Abstract: Resources of a virtualized ecosystem are intelligently secured by defining and analyzing object handling security control information for one or more logical resources in the virtualized ecosystem and deriving therefrom object properties for each of the logical resources involved in the execution of a virtual machine in any given context within the virtualized ecosystem.

Abstract: The present invention provides methods of predicting protein aggregation and designing aggregation inhibitors. One such method for predicting potential protein aggregation inhibiting peptide sequences, includes the steps of: a) identifying a peptide sequence forming at least part of an aggregation region in a target protein; b) testing whether said peptide sequence forms part of a ?-sheet; c) if a positive result is achieved in step b), extracting the adjacent strands of that sheet; d) identifying residues in the adjacent strands to said peptide sequence whose side chains interact with said peptide sequence, those residues forming a potential protein aggregation inhibiting peptide sequence. The present invention also provides methods of designing compounds using the residues identified in the above method; compounds produced by the methods and computer programs for carrying out the above methods.

Abstract: One automatically accesses (101) a hierarchical task model as corresponds to a particular task to be executed by a given end user to thereby identify one or more presently un-executed agenda elements. One also automatically accesses (102) characterizing information for that given end user. (By one approach, for example, this characterizing information can comprise information regarding the given end user's knowledge.) This information regarding the un-executed agenda elements and the characterizing information are then used (103) to identify a highest hierarchical level within the hierarchical task model as corresponds to the given end user's wherewithal to successfully execute without also needing lower hierarchical level content within the hierarchical task model. The identified highest hierarchical level within the hierarchical task model is then used (104) to generate a presentation to present to the given end user to thereby facilitate execution of the particular task by the given end user.

Abstract: Method of and system for analysing a set of exhaustive and exclusive hypotheses, including assessing and assigning base rates for each hypothesis; determining a set of items of evidence that are relevant to, have a causal influence on, or would disconfirm more than one hypothesis; assessing and assigning base rates for each item of evidence; deciding, for each item of evidence, whether the item should be treated as being a causal influence or diagnostic indicator with respect to the set of the hypotheses; if the item of evidence is to be treated as a causal influence—making a judgement as to the likelihood of each hypothesis, both if the evidence were true, and also if the evidence were false; if the item of evidence is to be treated as a diagnostic indicator—making a judgement as to the evidence being true if the hypothesis were true; assessing the belief for each item of evidence being true; deciding a set of interim beliefs in each hypothesis for each individual item of evidence by: employing a conditio

Abstract: Computer-implemented systems and methods generate forecasts or estimates with respect to one or more attributes contained in an attribute-based hierarchy. Physical hierarchical data and attribute input data are received so that an attribute-based hierarchy can be created. A mapping table is created that indicates relationships between the attribute-based hierarchy and the physical hierarchy, wherein the attribute-based hierarchy is accessed during model forecasting analysis or model estimation analysis.

Abstract: Machine-learned ranking algorithms, e.g. for ranking search results, often use a sequence of decision trees involving decision nodes based on threshold values of features. Modules, systems and methods of optimizing such algorithms involve analyzing threshold feature values to determine threshold intervals for each feature and grouping decision trees according to the feature used in a root decision node. Then coalescing the decision trees within each group to form a coalesced group tree for each group and finally coalescing the coalesced group trees to form a coalesced tree that implements the algorithm.

Abstract: A method, apparatus, and electronic device for hierarchical communications are disclosed. A connection interface 1260 may receive a query. A processor 1210 may select an initial expert from the hierarchical expert tree based upon the query and direct the query towards the initial expert. A session initiation protocol server 418 may generate a hierarchical expert tree from an expert pool.

Abstract: A real time data processing system, method and program product for processing a stream of data events. A system is provided that includes: a running profile processing system for updating a running profile each time a new data event value is inputted, wherein the running profile includes percentile data; and an analysis system for analyzing the running profile, wherein the analysis system performs a composite analysis that utilizes: (a) results obtained from comparing a new data event value to the percentile data, and (b) stored results obtained from previous compare operations.

