Abstract: In an embodiment, a correlated forecast is computer generated by a processor that receives input data for historic values of a first input variable, creates forecast data for future values of the first input variable using the historic values of the first input variable, generates diagnostic data based on a diagnostic analysis of the forecast data, creates a first diagnostic variable that includes a first diagnostic value from a first cognitive process, generates a feature vector based on a second cognitive process that determines the feature vector by identifying a correlation between the first diagnostic variable and a second diagnostic variable, and generates a final forecast using the feature vector as an input for a cognitive forecasting process, where the first cognitive process determines the first diagnostic value based on the diagnostic data.

Abstract: A computer-implemented method includes: receiving, by a computer device, preference information from a plurality of people, the preference information including an individual level of preference for various activities for each of the people; receiving, by the computer device, biometric data of the people, the biometric data relating to the various activities; building, by the computer device, a corpus of relationships between the preference information and the biometric data; receiving, by the computer device, biometric data of a user; and predicting, by the computer device, a user level of preference with a particular activity of the various activities, the predicting being based on a comparison of the biometric data of the user and the biometric data of the people who participated in the particular activity.

Abstract: One embodiment of the invention provides a method for data deduplication storage management in a data platform including a plurality of data stores. The method comprises, for each data store of the plurality of data stores, determining a corresponding multi-level signature mapping data content of the data store into an ordered logical form comprising a plurality of data abstraction levels, determining a data similarity between the data store and each other data store of the plurality of data stores based on the multi-level signature corresponding to the data store and another multi-level signature corresponding to the other data store, and determining data usage of the data content of the data store. The method further comprises improving storage in the data platform by detecting duplicate data across the plurality of data stores based on each data similarity determined and each data usage determined.

Abstract: A computer-implemented method for effective agriculture and environment monitoring. The method may comprise measuring a desired variable over an area of interest using a remote inspection platform according to an inspection plan, predicting an occlusion of the remote inspection platform, and in response to the predicted occlusion, determining whether to invoke a local inspection platform to complete the inspection plan. The occlusion in some embodiments interrupts the inspection plan for the remote inspection platform.

Abstract: The present invention relates to a method, system and computer program product for defect enhancement. According to the method, a plurality of proposed regions from a plurality of images taken for a display panel is obtained. Each of proposed region of the plurality of proposed regions include a suspected defect on the display panel. At least two proposed regions from the plurality of proposed regions that deserve to be superimposed based on a set of conditions is determined. The at least two proposed regions for acquiring an enhanced defect are superimposed.

Abstract: Provided are a computer program product, system, and method for pre-processing a table in a document for natural language processing. A table in a document is parsed to extract column headers, row headers, and data cells, which are processed to determine an initial set of a main element comprising an entity whose value is to be extracted, a conditional element that refines the entity, and a value element comprising a value for the entity. A user selection is received of at least one of the column headers, row headers, and data cells for at least one of the main element, conditional element, and the value element in the initial set to produce a modified set of the main element, conditional element, and value element. The modified set is provided to a natural language processing engine to perform natural language processing of the document including the table, using the modified set.

Abstract: A system is configured to avoid establishing an electrostatic discharge (ESD) region in an integrated circuit (IC). The system includes a processor and memory storing an IC simulator. The IC simulator establishes an IC chip that is sub-divided into a plurality of hierarchical levels. The IC simulator further analyzes a first hierarchical level to determine first connectivity information indicating connectivity between the first hierarchical level and one or both of lower-level pins and lower-level nets of a targeted hierarchical level having a lower-level of hierarchy with respect to the first hierarchical level and analyzes the targeted hierarchical level to determine second connectivity information indicating diode connectivity to one or both high-level pins and higher-level nets included in the first hierarchical level.

Abstract: A vertical resistive memory array is presented. The array includes a pillar electrode and a switching liner around the side perimeter of the pillar electrode. The array includes two or more vertically stacked single cell (SC) electrodes connected to a first side of the switching liner. The juxtaposition of the switching liner, the pillar electrode, and each SC electrode forms respective resistance switching cells (e.g., OxRRAM cell). A vertical group or bank of these cells may be connected in parallel and each share the same pillar electrode. The cells in the vertical cell bank may written to or read from as a group to limit the effects of inconsistent CF formation of any one or more individual cells within the group.

