Publications

Bernard, Michael L.; Bernard, Michael L.

Abstract not provided.

Proceedings - Winter Simulation Conference

Naugle, Asmeret B.; Miner, Nadine E.; Aamir, Munaf S.; Jeffers, Robert F.; Verzi, Stephen J.; Bernard, Michael L.

We created a cognition-focused system dynamics model to simulate the dynamics of smoking tendencies based on media influences and communication of opinions. We based this model on the premise that the dynamics of attitudes about smoking can be more deeply understood by combining opinion dynamics with more in-depth psychological models that explicitly explore the root causes of behaviors of interest. Results of the model show the relative effectiveness of two different policies as compared to a baseline: A decrease in advertising spending, and an increase in educational spending. The initial results presented here indicate the utility of this type of simulation for analyzing various policies meant to influence the dynamics of opinions in a population.

Passell, Howard D.; Passell, Howard D.; Aamir, Munaf S.; Aamir, Munaf S.; Bernard, Michael L.; Bernard, Michael L.; Beyeler, Walter E.; Beyeler, Walter E.; Fellner, Karen M.; Fellner, Karen M.; Hayden, Nancy K.; Hayden, Nancy K.; Jeffers, Robert F.; Jeffers, Robert F.; Keller, Elizabeth J.; Keller, Elizabeth J.; Malczynski, Leonard A.; Malczynski, Leonard A.; Mitchell, Michael D.; Mitchell, Michael D.; Silver, Emily S.; Silver, Emily S.; Tidwell, Vincent C.; Tidwell, Vincent C.; Villa, Daniel V.; Villa, Daniel V.; Vugrin, Eric D.; Vugrin, Eric D.; Engelke, Peter E.; Engelke, Peter E.; Burrow, Mat B.; Burrow, Mat B.; Keith, Bruce K.; Keith, Bruce K.

The Integrated Human Futures Project provides a set of analytical and quantitative modeling and simulation tools that help explore the links among human social, economic, and ecological conditions, human resilience, conflict, and peace, and allows users to simulate tradeoffs and consequences associated with different future development and mitigation scenarios. In the current study, we integrate five distinct modeling platforms to simulate the potential risk of social unrest in Egypt resulting from the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile in Ethiopia. The five platforms simulate hydrology, agriculture, economy, human ecology, and human psychology/behavior, and show how impacts derived from development initiatives in one sector (e.g., hydrology) might ripple through to affect other sectors and how development and security concerns may be triggered across the region. This approach evaluates potential consequences, intended and unintended, associated with strategic policy actions that span the development-security nexus at the national, regional, and international levels. Model results are not intended to provide explicit predictions, but rather to provide system-level insight for policy makers into the dynamics among these interacting sectors, and to demonstrate an approach to evaluating short- and long-term policy trade-offs across different policy domains and stakeholders. The GERD project is critical to government-planned development efforts in Ethiopia but is expected to reduce downstream freshwater availability in the Nile Basin, fueling fears of negative social and economic impacts that could threaten stability and security in Egypt. We tested these hypotheses and came to the following preliminary conclusions. First, the GERD will have an important short-term impact on water availability, food production, and hydropower production in Egypt, depending on the short- term reservoir fill rate. Second, the GERD will have a very small impact on water availability in the Nile Basin over the longer term. Depending on the GERD fill rate, short-term (e.g., within its first 5 years of operation) annual losses in Egyptian food production may peak briefly at 25 percent. Long-term (e.g., 15 to 30 year) cumulative losses in Egypt's food production may be less than 3 percent regardless of the fill rate, with the GERD having essentially no impact on projected annual food production in Egypt about 25 years after opening. For the quick fill rates, the short-term losses may be sufficient to create an important decrease in overall household health among the general population, which, along with other economic stressors and different strategies employed by the government, could lead to social unrest. Third, and perhaps most importantly, our modeling suggests that the GERD's effect on Egypt's food and water resources is small when compared to the effect of projected Egyptian population and economic growth (and the concomitant increase in water consumption). The latter dominating factors are exacerbated in the modeling by natural climate variability and may be further exacerbated by climate change. Our modeling suggests that these growth dynamics combine to create long-term water scarcity in Egypt, regardless of the Ethiopian project. All else being equal, filling strategies that employ slow fill rates for the GERD (e.g., 8 to 13 years) may mitigate the risks in future scenarios for Egypt somewhat, but no policy or action regarding the GERD is likely to significantly alleviate the projected water scarcity in Egypt's Nile Basin. However, general beliefs among the Egyptian populace regarding the GERD as a major contributing factor for scarcities in Egypt could make Ethiopia a scapegoat for Egyptian grievances -- contributing to social unrest in Egypt and generating undesirable (and unnecessary) tension between these two countries. Such tension could threaten the constructive relationships between Egypt and Ethiopia that are vital to maintaining stability and security within and between their respective regional spheres of influence, Middle East and North Africa, and the Horn of Africa.

