Miracle-dz/UniFAR-FTUs huggingface dataset:
A Power-Efficient Fractional-N DPLL With Phase Error Quantized in Fully Differential-Voltage Domain

This article presents a power-efficient low-jitter fractional-N digital phase-locked loop (DPLL) that resolves phase error (PE) in the fully differential voltage (FDV) domain. Compared with adopting a traditional time-to-digital converter (TDC), which relies on gate delay in the time domain, power-efficient quantization of PE by the proposed conversion scheme in the FDV domain can be accomplished with a higher power-supply/common-mode rejection ratio (PSRR/CMRR), lower process, voltage, and temperature (PVT) sensitivity, finer resolution, and better linearity. The implemented DPLL covers the fractional-N operation by a 10-bit differential current digital-to-analog converter (DAC) with a resistive load to represent the fractional phase/time. A differential $dv/dt$ ramp is employed to linearly transfer the preset initial voltage into a small phase/voltage error, which is digitized by a narrow-range fine-resolution 7-bit self-timed successive-approximation-register analog-to-digital converter (SAR-ADC). The prototype DPLL, implemented in 130-nm CMOS, achieves 101-fs rms jitter, integrated from 10 kHz to 40 MHz, in the fractional-N mode with sub-12-bit fractional-frequency-control words, using an 80-MHz reference clock (REF), consuming 9.2 mW. This corresponds to a figure of merit (FoM) of −250.3 dB. The measured worst case fractional spur level is −56 dBc.
Investigation of the dependence of the evaluation parameters in protection of cardio data on the applied wavelet basis

The report presents an analysis of an algorithm for the protection of electrocardiological holter records of patients, including compression, watermarking and encrypting. Parameters were studied and analyzed using the latest technologies for analysis, processing and protection of digital information. Methods and technological approaches for organizing unstructured data with physiological information in digital repositories have been developed.The analysis is performed from the point of view of the choice of wavelet basis when performing wavelet transformation on the studied data and the influence of the specific selected basis on the next stages of the protection algorithm. An analysis of the protection procedure was performed using the Wavelet bases of Haar and Daubechies (Db) with 2, 4, 6, 8, 12 and 20 coefficients and 8 level of decomposition. The evaluation of the procedure was performed with the parameters PRD(Percentage Residual Difference) and PSNR (Peak Signal to Noise Ratio). The obtained results (PRD = 0.1724 and PSNR = 52.06 with Db4 and PRD = 0.1744 and SNR = 51.99 with Db8 show that the Dd4 and Db8 are the most suitable wavelet bases for performing watermarked procedure. After performing the encryption procedure, the following values are calculated PRD = 0.1802 and PSNR = 47.22 when applying Db4 basis.
A Piezoelectric Linear Actuator Controlled by the Reversed-Phase Connection of Two Bimorphs

A linear actuator controlled by the reversed-phase connection of two piezoelectric bimorphs is proposed in this study to solve the problem of drawback in the existing piezoelectric linear actuators. The actuator is driven by one excitation signal, the two piezoelectric bimorphs will always bend in opposite directions by the reversed-phase connection, so the directions of the force output by the two piezoelectric bimorphs are opposite. Because of the length difference of the clamping blocks, the two forces outputted by each bending is different in magnitude, and always have a resultant force in the same direction to make the actuator move forward two steps in one cycle without drawback. A series of experiments were conducted to evaluate the performance of the actuator provided. The starting voltage is 40 <inline-formula> <tex-math notation="LaTeX">$\text{V}_{\mathrm {p-p}}$ </tex-math></inline-formula>, resolution can reach <inline-formula> <tex-math notation="LaTeX">$1.16~\mu \text{m}$ </tex-math></inline-formula> without load. The load capacity of the actuator is 450 g with a 100 <inline-formula> <tex-math notation="LaTeX">$\text{V}_{\mathrm {p-p}}$ </tex-math></inline-formula> voltage, a 2-Hz frequency, and the average step displacement in this case is <inline-formula> <tex-math notation="LaTeX">$0.725~\mu \text{m}$ </tex-math></inline-formula>. The prototype has high linearity and good repeatability. Experiments have proved that the actuator controlled by reversed-phase connection can eliminate drawback in principle, and can move forward two steps in one cycle. The resolution of the prototype by the reversed-phase connection is much higher than the in-phase connection, and it is a new method to improve the driving performance of piezoelectric actuators.
A Quantitative Analysis of Battery Energy Storage System Integration Solutions into Isolated Hybrid Generation Networks: Application to Phu Quy Island

