Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual-Mode Conjoint Patch-Pair for 5G Wideband Patch Antenna Array Application

A dual-mode conjoint patch-pair is presented in this letter. Because the initial frequency ratio between the seventh and fifth modes of the proposed conjoint patch-pair is low, dual-mode characteristic can be easily achieved by further compressing the frequency ratio between these two modes. Through loading two metallized connection vias near the current nulls of the fifth mode, the resonant frequency of the seventh mode can be enormously reduced with little impact on that of the fifth mode, resulting in the realization of frequency-ratio compression. Based on the proposed dual-mode conjoint patch-pair, a broadband 4 × 4 patch antenna arrays is implemented. The measurements of the 4 × 4 array indicate that the achieved −10 dB impedance bandwidth is about 23.7% (23.8–30.2 GHz), which is wide enough to cover the 26 and 28 GHz bands at the same time.
An Empirical Study on Patent Novelty Detection: A Novel Approach Using Machine Learning and Natural Language Processing

Patent, a form of intellectual property often be in the first place when it comes to securing an invention. The legal boundaries created then will become key stages of turning an invention into a commercial product. In recent years, the unprecedented growth of patent applications has induced a great challenge to patent examiners. Novelty detection is one major step considered before and after filing a patent application to assure claimed inventions are new and non-obvious. This itself is considered as a salient stage of prior art search by patent applicants, patent examiners, patent attorneys, patent agent professionals. Management in terms of critical analysis of such a large scale of documents has become a challenge since missing an optimal, effective, and efficient system. To this end, we come up with a novel experimental case study to foster highly recursive and interactive tasks. We developed and investigated more than 50 machine learning models on the considered dataset. The contributions of this work include: (1) outlined and anticipated the importance of novelty detection in the patent domain, (2) develop various baseline models for novelty detection, (3) utilize immense contributions of deep learning towards NLP to improve baseline models, (4) assess the performance of every model by using different word embeddings like word2vec, glove, fasttext, and domain-specific embeddings, (5) a novel application of NBSVM algorithm on our dataset, and considered as exceptionally good of our models. We articulated the fulfillment of models using training and validation curves to prove seemingly negligible overfit or no overfit, in the hope that effective automation in novelty detection helps in driving down the routine prior art search efforts.
Fast Algorithm Based on Parallel Computing for Sample Entropy Calculation

Sample entropy is a widely used method for assessing the irregularity of physiological signals, but it has a high computational complexity, which prevents its application for time-sensitive scenes. To improve the computational performance of sample entropy analysis for the continuous monitoring of clinical data, a fast algorithm based on OpenCL was proposed in this paper. OpenCL is an open standard supported by a majority of graphics processing unit (GPU) and operating systems. Based on this protocol, a fast-parallel algorithm, OpenCLSampEn, was proposed for sample entropy calculation. A series of 24-hour heartbeat data were used to verify the robustness of the algorithm. Experimental results showed that OpenCLSampEn exhibits great accelerating performance. With common parameters, this algorithm can reduce the execution time to 1/75 of the base algorithm when the signal length is larger than 60,000. OpenCLSampEn also exhibits robustness for different embedding dimensions, tolerance thresholds, scales and operating systems. In addition, an R package of the algorithm is provided in GitHub. We proposed a sample entropy fast algorithm based on OpenCL that exhibits significant improvement for the computation performance of sample entropy. The algorithm has broad utility in sample entropy when facing the challenge of future rapid growth in the quantity of continuous clinical and physiological signals.
High Frequency Ripple Injection Signals for the Effective Utilization of Residential EV Storage in Future Power Grids with Rooftop PV System

