Abstract: An operation assistance system for a small watercraft includes: a position specification unit that specifies an abnormality occurrence position, which is a position where an abnormality has occurred, when the abnormality has occurred in a small watercraft; a transmission unit that transmits information on the abnormality occurrence position specified by the position specification unit; and a processing circuit, in which the processing circuit includes a storage unit that stores information on the abnormality occurrence position transmitted from the transmission unit, and an information provision unit that creates predetermined operation assistance information based on information on the abnormality occurrence position stored in the storage unit and transmits the created operation assistance information.

Abstract: The present invention provides a protein having pentosidine oxidase activity, a method for measuring pentosidine comprising: contacting the protein with a specimen; and detecting a change caused by the contact, and the like.

Abstract: The inconsistency determination device 1 includes inconsistency determination means 9. The inconsistency determination means 9 determines whether or not there is inconsistency in an expression, which is to be converted into an energy function of a model representing states of individual spins by a first value or a second value, representing energy in a combinatorial optimization problem.

Abstract: A data processing apparatus (1) of the present invention includes a unit that retrieves a predetermined subject from moving image data. The data processing apparatus includes a person extraction unit (10) that analyzes moving image data to be analyzed and extracts a person whose appearance frequency in the moving image data to be analyzed satisfies a predetermined condition among persons detected in the moving image data to be analyzed, and an output unit (20) that outputs information regarding the extracted person.

Abstract: The feature information derivation means 72 derives feature information that represents a feature of a model used to solve a combinatorial optimization problem, when the model is given. The solution method selection means 73 selects a solution method for the combinatorial optimization problem from among predetermined multiple types of solution methods based on the feature information. The solution request means 74 send a solution request that includes information that can specify the model used to solve the combinatorial optimization problem to a solution device that solves the combinatorial optimization problem using the selected solution method.

Abstract: The conversion means 72 generates a program for deriving a QUBO matrix that is a matrix that defines an energy function of QUBO, by converting a description of a natural language representing a combinatorial optimization problem into a description of the program for deriving the QUBO matrix. It is possible to generate a program for deriving a QUBO matrix based on a description of a natural language representing a combinatorial optimization problem.

Abstract: An information processing device that compares a data amount of a QUBO model to be processed by an annealing engine and a data amount of a program representing the QUBO model, and that transmits whichever has a lower data amount to the annealing engine.

Abstract: The annealing execution means 73 executes annealing using an energy function, when a solution to a combinatorial optimization problem, and the energy function of a model representing states of individual spins by a first value or a second value which is used to obtain the solution are given, and derives multiple new solutions to the combinatorial optimization problem. The solution determination means 74 determines a solution from among the multiple solutions derived by the annealing execution means 73, based on a solution determination rule for determining a solution among the multiple new solutions and the given solution to the combinatorial optimization problem.

Abstract: An optimization device includes a determination unit which determines weights for a plurality of constraint conditions imposed on a combinatorial optimization problem, respectively, and a generation unit which generates an energy function for the combinatorial optimization problem using a constant that is a sum of a constant used in formulation of an energy to be optimized in the combinatorial optimization problem and a sum over the plurality of constraint conditions of a constant used in formulation of an energy of one constraint condition multiplied by a weight determined for the one constraint condition.

Abstract: The difference matrix calculation means 72 calculates a difference matrix which is a difference between a first matrix representing a combinatorial optimization problem for which a solution was found last time and a second matrix representing the latest combinatorial optimization problem. The difference matrix compression means 73 compresses the difference matrix. The transmission means 74 transmits the difference matrix after compression to a combinatorial optimization problem solution device that finds a solution to the combinatorial optimization problem.

Abstract: A state output system includes a solving unit which executes a solving process for solving a combinatorial optimization problem by a simulated annealing method, an acquiring unit which acquires data indicating states of the solving process in execution from the solving unit, and an outputting unit which outputs the acquired data during the execution of the solving process.

Abstract: A solution accuracy guaranteeing annealing calculation device includes a first solving unit which solves a combinatorial optimization problem by an annealing method, and a second solving unit which solves a relaxation problem, which is a problem generated by relaxing constraints imposed on the combinatorial optimization problem, wherein the second solving unit calculates, if the combinatorial optimization problem is a minimization problem, a lower bound of a minimization target in the minimization problem by solving the relaxation problem generated from the combinatorial optimization problem, and calculates, if the combinatorial optimization problem is a maximization problem, an upper bound of a maximization target in the maximization problem by solving the relaxation problem generated from the combinatorial optimization problem.