For hybrid energy systems utilizing renewable energy sources such as the power grid of Phu Quy island - Binh Thuan province, the integration of battery energy storage system (BESS) could be seen as a practical solution with remarkable advantages including economic and technical preeminence. BESS contributes to increasing renewable energy penetration, enhancing system stability and reducing the dependence on fossil fuel generation. However, the integration of BESS into an existing hybrid power system also necessitates to conduct a quantitative analysis of the performance of different solutions. This study investigates operational data of Phu Quy power grid for one year, evaluates solar energy potential and proposes a proper BESS integration solution based on a careful quantitative analysis. The simulation results show that selection of larger BESS capacity increases penetration rate of renewable energy. Nevertheless, of all proposed BESS integrated scenarios, renewable energy penetration rate as well as diesel consumption do not show a major difference. Therefore, choosing BESS also needs to consider the load capacity and time required to start and interconnect standby diesel generators.
Total Variation Deconvolution of Raman Distributed Temperature Sensing Signals

The diffusion of optical fibers has leveraged the development of several researches studies in the field of industrial applications. The sensing element is the fiber itself, and the reading is performed by commercial distributed temperature sensing (DTS) equipament based on Raman scattering. Most commercial DTS equipament has a spatial resolution of one meter, which makes it difficult to employ in small and medium structures or equipment. In addition to the advantage of having reduced dimensions, these sensors are immune to electromagnetic interference (EMI). These characteristics are fundamental for use in electric machines. This paper presents a scheme to reduce the spatial resolution through signal processing without changing the hardware of the equipament, thus aiming at new applications of this technology in small and medium-sized structures.
Data Architecture for Motivation Measurement in a Game based Rehabilitation System

The purpose of this paper is to demonstrate the data model including a quantitative motivational assessment model for a game-based exercise therapy system. The data model comprises of three parts. The set-up data for the users and the feedback form templates. The set-up data model for an exercise session for each individual user/ patient. A feedback capture system along with an analytics module for motivation measurement. Our hypothesis is motivation is critical to participant engagement and desire to participate in therapy. In patients with neuro-muscular deficits resulting from conditions such as Cerebral Palsy (CP), Traumatic Brain Injury (TBI) and Stroke neuro muscular stimulation along with cognitive stimulation leads to neuro plastic recovery. The key contribution of this paper is to demonstrate the advancement of science in architecting data model of this system.
Estimating the DP Value of the Paper Insulation of Oil-Filled Power Transformers Using an ANFIS Algorithm

The condition of the transformer insulation has an impact on the transformer’s performance during the operation. The aging of the oil-impregnated cellulose insulation and the associated loss of mechanical strength are the important factors that limit the life of expectancy of a transformer. To determine the condition of the oil-impregnated cellulose insulation, the Degree of Polymerization (DP) parameter is commonly used. An Adaptive Neuro-Fuzzy Inference System (ANFIS) has been developed to predict the DP Value by the chemical characteristics and dissolved gas parameters (acidity, interfacial tension, CO, CO2, breakdown voltage, and water content of the oil). This paper generates some algorithms which are based on the input space partitioning method to generate rules (grid partition or subtractive clustering) and data is normalized or not. The estimation result has been observed and evaluated to provide that the ANFIS algorithm is suitable to estimate insulation condition on field operating transformers.
The Challenges of Artificial Intelligence in Wireless Networks for the Internet of Things: Exploring Opportunities for Growth

The Internet of Things (IoT), a term first coined by Ashton in [1], is an extension of network connectivity to physical devices, such as actuators, sensors, and mobile devices, that are enabled to interact and communicate among themselves and can be controlled or monitored remotely. The IoT, hailed as the enabler of the next industrial revolution, will transform how we view, interact with, and use the current physical systems around us. It has already had a major impact on health care, smart homes, manufacturing, commerce, education, and many other key areas of daily life.
A CMOS Dual-Polarized Phased-Array Beamformer Utilizing Cross-Polarization Leakage Cancellation for 5G MIMO Systems

This article introduces a power-efficient and low-cost CMOS 28-GHz phased-array beamformer supporting fifth-generation (5G) dual-polarized multiple-in-multiple-out (MIMO) (DP-MIMO) operation. To improve the cross-polarization (cross-pol.) isolation degraded by the antennas and propagation, a power-efficient analog-assisted cross-pol. leakage cancellation technique is implemented. After the high-accuracy cancellation, more than 41.3-dB cross-pol. isolation is maintained along with the transmitter array to the receiver array. The element-beamformer in this work adopts the compact neutralized bi-directional architecture featuring a minimized manufacturing cost. The proposed beamformer achieves 22% per path TX-mode efficiency and a 4.9-dB RX-mode noise figure. The required on-chip area for the beamformer is only 0.48 mm2. In over-the-air measurement, a 64-element dual-polarized phased-array module achieves 52.2-dBm saturated effective isotropic radiated power (EIRP). The 5G standard-compliant OFDMA-mode modulated signals of up to 256-QAM could be supported by the 64-element modules. With the help of the cross-pol. leakage cancellation technique, the proposed array module realizes improved DP-MIMO EVMs even under severe polarization coupling and rotation conditions. The measured DP-MIMO EVMs are 3.4% in both 64-QAM and 256-QAM. The consumed power per beamformer path is 186 mW in the TX mode and 88 mW in the RX mode.
Structure Optimization of a Superconducting Linear Generator With YBCO Tape Windings

