Abstract: A power distribution system is described. The system comprises connectable modules, including an input module and at least a first output module. The input module comprises a power input interface configured to receive alternating current power and direct current power from external sources, an output controller configured to generate control signals that control power delivery by the first output module, and an output module interface having i) a power output interface that provides AC power and DC power to the first output module, and ii) a control interface that provides the control signals to the first output module for controlling the power delivery. The first output module comprises an input module interface configured to engage the output module interface and receive the AC power and the DC power from the power output interface, and two or more outlets, each configured to deliver either the AC power or the DC power.

Abstract: A multi-dimensional human resource allocation adviser integrates with one or more employee skill set data sources and processes and aggregates both initial/static and dynamic skill set data from those sources. Machine learning algorithms are then used to normalize and rank the aggregated employee skills with respect to the skill set and requirements associated with a given task, project, or case. The set of employees determined to have employee skill sets that most closely match the skill set and other requirements associated with the given project, task, or case are then filtered based on rules and constraints determined by the requirements of the business and/or the client. The best employee match, or matches, remaining after the rules and constraints filtering are then recommended for assignment/allocation to the given task, project, or case.

Abstract: A multi-dimensional human resource allocation adviser integrates with one or more employee skill set data sources and processes and aggregates both initial/static and dynamic skill set data from those sources. Machine learning algorithms are then used to normalize and rank the aggregated employee skills with respect to the skill set and requirements associated with a given task, project, or case. The set of employees determined to have employee skill sets that most closely match the skill set and other requirements associated with the given project, task, or case are then filtered based on rules and constraints determined by the requirements of the business and/or the client. The best employee match, or matches, remaining after the rules and constraints filtering are then recommended for assignment/allocation to the given task, project, or case.