The electrification of the transport industry is expected to have a major impact on the operation of future distribution grids which includes overloading of components, voltage unbalance and power quality issues. This paper proposes the use of Ripple Injection Load Control Signals for the control of EV charging load, considering a large integration of PV systems in the grid. Currently Ripple Injection signals are widely used by distribution network service providers (DNSPs) around the world for control of loads such as streetlights and hot water systems. Ripple Injection Signals or Audio Frequency Injection Control (AFIC) signals are the applications of a high frequency signal superimposed on to the 50/60 Hz supply. The proposed control will make use of the existing infrastructure and offers a viable solution where a smart grid solution is not available. AFIC signals can be encoded in binary to carry different information which can be used to set the maximum allowable charging rate of future charging stations or activate the Vehicle-to-Grid (V2G) mode when necessary. This provides a method to control the EV load depending on the stochastic nature of a future grid. A multimode energy management algorithm has been proposed depending on the load consumption of a particular substation. A power flow simulation study have been used to demonstrate the efficacy of the proposed method.
On pinning couple-group consensus for cooperative-competitive heterogeneous multi-agent systems with Markov switching topology

The paper investigates the control problem of pinning couple-group consensus for heterogeneous multi-agent systems with the Markov switching topology. A novel protocol of group consensus is designed based on the cooperative-competitive relationship among the agents. By means of the algebraic graph theory, Lyapunov stability theory, matrix theory as well as continuous Markov process analysis, several sufficient conditions and pinning control strategy are presented for the realization of group consensus of the system with connected components topology. Besides, we find that the in-degree of the agents, the control parameters of the system and the pinning gains of the second -order agents are closely related to the achievement of couple-group consensus. Finally, the correctness of the theoretical results is verified by simulation experiments.
A Conductor-Backed Coplanar Waveguide Leaky-Wave Antenna with Metasurface

In this paper, a laterally-bounded conductor-backed coplanar waveguide leaky-wave antenna with metasurface is proposed. The metasurface is made of periodic staggered patches. The propagation characteristics are analyzed with a magnetic field integral equation method. With the analysis, it is found that the structure supports an improper leaky mode and a proper mode which behaves as a surface-wave mode in lower frequency range. The leaky mode contributes to a beam scanning with frequency, whereas the surface-wave mode gives rise to a beam close to endfire. Based on the structure, a leaky-wave antenna is design which exhibits a narrow beam scanning from near broadside to endfire.
Parallel Scheduling of Multiple SDF Graphs Onto Heterogeneous Processors

Parallel scheduling of multiple real-time applications onto heterogeneous processors is needed in the emerging embedded systems such as self-driving cars, smart cameras, and smartphones. Assuming that an embedded application is specified as a synchronous dataflow (SDF) graph or its extension, we propose a novel parallel scheduling methodology based on an evolutionary algorithm where the mapping of tasks onto processors is evolved to optimize a given objective function in an iterative fashion. In each iteration, we use an existing worst-case response time (WCRT) analysis tool to check if all applications satisfy their real-time requirements by translating each SDF graph into a directed acyclic graph (DAG) that is assumed in the WCRT analysis tool. Since the WCRT analysis must be performed in each iteration of evolution, we propose a clustering technique to reduce drastically the analysis time that depends on the number of nodes and their dependency. We formally prove that the proposed clustering technique does not change the estimated WCRT of each application. The effectiveness of the proposed scheduling methodology with the clustering technique is verified with extensive experiments using real-life benchmarks, randomly generated graphs, and the comparison with the existing technique.
A 94 GHz Down-Conversion Mixer for Radar System in 40 nm Digital CMOS Technology

A W-band single-balanced mixer is designed and fabricated in 40 nm digital CMOS technology. The circuit consumes 11.5 mW dc power with the supply voltage of 1 V, while the core circuit consumes only 4.2 mW. The measured peak conversion gain achieves 2.5 dB at 94 GHz, and the input 1- dB compression point (iPidB) is-12 dBm with the IF frequency of 10 GHz. The circuit occupies a core area of only 0.33 mm2.
Optimized Hardware/Software Co-Verification using the UCLID Satisfiability Modulo Theory Solver

