Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of Jamming in DSSS Systems Using FRESH Filters

This paper addresses the problem of blind jamming detection in direct-sequence spread-spectrum (DSSS) systems. The theory of cyclic wiener filter is used as the theoretical basis of the proposed jamming detection technique, named the time varying whitener (TVW)-based detector. The TVW, which is based on the different cyclostationarity properties of the desired signal and the jamming signal respectively, is realized by the frequency-domain adaptive FRESH filter. The FRESH filter, which uses white noise as desired signal, applies the subset of cycle frequencies of the DSSS signal to be the frequency shifts, and is able to whiten the DSSS signal and fix the tap weights of the TVW. Thus, the TVW with fixed tap weights can only whiten the DSSS signal, while pass through the unknown jamming signal. And then we analyze the statistic distribution of the TVW output in order to obtain the detection threshold adaptively. Finally, a jamming decision is made by operating the energy detection for a given false alarm rate and threshold. The numerical results show that receiving structures based on the proposed cyclostationarity-based jamming detection shows robustness to background noise, and outperforms the time invariant whitener, which fails when trying to detect jamming signal.
Single-Layer Low-Profile Patch Antennas with Improved CP Performance by Using Multiresonant Modes (Invited Paper)

In this letter, a novel design concept for circularly-polarized (CP) performance improvement of a single microstrip patch antenna (MPA) is studied and summarized via multiresonant modes. By investigating the internal E-field, it demonstrates that the direction of the equivalent magnetic currents (EMCs) at the patch edge are significantly changed under different feeding positions. Hence, two types of CP antennas are simulated and designed. Firstly, by reallocating three orthogonal modes in proximity to each other without sequential rotation, an extremely small frequency-ratio of about 1.04 is generated for the dual-polarized CP MPA. Secondly, by reallocating three orthogonal modes closely to each other with sequential rotation, the dual working bands of the MPA with same CP-polarization are merged to extend its CP bandwidth. In final, these MPAs are fabricated and measured. The measured results verify these predicted performances and the antenna keeps several advantages, i.e., low-profile, single-layer, single-element, wide AR-bandwidth, small frequency-ratio, and high efficiency.
A 44-52 GHz Reflection-type Phase Shifter with 1.4° Phase Resolution in 28nm CMOS Process

This paper presents a 44-52 GHz passive reflection-type phase shifter with high phase resolution in 28nm CMOS process. The circuit consists of a hybrid coupler and two $\pi$-network loads. In the $\pi$-network loads, variable capacitance is realized by the capacitor array. Compared with the previously reported 6-bit phase shifter with 360° phase shift range, the proposed phase shifter achieves 1.4° phase shift accuracy. Although the proposed phase shift range is 96°, it can be extended to an 8-bit 360° phase shifter by cascading a coarse-tuning phase switcher. Across the full operating band, the post-layout simulated RMS phase error is 0.15° and the post-layout simulated RMS gain error is 0.34 dB, and the chip core area is 300 $\mu \mathrm{m}\times 270\mu \mathrm{m}. $
Computationally Simple Nonlinear MPC Algorithm for Vehicle Obstacle Avoidance With Minimization of Fuel Utilization

This work is concerned with Model Predictive Control (MPC) algorithm for vehicle obstacle avoidance. The second objective of the algorithm is on-line minimization of fuel utilization. At first, the rudimentary nonlinear MPC optimization problem is formulated. Next, the constraints related to the predicted process state variables are formulated as soft ones to guarantee computational safety. Furthermore, in order to obtain a computationally simple procedure, the process dynamics and the fuel utilization model are linearized on-line and used for prediction in MPC. It leads to a quadratic programming MPC task, the necessity of nonlinear optimization performed in real-time is eliminated. In order to stress advantages of the discussed computationally uncomplicated MPC method it is compared with the basic scheme with on-line nonlinear optimization in terms of control quality and computational time. Additionally, effectiveness of the MPC algorithm is discussed in presence of modeling errors and measurement noise. Finally, additional constraints imposed on the rate of change of the manipulated variables are considered.
EMG Based Gesture Recognition Using Noise Removal

