Chaos-based color image block encryption scheme using S-box

A chaos-based color image encryption scheme using bijection is designed. The whole image is diffused by exclusive or (XOR) operation for random rounds, each color component is separated into blocks with the same size. A bijective function f: B → S between block set B and S-box set S, is built. The corresponding 8 × 8 S-box is dynamically generated by the Chen system with variable conditions. The ciphered image can be obtained after substituting each block with the paired S-box. Numerical simulation and security analysis demonstrate that the scheme is practical in image encryption.     

The nonparametric Bayesian dictionary learning based interpolation method for WSNs missing data

The conventional data interpolation methods based on sparse representation usually assume that the signal is sparse under the overcomplete dictionary. Specially, they must confirm the dimensions of dictionary and the signal sparse level in advance. However, it is hard to know them if the signal is complicated or dynamically changing. In this paper, we proposed a nonparametric Bayesian dictionary learning based interpolation method for WSNs missing data, which is the combination of sparse representation and data interpolation. This method need not preset sparse degrees and dictionary dimensions, and our dictionary atoms are drawn from a multivariate normal distribution. In this case, the dictionary size will be learned adaptively by the nonparametric Bayesian method. In addition, we implement the Dirichlet process to exploit the spatial similarity of the sensing data in WSNs, thus to improve the interpolation accuracy. The interpolation model parameters, the optimal dictionary and sparse coefficients, can be inferred by the means of Gibbs sampling. The missing data will be estimated commendably through the derived parameters. The experimental results show that the data interpolation method we proposed outperforms the conventional methods in terms of interpolation accuracy and robustness.     

Analysis of nanometer-scale InGaAs/InAs/InGaAs composite channel MOSFETs using high-K dielectrics for high speed applications

The outstanding electron transport properties of InGaAs and InAs semiconductor materials, makes them attractive candidates for future nano-scale CMOS. In this paper, the ON state and OFF state performance of 30 nm gate length InGaAs/InAs/InGaAs buried composite channel MOSFETs using various high-K dielectric materials is analyzed using Synopsys TCAD tool. The device features a composite channel to enhance the mobility, an InP spacer layer to minimize the defect density and a heavily doped multilayer cap. The simulation results show that MOSFETs with Al₂O₃/ZrO₂ bilayer gate oxide exhibits higher gm/I_D ratio and lower sub threshold swing than with the other dielectric materials. The measured values of threshold voltage (V_T), on resistance (R_ON) and DIBL for Lg = 30 nm In_0.53Ga_0.47As/InAs/In_0.53Ga_0.47As composite channel MOSFET having Al₂O₃/ZrO₂ (EOT = 1.2 nm) bilayer dielectric as gate oxide are 0.17 V, 290 Ω-µm, and 65 mV/V respectively. The device displays a transconductance of 2 mS/µm.     

Preparation and properties of silica filled PTFE flexible laminates for microwave circuit applications

Micron and nano size silica fillers are incorporated in the PTFE matrix to prepare flexible composite substrates. A proprietary process comprising of sigma mixing, extrusion, calendering followed by hot pressing (SMECH process) has been employed to obtain nearly isotropic and dimensionally stable filled PTFE substrates. Theoretical modeling has been employed to predict the effective dielectric constant of the composite system and validated the results with experimental data. The distribution of particulate filler in the PTFE matrix has been studied using scanning electron microscopy. The linear coefficient of thermal expansion and ultimate tensile strength of the composite systems with respect to filler loading have been found out. Dielectric properties of the composite substrates at X-band frequency (8.2–12.4 GHz) are measured using waveguide cavity perturbation technique. Moisture absorption of fused silica filled substrates is found out conforming to IPC-TM-650 2.6.2.     