Abstract: Core utilization optimization by dividing computational blocks across neurosynaptic cores is provided. In some embodiments, a neural network description describing a neural network is read. The neural network comprises a plurality of functional units on a plurality of cores. A functional unit is selected from the plurality of functional units. The functional unit is divided into a plurality of subunits. The plurality of subunits are connected to the neural network in place of the functional unit. The plurality of functional units and the plurality of subunits are reallocated between the plurality of cores. One or more unused cores are removed from the plurality of cores. An optimized neural network description is written based on the reallocation.

Abstract: Embodiments are provided to simulate a quantum circuit. A system receives a quantum circuit (or its representation), generates a graph, and adds edges for each n-qubit of fusion to be applied. Costs are estimated or calculated for various paths of gate fusion between endpoints in the graph. One or more paths are selected, for example, the lowest cost path based on a Dijkstra algorithm evaluation. A unitary matrix for each gate fusion is then generated for simulating the quantum circuit. A simulation is performed locally or remotely based on the gate fusions along the selected one or more paths, and thus, improving the memory and processor performance of the simulation.

Abstract: Systems and methods for dynamic quality metrics forecasting and management are provided. In embodiments, a method includes receiving, by a computing device, parameter data from one or more data sources for selected parameters, wherein the parameters are associated with one or more processes; generating, by the computing device, output values for plural quality metrics based on the parameter data; identifying, by the computing device, relationships between the plural quality metrics based on changes in the received parameter data and output values for the plural quality metrics over time; receiving, by the computing device, user-selected values for the selected parameters; and generating, by the computing device, predicted output values for the quality metrics based on the identified relationships between the quality metrics and the user-selected values.

Abstract: Embodiments of the present disclosure relate to a method, system, and computer program product for generating one or more in-memory data structures for data access. According to the method, target data associated with a database is identified. Further, the method determines at least one data structure for the target data based on at least one access pattern of the target data in a plurality of historical queries against the database, wherein the target data is accessed in execution of the plurality of historical queries. The method further implements the at least one data structure in a memory to store the target data. The at least one data structure is used for further access to the target data in execution of a further query against the database.

Abstract: Systems and techniques that facilitate universal and efficient privacy-preserving vertical federated learning are provided. In various embodiments, a key distribution component can distribute respective feature-dimension public keys and respective sample-dimension public keys to respective participants in a vertical federated learning framework governed by a coordinator, wherein the respective participants can send to the coordinator respective local model updates encrypted by the respective feature-dimension public keys and respective local datasets encrypted by the respective sample-dimension public keys. In various embodiments, an inference prevention component can verify a participant-related weight vector generated by the coordinator, based on which the key distribution component can distribute to the coordinator a functional feature-dimension secret key that can aggregate the encrypted respective local model updates into a sample-related weight vector.

Abstract: Disclosed are techniques for determining network configurations through machine logic from security certificates of destination computer devices in the network. When a security component of a network receives an incoming data packet sent to a destination computer device in the network, a security certificate is requested from the destination computer device. The security component then configures a set of network rules for forwarding data packets to the destination computer device based on information in the security certificate of the destination computer device. Properties of the incoming data packet are compared to the set of network rules to determine whether to forward the incoming data packet to the destination computer.

Abstract: Embodiments relate to a system, program product, and method for smart contract implementation and management. A request for resources is modeled and a reservation of resources is captured in a first computation model interface. A provision of services is modeled as a second computation model interface. Compatibility of the first and second computation model interfaces is verified. Input and output actions are synchronized between the first and second computation model interfaces responsive to the compatibility verification. A smart contract is composed as a third computation model interface to model negotiation of contractual terms, including the captured resources with the provision of services. The composed smart contract is recorded in an operatively coupled immutable venue.

Abstract: A first service's exhibition of a first symptom while executing a set of transactions is detected. A graph is constructed representing data flow between a set of services including the first service. By traversing the graph, a set of candidate services is constructed, a candidate service in the set of candidate services comprising a service exhibiting the first symptom, the set of candidate services including the first service. A probability of a first cause is evaluated, for the candidate service. At a problem service in the set of candidate services, a problem cause is ameliorated, the problem service identified using the set of candidate services and the probability of the first cause, the problem cause causing the first symptom.

