Abstract: A toner classification apparatus comprising a classification rotor in which the classification rotor has a vane A which extends from a rotation center direction of the classification rotor to an outer circumference direction thereof and a vane B having a length longer than that of the vane A, the vane A, and the vane B are disposed so as to satisfy a predetermined relationship, and a toner production method comprising a classification step of carrying out a classification process on particles to be classified by using the toner classification apparatus.

Abstract: The present invention is a method to determine an azimuthal orientation of a borehole seismometer sensor performed by a computing device using a control server having a database and an arithmetic function, the computing device performing a method to determine the azimuthal orientation of a borehole seismometer sensor using long-period surface waves in microseisms, including step S100 in which a data collection unit 100 collects continuous waveform data recorded by a borehole seismometer and a reference seismometer; step S200 in which a frequency band setting unit 200 sets a frequency band to be analyzed in the collected continuous waveform data; step S300 in which a filtering unit 300 performs bandpass filtering on the frequency band to be analyzed; step S400 in which a waveform dividing unit 400 divides seismic waveform into waveform segments with preset time units; step S500 in which a phase shift unit 500 shifts the phase of the divided vertical component waveforms by 90°; step S600 in which a waveform cal

Abstract: In one embodiment, a sensor device includes a sensor configured to obtain sensor data and a communication interface configured to communicate with a set of secondary sensor devices. The set of secondary sensor devices comprise a set of secondary sensors and a set of secondary processing devices. The set of secondary sensors obtain additional sensor data. The set of secondary processing devices process the additional sensor data based on a set of secondary machine learning models, and generate activation data based on the additional sensor data. The sensor device also includes a processing device. The processing device is also configured to receive the activation data from the set of secondary sensor devices and cause the sensor to obtain first sensor data based on the activation data. The processing device is further configured to generate one or more inferences based on the first sensor data and a machine learning model.

Abstract: A method of enhancing adhesion of an image to at least one surface of a substrate is provided herein. The method includes treating at least a portion of the surface by applying a composition comprising one or more polymers to the portion of the surface. The method further includes drying the composition after applying the composition to the substrate to form a treated substrate. The method further includes printing an image from an electrophotographic printer utilizing liquid toner technology on the treated substrate. The substrate is treated and dried less than about 5 minutes prior to being printed.

Abstract: An optical scanning device includes a light source and a beam detector for taking a main scanning start time of a light beam emitted from the light source and deflection-scanned by a deflection-scanning component to a predetermined main scanning direction. On the light source and the beam detector, the emission side of the light source and the light receiving side of the beam detector face the light-incident side of an f? lens, which is longer in the main scanning direction. The light source is arranged on the upstream side in the main scanning direction and the beam detector is arranged on the downstream side in the main scanning direction, or the beam detector is arranged on the upstream side in the main scanning direction and the light source is arranged on the downstream side in the main scanning direction.

Abstract: Systems and methods for processing sensor data and end of life detection are provided. In some embodiments, a method for determining the end of life of a continuous analyte sensor includes receiving a sensor signal from an analyte sensor. A plurality of risk factors associated with end of life symptoms of analyte sensors is evaluated. The risk factors include a downward drift in sensor sensitivity over time, an amount of non-symmetrical, nonstationary noise and a duration of noise. An end of life status of the analyte sensor is determined based at least in part on the evaluating. An output related to the end of life status of the analyte sensor is provided.

Abstract: A method, apparatus, and computer program product are provided to determine sensor orientation. In the context of a method, the orientation of a sensor is predicted based on a predetermined dataset. The method also includes receiving information regarding a location of the sensor and information from which a gravity direction of the sensor is derivable. The method further includes determining a relative orientation of the sensor in relation to a frame of reference and the gravity direction of the sensor. The method still further includes comparing the orientation of the sensor that was predicted and the relative orientation of the sensor to determine a prediction accuracy. The method finally includes updating the predetermined dataset based on the prediction accuracy of the sensor orientation.

Abstract: An image forming apparatus includes: a fixing portion for fixing an image formed on a recording material; and a guide member for guiding the recording material. The guide member is provided at an entrance to the fixing portion and at an end portion with respect to a direction perpendicular to a feeding direction of the recording material The guide member is moved when the guide member is pushed by the recording material.

Abstract: The present invention relates to miniature biosensor technology which can be directly embedded into medical device technology to create a new category of multifunctional smart medical devices. The resulting data from these smart medical devices results in wireless communication networks and standardized referenceable databases, which are used in the creation of best practice guidelines, clinical decision support tools, personalized medicine applications, and comparative technology assessment.

Abstract: Methods, systems, and devices for equipment monitoring and fault prediction are described, including: receiving measurement data associated with a set of equipment; providing at least a portion of the measurement data to a machine learning network; receiving an output from the machine learning network in response to the machine learning network processing at least the portion of the measurement data; and outputting a notification based on the output from the machine learning network, the notification including an indication of the predicted status. The processing of at least the portion of the measurement data may be based on a predictive model associated with the set of equipment. The output from the machine learning network may include a predicted status of the set of equipment.

Abstract: An exposure device includes: at least one light emitter that includes a substrate and a light-emitting device disposed on the substrate; and a position adjuster that includes a contact member having an outer periphery in contact with the substrate, a support member that rotatably supports the contact member, and at least one mover that is in contact with the support member to move the support member in a light emission direction of the light emitter.