Vineyard, Craig M.; Aimone, James B.; Bernard, Michael L.; Carlson, Kristofor D.; Chance, Frances S.; Forsythe, James C.; James, Conrad D.; Rothganger, Fredrick R.; Severa, William M.; Speed, Ann S.; Verzi, Stephen J.; Warrender, Christina E.; Wagner, John S.; Miller, Leann A.

Abstract not provided.

Bernard, Michael L.

The purpose of this work is to create a generalizable data- and theory-supported capability to better understand and anticipate (with quantifiable uncertainty): 1) how the dynamics of allegiance formations between various groups and society are impacted by active conflict and by third-party interventions and 2) how/why extremist allegiances co-evolve over time due to changing geopolitical, sociocultural, and military conditions.

Bernard, Michael L.; Backus, George A.; Naugle, Asmeret B.; Jeffers, Robert F.; Damron, Regan W.

Abstract not provided.

Bernard, Michael L.

Abstract not provided.

Backus, George A.; Bernard, Michael L.; Naugle, Asmeret B.

Abstract not provided.

Naugle, Asmeret B.; Miner, Nadine E.; Aamir, Munaf S.; Jeffers, Robert F.; Verzi, Stephen J.; Bernard, Michael L.

Abstract not provided.

Procedia Manufacturing

Jeffers, Robert F.; Bernard, Michael L.; Passell, Howard D.; Silver, Emily J.

The construction of the Grand Ethiopian Renaissance Dam (GERD) has generated tensions between Egypt and Ethiopia over control of the Nile River in Northern Africa. However, tensions within Egypt have also been pronounced, leading up to and following the Arab Spring uprising of 2011. This study used the Behavior Influence Assessment (BIA) framework to simulate a dynamic hypothesis regarding how tensions within Egypt may evolve given the impacts of the GERD. Primarily, we addressed the interplay between four parties over an upcoming ten-year period: the Egyptian Regime, the Military-Elite, the Militant population, and the non-Militant population. The core tenant of the hypothesis is that rising food prices was a strong driver to the unrest leading up to the Arab Spring events and that this same type of economic stress could be driven by the GERD—albeit with different political undertones. Namely, the GERD offers the Regime a target for inciting nationalism, and while this may buy the regime time to fix the underlying economic impacts, ultimately there exists a tipping point beyond which exponentially increasing unrest is unavoidable without implementing strong measures, such as state militarization.

Backus, George A.; Naugle, Asmeret B.; Bernard, Michael L.; Aamir, Munaf S.; Glickman, Matthew R.; Jeffers, Robert F.; Silva, Austin R.; Trumbo, Derek T.; Verzi, Stephen J.

Abstract not provided.

Procedia Manufacturing

Bernard, Michael L.

