This paper mainly proposes a line segment detection method based on pseudo peak suppression and local Hough transform, which has good noise resistance and can solve the problems of short line segment missing detection, false detection, and oversegmentation. In addition, in response to the phenomenon of uneven development in nuclear emulsion tomographic images, this paper proposes an image preprocessing process that uses the “Difference of Gaussian” method to reduce noise and then uses the standard deviation of the gray value of each pixel to bundle and unify the gray value of each pixel, which can robustly obtain the linear features in these images. The tests on the actual dataset of nuclear emulsion tomographic images and the public YorkUrban dataset show that the proposed method can effectively improve the accuracy of convolutional neural network or vision in transformer-based event classification for alpha-decay events in nuclear emulsion. In particular, the line segment detection method in the proposed method achieves optimal results in both accuracy and processing speed, which also has strong generalization ability in high quality natural images.

This paper proposes an accurate and efficient method to calculate probability distributions of pulse-shaped complex signals. We show that the distribution over the in-phase and quadrature-phase (I/Q) complex plane is obtained by a recursive probability mass function of the accumulator for a pulse-shaping filter. In contrast to existing analytical methods, the proposed method provides complex-plane distributions in addition to instantaneous power distributions. Since digital signal processing generally deals with complex amplitude rather than power, the complex-plane distributions are more useful when considering digital signal processing. In addition, our approach is free from the derivation of signal-dependent functions. This fact results in its easy application to arbitrary constellations and pulse-shaping filters like Monte Carlo simulations. Since the proposed method works without numerical integrals and calculations of transcendental functions, the accuracy degradation caused by floating-point arithmetic is inherently reduced. Even though our method is faster than Monte Carlo simulations, the obtained distributions are more accurate. These features of the proposed method realize a novel framework for evaluating the characteristics of pulse-shaped signals, leading to new modulation, predistortion and peak-to-average power ratio (PAPR) reduction schemes.

The configurable Ring oscillator Physical unclonable function (CRO PUF) is the newly proposed strong PUF based on classic RO PUF, which can generate exponential Challenge-Response Pairs (CRPs) and has good uniqueness and reliability. However, existing proposals have low hardware utilization and vulnerability to modeling attacks. In this paper, we propose a Novel Configurable Dual State (CDS) PUF with lower overhead and higher resistance to modeling attacks. This structure can be flexibly transformed into RO PUF and TERO PUF in the same topology according to the parity of the Hamming Weight (HW) of the challenge, which can achieve 100% utilization of the inverters and improve the efficiency of hardware utilization. A feedback obfuscation mechanism (FOM) is also proposed, which uses the stable count value of the ring oscillator in the PUF as the updated mask to confuse and hide the original challenge, significantly improving the effect of resisting modeling attacks. The proposed FOM-CDS PUF is analyzed by building a mathematical model and finally implemented on Xilinx Artix-7 FPGA, the test results show that the FOM-CDS PUF can effectively resist several popular modeling attack methods and the prediction accuracy is below 60%. Meanwhile it shows that the FOM-CDS PUF has good performance with uniformity, Bit Error Rate at different temperatures, Bit Error Rate at different voltages and uniqueness of 53.68%, 7.91%, 5.64% and 50.33% respectively.

The existing literature focuses on the applications of fast filter bank due to its excellent frequency responses with low complexity. However, the topic is not addressed related to the general transfer function expressions of the corresponding subfilters for a specific channel. To do this, in this paper, general closed-form transfer function expressions for fast filter bank are derived. Firstly, the cascaded structure of fast filter bank is modelled by a binary tree, with which the index of the subfilter at each stage within the channel can be determined. Then the transfer functions for the two outputs of a subfilter are expressed in a unified form. Finally, the general closed-form transfer functions for the channel and its corresponding subfilters are obtained by variables replacement if the prototype lowpass filters for the stages are given. Analytical results and simulations verify the general expressions. With such closed-form expressions lend themselves easily to analysis and direct computation of the transfer functions and the frequency responses without the structure graph.

