In this paper, new classes of binary generalized cyclotomic sequences of period 2pm+1qn+1 are constructed. These sequences are balanced. We calculate the linear complexity of the constructed sequences with a simple method. The results show that the linear complexity of such sequences attains the maximum.

In the past two decades, many generalized cyclotomic sequences have been constructed and they have been used in cryptography and communication systems for their high linear complexity and low autocorrelation. But there are a few of papers focusing on the 2-adic complexities of such sequences. In this paper, we first give a property of a class of Gaussian periods based on Whiteman's generalized cyclotomic classes of order 4. Then, as an application of this property, we study the 2-adic complexity of a class of Whiteman's generalized cyclotomic sequences constructed from two distinct primes p and q. We prove that the 2-adic complexity of this class of sequences of period pq is lower bounded by pq-p-q-1. This lower bound is at least greater than one half of its period and thus it shows that this class of sequences can resist against the rational approximation algorithm (RAA) attack.

We propose a penalty-based and constraint Bayesian optimization methods with an agent-based supply-chain (SC) simulator as a new Monte Carlo optimization approach for multi-echelon inventory management to improve key performance indicators such as inventory cost and sales opportunity loss. First, we formulate the multi-echelon inventory problem and introduce an agent-based SC simulator architecture for the optimization. Second, we define the optimization framework for the formulation. Finally, we discuss the evaluation of the effectiveness of the proposed methods by benchmarking it against the most commonly used genetic algorithm (GA) in simulation-based inventory optimization. Our results indicate that the constraint Bayesian optimization can minimize SC inventory cost with lower sales opportunity loss rates and converge to the optimal solution 22 times faster than GA in the best case.

In this paper, we consider the problem of waveform optimization for multi-input multi-output (MIMO) radar in the presence of signal-dependent noise. A novel diagonal loading (DL) based method is proposed to optimize the waveform covariance matrix (WCM) for minimizing the Cramer-Rao bound (CRB) which improves the performance of parameter estimation. The resulting nonlinear optimization problem is solved by resorting to a convex relaxation that belongs to the semidefinite programming (SDP) class. An optimal solution to the initial problem is then constructed through a suitable approximation to an optimal solution of the relaxed one (in a least squares (LS) sense). Numerical results show that the performance of parameter estimation can be improved considerably by the proposed method compared to uncorrelated waveforms.

In this letter, a micro-expression recognition method is investigated by integrating both spatio-temporal facial features and a regression model. To this end, we first perform a multi-scale facial region division for each facial image and then extract a set of local binary patterns on three orthogonal planes (LBP-TOP) features corresponding to divided facial regions of the micro-expression videos. Furthermore, we use GSLSR model to build the linear regression relationship between the LBP-TOP facial feature vectors and the micro expressions label vectors. Finally, the learned GSLSR model is applied to the prediction of the micro-expression categories for each test micro-expression video. Experiments are conducted on both CASME II and SMIC micro-expression databases to evaluate the performance of the proposed method, and the results demonstrate that the proposed method is better than the baseline micro-expression recognition method.

Codebooks with small inner-product correlation have applied in direct spread code division multiple access communications, space-time codes and compressed sensing. In general, it is difficult to construct optimal codebooks achieving the Welch bound or the Levenstein bound. This paper focuses on constructing asymptotically optimal codebooks with characters of cyclic groups. Based on the proposed constructions, two classes of asymptotically optimal codebooks with respect to the Welch bound are presented. In addition, parameters of these codebooks are new.

Geographic routing uses the geographical location information provided by nodes to make routing decisions. However, the nodes can not obtain accurate location information due to the effect of measurement error. A new routing strategy using maximum expected distance and angle (MEDA) algorithm is proposed to improve the performance and promote the successive transmission rate. We firstly introduce the expected distance and angle, and then we employ the principal component analysis to construct the object function for selecting the next hop node. We compare the proposed algorithm with maximum expectation within transmission range (MER) and greedy routing scheme (GRS) algorithms. Simulation results show that the proposed MEDA algorithm outperforms the MER and GRS algorithms with higher successive transmission rate.

