Abstract:
PROBLEM TO BE SOLVED: To derive an optimum arrangement configuration for allocating one or more virtual machines to one or more physical machines.SOLUTION: An arrangement configuration control device 120 includes a prediction unit 126 that determines a predicted peak usage amount of physical resources in each time section for each cluster containing a plurality of virtual machines having the same function; a setting unit 128 that sets a constraint condition for assuring that, when a physical machine 110 has failed in a time section, a predicted total peak usage amount of the physical resources for other physical machines 110 does not exceed a physical resource quantity prepared for the physical machines 110 for each combination of physical machines 110 and time sections; and an arrangement configuration deriving unit 132 for deriving the arrangement configuration by calculating a solution of an optimization problem that minimizes, as an object function, a total amount of physical resources of the whole of the plurality of physical machines to which the virtual machines are allocated according to the constraint condition.
Abstract:
PROBLEM TO BE SOLVED: To provide a system and the like for efficiently scheduling task distribution to an operation system for distributing tasks to a plurality of lots to be executed. SOLUTION: The system includes: (A) a task arrival time setting part for determining the task arrival time so as to equalize the processing standby time of the respective tasks for the respective lots; (B) a first start time adjustment part for adjusting each processing start time at one time of the overlapping period of the allowable time zone of the task processing for the respective tasks using an implement over the entire lots after the setting of the task arrival time is completed; and (C) a second start time adjustment part for adjusting the processing start time of implement non-using tasks so as to be equally distributed between adjacent implement using tasks for the respective lots after the adjustment of the processing start time of the implement using task is completed. COPYRIGHT: (C)2010,JPO&INPIT
Abstract:
PROBLEM TO BE SOLVED: To support determination of the efficient processing order of design process. SOLUTION: A system supports determination of a design process order. The system includes: a storage device that stores constraint data indicating a strength of a constraint that is given to each design process from each of the other design processes; a detection unit that accesses the storage device to detect, from the constraint data, a loop of relationships concerning a design process receiving a constraint from another design process; a selection unit that accesses the storage device to select, from the detected loop, a pair capable of canceling the loop when the pair is deleted and having a minimum total constraint strength; and an output unit that deletes the selected constraint pair from the constraint data and outputs data indicating a constraint that is to be satisfied by each design process. COPYRIGHT: (C)2009,JPO&INPIT
Abstract:
PROBLEM TO BE SOLVED: To solve the problems of conventional techniques being unable to define customer states in consideration of marketing actions and to obtain, as parameters of customer state, information on what kinds of effects marketing actions produce in the short and long terms. SOLUTION: In order to obtain customer state transition probabilities and short-term rewards conditioned by actions, customer behaviors are modeled with a hidden Markov model (HMM) using composite states each composed of a pair of a customer sate and a marketing action. Parameters of the estimated hidden Markov model (the composite state transition probabilities and a reward distribution for each composite state) are further transformed into the customer state transition probabilities and the distribution of rewards for each customer state conditioned by marketing actions. In order to model purchase properties in more detail, an inter-purchase time is always included as an element in the customer state vector, thereby allowing the customer state to have information on the probability distribution of the inter-purchase time. COPYRIGHT: (C)2008,JPO&INPIT
Abstract:
A method, a computer program product, and a system of adversarial semi-supervised one-shot training using a data stream. The method includes receiving a data stream based on an observation, wherein the data stream includes unlabeled data and labeled data. The method also includes training a prediction model with the labeled data using stochastic gradient descent based on a classification loss and an adversarial term and training a representation model with the labeled data and the unlabeled data based on a reconstruction loss and the adversarial term. The adversarial term is a cross-entropy between the middle layer output data from the models. The classification loss is a cross-entropy between the labeled data and an output from the prediction model. The method further includes updating a discriminator with middle layer output data from the prediction model and the representation model and based on a discrimination loss, and discarding the data stream.
Abstract:
The method includes the steps of : storing a plurality of parameter sets; selecting one of the plurality of parameter sets as a test parameter set to be evaluated; measuring performance only for one batch job out of N (N is a positive integer) batch jobs constituting full set performance measurement for the test parameter set; and calculating an evaluation value on the basis of a difference between an integral of measurement values obtained until the performance has been measured for r (r is a positive integer smaller than N) batch jobs by using the test parameter set; and an integral of mean measurement values of the performance for the r batch jobs by using an optimal parameter set which is one of the parameter sets used in the performance evaluation having been performed; determining whether or not the evaluation value has deviated from a predetermined evaluation continuing range; and terminating the evaluation of the test parameter set on condition that it is determined that the evaluation value has deviated form the evaluation continuing range toward performance deterioration. It is preferable that the predetermined evaluation continuing range be of a width from a width W where r is equal to zero, to a width W' (0