Abstract: The term generation means 73 generates a term, when a solution to a combinatorial optimization problem, an energy function, which is used to obtain the solution, of a model representing states of individual spins by a first value or a second value, and a pair of identification information of spin and degree of wish to change which indicates degree to which an user wishes to change state of spin corresponding to the identification information in the solution are given, wherein the term is generated for each pair of the identification information and the degree of wish to change, based on the state of spin corresponding to the identification information in the solution and the degree of wish to change. The energy function derivation means 74 deriving a new energy function by adding terms generated by the term generation means 73 for each pair to the energy function.

Abstract: An information processing device includes: a feature quantity obtaining unit which obtains a feature quantity of an object to be extracted, which is extracted from a retrieval target, and specific information to be specified an appearing location of it; a feature quantity holding unit which, when storing the feature quantity in a feature quantity table, adds new identification information to the feature quantity and holds the feature quantity in the feature quantity table when a similar feature quantity in which a similarity with the feature quantity is no less than a threshold is not included in the feature quantity table, and outputs identification information of the similar feature quantity as identification information of the feature quantity when the similar feature quantity is included in the feature quantity table; and a retrieval table holding unit which holds the specific information associated with the added identification information or the outputted identification information.

Abstract: A computation unit 11 performs, for each column of a target matrix to be standardized, a computation process to compute the average and standard deviation of the value of each component of the column. A first dividing unit 12 performs, for each column of the target matrix, a first dividing process to divide the value of each component of the column by the standard deviation computed based on the column. A second dividing unit 13 performs, for each column of the target matrix, a second dividing process to divide the average computed based on the column by the standard deviation computed based on the column. A generation unit 14 which arranges the quotients computed by a plurality of second dividing processes, in a row in the order of the columns of the target matrix from which the quotients are computed, thereby generating a row vector.

Abstract: Provided is an analysis apparatus (10) including a person extraction unit (11) that analyzes video data to extract a person, a time calculation unit (12) that calculates a continuous appearance time period for which the extracted person has been continuously present in a predetermined area and a reappearance time interval until the extracted person reappears in the predetermined area for each extracted person, and an inference unit (13) that infers a characteristic of the extracted person on the basis of the continuous appearance time period and the reappearance time interval.

Abstract: A parallel union control device includes: at least one memory storing a set of instructions; and at least one processor configured to execute the set of instructions to cause each of the plurality of arithmetic units included in an parallel computer including a vector register to: successively compare input elements of a pair of input sets to undergo union processing, the pair being stored in an input operand register in the vector register; select one of the input elements as an output element of an output set, based on a comparison result; and store the output element into an output operand register in the vector register; shift a pointer pointing to the input element; load the input sets into the input operand register from a memory; store the output sets into the memory from the output operand register; and determine whether union processing performed in parallel is ended.

Abstract: Provided is an analysis apparatus (10) including a person extraction unit (11) that analyzes video data to extract a person, a time calculation unit (12) that calculates a continuous appearance time period for which the extracted person has been continuously present in a predetermined area and a reappearance time interval until the extracted person reappears in the predetermined area for each extracted person, and an inference unit (13) that infers a characteristic of the extracted person on the basis of the continuous appearance time period and the reappearance time interval.

Abstract: Provided are an area allocation device and the like that can efficiently allocate memory volume for processing of matrix operations. The area allocation device specifies array identifiers representing positions of elements storing a value different from a predetermined value in each array of subarray information in array information, arrays consisting of a plurality of element, the array information including a plurality of information representing the arrays, the subarray information corresponding to at least a part of the arrays; calculates a number of the specified array identifiers; and allocates a memory area having a memory volume depending the calculated number.

Abstract: Provided is an analysis apparatus (10) including a person extraction unit (11) that analyzes video data to extract a person, a time calculation unit (12) that calculates a continuous appearance time period for which the extracted person has been continuously present in a predetermined area and a reappearance time interval until the extracted person reappears in the predetermined area for each extracted person, and an inference unit (13) that infers a characteristic of the extracted person on the basis of the continuous appearance time period and the reappearance time interval.