Embedded systems are often used in safety-critical applications like cars or airplanes. This makes it crucial to verify their hardware and software under all circumstances. In previous work, we have presented an approach for the formal verification of integrated hardware/software systems using the satisfiability modulo theory solving based verification system UCLID. However, the transformation of integrated hardware/software systems into the input language of the UCLID verification system causes a considerable overhead in the number of symbolic simulation steps necessary for k-inductive verification. In this paper, we overcome this problem by presenting two optimizations for the symbolic simulation of cooperatively scheduled concurrent processes: First, we realize a reduction of redundant states in individual functions that respects all data, control and inter-process dependencies. To capture these dependencies precisely, we present the novel concept of a cooperative dominator tree, which extends the classical concept of a dominator tree to cooperatively scheduled concurrent processes. Second, we present a process parallelization for cooperatively scheduled concurrent processes based on a SystemC dependence graph. In our evaluation based on a set of 21 synthetic case studies, we reach an average reduction of the inductive verification times by 40 %.
A Simultaneous Wireless Power and Uplink Data Transfer System with Ultra-Low Crosstalk between the Power and Data Link

Baes on the same inductive link, a pulse phase modulation method is proposed for uplink data transfer in a wireless power transfer system. It is proved that the crosstalk between the power and data link is small. The proposed system was simulated under 1MHz resonant frequency for power transfer. Simulation results show that the maximum data rate can be 62.25kbps that is half of carrier frequency, and the bit error rate is extremely low. In addition, there is ultra-low crosstalk between the power and data link.
Terahertz Antenna Characterization by the Josephson Effect for Superconducting Terahertz Detectors

Bowtie loaded meander antenna was applied on a high-Tc superconducting Josephson-junction terahertz detector to enhance the coupling efficiency. The antenna performance is evaluated by a new method based on measuring the maximum of the 1st-order Shapiro step under per incident power. The experiment indicates that the outcome by this new method fits the coupling efficiency well. Thus, THz antenna can be characterized in a new way besides the traditional vector network analyzer.
Speed Sensorless Model Predictive Flux Control of Induction Motor Based on Adaptive Gain Sliding Mode Observer

In order to improve the chattering problem in the traditional sliding mode observer, this paper proposes an adaptive gain sliding mode observer which can update the sliding mode gain adaptively according to the system state. This effectively suppresses chattering in the traditional sliding mode observer and improves the estimation accuracy of the flux and speed. This adaptive gain sliding mode observer is then combined with the model predictive flux control so as to improve the practicability of the latter. At the same time, for reducing the influence of speed estimation error on speed sensorless model predictive flux control, this paper improves the rotor flux prediction model in it. The simulation results justify the proposed theory.
A Simple Design Methodology of Compact, Wide OBO Range, Symmetrical Doherty Amplifier with Non-Ideal Effects

A compact design of symmetrical Doherty power amplifier with wide OBO (Output Back-Off) range is presented. This investigation reveals that, the drain parasitic effect of the power devices as well as the inherently reduced peak current ratio (due to class-B/-C operation) can be taken into consideration by the introduction of the explicit circuit model and design formulae. For verification, a 42-dBm, 2-GHz DPA with OBO of 10 dB was designed and fabricated using GaN HEMT devices. Under continuous-wave (CW) excitation, measurement results show excellent Doherty behavior with back-off efficiency (10dB) of 50-57%, saturation efficiency of 70-77% over a fractional bandwidth of 15%.
Gold nanowire synthesis by semi-immersed nanoporous anodic aluminium oxide templates in potassium dicyanoaurate-hexacyanoferrate electrolyte

