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.

Balancing auditability and privacy in vehicular networks

Abstract: We investigate how to obtain a balance between privacy and audit requirements in vehicular networks. Challenging the current trend of relying on asymmetric primitives within VANETs, our investigation is a feasibility study of the use of symmetric primitives, resulting in some efficiency improvements of potential value. More specifically, we develop a realistic trust model, and an architecture that supports our solution. In order to ascertain that most users will not find it meaningful to disconnect or disable transponders, we design our solution with several types of user incentives as part of the structure. Examples of resulting features include anonymous toll collection; improved emergency response; and personalized and route-dependent traffic information.

Market Reaction to Verbal Components of Earnings Press Releases: Event Study Using a Predictive Algorithm

Abstract: Similar to a classic event study, this study examines market reaction to firms' earnings announcements. This study extends the examination to include a broad range of concurrent disclosure contained in earnings press releases: financial disclosure captured as accounting ratios; and verbal components of disclosure, both content and style, which are captured using elementary computer-based content analysis. Extending the analysis to such a broad range of concurrent disclosures requires a methodology designed to utilize a large number of predictor variables, and predictive data mining algorithms are specifically designed to do so. Therefore, this study employs a widely used data-mining algorithm - classification and regression trees (CART). Results of the study show that inclusion of predictor variables capturing verbal content and writing style of earnings-press releases results in more accurate predictions of market response.

Stochastic learning solution for distributed discrete power control game in wireless data networks

Abstract: Distributed power control is an important issue in wireless networks. Recently, noncooperative game theory has been applied to investigate interesting solutions to this problem. The majority of these studies assumes that the transmitter power level can take values in a continuous domain. However, recent trends such as the GSM standard and Qualcomm's proposal to the IS-95 standard use a finite number of discretized power levels. This motivates the need to investigate solutions for distributed discrete power control which is the primary objective of this paper. We first note that, by simply discretizing, the previously proposed continuous power adaptation techniques will not suffice. This is because a simple discretization does not guarantee convergence and uniqueness. We propose two probabilistic power adaptation algorithms and analyze their theoretical properties along with the numerical behavior. The distributed discrete power control problem is formulated as an N-person, nonzero sum game. In this game, each user evaluates a power strategy by computing a utility value. This evaluation is performed using a stochastic iterative procedures. We approximate the discrete power control iterations by an equivalent ordinary differential equation to prove that the proposed stochastic learning power control algorithm converges to a stable Nash equilibrium. Conditions when more than one stable Nash equilibrium or even only mixed equilibrium may exist are also studied. Experimental results are presented for several cases and compared with the continuous power level adaptation solutions.

Systems and methods for automatically detecting deception in human communications expressed in digital form

Abstract: An apparatus and method for determining whether a text is deceptive has a computer programmed with software that automatically analyzes a text message in digital form for deceptiveness by at least one of statistical analysis of text content to ascertain and evaluate psycho-linguistic cues that are present in the text message, IP geo-location of the source of the message, gender analysis of the author of the message, authorship similarity analysis, and analysis to detect coded/camouflaged messages. The computer has access to truth data against which the veracity of the text message can be compared and a graphical user interface through which a user of the system can control the system and receive results concerning the deceptiveness of the text message analyzed by the system. The computer may be connectable to the Internet and may obtain the text to be analyzed either under the control of the user or automatically.

In situ SERS study of Rhodamine 6G adsorbed on individually immobilized Ag nanoparticles

Abstract: We report a study on polymer-mediated immobilization of non-aggregated Ag nanoparticles on planar glass substrates and the resultant surface-enhanced Raman scattering (SERS) activity using Rhodamine 6G (R6G) as a model molecule. Ag colloidal solution with an average particle diameter of 70 nm was prepared by citrate reduction of AgNO3 using the Lee-Meisel method, and subsequent fractionation by filtration. A self-assembled polyallylamine hydrochloride (PAH) monolayer was employed as the intermediate polymer layer. We have shown that the coverage density of Ag nanoparticles on the glass substrates correlates with the amount of adsorbed PAH. This parameter can be easily controlled by varying the pH and ionic strength during polymer deposition. The highest coverage density was obtained for the polymer deposition from buffer solutions at pH 9.0, which additionally contained 0.25 M NaCl. The SERS-active substrates were robust and stable in 0.5 M NaCl solutions, as well as under extreme acidic and basic conditions. The glass substrates with immobilized non-aggregated Ag nanoparticles exhibited SERS enhancement and provided in situ detection sensitivity of R6G at 5 ppt level, with estimated surface coverage of two to four R6G molecules per silver particle. We found that adsorption of R6G in the presence of N-(2-hydroxyethyl)piperazine-N′-(2-ethanesulfonic acid) (HEPES) buffer resulted in complete inhibition of photodecomposition of adsorbed R6G molecules. Studies of the effect of sodium chloride on the SERS activity of the glass substrates with individually attached nanoparticles showed that chloride anions resulted in a two to threefold increase in SERS intensity. Our approach has enabled the isolation of chloride-activated SERS enhancement from contributions arising from nanoparticle aggregation. The observed SERS enhancement in salt solutions results from coadsorption of chloride ions by the silver surface, and manifests itself in changing of orientation of adsorbed R6G molecules. The observed enhancement was reversed by exposing the substrate to 514-nm laser radiation, which resulted in the cleavage of AgCl bonds. Copyright © 2006 John Wiley & Sons, Ltd.