We propose a feature calibration method for the electromyography (EMG) based gesture recognition to be robust to noise. The proposed method is to subtract the feature of noise calculated in resting period from the signal feature. For the performance evaluation, we compare the recognition accuracy of the feature calibration applied with that of the feature calibration not applied. As noise level increases, the result of the proposed feature calibration method applied shows clear improvement in accuracy. When SNR is 0dB, the recognition result of the proposed method applied shows about 20% improvement in average accuracy compared to that of the proposed method not applied.
Lossy Beam Generation of Circular Arrays

This work examines the characteristic modes and measurement of various circularly distributed array topologies in which element radiators are used independently to deliver both sum and difference beams under lossy conditions. An associated moment generating function is derived, such that analytical patterns use even-odd symmetries for sum difference beam behavior. This approach generalizes the Fourier probabilistic methods by using the Laplace transform to analyze statistical averages catering to the degenerating effects of pattern behavior that is influenced by the environment.
High Power 400W Symmetric Doherty with Extended Back-off Efficiency Range for 5G Cellular Infrastructure Applications

This paper demonstrates, for the first time, a high-power 400W symmetric Doherty power amplifier (DPA) with extended efficiency range utilizing a complex combining load targeting 5G cellular infrastructure applications. A practical, cost-effective implementation of a high-power DPA architecture suited for high volume manufacturing is reported, providing potential benefits over a traditional asymmetric DPA. A prototype implementation is built using NXP’s single-packaged device containing two 24.6mm gate width 220 W Gallium Nitride on silicon carbide pre-matched die. The prototype achieves a peak power of 56dBm, linearized efficiency of 59% and ACLR of -54dBc at 8dB OBO with a 2-carrier 20MHz 7dB PAPR LTE excitation with an instantaneous signal bandwidth of 60MHz in LTE band 3 (1.805-1.88 GHz).
Advanced Modelling Techniques Enabling E-Band Power Amplifier Design for 5G Backhauling

In this paper, a nonlinear transistor model extraction technique oriented to E-band power amplifier design is discussed. Two models are extracted, based on analytical functions and look-up-tables, respectively. The latter was used for the design of two power amplifiers (PAs) covering the bandwidths 71–76 and 81–86 GHz. The models have been fully validated by comparing their predictions with measurements carried out on the realized MMIC PAs.
An electronic scanning leaky-wave antenna based on the half-mode corrugated integrated waveguide

An electronic scanning leaky-wave antenna based on the half-mode corrugated integrated waveguide is proposed in this paper. Electronic scanning is achieved by the employment of varactor diodes. The scanning angle ranges from −24°to +38°continuously at 5.8 GHz, and the gain is greater than 6 dB at all scanning angles. Meanwhile, the circular polarization is achieved by two symmetrical bent slots and the axial ratio is lower than 6 dB. Because of the advantage of half-mode corrugated integrated waveguide, this kind of antenna is compact and beneficial to be applied in some devices without via hole.
The labelling algorithm for unicyclic graphs with a condition at distance 2

The distance label is a label model derived from the frequency allocation problem. This article mainly studies the L(2,1)-label in the label. L(2,1)-label refers to the use of non-negative integers to label the vertices of the graph G. The goal is to make the label values of adjacent vertices differ by at least 2 and the label values of vertices with a distance of 2 are different. This paper proposes a recursive backtracking greedy algorithm based on Griggs’ conjecture, and also gives the algorithm’s execution steps, analysis and test results. The experimental results show that for a unicyclic graph containing only one maximum degree point, its L(2,1)-label number is $\Delta$+1. In addition, the L(2,1)-label number characteristics of the unicyclic graph are given and expressed in the form of forbidden subgraphs.
Cocrystal and Salts of 2,2′,6,6′-Tetracarboxybiphenyl with Bis(pyridyl) Derivatives: Eight-fold Interpenetrated Diamondoid and Layered Networks

The cocrystallization reactions of 2,2′,6,6′-tetracarboxybiphenyl with bis(4-pyridyl) ethylene and 4,4′-bipyridine were studied, and it was found that molecular symmetry (pseudo-S4) has been transferred into supramolecular symmetry to form an 8-fold interpenetrated diamondoid network only in the case of cocrystals but not in the case of salts.
Finite-time quasi-synchronization time-delay multilayer networks

