Abstract: State of the art techniques provide dedicated High-Level Synthesis (HLS) performance estimator tools that can give insights on performance bottlenecks, stall rate, stall cause etc., in HLS designs. These estimators often limit themselves to simple loop topologies and limited pragma use which makes them unreliable for large designs with complex datapaths. Embodiments herein provide a method and system for non-intrusive profiling for high-level synthesis HLS based applications. The method provides a cycle-accurate, fine-grained performance profiling framework that is non-intrusive and provides an end-to-end profile of the design. Such profiling tool can help the designer/DSE tool to quickly identify the performance bottlenecks and have a guided approach towards tuning it.

Abstract: A wrapper of a smoking article includes a base web and at least one transverse banded region. The banded region includes a first zone, a second zone and a third zone of add-on material. The second zone has about 25% to about 75% less add-on material than the first zone and the third zone. The banded region is about 5 mm to about 9 mm wide and the second zone is centrally located between the first zone and the third zone. The second zone includes a plurality of dots of the add-on material spaced from adjacent dots in the second zone by a distance greater than a distance between adjacent dots in the first zone and the third zone.

Abstract: The present invention relates to methods of distributing pharmaceuticals in a pharmaceutical dispensing system comprising two or more pharmaceutical dispensers configured to store, package and dispense pharmaceuticals in batches according to a schedule and/or immediately dispense non-scheduled pharmaceuticals in response to at least one non-scheduled demand, where some of the pharmaceutical dispensers comprise a limited pharmaceutical storage capacity. The method comprises distributing pharmaceuticals scheduled to be dispensed in batches to one pharmaceutical dispenser and distributing only a subset of non-scheduled pharmaceuticals to another pharmaceutical dispenser.

Abstract: Methods and systems for manipulating surface topology of additively manufactured fluid interacting structures, such as additively manufactured heat exchangers or airfoils, and associated additively manufactured articles, are disclosed. In one aspect, an article which interacts with a fluid is imparted with surface topology features which affect performance parameters related to the fluid flow. The topological features may be sequenced, combined, intermixed, and functionally varied in size and form to locally manipulate and co-optimize multiple performance parameters at each or selectable differential lengths along a flow path. The co-optimization method may uniquely prioritize selectable performance parameters at different points along the flow path to improve or enhance overall system performance.

Abstract: Provided are transaction cards including an expanded identification ship. In some approaches, a transaction card may include a body having a first main side opposite a second main side, wherein the body defines an outer perimeter including a first end perimeter opposite a second end perimeter, and a first side perimeter opposite a second side perimeter. The transaction card may further include an identification chip having a plurality of contacts, wherein a first contact of the plurality of contacts extends to at least one of the following: the first end perimeter, the second end perimeter, the first side perimeter, and the second side perimeter.

Abstract: A method is disclosed. The method includes transmitting interaction history information comprising at least a plurality of addresses to a server computer, receiving a challenge summary from the server computer, the challenge summary associates each address of the plurality of addresses to a challenge rate from a range of challenge rates, and determining a challenge rate threshold based on the challenge summary. The method also includes interacting with a user utilizing at least an address, determining if the challenge rate associated with the address exceeds the challenge rate threshold, performing an authentication of the user if the challenge rate associated with the address does not exceed the challenge rate threshold; and initiating an authorization process of the interaction with the user.

Abstract: Methods and systems for the dynamically re-clustering of nodes in clusters to provide optimal performance and/or the most efficient use of resources through the use of machine learning models. Specifically, the methods and systems may determine a cluster that optimally performs and/or has the most efficient use of resources based on a first machine learning model. The methods and system may then retrieve available substitute nodes from other domains and/or networks that may lie outside the cluster, but may nonetheless be available to, or accessed by the cluster. The methods and systems may then generate an additional plurality of clusters using one or more of the original nodes of the originally selected clusters and/or one or more of the available substitute nodes.

Abstract: Disclosed herein are system, method, and computer program product embodiments for identifying and managing emerging risks. Businesses, such as those participating in regulated industries, may need to regularly monitor enforcement actions that are cited in a variety of sources. Embodiments disclosed herein provide for scraping information from those sources and comparing it to existing risk events in order to determine possible discrepancies that should be assessed.

Abstract: Methods and systems use an additional determination to generate predictions of future data processing load predictions. Specifically, the methods and systems generate additional predictions based on other data sets and data calculation methodologies (e.g., data with non-homogenous time dependencies). The methods and systems then use these additional predictions to determine whether or not the prediction of the real-time average of data processing loads is an outlier. Thus, the methods and systems generate a time-specific data processing prediction.

Abstract: Aspects of the subject disclosure may include, for example, detecting communications between a source device and a destination device, wherein the communications relate to a particular context and are facilitated over a first network associated with the destination device, determining a state or trust level for the particular context based on reference data, detecting a change in behavior of the source device, updating the state or trust level based on the detecting the change in behavior of the source device, resulting in an updated state or trust level, identifying a loss of trust condition based on the updated state or trust level, restricting communications between the source device and the destination device, and performing a trust rebuild process in an attempt to address the loss of trust condition and to enable the source device to resume communications with the destination device. Other embodiments are disclosed.

Abstract: Unique key fields in structured data is a critical characteristic of data which plays significant role in data management. Profiling high volume of data for discovering all possible unique keys with high accuracy is a costly and time taking affair. A method and system for finding one or more unique entities in a data have been provided. The one or more unique entities obtained by this approach are complete and the response time is quick. The method is scalable to increasing volume of data and number of fields. The system is configured to perform the analysis process in multiple phases taking the less volume initially and increasing it gradually, thereby reducing the load on later phases as the unique results found with light volume phases. The method also comprises a time check mechanism after different stages if a user wants to do discovery for limited time.