Abstract: An embodiment includes determining, in response to receiving data at a source node for transmission as streaming data on a network, whether a characteristic of the data indicates that an attribute of the data includes sensitive information. The embodiment also includes calculating, responsive to determining that the attribute includes sensitive information, an entropy value for the attribute. The embodiment also includes determining, responsive to the calculating of the entropy value, a likelihood that the attribute is encrypted by comparing the entropy value to a threshold value. The embodiment also includes generating a parameter value for a cryptographic parameter for the attribute.

Abstract: A method, system, and computer program product for virtual reality-based network traffic load simulation are provided. The method monitors a set of activities for a set of applications. A network load simulation for the set of applications is generated based on the set of activities. A contextual change is identified for an application of the set of applications. The method generates a virtual reality visualization of the network load simulation based on the contextual change. A parameter change is detected from a user interaction within the virtual reality visualization of the network load simulation. The method dynamically modifies the network load simulation within the virtual reality visualization in response to the parameter change.

Abstract: Devices and/or computer-implemented methods facilitating static ZZ suppression and Purcell loss reduction using mode-selective coupling in two-junction superconducting qubits are provided. In an embodiment, a device can comprise a superconducting bus resonator. The device can further comprise a first superconducting qubit. The device can further comprise a second superconducting qubit, the first superconducting qubit and the second superconducting qubit respectively comprising: a first superconducting pad; a second superconducting pad; a third superconducting pad; a first Josephson Junction coupled to the first superconducting pad and the second superconducting pad; and a second Josephson Junction coupled to the second superconducting pad and the third superconducting pad. The first superconducting pad and the second superconducting pad of the first superconducting qubit and the second superconducting qubit are coupled to the superconducting bus resonator.

Abstract: Die stacks and methods of making die stacks with very thin dies are disclosed. The die surfaces remain flat within a 5 micron tolerance despite the thinness of the die and the process steps of making the die stack. A residual flux height is kept below 50% of the spacing distance between adjacent surfaces or structures, e.g. in the inter-die spacing.

Abstract: A device and related method are associated with a focus vehicle. The device comprises a sensor that senses area information about an information area usable to assist the focus vehicle and an oncoming vehicle to pass each other, a transmitter that broadcasts the area information via a vehicle-to-vehicle network protocol, and a controller. The controller produces an assisting result from the area information and vehicle information related to the focus vehicle and the oncoming vehicle. The vehicle information includes first distance information of the focus vehicle from the information area, and second distance information of the oncoming vehicle from the information area. The device includes a display that displays virtual traffic information representing at least stopping and proceeding of the focus vehicle onto a windshield of the vehicle.

Abstract: A system for and methods of semiconductor testing and characterization are disclosed. The system includes a parallel dipole line (PDL) system for applying a magnetic field to a sample in a measurement chamber and electrical equipment for testing the sample. The testing includes applying a first light exposure to the sample with the PDL system set to zero magnetic field and monitoring longitudinal resistance (Rxx) of the sample as intensity of the first light exposure varies. A second light exposure is applied with the PDL system set to maximum magnetic field, and transverse magnetoresistance (RB+) is monitored as light intensity varies. A third light exposure is applied with the PDL system set to minimum magnetic field, and transverse magnetoresistance (RB?) is monitored as light intensity varies. The characterization includes carrying out a photo-Hall analysis based on data from the testing.

Abstract: Embodiments of the present disclosure relate to managing power provided to a semiconductor circuit to prevent undervoltage conditions. A measured voltage value describing a measured supply voltage at a first subcircuit of a semiconductor circuit can be received, the measured voltage value having a first resolution. A selected metric indicative of a supply voltage present at the first subcircuit can be received, the selected metric having a second resolution higher than the first resolution. The selected metric is calibrated to obtain a calibrated metric when a transition of the measured voltage value occurs.