The paper proposed double-sided superconducting linear generator with YBCO tape windings. An analytical model of linear generator was developed based on electromagnetic field theory. A parameter-scanning method is used to search for optimal dimension parameters with the purpose of minimizing the non-sinusoidal components of the induced voltage curve. The results obtained show a significant improvement in the quality of air-gap magnetic field, and reduction of the higher harmonic in voltage wave obviously. The induction voltage in the generator coils at the speed of 130 m/s are studied. Finally, the feasibility of the superconducting linear generator was analyzed and confirmed.
Improving Convolutional Recurrent Neural Networks for Speech Emotion Recognition

Deep learning has increased the interest in speech emotion recognition (SER) and has put forth diverse structures and methods to improve performance. In recent years it has turned out that applying SER on a (log-mel) spectrogram and thus, interpreting SER as an image recognition task is a promising method. Following the trend towards using a convolutional neural network (CNN) in combination with a bidirectional long short-term memory (BLSTM) layer, and some subsequent fully connected layers, in this work, we advance the performance of this topology by several contributions: We integrate a multi-kernel width CNN, propose a BLSTM output summarization function, apply an enhanced feature representation, and introduce an effective training method. In order to foster insight into our proposed methods, we separately evaluate the impact of each modification in an ablation study. Based on our modifications, we obtain top results for this type of topology on IEMOCAP with an unweighted average recall of 64.5% on average.
Neural Network Nonlinear Equalizer in Long-Distance Coherent Optical Transmission Systems

Recently, neural network (NN) nonlinear equalizers which are expected to reduce computational complexity have attracted attention as fiber nonlinear compensation methods for coherent optical transmission systems. However, these fiber nonlinear compensation methods have problems that training of NN is not easy for long-distance transmission systems because of accumulated phase noise. In this letter, we propose a training method of NN nonlinear equalizer using the target outputs including phase noise which is produced by received signals. The phase noise is estimated by the inverse modulation of received signals and filtering. The estimated phase noise is added to transmitter signals, and the target outputs are obtained. The target outputs allow training of NN in long-distance coherent optical transmission systems. Since the NN trained by this proposed method compensates only for fiber nonlinearities, the phase locked loop (PLL) is placed after the NN to compensate for phase noise. The performances are evaluated by the simulation of 32 Gbaud 16QAM 4000 km long-distance coherent optical transmission. These results indicate that the proposed training method is effective in training NN nonlinear equalizer in long-distance coherent optical transmission in the presence of phase noise.
Uncertainty-Aware Representations for Spoken Question Answering

This paper describes a spoken question answering system that utilizes the uncertainty in automatic speech recognition (ASR) to mitigate the effect of ASR errors on question answering. Spoken question answering is typically performed by transcribing spoken con-tent with an ASR system and then applying text-based question answering methods to the ASR transcriptions. Question answering on spoken documents is more challenging than question answering on text documents since ASR transcriptions can be erroneous and this degrades the system performance. In this paper, we propose integrating confusion networks with word confidence scores into an end-to-end neural network-based question answering system that works on ASR transcriptions. Integration is performed by generating uncertainty-aware embedding representations from confusion networks. The proposed approach improves F1 score in a question answering task developed for spoken lectures by providing tighter integration of ASR and question answering.
Execution of battery charging for electric vehicles using five level methods

This paper shows a charging scheme for electric vehicles that would be faster, effective, and reliable than the existing system. This work proposed the method of changing the current parameters at discrete intervals dependent on the battery’s using the five-level battery charging method. To validate the results and design technique, the proposed work is executed by Matrix Laboratory, the obtained output results were extremely gratifying. Further motivated to build a practical working model and verify it with the obtained software values. Both the results were convincing and confirmed to be much faster than the existing schemes.
Classification of β-Thalassemia Carriers From Red Blood Cell Indices Using Ensemble Classifier

