Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Assessment of an Orthomode Transducer Under High Power Handling and Harsh Temperature Exposure

In the context of assessing radio frequency devices under harsh operating conditions, we present this study as a basic part of qualification package of critical communication systems. The study considers a ka–band, (29 - 31) GHz, circularly polarized septum-based orthomode transducer (OMT). The tough conditions embrace both high power handling and extreme environmental circumstances. The thermal expansion causes a clear deviation on the OMT parameters including common port axial ratio and impedance matching.
Metamaterial-Based MM-Wave Phased Array for Broadband Cellular Networks

A new broadband phased array antenna with wide-scan and high-gain beam-scanning are desirable to meet the requirements of future cellular networks. This paper discusses the characteristics of a new beam-steerable array design having broad bandwidth for 5G communications. The discussion is focused on smartphones, due to their small size and complexity. The design procedure is straightforward and accomplished on a mainboard of future smart handheld devices. The introduced phased array design involves eight metamaterial-based dipole resonators with a 1×8 linear form. The resonators have small sizes with microstripline feedings. For -10 dB, the design represents 28-38 GHz covering several bands in the 5G spectra.
Long Range Chipless RFID System Based on FMCW RADAR and Dielectric Resonators

This paper presents novel design approach for a long reading range chipless RFID system based on FMCW RADAR and dielectric resonators. In this paradigm, the high sensitivity of FMCW RDAR is exploited to enlarge the detection range. Furthermore, a novel encoding approach is proposed to enable the ID detection in the FMCW baseband beat signal. This encoding approach uses frequency domain to characterize the dielectric resonator and performs group delay rather than scalar measurement. Consequently, the information bits are deferentially encoded in the group delay frequency signature of the dielectric resonator. Hence, a system model of the reader interrogation waveform and the dielectric resonator backscattered signals is developed. The FMCW system simulation is carried out to prove the novel group delay encoding approach. The theoretical reading range is calculated to be $\approx$ 20m with 0dBm transmit power and DR RCS of −25dBsm. The coverage of the proposed chipless RFID system is exceeding the well known chipped passive RFID system with lower transmit power and tag RCS. Lastly, the unique group delay spectral signature of the dielectric resonator would enable the clutter mitigation to great extent.
Using Wavelet Packet Trees to Efficiently Estimate Clustered High Order Harmonics

This study deals with the capabilities of a 7 level Wavelet Packet tree (WPT) relative to fast estimation of joint harmonic contributions of components oscillating with frequencies higher than 2kHz. The analyzed signal from the tree’s root node spans across 7 periods such as to yield results unaffected by the edge effect. Clusters connecting nodes from the 7-th level and associated harmonics are deduced, along with flags to be used such as to obtain subtrees dedicated to each cluster for runtime savings. Tests on artificial signals with rich harmonic content and respectively with harmonics from a single cluster were made. The analysis of performance metrics revealed that 6 clusters can be used for the estimation of contributions of harmonic exceeding 2kHz, up to the limit of 4.25 kHz, while considering a threshold of at most 2.5% for the energy of individual odd harmonics to appear outside their associated cluster of nodes. An example of algorithm utilization for the output voltage of an auxiliary services converter used on a Romanian locomotive is provided.
AxASRE: A Novel Approach to Approximate Adder Synthesis Results Estimation.

Thanks to the high energy efficiency achieved by approximate circuits, the exploration of approximate solutions for a wide of applications is the focus of academic and industrial research. However, defining the most appropriate approximation considering the power consumption and accuracy trade-off can be exhaustive. This paper proposes a novel approach to estimate the synthesis results for approximate adders (AxA) with different bit-width and approximation levels based on a database and simple mathematical operations to reduce the synthesis process complexity during an approximate circuit development. We implement the proposed approach to estimate the synthesis results for the Copy, Error-Tolerant Adder I (ETA-I), Lower-part-or (LOA), and Truncation (Trunc) AxAs. Comparing our estimation with real synthesis results obtained by an industrial synthesis tool, we prove the approach’s efficiency by presenting an average error on the estimated parameters (area, power and delay) less than 10% in the worst case. In addition, our approach reduces by more than 25 times the number of synthesis runs when estimating the synthesis results for all circuits in the bit width range of 2 to 64 with all possible approximation levels.
Electroencephalography-Based Brain-Computer Interfaces for Robots Control Using Deep Learning