There is a recognized need to develop computational models that can represent and simulate the decision making process of various groups across socio-cultural domains [5]. Yet, developing such models can be greatly hampered by the need to acquire and represent information pertaining to the psychological and social aspects of decision-making within these groups. Currently, there are numerous techniques and tools to help facilitate the elicitation and structuring of knowledge within expert-type systems—particularly those that focus on technical processes such as mechanical troubleshooting [3]. However, few techniques and tools have been developed for models that are intended to represent and assess the decision making of groups within different societies—particularly including cultural elements within these societies. This paper seeks to help address this challenge by discussing an approach to eliciting and structuring cross-cultural psychosocial and behavioral-economic elements within a theory-based assessment model. This work was developed to address the needs of Sandia National Laboratories’ Behavioral Influence Assessment modeling capability, which assesses decision-making within societies. The main component of the knowledge engineering effort is what we call the “knowledge structure.” The knowledge structure acts as scaffolding for the organization of psychosocial processes underlying decision-making, as well as the actual content of that knowledge with respect to a modeled society.

Aimone, James B.; Bernard, Michael L.; Vineyard, Craig M.; Verzi, Stephen J.

Adult neurogenesis in the hippocampus region of the brain is a neurobiological process that is believed to contribute to the brain's advanced abilities in complex pattern recognition and cognition. Here, we describe how realistic scale simulations of the neurogenesis process can offer both a unique perspective on the biological relevance of this process and confer computational insights that are suggestive of novel machine learning techniques. First, supercomputer based scaling studies of the neurogenesis process demonstrate how a small fraction of adult-born neurons have a uniquely larger impact in biologically realistic scaled networks. Second, we describe a novel technical approach by which the information content of ensembles of neurons can be estimated. Finally, we illustrate several examples of broader algorithmic impact of neurogenesis, including both extending existing machine learning approaches and novel approaches for intelligent sensing.

Naugle, Asmeret B.; Miner, Nadine E.; Aamir, Munaf S.; Jeffers, Robert F.; Verzi, Stephen J.; Bernard, Michael L.

Abstract not provided.

Naugle, Asmeret B.; Bernard, Michael L.

Abstract not provided.

Bernard, Michael L.

Abstract not provided.

Tedeschi, William J.; Stamber, Kevin L.; Pless, Daniel J.; Bernard, Michael L.

Abstract not provided.

Verzi, Stephen J.; Bernard, Michael L.; Aimone, James B.

Abstract not provided.

Chu, Dahlon D.; Wiegandt, David A.; Harrison, Kevin L.; McCrory, Fredrick M.; Davis, Christopher E.; Bernard, Michael L.; Abbott, Robert G.; Clifford, Bernard P.

Abstract not provided.

Proposed for publication in Security Informatics.

Verzi, Stephen J.; Bernard, Michael L.; Taylor, Shawn E.; Dubicka, Irene D.

Abstract not provided.

Bernard, Michael L.

Abstract not provided.

Vineyard, Craig M.; Verzi, Stephen J.; Taylor, Shawn E.; Dubicka, Irene D.; Bernard, Michael L.

This report describes the laboratory directed research and development work to model relevant areas of the brain that associate multi-modal information for long-term storage for the purpose of creating a more effective, and more automated, association mechanism to support rapid decision making. Using the biology and functionality of the hippocampus as an analogy or inspiration, we have developed an artificial neural network architecture to associate k-tuples (paired associates) of multimodal input records. The architecture is composed of coupled unimodal self-organizing neural modules that learn generalizations of unimodal components of the input record. Cross modal associations, stored as a higher-order tensor, are learned incrementally as these generalizations form. Graph algorithms are then applied to the tensor to extract multi-modal association networks formed during learning. Doing so yields a novel approach to data mining for knowledge discovery. This report describes the neurobiological inspiration, architecture, and operational characteristics of our model, and also provides a real world terrorist network example to illustrate the model's functionality.

Naugle, Asmeret B.; Bernard, Michael L.; Backus, George A.; Glickman, Matthew R.; Verzi, Stephen J.

Abstract not provided.

Verzi, Stephen J.; Bernard, Michael L.; Taylor, Shawn E.; Dubicka, Irene D.; McClain, Jonathan T.

Abstract not provided.

Bernard, Michael L.; Verzi, Stephen J.; Taylor, Shawn E.; Dubicka, Irene D.; McClain, Jonathan T.; Vineyard, Craig M.

Abstract not provided.