Thalassemia is viewed as a prevalent inherited blood disease that has gotten exorbitant consideration in the field of medical research around the world. Inherited diseases have a high risk that children will get these diseases from their parents. If both the parents are <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Thalassemia carriers then there are 25% chances that each child will have <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Thalassemia intermediate or <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Thalassemia major, which in most of its cases leads to death. Prenatal screening after counseling of couples is an effective way to control <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Thalassemia. Generally, identification of the Thalassemia carriers is performed by some quantifiable blood traits determined effectively by high-performance-liquid-chromatography (HPLC) test, which is costly, time-consuming, and requires specialized equipment. However, cost-effective and rapid screening techniques need to be devised for this problem. This study aims to detect <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Thalassemia carriers by evaluating red blood cell indices from the complete-blood-count test. The present study included Punjab Thalassemia Prevention Project Lab Reports dataset. The proposed SGR-VC is an ensemble of three machine learning algorithms: Support Vector Machine, Gradient Boosting Machine, and Random Forest. Comparative analysis proved that the proposed ensemble model using all indices of red blood cells is very effective in <inline-formula> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula>-Thalassemia carrier screening with 93% accuracy.
Comparison of Coupled-Inductor based Interleaved High Gain DC-DC Converter Topologies

A group of high gain DC-DC converters derived from the basic interleaved converter is proposed in this paper. The output of the interleaved structure is further boosted by the diode capacitor multiplier (DCM) pairs. The interleaved nature of the converters helps in reducing the input current ripple. Further, the energy storage inductors are supplanted by coupled inductors. Resultantly, the series arrangement of the secondary winding of the coupled inductors (CI) also takes active participation in improving the voltage gain. The three converters presented in this paper are simulated with an input voltage of 18V, making the switches to operate at a duty ratio of 0.5 and achieve 380V at the load terminals. The simulated waveforms and other parameters are compared to analyze the pros and cons of the three presented converters with regards to their ability to achieve high voltage gain.
Calcium phosphate system in saliva-like media

Despite the well documented importance of carbon dioxide dissolved in physiological media, consideration of its effect on calcium phosphate solubilities has been neglected, an omission now shown to be serious. A solid titration technique has been developed to avoid a number of the difficulties inherent in solubility studies of calcium phosphates; this employed a graphical method based on pH and calcium-ion electrode potential to identify breakpoints. The solubility isotherm at 37.0 °C for hydroxyapatite has thus been determined for the chosen saliva-like medium. A numerical model of the system provided corroboration for the results obtained. An approximately 10-fold increase in the calcium-carrying capacity of that medium was then demonstrated with CO2 present at a fixed partial pressure of 0.035 bar, a result not explicable in terms of known equilibria. Two new complexes, CaH2PO4H2CO+3(β= 54) and CaH2PO4HCO3(β= 43), are postulated to account for the data.
Investigation of a Novel Radial Partitioned Stator HTS-Excitation Flux-Switching Machine

This paper proposes and analyzes a novel radial partitioned stator HTS-excitation flux-switching (RPS-HTSFS) machine. The key is that the single ring-shaped HTS-excitation coil is independently placed in the coaxial claw-pole outer stator while the armature windings are wound around the U-shaped iron core on the inner flux-switching armature stator without permanent magnets. This solution has been explored to realize the physical isolation of armature winding and excitation winding, relieving the influence of armature field on the HTS-excitation coil. Moreover, only a single ring-shaped HTS-excitation coil is employed, therefore, reducing the HTS wires and the bending strain of the HTS-excitation coil. Also, the special refrigeration system can realize stationary seals of the double-layer ring-shaped cooling Dewar pattern, improving the cooling performance. By using the three-dimensional finite element analysis (3D-FEA), the machine performances are investigated and the validity of the proposed machine is verified.
An Improved Transistor Modeling Methodology Exploiting the Quasi-Static Approximation

In this paper, a new modeling technique is proposed for extracting small-signal lumped-element equivalent-circuit models for microwave transistors. The proposed procedure is based on using an optimization approach that is improved by targeting a quasi-static behavior as additional objective function rather than only minimizing the error between the simulated and measured scattering parameters. The validity of the developed modeling methodology is successfully demonstrated by considering a 0.25x1000 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}^{2}$ </tex-math></inline-formula> gallium nitride (GaN) high-electron-mobility transistor (HEMT) as a case study.
Electromagnetic parametric study of a MIMO dipole array antenna by FDTD technique

In this work we present preliminary results for a MIMO antenna array comprising two dipoles. An FDTD solver was developed in order to characterize the antenna and computed important electromagnetic parameters such as input impedance, reflection coefficient, radiation patterns and S-parameters. Furthermore, the MIMO channel capacity is estimated as a function of elements distance separation and signal frequency.
Five Methods for Neural Recording Application and Comparison of Neural Amplifiers

The so-called neural activity refers to the enhancement of electrical activity, metabolic activity and chemical secretion when the neural pathway performs normal functions. And neural recording is to speculate on the function of different brain regions by observing the neural activity when animals are stimulated or engaged in various activities. In order to improve the efficiency of neural recording, in this paper, a Complementary Metal Oxide Semiconductor (CMOS) amplifier for neural recording applications are investigated. More than this, three neural recording microsystems and a neural recording tag in a CMOS, which are helpful to enhance neural recording technology and amplifiers in them are also discussed.