An empirical Bayesian method was used to obtain a point estimator for the reliability function of a bivariate exponential distribution associated to a two-component parallel electronic system.

In order to realize an Internet-of-Things (IoT) with tiny sensors integrated in our buildings, our clothing, and the public spaces, battery lifetime and battery size remain major challenges. Power reduction in IoT sensor nodes is determined by both sleep mode as well as active mode contributions. A power state machine, at the system level, is the key to achieve ultra-low average power consumption by alternating the system between active and sleep modes efficiently. While, power consumption in the active mode remains dominant, other power contributions like for timekeeping in standby and sleep conditions are becoming important as well. For example, non-conventional critical blocks, such as crystal oscillator (XO) and resistor-capacitor oscillator (RCO) become more crucial during the design phase. Apart from power reduction, low-voltage operation will further extend the battery life. A 2.4GHz multi-standard radio is presented, as a test case, with an average power consumption in the µW range, and state-of-the-art performance across a voltage supply range from 1.2V to 0.9V.

The forbidden state problem is to synthesize a control policy for preventing a Petri net from reaching any state in its forbidden set. In this paper, we address a liveness preserving version of the forbidden state problem for lossy Petri nets. During the process of keeping Petri nets out of the set of their forbidden states, a control policy does not disable a live marking. We present a method to solve the above problem based on fixed point computations. We show that for lossy Petri nets, the problem is decidable. From a practical viewpoint, the problem associated with our fixed point approach is 'state explosion. ' In order to overcome this problem, we propose a symbolic approach, which uses Boolean functions for implicitly representing the set of states. We use Boolean functions for representing reachable markings. Thus OBDDs, compact representations of Boolean functions, can reduce the time and space involved in solving the forbidden state problem described in this paper.

A gold coated carbon nanotubes composite was used as a contact material in Micro-Electrical-Mechanical-System (MEMS) switches. The switching contact was tested under typical conditions of MEMS relay applications: load voltage of 4 V, contact force of 1 mN, and load current varied between 20-200 mA. This paper focuses on the wear process over switching lifetime, and the dependence of the wear area on the current is discussed. It was shown that the contact was going to fail when the wear area approached the whole contact area, at which point the contact resistance increased sharply to three times the nominal resistance.

With the rapid development of Internet of things (IoT), Radio Frequency Identification (RFID) has become one of the most significant information technologies in the 21st century. However, more and more privacy threats and security flaws have been emerging in various vital RFID systems. Traditional RFID systems only focus attention on foundational implementation, which lacks privacy protection and effective identity authentication. To solve the privacy protection problem this paper proposes a privacy protection method with a Privacy Enhancement Model for RFID (PEM4RFID). PEM4RFID utilizes a “2+2” identity authentication mechanism, which includes a Two-Factor Authentication Protocol (TFAP) based on “two-way authentication”. Our TFAP employs “hardware information + AES-ECC encryption”, while the ”“two-way authentication” is based on improved Combined Public Key (CPK). Case study shows that our proposed PEM4RFID has characteristics of untraceability and nonrepeatability of instructions, which realizes a good trade-off between privacy and security in RFID systems.

Wi-Fi-based person identification (PI) tasks are performed by analyzing the fluctuating characteristics of the Channel State Information (CSI) data to determine whether the person's identity is legitimate. This technology can be used for intrusion detection and keyless access to restricted areas. However, the related research rarely considers the restricted computing resources and the complexity of real-world environments, resulting in lacking practicality in some scenarios, such as intrusion detection tasks in remote substations without public network coverage. In this paper, we propose a novel neural network model named SimpleViTFi, a lightweight classification model based on Vision Transformer (ViT), which adds a downsampling mechanism, a distinctive patch embedding method and learnable positional embedding to the cropped ViT architecture. We employ the latest IEEE 802.11ac 80MHz CSI dataset provided by [1]. The CSI matrix is abstracted into a special “image” after pre-processing and fed into the trained SimpleViTFi for classification. The experimental results demonstrate that the proposed SimpleViTFi has lower computational resource overhead and better accuracy than traditional classification models, reflecting the robustness on LOS or NLOS CSI data generated by different Tx-Rx devices and acquired by different monitors.

Compared to subword based Neural Machine Translation (NMT), character based NMT eschews linguistic-motivated segmentation which performs directly on the raw character sequence, following a more absolute end-to-end manner. This property is more fascinating for machine translation (MT) between Japanese and Chinese, both of which use consecutive logographic characters without explicit word boundaries. However, there is still one disadvantage which should be addressed, that is, character is a less meaning-bearing unit than the subword, which requires the character models to be capable of sense discrimination. Specifically, there are two types of sense ambiguities existing in the source and target language, separately. With the former, it has been partially solved by the deep encoder and several existing works. But with the later, interestingly, the ambiguity in the target side is rarely discussed. To address this problem, we propose two simple yet effective methods, including a non-parametric pre-clustering for sense induction and a joint model to perform sense discrimination and NMT training simultaneously. Extensive experiments on Japanese⟷Chinese MT show that our proposed methods consistently outperform the strong baselines, and verify the effectiveness of using sense-discriminated representation for character based NMT.