The prevalent motor bearing premature failures due to the high frequency electric current passage

Bearing premature failures are prevalent in VFD (Variable Frequency Drives) motors. The three common symptoms of the modern bearing current appeared on the bearings of a group of pump motors. The bearing failure mechanisms have been studied from the tribological point of view. The natures of the three common symptoms have been uncovered. A hypothesis of the skin effect has been proposed to explain the three common symptoms. The discovery of the serial microcraters reveals the discharge with Fourier series features. The nature of the fluting patterns excluded the theories of both EDM (Electrical Discharge Machining) and discharge corrugation. VA (Vibration Analysis) detected the harmonics of the BPOR (Ball Pass Outer Ring) frequency which associated with the fluting on the outer raceway. This discovery may be applied to detect fluting in condition monitoring.     

差分振子时间历程在微弱调制信号检测中的应用

单一的差分振子仅可实现对周期信号中某一频率成分进行检测,对于强噪声背景下的边频带,尽管可以利用多个差分振子组成差分阵列进行逐个检测,进而确定边频带的间隔,但这种做法无疑会带来巨大的计算量。在对调制信号进行Hilbert变换包络分析时,所得到的时域信号是原始调制信号中的低频分量,亦是调制波信号,若该低频分量仍然包含较强的噪声成分,传统的频谱分析将会失效。此时,我们可借助差分振子时间历程对含较强的噪声的包络进行检测。因此,提出基于差分振子时间历程的微弱调制信号检测方法,即首先对信号进行Hilbert包络解调,然后利用差分振子时间历程对含较强的噪声的幅值包络进行检测,并成功应用于风机早期故障检测中。     

Detecting image seam carving with low scaling ratio using multi-scale spatial and spectral entropies

Seam carving is the most popular content-aware image retargeting technique. However, it may also be used to correct poor photo composition in photography competition or to remove object from image for malicious purpose. A blind detection approach is presented for seam carved image with low scaling ratio (LSR). It exploits spatial and spectral entropies (SSE) on multi-scale images (candidate image and its down-sampled versions). We observe that when a few seams are deleted from an original image, its SSE distribution is greatly changed. Forty-two features are designed to unveil the statistical properties of SSE in terms of centralized tendency, dispersion tendency and distribution tendency. They are combined with the local binary pattern (LBP)-based energy features to form ninety-six features. Finally, support vector machine (SVM) is exploited as classifier to determine whether an image is original or suffered from seam carving. Experimental results show that the proposed approach achieves superior detection accuracy over the state-of-the-art works, especially for resized image by seam carving with LSRs. Moreover, it is robust against JPEG compression and seam insertion.     

Improved online fountain codes based on shaping for left degree distribution

In this paper, an improved encoding scheme for online fountain codes is proposed with the joint optimization of variable node degree and check node degree is proposed. The coding scheme can be divided into the build-up phase and the completion phase. In the build-up phase, left degree distribution is exploited to guarantee optimal performance phase by modifying the traditional coding scheme of choosing input symbols uniformly at random. A memory-based selecting of the source symbols is employed to decrease the number of connected components, which can thus produce the dimension increasement of the linear subspace of a decoding graph constructed in the build-up phase. The upper bound on coding overhead is also derived from the analysis of random graph theory. Compared with conventional online fountain codes, it can be seen from the simulation results that the proposed scheme can provide significant performance improvement with respect to both coding overhead and feedback cost. Moreover, the lower encoding/decoding complexities may make the proposed scheme more practical in energy-constrained applications such as distributed storage.     

Progressive iterative channel estimation in fast time-varying OFDM systems

Considering the joint channel estimation and data detection in time-varying orthogonal frequency division multiplexing （OFDM） and addressing transmission performance degradation induced by the severe inter-carrier interference （ICI） at very high speed, a new progressive iterative channel estimation scheme is proposed. To alleviate the error propagation of the inaccurate data due to ICI, the measurement subcarriers in the Kalman filter is designed to be extended from pilots subcarriers to all the subcarriers progressively through the iterations. Furthermore, in iteration process, the interference of the non-pilot data to the measurement subcarriers is considered to be part of noise in the modified Kalman filter, which improves the estimation accuracy. Simulation indicates that the proposed scheme improves the performance in fast time-varying situation.