Abstract: An electrical shielding member for a network connector includes a receiving portion for receiving a cable end of a shielded cable and a contact beam extending from the receiving portion. The contact beam has a first contact point for electrically connecting the electrical shielding member to a counter shielding member of a counter network connector, and a coupling portion, provided at a distal end of the contact beam. The coupling portion is configured to be coupled to a corresponding coupling portion of a network connector housing. The network connector is configured for network communication at data rates of at least 100 megabits per second (Mbit/s) and preferably at least 1 gigabits per second (Gbit/s).

Abstract: A unidirectional workflow execution engine is accessed. The unidirectional workflow includes at least a first node and a second node, where the first node is executed before the second node. A timeout setting of the first node is retrieved. An actual execution time of the first node is determined. A difference between the retrieved timeout setting and the actual execution time of the first node is calculated. A timeout setting of the second node is retrieved. The timeout setting of the second node is modified by adding, to the retrieved timeout setting of the second node, the calculated difference between the retrieved timeout setting and the execution time of the first node.

Abstract: Methods and systems for automatically discovering data types required by a computer-based rule engine for evaluating a transaction request are presented. Multiple potential paths for evaluating the transaction request according to the rule engine are determined. An abstract syntax tree may be generated based on the rule engine to determine the multiple potential paths. Based on an initial set of data extracted from the transaction request, one or more potential paths that are determined to be irrelevant to evaluating the transaction request are identified. Types of data required to evaluate the transaction request according to the remaining potential paths are determined. Only data that corresponds to the determined types of data is retrieved to evaluate the transaction request.

Abstract: Methods and systems for using machine learning to automatically determine a data loading configuration for a computer-based rule engine are presented. The computer-based rule engine is configured to use rules to evaluate incoming transaction requests. Data of various data types may be required by the rule engine when evaluating the incoming transaction requests. The data loading configuration specifies pre-loading data associated with at least a first data type and lazy-loading data associated with at least a second data type. Statistical data such as use rates and loading times associated with the various data types may be supplied to a machine learning module to determine a particular loading configuration for the various data types. The computer-based rule engine then loads data according to the data loading configuration when evaluating a subsequent transaction request.

Abstract: Methods and systems for providing credit through USSD are described. A user dials a short USSD code onto his or her mobile device, and is prompted to enter an authentication code to confirm his or her identity. Once authenticated, the user is presented with a USSD menu that includes an option to pay with credit. The user chooses this option, and is prompted to enter an amount for the credit. The service provider checks the credit score of the user, and approves or denies credit based on the score. When the credit score is acceptable, the user is asked to enter the merchant ID for the store and to confirm checkout. The amount for the purchase is then transferred to the merchant by the service provider.