The synthesis reaction of potassium dicyanoaurate-hexacyanoferrate electrolyte and the pertinence of this electrolyte for gold nanowire synthesis are reported. Gold nanowires were synthesised in anodic aluminium oxide (AAO) nanopores using an improved design of the electrochemical cell. AAO templates with thick gold layers were placed on the surface of the electrolyte, thus the ends of the nanopores were opened, allowing the electrolyte to freely diffuse into the nanopores, extruding gases. The presented procedure simplifies the preparation before nanowire synthesis: AAO templates before synthesis do not need to degas and isolate themselves from contact with the electrolyte by a parafilm or a non-conductive adhesive. A considerably faster nanowire growth in the given conditions in the case of a semi-immersed AAO template when compared with the complete immersion method is reported. For comparison with literature data, gold nanowires were synthesised by the classical electrochemical cell using potassium dicyanoaurate-citrate electrolyte. Long, smooth and high purity nanowires were obtained using semi-immersed templates.
Frequency Reconfigurable SRR-Based Compact Antenna for IoT Application

This paper presents a novel compact frequency reconfigurable antenna based on split-ring resonator (SRR) for Internet of Thing (IoT) applications. Inspired by the conventional planar SRR structure, a novel metallic vertical SRR is proposed and analyzed by equivalent circuit model and field distribution. By replacing the fixed capacitor with a tunable capacitor, a frequency tunable vertical SRR is realized. To validate this method, a frequency reconfigurable SRR-based antenna with a compact size of $0.23 \lambda_{0}$ $\times 0.23 \lambda_{0}$ $\times 0.04 \lambda_{0}$ is implemented. The measured tunable frequency region is greater than the 850 MHz to 950 MHz region, which well covers the 902928 MHz UHF band. Besides, robust broadside patterns are obtained across the tunable region. It features the merits of a compact size, simple design, a wide tunable frequency region and low cost, which shows a promising perspective in the IoT system applications.
Asymmetric Full-Digital Beamforming mmWave Massive MIMO Systems for B5G/6G Wireless Communications

In this talk, a brief review on the newly proposed concept of asymmetric millimeter wave (mmWave) massive multi-input and multi-output (MIMO) system for beyond 5G(B5G) and 6G mobile communications is presented, including the system architecture, requirements for integrated circuits (ICs) design etc., and some research advances.
A Modified Newton Method Formulation for Microwave Imaging

A new variant of Newton type methods has been developed for quantitative microwave imaging. To deal with the ill-posedness of the inverse problems, standard Newton type methods involve a linearization of the so called data equation using the Fréchet derivative with respect to the contrast function. Here, the formulation is expanded to include the object equation, therefore, the formulation seeks to reduce the errors in both the data and the object equations. While this modification does not remove the need to solve forward problem at each step, it nevertheless significantly improves convergence rate and the performance. To assess the efficiency of the proposed technique, numerical simulations with synthetic and experimental data have been carried out. The results demonstrate that the proposed variant outperforms the standard Newton method, and shows comparable performance to the contrast source inversion (CSI) algorithm with fewer iterations.
A fault feature extraction method for reciprocating compressor based on optimized local mean decomposition

Reciprocating compressors are widely used in petroleum and chemical industries, excessive clearance caused by bearing wear is the main form of failure. The fault vibration signal of reciprocating compressor bearing has strong non-stationary characteristics, aiming at the deficiency of adaptive algorithm in smoothing process, this paper presents an optimize local mean decomposition (OLMD) method. In interpolation calculation, interpolation points such as extreme value and eigenvalue are added, the optimized local mean function and envelope estimation function were obtained by using monotone cubic Hermite interpolation method, thus the interpolation fitting accuracy is improved. Through analog signal analysis and field test signal analysis, different LMD methods were used to resolve the large fault signal of large axle bushing clearance of type 2D12 reciprocating compressor, quantitative comparative analysis with the help of relevant evaluation indicators, through the above research, it is proved that the mono-mite interpolation LMD algorithm can be used to accurately extract and diagnoses the bearing clearance fault characteristics of reciprocating compressor.
A Survey on Blockchain for Healthcare Informatics and Applications

