Stevens Institute of Technology

About: Stevens Institute of Technology is a education organization based out in Hoboken, New Jersey, United States. It is known for research contribution in the topics: Computer science & Cognitive radio. The organization has 5440 authors who have published 12684 publications receiving 296875 citations. The organization is also known as: Stevens & Stevens Tech.

Generalized deviations in risk analysis

Abstract: General deviation measures are introduced and studied systematically for their potential applications to risk management in areas like portfolio optimization and engineering. Such measures include standard deviation as a special case but need not be symmetric with respect to ups and downs. Their properties are explored with a mind to generating a large assortment of examples and assessing which may exhibit superior behavior. Connections are shown with coherent risk measures in the sense of Artzner, Delbaen, Eber and Heath, when those are applied to the difference between a random variable and its expectation, instead of to the random variable itself. However, the correspondence is only one-to-one when both classes are restricted by properties called lower range dominance, on the one hand, and strict expectation boundedness on the other. Dual characterizations in terms of sets called risk envelopes are fully provided.

Adsorption Mechanism of Arsenic on Nanocrystalline Titanium Dioxide

Abstract: Arsenate [As(V)] and arsenite [As(III)] interactions at the solid-water interface of nanocrystalline TiO2 were investigated using electrophoretic mobility (EM) measurements, Fourier transform infrared (FTIR) spectroscopy, extended X-ray absorption fine structure (EXAFS) spectroscopy, and surface complexation modeling. The adsorption of As(V) and As(III) decreased the point of zero charge of TiO2 from 5.8 to 5.2, suggesting the formation of negatively charged inner-sphere surface complexes for both arsenic species. The EXAFS analyses indicate that both As(V) and As(III) form bidentate binuclear surface complexes as evidenced by an average Ti-As(V) bond distance of 3.30 A and Ti-As(III) bond distance of 3.35 A. The FTIR bands caused by vibrations of the adsorbed arsenic species remained at the same energy levels at different pH values. Consequently, the surface complexes on TiO2 maintained the same nonprotonated speciation at pH values from 5 to 10, and the dominant surface species were (TiO)2AsO2- and (TiO)2AsO- for As(V) and As(III), respectively. The surface configurations constrained with the spectroscopic results were formulated in the diffuse layer model to describe the adsorption behavior of As in the pH range between 4 and 12. The study suggests that TiO2 is an effective adsorbent for As removal due to its high surface area and the presence of high affinity surface hydroxyl groups.

A core calculus of dependency

Abstract: Notions of program dependency arise in many settings: security, partial evaluation, program slicing, and call-tracking. We argue that there is a central notion of dependency common to these settings that can be captured within a single calculus, the Dependency Core Calculus (DCC), a small extension of Moggi's computational lambda calculus. To establish this thesis, we translate typed calculi for secure information flow, binding-time analysis, slicing, and call-tracking into DCC. The translations help clarify aspects of the source calculi. We also define a semantic model for DCC and use it to give simple proofs of noninterference results for each case.

Morphological Development in Solvent-Cast Polystyrene−Polybutadiene−Polystyrene (SBS) Triblock Copolymer Thin Films

Abstract: This paper describes morphological development in solvent-cast polystyrene (PS)−polybutadiene (PB)−polystyrene (SBS) triblock copolymer thin films (30 wt % PS) as a function of solvent evaporation ...