In recent years, there has been considerable progress in the invention of brain-controlled mobile robots and robotic arms. The development of electroencephalography (EEG) technology has made it possible to operate external equipment directly from the brain. A brain-computer interface (BCI) enables the communication between the brain and an external device. It is used in many applications such as security, education, neuro-marketing, entertainment, and medical applications. In this paper, we present an approach to supply the control of a robot based on the identification of given commands. We control the direction of the robot according to the attention level. We also use eye blinking as an alternative way to control the robot’s direction in the left and right directions. We implemented the full pipeline to achieve this goal and verify the correctness of the desired behavior. We start by acquiring the signal, processing, classification, and action execution. For the signal classification step, we apply a deep learning 1D convolutional neural network, which outperformed several classical machine-learning models. The outcomes show that the 1D convolutional neural network is the most proper deep learning method to detect the level of attention with a testing accuracy of 95% to control our robot’s motor direction. In this research, a 1D-convolutional neural network technique based on a deep learning model for attention level, eye blinking to classify the brain wave, and the method to control the robot will be presented.
Design with low complexity fine-grained Dual Core Lock-Step (DCLS) RISC-V processors

Embedded systems in critical domains require both hard real-time and reliable execution. Real-time execution requires bounds in the worst-case execution time, while reliable execution is under threat, as systems are becoming more and more sensitive to transient faults. Thus, systems should be enhanced with fault-tolerant mechanisms with bounded error detection and correction overhead. Such mechanisms are typically based on redundancy at different granularity levels. Coarse-grained granularity has low comparison overhead, but may jeopardize timing guarantees. Fine-grained granularity immediately detects and corrects the error, but its implementation has increased design complexity. To mitigate this design complexity, we leverage high-level specification languages to design intrusive fine-grained lockstep processors based on the use of shadow registers and rollback, with bounded error detection and correction time, being appropriate for critical systems.
Multicolor CRISPR labeling of chromosomal loci in human cells

Significance The detection of specific genes in fixed cells was first accomplished in 1969 by Gall and Pardue. The development of analogous methods applicable to living cells is now at hand. At the forefront of this advance (2013–2014), we and other investigators have used transcription activator-like effectors (TALEs) conjugated with fluorescent proteins to tag genomic loci in live cells. More recently, the CRISPR/Cas9 system has provided a more flexible approach to targeting specific loci. In this paper, we describe the labeling of human genomic loci in live cells with three orthogonal CRISPR/Cas9 components, allowing multicolor detection of genomic loci with high spatial resolution, which provides an avenue for barcoding elements of the human genome in the living state. The intranuclear location of genomic loci and the dynamics of these loci are important parameters for understanding the spatial and temporal regulation of gene expression. Recently it has proven possible to visualize endogenous genomic loci in live cells by the use of transcription activator-like effectors (TALEs), as well as modified versions of the bacterial immunity clustered regularly interspersed short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system. Here we report the design of multicolor versions of CRISPR using catalytically inactive Cas9 endonuclease (dCas9) from three bacterial orthologs. Each pair of dCas9-fluorescent proteins and cognate single-guide RNAs (sgRNAs) efficiently labeled several target loci in live human cells. Using pairs of differently colored dCas9-sgRNAs, it was possible to determine the intranuclear distance between loci on different chromosomes. In addition, the fluorescence spatial resolution between two loci on the same chromosome could be determined and related to the linear distance between them on the chromosome’s physical map, thereby permitting assessment of the DNA compaction of such regions in a live cell.
Design Space Exploration of Approximate Computing Techniques with a Reinforcement Learning Approach

Approximate Computing (AxC) techniques have become increasingly popular in trading off accuracy for performance gains in various applications. Selecting the best AxC techniques for a given application is challenging. Among proposed approaches for exploring the design space, Machine Learning approaches such as Reinforcement Learning (RL) show promising results. In this paper, we proposed an RL-based multi-objective Design Space Exploration strategy to find the approximate versions of the application that balance accuracy degradation and power and computation time reduction. Our experimental results show a good trade-off between accuracy degradation and decreased power and computation time for some benchmarks.
A Hybrid Architecture Based on Conformer and CRN Parallelism for Regulated Speech Quality Measurement Model

Assessing the quality of speeches between pilots and air traffic controllers(ATC) is a crucial challenge for intelligent and industrialized civil aviation. Assessing the voice quality between air traffic controllers and pilots during communication requires both clean speech without noise and speech with noise introduced. However, clean speech without noise cannot be obtained. To tackle this issue, we propose a non-intrusive pilots and ATC speech quality evaluation algorithm that operates in parallel with a conformer network and convolutional recurrent network (CRN). To more realistically characterize the key factors impacting speech quality in pilots and ATC calls, our algorithm initially employs Meer cepstrum coefficients (MFCC) as the characterization method for speech signals. Our algorithm constructs a convolutional neural network to extract features from the MFCC, and then utilizes a conformer network and a CRN network to simultaneously extract the relevant features of speech quality from the pilots and ATC speech, using global attention adaptation and inter-frame time dependence methods, respectively. Finally, the features are mapped to objective scores using attention pooling methods. Experimental results based on an open-source database indicate that our proposed algorithm correlates exceptionally well with the mean opinion score (MOS). By utilizing this algorithm to measure ATC speech, we can effectively distinguish pilots and ATC speech data with different speech quality. Overall, our nonintrusive ATC speech quality evaluation algorithm provides a promising solution to the challenges facing intelligent and industrialized civil aviation.
Bill Gross' Alpha: The King Versus the Oracle