Blockchain, cryptographically linked blocks of data, is the key technology behind the infamous cryptocurrency Bitcoin, however, blockchain can serve more use cases than just cryptocurrency. The technology has use cases in any industry that generates and transfers data. In a use case such as cryptocurrency the blockchain is used to manage transactions from peer-to-peer in a way that does not allow for that transaction’s data to be manipulated by one of the involved parties or a third party. This is a valuable process that other industries could leverage. One such industry that could benefit from applying blockchain technology for a multitude of cases is the healthcare industry. Primary care doctors could be connected to a blockchain system that allowed them to access patient data and securely monitor the respective patient, pharmaceutical companies could increase their products validity in the marketplace with individual product tracking, and the insurance industry could trust all the information about a client. All of these are possible use cases for blockchain in the healthcare industry. Currently, the healthcare industry is not leveraging the blockchain at scale. Within this paper we are going to explore the possibilities for blockchain technology and the use cases in the healthcare industry specifically, and how the different industries within the healthcare industry can implement a blockchain system.
Realizing Autonomous and Intelligent Smart Grid Using Multi-Agent Based Control System

This paper addresses remarkable changes that the traditional grid is currently undergoing to withstand the modern- day requirements. It also presents the important characteristics that a modern smart grid should possess. A smart grid is an integration of technological advancements in communication, control, and information in the power grid to make it intelligent and autonomous. The aim of this paper is to address the complexity of optimality and control functions implemented at different layers of the smart grid. This paper has suggestions that a distributed, decentralized control and optimality functions based on a layered architecture will be an appropriate management strategy to realize the smart grid.
An Accurate SAR Imaging Method Based on Total Variation & Nonconvex Regularization

Sparse signal processing is widely used in synthetic aperture radar (SAR) imaging with the development of compressed sensing. As a typical sparse reconstruction method, $L_{1}$ regularization generally causes bias effect. In this paper, we linearly combine the nonconvex penalty and the total variation (TV)-norm penalty as a compound regularizer in the imaging model, which can improve the reconstruction accuracy of targets as well as maintain the continuity of the backscattering coefficient in uniform regions. Simulations and experiments based on real data from Gaofen-3 are performed to verify the effectiveness of the proposed method.
A 0.65μW 70nV/rtHz capacitively-coupled chopper instrumentation amplifier for bio-potential sensing in 28-nm CMOS

A low-power low-noise capacitively-coupled chopper instrumentation amplifier (CCIA) using stacked transconductance amplifiers (OTAs) for bio-potential sensing is presented. It utilizes stacked OTAs as the first stage for noise and power efficiency optimization. A DC servo loop is added to eliminate the DC electrode offset, and pseudo-resistors are designed to realize high-pass filters with ultra-low cut-off frequency without using large capacitors. The CCIA was designed in a 2Snm CMOS process, occupying a chip area of 0.15mm2. It consumes 0.65$\mu$A current under 1-V supply. Simulation results indicate that the input-referred noise is 70nV/rtHz and the noise efficiency factor is 2.7.
A Method of Partitioning Convolutional Layer to Multiple FPGAs

We propose a partition method to improve the performance of convolutional neural networks (CNN) on a multi-FPGA system called Flow-in-Cloud (FiC) and implement the 2nd layer of AlexNet on FiC. As a result, our implementation is slightly more energy-efficient than the CPU and the GPU with an optimized machine learning framework.
A Two-port Compact and High-isolated Microstrip MIMO Antenna

In this paper, a double-layer compact and high-isolated multiple-input multiple-output (MIMO) antenna composed of rectangular microstrip patches is designed on a 36.8 mm $\times 30$ mm substrate. Because one antenna port is located at the zero point of the electric current distribution generated when the other antenna is excited, a high isolation can be achieved. Specifically, when the distance between the centers of the two patches is 0.167 $\lambda_{0}$,($\lambda_{0}$ is the free space wavelength at 6.5 GHz), a very low mutual coupling of -23 dB can be achieved, and the lowest coupling of -39 dB can even be achieved in the -10 dB working bandwidth. The proposed structure and design procedure can provide a valuable idea for the realization of compact and high-isolated MIMO antenna array.