Abstract: According to one embodiment, a detection system includes an acquirer, a trainer, and a detector. The acquirer acquires first data, second data, and third data. The first data is based on an action of a first body part in a first work of a first worker having a first proficiency. The second data is based on an action of the first body part in the first work of a second worker having a second proficiency. The third data is based on an action of the first body part in the first work of a third worker. The trainer trains a recurrent neural network including a first output layer using the first data and the second data. The detector inputs the third data to the trained recurrent neural network and detects a response of the first neuron or the second neuron.

Abstract: According to one embodiment, a processing device causes a display of a first object at a position separated from a fastening location of a screw. The first object is virtual and indicates the fastening location. The processing device associates first data and second data when a prescribed physical object contacts the first object and the first data is received from a tool turning the screw. The second data is related to the fastening location.

Abstract: According to one embodiment, a production management device acquires a first short-term plan generated based on a first long-term plan. The first long-term plan is of a plan of production in a prescribed period. The first short-term plan is of a plan of production in a first period. The device acquires first progress data of a progress in a task, and acquires first prediction data by using the first progress data. The first prediction data is of a prediction of a progress in the task. The device revises the first short-term plan based on the first prediction data, and acquires second prediction data by using second progress data. The second progress data is of a progress in the task. The second prediction data is of a prediction of a progress of the production in the prescribed period. The device generates a second long-term plan in the prescribed period.

Abstract: According to one embodiment, a processing system estimates a pose of a worker, a position of an article, an orientation of the article, and a state of the article based on an image of the worker and the article. The processing system further estimates a work spot of the worker on the article based on an estimation result of the pose, an estimation result of the position, and an estimation result of the orientation. The processing system further estimates a task performed by the worker based on an estimation result of the work spot and an estimation result of the state.

Abstract: According to one embodiment, a training system includes a first generator, a second generator, a third generator, and a trainer. The first generator uses a human body model to generate a first image. The human body model models a human body and is three-dimensional and virtual. The second generator generates a teacher image by annotating body parts of the human body model in the first image. The third generator generates a second image including noise by performing, on the first image, at least one selected from first processing, second processing, third processing, fourth processing, or fifth processing. The trainer uses the second image and the teacher image to train a first model.

Abstract: According to one embodiment, an analysis device performs an analysis related to a plurality of tasks of a manufacturing process. The analysis device receives an image when each of the plurality of tasks is performed. The analysis device receives the images from an imaging device acquiring the images. The analysis device receives a detection signal from a tool used in at least one of the plurality of tasks. The detection signal is detected by the tool. The analysis device refers to end determination data for determining an end of each of the plurality of tasks. The analysis device determines the end of each of the plurality of tasks based on the images, the detection signal, and the end determination data.

Abstract: According to one embodiment, an information collection system comprises a transmitter, a receiver, and a processor. The transmitter emits a signal. The receiver receives the signal. The processor calculates a distance between the transmitter and the receiver from a strength of the signal received by the receiver. The processor calculating the distance between the transmitter and the receiver from the strength of the signal for each of the signals received during a first interval, and using an average distance as the distance between the transmitter and the receiver, the average distance being obtained by averaging the plurality of calculated distances.

Abstract: According to one embodiment, an analysis apparatus includes an acquisition unit and a processor. The acquisition unit acquires first information with a first time length between a first time and a second time. The first information is based on motion of an object person. The processor extracts multiple similarity points from the first information. The multiple similarity points are similar to each other in the first information. The processor calculates a time interval between the similarity points.

Abstract: According to one embodiment, a training device trains a first model. The first model estimates a period of a task from time-series data of an operation of a human. The device acquires first time-series data to which a label of the task is assigned. The device extracts a pattern from a period indicated by the label in the first time-series data. The pattern is used as a feature. The device generates timing data of an appearance timing of the pattern in the first time-series data. The device trains the first model by using the label, the first time-series data, and the timing data.

Abstract: According to one embodiment, a calculating device performs at least a calculation for a database system. A database of the database system is split into a plurality of partitions and placed in a plurality of nodes. The device is configured to accept statistical information relating to the plurality of partitions and the plurality of nodes and being collected by the plurality of nodes, and generate fluctuation information by using the statistical information and perturbation information. The perturbation information corresponds to statistical fluctuation of the statistical information. The device is configured to calculate a placement of the plurality of partitions in the plurality of nodes by using the statistical information and the fluctuation information. The placement is capable of improving a performance of the database system.