The paper studies finite-time quasi-synchronization (FTQS) for time-delay multilayer networks (MLNs), the FTQS of MLNs is achieved by applying delay controller. Compared with some existing results, the optimal combination relevance between exponential power of FT controller and initial value of system is gained when the QS time is minimal. In particular, there is no necessary correlation between the FT convergence of the system and the range of QS error. Lastly, the validity of the advanced method is verified by FTQS simulation of MLNs with financial oscillators.
Frontend module for 5G millimeter Wave application made by ceramic multilayer substrate

Antenna of user equipment needs to support broad band and have dual polarization property. We developed module which had broadband and dual polarization antenna using an LTCC technology in a 28GHz band in this study. The designed array antenna is a combination of 4 V&H polarization antennas. These antenna elements were miniaturized. V&H combined element could arraign a half of wavelength at 28GHz (5.3mm). Size of antenna array could be small (5 x 20 x t1.5mm). From the result of S11 return loss, it was confirmed that combined antenna had wider bandwidth (over 6GHz from 24GHz to 30GHz, n257 and n258 band on each polarization). The frontend module was developed based on the above antenna substrate. That module includes a divider and RFIC which has the functions of phase shifter, PA and LNA. From the result of beam shifting evaluation, it was confirmed that the beam angle was able to control between +/-30 degree. Furthermore, we also confirmed that the developed antenna module can be used to stream video data from module to module.
Quantitative Scanning Microwave Microscopy of Few-layer Platinum Diselenide

PtSe2 is unique among all 2D materials by having simultaneously sizable bandgap, high carrier mobility, and air stability. Moreover, PtSe2 undergoes a semiconductor-semimetal transition when its thickness increases beyond a few atomic layers, which facilitates low-resistance contact. However, there has been a controversy in how abruptly PtSe2 transitions from a semiconductor to a semimetal. In this work, scanning microwave microscopy was used to quantify the conductivity in two PtSe2 layers 1.5-nm-thick and 3-nm-thick, respectively. The resulted conductivity in 3-nm-thick PtSe2 of (1.7 ± 0.2) × 104 S/m is consistent with that reported for bulk PtSe2, confirming that 3-nm-thick PtSe2 is a semimetal. However, although the conductivity in 1.5-nm-thick PtSe2 appears much lower, it is too close to that of TiN to be reliably quantified. To characterize low conductivity in few-layer semiconductors, the signal-to-noise ratio of scanning microwave microscopy needs to be further improved.
Transferability of Privacy-related Behaviours to Shared Smart Home Assistant Devices

Smart assistant devices (such as Amazon Echo or Google Home) have notable differences to more conventional consumer computing devices. They can be used through voice control as well as physical interaction, and are often positioned as a shared device within a home environment. We conduct an exploratory online survey with 97 UK-based users of smart assistant devices, to examine the differences users perceive between smart assistants and more familiar devices (such as smartphones and computers), in terms of shared use dynamics, privacy-related behaviours, and privacy concerns. The survey explores typical usage, setup practices, perceived ease of use and control, privacy concerns for multiple users, shared usage of existing devices, and smart assistant privacy control usage. Approximately half of participants were unsure of where to access privacy settings on their smart home assistants; basic device controls and informal privacy controls saw general use. Those who had used privacy controls with previous devices used at least one smart assistant privacy control. Results have implications for supporting transferable privacy behaviours from computing devices to smart home devices, and improving privacy-related design for smart assistants.
Prediction of Forest Fire Risk to Trigger IoTs Reconfiguration Action

Nowadays, the ever-increasing demand for IoT nodes for adapting to changing environment conditions and application requirements rapidly raising the need of reconfiguring already existing IoTs nodes. Forest fires is one of the main causes of environmental degradation and its detection and prediction is a challenge, a case study of predicting IoTs reconfiguration. Each prediction algorithm has its own advantages and disadvantages, which lead to different predictive results for each specific IoT application reconfiguration behavior. It is important to determine which set of metrics are effective for predicting. The objective of this work is to choose the most suitable prediction algorithms for detection of Forest Fire Risk for trigger IoTs reconfiguration actions. In this work, a comparative study between various prediction algorithms is carried out. The performance metric is based on the accuracy, precision, recall, and the training time. The experimental results show that Feedforward Neural Network is the most accurate that gives a good prediction accuracy.
Hepatocellular Carcinoma Patient’s Survival Prediction Using Oversampling and Machine Learning Techniques