Abstract: The present invention relates to methods, systems and apparatus for capturing, integrating, organizing, navigating and querying large-scale data from high-throughput biological and chemical assay platforms. It provides a highly efficient meta-analysis infrastructure for performing research queries across a large number of studies and experiments from different biological and chemical assays, data types and organisms, as well as systems to build and add to such an infrastructure. According to various embodiments, methods, systems and interfaces for associating experimental data, features and groups of data related by structure and/or function with chemical, medical and/or biological terms in an ontology or taxonomy are provided. According to various embodiments, methods, systems and interfaces for filtering data by data source information are provided, allowing dynamic navigation through large amounts of data to find the most relevant results for a particular query.

Abstract: A method including receiving inputs; determining an expected variance of the inputs; and testing a first hypothesis that the inputs include a signal.

Abstract: The invention relates to architecture of a computer program in order to implement a multi-agent system. The architecture enables the agents to interact with a simulation or game world on a first plane and/or with robots in the real world. Said architecture has a second and third plane. Said second plane contains an abstract representation of the simulation world on the first plane which reduces on concepts. Said third plane implements the agents of the multi-agent system. Interfaces are only arranged between the first and second plane, and between the second and third plane, not however between the first and the third plane. The artificial intelligence of the agents is implemented on the second and third planes such that the simulation world of the first plane can be widened, which leads to artificial intelligence. As a result, the architecture provides a KI-middleware for, for example, computer games.

Abstract: Embodiments of the present invention relate to knowledge representation systems which include a knowledge base in which knowledge is represented in a structured, machine-readable format that encodes meaning.

Abstract: A method, computer program product, and system are provided for decomposing human behavior into quantifiable layers of perception. The method for decomposing human behavior into quantifiable layers of perception may be referred to as “DAP-E,” which is an acronym representative of four main phases of the method. Theses phases include the following: decompose; aggregate; propagate; and, evaluate. For example, an embodiment of the method may include aggregating one or more outputs from one or more behavioral models to represent a statistically significant conclusion and propagating the conclusion across a social network to allow opinions of a first entity within the social network to influence a conclusion of a second entity. The method may also include updating the one or more behavioral models based on new data.

Abstract: The present invention relates to a method for determining behaviour of an autonomous entity within an environment using a weighted memory of observed objects, including the steps of: processing the weighted memory; generating an image of the environment from the perspective of the entity; recognizing visible objects within the image from a list of object types; storing data about the visible objects within the memory; and processing object data extracted from the memory in accordance with each object's type using an artificial intelligence engine in order to determine behavior for the entity. A system and software for determining behavior of an autonomous entity are also disclosed.

Abstract: A risk assessment method and system. The method includes receiving by an inference engine, first sensor cohort data associated with a first cohort located within a first airport. The inference engine receives first group technology inferences associated with the first cohort. The inference engine generates first risk cohort inferences based on the first group technology inferences and the first sensor cohort data. The inference engine receives first inference data comprising a first plurality of inferences associated with the first cohort. The inference engine generates second inference data comprising a second plurality of inferences associated with the first cohort. The second inference data is based on the first inference data and the first risk cohort inferences. The inference engine generates a first associated risk level score for the first cohort. The computing system stores the second inference data and the first associated risk level score.

Abstract: A risk assessment method and system. The method includes receiving by an inference engine, first sensor cohort data associated with a first cohort located within a first aircraft. The inference engine receives first group technology inferences associated with the first cohort. The inference engine generates first risk cohort inferences based on the first group technology inferences and the first sensor cohort data. The inference engine receives first inference data comprising a first plurality of inferences associated with the first cohort. The inference engine generates second inference data comprising a second plurality of inferences associated with the first cohort. The second inference data is based on the first inference data and the first risk cohort inferences. The inference engine generates a first associated risk level score for the first cohort. The computing system stores the second inference data and the first associated risk level score.

Abstract: Models that encapsulate information on how remote applications are controlled and data is accessed are created to be used by a runtime agent that intelligently reasons out goal-oriented plans and execute tasks to solve problem statements generated by a user interface or other software agents.