We set out to investigate whether ''Bond King" Bill Gross demonstrated alpha (excess average return after adjusting for market exposures) over his career, in the spirit of earlier papers asking the same question of ''Oracle of Omaha," Warren Buffett. The journey turned out to be more interesting than the destination. We do find, contrary to previous research, that Gross demonstrated alpha at conventional levels of statistical significance. But we also find that result depends less on the historical record than on whether we take the perspective of academics interested in market efficiency, investors picking a fund or someone (say a potential employer) asking whether a manager has skill or is throwing darts to pick positions. These are often thought to be overlapping or even identical questions. That's not completely unreasonable in equity markets, but in fixed income these are distinct. We also find quantitative differences, mainly that fixed-income securities have much higher correlations with each other than equities, make alpha 4.5 times as hard to measure for Gross than Buffett. We don't think our results will have much practical effect on attitudes toward Gross as an investor, but we hope they will advance understanding of what alpha means and appropriate ways to estimate it.
Minimal Risk Manoeuvre Strategies for Cooperative and Collaborative Automated Vehicles

During the last decade, there has been significant increase in research focused on automated vehicles (AVs) and ensuring safe operation of these vehicles. However, challenges still remain, some involving the cooperation and collaboration of multiple AVs, including when and how to perform a minimal risk manoeuvre (MRM), leading to a minimal risk condition (MRC) when an AV within one of these systems is unable to complete its original goal. As most literature is focused on individual AVs, there is a need to adapt and extend the knowledge and techniques to these new contexts. Based on existing knowledge of individual AVs, this paper explores MRM strategies involving cooperative and collaborative AV systems with different capabilities. Specifically, collaborative systems have the potential to enact local MRCs, allowing continued productivity despite having one (or several) of its constituents encounter a fault. Definitions are provided for local and global MRCs, alongside discussions of their implications for MRMs. Illustrative examples are also presented for each type of system.
Automated SIW Slotted Waveguide Antenna Design Using ANSYS HFSS Scripts

This paper covers the development of an IronPython language script for the Ansys HFSS environment. It allows users to fully automate the SIW slotted waveguide antenna simulation process in Ansys HFSS. The script creates a SIW antenna model using the energy method for given values of half-power beamwidth and sidelobe level, sets the excitation port and radiation boundary conditions, and shows a radiation pattern at a fixed frequency after the electromagnetic simulation is finished. The script prevents the need to manually perform routine operations in Ansys HFSS while building the same type of objects in SIW slotted waveguide antennas, significantly reducing the antenna design time.
Fully Differential 90 GHz and 180 GHz Signal Sources With Tuning Ranges of 24.1 GHz and 51.7 GHz in 90 nm SiGe-BiCMOS

Currently, commercial radar systems are mainly found in the E-band. However, higher frequencies offer significant advantages in terms of absolute bandwidth and system design. The use of on-chip antennas and FR4 PCB materials is enabled by frequencies above $\approx$100GHz. This work presents two wideband and fully integrated signal sources for radar applications at 90 and 180 GHz. By using the novel 90nm SiGe BiCMOS B12HFC technology, the signal sources provide up to 6.43 dBm and 3.8 dBm output power and dc-to-RF efficiencies of 4.59% and 0.98%, respectively. Furthermore, the two signal sources achieve a tuning range of 24.1 GHz (26.6%) and 51.7 GHz (28.8%). The 90 GHz signal source is based on a fundamental voltage-controlled oscillator and a static by-16 frequency divider, which operates up to 120 GHz. The divided LO signal allows the use of commercial PLL components to enable different modulation schemes. The 180GHz signal source uses the same building blocks but is extended by a power amplifier and a bootstrapped Gilbert-Cell-based frequency doubler, which has a differential output.
A Method of Frequency-Invariant Array Pattern Nulling by Fourier Transform

In this paper, fixed beamforming methods are discussed. We propose a way to extend existing fixed narrowband method to frequency-invariant beam pattern nulling. The narrowband method is based on a property of adaptive array, i.e. beam pattern is the sum of the weighted patterns of the array. The proposed approach is implemented as follows: we represent the frequency response of the finite impulse response filter as a function of frequency and main lobe direction of the beam pattern, next we apply the Fourier transform to find the frequency-invariant beamforming coefficients. The proposed method of pattern nulling can be implemented using real filters with finite impulse responses, as shown by numerical experiments.
A Study on the Factors Influencing the Passenger throughput of Civil Aviation in Sichuan Province Based on Multi-linear Regression Model

