Abstract: An inference method according to the present invention in an inference system inferring a probability that an ending state holds based on a starting state and a rule set, the method includes: when a rule set derived by excluding one rule from rules constituting a first rule set is set as a second rule set, a probability that the ending state holds based on the starting state and the first rule set is set as a first inference result, and a probability that the ending state holds based on the starting state and the second rule set is set as a second inference result, calculating an importance being an indicator indicating magnitude of a difference between the first inference result and the second inference result; and outputting the rule and the importance of the rule, being associated with each other for each of the excluded rule.

Abstract: The current invention concerns a computer-implemented method, a computer system, and a computer program product for the semantic classification of an entity in a building information model (BIM). The BIM comprises multiple target entities. Update data is obtained. For each target entity, geometric information about the target entity is obtained from the BIM. For each target entity, an initial probability distribution of semantic classification is determined based on the obtained geometric information about the target entity. Relative geometric information about the target entities is obtained from the BIM. For each target entity, an updated probability distribution of semantic classification is determined based on the obtained relative geometric information, the initial probability distributions of all target entities, and the update data. For each target entity, a semantic classification is selected based on the updated probability distribution of the target entity.

Abstract: Gene expression programming-based behavior monitoring is disclosed. A machine receives, as input, a plurality of data examples. A method can include receiving data indicating behaviors of the device, determining, using a gene expression programming (GEP) method, a data model that explains the data, and comparing further data indicating further behavior of the device to the data model to determine whether the further behavior is explained by the data model.

Abstract: Asset recommendation for a particular input dataset is provided. Candidate data analysis assets having a corresponding relatedness score associated with the particular input dataset greater than a defined relatedness score threshold value are selected. Those candidate data analysis assets having a corresponding relatedness score greater than the defined relatedness score threshold value are ranked by score. Those candidate data analysis assets having a corresponding relatedness score greater than the defined relatedness score threshold value are listed by rank from highest to lowest. A justification for each candidate data analysis asset is inserted in the ranked list of candidate data analysis assets. The ranked list of candidate data analysis assets along with each respective justification is outputted on a display device.

Abstract: A device and method of producing electrical energy by gravitomagnetic induction utilizing Nano-features fabricated on an object surface of an object is presented. The Nano-features may include Nano-bumps and Nano-pits. One device version includes a computer hard disk, a piezoelectric glide head, and/or a GMR read head, a prior art hard drive module electronics. By spinning the nano-features disk one produces an associated magnetic force utilizing a GMR read head for producing power by the presence or the absence of matter on an object that is in motion relative to the GMR read head. A computer system generated by the alternate computer system generates gravito-magnetic energy to power itself and/or other electrical or electronic devices, and/or, detects patterns of asperities or bump on a hard disk to generate binary value private keys applicable in asymmetric cryptography, such as public key cryptography.

Abstract: Millions of bodily injury insurance claims are filed yearly to help people who've suffered accidents from work, slip-and-falls, and auto collisions. In processing these claims, insurance companies, TPAs, and law firms routinely hire experts, such as physicians, to conduct independent medical evaluations (IMEs) to assist claims adjusters and attorneys in analyzing the eligibility of claimants for indemnity and medical benefit payments. IMEs typically cost thousands of dollars each. Yet, many are ordered too early, wasting money that could otherwise be used to reduce insurance premiums. To reduce this waste, the inventors devised, among other things, one or more exemplary systems which not only predict the outcomes of IMEs based on claimant medical records and/or or activity data before ordering them, but also presents selected claims and predictions within a graphical user interface that facilitates ordering the IMEs from a list of available physicians.

Abstract: A neuro-bionic device based on a two-dimensional Ti3C2 material is provided. The device includes a Pt/Ti/SiO2/Si substrate, a neuro-bionic layer formed on a Pt film layer of the Pt/Ti/SiO2/Si substrate, and an Al electrode layer formed on the neuro-bionic layer. The neuro-bionic layer is made of a two-dimensional Ti3C2 material. The neuro-bionic device of the present invention is prepared by an evaporating coating method and a drop-coating method. The preparation process is relatively simple. The prepared device can successfully simulate the characteristics of synapse. More importantly, the resistance of the device can be modulated continuously under a scanning of a pulse sequence with pulse width and interval of 10 ns, which is beneficial to the application of the device in the ultrafast synapse simulation.

Abstract: Methods and apparatus for training a matrix-based differentiable program using a photonics-based processor. The matrix-based differentiable program includes at least one matrix-valued variable associated with a matrix of values in a Euclidean vector space. The method comprises configuring components of the photonics-based processor to represent the matrix of values as an angular representation, processing, using the components of the photonics-based processor, training data to compute an error vector, determining in parallel, at least some gradients of parameters of the angular representation, wherein the determining is based on the error vector and a current input training vector, and updating the matrix of values by updating the angular representation based on the determined gradients.

Abstract: An information processing apparatus includes: a memory configured to store an image processing program having a tree structure in which a partial program is incorporated in each of a plurality of nodes; and a processor configured to performs, based on the image processing program, operations of; calculating a feature amount based on a processing result in each intermediate node excluding a terminal node among the plurality of nodes when executing image processing on a captured image which is captured by an imaging device; and calculating a performance evaluation value of the image processing program based on a variation amount of the feature amount in accordance with elapse of time.

