This image sharing method is a secure way of protecting the security of the secret images. In 2011, Wang et al. proposed an image sharing method with verification. The idea of the method is to embed the secret and the watermark images into two shares by two equations to achieve the goal of the secret sharing. However, the constructed shares are meaningless images which are difficult to manage. Authors utilize the algorithm of the torus automorphism to increase the security of the shares. However, the algorithm of the torus automorphism must take much time to encrypt and decrypt an image. This paper proposes a friendly image sharing method to improve the above problem. Experimental results show the significant efficiency of the proposed method.

An asymmetric zero correlation zone (A-ZCZ) sequence set is a type of ZCZ sequence set and consists of multiple sequence subsets. It is the most important property that is the cross-correlation function between arbitrary sequences belonging to different sequence subsets has quite a large zero-cross-correlation zone (ZCCZ). Our proposed A-ZCZ sequence sets can be constructed based on interleaved technique and orthogonality-preserving transformation by any perfect sequence of length P=Nq(2k+1) and Hadamard matrices of order T≥2, where N≥1, q≥1 and k≥1. If q=1, the novel sequence set is optimal ZCZ sequence set, which has parameters (TP,TN,2k+1) for all positive integers P=N(2k+1). The proposed A-ZCZ sequence sets have much larger ZCCZ, which are expected to be useful for designing spreading sequences for QS-CDMA systems.

A code shift keying (CSK) using pseudo-noise (PN) codes for optical wireless communications with intensity/modulation and direct detection (IM/DD) is considered. Since CSK has several PN codes, the data transmission rate and the bit error rate (BER) performance can be improved by increasing the number of PN codes. However, the conventional optical PN codes are not suitable for optical CSK with IM/DD because the ratio of the number of PN codes and the code length of PN code, M/L is smaller than 1/√L. In this paper, an optical CSK with a new PN code, which combines the generalized modified prime sequence code (GMPSC) and Hadamard code is analyzed. The new PN code can achieve M/L=1. Moreover, the BER performance and the data transmission rate of the CSK system with the new PN code are evaluated through theoretical analysis by taking the scintillation, background-noise, avalanche photodiode (APD) noise, thermal noise, and signal dependent noise into account. It is found that the CSK system with the new PN code outperforms the conventional optical CSK system.

In this paper, the low density generator matrix (LDGM) coded scheme with unequal transmission power allocation (UTPA) in optical wireless channel is evaluated by computer simulation. In particular, the bit error rate performance of the LDGM-coded binary pulse position modulation (LDGM-BPPM) with the UTPA scheme is investigated in the presence of avalanche photo diode (APD) noise, scintillation and background noise. Consequently, the BER performance of the LDGM-BPPM with UTPA is better than that of the conventional LDGM-BPPM. It is found that there is the optimum power ratio (R). The optimum R varies with scintillation and background noise. For example, when the average received laser power is -47[dBm], the variance of scintillation is 0.1, and background noise is -45[dBm], the optimum R is 3.1. Thus, the LDGM-BPPM with the UTPA scheme is superior to the conventional LDGM-BPPM system.

The maximization of non-Gaussianity is an effective approach to achieve the complex independent component analysis (ICA) problem. However, the traditional complex maximization of non-Gaussianity (CMN) algorithm does not consider the influence of noise. In this letter, a modification of the fixed-point algorithm is proposed for more practical occasions of the complex noisy ICA model. Simulations show that the proposed method demonstrates significantly improved performance over the traditional CMN algorithm in the noisy ICA model when the sample size is sufficient.

In this paper, we show that if the d-decimation of a (q-1)-ary Sidelnikov sequence of period q-1=pm-1 is the d-multiple of the same Sidelnikov sequence, then d must be a power of a prime p. Also, we calculate the crosscorrelation magnitude between some constant multiples of d- and d'-decimations of a Sidelnikov sequence of period q-1 to be upper bounded by (d+d'-1)√q+3.

We present a dynamic key generation method, KeyQ, for establishing shared secret keys in EPCglobal Generation 2 (Gen2) compliant systems. Widespread adoption of Gen2 technologies has increased the need for protecting communications in these systems. The highly constrained resources on Gen2 tags limit the usability of traditional key distribution techniques. Dynamic key generation provides a secure method to protect communications with limited key distribution requirements. Our KeyQ method dynamically generates fresh secret keys based on the Gen2 adaptive Q algorithm. We show that the KeyQ method generates fresh and unique secret keys that cannot be predicted with probability greater than 10-250 when the number of tags exceeds 100.

