Abstract: A modular quantum computer architecture is developed with a hierarchy of interactions that can scale to very large numbers of qubits. Local entangling quantum gates between qubit memories within a single modular register are accomplished using natural interactions between the qubits, and entanglement between separate modular registers is completed via a probabilistic photonic interface between qubits in different registers, even over large distances. This architecture is suitable for the implementation of complex quantum circuits utilizing the flexible connectivity provided by a reconfigurable photonic interconnect network. The subject architecture is made fault-tolerant which is a prerequisite for scalability.

Abstract: A method for creating on chip analog mathematical engines is provided utilizing a neural network with a switched capacitor structure to implement coefficients for weighted connections and error functions for the neural network. The neural networks are capable of any transfer function, learning, doing pattern recognition, clustering, control or many other functions. The switched capacitor charge controls allow for nodal control of charge transfer based switched capacitor circuits. The method reduces reliance on passive component programmable arrays to produce programmable switched capacitor circuit coefficients. The switched capacitor circuits are dynamically scaled without having to rely on switched in unit passives, such as unit capacitors, and the complexities of switching these capacitors into and out of circuit.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for predicting user interests. In one aspect, a method includes training a prediction model to generate a category prediction of a next query from a set of queries, the category prediction specifying categories to which a next query belongs, the prediction model comprising a plurality of prediction functions that each generate a category prediction of a next query, wherein the prediction functions include two or more of a time-based prediction functions that generate a category prediction based on the category data and a difference of submission times of the queries, a rank-based prediction functions that generate a category prediction based on the category data and a rank order by which the queries were received, and a category-based prediction function that generates a category prediction based on the category data.

Abstract: An event analyzer includes an event log collection module configured to collect an event log, an event log storage module configured to convert the event log into an event matrix and to store the event matrix, an event occurrence-order determination module configured to determine occurrence-order of device events based on the event matrix, a Bayesian network generation module configured to specify device events serving as parent node candidates, to calculate evaluation values corresponding to each specified parent node candidate at a virtual device event obtained by shifting the device event serving as a processing object each unit time, and to select an device event serving as a parent node together with a shift amount, and an analysis module configured to output an device event estimated as a cause of an device event to be analyzed, or an device event estimated to occur later based on the shift amount.

Abstract: An illumination system and method is disclosed. In one example, the illumination system comprises a lamp assembly for generating color-variable light, a controller for generating control signals for the lamp assembly, source color input means, preferably a color sensor, for inputting to the controller information defining a source color; a memory associated with the controller, containing information defining at least one color harmony rule. On the basis of the input source color, and using the harmony rule from the memory, the controller calculates a target color and generates its output control signals accordingly. Thus, the light output from the lamp assembly harmoniously matches the measured color of surroundings or objects.

Abstract: Embodiments of an informatics platform where collected data can be normalized, integrated and mapped to a knowledge source, such as medical vocabulary systems are disclosed. One example of such a knowledge source is Unified Medical Language System (UMLS) which is a knowledge source for biomedical applications. Embodiments as depicted herein may provided a method to convert the desired information from UMLS into an ontology representation to allow for its use in conjunction with an informatics system.

Abstract: A device may receive an instruction to automatically install a program using a click area prediction model. The click area prediction model may be associated with predicting a click area of a user interface that, when selected, causes a program installation procedure to proceed. The device may identify an installation user interface associated with installing the program. The device may determine a group of regions included in the installation user interface. The device may identify sets of features associated with the group of regions. The device may determine, based on the sets of features and the click area prediction model, a group of scores associated with the group of regions. The device may identify a particular region as a predicted click area based on the group of scores. The device may select the predicted click area to attempt to cause the program installation procedure to proceed.

Abstract: Embodiments of the invention relate to implementing a probabilistic graphical model (PGM) using magnetic tunnel junctions (MTJs). One embodiment comprises a memory array of magnetic tunnel junctions and a driver unit for programming the memory array to represent a probabilistic graphical model. The magnetic tunnel junctions are organized into multiple subsets of magnetic tunnel junctions. The driver unit selectively applies an electrical pulse to a subset of magnetic tunnel junctions to program information representing a probabilistic belief state in said subset of magnetic tunnel junctions.

Abstract: The invention relates to an electronic assembly comprising a plurality of electronic component groups and a cooling device for cooling the electronic component groups. The cooling device provides a cooling-power distributor. A cooling power of the cooling device can be individually controlled by the cooling-power distributor for every component group. Furthermore, the assembly provides temperature-registering means for every component group for registering a temperature of every component group, and a load-determining device for determining a parameter for every component group which describes the load experienced by a component group on the basis of the temperature registered for this component group. A control unit controls the cooling-power distributor on the basis of the parameters determined for the component groups.

Abstract: Calculating a value of a website visitor includes initializing a calculation model for calculating the value of the website visitor, the calculation model being a neural network model with visitor information as an input and the visitor's value as an output; training the calculation model by using a data sample and determining the calculation model; and obtaining the visitor information, and calculating the value of the visitor by using the determined calculation model.