Abstract: A computer-implemented method of performing a link stack based prefetch augmentation using a sequential prefetching includes observing a call instruction in a program being executed, and pushing a return address onto a link stack for processing the next instruction. A stream of instructions is prefetched starting from a cached line address of the next instruction and is stored in an instruction cache.

Abstract: One embodiment provides a method, including: receiving at least one deep learning job for scheduling and running on a distributed system comprising a plurality of nodes; receiving a batch size range indicating a minimum batch size and a maximum batch size that can be utilized for running the at least one deep learning job; determining a plurality of runtime estimations for running the at least one deep learning job; creating a list of optimal combinations of (i) batch sizes and (ii) numbers of the plurality of nodes for running both (a) the at least one deep learning job and (b) current deep learning jobs; and scheduling the at least one deep-learning job at the distributed system, responsive to identifying, by utilizing the list, that the distributed system has necessary processing resources for running both (iii) the at least one deep learning job and (iv) the current deep learning jobs.

Abstract: A set of workload criteria is determined from a workload associated with a plurality of sources. The workload is divided among a set of workload groups according to the set of workload criteria and a first workload scheduler. A set of edge computing resources is assigned to each workload group within the set according to the set of workload criteria and the set of workload groups. A portion of the workload associated with a subset of the plurality of sources is handled by a first subset of edge computing resources and a second workload scheduler, where the subset of sources is associated with a first workload group. The handling includes balancing, by the second workload scheduler, the portion of the workload among the subset of sources. The handled workload is reported to a control center.

Abstract: Methods, systems, and circuits for training a neural network include applying noise to a set of training data across wordlines using a respective noise switch on each wordline. A neural network is trained using the noise-applied training data to generate a classifier that is robust against adversarial training.

Abstract: An application (App)-BOT, scans a context of a user of an application and obtains current scanned user data. The App BOT determines a set of user information entities from the scanned user data containing current information about the user. In a negotiation phase, the App BOT a data access request offer from a mixed reality data (MRD)-BOT. A privacy leak score is estimated that represents a user value attributed to the permission to access the labelled user information entity based on the data access request offer. Responsive to determining that the privacy leak score exceeds a privacy leak score threshold, an acceptance of the data access request offer is sent to the MRD BOT and providing access requested by the data access request. Otherwise, a counteroffer is sent to the offer to the MRD BOT.

Abstract: The exemplary embodiments disclose a system and method, a computer program product, and a computer system for resolving the intents of user expression. The exemplary embodiments may include receiving a user expression, receiving a first resolver having an input class and an output class based on the user expression, determining whether the first resolver can be resolved based on the user expression, and based on determining that the first resolver can be resolved based on the user expression, resolving the first resolver.

Abstract: A method and a system detects a cache line as a potential or confirmed hot cache line based on receiving an intervention of a processor associated with a fetch of the cache line. The method and system include suppressing an action of operations associated with the hot cache line. A related method and system detect an intervention and, in response, communicates an intervention notification to another processor. An alternative method and system detect a hot data object associated with an intervention event of an application. The method and system can suppress actions of operations associated with the hot data object. An alternative method and system can detect and communicate an intervention associated with a data object.

Abstract: One or more memory systems, architectural structures, and/or methods of storing information in memory devices is disclosed to improve the data bandwidth and or to reduce the load on the communication links. The system may include one or more memory devices, one or more memory control circuits and one or more data buffer circuits. The memory system, architectural structure and/or method improves the ability of the communications links to transfer data downstream to the data buffer circuits. The memory control circuit receives a store command and a store data tag (Host tag) from a Host and sends the store data command and the store data tag to the data buffer circuits. No store data tag or control signal is sent over the communication links between the Host and the data buffer circuits, only data is sent over the communication links between the Host and the data buffer circuits.

Abstract: Tailoring textual content to a target audience by receiving an input of a user, wherein the input of the user includes textual data, identifying a target audience of the textual data based at least in part on the input of the user, determining a style of the target audience, wherein the style is a variety of language used by the target audience, generating a modification recommendation to the textual data of the input of the user based at least in part on the textual data and the determined style.