To achieve more high speed and high quality systems of wireless communications, orthogonal frequency division multiple access (OFDMA) has been proposed. Moreover, OFDMA considering the multiuser diversity (MUDiv) has been also proposed to achieve more high system performance. On the other hand, the conventional MUDiv/OFDMA requires large complexity to select the subcarrier of each user. To solve this problem, we have proposed a MUDiv/OFDMA based on the low granularity block (LGB). However, it degrades the system performance in the environment which contains many deep faded subcarrier channels. Therefore, in this paper, we propose a cooperative LGB-MUDiv/OFDMA to mitigate the influence due to the deep faded subcarrier channel.

Misbehaving nodes intrinsic to the physical vulnerabilities of ad-hoc sensor networks pose a challenging constraint on the designing of data fusion. To address this issue, a statistics-based reputation method for reliable data fusion is proposed in this study. Different from traditional reputation methods that only compute the general reputation of a node, the proposed method modeled by negative binomial reputation consists of two separated reputation metrics: fusion reputation and sensing reputation. Fusion reputation aims to select data fusion points and sensing reputation is used to weigh the data reported by sensor nodes to the fusion point. So, this method can prevent a compromised node from covering its misbehavior in the process of sensing or fusion by behaving well in the fusion or sensing. To tackle the unexpected facts such as packet loss, a discounting factor is introduced into the proposed method. Additionally, Local Outlier Factor (LOF) based outlier detection is applied to evaluate the behavior result of sensor nodes. Simulations show that the proposed method can enhance the reliability of data fusion and is more accurate than the general reputation method when applied in reputation evaluation.

This paper presents an efficient method using Hadoop MapReduce for constructing a K-nearest neighbor graph (K-NNG) from a large-scale data set. K-NNG has been utilized as a data structure for data analysis techniques in various applications. If we are to apply the techniques to a large-scale data set, it is desirable that we develop an efficient K-NNG construction method. We focus on NN-Descent, which is a recently proposed method that efficiently constructs an approximate K-NNG. NN-Descent is implemented on a shared-memory system with OpenMP-based parallelization, and its extension for the Hadoop MapReduce framework is implied for a larger data set such that the shared-memory system is difficult to deal with. However, a simple extension for the Hadoop MapReduce framework is impractical since it requires extremely high system performance because of the high memory consumption and the low data transmission efficiency of MapReduce jobs. The proposed method relaxes the requirement by improving the MapReduce jobs, which employs an appropriate key-value pair format and an efficient sampling strategy. Experiments on large-scale data sets demonstrate that the proposed method both works efficiently and is scalable in terms of a data size, the number of machine nodes, and the graph structural parameter K.

As VLSI process node continue to shrink, chemical mechanical planarization (CMP) process for copper interconnect has become an essential technique for enabling many-layer interconnection. Recently, Edge-over-Erosion error (EoE-error), which originates from overpolishing and could cause yield loss, is observed in various CMP processes, while its mechanism is still unclear. To predict these errors, we propose an EoE-error prediction method that exploits machine learning algorithms. The proposed method consists of (1) error analysis stage, (2) layout parameter extraction stage, (3) model construction stage and (4) prediction stage. In the error analysis and parameter extraction stages, we analyze test chips and identify layout parameters which have an impact on EoE phenomenon. In the model construction stage, we construct a prediction model using the proposed multi-level machine learning method, and do predictions for designed layouts in the prediction stage. Experimental results show that the proposed method attained 2.7∼19.2% accuracy improvement of EoE-error prediction and 0.8∼10.1% improvement of non-EoE-error prediction compared with general machine learning methods. The proposed method makes it possible to prevent unexpected yield loss by recognizing EoE-errors before manufacturing.

It is shown that an infinite lumped-element LC- ladder network generates all Bessel functions Jn(t) of the first kind as a response to a single non-zero initial condition. Closed-form expressions for the voltage responses in the time domain are presented if the LC- ladder is driven by a step-like input voltage.

We analyze the correlation between BTI (Bias Temperature Instability) -induced degradations and process variations. Those reliability issues are correlated. BTI is one of the most significant aging-degradations on LSIs. Threshold voltages of MOSFETs increase with time when biases stress their gates. It shows a strong effect of BTI on highly scaled LSIs in the same way as the process variations. The accurate prediction of the combinational effects is indispensable. We should analyze both aging-degradations and process variations of MOSFETs to explain the correlation. We measure frequencies of ROs (Ring Oscillators) of 65-nm process test circuits on two types of LSIs, ASICs and FPGAs. There are 98 and 837 ROs on our ASICs and FPGAs respectively. The frequencies of ROs follow gaussian distributions. We describe the highest frequency group as the “fast” conditon, the average group as the “typical” conditon and the lowest group as the “slow” conditon. We measure the aging-degradations of the ROs of the three conditions on the accelerated test. The degradations can be approximated by logarithmic function of stress time. The degradation at the “fast” condition has a higher impact on the frequency than the “slow” one. The correlation coefficient is 0.338. In this case, we can define a smaller design margin for BTI-induced degradations than that without considering the correlation because the degradation at the “slow” conditon is smaller than the average and the fast.