Mission-critical monitoring services, such as finding criminals with a monitoring camera, require rapid detection of newly updated data, where suppressing delay is desirable. Taking this direction, this paper proposes a network design scheme to minimize this delay for monitoring services that consist of Internet-of-Things (IoT) devices located at terminal endpoints (TEs), databases (DB), and applications (APLs). The proposed scheme determines the allocation of DB and APLs and the selection of the server to which TE belongs. DB and APL are allocated on an optimal server from multiple servers in the network. We formulate the proposed network design scheme as an integer linear programming problem. The delay reduction effect of the proposed scheme is evaluated under two network topologies and a monitoring camera system network. In the two network topologies, the delays of the proposed scheme are 78 and 80 percent, compared to that of the conventional scheme. In the monitoring camera system network, the delay of the proposed scheme is 77 percent compared to that of the conventional scheme. These results indicate that the proposed scheme reduces the delay compared to the conventional scheme where APLs are located near TEs. The computation time of the proposed scheme is acceptable for the design phase before the service is launched. The proposed scheme can contribute to a network design that detects newly added objects quickly in the monitoring services.

This study proposes a new asynchronous Multi-Rate Multiple-Access Differential Chaos Shift Keying (MRMA-DCSK) scheme, ensuring significant data rates for all users. This scheme assigns a unique chaos sequence with a different length to each user. During the first data transmission period, each user transmits the chaos sequence as the reference signal, followed by multiple data bits by sharing the same reference signal in subsequent periods. The proposed scheme affects the bit-error-rate (BER) performance with the number of users, data rate related parameters (L), and length of chaos signals. The simulation results are verified by the derived analysis and show that the proposed scheme achieves higher data rates (from 1/2 to L/L+1) than a conventional scheme while enhancing bit-error-rate (BER) performance.

In the current heterogeneous wireless communication system, the sharp rise in energy consumption and the emergence of new service types pose great challenges to nowadays radio access network selection algorithms which do not take care of these new trends. So the proposed energy efficiency based multi-service heterogeneous access network selection algorithm-ESRS (Energy Saving Radio access network Selection) is intended to reduce the energy consumption caused by the traffic in the mobile network system composed of Base Stations (BSs) and Access Points (APs). This algorithm models the access network selection problem as a Multiple-Attribute Decision-Making (MADM) problem. To solve this problem, lots of methods are combined, including analytic Hierarchy Process (AHP), weighted grey relational analysis (GRA), entropy theory, simple additive weight (SAW), and utility function theory. There are two main steps in this algorithm. At first, the proposed algorithm gets the result of the user QoS of each network by dealing with the related QoS parameters, in which entropy theory and AHP are used to determine the QoS comprehensive weight, and the SAW is used to get each network's QoS. In addition to user QoS, parameters including user throughput, energy consumption utility and cost utility are also calculated in this step. In the second step, the fuzzy theory is used to define the weight of decision attributes, and weighted grey relational analysis (GRA) is used to calculate the network score, which determines the final choice. Because the fuzzy weight has a preference for the low energy consumption, the energy consumption of the traffic will be saved by choosing the network with the least energy consumption as much as possible. The simulation parts compared the performance of ESRS, ABE and MSNS algorithms. The numerical results show that ESRS algorithm can select the appropriate network based on the service demands and network parameters. Besides, it can effectively reduce the system energy consumption and overall cost while still maintaining a high overall QoS value and a high system throughput, when compared with the other two algorithms.

This paper proposes a virtual network function (VNF) placement model considering both availability and probabilistic protection for the service delay to minimize the service deployment cost. Both availability and service delay are key requirements of services; a service provider handles the VNF placement problem with the goal of minimizing the service deployment cost while meeting these and other requirements. The previous works do not consider the delay of each route which the service can take when considering both availability and delay in the VNF placement problem; only the maximum delay was considered. We introduce probabilistic protection for service delay to minimize the service deployment cost with availability. The proposed model considers that the probability that the service delay, which consists of networking delay between hosts and processing delay in each VNF, exceeds its threshold is constrained within a given value; it also considers that the availability is constrained within a given value. We develop a two-stage heuristic algorithm to solve the VNF placement problem; it decides primary VNF placement by solving mixed-integer second-order cone programming in the first stage and backup VNF placement in the second stage. We observe that the proposed model reduces the service deployment cost compared to a baseline that considers the maximum delay by up to 12%, and that it obtains a feasible solution while the baseline does not in some examined situations.