Abstract: A governance apparatus and a communication method for communicating within the governance apparatus. The governance apparatus includes a Government. The Government includes Councils such that a macro grid including an artificial intelligence and the Government is configured to respond to an alert pertaining to an event through use of the artificial intelligence and the Government. The governance apparatus also includes an enhanced Transmission Control Protocol/Internet Protocol (TCP/IP) communication stack of layers including a Governance Layer and an Intelligence Layer. The Intelligence Layer includes intelligence software configured to process data pertaining to the event, data pertaining to the alert, and data pertaining to the Government.

Abstract: A plurality of user made decisions concerning unknown data objects are received from a plurality of users. Each specific user made decision concerns a specific unknown data object made by a specific user, wherein the specific decision could not be made automatically with a sufficient level of confidence without user input. Accuracy of the received user made decisions is automatically determined, as empirical data determinative of the accuracy of the decisions becomes available over time. User weights are automatically dynamically calculated, based on the determined accuracy of decisions made by associated users. Multiple user made decisions received from multiple users concerning a specific unknown data object are aggregated, taking into account the user weights. A definitive decision concerning the specific unknown data object is automatically made without prompting any user for confirmation, based on the aggregating of the user made decisions concerning the specific unknown data object.

Abstract: A method and system for classifying documents is provided. A set of document classifiers is generated by applying a classification algorithm to a trusted corpus that includes a set of training documents representing a taxonomy. One or more of the generated document classifiers are executed against a plurality of input documents to create a plurality of classified documents. Each classified document is associated with a classification within the taxonomy and a classification confidence level. One or more classified documents that are associated with a classification confidence level below a predetermined threshold value are selected to create a set of low-confidence documents. The low-confidence documents are disassociated from each of the associated classifications. A user is prompted to enter a classification within the taxonomy for at least one low-confidence document.

Abstract: A request to diagnose a problem with an appliance is provided to a diagnostic system whereupon the diagnostic system functions to interpret the information indicative of the problem with the appliance to thereby normalize the information indicative of the problem with the appliance. The normalized information indicative of the problem with the appliance is then used to select from a knowledge base in which is maintained a plurality of solutions each having associated tags that function to identify concepts and values in a domain model a set of possible solutions for the problem with the appliance. As necessary, information within the set of possible solutions for the problem with the appliance is used to dynamically generate additional questions to thereby obtain further information indicative of the problem with the appliance.

Abstract: Techniques for computing a solution to a query formulated against a knowledge base (KB) are provided. The techniques include receiving a query formulated against a knowledge base, wherein the knowledge base comprises a set of one or more axioms, wherein each axiom is annotated with a specific probability value indicating a degree of certainty assigned thereto, ignoring each probability value of the one or more axioms and computing a solution to the query, computing each of one or more justifications for the query solution, wherein computing each of one or more justifications for the query solution comprises determining a minimal set of one or more axioms in the knowledge base that entail the query solution, and using each probability value of the one or more axioms in each justification to compute a net probability of an inferred query solution.

Abstract: A virtual parallel computing system and method represents bits with matrices and computes over all input states in parallel through a sequence of matrix operations. The matrix operations relate to logic gate operators to carry out a function implementation that represents a problem to be solved. Initial matrices are prepared to encode the weights of all input states, which can be binary states. Intermediate results can be simplified to decrease computational complexity while maintaining useful approximation results. The final matrices can encode the answer(s) to the problem represented by the function implementation. The system and method are particularly useful in speeding up database searches and in counting solutions of satisfiability problems.

Abstract: A method and a system of associating a runtime event with a component. The method includes catching the runtime event; catching the context of the current running environment and determining the current component based on said context; and getting the associating policy of current component and determining the responsible component associated with said runtime event based on said associating policy.

Abstract: According to one embodiment, an object retrieval apparatus includes a query acceptance unit and a collision decision unit. The query acceptance unit is configured to accept a retrieval query indicating (N?1)-dimensional surface in N-dimensional space (N is an integral number larger than or equal to three). The collision decision unit is configured to decide whether the (N?1)-dimensional surface intersects N-dimensional cuboid positioned in the N-dimensional space. The collision decision unit decides by using a plurality of decision functions. The plurality of decision functions includes zero-th˜(N?1)-th decision functions to decide whether at least a part of at least one of X-dimensional face (X is all integral numbers larger than or equal to zero, and smaller than or equal to (N?1)) of the N-dimensional cuboid is included in the (N?1)-dimensional surface.

Abstract: Quantification of a condition of a selected item using a neural network is disclosed. A device defines a good hypertube in a neural state space based on good item state points obtained from one or more items that exhibit desired operating characteristics, and a bad hypertube in the neural state space based on bad item state points obtained from one or more items that exhibit undesirable operating characteristics. A current item state hyperpoint is determined in the neural state space based on a current item state point of the selected item. A condition of the selected item is quantified as a function of a location of the current item state hyperpoint with respect to at least a portion of the good hypertube and with respect to at least a portion of the bad hypertube.

Abstract: A method for the computer-aided learning of a recurrent neural network for modeling a dynamic system which is characterized at respective times by an observable vector with one or more observables as entries is provided. The neural network includes both a causal network with a flow of information that is directed forwards in time and a retro-causal network with a flow of information which is directed backwards in time. The states of the dynamic system are characterized by first state vectors in the causal network and by second state vectors in the retro-causal network, wherein the state vectors each contain observables for the dynamic system and also hidden states of the dynamic system. Both networks are linked to one another by a combination of the observables from the relevant first and second state vectors and are learned on the basis of training date including known observables vectors.