Abstract: An artificial intelligence system for training a classifier has a database of training data and a modeling system for building a classification model based on the training data. The database has a binary classification for each entity and binary tokens indicating whether or not one or more indicators about the entity are true. The classification model is based on a tempered indication of the tokens. The tempered indication is a ratio of a weighted sum of the tokens for each entity divided by a tempering factor for each of the entities. The tempering factor is a function of the unweighted sum of the tokens for each entity. Thus, the tempering factor will reduce the tempered indication when large numbers of low weight tokens are present so that the model does not over predict the probability of an entity being in the classification.

Abstract: A digital controller controls contingency discharges of a utility from a reservoir to a plant during a first time period and compensatory charges from the plant back to the reservoir during a second time period. The utility can be electric power. The plant and reservoir are connected by a grid. The reservoir may be any electric power storage device. When the utility is electric power, the contingency discharges make up for the power not generated by the plant due to an accident. The compensatory charges replenish the reservoir.

Abstract: A statistical facility event monitor has a computer implemented event percentile meter. The event percentile meter counts the number of randomly initiated events that cause a monitored facility to consume a monitored utility over a monitored time period. The event percentile meter then calculates a cumulative distribution function for the randomly initiated events. The event percentile meter uses the cumulative distribution to determine the event percentile for the monitored facility. The event percentile meter then outputs the event percentile.

Abstract: A computer-implemented semantic analysis system for ranking search results has instructions including the steps: receive a query about a first document authored by a person; read in data identifying the first document; read in a second document about the person authored after the first document; identify indicator terms in the second document related to whether or not there is a significant discrepancy between the second document and the first document; read in weighting factors for the identified indicator terms; determine an aggregate weighting factor that decreases with an increasing number of indicator terms found; and calculate a score of how much of a discrepancy there is between the second document and the first document using the weighting factors. When multiple first documents are returned for multiple persons, present the links in order from high score to low score.

Abstract: A digital controller controls discharges of a utility from a reservoir to a plant during a first time period and recharges of said utility from the plant back to the reservoir during a second time period. The reservoir can be any storage device. When the utility is electric power, the discharges make up for the power not generated by the plant due to an accident. The digital controller may use a balanced nonlinear transfer function to control the recharges based on the discharges. If there is a long duration discharge that extends beyond the end of the first time period, the digital controller may use a Monte Carlo simulation along with a tail distribution for the long duration discharge and the balanced transfer function to forecast the recharge required during the second time period.

Abstract: A system verifies whether or not an employee is actually on a job at a location during a standard time period, such as a work shift, by sending alerts to the employee's smart phone. The employee must respond to the alerts. The alerts are sent at random time intervals with a certain average rate. The average rate, called a Poisson parameter, can be varied over the course of a shift.

Abstract: A digital controller controls contingency discharges of a utility from a reservoir to a plant during a first time period and compensatory charges from the plant back to the reservoir during a second time period. The utility can be electric power. The plant and reservoir are connected by a grid. The reservoir may be any electric power storage device. When the utility is electric power, the contingency discharges make up for the power not generated by the plant due to an accident. The compensatory charges replenish the reservoir. The digital controller may use a transfer function nomogram to control the compensatory charges based on the contingency discharges.

Abstract: A digital controller controls contingency discharges of a utility from a reservoir to a plant during a first time period and compensatory charges from the plant back to the reservoir during a second time period. The utility can be electric power. The plant and reservoir are connected by a grid. The reservoir may be any electric power storage device. When the utility is electric power, the contingency discharges make up for the power not generated by the plant due to an accident. The compensatory charges replenish the reservoir. The digital controller may use a sectionally linear transfer function with a maximum to control the compensatory charges based on the contingency discharges. The transfer function may be balanced using a trim function so that on average, the compensatory charges will make up for the contingency discharges.

Abstract: A statistical facility monitor has a consumption percentile meter. The consumption percentile meter reads in utility consumption data from a monitored facility over a period of time. The consumption percentile meter then reads in a cumulative distribution of consumption percentile versus normalized utility consumption for similar reference facilities. The cumulative distribution is based on other facilities in the same facility class as the monitored facility. The consumption percentile meter uses the cumulative distribution to determine the consumption percentile for the monitored facility relative to the reference facilities. The meter then outputs the consumption percentile.