In this article, a new Beamforming Network (BFN) realized in Broadside Coupled Stripline (BCS) is proposed to feed 1×4 and 2×2 arrays antenna at 28 GHZ-Band. The new BFN is composed only of couplers and phase shifters. It doesn't require any crossover compared to the conventional Butler Matrix (BM) which requires two crossovers. The tight coupling and low loss characteristics of the BCS allow a design of a compact and wideband BFN. The new BFN produces the phase differences of (±90°) and (±45°, ±135°) respectively in x- and y-directions. Its integration with a 1×4 linear array antenna reduces the array area by 70% with an improvement of the gain performance compared with the conventional array. The integration with a 2×2 array allows the realization of a full 2-D beam scanning. The proposed concept has been verified experimentally by measuring the fabricated prototypes of the BFN, the 1-D and 2-D patch arrays antennas. The measured 11.5 dBi and 11.3 dBi maximum gains are realized in θ0 = 14° and (θ0, φ0) = (45°,345°) directions respectively for the 1-D and 2-D patch arrays. The physical area of the fabricated BFN is only (0.37λ0×0.3λ0×0.08λ0), while the 1-D array and 2-D array antennas areas without feeding transmission lines are respectively (0.5λ0×2.15λ0×0.08λ0) and (0.9λ0×0.8λ0×0.08λ0).

To cope with ever growing mobile data traffic, we recently proposed a concept of cellular ultra-dense radio access network (RAN). In the cellular ultra-dense RAN, a number of distributed antennas are deployed in the base station (BS) coverage area (cell) and user-clusters are formed to perform small-scale distributed multiuser multi-input multi-output (MU-MIMO) transmission and reception in each user-cluster in parallel using the same frequency resource. We also proposed a decentralized interference coordination (IC) framework to effectively mitigate both intra-cell and inter-cell interferences caused in the cellular ultra-dense RAN. The inter-cell IC adopted in this framework is the fractional frequency reuse (FFR), realized by applying the channel segregation (CS) algorithm, and is called CS-FFR in this paper. CS-FFR divides the available bandwidth into several sub-bands and allocates multiple sub-bands to different cells. In this paper, focusing on the optimization of the CS-FFR, we find by computer simulation the optimum bandwidth division number and the sub-band allocation ratio to maximize the link capacity. We also discuss the convergence speed of CS-FFR in a cellular ultra-dense RAN.

Non-orthogonal multiple access (NOMA), which combines multiple user signals and transmits the combined signal over one channel, can achieve high spectral efficiency for mobile communications. However, combining the multiple signals can lead to degradation of bit error rates (BERs) of NOMA under severe channel conditions. In order to improve the BER performance of NOMA, this paper proposes a new NOMA scheme based on orthogonal space-time block codes (OSTBCs). The proposed scheme transmits several multiplexed signals over their respective orthogonal time-frequency channels, and can gain diversity effects due to the orthogonality of OSTBC. Furthermore, the new scheme can detect the user signals using low-complexity linear detection in contrast with the conventional NOMA. The paper focuses on the Alamouti code, which can be considered the simplest OSTBC, and theoretically analyzes the performance of the linear detection. Computer simulations under the condition of the same bit rate per channel show that the Alamouti code based scheme using two channels is superior to the conventional NOMA using one channel in terms of BER performance. As shown by both the theoretical and simulation analyses, the linear detection for the proposed scheme can maintain the same BER performance as that of the maximum likelihood detection, when the two channels have the same frequency response and do not bring about any diversity effects, which can be regarded as the worst case.

In this paper, we propose a hybrid crystal oscillator which achieves both quick startup and low steady-state power consumption. At startup, a large negative resistance is realized by configuring a Pierce oscillating circuit with a multi-stage inverter amplifier, resulting in high-speed startup. During steady-state oscillation, the oscillator is reconfigured as a class-C complementary Colpitts circuit for low power consumption and low phase noise. Prototype chips were fabricated in 65nm CMOS process technology. With Pierce-type configuration, the measured startup time and startup energy of the oscillator are reduced to 1/11 and 1/5, respectively, compared with the one without Pierce-type configuration. The power consumption during steady oscillation is 30 µW.

This paper presents a divide-by-9 injection-locked frequency divider (ILFD). It can lock onto about 6-GHz input with a locking range of 3.23GHz (58%). The basic concept of the ILFD is based on employing self-gated multiple inputs into the multiple-stage ring oscillator. A wide lock range is also realized by adapting harmonic-control circuits, which can boost specific harmonics generated by mixing. The ILFD was fabricated using a 55-nm deeply depleted channel (DDC) CMOS process. It occupies an area of 0.0210mm2, and consumes a power of 14.4mW.

This paper presents a high-NIR sensitivity SOI-gate lock-in pixel with improved modulation contrast. The proposed pixel has a shallow buried channel and intermediate gates to create both a high lateral electric field and a potential barrier to parasitic light sensitivity. Device simulation results showed that parasitic light sensitivity reduced from 13.7% to 0.13% compared to the previous structure.