Abstract: An electronic circuit for use in providing computational decision-making capabilities. The circuit implements a hierarchy of decision-making cells, with outputs derived from input signals supplying argument values, configuration signals for controlling the decision making model and wires between cells defining relationships between cells that modify the decision-making model of dependent cells. The cells are primarily characterized by modified values that may represent outputs although they may have a variety of other function features such as importance values and threshold values. The arguments are characterized by argument values that may represent inputs. The arguments are associated with particular cells and the values of the arguments associated with a given cell are combined to determine the value of that cell. The wires between different cells define different types of functional relationships between them.

Abstract: A system provides a user interface for viewing nursing problems with multiple levels of granularity in a knowledge base and rendered in an application that are dependent on context of problems, patient demographic information and information needed by a user interface image. A user interface system presents patient medical problem information to a user. The system includes a first search processor for automatically searching a knowledge base of information associating multiple different medical problems with corresponding attributes to find an attribute indicating a particular characteristic of a particular medical problem, in response to occurrence of an event. A display processor initiates generation of data representing a display image.

Abstract: Models that encapsulate information on how remote applications are controlled and data is accessed are created to be used by a runtime agent that intelligently reasons out goal-oriented plans and execute tasks to solve problem statements generated by a user interface or other software agents. The models may be used to assemble workflows using a reasoning process. In particular, the models of the present invention include a state that includes a planning state and a navigational value. In embodiments of the invention, the models may include intelligent agents, a loop state, submodel invocation that allows the models to invoke agents over a network, and the ability to integrate the three application layers in a computer.

Abstract: A method (and system) of predicting an unobserved target variable includes building a graphical predictive model from domain knowledge, which takes advantage of conditional independence to facilitate inference about the unobserved target variable, given observations of other variables in the graphical predictive model from a plurality of information sources.

Abstract: A system and method for collecting evidence pertaining to relationships between biomolecules and a disease, or other clinical condition, wherein biomolecules associated with the disease or condition identified, and ontologies relating to the biomolecules, disease or condition, and a predicate relationship therebetween are generated (or input to a processing system). Triplets, subject/predicate/object, for example, biomolecule/relationship/disease, are constructed by processing the ontologies. The triplets are used to search a body of relevant evidence to extract pertinent data from the body of relevant data based on the triplets. The system and method of the invention is used to provide researchers in the field of molecular diagnostics with biological evidence for or against statistical predictions.

Abstract: A method and system to minimize to redundancy in testing a new software system by utilizing a knowledge base is provided. The knowledge base may be represented in a form of a decision tree including leaf nodes which store previously tested optimal configurations. When the knowledge base does not contain an optimal configuration for the new software, an optimal solution for the new software system may be determined by adding a further decision tree branch to the initial decision tree. A desirable tree branch may be selected from a table including a predetermined set of desirable tree branches for each category of software. As a result, the number of solutions to be tested on the input software may be limited and cost and effort to run redundant tests on a software system may be reduced.

Abstract: Method of and system for analysing a set of exhaustive and exclusive hypotheses, including assessing and assigning base rates for each hypothesis; determining a set of items of evidence that are relevant to, have a causal influence on, or would disconfirm more than one hypothesis; assessing and assigning base rates for each item of evidence; deciding, for each item of evidence, whether the item should be treated as being a causal influence or diagnostic indicator with respect to the set of the hypotheses; if the item of evidence is to be treated as a causal influence—making a judgement as to the likelihood of each hypothesis, both if the evidence were true, and also if the evidence were false; if the item of evidence is to be treated as a diagnostic indicator—making a judgement as to the evidence being true if the hypothesis were true; assessing the belief for each item of evidence being true; deciding a set of interim beliefs in each hypothesis for each individual item of evidence by: employing a conditio

Abstract: Models that encapsulate information on how remote applications are controlled and data is accessed are created to be used by a runtime agent that intelligently reasons out goal-oriented plans and execute tasks to solve problem statements generated by a user interface or other software agents.

Abstract: A computer-implemented decision device and a family of methods and procedures are used for representing and analyzing imprecise, vague, and incomplete probabilistic decision and risk problems and/or when a criteria hierarchy is present. Decision makers can state the problems simply with the precision the decision-makers feel they have evidence for. Probabilities, values (utilities), criteria weights with belief distributions over them, and optimization procedures for fast evaluation of decision rules with respect to such statements are determined and analyzed.

