Abstract: A waypoint setting device sets a waypoint on the basis of a predictive distribution representing a demand prediction of occurrence points indicating positions from which a mobile object is called, position information indicating a position of a target mobile object that is a mobile object for which the waypoint is to be set, and destination information indicating information regarding a destination to which the target mobile object is to be moved. Then, the waypoint setting device outputs the set waypoint.

Abstract: A position estimation unit 25 estimates, for each movement in a predetermined section, a plurality of position candidates of a position estimation target on the basis of position information and sensor information. A position determination unit 26 evaluates, for each movement in the predetermined section, on the basis of the plurality of position candidates of the position estimation target obtained by the movement in the predetermined section, whether the position information used to estimate the position candidates has an error caused by any of a position of a GPS satellite, a position of a mobile body in a real space, or the mobile body or does not have any error caused thereby.

Abstract: A state estimation method executed by a state estimation apparatus including a processor and a memory storing program instructions that cause the processor to estimate a state related to congestion on a subject lane, includes acquiring a state related to congestion of a monitoring vehicle traveling on a non-subject lane, counting a number of vehicles traveling on the subject lane, the vehicles being overtaken by the monitoring vehicle or being oncoming vehicles passed by the monitoring vehicle, and estimating the state related to the congestion on the subject lane, using the state related to the congestion of the monitoring vehicle and the number of vehicles. In the estimating, when the number of the vehicles is equal to or greater than a threshold value according to the state related to the congestion of the monitoring vehicle, the state related to the congestion on the subject lane is estimated as traffic congestion.

Abstract: A vehicle condition estimation method performed by an information processing device including a processor and a memory connected to the processor to estimate a position or a condition of a vehicle, includes: acquiring an image including a vehicle to be estimated; and estimating the position or the condition of the vehicle to be estimated, using a line segment connecting at least two points selected from a region in which the vehicle to be estimated is captured in the image, with reference to an imaging device that has captured the image.

Abstract: A people flow prediction device includes a training data selection unit configured to select, in accordance with a prediction condition including a target prediction period subject to prediction, training data related to people flow data of a plurality of dates and times corresponding to the target prediction period, a prediction model creation unit configured to train, in accordance with the training data being selected, and store, in a model storage unit, a prediction model having a predetermined feature and for predicting people flow data of a predetermined date and time, and a prediction unit configured to select the prediction model from the model storage unit in accordance with the prediction condition and a permission condition related to a feature of the prediction model, and to predict people flow data under the prediction condition in accordance with the prediction model being selected.

Abstract: A hospital that has a high possibility of accepting a user can be predicted with good precision. An estimating method is an estimating method of estimating a prospect of a hospital accepting a user at a first time. In the estimating method, a prospect of accepting the user at the first time is estimated by correlating a reason of the hospital rejecting acceptance of a user at a second time, and an amount of time from the second time to the first time.

Abstract: Features serving as a basis for prediction can be explained. In an explanation creating method, with regard to a prospect of each of hospitals accepting a user, prediction results are found in advance using each of features including information relating to a reason of each of the hospitals rejecting acceptance of the user. Processing prescribed in advance is performed regarding each of features to be taken as an object, out of each of the features, and finds prediction results following modification. On the basis of a difference between prediction results using each of the features and prediction results following modification found regarding the features to be taken as an object, in a case in which there is a difference that satisfies a standard set in advance regarding each of the features to be taken as an object, creating an explanation regarding prediction results relating to the reason of rejection regarding this feature.

Abstract: Provided is a technique for efficiently predicting the number of occurrences of emergency medical service requests in a target area. At least patient attributes being attributes of patients, date/time information indicating dates and times of occurrences of emergency medical service requests, position information indicating places of the occurrences of the emergency medical service requests, and illness/injury information indicating illnesses and injuries that caused the emergency medical service requests are obtained. The illnesses and injuries are categorized into illness/injury groups, on a basis of a likelihood of occurrences of the illnesses and injuries in the illness/injury information obtained by bringing the patient attributes, the position information, and the date/time information into association with one another.

Abstract: Provided is a technique for efficiently predicting the number (quantity) of occurrences of emergency medical service requests in a target area.

Abstract: A slice management system (1) is a slice management system managing slices that are virtual networks generated on a network infrastructure, comprises a memory storing a priority list in which slices of connection destination candidates of a UE (2) are aligned in order of priority levels and, in a case in which a connection request for a slice from the UE (2) is acquired, determines a slice to which UE (2) is to be connected on the basis of the priority list stored in the memory.

Abstract: A slice management system is a system managing a slice that is a virtual network generated on a network infrastructure and includes a DNS storing slice information relating to a slice to which a UE can be connected for each area and determines whether or not the UE can, in a moving destination area that is a destination of movement of the UE between areas, be connected to a slice to which the UE was connected in a moving source area by referring to the DNS. In a case in which it is determined that the connection cannot be made, the slice management system generates the slice in the moving destination area such that the UE can be connected to the slice in the moving destination area.

Abstract: A slice management system (1) is a slice management system managing slices that are virtual networks generated on a network infrastructure, comprises a memory storing a priority list in which slices of connection destination candidates of a UE (2) are aligned in order of priority levels and, in a case in which a connection request for a slice from the UE (2) is acquired, determines a slice to which UE (2) is to be connected on the basis of the priority list stored in the memory.

Abstract: The number of response-waiting requests which are already sent to a server (4) but to which a response is not yet returned from the server (4) is limited. To limit this number, received requests are temporarily accumulated in a buffer if the number of response-waiting requests has reached a threshold and, until the number of response-waiting requests falls below the threshold, requests are not sent from the buffer. The execution status of the server (4) is monitored, and the threshold is increased when the response time from the server (4) to a request is within an allowable range, and the threshold is decreased when the response time exceeds the allowable range. In addition, TCP connections between a load control device (3) and clients (1-1, . . . , 1-n) are aggregated so that the number of simultaneous connections of TCP connections between the server (4) and the load control device (3) becomes equal to or smaller than the threshold of the number of response-waiting requests.

Abstract: The number of response-waiting requests which are already sent to a server (4) but to which a response is not yet returned from the server (4) is limited. To limit this number, received requests are temporarily accumulated in a buffer if the number of response-waiting requests has reached a threshold and, until the number of response-waiting requests falls below the threshold, requests are not sent from the buffer. The execution status of the server (4) is monitored, and the threshold is increased when the response time from the server (4) to a request is within an allowable range, and the threshold is decreased when the response time exceeds the allowable range. In addition, TCP connections between a load control device (3) and clients (1-1, 1-n) are aggregated so that the number of simultaneous connections of TCP connections between the server (4) and the load control device (3) becomes equal to or smaller than the threshold of the number of response-waiting requests.