Abstract: A relearning necessity determination method is provided for determining a necessity of relearning of a learned diagnostic model in a machine tool including a machining abnormality diagnosing unit. The machining abnormality diagnosing unit determines normal or abnormality of machining using the diagnostic model generated through machine learning. The method includes storing a cumulative cutting time or a cumulative cutting distance of a tool mounted to the machine tool as a tool usage, storing the tool usage when the machining abnormality diagnosing unit diagnoses the machining as machining abnormality, and determining the necessity of the relearning of the diagnostic model based on a frequency distribution of the tool usage stored in the storing of the tool usage.

Abstract: An abnormal temperature detection device includes a temperature acquirer configured to acquire temperature data, a preprocessor configured to perform preprocessing for calculating difference data indicating a difference sequence in the temperature data, generating substituted data in which either of a piece of difference data which is a positive number or a piece of difference data which is a negative number is substituted with zero, and calculating a similarity between the substituted data and reference data obtained from training data in which normality or abnormality has been identified, a learner configured to perform machine learning on the similarity calculated by the preprocessor and output an identification function, and a determiner configured to determine whether temperature data for detection acquired by the temperature acquirer and subjected to the preprocessing by the preprocessor is normal or abnormal by using the identification function.

Abstract: A test and measurement instrument, such as an oscilloscope, having a Nyquist frequency lower than an analog bandwidth, the test and measurement instrument having an input configured to receive a signal under test having a repeating pattern, a single analog-to-digital converter configured to receive the signal under test and sample the signal under test over a plurality of repeating patterns at a sample rate, and one or more processors configured to determine a frequency of the signal under test and reconstruct the signal under test based on the determined frequency of the signal, the pattern length of the signal under test, and/or the sample rate without a trigger.

Abstract: The present disclosure relates to a sensor system having at least one measuring point having at least one first sensor and one measuring transducer. The first sensor is configured to output first sensor signals that are a function of a first measurand of a measuring medium present at the measuring point. The measuring transducer is connected to the first sensor in order to receive the first sensor signals and comprises an evaluation application which is configured to determine one additional piece of information that is different from the first measurand using an evaluation algorithm on the basis of at least the first sensor signals. The sensor system furthermore comprises a higher-level data processing structure, such as a server or a cloud. Both the higher-level data processing structure and the measuring transducer are configured to execute a training application configured to train the evaluation algorithm.

Abstract: A method for predicting heaving motion parameters of a semi-submersible offshore platform based on heaving acceleration includes: in heaving motion of a semi-submersible offshore platform, representing heaving acceleration of the semi-submersible offshore platform based on a linear potential flow theory; considering a noise influence of a heaving motion measurement marine environment, a low-frequency influence caused by a slow change of the environment and an influence caused by a baseline drift error of an acceleration sensor, introducing a noise term, a low-frequency change term and a baseline drift error term, and uniformly representing the noise term, the low-frequency change term and the baseline drift error term by a unified Prony sequence; and removing a drift term from uniformly represented heaving acceleration, establishing a relationship between the heaving acceleration and heaving motion parameters in terms of the remaining Prony sequence with the drift term being removed, and estimating the heavin

Abstract: A toner container includes a container body, a gear, a held portion, an information storage device, a holding portion, and a connecting portion. The container body is rotatable around a rotation axis. The gear is disposed on a leading end of the toner container in the attaching direction of the toner container. The held portion is disposed such that the gear is exposed on the leading end in the attaching direction. The information storage device communicates with the body of the image forming apparatus. The holding portion is held by the held portion via the connecting portion. The information storage device, the holding portion, and the connecting portion are disposed at oblique positions excluding positions on a horizontal line and a vertical line. The connecting portion covers a part of the gear in a rotation direction and includes a rib-shaped portion that connects the held portion and the holding portion.

Abstract: A disruptor adjustment system comprising: a disruptor assembly configured to disrupt a volume of smelt flowing from a smelt spout into a dissolving tank, wherein the disruptor assembly comprises an actuator operatively engaged to a disruptor, a sensor configured to record process data from the recovery boiler; and a control system configured to receive a sensor output signal from the sensor, wherein the sensor output signal indicates the process data at a measured time, wherein the control system is further configured to compare the sensor output signal to a programmed operation range, and to send a disruptor input signal to the disruptor assembly to adjust a disruptor operating condition if the process data of the sensor output signal is outside of the programmed operation range. In certain exemplary embodiments, the sensor is an image capture device. In certain exemplary embodiments, the disruptor assembly can be adjusted remotely.

Abstract: An optical pulse measuring method measuring an optical pulse generated from a pulse light source is provided. The method includes: splitting the optical pulse and then focusing them at a measuring point, so as to generate gas plasma by the autocorrelation of the split optical pulses; receiving the sound signal from the gas plasma and generate a plasma sound signal; and using the plasma sound signal to calculate the characteristics of the optical pulse. A measuring device is also provided.

Abstract: A predictive engine includes an optimizer and a predictor. The optimizer is configured to receive an observed dataset having inputs and multivariate responses and determine latent response variables based on the predictive inputs and the multivariate responses. The optimizer is further configured to select latent response variables, measure dependencies between multivariate responses, estimate coefficients that relate the input predictors to determined latent response variables, and correlate dependencies and coefficients with the latent response variables. The predictor is configured to generate a predictive distribution of probabilities for the latent variables, map the probabilities to multivariate responses, generate a predictive distribution of probabilities for the multivariate responses, and determine at least one optimized input from the multivariate responses.