International Business Machines Corporation

Edward John Pring

Young Min Lee

Jayant R Kalagnanam

David Michael Chess

Christian Makaya

John Frederick Morar

Nam H Nguyen

Kyong Min Yeo

James P Hofmeister

Hui Qi

Geoffrey M Bartlett

Jeffrey Owen Kephart

Anton Viktorovich Riabov

Yuan-Chi Chang

Deepak Srinivas Turaga

Steve Richard White

Nagui Halim

Octavian Udrea

Shirin Sohrabi Araghi

Mark David Feblowitz

Dhaval Patel

Stuart S Horn

Edward W Shay

Fang Yuan

Derald D Nye

Peter Zimmer

Ian N Whalley

Alla Segal

Sophia Krasikov

Dhavalkumar C Patel

David W Levine

Michael W Pousson, Jr

Nancy L Stone

Dorothy I Boulia

Based on at least one manufacturing process characteristics associated with a manufacturing process, a prediction time at which to execute a selected machine learning model selected from multiple trained machine learning models is determined, and at the prediction time, the selected machine learning model is executed. Executing the selected machine learning model predicts a control set point for future values of state variables of the manufacturing process, for controlling the manufacturing process. Based on at least one of the manufacturing process characteristics, a learning time at which to train a machine learning model is determined, and at the learning time, the machine learning model is trained based on historical process data associated with the manufacturing process.

Orchestration of learning and execution of model predictive control tool for manufacturing processes

Techniques for scenario planning are provided. In one example, a computer-implemented method can comprise analyzing, by a device operatively coupled to a processor, content using a topic model. The content can be associated with a defined source and is related to one or more current events. The computer-implemented method can also comprise determining, by the device, one or more portions of the analyzed content that are relevant to one or more key risk drivers using a risk driver model. The computer-implemented method can also comprise aggregating, by the device, the determined one or more portions into one or more emerging storylines based on values of one or more attributes of the topic model.

Scenario planning and management

Scenario planning and risk management

A system, computer program and method for inspection of a system under inspection. The system may include an inspection program configured to access information available at the system under inspection and generate inspection data for the system under inspection. A runtime platform independent from the inspection program at the system under inspection is configured to limit the limit the contents of the inspection data to a maximum information content. A trusted third-party computer system may assist in selecting the inspection program and transferring the resulting inspection data.

Computer system evaluation

In a network-connected distributed system including nodes through which digital data flow, one or more of the nodes adapted to process the digital data, a method for efficiently managing the transmission of units of digital data from node to node, includes the steps of receiving, at one of the one or more nodes, units of digital data first transmitted by an originating node; filtering out sufficiently processed units of the digital data based on filtering information; transmitting, to the originating node and/or other nodes, filtered results relating to the sufficiently processed units; queuing, for processing at other nodes, unfiltered units of the digital data which are not filtered out; and updating the filtering information according to results of automatic processing performed in and received from the one of the one or more nodes and/or other nodes in the system.

System and method for managing files in a distributed system using filtering

In a network-connected distributed system including nodes through which digital data flow, one or more of the nodes adapted to process the digital data, a method for efficiently managing the transmission of units of digital data from node to node includes the steps of receiving, at one of the one or more nodes, units of digital data first transmitted by an originating node; queuing, for processing at other nodes, one or more units of the digital data; prioritizing the queued units of digital data for transmission to a next node based on prioritizing information; and updating the prioritizing information according to results of processing performed in and received from the one of the one or more nodes and/or other nodes in the system.

System and method for managing files in a distributed system using prioritization

Text and graphics are justified along one physical dimension to a predetermined line of justification. A plurality of physical parameters are employed in the justification, each of the parameters is assigned a compression and an expansion adjustment ratio. Such ratios define the maximum adjustment range of each of the parameters. A priority of adjustment is assigned to each of the parameters such that one parameter being adjusted and capable of meeting justification needs is adjusted to the exclusion of all other possible parameter adjustments. In vertical justification of a plurality of columns, text distribution precedes the vertical adjustment. For such vertical justification, the priority of adjustment is based upon natural text/graphics breaks; top priority is use of lead outs, second is skips, third is spaces and last is textual adjustments. Justification is preferably proportional, i.e., the ratios are adjusted when the maximum permitted adjustment is not required for justification. For horizontal justification, similar ratio selections apply.

Automatically balancing and vertically justifying a plurality of

A large plurality of electronically-stored fonts are managed and selected for use in a particular presentation (printing, display) of a document represented by electrical signals by either an explicit or implicit method. A new font by either selecting a completely defined font or by selecting predetermined characteristics of font graphics, such as italics, bold, point size, and the like which enable an implicit selection of a completely defined font. Such defined characteristics are interpreted by an automatic machine to complete font definitions for use by a document presentation device. A begin font command can specify a plurality of internal fonts with the order of specification indicating priority of selection for use in document presentation. Whether or not a specified internal font results in a defined font being activated is selectable by font definitions embedded with a received-text-data stream representing text/graphics to be presented. Such combination yields a presentation device and font independency to the unformatted input-text-data stream.

Generating and storing electronic fonts

Text and graphics are recursively (includes iteratively) distributed among a set of balanceable columns capable of receiving text and graphics. The recursive distributions are at successively varying columnar depths (all columns in each recursion have a common target depth), upon completing each recursion, the difference between the resulting shortest and longest column depths is measured and compared with a standard. If the standard is met, the distribution is made final, otherwise subsequent recursions up to a predetermined number of recursions are employed. If the standard is not met, then after the predetermined number of recursions, the distribution yielding the least differential is selected as the final distribution. Vertical justification of the columns follows.

Machine-implemented text/graphics formatting is based upon a logical page area on a presentation-receiving medium, such as a CRT face, sheet of paper and the like. Named text and graphics receiving areas are selectively assignable to the logical pages of a document being formatted for visual presentation and are addressable and formattable independent of other formatting in any logical page. The named areas are machine defined such that one area can have portions thereof automatically assigned to and presented with any arbitrary number of logical pages. Such areas are managed in a text formatting machine to facilitate formatting headers based upon text contained in a succession of logical pages that are outside the named area. A first class of such named areas is placed upon the page when formatting to the page is ended, while a second class of such named areas is placed on the page in response to a command. The placement of the second class on a page can result in starting formatting new pages. Bleed tabs, annotations, and other typographic niceties are machine formattable using such named areas.

Formatting text/graphics using plural independent formatting mechanisms

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Putnam Valley, NY, United States of America

Edward John Pring