Hepatocellular Carcinoma (HCC) is the most crucial liver neoplasm and the subsequent driving reason for malignant growth demise worldwide. The survival rates for patients determined to have HCC and to distinguish prognostic components, which will help in picking ideal treatment for singular patients. Throughout the long term, and for the specific instance of HCC, some investigation contemplates have been creating procedures for helping physicians, employing machine learning methods to anticipate the survival rate after treatment. In this paper, we have applied machine learning calculations to anticipate the 1-year endurance of patients and discover the feature importance. We have employed an oversampling strategy named SMOTE, for adjusting the dataset to improve the model performance. We have shown the difference in model performance before and after using SMOTE. Our proposed system with the XGBoost classifier performed better with 87% accuracy in comparison with other existing models.
Human-Interactive Mapping Method for Indoor Magnetic Based on Low-Cost MARG Sensors

Indoor magnetic map (IMM) based on magnetic field fluctuations can be used in map assisted indoor positioning and navigation, etc. However, many IMM mapping solutions are time-consuming, labor-intensive, and high-cost, which limit the development and application of IMM. To solve the issues of accuracy, efficiency, and cost of IMM mapping collaboratively, we absorbed the idea of simultaneous localization and mapping (SLAM) method, and proposed a human-interactive mapping method of IMM based on the low-cost magnetometer, accelerometer, and rate gyro, i.e., MARG sensors. First, we defined IMM as the structured data set with a series of position stamps and magnetic field fluctuations. Then, we proposed the concept of general sensory calibration source (GSCS) and related metrics for human-interactive activities which provide virtual information to eliminate the time-accumulated error of position stamps and assist in obtaining stable magnetic field fluctuations. Finally, we conduct a series of experiments to verify the performance of the proposed method. The test results show that the proposed method can not only meet the requirements of mapping accuracy but also significantly improve mapping efficiency and reduce mapping cost, which is superior to other state-of-the-art algorithms. Specifically, the significant results are as follows: the mapping accuracy is about 0.31 m, and the mapping efficiency is 1800 m$^2$ per hour, and the cost of the main module of IMM mapping does not exceed U.S. $10.
A Hybrid Microwave-Optical Applicator for Local Muscle Warming and Monitoring

Local warming of human tissue causes vasodilation and therefore blood volume to increase. Such thermal blood volume response allows the assessment of microcirculation in tissue, providing clinically important information. The deep warming is provided by a novel microwave applicator, which has a annular-ring microstrip patch operating at 2450 MHz with a superstrate interface layer to improve the coupling of electromagnetic (EM) waves into the skin. The design is based on computer simulations of specific absorption rate (SAR) and thermal distribution of the EM waves in a biological medium. The simulation results show that the applicator can elevate the muscle temperature by 3 to $4^{\circ}\mathrm{C}$. The thermal response is measured by an integrated optical probe which measures tissue oxygenation changes in deep tissue using the near infrared spectroscopy technique.
Optical Receiver Front-end for Active Optical Cable in 180 nm CMOS

This paper introduces a 4-channel optical receiver front-end in 180 nm CMOS technology for active optical cable application. The receiver is composed of HDMI 2.0 configuration, occupying area of $2.52\ \mathrm{mm}^{2}$. Regulated-cascode transimpedance amplifier is used in the chip. Shared inductor and capacitive feedback techniques are applied in limiting amplifiers to enhance bandwidth. The receivers consumes power of 54 mW at the data rate of 6 Gb/s with the energy efficiency of 3 pJ/bit/channel.
Evaluation of Harmonic Distortion in the CIGRE Residential Low Voltage Network with Photovoltaic Penetration