Abstract: The method in accordance with the invention is a method making it possible to explain a decision taken by a compensatory multi-criterion aggregation model, according to which a single compensatory multi-criterion aggregation model is established for the application considered, described by a certain number of phenomena and reproducing a determined expert opinion, and it is characterized in that no reference is made in the explanation to the specificities of the aggregation model if the decision taken had been the same on replacing the aggregation model by any other close model, that, if such is not the ease, the aggregation model is simplified by taking into account fewer and fewer phenomena as long as the decision taken remains the same, and that an explanation based solely on the compensation phenomena present in the simplest model previously determined is returned to the expert.

Abstract: Systems and methods for solving nogood databases involve generating a representation comprising a plurality of contexted disjunctions, conjoining all of the contented disjunctions to form a conjunction of contexted disjunctions, and storing the representation as the conjunction of contexted disjunctions. Nogoods are eliminated by refining the representation until a result of the conjunction of contexted disjunctions is backtrack-free or the result of the conjunction of contexted disjunctions reduces to false. In various embodiments, the refining is carried out without reordering the disjunctions and/or without merging the disjunctions. In various embodiments, the systems and methods are used for various constraint satisfaction problems, such as syntactic processing of natural language sentences, map coloring, understanding line drawings, electronic circuit analysis, and truth maintenance systems.

Abstract: Versioning may be utilized in a knowledge base decision tree in order to provide several useful features. To accomplish this, when a decision tree is traversed, the decision tree representing a knowledge base and having non-leaf nodes with one or more branches representing possible symptoms, and leaf nodes with no branches, branches may be followed corresponding to symptoms experience by the application until a leaf node is reached. This traversal may be recorded as a version, with subsequent traversals having a different version. This allows a user to rerun performance tuning either from the beginning or from an earlier node without having to re-enter information already provided. It also allows a user to resume the performance tuning should he be interrupted in the middle, such as by a crash or by having to halt a long traversal.

Abstract: Apparatus and methods that approximately solve an actuation allocation problem by breaking the solution into modules, which may or may not be overlapping. The solution to the actuation allocation problem is expressed in terms of solutions for each of the modules. The solutions for the modules serve as constraints for a solution of the optimization problem on each module. The optimization problem for each module is decomposed into further modules until the modules consist of a small enough number of individual implementation units so that the solution for the module can be solved using conventional optimization techniques.

Abstract: A data model is provided for storing data related to multiple variants of assemblies in a computer-associated memory. A multivariant assembly data object functions as a container for component usages, logical component usages, and also for the assembly-components, each of which represents a variant of the corresponding product or assembly family. Component usages can be shared by multiple assembly-components all of which are members of the same multivariant assembly.

Abstract: A system and method for diagnosing one or more faults or one or more potential faults in a machine. The system and method has a communications module for communicating machine data between the machine and the system. It also has a fault recognition module for analyzing the machine data, which can determine one or more faults or potential faults in the machine. An expert system module having a fault tree is guided through only a truncated portion of the fault tree based upon output from the fault recognition module.

Abstract: An apparatus, computer-readable medium and method for use in association with case-based reasoning and the like utilize a novel decision tree data structure that incorporates a search criterion in association with each test answer to a test criterion defined within a decision node, for use in selecting cases from a search space that match the associated test answer to the test criterion. As such, rather than storing identifiers to the actual cases in a case library, or search space, within a decision tree data structure, search criteria are used to provide the mechanism by which those cases that represent most likely best matches can be dynamically selected.

Abstract: A solution advisor tool for designing an information technology (IT) solution, comprising: (1) a knowledge management system for generating and storing information in a hierarchical format, wherein the knowledge management system includes: (a) a first knowledge base of characteristics; (b) a second knowledge base that manages relationship information regarding the interactions of characteristics and defines all valid characteristic combinations, wherein each valid characteristic combination forms a network unit; (c) a third knowledge base that manages information regarding the interconnectability of network units, wherein a valid combination of network units comprises a configuration; and (d) a fourth knowledge base that manages information regarding sets of possible configurations that can fulfill a predetermined function, wherein each set comprises a cloud; and (2) a design interface system for generating the IT solution.

