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After a long in-service period, the electrical aging phenomenon of Nylon 6 may cause insulation degradation. Most of the researches focus on AC/DC or room temperature conditions. Less attention is paid to the nanosecond pulses conditions. In this paper, frequency effect on the electrical tree growth of nylon 6 was investigated. A solid-state pulse generator MPC50D was used to export nanosecond pulses...
The micro-loading effect in this work seems obviously. According to the extraction of drive current (IDS) for dense and isolated FinFET devices at the on-drawn layout (W/L=0.11/0.5 (μm/μm), the ratio with 11-fin fingers vs. single fin was 10.01. Using the re-work concept to derive the un-etching depth (ΔH) located at the inner sidewall fin height was still around 2.4 nm as the outer sidewall height...
In recent years, along with the rapid development of real estate industry, real estate tax has become an important source of local tax revenue. However, because the real estate industry tax categories are various and tax links are complicated, real estate tax integration management becomes the trend of the Times. Implementation of the real estate tax “integration” is necessary to improve the scientific,...
The 3-D structural fin-like channels of FinFET suppress the leakage current as the sizes of devices get substantially shrunk. In this study, the fin-thickness effects on the electrical performances are mainly observed. Two different kinds of thickness (namely, 110nm, and 120nm) with the same channel length (0.1 micron) are put into comparison. The phosphorus implants of the same dose with different...
FinFET devices have the structure of 3-D fins as channels, which are capable of being fully depleted as the gate is biased and potentially suppress the leakage currents. In this paper, one compares poly-silicon gates with fully cobalt silicide gate to see how much they are affected by the fin widths. Two channel lengths (0.1 micron and 0.12 micron) at two different fin widths (namely, 110nm, and 120nm)...
Support vector machine(SVM) is based on the minimum of structure risk and used for small samples in machine learning. Memory support vector machine(MSVM) feedback is based on SVM and used cumulation samples replacing feedback samples by memory. It reduces the risk of recall vibration. MSVM feedback also proposes memory label which is used for lightening user's burden. MSVM feedback is proved its superiority...
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