In recent years, blockchain has been widely applied in the Internet of Things (IoT). Blockchain oracle, as a bridge for data communication between blockchain and off-chain, has also received significant attention. However, the numerous and heterogeneous devices in the IoT pose great challenges to the efficiency and security of data acquisition for oracles. We find that the matching relationship between data sources and oracle nodes greatly affects the efficiency and service quality of the entire oracle system. To address these issues, this paper proposes a distributed and efficient oracle solution tailored for the IoT, enabling fast acquisition of real-time off-chain data. Specifically, we first design a distributed oracle architecture that combines both Trusted Execution Environment (TEE) devices and ordinary devices to improve system scalability, considering the heterogeneity of IoT devices. Secondly, based on the trusted node information provided by TEE, we determine the matching relationship between nodes and data sources, assigning appropriate nodes for tasks to enhance system efficiency. Through simulation experiments, our proposed solution has been shown to effectively improve the efficiency and service quality of the system, reducing the average response time by approximately 9.92% compared to conventional approaches.

This paper shows that sum-of-product expression (SOP) minimization produces the generalization ability. We show this in three steps. First, various classes of SOPs are generated. Second, minterms of SOP are randomly selected to generate partially defined functions. And, third, from the partially defined functions, original functions are reconstructed by SOP minimization. We consider Achilles heel functions, majority functions, monotone increasing cascade functions, functions generated from random SOPs, monotone increasing random SOPs, circle functions, and globe functions. As for the generalization ability, the presented method is compared with Naive Bayes, multi-level perceptron, support vector machine, JRIP, J48, and random forest. For these functions, in many cases, only 10% of the input combinations are sufficient to reconstruct more than 90% of the truth tables of the original functions.

Binary Neural Networks (BNN) have binarized neuron and connection values so that their accelerators can be realized by extremely efficient hardware. However, there is a significant accuracy gap between BNNs and networks with wider bit-width. Conventional BNNs binarize feature maps by static globally-unified thresholds, which makes the produced bipolar image lose local details. This paper proposes a multi-input activation function to enable adaptive thresholding for binarizing feature maps: (a) At the algorithm level, instead of operating each input pixel independently, adaptive thresholding dynamically changes the threshold according to surrounding pixels of the target pixel. When optimizing weights, adaptive thresholding is equivalent to an accompanied depth-wise convolution between normal convolution and binarization. Accompanied weights in the depth-wise filters are ternarized and optimized end-to-end. (b) At the hardware level, adaptive thresholding is realized through a multi-input activation function, which is compatible with common accelerator architectures. Compact activation hardware with only one extra accumulator is devised. By equipping the proposed method on FPGA, 4.1% accuracy improvement is achieved on the original BNN with only 1.1% extra LUT resource. Compared with State-of-the-art methods, the proposed idea further increases network accuracy by 0.8% on the Cifar-10 dataset and 0.4% on the ImageNet dataset.

This paper analyzes the typical functions of digital control circuit and its function modules, and develops a set of digital control circuit equipment based on Advanced RISC Machines (ARM) with typical function modules, including principle design, interference injection trace design, function design, and study the failure mode and threshold of typical function modules. Based on continuous wave (CW) and pulse wave, the direct power injection (DPI) method is used to test the conduction immunity of the digital control circuit, and the failure mode and sensitivity threshold of the digital control circuit are quantitatively obtained. This method can provide experimental verification for the immunity ability of the digital control circuit to different electromagnetic interference.

We show that every polynomial threshold function that sign-represents the ODD-MAXBITn function has total absolute weight 2Ω(n1/3). The bound is tight up to a logarithmic factor in the exponent.

The decoders, which improve the error-correction performance by finding and correcting the error bits caused by channel noise, are a hotspot for polar codes. In this paper, we present a threshold based D-SCFlip (TD-SCFlip) decoder with two improvements based on the D-SCFlip decoder. First, we propose the LLR fidelity criterion to define the LLR threshold and investigate confidence probability to calculate the LLR threshold indirectly. The information bits whose LLR values are smaller than the LLR threshold will be excluded from the range of candidate bits, which reduces the complexity of constructing the flip-bits list without the loss of error-correction performance. Second, we improve the calculation method for flip-bits metric with two perturbation parameters, which locates the channel-induced error bits faster, thus improving the error-correction performance. Then, TD-SCFlip-ω decoder is also proposed, which is limited to correcting up to ω bits in each extra decoding attempt. Simulation results show that the TD-SCFlip decoding is slightly better than the D-SCFlip decoding in terms of error-correction performance and decoding complexity, while the error-correction performance of TD-SCFlip-ω decoding is comparable to that of D-SCFlip-ω decoding but with lower decoding complexity.