Abstract: A system and method for managing garment alterations. The system includes a workroom processor having a display and operating a garment alteration application system. Alterations tickets are created using a garment alterations ticket terminal, or display interfaces on the workroom processor that prompt the user for garment alteration data. The alteration data is stored in an alteration ticket data structure that relates to the workflow of a typical workroom. Alterations tickets are presented in the ticket list from which the alteration ticket status updated according to work performed. The reports module generates corporate and workroom management reports based on data stored in relation to the alterations.

Abstract: A framework for use with object-oriented programming systems provides a case-based reasoning (CBR) system shell that permits a framework user to develop a case base having case histories and generates a case-based reasoning system that receives user requests for query solutions and produces a query solution that can be incorporated into the case base. The framework includes a Session component that controls processing of the CBR system, a Control Flow component that manages the extension of the categories and classes of the OO framework, a Data Store component that stores persistent case structure definitions, case instances, and a change log, a Presentation component that manages the user interface to the CBR system user, and a Query Engine that evaluates a received query against the case base. The case definitions and case base descriptions comprise a set of object oriented classes that are organized into an inheritance hierarchy.

Abstract: A method of managing objects within the simulation model commences with the storage of a first value for a particular parameter within an object of the simulation model. A panel is then displayed within the user interface. The relevant parameter of the above-identified object may then be identified for inclusion within this panel. In response to the identification of the parameter, an identifier (such as an icon) associated with the parameter is displayed within the panel. A second value for the relevant parameter of the object may then be inputted by a user via the panel. The second value for the parameter is then stored separately from the first value for the parameter, and these first and second values can be selectively applied to the parameter.

Abstract: The Object-Oriented Data Mining and Decision Making System is invented and disclosed. This system is an integration of two subsystems, the object-oriented data mining subsystem which is an object-oriented machine learning system, and the object-oriented decision making subsystem which is also called the object-oriented expert system. In this invention, object-oriented technology, a new technology in software design and development is applied. The difference between the methodology used in this invention and that used in all other learning systems and expert systems is that in this invention, all objects have the same attributes and actions and are in the same class in the whole process. At the same time, only objects themselves, nothing else are processed, without adding any additional structures, such as trees, hierarchies, and relations to them. Therefore a single class can cover all working objects in the whole process. Besides, statistical methodology is introduced to each object in the class.

Abstract: A data processing apparatus comprises apparatus arranged to model a number of modules (302,314) with each module containing a number of interconnected behaviours (320-325). A behaviour identified as a marker (304) is able to access a behaviour (321) within another module via an identify link (306) and from information denoting that behaviour within a look-up table (312) held in a further behaviour (310). Having established access, a direct identify link (316) can be set up between the selected behaviour (321) and a nominated behaviour (318) within the module containing the marker. This direct identify link is maintained when the identify link between the marker and the further behaviour is terminated, allowing the marker to go on and establish other direct links (330) to the internal behaviours of other modules (336).

Abstract: A computer implemented method for defining, organizing, and analyzing systems and the connections, or relationships, between the systems, in a flexible manner according to a user's focus, perspective, and desired level of detail. A set of systems is selected by a user. A set of attributes by which to distinguish the systems is selected by the user. The systems are grouped according to the values for the selected attributes, thereby forming a taxonomy tree. A user then selects one or more resources that are potentially produced by, i.e., flow from, or consumed by, i.e., flow to, one or more of the systems of interest. A hypercube data structure is created that defines between which systems the resources flow. Utilizing the taxonomy tree, the hypercube further summarizes resource flows between parent systems for which resource flows are defined between their corresponding child systems.

Abstract: An object-oriented decision structure usable by different diagnostic software engines defines a knowledge base that includes a problem, a symptom of the problem, a solution, and case in which the solution is the solution to the problem. The data structure includes a question object defining a question, a response object defining an answer, a question node object, a solution node object defining the case, a case master object defining the problem, the solution, and the case, and a symptom object defining the symptom and pointing to the case master object and to the solution node object. The question node object points to the solution node object, the question object, and the response object and correlates the question, the response, and the solution node object, and the solution node object points to the case master object.