This paper proposes a determination method of the cascaded number for lumped parameter models (LPMs) of the transmission lines. The LPM is used to simulate long-distance transmission lines, and the cascaded number significantly impacts the simulation results. Currently, there is a lack of a system-level determination method of the cascaded number for LPMs. Based on the theoretical analysis and eigenvalue decomposition of network matrix, this paper discusses the error in resonance characteristics between distributed parameter model and LPMs. Moreover, it is deduced that optimal cascaded numbers of the cascaded π-type and T-type LPMs are the same, and the Γ-type LPM has a lowest analog accuracy. The principle that the maximum simulation frequency is less than the first resonance frequency of each segment is presented. According to the principle, optimal cascaded numbers of cascaded π-type, T-type, and Γ-type LPMs are obtained. The effectiveness of the proposed determination method is verified by simulation.

The paper demonstrates a novel multiple-valued logic (MVL) design using a three-peak negative differential resistance (NDR) circuit, which is made of several Si-based metal-oxide-semiconductor field-effect-transistor (MOS) and SiGe-based heterojunction bipolar transistor (HBT) devices. Specifically, this three-peak NDR circuit is biased by two switch-controlled current sources. Compared to the traditional MVL circuit made of resonant tunneling diode (RTD), this multiple-peak MOS-HBT-NDR circuit has two major advantages. One is that the fabrication of this circuit can be fully implemented by the standard BiCMOS process without the need for molecular-beam epitaxy system. Another is that we can obtain more logic states than the RTD-based MVL design. In measuring, we can obtain eight logic states at the output according to a sequent control of two current sources on and off in order.

H.264 video codec system requires big capacity and high bandwidth of Frame Store (FS) for buffering reference frames. The up-to-date three dimensional (3D) stacked Phase change Random Access Memory (PRAM) is the promising approach for on-chip caching the reference signals, as 3D stacking offers high memory bandwidth, while PRAM possesses the advantages in terms of high density and low leakage power. However, the write endurance problem, that is a PRAM cell can only tolerant limited number of write operations, becomes the main barrier in practical applications. This paper studies the wear reduction techniques of PRAM based FS in H.264 codec system. On the basis of rate-distortion theory, the content oriented selective writing mechanisms are proposed to reduce bit updates in the reference frame buffers. With the proposed control parameter a, our methods make the quantitative trade off between the quality degradation and the PRAM lifetime prolongation. Specifically, taking a in the range of [0.2,2], experimental results demonstrate that, our methods averagely save 29.9–35.5% bit-wise write operations and reduce 52–57% power, at the cost of 12.95–20.57% BDBR bit-rate increase accordingly.

We present a new method to detect weak linear frequency modulated (LFM) signals in strong noise using the chaos oscillator. Chaotic systems are sensitive to specific signals yet immune to noise. With our new method we firstly use the Radon-Wigner transform to dechirp the LFM signal. Secondly, we set up a chaotic oscillator sensitive to weak signals based on the Duffing equation, and poising the system at its critical state. Finally, we input the dechirped sequence into the system as a perturbation of the driving force. A weak signal with the same frequency will lead to a qualitative transition in the system state. The weak signal in the presence of strong noise can then be detected from the phase transition of the phase plane trajectory of the chaotic system. Computer simulation results show that LFM signals with an SNR lower than -27 dB can be detected by this method.

A novel parallel acceleration technique is proposed based on intrinsic parallelism characteristics of shooting-and-bouncing ray launching (SBR) algorithm, which has been implemented using the MPI parallel library on common PC cluster instead of dedicated parallel machines. The results reveal that the new technique achieves very large speedup gains and could be the efficient and low-cost propagation prediction solution.

In most phrase-based statistical machine translation (SMT) systems, the translation model relies on word alignment, which serves as a constraint for the subsequent building of a phrase table. Word alignment is usually inferred by GIZA++, which implements all the IBM models and HMM model in the framework of Expectation Maximum (EM). In this paper, we present a fully Bayesian inference for word alignment. Different from the EM approach, the Bayesian inference makes use of all possible parameter values rather than estimating a single parameter value, from which we expect a more robust inference. After inferring the word alignment, current SMT systems usually train the phrase table from Viterbi word alignment, which is prone to learn incorrect phrases due to the word alignment mistakes. To overcome this drawback, a new phrase extraction method is proposed based on multiple Gibbs samples from Bayesian inference for word alignment. Empirical results show promising improvements over baselines in alignment quality as well as the translation performance.