Abstract: Disclosed are methods of isolating T cells and TCRs having antigenic specificity for a mutated amino acid sequence encoded by a cancer-specific mutation. Also disclosed are related methods of preparing a population of cells, populations of cells, TCRs, pharmaceutical compositions, and methods of treating or preventing cancer.

Abstract: This disclosure relates to field of machine learning. The outcome of the ML model translates to economic damage for a business. While the risk associated with outcome of ML model can be mitigated by interpreting/explanation each prediction of the ML model, interpreting ML models is challenging as ML models are built in dynamically changing complex mathematical design. The disclosure is a technique for interpreting machine learning model's prediction by computing a percentage contribution of each of the predictors. The percentage contribution indicates an importance of each of the predictors during prediction by the ML model. The percentage contribution is computed in several steps using several parameters associated with the ML Model including a pre-defined threshold of the ML model, an input feature vector comprising a plurality of predictors, an original prediction (N) for each predictor, a pre-determined duplication factor, and a plurality of pre-trained data statistics.

Abstract: Computer vision systems and methods for hazard detection from digital images and videos are provided. The system obtains media content indicative of an asset, preprocesses the media content, and extracts, based at least in part on one or more feature extractors, features from the preprocessed media content. The system determines, based at least in part on one or more classifiers, a value associated with a hazard, which can indicate the likelihood of a media content having the hazard. The system determines that the media content includes the hazard based at least in part on a comparison of the value to a threshold value. The system can generate a visual indication in the image indicative of the hazard.

Abstract: This disclosure relates generally to methods and systems for determining the power load disaggregation profile of a building. Most of the conventional techniques are algorithmic centric, specific to certain scenarios and does not employ the low-sampling rate data due to the complexity involved. Present disclosure determines the power load disaggregation profile of the building using the low-sampling rate power consumption data accurately. According to the present disclosure, firstly, the background power loads are detected and removed from the low-sampled data samples. Next, a robust event detection mechanism is employed to detect the events when the change in the power consumption occurred, and such events are paired using the iterative pairing technique. Further, a set of event clusters are formed using the density-based clustering technique and lastly, each of the set of event clusters are classified with each appliance type using a rule-based classification technique.

Abstract: Flow Shop Scheduling Problems (FSSP) solved using combination of Reinforcement Learning (RL), Genetic Algorithm (GA) and Heuristics is effective if can provide makespan as minimum as possible. Embodiments herein provide a method and system for evolved State-Action-Reward-State-Action (evolved SARSA) RL for flow shop scheduling, which is a hybrid framework of hierarchical RL with evolutionary techniques and heuristics method to solve FSSP. An optimum job sequence is estimated that minimizes the makespan thereby achieving maximum utilization of the resources. The evolutionary and heuristics strategy is applied in a reinforced way of learning for estimating the optimal schedule. The framework refines FSSP solution provided by Reinforced-SARSA (R-SARSA) using the evolutionary Genetic Algorithms (GAs), which is further guided by heuristic in moving towards the optimal solutions and prevents from being stuck at a local optimum.

Abstract: A method is disclosed. The method includes receiving, from a resource provider computer, a token request message comprising a credential, after a user provides the credential to the resource provider computer. The method also includes transmitting, to the resource provider computer, a token response message comprising one or more supplemental data identifiers and one or more tokens associated with the one or more supplemental data identifiers. The one or more tokens are linked to the credential. Then, a user selects a supplemental data identifier. The method also comprises receiving, from the resource provider computer, an authorization request message comprising a token of the one or more tokens, the token linked to the selected supplemental data identifier, and a value, determining the credential using the token; and transmitting, to an authorizing entity computer, a modified authorization request message comprising the credential, the value, and the supplemental data identifier.

Abstract: An electrically conductive flat filament arrangement for a fluid permeable heater assembly for aerosol-generating systems includes a center portion and two side portions. The two side portions are on opposite sides of the center portion. The center portion defines a heating region of the filament arrangement and the side portions define electrical contact regions of the filament arrangement. The center portion and the two side portions each include a plurality of openings. Each plurality of openings defines an open area of the center portion and an open area of each of the two side portions. A percentage of the total area of the center portion including the open area of the center portion is greater than the percentage of the total area of one of the side portions including the open area of the side portion.

Abstract: Disclosed herein are embodiments of a compound that inhibits c-Abl tyrosine kinase (also referred to herein as “c-Abl”). The compound embodiments described herein are novel c-Abl inhibitors that can bind to c-Abl at an allosteric site and inhibit its activity in various pathways. The compound embodiments also are capable of crossing the blood brain barrier and therefore are useful in inhibiting c-Abl activity as it affects pathways and/or proteins in the brain. The compound embodiments described herein are effective therapeutic agents for treating diseases involving c-Abl, such as cancers, motor neuron diseases, and neurodegenerative diseases. Also disclosed herein are embodiments of methods for making and using the c-Abl inhibitory compound embodiments.

Abstract: A computing resource of a cloud computing environment receives, from customers in a customer population, requests to enroll in group-based subscriptions provided by third-party providers. The requests include customer preferences associated with the customers. The computing resource determines customer account attributes for customer accounts, and determines, using a customer matching model, scores for the customers based on the customer preferences and the customer account attributes. The scores predict a successful matching among the customers in the customer population. The computing resource assigns a first subset of the customers in the customer population to a first group of customers based on the scores, enrolls the first group of customers in a first account for a first group-based subscription provided by a first third-party provider, and allocates a payment for the first group-based subscription among a first group of customer accounts associated with customers in the first group of customers.