Abstract: Embodiments of the present invention are directed to fabrication method and resulting structures for vertical tunneling field effect transistors (VFETs) having an oxygen vacancy passivating bottom spacer. In a non-limiting embodiment of the invention, a first semiconductor fin is formed in a first region of a substrate and a second semiconductor fin is formed in a second region of the substrate. A bilayer bottom spacer is formed in direct contact with sidewalls of the semiconductor fins. The bilayer bottom spacer includes a first layer and an oxygen-donating second layer positioned on the first layer. A first dielectric film is formed on the sidewalls of the first semiconductor fin. The first dielectric film terminates on the first layer. A second dielectric film is formed on the sidewalls of the second semiconductor fin. The second dielectric film extends onto a surface of the oxygen-donating second layer.

Abstract: Techniques regarding mitigating bias in one or more machine learning models are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a model component that can evaluate a machine learning model at a plurality of threshold settings to generate a sample set and can define a relationship between a fairness metric and a utility metric of the machine learning model based on the sample set.

Abstract: According to a first aspect of the present invention, a computer implemented method, a computer system and a computer program product for creating an ontological conversational agent, the method including creating an ontological specification of a domain of discourse of the ontological conversational agent, and creating a description of one or more goals of the ontological conversational agent. In an embodiment, the ontological description includes classes of entities, their associated attributes and relationships between the classes of entities. In an embodiment, the ontological description includes language-related descriptions. In an embodiment, the method, computer system and computer program product further includes creating a description of services of the ontological conversational agent.

Abstract: A request to move along a route is detected. The request is from a first electric vehicle. The route may include a start point and an end point. It may be determined that the first vehicle is an electric vehicle including a battery. In response to determining that the first vehicle is an electric vehicle, one or more battery parameters of the first vehicle may be retrieved. One or more electric vehicle chargers may be identified based on the start point and the end point. A subset of the electric vehicle chargers may be selected based on the battery parameters of the first vehicle. A second route is generated based on the subset of the electric vehicle chargers. The second route is generated such that the first vehicle is capable of reaching the end point. The route of the first vehicle may be replaced with the second route.

Abstract: Concepts for creating a mock for an integration flow are presented. One example comprises analyzing a response to each of a plurality of requests from an integration flow and determining whether or not an identifying property of each of the plurality of requests is present in the response. The method then comprises, responsive to determining that the identifying property is present in the response, generating a mock with an associated matcher based on the plurality of requests.

Abstract: An embodiment for contextualizing abnormal events which employ location-based social networks, LBSN, data to determine events that may be linked to the abnormal events is provided. The embodiment may include detecting an occurrence of an abnormal event within a geographic region, wherein the abnormal event occurs at an occurrence time. The embodiment may also include obtaining location-based social networks, LBSN, data relating to the geographic region for a time period including the occurrence time. The embodiment may further include analyzing the obtained LBSN data, wherein the analyzation determines a linked event within the geographic region for the time period. The embodiment may also include associating the linked event with the abnormal event.

Abstract: A computer automatically groups IoT devices. The computer identifies at least one individual interaction zone within an operating environment, the at least one individual interaction zone characterized by pre-established device mounting regions each associated with a device category. The computer receives a location indicating signal from an IoT device located within the at least one individual interaction zone. The computer, in response to receiving the location indicating signal and based at least in part thereon, the computer recognizes that the IoT device is occupying one of the device mounting regions. In response to the recognition, the computer determines that the IoT device belongs to the device category associated with the occupied mounting region. In response to the determination, the computer adds the device to an IoT device group associated with the individual interaction zone associated with the occupied mounting region.

Abstract: A method, system, and computer program product for implementing automated system capacity optimization is provided. The method includes retrieving from plug-in components running on a plurality of hardware and software sources, metrics data associated with the plug-in components. The metrics data is cross-referenced with respect to operational sizing recommendations for each plug-in component based on aggregated disparate sizing guidelines and resulting software code modules are generated. Software and hardware requirements for enabling target computing components are determined based on results of executing the software code modules and operational functionality of the target computing components are enabled in accordance with the software and hardware requirements.

Abstract: A clock driver circuit for low powered clock driving may include: a multiple phase divider; a buffer supplying at least one of multiple phases to the multiple phase divider at a center frequency that is an integer multiple of an input frequency; and wherein the multiple phase divider and the buffer share a same current from a supply rail.