Abstract: A system verifies the location of a first person during a specified period by sending random alerts to the smart phone of the first person. A user must respond to the alerts. A second person defines acceptable locations. The smart phone has location measuring capability, such as a GPS or connection to a WAN. The identity of the user can be verified by requiring the input of a security code that also gives the user access to confidential information of the first person.

Abstract: A digital controller controls contingency discharges of a utility from a reservoir to a plant during a first time period and compensatory charges from the plant back to the reservoir during a second time period. The utility can be electric power. The plant and reservoir are connected by a grid. The reservoir may be any electric power storage device. When the utility is electric power, the contingency discharges make up for the power not generated by the plant due to an accident. The compensatory charges replenish the reservoir. The digital controller may use a sectionally linear transfer function with a maximum to control the compensatory charges based on the contingency discharges. The transfer function may be balanced using a trim function so that on average, the compensatory charges will make up for the contingency discharges.

Abstract: An artificial intelligence expert system detects an anomaly between an application and a publication provided by an applicant in a given class. The system calculates an application score then uses a decision tree to determine a publication score based on the presence or absence of tokens in the publication. An anomaly is detected when the ratio of the application score to the publication score is greater than a threshold value. The decision tree is trained using prior applications in the same class. The publication score of each leaf node of the decision tree is set equal to an average application score of the prior applications associated with the leaf node.

Abstract: An artificial intelligence system for training a classifier has a database of training data and a modeling system for building a classification model based on the training data. The database has a binary classification for each entity and binary tokens indicating whether or not one or more indicators about the entity are true. The classification model is based on a tempered indication of the tokens. The tempered indication is a ratio of a weighted sum of the tokens for each entity divided by a tempering factor for each of the entities. The tempering factor is a function of the unweighted sum of the tokens for each entity. Thus the tempering factor will reduce the tempered indication when large numbers of low weight tokens are present so that the model does not over predict the probability of an entity being in the classification.

Abstract: A payroll company makes use of networked peripherals located with a client company's employees to perform tasks like monitoring employee attendance at jobsites according to schedule, using attendance data to compute wages, benefits and insurance premiums, permitting instant employee access to payroll and benefit data, and permitting the client's managers to actively check up on employees' statuses.

Abstract: An artificial intelligence expert system for screening provides characteristic profiles to candidates to perform a particular task. The profiles have individual screening items within them that are expected to be related to whether or not a person is suitable for the task. The responses from the persons to the items are received by a computer implemented expert system. The expert system applies a combined model to the responses to generate a forecasted performance of the person to the task. The combined model is a linear combination of two or more path dependent regressions performed on data from a set of N training persons with known abilities to do the task. The number of parameters in each path dependent model is limited to a fraction of the number N so that the path dependent models are not over fit to the data. A suitable fraction is ?.

Abstract: A stable board book has multiple stiff pages bound together and a stand connected to an end panel for holding the pages vertical when the book is put on a surface and each page is opened. The stand is attached by a hinge to the top cover of the book and by a hinge to the end panel. The end panel is attached by a hinge to the ventral edge of the bottom page of the book. The length of the stand is at least ½ of the length of the cover so that when the pages are opened and leaned against the stand, they will be stable and not fall back down.

Abstract: A reinsurance participation plan allows an insurance carrier to provide novel loss participation plans to insureds. The insurance carrier cedes a portion of the risk to a reinsurance company, such as a captive reinsurance company. The captive reinsurance carrier then enters into a contractual agreement with the insured for the participation plan, subject to the appropriate regulations for the primary line of insurance in question. The participation plan may be a non-linear participation plan, such as a curvilinear participation plan, where the non-linearities allow the plan to be offered to smaller companies than would otherwise qualify for more traditional retrospective participation plans, and to provide more advantageous plans to larger companies than they would otherwise be offered. The plans may be offered on a multi-year basis with particular diligence in informed consent for the prospective insured.