To simultaneously enhance data rate and physical layer security (PLS) for low-luminance smartphone screen to camera uplink communication, space division multiplexing using high-luminance cell-size reduction arrangement is numerically analyzed and experimentally verified. The uplink consists of a low-luminance smartphone screen and an indoor telephoto camera at a long distance of 3.5 meters. The high-luminance cell-size reduction arrangement avoids the influence of spatial inter-symbol interference (ISI) and ambient light to obtain a stable low-luminance screen. To reduce the screen luminance without decreasing the screen pixel value, the arrangement reduces only the high-luminance cell area while keeping the cell spacing. In this study, two technical issues related to high-luminance cell-size reduction arrangement are solved. First, a numerical analysis and experimental results show that the high-luminance cell-size reduction arrangement is more effective in reducing the spatial ISI at low luminance than the conventional low-luminance cell arrangement. Second, in view point of PLS enhancement at wide angles, symbol error rate should be low in front of the screen and high at wide angles. A numerical analysis and experimental results show that the high-luminance cell-size reduction arrangement is more suitable for enhancing PLS at wide angles than the conventional low-luminance cell arrangement.

This study considered an extension of a sparse regularization method with scaling, especially in thresholding methods that are simple and typical examples of sparse modeling. In this study, in the setting of a non-parametric orthogonal regression problem, we developed and analyzed a thresholding method in which soft thresholding estimators are independently expanded by empirical scaling values. The scaling values have a common hyper-parameter that is an order of expansion of an ideal scaling value to achieve hard thresholding. We simply refer to this estimator as a scaled soft thresholding estimator. The scaled soft thresholding method is a bridge method between soft and hard thresholding methods. This new estimator is indeed consistent with an adaptive LASSO estimator in the orthogonal case; i.e., it is thus an another derivation of an adaptive LASSO estimator. It is a general method that includes soft thresholding and non-negative garrote as special cases. We subsequently derived the degree of freedom of the scaled soft thresholding in calculating the Stein's unbiased risk estimate. We found that it is decomposed into the degree of freedom of soft thresholding and the remainder term connecting to the hard thresholding. As the degree of freedom reflects the degree of over-fitting, this implies that the scaled soft thresholding has an another source of over-fitting in addition to the number of un-removed components. The theoretical result was verified by a simple numerical example. In this process, we also focused on the non-monotonicity in the above remainder term of the degree of freedom and found that, in a sparse and large sample setting, it is mainly caused by useless components that are not related to the target function.

This paper proposes a novel maximum Doppler frequency detection technique for user moving velocity estimation. The maximum Doppler frequency is estimated in the proposed detection technique by making use of the fact that user moving velocity is not distributed continuously. The fluctuation of the channel state information during a packet is applied for the proposed detection, in which likelihood estimation is performed by comparing the fluctuation with the thresholds. The thresholds are theoretically derived on the assumption that the fluctuation is distributed with an exponential function. An approximated detection technique is proposed to simplify the theoretical threshold derivation. The performance of the proposed detection is evaluated by computer simulation. The proposed detection accomplishes better detection performance as the fluctuation values are summed over more packets. The proposed detection achieves about 90% correct detection performance in a fading channel with the Eb/N0 = 35dB, when the fluctuation values are summed over only three packets. Furthermore, the approximated detection also achieves the same detection performance.

As an emerging technology, device-free localization (DFL) using wireless sensor networks to detect targets not carrying any electronic devices, has spawned extensive applications, such as security safeguards and smart homes or hospitals. Previous studies formulate DFL as a classification problem, but there are still some challenges in terms of accuracy and robustness. In this paper, we exploit a generalized thresholding algorithm with parameter p as a penalty function to solve inverse problems with sparsity constraints for DFL. The function applies less bias to the large coefficients and penalizes small coefficients by reducing the value of p. By taking the distinctive capability of the p thresholding function to measure sparsity, the proposed approach can achieve accurate and robust localization performance in challenging environments. Extensive experiments show that the algorithm outperforms current alternatives.

