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.

Scaling from trees to forests: tractable macroscopic equations for forest dynamics

Abstract: Individual-based forest simulators, such as TASS and SORTIE, are spatial stochastic processes that predict properties of populations and communities by simulating the fate of every plant throughout its life cycle. Although they are used for forest management and are able to predict dynamics of real forests, they are also analytically intractable, which limits their usefulness to basic scientists. We have developed a new spatial individual-based forest model that includes a perfect plasticity formulation for crown shape. Its structure allows us to derive an accurate approximation for the individual-based model that predicts mean densities and size structures using the same parameter values and functional forms, and also it is analytically tractable. The approximation is represented by a system of von Foerster partial differential equations coupled with an integral equation that we call the perfect plasticity approximation (PPA). We have derived a series of analytical results including equilibrium abundances for trees of different crown shapes, stability conditions, transient behaviors, such as the constant yield law and self-thinning exponents, and two species coexistence conditions.

Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians.

Abstract: Artificial intelligence (AI) can transform health care practices with its increasing ability to translate the uncertainty and complexity in data into actionable-though imperfect-clinical decisions or suggestions In the evolving relationship between humans and AI, trust is the one mechanism that shapes clinicians' use and adoption of AI Trust is a psychological mechanism to deal with the uncertainty between what is known and unknown Several research studies have highlighted the need for improving AI-based systems and enhancing their capabilities to help clinicians However, assessing the magnitude and impact of human trust on AI technology demands substantial attention Will a clinician trust an AI-based system? What are the factors that influence human trust in AI? Can trust in AI be optimized to improve decision-making processes? In this paper, we focus on clinicians as the primary users of AI systems in health care and present factors shaping trust between clinicians and AI We highlight critical challenges related to trust that should be considered during the development of any AI system for clinical use

Conversion of biomass to fuel: Transesterification of vegetable oil to biodiesel using KF loaded nano-γ-Al2O3 as catalyst

Abstract: KF-impregnated nanoparticles of γ-Al2O3 were calcinated and used as heterogeneous catalysts for the transesterification of vegetable oil with methanol for the synthesis of biodiesel (fatty acid methyl esters, FAME). The ratio of KF to nano-γ-Al2O3, calcination temperature, molar ratio of methanol/oil, transesterification reaction temperature and time, and the concentration of the catalyst were used as the parameters of the study. A methyl ester yield of 97.7 ± 2.14% was obtained under the catalyst preparation and transesterification conditions of KF loading of 15 wt%, calcination temperature of 773 K, 8 h of reaction time at 338 K, and using 3 wt% catalysts and molar ratio of methanol/oil of 15:1. This relatively high conversion of vegetable oil to biodiesel is considered to be associated with the achieved relatively high basicity of the catalyst surface (1.68 mmol/g) and the high surface to volume ratio of the nanoparticles of γ-Al2O3.

Project Management Research—The Challenge and Opportunity:

Abstract: Project management is one of the fastest growing disciplines in organizations today. However, ironically, the statistics of project success suggests that most projects still fail and many projects ...

Spectrum management in coordinated dynamic spectrum access based cellular networks

Abstract: This paper focuses on spectrum management in next generation cellular networks that employ coordinated dynamic spectrum access (DSA). In our model, a spectrum broker controls and provides time-bounded access to a band of spectrum to wireless service providers and/or end users and implements the spectrum pricing and allocation schemes and policies. We introduce several concepts that are central to the design of spectrum management algorithms. These include: (1) demand processing model (batched vs. online), (2) spectrum pricing models (merchant mode, simple bidding, and iterative bidding), (3) different network infrastructure options such as shared base stations with collocated antennas, non-shared base stations with collocated antennas, and non-shared base stations and non-collocated antennas, and (4) important spectrum management concepts of scope, access fairness, "stickiness" and spectrum utilization. Based on these concepts, we investigate practically realizable candidate algorithms for spectrum allocation for homogeneous CDMA networks