was determined as having periodicities. The processor classifies the target specific parts into periodic specific part and non-periodic specific part by comparing positions of the target specific parts with a peak position in a waveform represented by the secondary conversion data.