In this paper, a stochasic geometry analysis of the inversely proportional setting (IPS) of carrier sense threshold (CST) and transmission power for densely deployed wireless local area networks (WLANs) is presented. In densely deployed WLANs, CST adjustment is a crucial technology to enhance spatial reuse, but it can starve surrounding transmitters due to an asymmetric carrier sensing relationship. In order for the carrier sensing relationship to be symmetric, the IPS of the CST and transmission power is a promising approach, i.e., each transmitter jointly adjusts its CST and transmission power in order for their product to be equal to those of others. This setting is used for spatial reuse in IEEE 802.11ax. By assuming that the set of potential transmitters follows a Poisson point process, the impact of the IPS on throughput is formulated based on stochastic geometry in two scenarios: an adjustment at a single transmitter and an identical adjustment at all transmitters. The asymptotic expression of the throughput in dense WLANs is derived and an explicit solution of the optimal CST is achieved as a function of the number of neighboring potential transmitters and signal-to-interference power ratio using approximations. This solution was confirmed through numerical results, where the explicit solution achieved throughput penalties of less than 8% relative to the numerically evaluated optimal solution.

A new threshold circuit technique is proposed for a vibration sensing circuit that operates at a nanowatt power level. The sensing circuits that use sample-and-hold require a clock signal, and they consume power to generate a signal. In the use of a Schmitt trigger circuit that does not use a clock signal, a sink current flows when thresholding the analog signal output. The requirements for millimeter-sized wireless sensor nodes are an average power on the order of a nanowatt and a signal transition time of less than 1 ms. To meet these requirements, our circuit limits the sink current with a nanoampere-level current source. The chattering caused by current limiting is suppressed by feeding back the change in output voltage to the limiting current. The increase in the signal transition time that is caused by current limiting is reduced by accelerating the discharge of the load capacitance. For a test chip fabricated in the 0.35-µm CMOS process, the proposed threshold circuits operate without chattering and the average powers are 0.7-3 nW. The signal transition times are estimated in a circuit simulation to be 65-97 µs. The proposed circuit has 1/150th the power-delay product with no time interval of the sensing operation under the condition that the time interval is 1s. These results indicate that, the proposed threshold circuits are suitable for vibration sensing in millimeter-sized wireless sensor nodes.

In this study, the transient characteristics on the super-steep subthreshold slope (SS) of a PN-body tied (PNBT) silicon-on-insulator field-effect transistor (SOI-FET) were investigated using technology computer-aided design and pulse measurements. Carrier charging effects were observed on the super-steep SS PNBT SOI-FET. It was found that the turn-on delay time decreased to nearly zero when the gate overdrive-voltage was set to 0.1-0.15 V. Additionally, optimizing the gate width improved the turn-on delay. This has positive implications for the low speed problems of this device. However, long-term leakage current flows on turn-off. The carrier lifetime affects the leakage current, and the device parameters must be optimized to realize both a high on/off ratio and high-speed operation.

With increasing technology scaling and the use of lower voltages, more research interest is being shown in variability-tolerant analog front end design. In this paper, we describe an adaptive amplitude control transmitter that is operated using differential signaling to reduce the temperature variability effect. It enables low power, low voltage operation by synergy between adaptive amplitude control and Vth temperature variation control. It is suitable for high-speed interface applications, particularly cable interfaces. By installing an aggressor circuit to estimate transmitter jitter and changing its frequency and activation rate, we were able to analyze the effects of the interface block on the input buffer and thence on the entire system. We also report a detailed estimation of the receiver clock-data recovery (CDR) operation for transmitter jitter estimation. These investigations provide suggestions for widening the eye opening of the transmitter.

Lately, an increasing number of wireless local area network (WLAN) access points (APs) are deployed to serve an ever increasing number of mobile stations (STAs). Due to the limited frequency spectrum, more and more AP and STA nodes try to access the same channel. Spatial spectrum reuse is promoted by the IEEE 802.11ax task group through dynamic sensitivity control (DSC), which permits cochannel operation when the received signal power at the prospective transmitting node (PTN) is lower than an adjusted carrier sensing threshold (CST). Previously-proposed DSC approaches typically calculate the CST without node grouping by using a margin parameter that remains fixed during operation. Setting the margin has previously been done heuristically. Finding a suitable value has remained an open problem. Therefore, herein, we propose a DSC approach that employs a node grouping method for adaptive calculation of the CST at the PTN with a channel-aware and margin-free formula. Numerical simulations for dense residential WLAN scenario reveal total throughput and Jain's fairness index gains of 8.4% and 7.6%, respectively, vs. no DSC (as in WLANs deployed to present).