Abstract: A red, green, and blue values for a fluid are received. A standard red, green, and blue values for the fluid are determined. A tolerance red, green, and blue values are determined for the fluid based on the standard red, green, and blue value for the fluid. An updated red, green, and blue values for the fluid are received. Whether any of the updated red, green, and blue values for the fluid are outside of the associated tolerance red, green, and blue values for the fluid is determined.

Abstract: One or more computer processors generate a network fractal based on one or more predicted network conditions for a network that includes a change in user density, user device latency, and network throughput, wherein the network fractal is a deployment template comprised of a plurality of nodes. The one or more computer processors select a configuration of network infrastructure devices placed at each node in the plurality of nodes comprised in the generated network fractal. The one or more computer processors modify the network utilizing the generated network fractal and the selected configuration of network infrastructure devices. The one or more computer processors deploy the modified network.

Abstract: Mechanisms are provided for training a hybrid machine learning (ML) computer model to simulate a biophysical system of a patient and predict patient classifications based on results of simulating the biophysical system. A mechanistic model is executed to generate a training dataset. A surrogate ML model is trained to replicate logic of the mechanistic computer model and generate patient feature outputs based on surrogate ML model input parameters. A transformation ML model is trained to transform patient feature outputs of the surrogate ML model into a distribution of patient features. A generative ML model is trained to encode samples from a uniform distribution of input patient data into mechanistic model parameter inputs that are coherent to the target distribution of patient features and are input to the surrogate ML model. Input patient data for a patient is processed through the ML models to predict a patient classification for the patient.

Abstract: Feedback tuples are implemented in a stream computing environment to provide data flow status information for use in detecting, identifying and/or handling data flow anomalies for a stream computing application.

Abstract: Methods and a system of generating a master seed using location-based data. The system includes a pseudo-random number generator configured to generate a random number and a global positioning system module configured to determine a location of the system. The system also includes an encryption module configured to generate a signing request message. The signing request message includes the random number and the location. The system further includes a communication device configured to transmit the signing request message to a location authority for authorization. The communication device further configured to receive a signature from the location authority upon authorization of the signing request message. The system is further configured to generate a master seed based on the signature.

Abstract: Embodiments may determine user intent in conversations with dialogue systems so as to improve the quality of such conversations and to reduce the number of failed conversations. For example, a method may comprise receiving, at a dialogue system, a first text utterance from a user, generating a plurality of second text utterances at the dialogue system in response to the received text utterance, generating a third text utterance based on each generated second text utterance using a trained deep neural network model, generating a score indicating a quality of each conversation, wherein each conversation includes the first text utterance, one of the second text utterances, and the third text utterance based on the one of the second text utterances, and outputting to the user the second text utterance included in the conversation having the highest quality score.

Abstract: A processor may detect a risk on a local machine. The processor may determine that the risk warrants a heightened-level remediation. The processor may connect the local machine to a cloud-based desktop environment. The processor may perform the heightened-level remediation on the local machine. The processor may merge data from the cloud-based desktop environment to the local machine in response to the heightened-level remediation being performed.

Abstract: Embodiments relate to a system, program product, and method for proactively initiating throttle action on one or more cores in a multicore processing device to mitigate voltage droop therein. The method includes determining, in real-time, an indication of stall events within the core and determining one or more resolutions of the stall events. The method also includes determining, in real-time, a timing margin value for the core and predicting inducement of a voltage droop on the core. The method further includes integrating the resolutions of the stall events and the timing margin value for the core, determining, subject to the predicting, a throttle action for the core, and executing the throttle action on the core.

Abstract: A computer-implemented method includes identifying two or more memory locations and referencing, by a memory access request, the two or more memory locations. The memory access request is a single action pursuant to a memory protocol. The computer-implemented method further includes sending the memory access request from one or more processors to a node and fetching, by the node, data content from each of the two or more memory locations. The computer-implemented method further includes packaging, by the node, the data content from each of the two or more memory locations into a memory package, and returning the memory package from the node to the one or more processors. A corresponding computer program product and computer system are also disclosed.