P3 Puckster Partial Automation

MOVES Institute Research ProjectAutomated placement of sonobuoys to maintain contact with tracks and reduce NCTE operator workload

Innovation, Entrepreneurialism, and Intellectual Property from a Technologist’s Point of View

The article of record as published may be located at http://dx.doi.org/10.2312/egve.20162028We will discuss the key elements of taking an idea from its conception to commercialized product, with a particular focus on how this happens (or more importantly doesn’t happen often enough) within universi- ties. Technology transfer is how a technical innovation is able to exit the laboratory in order to become a product. How does that work? Who is involved? We will then discuss the open innovation model whereby technical innovations are spun out via licensing or sale, and they are also brought in via the same means. Innovation has become a sociological phenomenon, but we have to understand how it works in practice, how we can and should protect our ideas, and thus put our innovations in the best possible position to suc- ceed. The discussion will conclude with thoughts on what universities can do to be a catalyst rather than a barrier to technical innovation and successful commercial ventures that have their roots in the university

Towards Learned Anticipation in Complex Stochastic Environments

We describe a novel methodology by which a software agent can learn to predict future events in complex stochastic environmentals. It is particularly relevant to environments that are construed specifically so as to be able to support high-performance software agents, such as video games. We present results gathered from a first prototype of our approach. The technique presented may have applications that range beyond improving agent performance, in particular to user modeling in the service of automated game testing

Unified derivation of phase-field models for alloy solidification from a grand-potential functional

In the literature, two quite different phase-field formulations for the problem of alloy solidification can be found. In the first, the material in the diffuse interfaces is assumed to be in an intermediate state between solid and liquid, with a unique local composition. In the second, the interface is seen as a mixture of two phases that each retain their macroscopic properties, and a separate concentration field for each phase is introduced. It is shown here that both types of models can be obtained by the standard variational procedure if a grand-potential functional is used as a starting point instead of a free-energy functional. The dynamical variable is then the chemical potential instead of the composition. In this framework, a complete analogy with phase-field models for the solidification of a pure substance can be established. This analogy is then exploited to formulate quantitative phase-field models for alloys with arbitrary phase diagrams. The precision of the method is illustrated by numerical simulations with varying interface thickness.Comment: 36 pages, 1 figur

Further Evidence For The Upward Transport Of Minerals Through The Phloem Of Stems

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141651/1/ajb209156.pd

Dynamics of gas bubble growth in a supersaturated solution with Sievert's solubility law

This paper presents a theoretical description of diffusion growth of a gas bubble after its nucleation in supersaturated liquid solution. We study systems where gas molecules completely dissociate in the solvent into two parts, thus making Sievert's solubility law valid. We show that the difference between Henry's and Sievert's laws for chemical equilibrium conditions causes the difference in bubble growth dynamics. Assuming that diffusion flux is steady we obtain a differential equation on bubble radius. Bubble dynamics equation is solved analytically for the case of homogeneous nucleation of a bubble, which takes place at a significant pressure drop. We also obtain conditions of diffusion flux steadiness. The fulfillment of these conditions is studied for the case of nucleation of water vapor bubbles in magmatic melts.Comment: 22 pages, 3 figure

Utilizing Biological Models to Determine the Recruitment of the Irish Republican Army

Sociological models (e.g., social network analysis, small-group dynamics and gang models) have historically been used to predict the behavior of terrorist groups. However, they may not be the most appropriate method for understanding the behavior of terrorist organizations because the models were not initially intended to incorporate violent behavior of its subjects. Rather, models that incorporate life and death competition between subjects, i.e., models utilized by scientists to examine the behavior of wildlife populations, may provide a more accurate analysis. This paper suggests the use of biological models to attain a more robust method for understanding the behavior of terrorist organizations as compared to traditional methods. This paper also describes how a biological population model incorporating predator-prey behavior factors can predict terrorist organizational recruitment behavior for the purpose of understanding the factors that govern the growth and decline of terrorist organizations. The Lotka-Volterra, a biolgical model that is based on a predator-prey relationship, is applied to a highly suggestive case study, that of the Irish Republican Army. This case study illuminates how a biological model can be utilized to understand the actions of a terrorist organization

A Reference Model of Soldier Attention and Behavior

Proceedings of Behavior Representation in Modeling and Simulation (BRIMS) 2008.pdfThis research expands entity level representation of situation awareness and behavior. Building on previous work, the researchers developed an integrated and tractable modeling framework for the representation of a soldier's visual attention, situational awareness, and target acqusition ptior to a close range encounter, as well as the soldier's initial action choice. The researchers developed data to populate the model through subject matter expert questionnaires and a live virtual experiment. The resulting algorithms provide insight into soldier action of choice on contact. These and other aspects of the model have been coded for demonstration as a proof of principle, while work on the full reference model continues

Threat Density Map Modeling for Combat Simulations

The modeling and simulation community has used probability threat maps and other similar approaches to address search problems and improve decision-making. Probability threat maps describe the probability of a location containing one or more enemy entities at a particular time. Although useful, they only describe the likelihood that the location is occupied without addressing the degree to which it is occupied. Thus, we investigate whether threat density maps that describe the searcher’s expectation of seeing a number of target agents at a certain location in a given time interval are a viable method for improving synthetic behaviors in combat simulations. As a proof of principle, this paper introduces a probability model which quantifies the searcher agent’s subjective belief about the number of enemy entities in a location, given the initial information described by a prior density function and the information provided by the assumed sensing model. In addition, this paper discusses a framework for initializing the model, as well as the model’s key advantages and current limitations