Framework for optimizing intelligence collection requirements

In the military, typical mission execution goes through cycles of intelligence collection and action planning phases. For complex operations where many parameters affect the outcomes of the mission, several steps may be taken for intelligence collection before the optimal Course of Action is actually carried out. Human analytics suggests the steps of: (1) anticipating plausible futures, (2) determining information requirements, and (3) optimize the choice of feasible and cost-effective intelligence requirements. This work formalizes this process by developing a decision support tool to determine information requirements needed to differentiate critical plausible futures, and formulating a mixed integer programming problem to trade-off the feasibility and benefits of intelligence collection requirements. Course of Action planning has been widely studied in the military domain, but mostly in an abstract fashion. Intelligence collection, while intuitively aiming at reducing uncertainties, should ultimately produce optimal outcomes for mission success. Building on previous efforts, this work studies the effect of plausible futures estimated based on current adversary activities. A set of differentiating event attributes are derived for each set of high impact futures, forming a candidate collection requirement action. The candidate collection requirement actions are then used as inputs to a Mixed Integer Programming formulation, which optimizes the plausible future mission state subject to timing and cost constraints. The plausible future mission state is estimated by assuming that the Collection Requirement Actions can potentially avert the damages adversary future activities might cause. A case study was performed to demonstrate several use cases for the overall framework

The Brain on Low Power Architectures - Efficient Simulation of Cortical Slow Waves and Asynchronous States

Efficient brain simulation is a scientific grand challenge, a parallel/distributed coding challenge and a source of requirements and suggestions for future computing architectures. Indeed, the human brain includes about 10^15 synapses and 10^11 neurons activated at a mean rate of several Hz. Full brain simulation poses Exascale challenges even if simulated at the highest abstraction level. The WaveScalES experiment in the Human Brain Project (HBP) has the goal of matching experimental measures and simulations of slow waves during deep-sleep and anesthesia and the transition to other brain states. The focus is the development of dedicated large-scale parallel/distributed simulation technologies. The ExaNeSt project designs an ARM-based, low-power HPC architecture scalable to million of cores, developing a dedicated scalable interconnect system, and SWA/AW simulations are included among the driving benchmarks. At the joint between both projects is the INFN proprietary Distributed and Plastic Spiking Neural Networks (DPSNN) simulation engine. DPSNN can be configured to stress either the networking or the computation features available on the execution platforms. The simulation stresses the networking component when the neural net - composed by a relatively low number of neurons, each one projecting thousands of synapses - is distributed over a large number of hardware cores. When growing the number of neurons per core, the computation starts to be the dominating component for short range connections. This paper reports about preliminary performance results obtained on an ARM-based HPC prototype developed in the framework of the ExaNeSt project. Furthermore, a comparison is given of instantaneous power, total energy consumption, execution time and energetic cost per synaptic event of SWA/AW DPSNN simulations when executed on either ARM- or Intel-based server platforms

Early Assessment of Environmental Interventions to Prevent Childhood Obesity

Outlines January 2006 discussions on evaluating the plausibility -- clear, shared goals, activities, and expected outcomes -- and feasibility of various environmental interventions to help prevent childhood obesity. Discusses evaluation design

Agent-based modeling: a systematic assessment of use cases and requirements for enhancing pharmaceutical research and development productivity.

A crisis continues to brew within the pharmaceutical research and development (R&D) enterprise: productivity continues declining as costs rise, despite ongoing, often dramatic scientific and technical advances. To reverse this trend, we offer various suggestions for both the expansion and broader adoption of modeling and simulation (M&S) methods. We suggest strategies and scenarios intended to enable new M&S use cases that directly engage R&D knowledge generation and build actionable mechanistic insight, thereby opening the door to enhanced productivity. What M&S requirements must be satisfied to access and open the door, and begin reversing the productivity decline? Can current methods and tools fulfill the requirements, or are new methods necessary? We draw on the relevant, recent literature to provide and explore answers. In so doing, we identify essential, key roles for agent-based and other methods. We assemble a list of requirements necessary for M&S to meet the diverse needs distilled from a collection of research, review, and opinion articles. We argue that to realize its full potential, M&S should be actualized within a larger information technology framework--a dynamic knowledge repository--wherein models of various types execute, evolve, and increase in accuracy over time. We offer some details of the issues that must be addressed for such a repository to accrue the capabilities needed to reverse the productivity decline

From Pine Cones to Read Clouds: Rescaffolding the Megagenome of Sugar Pine (Pinus lambertiana).

We investigate the utility and scalability of new read cloud technologies to improve the draft genome assemblies of the colossal, and largely repetitive, genomes of conifers. Synthetic long read technologies have existed in various forms as a means of reducing complexity and resolving repeats since the outset of genome assembly. Recently, technologies that combine subhaploid pools of high molecular weight DNA with barcoding on a massive scale have brought new efficiencies to sample preparation and data generation. When combined with inexpensive light shotgun sequencing, the resulting data can be used to scaffold large genomes. The protocol is efficient enough to consider routinely for even the largest genomes. Conifers represent the largest reference genome projects executed to date. The largest of these is that of the conifer Pinus lambertiana (sugar pine), with a genome size of 31 billion bp. In this paper, we report on the molecular and computational protocols for scaffolding the P. lambertiana genome using the library technology from 10× Genomics. At 247,000 bp, the NG50 of the existing reference sequence is the highest scaffold contiguity among the currently published conifer assemblies; this new assembly's NG50 is 1.94 million bp, an eightfold increase

EOR as sequestration: Geoscience perspective

CO2 Enhanced Oil Recovery (EOR) has a development and operational history several decades longer than geologic sequestration of CO2 designed to benefit the atmosphere and provides much of the experience on which confidence in the newer technology is based. With modest increases in surveillance and accounting, future CO2 EOR using anthropogenic CO2 (CO2-A) captured to decrease atmospheric emissions can be used as part of a sequestration program.Bureau of Economic Geolog

Evaluation of spoken document retrieval for historic speech collections

The re-use of spoken word audio collections maintained by audiovisual archives is severely hindered by their generally limited access. The CHoral project, which is part of the CATCH program funded by the Dutch Research Council, aims to provide users of speech archives with online, instead of on-location, access to relevant fragments, instead of full documents. To meet this goal, a spoken document retrieval framework is being developed. In this paper the evaluation efforts undertaken so far to assess and improve various aspects of the framework are presented. These efforts include (i) evaluation of the automatically generated textual representations of the spoken word documents that enable word-based search, (ii) the development of measures to estimate the quality of the textual representations for use in information retrieval, and (iii) studies to establish the potential user groups of the to-be-developed technology, and the first versions of the user interface supporting online access to spoken word collections