Real-time pulse rate (PR) monitoring based on photoplethysmography (PPG) has been drawn much attention in recent years. However, PPG signal detected under movement is easily affected by random noises, especially motion artifacts (MA), affecting the accuracy of PR estimation. In this paper, a parallel method structure is proposed, which effectively combines wavelet threshold denoising with recursive least squares (RLS) adaptive filtering to remove interference signals, and uses spectral peak tracking algorithm to estimate real-time PR. Furthermore, we propose a parallel structure RLS adaptive filtering to increase the amplitude of spectral peak associated with PR for PR estimation. This method is evaluated by using the PPG datasets of the 2015 IEEE Signal Processing Cup. Experimental results on the 12 training datasets during subjects' walking or running show that the average absolute error (AAE) is 1.08 beats per minute (BPM) and standard deviation (SD) is 1.45 BPM. In addition, the AAE of PR on the 10 testing datasets during subjects' fast running accompanied with wrist movements can reach 2.90 BPM. Furthermore, the results indicate that the proposed approach keeps high estimation accuracy of PPG signal even with strong MA.

In this paper, we propose the low voltage CMOS current mode reference circuit using self-regulator with adaptive biasing technique. It drastically reduces the line sensitivity (LS) of the output voltage and the power supply voltage dependence of the temperature coefficient (TC). The self-regulator used in the proposed circuit adaptively generates the minimum voltage required the reference core circuit following the PVT (process, voltage and temperature) conditions. It makes possible to improve circuit performances instead of slightly increasing minimum power supply voltage. This proposed circuit has been designed and evaluated by SPICE simulation using TSMC 65nm CMOS process with 3.3V (2.5V over-drive) transistor option. From simulation results, LS is reduced to 0.0065%/V under 0.8V < VDD < 3.0V. TC is 67.6ppm/°C under the condition that the temperature range is from -40°C to 125°C and VDD range is from 0.8V to 3.0V. The power supply rejection ratio (PSRR) is less than -80.4dB when VDD is higher than 0.8V and the noise frequency is 100Hz. According to the simulation results, we could confirm that the performances of the proposed circuit are improved compared with the conventional circuit.

In this paper, we propose an adaptive fusion successive cancellation list decoder (ADF-SCL) for polar codes with single cyclic redundancy check. The proposed ADF-SCL decoder reasonably avoids unnecessary calculations by selecting the successive cancellation (SC) decoder or the adaptive successive cancellation list (AD-SCL) decoder depending on a log-likelihood ratio (LLR) threshold in the decoding process. Simulation results show that compared to the AD-SCL decoder, the proposed decoder can achieve significant reduction of the average complexity in the low signal-to-noise ratio (SNR) region without degradation of the performance. When Lmax=32 and Eb/N0=0.5dB, the average complexity of the proposed decoder is 14.23% lower than that of the AD-SCL decoder.

(k,n)-visual secret sharing scheme ((k,n)-VSSS) is a method to divide a secret image into n images called shares that enable us to restore the original image by only stacking at least k of them without any complicated computations. In this paper, we consider (2,2)-VSSS to share two secret images at the same time only by two shares, and investigate the methods to improve the quality of decoded images. More precisely, we consider (2,2)-VSSS in which the first secret image is decoded by stacking those two shares in the usual way, while the second one is done by stacking those two shares in the way that one of them is used reversibly. Since the shares must have some subpixels that inconsistently correspond to pixels of the secret images, the decoded pixels do not agree with the corresponding pixels of the secret images, which causes serious degradation of the quality of decoded images. To reduce such degradation, we propose several methods to construct shares that utilize 8-neighbor Laplacian filter and halftoning. Then we show that the proposed methods can effectively improve the quality of decoded images. Moreover, we demonstrate that the proposed methods can be naturally extended to (2,2)-VSSS for RGB images.

Let us consider a situation where someone wants to encrypt his/her will on an existing blockchain, e.g. Bitcoin, and allow an encrypted will to be decryptable only if designated members work together. At a first glance, such a property seems to be easily provided by using conventional threshold encryption. However, this idea cannot be straightforwardly implemented since key pairs for an encryption mechanism is additionally required. In this paper, we propose a new threshold encryption scheme in which key pairs for ECDSA that are already used in the Bitcoin protocol can be directly used as they are. Namely, a unique key pair can be simultaneously used for both ECDSA and our threshold encryption scheme without losing security. Furthermore, we implemented our scheme on the Bitcoin regtest network, and show that it is fairly practical. For example, the execution time of the encryption algorithm Enc (resp., the threshold decryption algorithm Dec) is 0.2sec. (resp., 0.3sec.), and the total time is just only 3sec. including all the cryptographic processes and network communications for a typical parameter setting. Also, we discuss several applications of our threshold encryption scheme in detail: Claiming priority of intellectual property, sealed-bid auction, lottery, and coin tossing service.