Abstract: The exemplary embodiments of the invention provide at least a method and machine including a memory tangibly embodying at least one program of instructions executable by at least one processor to perform operations with the machine including inputting project data of at least one project, applying more than one layer of different predictive models to the input project data, where the different predictive models are applied in a hierarchical manner across the more than one layer taking into account at least one of data availability and a stage of a lifecycle of each of the at least one project, and based on the applied more than one predictive model, determining a predicted future performance for each project of the at least one project

Abstract: The exemplary embodiments of the invention provide at least a method and machine including a memory tangibly embodying at least one program of instructions executable by at least one processor to perform operations with the machine including inputting project data of at least one project, applying more than one layer of different predictive models to the input project data, where the different predictive models are applied in a hierarchical manner across the more than one layer taking into account at least one of data availability and a stage of a lifecycle of each of the at least one project, and based on the applied more than one predictive model, determining a predicted future performance for each project of the at least one project

Abstract: A method, an apparatus and an article of manufacture for modeling a task-site allocation. The method includes generating a task-site allocation network based on at least one site-task pair and at least one site-centric constraint of at least two sites, wherein generating a task-site allocation network comprises generating a task-specific constraints model based on task context information and generating a task-site pair that satisfies at least one constraint based on the task-specific constraints model, and determining a preferred allocation of task to site by comparing estimated task-site allocation cost between a single site allocation and a distributed site allocation among the at least two sites.

Abstract: A method, an apparatus and an article of manufacture for modeling a task-site allocation. The method includes generating a task-site allocation network based on at least one site-task pair and at least one site-centric constraint of at least two sites, wherein generating a task-site allocation network comprises generating a task-specific constraints model based on task context information and generating a task-site pair that satisfies at least one constraint based on the task-specific constraints model, and determining a preferred allocation of task to site by comparing estimated task-site allocation cost between a single site allocation and a distributed site allocation among the at least two sites.

Abstract: Ultra-wide bandwidth (UWB) transmission is a promising technology for indoor localization due to its fine delay resolution and obstacle-penetration capabilities. However, the presence of walls and other obstacles present a significant challenge in terms of localization, as they result in positively biased distance estimates. Measurement campaigns with FCC-compliant UWB radios can quantify effects of non-line-of-sight (NLOS) propagation. Features of waveforms measured during a campaign can be extracted for use in distinguishing between NLOS and line-of-sight situations in embodiments of the present invention. Embodiments further include classification and regression methods based on machine learning that improve the localization performance while relying solely on the received signal. Applications for systems employing an example embodiment of the invention include indoor or outdoor search and recovery with high accuracy and low cost.