This paper presents a NMOS-based ESD protection circuit with a low trigger voltage using the 65-nm CMOS process. The proposed ESD protection circuit is achieved by using a gate-substrate triggered technique. We measured the I-V characteristics, temperature characteristics and leakage current under normal operating conditions. The results of the ESD protection circuit were validated using a transmission line pulse (TLP) system. Also, the temperature range from 300K to 500K facilitates the understanding of physical mechanisms for the ESD protection circuit's reliability. From the results, this structure not only exhibited a lower trigger voltage but also has a lower leakage current.

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A filter-based algorithm for estimating the ionosphere error of the GNSS signals in the differential system is proposed in the paper. Based on the slow-varying characteristic of the ionosphere delay, the historical ionosphere delay data is involved in the algorithm. The measurement model is constructed according to the Grid Interpolation Model (GIM).The relevant analysis is conducted by the simulation and the corresponding results indicated that comparing with the traditional method, at least 60% promotion on the accuracy has been accomplished so that the algorithm in this paper can provide a more accurate estimation of the ionosphere error for GNSS signals.

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This paper proposes a new heterogeneous multi-cast with network coding in lossy networks. Subgraphs are constructed to determine transmission routes of layered data. Network coding is utilized so that all destinations achieve the data rates which are equal to their max-flows. Layered data are then allocated to predetermined routes. The allocation algorithm considers decodable probabilities of layered data at all destinations resulted by linear network coding and lossy network. More important layered data is allocated to the route that has a better decodable probability. Evaluation results show that the proposed heterogeneous multi-cast algorithm outperforms other heterogeneous multi-cast algorithms without network coding or without considering the reliabilities of routing paths.

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We propose a combining scheme for hard decisions of secondary users to improve the performance of cooperative spectrum sensing in a cognitive radio system. In contrast to the conventional equal-weight combining, the proposed scheme assigns unequal weights to different users to form the global decision statistics. Specifically, the combining weights are updated adaptively such that a higher weight is given to the decision of a more reliable user. In order to update the weights, the fusion center estimates the reliability of each user based on the past recode of the user's local decisions. Numerical results show that the proposed scheme outperforms the equal-weight scheme and optimal scheme with counting method, especially when the channels from the primary transmitter to the secondary users are highly disparate.

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Orthogonal matching pursuit (OMP) algorithm with random measurement matrix (RMM), often selects an incorrect variable due to the induced coherent interference between the columns of RMM. In this paper, we propose a sensing measurement matrix (SMM)-OMP which mitigates the coherent interference and thus improves the successful recovery probability of signal. It is shown that the SMM-OMP selects all the significant variables of the sparse signal before selecting the incorrect ones. We present a mutual incoherent property (MIP) based theoretical analysis to verify that the proposed method has a better performance than RMM-OMP. Various simulation results confirm our proposed method efficiency.

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In this paper an electrostatically driven MEMS resonator with resonance and hysteresis characteristics is reported. The resonator begins to exhibit spring-hardening effect at ac excitation voltage of 105mV and dc bias voltage of 5V in vacuum at 50Pa. An extended hysteresis at low pressure and high excitation voltage during upsweep and downsweep of excitation frequency was observed. This characteristic facilitates the usage of this type of resonator in a range of applications such as a cascaded filter array or as a high bandwidth resonator.

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In this paper the small-signal equivalent circuit model of SiGe:C heterojunction bipolar transistors (HBTs) has directly been extracted from S-parameter data. Circuit simulations by the use of neural network architecture and a standard IHP 0.13um BiCMOS technology confirmed our design goals. To check the capability of the direct approach, scattering parameters were generated and compared with Artificial Neural Network (ANN). Then measured and model-calculated data have represented an excellent agreement with less than 0.166% discrepancy in the frequency range of > 300GHz over a wide range of bias points.

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Traditional methods for event causal relation extraction covered only part of the explicit causal relation in text. This paper presents a method for event causal relation extraction by using dual-layer Conditional Random Fields (CRFs). The method casts the problem of event causal relation extraction as event sequence labeling and employs dual-layer CRFs model to label the causal relation of event sequence. The first layer of the CRFs model is used to label the semantic role of causal relation of the events, and then the output of the first layer is passed to the second layer for labeling the boundaries of the event causal relation. Experimental results show that our method not only covers each class of explicit event causal relation in the text, but also achieves good performance and the F-Measure of the overall performance arrives at 85.3%.

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