This brief presents a side-channel attack (SCA) technique on a high-speed asynchronous successive approximation register (SAR) analog-to-digital converter (ADC). The proposed dual neural network based on multiple noise waveforms separately discloses sign and absolute value information of input signals which are hidden by the differential structure and high-speed asynchronous operation. The target SAR ADC and on-chip noise monitors are designed on a single prototype chip for SCA demonstration. Fabricated in 40 nm, the experimental results show the proposed attack on the asynchronous SAR ADC successfully restores the input data with a competitive accuracy within 300 mV rms error.

The complexity and scale of Networks-on-Chip (NoCs) are growing as more processing elements and memory devices are implemented on chips. However, under strict power budgets, it is also critical to lower the power consumption of NoCs for the sake of energy efficiency. In this paper, we therefore present three novel input unit designs for on-chip routers attempting to shrink their power consumption while still conserving the network performance. The key idea behind our designs is to organize buffers in the input units with characteristics of the network traffic in mind; as in our observations, only a small portion of the network traffic are long packets (composed of multiple flits), which means, it is fair to implement hybrid, asymmetric and reconfigurable buffers so that they are mainly targeting at short packets (only having a single flit), hence the smaller power consumption and area overhead. Evaluations show that our hybrid, asymmetric and reconfigurable input unit designs can achieve an average reduction of energy consumption per flit by 45%, 52.3% and 56.2% under 93.6% (for hybrid designs) and 66.3% (for asymmetric and reconfigurable designs) of the original router area, respectively. Meanwhile, we only observe minor degradation in network latency (ranging from 18.4% to 1.5%, on average) with our proposals.

In this research, we investigated the threshold voltage (VTH) control by partial polarization of metal-ferroelectric-semiconductor field-effect transistors (MFSFETs) with 5 nm-thick nondoped HfO2 gate insulator utilizing Kr-plasma sputtering for Pt gate electrode deposition. The remnant polarization (2Pr) of 7.2 μC/cm2 was realized by Kr-plasma sputtering for Pt gate electrode deposition. The memory window (MW) of 0.58 V was realized by the pulse amplitude and width of -5/5 V, 100 ms. Furthermore, the VTH of MFSFET was controllable by program/erase (P/E) input pulse even with the pulse width below 100 ns which may be caused by the reduction of leakage current with decreasing plasma damage.

Reducing on-chip microwave crosstalk is crucial for semiconductor spin qubit integration. Toward crosstalk reduction and qubit integration, we investigate on-chip microwave crosstalk for gate electrode pad designs with (i) etched trenches between contact pads or (ii) contact pads with reduced sizes. We conclude that the design with feature (ii) is advantageous for high-density integration of semiconductor qubits with small crosstalk (below -25 dB at 6 GHz), favoring the introduction of flip-chip bonding.

Human motion prediction has always been an interesting research topic in computer vision and robotics. It means forecasting human movements in the future conditioning on historical 3-dimensional human skeleton sequences. Existing predicting algorithms usually rely on extensive annotated or non-annotated motion capture data and are non-adaptive. This paper addresses the problem of few-frame human motion prediction, in the spirit of the recent progress on manifold learning. More precisely, our approach is based on the insight that achieving an accurate prediction relies on a sufficiently linear expression in the latent space from a few training data in observation space. To accomplish this, we propose Regressive Gaussian Process Latent Variable Model (RGPLVM) that introduces a novel regressive kernel function for the model training. By doing so, our model produces a linear mapping from the training data space to the latent space, while effectively transforming the prediction of human motion in physical space to the linear regression analysis in the latent space equivalent. The comparison with two learning motion prediction approaches (the state-of-the-art meta learning and the classical LSTM-3LR) demonstrate that our GPLVM significantly improves the prediction performance on various of actions in the small-sample size regime.

Due to the global outbreak of coronaviruses, people are increasingly wearing masks even when photographed. As a result, photos uploaded to web pages and social networking services with the lower half of the face hidden are less likely to convey the attractiveness of the photographed persons. In this study, we propose a method to complete facial mask regions using StyleGAN2, a type of Generative Adversarial Networks (GAN). In the proposed method, a reference image of the same person without a mask is prepared separately from a target image of the person wearing a mask. After the mask region in the target image is temporarily inpainted, the face orientation and contour of the person in the reference image are changed to match those of the target image using StyleGAN2. The changed image is then composited into the mask region while correcting the color tone to produce a mask-free image while preserving the person's features.