Abstract: A system and method of generating a Boolean network development environment for qualitative processing may include an alternative setup of NAND-gates implemented in a design to solve complex problems, such as image recognition and automatic decision making/categorization. The method may include initializing a network using a target bitstring and actuating binary propagation thereby, using a predetermined set of inputs to generate an output bitstring. Further, the method may include actuating binary feedback using the output bitstring. A source may be updated until the convergence of all values are completed, wherein the result is compared to the target bitstring.

Abstract: A system for question answering (QA) documents data ingestion decides to ingest the documents data through a first plurality of sub-pipelines including a first sub-pipeline having a first set of engines and a second sub-pipeline having a second set of engines being independent from the first set of engines. The system determines a subset of the documents data and decides to ingest the subset through a second plurality of sub-pipelines including a third sub-pipeline having a third set of engines and a fourth sub-pipeline having a fourth set of engines being independent from the third set of engines. A set of engines of the second plurality of sub-pipelines and a set of engines of the first plurality of sub-pipelines are in a common class. The system selects output data from the second plurality of sub-pipelines over corresponding output data from the first plurality of sub-pipelines and generates a knowledge base.

Abstract: A system for generating a supplement instruction set using artificial intelligence. The system includes at least a server wherein the at least a server is designed and configured to receive training data. The system includes a diagnostic engine operating on the at least a server designed and configured to record at least a biological extraction from a user and generate a diagnostic output based on the at least a biological extraction and training data. The system includes a plan generator module operating on the at least a server designed and configured to generate a comprehensive instruction set associated with the user as a function of the diagnostic output. The system includes a supplement plan generator module operating on the at least a server designed and configured to generate a supplement instruction set as a function of the comprehensive instruction set.

Abstract: Technologies are provided for identifying individuals having a risk of non-adherence to or from a prescribed treatment program; for predicting and the risk, which may be determined as a forecast over a future time span; and evaluating it to further determine or invoke specific actions to mitigate the risk or otherwise improve likelihood of compliance. A singular spectrum analysis (SSA) is utilized to analyze temporal properties of a time series determined from measured or observational data to determine an emergent pattern. Based on this pattern, a risk of non-adherence, including relapse or absconding, over a future time interval by the individual may be determined and utilized to implement an intervening action.

Abstract: An embodiment of a semiconductor package apparatus may include technology to apply a low rank factorization to a weight matrix of a decision network to determine a first weight matrix approximation, reshape the first weight matrix approximation into a second weight matrix approximation, and compress the decision network based on the second weight matrix approximation. Other embodiments are disclosed and claimed.

Abstract: A method and system for constructing a convolutional neural network (CNN) model are herein disclosed. The method includes regularizing spatial domain weights, providing quantization of the spatial domain weights, pruning small or zero weights in a spatial domain, fine-tuning a quantization codebook, compressing a quantization output from the quantization codebook, and decompressing the spatial domain weights and using either sparse spatial domain convolution and sparse Winograd convolution after pruning Winograd-domain weights.

Abstract: A machine learning system may be used to predict clinical questions to ask on a clinical form. A first encoder may encode first information and a second encoder may encoder second information from a medical record of a past appointment. The first and second encoded information and additional encoded information may be used to predict a clinical question to ask by using a reinforcement learning system. The reinforcement learning system may be trained by receiving ratings of questions from users.

Abstract: Systems and methods for generating reduced order models are provided herein. In embodiments, a set of learning points is identified in a parametric space. A 3D physical solver may be used to perform a simulation for each learning point in the set of learning points to generate a learning data set, where the 3D physical solver is selected from a plurality of compatible 3D physical solvers for simulating different physical aspects of a product or process. The learning data set may be compressed to reduce the learning data set to a smaller set of vectors. Coefficients from the learning data set and the smaller set of vectors may then be used to interpolate a set of coefficients within a design space for the reduced order model.

Abstract: An optimization calculation method includes: generating, by a computer, current generation individuals with a selected previous generation individual as a parent individual; evaluating each current generation individual by using a predetermined evaluation function; calculating a current generation constraint condition value based on a previous generation constraint condition value and a constraint condition provisional value which is achieved by more than half of the current generation individuals; determining whether a result of the evaluation for each current generation individual satisfies the current generation constraint condition value; determining a predetermined offset based on an attribute of each individual, which is generated by a mutation generating process, among individuals having the evaluation results satisfying the current generation constraint condition value; and adding the predetermined offset to a random number used to generate each next generation individual by the mutation generating pr

Abstract: Embodiments for training a neural network are provided. A neural network is divided into a first block and a second block, and the parameters in the first block and second block are trained in parallel. To train the parameters, a gradient from a gradient mini-batch included in training data is generated. A curvature-vector product from a curvature mini-batch included in the training data is also generated. The gradient and the curvature-vector product generate a conjugate gradient. The conjugate gradient is used to determine a change in parameters in the first block in parallel with a change in parameters in the second block. The curvature matrix in the curvature-vector product includes zero values when the terms correspond to parameters from different blocks.

Abstract: A data analysis and processing method includes forming an initial assembly of datasets comprising multiple entities, where each entity is a collection of variables and relationships that define how entities interact with each other, simulating an evolution of the initial assembly by performing multiple iterations in which a first iteration uses the initial assembly as a starting assembly, and querying, during the simulating, the evolution of the initial assembly, for datasets that meet an optimality criterion.