A semi-Lagrangian scheme for the game pp-Laplacian via pp-averaging

We present and analyze an approximation scheme for the two-dimensional game $p$-Laplacian in the framework of viscosity solutions. The approximation is based on a semi-Lagrangian scheme which exploits the idea of $p$-averages. We study the properties of the scheme and prove that it converges, in particular cases, to the viscosity solution of the game $p$-Laplacian. We also present a numerical implementation of the scheme for different values of $p$; the numerical tests show that the scheme is accurate.Comment: 34 pages, 3 figures. To appear on Applied Numerical Mathematic

Using Value-Focused Thinking to Evaluate the Use of Innovative Stormwater Management Technologies on Air Force Installations

Stormwater runoff occurs naturally after every storm event; however, traditional development practices have created many impervious surfaces, such as buildings, parking lots, and streets that increase runoff volume and flow rate. Conventional stormwater management practices focus on collecting runoff into centralized channels and conveying it as quickly as possible to local bodies of water. This type of conveyance system decreases the opportunity for stormwater to naturally infiltrate back into the ground. It also prevents contaminants from being naturally filtered out of stormwater flows. As a result, centralized conveyance systems can cause flooding, erosion, and terrestrial and aquatic habitat degradation. Innovative stormwater management strategies treat stormwater on-site by encouraging infiltration, decreasing flow rates, and reducing pollutant loads. Value-Focused Thinking (VFT) was used in this research to develop a decision analysis model to assist Air Force decision makers in evaluating and selecting innovative stormwater management strategies. VFT is a multi-objective decision analysis model that compares alternatives based on the values of the decision maker. Nine stormwater technologies were evaluated across thirteen evaluation measures. Through deterministic analysis and sensitivity analysis, a grassed swale was found to be the top alternative, followed very closely by the infiltration basin and wet detention options. VFT proved to be a useful methodology in producing an objective solution to this complex, multiobjective decision problem

An approximation scheme for an Eikonal Equation with discontinuous coefficient

We consider the stationary Hamilton-Jacobi equation where the dynamics can vanish at some points, the cost function is strictly positive and is allowed to be discontinuous. More precisely, we consider special class of discontinuities for which the notion of viscosity solution is well-suited. We propose a semi-Lagrangian scheme for the numerical approximation of the viscosity solution in the sense of Ishii and we study its properties. We also prove an a-priori error estimate for the scheme in an integral norm. The last section contains some applications to control and image processing problems

Verifying Policy Enforcers

Policy enforcers are sophisticated runtime components that can prevent failures by enforcing the correct behavior of the software. While a single enforcer can be easily designed focusing only on the behavior of the application that must be monitored, the effect of multiple enforcers that enforce different policies might be hard to predict. So far, mechanisms to resolve interferences between enforcers have been based on priority mechanisms and heuristics. Although these methods provide a mechanism to take decisions when multiple enforcers try to affect the execution at a same time, they do not guarantee the lack of interference on the global behavior of the system. In this paper we present a verification strategy that can be exploited to discover interferences between sets of enforcers and thus safely identify a-priori the enforcers that can co-exist at run-time. In our evaluation, we experimented our verification method with several policy enforcers for Android and discovered some incompatibilities.Comment: Oliviero Riganelli, Daniela Micucci, Leonardo Mariani, and Yli\`es Falcone. Verifying Policy Enforcers. Proceedings of 17th International Conference on Runtime Verification (RV), 2017. (to appear

Advanced thermoplastic resins, phase 1

Eight thermoplastic polyimide resin systems were evaluated as composite matrix materials. Two resins were selected for more extensive mechanical testing and both were versions of LaRC-TPI (Langley Research Center - Thermoplastic Polyimide). One resin was made with LaRC-TPI and contained 2 weight percent of a di(amic acid) dopant as a melt flow aid. The second system was a 1:1 slurry of semicrystalline LaRC-TPI powder in a polyimidesulfone resin diglyme solution. The LaRC-TPI powder melts during processing and increases the melt flow of the resin. Testing included dynamic mechanical analysis, tension and compression testing, and compression-after-impact testing. The test results demonstrated that the LaRC-TPI resins have very good properties compared to other thermoplastics, and that they are promising matrix materials for advanced composite structures

STEM-IS Flyer

Flyer for teachers or facilitators interested in the STEM Interest Sweepstakes Competition.https://digitalcommons.njit.edu/stemshowcase/1003/thumbnail.jp

Testing quark mass matrices with right-handed mixings

In the standard model, several forms of quark mass matrices which correspond to the choice of weak bases lead to the same left-handed mixings $V_L=V_{CKM}$, while the right-handed mixings $V_R$ are not observable quantities. Instead, in a left-right extension of the standard model, such forms are ansatze and give different right-handed mixings which are now observable quantities. We partially select the reliable forms of quark mass matrices by means of constraints on right-handed mixings in some left-right models, in particular on $V^R_{cb}$. Hermitian matrices are easily excluded.Comment: 12 pages RevTex, no figures. Minor corrections. Comment on SO(10) changed and one reference adde

Squeezing out predictions with leptogenesis from SO(10)

We consider the see-saw mechanism within a non-supersymmetric SO(10) model. By assuming the SO(10) quark-lepton symmetry, and after imposing suitable conditions that ensure that the right-handed (RH) neutrino masses are at most mildly hierarchical (compact RH spectrum) we obtain a surprisingly predictive scenario. The absolute neutrino mass scale, the Dirac and the two Majorana phases of the neutrino mixing matrix remain determined in terms of the set of already measured low energy observables, modulo a discrete ambiguity in the signs of two neutrino mixing angles and of the Dirac phase. The RH neutrinos mass spectrum is also predicted, as well as the size and sign of the leptogenesis CP asymmetries. We compute the cosmological baryon asymmetry generated through leptogenesis and obtain the correct sign and a size compatible with observations.Comment: 18 pages, 2 figures; minor changes, version accepted for publication in PR

Automating Vehicles by Deep Reinforcement Learning using Task Separation with Hill Climbing

Within the context of autonomous driving a model-based reinforcement learning algorithm is proposed for the design of neural network-parameterized controllers. Classical model-based control methods, which include sampling- and lattice-based algorithms and model predictive control, suffer from the trade-off between model complexity and computational burden required for the online solution of expensive optimization or search problems at every short sampling time. To circumvent this trade-off, a 2-step procedure is motivated: first learning of a controller during offline training based on an arbitrarily complicated mathematical system model, before online fast feedforward evaluation of the trained controller. The contribution of this paper is the proposition of a simple gradient-free and model-based algorithm for deep reinforcement learning using task separation with hill climbing (TSHC). In particular, (i) simultaneous training on separate deterministic tasks with the purpose of encoding many motion primitives in a neural network, and (ii) the employment of maximally sparse rewards in combination with virtual velocity constraints (VVCs) in setpoint proximity are advocated.Comment: 10 pages, 6 figures, 1 tabl

Strong X-ray Emission from High-Temperature Plasmas Produced by Intense Irradiation of Clusters

The interaction of an intense laser pulse with large (∼100Å) clusters present in pulsed gas jets is shown to produce novel plasmas with electron temperatures far in excess of that predicted by above-threshold ionization theory. The enhanced absorption of the laser light by the dense clusters results in the production of high ion charge states via collisional ionization resulting in strong x-ray emission from the hot plasma