Abstract: According to one embodiment, a training system includes a first generator, a second generator, a third generator, and a trainer. The first generator uses a human body model to generate a first image. The human body model models a human body and is three-dimensional and virtual. The second generator generates a teacher image by annotating body parts of the human body model in the first image. The third generator generates a second image including noise by performing, on the first image, at least one selected from first processing, second processing, third processing, fourth processing, or fifth processing. The trainer uses the second image and the teacher image to train a first model.

Abstract: According to one embodiment, an analysis apparatus includes an acquisition unit and a processor. The acquisition unit acquires first information with a first time length between a first time and a second time. The first information is based on motion of an object person. The processor extracts multiple similarity points from the first information. The multiple similarity points are similar to each other in the first information. The processor calculates a time interval between the similarity points.

Abstract: According to one embodiment, an information collection system comprises a transmitter, a receiver, and a processor. The transmitter emits a signal. The receiver receives the signal. The processor calculates a distance between the transmitter and the receiver from a strength of the signal received by the receiver. The processor calculating the distance between the transmitter and the receiver from the strength of the signal for each of the signals received during a first interval, and using an average distance as the distance between the transmitter and the receiver, the average distance being obtained by averaging the plurality of calculated distances.

Abstract: According to one embodiment, a calculating device performs at least a calculation for a database system. A database of the database system is split into a plurality of partitions and placed in a plurality of nodes. The device is configured to accept statistical information relating to the plurality of partitions and the plurality of nodes and being collected by the plurality of nodes, and generate fluctuation information by using the statistical information and perturbation information. The perturbation information corresponds to statistical fluctuation of the statistical information. The device is configured to calculate a placement of the plurality of partitions in the plurality of nodes by using the statistical information and the fluctuation information. The placement is capable of improving a performance of the database system.

Abstract: According to one embodiment, an analysis apparatus includes an acquisition unit and a processor. The acquisition unit acquires first information with a first time length between a first time and a second time. The first information is based on motion of an object person. The processor extracts multiple similarity points from the first information. The multiple similarity points are similar to each other in the first information. The processor calculates a time interval between the similarity points.

Abstract: According to one embodiment, an information collection system comprises a transmitter, a receiver, and a processor. The transmitter emits a signal. The receiver receives the signal. The processor calculates a distance between the transmitter and the receiver from a strength of the signal received by the receiver. The processor calculating the distance between the transmitter and the receiver from the strength of the signal for each of the signals received during a first interval, and using an average distance as the distance between the transmitter and the receiver, the average distance being obtained by averaging the plurality of calculated distances.

Abstract: According to one embodiment, an analysis apparatus includes an acquisition unit and a processor. The acquisition unit acquires first information with a first time length between a first time and a second time. The first information is based on motion of an object person. The processor extracts multiple similarity points from the first information. The multiple similarity points are similar to each other in the first information. The processor calculates a time interval between the similarity points.

Abstract: According to one embodiment, an analysis apparatus includes an acquisition unit and a processor. The acquisition unit acquires first information with a first time length between a first time and a second time. The first information is based on motion of an object person. The processor extracts multiple similarity points from the first information. The multiple similarity points are similar to each other in the first information. The processor calculates a time interval between the similarity points.

Abstract: According to one embodiment, a detection system includes an acquirer, a trainer, and a detector. The acquirer acquires first data, second data, and third data. The first data is based on an action of a first body part in a first work of a first worker having a first proficiency. The second data is based on an action of the first body part in the first work of a second worker having a second proficiency. The third data is based on an action of the first body part in the first work of a third worker. The trainer trains a recurrent neural network including a first output layer using the first data and the second data. The detector inputs the third data to the trained recurrent neural network and detects a response of the first neuron or the second neuron.

Abstract: According to one embodiment, an analysis apparatus includes an acquisition unit and a processor. The acquisition unit acquires first information with a first time length between a first time and a second time. The first information is based on motion of an object person. The processor extracts multiple similarity points from the first information. The multiple similarity points are similar to each other in the first information. The processor calculates a time interval between the similarity points.