We present the design of a secure identifier-based inter-domain routing, SIR, for the identifier/locator split network. On the one hand, SIR is a distributed path-vector protocol inheriting the flexibility of BGP. On the other hand, SIR separates ASes into several groups called trust groups, which assure the trust relationships among ASes by enforceable control and provides strict isolation properties to localize attacks and failures. Security analysis shows that SIR can provide control plane security that can avoid routing attacks including some smart attacks which S-BGP/soBGP can be deceived. Meanwhile, emulation experiments based on the current Internet topology with 47,000 ASes from the CAIDA database are presented, in which we compare the number of influenced ASes under attacks of subverting routing policy between SIR and S-BGP/BGP. The results show that, the number of influenced ASes decreases substantially by deploying SIR.

A low loss intelligent power module (IPM) that specifically designed for high performance frequency-alterable air conditioner applications is proposed. This IPM utilizes 600 V trench gate field stop insulated gate bipolar transistors (TFS-IGBTs) as the main switching devices to deliver extremely low conduction and switching losses. In addition, 600 V SiC schottky barrier diodes (SBDs) are employed as the freewheeling diodes. Compared to conventional silicon fast recovery diodes (FRDs) SiC SBDs exhibit practically no reverse recovery loss, hence can further reduce the power loss of the IPM. Experimental results reveal that the power loss of the proposed IPM is between 3.5∼21.7 W at different compressor frequencies from 10 to 70 Hz, which achieving up to 12.5%∼25.5% improvement when compared to the state-of-the-art conventional Si-based IGBT IPM.

An empirical formula of resonant frequency of bow-tie microstrip antennas is presented, which is based on the cavity model of microstrip patch antennas. A procedure to design a bow-tie antenna using genetic algorithm (GA) in which we take the formula as a fitness function is also given. An optimized bow-tie antenna by genetic algorithm was constructed and measured. Numerical and experimental results are used to validate the formula and GA. The results are in good agreement.

This paper proposes an improved method of reversible data hiding with increased capacity. The conventional method determines whether to embed a data bit in an image block according to the statistics of pixels in that block. Some images have pixel statistics that are inadequate for data hiding, and seldom or never have data embedded in them. The proposed method modulates the statistics invertibility to overcome such disadvantages, and is also able to improve the quality of the image containing the hidden data using block-adaptive modulation. Simulationresults show the effectiveness of the proposed method.

Numerical analysis of the photoinductive (PI) field mapping technique for characterizing the eddy-current (EC) probes with tilted coils above a thin metal film was investigated using a two-dimensional transient finite element method (FEM). We apply the FEM model of PI method to observe the influence of metal film materials on the field-mapping images used to characterize EC probes. The effects of film thickness on the PI mapping signal are also shown and discussed. The simulation results using the proposed model showed that the PI signals largely depend on the thermal conductivity and the thickness of the thin metal film. The field-mapping signals using the appropriate actual metal film material for EC probe coil with 0°, 5°, 10°, 15°, and 20° tilt angle are also examined. We demonstrate that the higher resolution in field-mapping images of commercial EC probes can be obtained by given higher thermal conductivity and thinner thickness of metal film. The fundamental understanding of distinct field distribution will aid in the selection of the higher-quality EC probe for accurate inspection with EC testing.

A multiple-peak negative differential resistance (NDR) circuit made of standard Si-based metal-oxide-semiconductor field-effect-transistor (MOS) and SiGe-based heterojunction bipolar transistor (HBT) is demonstrated. We can obtain a three-peak I-V curve by connecting three cascoded MOS-HBT-NDR circuits by suitably designing the MOS parameters. This novel three-peak NDR circuit possesses the adjustable current-voltage characteristics and high peak-to-valley current ratio (PVCR). We can adjust the PVCR values to be as high as 11.5, 6.5, and 10.3 for three peaks, respectively. Because the NDR circuit is a very strong nonlinear element, we discuss the extrinsic hysteresis phenomena in this multiple-peak NDR circuit. The effect of series resistance on hysteresis phenomena is also investigated. Our design and fabrication of the NDR circuit is based on the standard 0.35 µm SiGe BiCMOS process.

More recently, there has been a growing interest in the study of wireless sensor network (WSN) technologies for Interest of Things (IoT). To improve the positioning accuracy of mobile station under the non-line-of-sight (NLOS) environment, a localization algorithm based on the single-hidden layer feedforward network (SLFN) using extreme learning machine (ELM) for WSN is proposed in this paper. Optimal reduction in the time difference of arrival (TDOA) measurement error is achieved using SLFN optimized by ELM. Compared with those traditional learning algorithms, ELM has its unique feature of a higher generalization capability at a much faster learning speed. After utilizing the ELM by randomly assigning the parameters of hidden nodes in the SLFN, the competitive performance can be obtained on the optimization task for TDOA measurement error. Then, based on that result, Taylor algorithm is implemented to deal with the position problem of mobile station. Experimental results show that the effect of NLOS propagation is reduced based on our proposed algorithm by introducing the ELM into Taylor algorithm. Moreover, in the simulation, the proposed approach, called Taylor-ELM, provides better performance compared with some traditional algorithms, such as least squares, Taylor, backpropagation neural network based Taylor, and Chan positioning methods.