Abstract: Disclosed is an injection stretch blow molded (ISBM) container containing a surface having a static coefficient of friction (COF) of 0.15 to 0.21, a dynamic COF of 0.06 to 0.1, wherein the surface retains a water contact angle of 76° or higher for up to three minutes after wetting of the surface with a water drop of 14 to 16 mm diameter and the container is made with a polymeric composition containing a high density polyethylene (HDPE) having a dispersity (Mw/Mn) of 9 or higher as measured by GPC; a MI2 of 1 g/10 min or higher as measured by ASTM D-1238; 190° C./2.16 kg, as measured by ASTM D-1238; and an environmental stress crack resistance (ESCR) at 100% Igepal of >150 hours as measured by ASTM D-1693, B.

Abstract: A disclosed method includes a) receiving by a server computer network data comprising a plurality of transaction data for a plurality of transactions. Each transaction data comprises a plurality of data elements with data values. At least one of the plurality of data elements comprises a user identifier for a user. The server computer can then b) generate one or more graphs comprising a plurality of communities based on the network data. The server computer can c) determine fuzzy values for at least some of the data values for each transaction of the plurality of transactions. For each user. the server computer can d) determine fuzzy values for communities within the plurality of communities. The server computer can then e) generate a model using the fuzzy values obtained in steps c) and d), and at least some of the data values.

Abstract: A method is described for iteratively training a policy model, such as a neural network, of a computer-implemented action selection system to control an agent interacting with an environment to perform a task subject to one or more constraints. The task has a reward associated with performance of the task. Each constraint limits to a corresponding threshold the expected value of the total of a corresponding constraint function which if the future actions of the agent are chosen according to the policy model, and each constraint is associated with a corresponding multiplier variable. In each iteration, a mixed reward function is generated based on values for the multiplier variables generated in the preceding iteration, and estimates of the rewards and the values of constraint reward functions if the actions are chosen based on the policy model generated in the preceding iteration.

Abstract: A blown polypropylene film or sheet is disclosed. The film or sheet can include at least 95 wt. % of a polypropylene, and at least one ?-nucleating agent or crystallization inhibitor, where the polypropylene blown film or sheet has a thickness of 0.5 mils to 15 mils, and where the polypropylene blown film has an increased dart impact strength, as measure by ASTM D1709, when compared with a second polypropylene blown film or sheet that has the same components in the same wt. % amounts as the polypropylene blown film or sheet except that the second polypropylene blown film or sheet does not include the at least one ?-nucleating agent or crystallization inhibitor.

Abstract: A system and method are described which attempt to connect merchants with phone numbers that are known to be associated with fraudulent users.

Abstract: A method for signal modulation includes: receiving network signals from a plurality of participants; analyzing the received network signals to detect latent signals; processing the network signals based on one or more external event data; processing the network signals to exclude sensitive data in the network signals and the latent signals; and encapsulating pan-network signals based on the processed network signals.

Abstract: A method for event detection includes: obtaining a subpopulation data from a graph structure for performing a graph analysis, wherein the subpopulation data is associated with personality and demographic characteristics of users; obtaining a user profile associated with a target user; inferring psychological traits of the user by performing the graph analysis based on the user profile and the subpopulation data; performing an outcome linkage analysis based on labeled event outcome profiles and the inferred psychological traits to generate personalized knowledge graph data associated with the target user; and profiling, monitoring, or performing an anomaly detection for event data streams based on the personalized knowledge graph data.

Abstract: Computer executable instructions including code sections are received and compared to previously analyzed computer executable instructions. The code sections are then analyzed and assigned a risk score. If the risk score is over a threshold, an alarm may be communicated or the system may substitute computer executable instructions that may have been created according to a standard or have been previously approved.

Abstract: A method includes receiving, by a server computer, data of a communication device; training, by the server computer, a neural network model based on the data of the communication device and communication device metadata from one or more additional communication devices, to generate a machine learning model configured to determine, based on a metadata associated with an application, a security value related to an indication of a security threat; and transmitting the machine learning model to the communication device. The communication device can use the machine learning model to determine the security value, by inputting the metadata associated with the application, as a vectorized data into the machine learning model. The communication device can determine whether to run or install the application based upon the security value.

Abstract: A method is disclosed and includes receiving, by a first communication device, a first local authentication model, the first local authentication model being derived from a master authentication model at a remote server computer, and receiving a request to perform an interaction with a second communication device, the interaction being performed in an offline manner. The method may further include applying, by the first communication device, the first local authentication model to the interaction to determine a first authentication result and determining whether or not to allow the interaction to proceed based upon the first authentication result. The method may also include updating the first local authentication model using the master authentication model when the first communication device is online.