This document presents an evaluation of harmonic distortion of the European CIGRE residential low voltage bench-mark network when considering distributed generation analysis. With the purpose of analyzing the photovoltaic penetration effects in a low voltage distribution network related with harmonic distortion, the network was modified changing the energy distributed resources by photovoltaic systems. Five scenarios of photovoltaic penetration are proposed, in all of them, the position of the photovoltaic systems is conserved, and the power of the systems varies in 1%, 5%, 15%, 30% and 50% with respect to the MV/LV transformer rating. The network was simulated with OpenDSS in combination with Python, in order to dynamically evaluate the harmonic distortion.
An Omnidirectional Antenna with Wide Bandwidth and High Gain for WiFi-5 and WiFi-6 Applications

This paper proposes an omni-directional printed antenna with broadband and high gain for WiFi-5 and WiFi-6 applications. In order to achieve stable omnidirectional gain, both of the ground plane and the radiating elements are arranged on the same side of the printed circuit board (PCB) substrate. Over the whole working frequency band, selecting the left end of the PCB board to supply power helps to achieve good radiation pattern in the H-plane. Simulated results exhibit that a relative bandwidth of 8% (5.15-7.125 GHz) is obtained. The corresponding gain ranges from 5.14 to 7.74 dBi in the operating band, which is about 4 dBi larger than that of the conventional omnidirectional antennas.
Contactless Multi-Sensor Solution for E-Treatment of Musculoskeletal Disorders

The treatment of Musculoskeletal Disorders requires physical exercises to be executed regularly and correctly. This paper presents a technological solution to support this therapy consisting of on-body sensors and a supporting platform that captures and forwards the data automatically. We implemented wireless communication and charging in the sensor module. The wireless functionality enhances patient’s comfort during movements and allows for easy and hygienic maintenance. Validation in a real-life case has demonstrated the suitability of the solution to monitor treatment remotely. Furthermore, it was shown to be easy-to-use by non-technical experts. The sensor has an autonomy of 20 hours, which contributes to its user friendliness. We explain and share the designs that have been realized with low cost IoT technologies including Micro-Electro-Mechanical System sensors, low power wireless connectivity and microcontrollers. The contactless multi-sensor solution can be broadly adopted both in medical cabinets and for remote treatment. The latter is of specific interest when the patient is far from the therapist, encounters mobility problems, or when safe distancing is needed.
Detection of Carbapenems Resistant K-mer Sequences in Bacteria of Critical Priority by the World Health Organization (Pseudomonas aeruginosa and Acinetobacter baumannii)

Antimicrobial resistance (AMR) (or drug resistance) is a natural phenomenon where microorganisms change their molecular, physical, or chemical structures to resist the drugs created by infections. The World Health Organization (WHO) had released for the first time a list of Multidrug-Resistant Bacteria (MRB) that pose the greatest threat to human health, and for which new antibiotics are desperately needed. Acinetobacter baumannii and Pseudomonas aeruginosa resistant to carbapenems are part of the Gramnegative group non-fermenting bacilli with critical priority according to the WHO. For this, the research final purpose was to create and train a bioinformatic study capable of finding critical k-mers that could differentiate those strains of P. aeruginosa and A. baumannii resistant to carbapenems. At the end, two sets of k-mers for both pathogens were obtained. Three Machine Learning algorithms were performed to prove the use of these k-mers in antimicrobial prediction Random Forest, Adaboost, and Xgboost. For Pseudomonas aeruginosa, an accuracy of 0.8 was obtained using Random Forest, an accuracy of 0.92 using Adaboost, and an accuracy of 0.84 when using Xgboost. In the case of Acinetobacter baumannii, an accuracy of 0.98 was obtained when using Random Forest and an accuracy of 0.99 when using Adaboost or Xgboost. To investigate the sequences of the k-mers obtained, the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool BLAST was used. Twenty sequences built with the k-mers were investigated for each bacteria. For A. baumannii, 18 out of 20 sequences represented a key sequence in antibiotic resistance. In the case of P. aeruginosa, 16 out of 20 sequences represented a key sequence. Further investigation over these sequences can be applied in creating new directed antibiotics or detecting easily resistant strains of Pseudomona aeruginosa or Acinetobacter baumannii resistant to carbapenems.