Periodic sequences, used as keys in cryptosystems, plays an important role in cryptography. Such periodic sequences should possess high linear complexity to resist B-M algorithm. Sequences constructed by cyclotomic cosets have been widely studied in the past few years. In this paper, the linear complexity of n-periodic cyclotomic sequences of order 2 and 4 over 𝔽p has been calculated, where n and p are two distinct odd primes. The conclusions reveal that the presented sequences have high linear complexity in many cases, which indicates that the sequences can resist the linear attack.

FPGA-based switches are appealing nowadays due to the balance between hardware performance and software flexibility. Packet parser, as the foundational component of FPGA-based switches, is to identify and extract specific fields used in forwarding decisions, e.g., destination IP address. However, traditional parsers are too rigid to accommodate new protocols. In addition, FPGAs usually have a much lower clock frequency and fewer hardware resources, compared to ASICs. In this paper, we present PLANET, a programmable packet-level parallel parsing architecture for FPGA-based switches, to overcome these two limitations. First, PLANET has flexible programmability of updating parsing algorithms at run-time. Second, PLANET highly exploits parallelism inside packet parsing to compensate FPGA's low clock frequency and reduces resource consumption with one-block recycling design. We implemented PLANET on an FPGA-based switch prototype with well-integrated datacenter protocols. Evaluation results show that our design can parse packets at up to 100 Gbps, as well as maintain a relative low parsing latency and fewer hardware resources than existing proposals.

Jacobi sequences have good cryptography properties. Li et al. [X. Li et al., Linear Complexity of a New Generalized Cyclotomic Sequence of Order Two of Length pq*, IEICE Trans. Fundamentals, vol.E96-A, no.5, pp.1001-1005, 2013] defined a new modified Jacobi sequence of order two and got its linear complexity. In this corresponding, we determine the linear complexity and minimal polynomials of the new modified Jacobi sequence of order d. Our results show that the sequence is good from the viewpoint of linear complexity.

CMOS SoCs can reduce power consumption by adopting voltage scaling (VS) technologies, where the level converter (LC) is required between voltage domains to avoid dc current. However, the LC often induces high delay penalty and usually results in non-balanced rise and fall delays. Therefore, the performance of the LC strongly affects the effectiveness of VS technologies. In this paper, heuristic sizing methodology for designing a state-of-the-art LC is developed and proposed. Using the proposed methodology, we can design the LC to achieve high performance with balanced rise and fall delay times in a deterministic way.

The issue of robust multi-input multi-output (MIMO) radar waveform design is investigated in the presence of imperfect clutter prior knowledge to improve the worst-case detection performance of space-time adaptive processing (STAP). Robust design is needed because waveform design is often sensitive to uncertainties in the initial parameter estimates. Following the min-max approach, a robust waveform covariance matrix (WCM) design is formulated in this work with the criterion of maximization of the worst-case output signal-interference-noise-ratio (SINR) under the constraint of the initial parameter estimation errors to ease this sensitivity systematically and thus improve the robustness of the detection performance to the uncertainties in the initial parameter estimates. To tackle the resultant complicated and nonlinear robust waveform optimization issue, a new diagonal loading (DL) based iterative approach is developed, in which the inner and outer optimization problems can be relaxed to convex problems by using DL method, and hence both of them can be solved very effectively. As compared to the non-robust method and uncorrelated waveforms, numerical simulations show that the proposed method can improve the robustness of the detection performance of STAP.

Permutation polynomials over Zpn are useful in the design of cryptographic algorithms. In this paper, we obtain an equivalent condition for polynomial functions over Zpn to be permutations, and this equivalent condition can help us to analysis the randomness of such functions. Our results provide a method to distinguish permutation polynomials from random functions. We also introduce how to improve the randomness of permutation polynomials over Zpn.

In this paper we present a 0.25–1.0 V, 0.1–200 MHz, 25632, 65 nm SRAM macro. The main design techniques include a bitline leakage prediction scheme and a non-trimmed non-strobed sense amplifier to deal with process and runtime variations and data dependence.