This paper investigated the main influencing factors of civil aviation passenger throughput in Sichuan Province by establishing a multi-linear regression model using the civil aviation passenger throughput data from 2001 to 2019. We uses statistical methods such as correlation analysis, variance test, and variable selection through Lasso to eliminating multicollinearity. Finally, using the established multi-linear regression model, the main factors affecting the passenger throughput in Sichuan Province are the per capita consumption spending of urban residents and the total number of inbound tourists. At the same time, according to the two main factors and the actual situation of Sichuan Province, the corresponding countermeasures and suggestions are put forward to promote the development level of civil aviation and increase the passenger throughput of Sichuan Province.
A Battery State of Charge Estimation Using Real-Time Characterization Data

Generally, the State of Charge (SoC) of a battery is used as an important parameter in the management energy system. Since the electrochemical process of such a device is complex and it is impossible to be accessed, its parameters such as SoC or energy storage capacity cannot directly be measured by any sensor. Besides, its dynamic energy storage does not depend only on its internal characteristics, but it also depends on its operating conditions. A method of the SoC determination may use certain electrical parameters such as the open circuit voltage or the internal impedance of the battery. For example, the Open Circuit Voltage OCV method is often described by a lookup table. This type of method is simple to implement and provides a good estimation of the SoC. However, an accurate estimate of SoC can only be obtained with an accurate measurement of OCV. This is due to an equilibrium voltage can only be measured after very long period of battery relaxation. In this work, we will study the different methods of SoC estimation for different batteries using real-time characterization data.
Experimental Analysis of VNA-based Measurement Errors in Mobile THz Applications

Terahertz (THz) measurement systems are crucial for the performance validation and testing of innovative designs and components to verify their reliability towards designated THz applications. This paper investigates the measurement uncertainty of THz measurement setup based on Vector Network Analyzer (VNA) with frequency extension modules. Our work focuses on the effects of equipment mobility and the accompanying radio-frequency (RF) cable flexure, which impact phase stability and measurement accuracy. The stability of THz VNA system is studied for four VNA extension setups at waveguide frequency bands from 75 GHz up to 1.5 THz. The upper bound of phase error caused by RF cable flexure is determined up to 330 GHz. The influence of the considered uncertainty is demonstrated by a degradation in the range accuracy and distortion in the image quality of a 2-D THz imaging scenario.
Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances

In a practical power system, the synchronous generators should cope with changes in both real and reactive power demand. In general, stabilization of real power variations is possible by rescheduling the operation of generators. To control the demand of the reactive power load, electric limits of the excitation loop is adjusted to initiate the reactive power of the network. In order to accelerate the reactive power delivery, a power system stabilizer (PSS) is connected to the generator through an exciter. We introduce here a latest biogeography-based optimization (BBO) algorithm to adjust PSS parameters for different operating conditions in order to improve the stability margin and the system damping. This is possible when the integral square error (ISE), which is the objective function, of the speed deviation in asynchronous machine intended to a range of turbulence is reduced. A relative comparative study is conducted between the algorithms such as BBO, particle swarm optimization (PSO) and the adaptation law based PSS on SMIB. The simulation results indicate that when compared to other available methods, the BBO algorithm damps out low-frequency oscillations in the synchronous machine rotor in an effective manner. Algorithms are simulated with the help of MATLAB®and Simulink®. Results obtained from simulations indicate that the recommended algorithm yields rapid convergence rate and improved dynamic performance; system stability, efficiency, dynamism and reliability are also improved.
Characteristic Mode Analysis based Flower Shape High Gain THz Antenna for Imaging and Defense Applications

The intriguing features of terahertz (THz) waves captivated the curiosity of many researchers toward THz technologies. This paper introduces a high-gain composite structure consisting of a circle and rectangle with a rectangular monopole antenna for terahertz (THz) imaging and defense applications. The projected THz antenna is designed on a $20 \mu \mathrm{m}$ thick polyimide substrate with a relative permittivity of 3.5. A ground plane is lowered to have wider impedance bandwidth for the conventional rectangular patch. The lowered ground plane alters the transmission line characteristics, and therefore quality factor reduces, which impacts improved bandwidth. Furthermore, to achieve the appropriate operational frequency, the antenna’s radiator is adjusted by inserting a sequence of circles and a rectangle. The proposed flower shape antenna operates in the frequency range of 0.096-0.701THz, having an overall dimension of $600 \times 600 \mu \mathrm{m}^{2}$. The variation of gain in the operational frequency varies from 8.7 dB to 10.8 dB; at the resonant frequency of 0.2 THz, the gain is 10.8 dB. To gain a better physical understanding, the projected antenna is exposed to a characteristic mode analysis. The proposed antenna is appropriate for imaging systems (0.6 THz) and military applications (0.7 THz).