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.

Robust Spectrum Sensing With Crowd Sensors

Abstract: This paper investigates the issue of cooperative spectrum sensing with a crowd of low-end personal spectrum sensors (such as smartphones, tablets, and in-vehicle sensors), where the sensing data from crowd sensors that may be unreliable, untrustworthy, or even malicious. Moreover, due to either unexpected equipment failures or malicious behaviors, every crowd sensor could sporadically and randomly contribute with abnormal data, which makes the existing cooperative sensing schemes ineffective. To tackle these challenges, we first propose a generalized modeling approach for sensing data with an arbitrary abnormal component. Under this model, we then analyze the impact of general abnormal data on the performance of the cooperative sensing, by deriving closed-form expressions of the probabilities of global false alarm and global detection. To improve sensing data quality and enhance cooperative sensing performance, we further formulate an optimization problem as stable principal component pursuit, and develop a data cleansing-based robust spectrum sensing algorithm to solve it, where the under-utilization of licensed spectrum bands and the sparsity of nonzero abnormal data are jointly exploited to robustly cleanse out the potential nonzero abnormal data component from the original corrupted sensing data. Extensive simulation results demonstrate that the proposed robust sensing scheme performs well under various abnormal data parameter configurations.

Adaptive CUSUM procedures with EWMA-based shift estimators

Abstract: Adaptive Cumulative SUM charts (ACUSUM) have been recently proposed for providing an overall good detection over a range of mean shift sizes. The basic idea of the ACUSUM chart is to first adaptively update the reference value based on an Exponentially Weighted Moving Average (EWMA) estimate and then to assign a weight on it using a certain type of weighting function. A linear weighting function is proposed that is motivated by likelihood ratio testing concepts and that achieves superior detection performance. Moreover, in view of the lower efficiency in tracking relative large mean shifts of the EWMA estimate, a generalized EWMA estimate is proposed as an alternative. A comparison of run length performance of the proposed ACUSUM scheme and other control charts is shown to be favorable to the former.

Evaporation kinetics of sessile water droplets on micropillared superhydrophobic surfaces.

Abstract: Evaporation modes and kinetics of sessile droplets of water on micropillared superhydrophobic surfaces are experimentally investigated. The results show that a constant contact radius (CCR) mode and a constant contact angle (CCA) mode are two dominating evaporation modes during droplet evaporation on the superhydrophobic surfaces. With the decrease in the solid fraction of the superhydrophobic surfaces, the duration of a CCR mode is reduced and that of a CCA mode is increased. Compared to Rowan's kinetic model, which is based on the vapor diffusion across the droplet boundary, the change in a contact angle in a CCR (pinned) mode shows a remarkable deviation, decreasing at a slower rate on the superhydrophobic surfaces with less-solid fractions. In a CCA (receding) mode, the change in a contact radius agrees well with the theoretical expectation, and the receding speed is slower on the superhydrophobic surfaces with lower solid fractions. The discrepancy between experimental results and Rowan's model is attributed to the initial large contact angle of a droplet on superhydrophobic surfaces. The droplet geometry with a large contact angle results in a narrow wedge region of air along the contact boundary, where the liquid-vapor diffusion is significantly restricted. Such an effect becomes minor as the evaporation proceeds with the decrease in a contact angle. In both the CCR and CCA modes, the evaporative mass transfer shows the linear relationship between mass(2/3) and evaporation time. However, the evaporation rate is slower on the superhydrophobic surfaces, which is more significant on the surfaces with lower solid fractions. As a result, the superhydrophobic surfaces slow down the drying process of a sessile droplet on them.