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: Cognitive radio & Wireless network. The organization has 5440 authors who have published 12684 publications receiving 296875 citations. The organization is also known as: Stevens & Stevens Tech.

Localizing jammers in wireless networks

Abstract: Wireless communication is susceptible to radio interference and jamming attacks, which prevent the reception of communications. Most existing anti-jamming work does not consider the location information of radio interferers and jammers. However, this information can provide important insights for networks to manage its resource and to defend against radio interference. In this paper, we explore methods to localize radio interferers in wireless networks. We first exploit the feasibility of using two existing range-free localization algorithms, Centroid Localization (CL) and Weighted Centroid Localization (WCL), to localize the position of the jammer. We then develop a novel algorithm, Virtual Force Iterative Localization (VFIL), which estimates the location of a jammer iteratively by utilizing the network topology. Our extensive simulation results have demonstrated that VFIL is less sensitive to node densities and can achieve higher accuracy when localizing the jammer's position compared with centroid-based approaches.

Renewable municipal solid waste pathways for energy generation and sustainable development in the Nigerian context

Abstract: The continued concerns over energy prices, increase in population, and climate change issues have led towards a need for alternative and new energy sources. Municipal solid waste (MSW) is generally accepted as a renewable energy resource. This research study presents a techno-economic assessment potential to utilize the energy obtainable from MSW for the generation of electrical power. The assessment was carried out for energy generation by thermochemical (incineration or combustion) and biochemical (landfilling and anaerobic digestion) processes and based on the available data from seven selected municipalities. Due to the broad scope of this topic, life cycle impact of waste management, social acceptance, policy aspects, and emission reduction or fossil fuel offset are not considered and are not part of the assessment. Results presented in tabular form indicate, for example, that the price of steam generated by a fluidized steam generator is in the range of US$0.018/kWht (Lagos) to US$0.044/kWh (Nsukka) and compares favorably with the typical cost of steam at US$0.015/kWh. Electrical power generation using a combined heat and power plant provides electricity at a cost that is in the range of US$0.017/kWhe (Lagos) to US$0.040/kWhe (Nsukka) and also compares well with the typical cost of electricity in Nigeria at US$0.14/kWhe (as of 2012).

Electrical properties of composites as affected by the degree of mixedness of the conductive filler in the polymer matrix

Abstract: The development of the electrical properties of composites as a function of the degree of mixedness of a conductive filler distributed into an insulating polymer is investigated. A wide-angle X-ray diffraction (WAXD)-based quantitative phase analysis method was used to characterize the variations of the concentrations of the insulating binder and the conductive particles around their mean values as a function of mixing time in an intensive batch mixer. Increasing the time and hence, the specific energy input, during the mixing process results in a more homogeneous spatial distribution of the conductive filler in the polymeric matrix, which in turn results in a decrease of the volume conductivity of the composite. The decreasing conductivity of the composite is attributed to the better coating and hence the isolation of the conductive particles from each other, thus hindering the formation of a conductive network “percolation”. Overall, these results suggest that the control of the electrical properties of conductive composites could benefit from a good understanding and adequate control of the dynamics of the mixing process and the resulting degree of mixedness of the conductive particles in the polymer matrix.

Automatic window factor analysis—A more efficient method for determining concentration profiles from evolutionary spectra†

Abstract: An algorithm called automatic window factor analysis (AUTOWFA) is developed for the purpose of determining, efficiently and automatically, the concentration profiles of the spectroscopically active components present in evolutionary processes, such as chemical titration, chromatography and kinetics. The method not only yields windows and profiles in agreement with those reported in the literature, but also reveals components not detected by precursor techniques. The method, however, has not been optimized and may require user interaction to fine-tune the windows.