This paper presents a channel operating margin (COM) based high-speed serial link optimization using machine learning (ML). COM that is proposed for evaluating serial link is calculated at first and during the calculation several important equalization parameters corresponding to the best configuration are extracted which can be used for the ML modeling of serial link. Then a deep neural network containing hidden layers are investigated to model a whole serial link equalization including transmitter feed forward equalizer (FFE), receiver continuous time linear equalizer (CTLE) and decision feedback equalizer (DFE). By training, validating and testing a lot of samples that meet the COM specification of 400GAUI-8 C2C, an effective ML model is generated and the maximum relative error is only 0.1 compared with computation results. At last 3 link configurations are discussed from the view of tradeoff between the link performance and cost, illustrating that our COM based ML modeling method can be applied to advanced serial link design for NRZ, PAM4 or even other higher level pulse amplitude modulation signal.

The integration of social networking concepts into the Internet of Things has led to the Social Internet of Things (SIoT) paradigm, and trust evaluation is essential to secure interaction in SIoT. In SIoT, when resource-constrained nodes respond to unexpected malicious services and malicious recommendations, the trust assessment is prone to be inaccurate, and the existing architecture has the risk of privacy leakage. An edge-cloud collaborative trust evaluation architecture in SIoT is proposed in this paper. Utilize the resource advantages of the cloud and the edge to complete the trust assessment task collaboratively. An evaluation algorithm of relationship closeness between nodes is designed to evaluate neighbor nodes' reliability in SIoT. A trust computing algorithm with enhanced sensitivity is proposed, considering the fluctuation of trust value and the conflict between trust indicators to enhance the sensitivity of identifying malicious behaviors. Simulation results show that compared with traditional methods, the proposed trust evaluation method can effectively improve the success rate of interaction and reduce the false detection rate when dealing with malicious services and malicious recommendations.

We consider a time-division multiple access (TDMA) transmission scheme in MIMO broadcast channels. To cope with the fairness issue in heterogeneous networks with slow fading, an opportunistic scheduling algorithm based on the channel eigen-direction is investigated. In the system with sparse users, the mismatch between a random beamforming vector and the principle eigenvector of the channel incurs a throughput penalty. To reduce such a throughput loss, a multiple random beams selection (MRBS) scheme exploiting chordal distances is proposed. Two feedback schemes (unquantized or quantized chordal distances) are considered. The closed-form throughput expressions of the proposed schemes are derived.

This paper presents an accurate and systematic method to simulate the interference imposed on the input/output (I/O) ports of electronic equipment under the electrical fast transients/burst (EFT/B) test. The equivalent circuit of the EFT/B generator and the coupling clamp are modeled respectively. Firstly, a transfer function (TF) of the EFT pulse-forming network is constructed with the latent parameters based on circuit theory. In the TF, two negative real parameters characterize the non-oscillation process of the network while one complex conjugate pair characterizes the damping-oscillation process. The TF of the pulse-forming network is therefore synthesized in the equivalent circuit of the EFT/B generator. Secondly, the standard coupling clamp is modeled based on the scatter (S) parameter obtained by using a vector network analyzer. By applying the vector fitting method during the rational function approximation, a macromodel of the coupling clamp can be obtained and converted to a Spice compatible equivalent circuit. Based on the aforementioned procedures, the interference imposed on the I/O ports can be simulated. The modeling methods are validated experimentally, where the interference in differential mode and common mode is evaluated respectively.

In this paper, the linear complexity and minimal polynomials of Legendre sequences over Fq have been calculated, where q = pm and p is a prime number. Our results show that Legendre sequences have high linear complexity over Fq for a large part of prime power number q so that they can resist the linear attack method.

CMOS SoCs can reduce power consumption while maintaining performance by adopting voltage scaling (VS) technologies. The operating speed of the level converter (LC) strongly affects the effectiveness of VS technologies. However, PVT variations can cause serious problems to the LC, because the state-of-the-art LC designs do not give enough attention to this issue. In this work, we proposed to analyze the impact of PVT variations on the performance of the LC using a previously developed heuristic sizing methodology. Based on the evaluation results from different operating corners with different offset voltages and temperatures, we proposed a variation-tolerant LC that achieves both high performance and low energy with a high tolerability for PVT variations.