Abstract: Computer-implemented systems and methods are disclosed herein for use within secure multi-party computation. A system and method are used for storing an operation preference and a cryptographic preference. A data set is stored based on the operation preference and the cryptographic preference. A determination is made that processing the query involves performing an allowable operation on the data set based on the operation preference.

Abstract: A method for the use of electronic transactional tokens includes: generating a plurality of transactional tokens including a first token; associating each of the transactional tokens with a plurality of users, the first token associated with a first user; monitoring usage of the transactional tokens in a plurality of transactions in a local region or network; and in response to receiving transactional data for the first transaction, updating the first token from a first state to a second state (e.g., to provide a benefit when the token is applied in the local region or network). The tokens may be generated and monitored using a token processing system, which uses transaction data received by a transaction handler that is handling transaction processing for the transactions.

Abstract: Embodiments are directed to a method for determining an interview script in a claims submission. The method may comprising receiving data relating to a claim being submitted, which may include claims submission data input by a user, information relating to the user, and one or more features. Data associated with the one or more features may be determined from an artificial intelligence model. A first score based on the data associated with the one or more features and data associated with the information relating to the user may be determined and used to determine an interview script. In one embodiment, questions in the interview script may continue to be provided to the interviewer computer if a continually updated score remains above a predetermined threshold. In another embodiment, the user may be routed to a live interview with a human representative if a continually updated score drops below a predetermined threshold.

Abstract: Computer-implemented systems and methods are disclosed herein for use within secure multi-party computation. A system and method are used for storing an operation preference and a cryptographic preference. A data set is stored based on the operation preference and the cryptographic preference. A determination is made that processing the query involves performing an allowable operation on the data set based on the operation preference.

Abstract: A method including collecting, by a communication device comprising a machine learning model obtained at least in part from a server computer, metadata associated with an application. The communication device can then embed the metadata to form vectorized data. The communication device can input the vectorized data into the machine learning model to obtain a security value. The communication device can determine whether to run or install the application based upon the security value.

Abstract: A method includes receiving, by a server computer, data of a communication device; training, by the server computer, a neural network model based on the data of the communication device and communication device metadata from one or more additional communication devices, to generate a machine learning model configured to determine, based on a metadata associated with an application, a security value related to an indication of a security threat; and transmitting the machine learning model to the communication device. The communication device can use the machine learning model to determine the security value, by inputting the metadata associated with the application, as a vectorized data into the machine learning model. The communication device can determine whether to run or install the application based upon the security value.

Abstract: Embodiments are directed to a method for determining an interview script in a claims submission. The method may comprising receiving data relating to a claim being submitted, which may include claims submission data input by a user, information relating to the user, and one or more features. Data associated with the one or more features may be determined from an artificial intelligence model. A first score based on the data associated with the one or more features and data associated with the information relating to the user may be determined and used to determine an interview script. In one embodiment, questions in the interview script may continue to be provided to the interviewer computer if a continually updated score remains above a predetermined threshold. In another embodiment, the user may be routed to a live interview with a human representative if a continually updated score drops below a predetermined threshold.

Abstract: A disclosed method an analysis computer determining a rolling window associated with interaction data for interactions that occur over time. The analysis computer can retrieve interaction data for interactions occurring in the rolling window. The analysis computer can then generate pseudo interaction data based upon historical interaction data. The analysis computer can optionally embed the interaction data for the interactions occurring within the rolling window and the pseudo interaction data to form interaction data matrices. The analysis computer can then form a neural network model using the interaction data matrices, which is derived from the interaction data in the rolling window and the pseudo interaction data.

Abstract: A computer system includes a memory configured to store instructions, and one or more processors configured to execute the instructions to cause the computer system to perform a method for event detection. The method includes obtaining a user profile and a persona category associated with the user profile corresponding to a user; receiving first data associated with the user and second data associated with one or more environmental or situational factors; detecting an event based on the first data or the second data; and querying a database in response to the detected event to determine one or more recommended actions for the user based on the user profile and the persona category of the user.

Abstract: A method for the use of electronic transactional tokens includes: generating a plurality of transactional tokens including a first token; associating each of the transactional tokens with a plurality of users, the first token associated with a first user; monitoring usage of the transactional tokens in a plurality of transactions in a local region or network; and in response to receiving transactional data for the first transaction, updating the first token from a first state to a second state (e.g., to provide a benefit when the token is applied in the local region or network). The tokens may be generated and monitored using a token processing system, which uses transaction data received by a transaction handler that is handling transaction processing for the transactions.