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Modeling of resonant detection of terahertz (THz) radiation of Metal-Oxide-Semiconductor (MOS) field effect transistors (FETs) under the optical beating mode is studied in this paper. An analytical model is first proposed which covers all operation regions of FETs from sub-threshold to the strong inversion, and then is verified by the numerical tool which has been improved to simulate THz detection...
Wireless Sensor Network (WSN) technology is employed in monitoring system to prevent the spontaneous combustion of coal gangue. A temperature monitoring system was designed, which monitor environment of gangue and prevent the occurrence of spontaneous combustion networking strategy through the collection of temperature in real-time or fix time. According to the energy-constrained problem of WSN, pseudo-parallel...
We propose a novel technique based on Fourier analysis and perturbation theory to describe completely the step discontinuity in a slab waveguide of any index contrast without the need for analytical approximations or assumptions. Through this technique, we derive a spectral overlapping criterion and a coupling matrix that analyzes effectively the roles of the radiation modes in the resultant computation...
We have designed and fabricated a low cost THz band pass filter based on a plastic substrate. The filter shows excellent performance for THz applications. We have also investigated its possible application to biological sensing.
We have developed anisotropically etched artificial dielectric quarter wave plates (QWPs) for use at 1.5 and 2.5 Terahertz. A SU8 anti-reflection coating is used to further improve the transmission coefficient by up to 12%.
The evaluation pattern that risk degree is a product of danger degree and vulnerability were introduced based on natural disasters risk expression recommended by the Humanitarian Affairs Department of United Nations. The transformed values function were put out to transfer overtopping probability into danger degree, which were measured on a scale of 0 to 1. "Property index" and "population...
One protocol of P2P-based single sign-on presented in this paper is verified by protocol executive analysis. This protocol use validity period of user credential as lifecycle of user and implement multiple sign-on after one authentication. This protocol can bilaterally authenticate between identity server and application, initialize the session key between communication peers, and set up the secure...
The atmospheric correction for the ocean color remote sensing is the most important technique to retrieve the water- leaving radiance, which is less than about 10% of the satellite radiance. In Case II waters, the standard atmospheric correction method embedded in SeaDAS frequently yields negative water- leaving radiance, and its major uncertainties are occurred by the estimation error of atmospheric...
The paper presents a hierarchical organization of two storage redundancy schemes to improve data availability caused by churn in structured overlay networks. To mask or hide the high churn from the portion of short-lived but frequent churn peers and permanent failure peers, we use replication among the nodes in a certain interval that can be considered as a virtual node. Then a set of virtual nodes...
The creep behavior of Zeolite molecular sieves has been investigated in this research by using a nanoindentation test. In the holding time, creep curves were obtained. The results show that the penetration depth during constant load phase is time-dependent. After analysis, creep stress exponents of Zeolite molecular sieves were determined from In epsivdot vs .InH curves. Given a secondary creep material...
Understanding the dynamics of the power output of a wind farm is important to the integration of large scale wind energy into the power system. In a large complex dynamic engineering system, such as a wind farm, clustering is an effective way to reduce the model complexity and improve the understanding of its local dynamics. The paper proposes a novel methodology to cluster wind turbines of a wind...
Linear discrimination analysis (LDA) is one of the most popular feature extraction and classifier design techniques. It maximizes the Fisher-ratio between between-class scatter matrix and within-class scatter matrix under a linear transformation, and the transformation is composed of the generalized eigenvectors of them. However, Fisher criterion itself can not decide the optimum norm of transformation...
In many uncertain complex systems it is observed that the system trajectories cluster in several subsets of the state space. In this paper we model the system behavior as a Markov process and consider the problem of finding a low dimensional approximation of the process that captures the clustering phenomena. Furthermore, we concentrate on Markov chain approximations on a finite state space of large...
In swimming competition, a rational disposition of physical strength is seen as a major factor in deciding the final outcome. Among various items in swimming competition, the issue of physical distribution over the 400 m race has aroused the most extensive controversy. In this paper, concerning the achievements of elite athletes home and abroad in 400 m freestyle swimming race, the principle of variation...
Communication data management (CDM) is an important issue in complex and large-scale modern geo-computation applications. In this paper, we review existing CDM schemes and propose an efficient adaptive quantization-based CDM scheme for geo-computation in grid environment. This model is based on theory of quantization and uses distributed clusters which are concerned about the features and geographical...
Computational grid technology has been noticed as an issue to solve large-scale bioinformatics-related problems and improves data accuracy and processing speed on multiple computation platforms with distributed bioDATA sets. This paper proposes a grid-based intelligence ART1 classifier which operates an ART1 clustering classification using grid computational resources with distributed GPCR data sets...
This paper presents a high performance head pose estimation system based on the newly-proposed sparse Bayesian regression technique (relevance vector machine, RVM) and sparse representation of facial patterns. In our system, after localizing 20 key facial points, sparse features of these points are extracted to represent facial property, and then RVM is utilized to learn the relation between the sparse...
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