N-Shift Regional Low Correlation (NS-RLC) sequences have the low values of the correlation function only in N-shift positions. Especially, N-Shift Regional Zero Correlation (NS-RZC) sequences have the zero values in N-shift positions. In this letter, the generation algorithm of N-shift RLC/RZC sequences derived from Three Low Correlation Zones (T-LCZ) sequence set and Three Zero Correlation Zones (T-ZCZ) sequence set is proposed. In order to highlight the relationship between these sequences, the corresponding theoretical bound is calculated and analyzed.

Due to the progress of the process technology in LSI, the yield of LSI chips is reduced by timing violations caused by delay variations. To recover the timing violations, delay tuning methods insert programmable delay elements called PDEs into the clock tree before fabrication and tune their delays after fabrication. The yield improvement of existing methods is not enough. In this paper, a delay tuning method of PDEs with an ordered finite set of delays is proposed for the yield improvement. The proposed delay tuning method is based on the modified Bellman-Ford algorithm. Therefore, its optimality is guaranteed and its time complexity is polynomial. In the experiments under Monte-Carlo simulation, the yield of the proposed method is improved higher when the number of delays in each PDE is increased.

In consideration of the image noise captured by photoelectric cameras at nighttime, a robust motion detection algorithm based on sparse representation is proposed in this study. A universal dictionary for arbitrary scenes is presented. Realistic and synthetic experiments demonstrate the robustness of the proposed approach.

Chronic liver disease is a major worldwide health problem. Diagnosis and staging of chronic liver diseases is an important issue. In this paper, we propose a quantitative method of analyzing local morphological changes for accurate and practical computer-aided diagnosis of cirrhosis. Our method is based on sparse and low-rank matrix decomposition, since the matrix of the liver shapes can be decomposed into two parts: a low-rank matrix, which can be considered similar to that of a normal liver, and a sparse error term that represents the local deformation. Compared with the previous global morphological analysis strategy based on the statistical shape model (SSM), our proposed method improves the accuracy of both normal and abnormal classifications. We also propose using the norm of the sparse error term as a simple measure for classification as normal or abnormal. The experimental results of the proposed method are better than those of the state-of-the-art SSM-based methods.

Current network technologies, mainly represented by the Internet, have demonstrated little capacity to evolve because of the strict binding of communications to identifiers and locators. While locator namespaces represent the position of communication participants in the graph of a specific protocol, unstructured/plain identifiers represent the position of communications participants in the global network graph. Although they are valid for forwarding packets along communication paths, both views fail to fully represent the actual entities behind communications beyond a simple vertex. In this paper we introduce and evaluate an identity-based control plane that resolves these problems by abstracting communications from identifiers and locators and by using identities to achieve enhanced security, and mobility management operations. This identity-based control plane can then be integrated into different network architectures in order to incorporate the features it provides. This facilitates the evolution capacity of those architectures that separate the information transmission concerns (networking, routing), from end-to-end aspects like security and mobility management.

This paper represents an illumination modeling method for lighting control which can model the illumination distribution inside office buildings. The algorithm uses data from the illumination sensors to train Radial Basis Function Neural Networks (RBFNN) which can be used to calculate 1) the illuminance contribution from each luminaire to different positions in the office 2) the natural illuminance distribution inside the office. This method can be used to provide detailed illumination contribution from both artificial and natural light sources for lighting control algorithms by using small amount of sensors. Simulations with DIALux are made to prove the feasibility and accuracy of the modeling method.

This paper reports a 65nm 8Mb spin transfer torque magnetoresistance random access memory (STT-MRAM) operating at a single supply voltage with a process-variation-tolerant sense amplifier. The proposed sense amplifier comprises a boosted-gate nMOS and negative-resistance pMOSs as loads, which maximizes the readout margin at any process corner. The STT-MRAM achieves a cycle time of 1.9µs (=0.526MHz) at 0.38V. The operating power is 1.70µW at this voltage. The minimum energy per access is 1.12 pJ/bit when the supply voltage is 0.44V. The proposed STT-MRAM operates at a lower energy than an SRAM when the utilization of the memory bandwidth is 14% or less.