Miracle-dz/UniFAR-FTUs huggingface dataset:
A Four-Degrees-of-Freedom Modulation Strategy for Dual-Active-Bridge Series-Resonant Converter Designed for Total Loss Minimization

This paper proposes a four-degrees-of-freedom modulation scheme to mitigate the conduction and switching losses in a dual-active-bridge (DAB) series-resonant converter. Under wide-range variations in the voltage gain and output current, the increased reactive power and root-mean-square tank current can contribute significantly to the conduction loss in a DAB converter, while the occurrence of hard switching leads to a switching loss and an increased device stress. The proposed modulation scheme utilizes internal, external phase shifts, and switching frequency as modulation parameters to achieve zero reactive power, minimum-tank-current, and complete soft-switching operation. Analysis of the proposed modulation scheme is given for both buck- and boost-mode operations. The proposed modulation scheme is validated by means of a 1-kW experimental prototype of a DAB series-resonant converter operating at 100 kHz, designed to interface a supercapacitor with a rated output voltage of 48 V to a 250-V dc bus. The effectiveness of the proposed topology for charging/discharging a supercapacitor under wide-range variations in the voltage gain and output current is verified by simulations and experimental results. A maximum efficiency of 97.7% is recorded from the experimental prototype (The experimental setup used for measuring converter's efficiency is shown in the supplementary material).
Improved Lateral Resolution Using sub Pitch Sampling of Ultrasound Data for Pulsed Laser Diode-Based Photoacoustic Imaging

The achievable resolution in PAT is dependent on the receive transducer parameters such as element size, inter-element spacing (pitch or sampling) and aperture length among a few other parameters. Ideally, dense spatial sampling of the generated photoacoustic signals using point detectors is required for obtaining the best possible image resolution in PAT. However, in most practical cases, data are acquired with only limited number of finite-sized detector elements. Manufacturing a high density, large-aperture linear array transducer with “sub©- $\lambda^{\prime \prime}$ pitch, especially at higher frequencies, is challenging and therefore is expensive. Hence, there is a need for alternate ways of increasing discrete array sampling for PAT application. In this work, we employ a linear translation-based approach in which the array transducer is translated by sub-pitch amount to create an augmented RF frame data having denser lateral spatial sampling. The results from simulation and experiments show 34% and 38% improvement in lateral resolution (LR) estimate, respectively, when using $\mathbf{a}\frac{\lambda}{4}$ -pitch configuration in comparison to using conventional $\lambda$ -pitch configuration.
Localization Optimal Multi-user Beamforming with multi-carrier mmWave MIMO

In this paper, we propose optimal beamforming strategies for a millimeter wave (mmWave) system consisting of multiple users based on the localization performance bounds. We consider a single base station (BS) with prior coarse knowledge of the users' positions and formulate the optimal beamforming problem in order to minimize the localization error consisting of Cramer Rao Lower Bounds (CRLBs) of delay, angle of departure (AoD) and angle of arrival (AoA) estimation at the mobile users. We first formulate the simplified CRLB of estimation parameters, taking advantage of multiple sub-carriers, and then formulate the localization error for optimization of the beamformer. Finally, we evaluate the resulting position and orientation error bounds after optimization for several fairness strategies through Monte Carlo simulations.
A Compact Passive Equalizer Design for Differential Channels in TSV-Based 3-D ICs

In this paper, a compact passive equalizer for differential transmission channel is designed in TSV-based three-dimensional integrated circuits (3-D ICs). The compact size of the equalizer is achieved by a square shunt metal line. Three simplified odd-mode half circuit models are proposed for ground-signal-signal-ground (G-S-S-G) type TSVs, differential on-interposer interconnects, and differential channels, respectively. Those simplified models merely consist of frequency-independent elements and can accurately predict the differential insertion losses up to 20 GHz. Moreover, the electrical parameters of the proposed serial resistance-inductance (RL) type equalizers are derived from the system transfer functions and optimized by virtue of the time-domain inter-symbol interference cancellation technique. Further, the geometrical parameters of the RL equalizers are calculated by using a genetic algorithm based multi-objective optimization method. Finally, the performance of the designed RL equalizer is validated by both frequency- and time-domain simulations for 20 Gb/s high-speed differential signaling.
Feature Descriptors for Spotting 3D Characters on Triangular Meshes

Increased use of 3D digitization methods leads to large numbers of 3D models with script like cuneiform tablets, temple wall inscriptions from the Mayan empire and Minoan and Mycenaean seal imprints. Analyzing and in particular comparing those objects in our projects is a core challenge for robust symbol-spotting and transcription of ancient scripts. The discrete manifolds using irregular grids describe the objects' surface and contain complex shapes that cannot be wholly captured by a single rendering to a two dimensional plane in an image format. As the plethora of standard image descriptor extraction methods is not available on those 3D meshes we propose a novel approach adapting relevant image descriptor methods to process irregular grids. We show preliminary evaluations of our approach by performing a symbol spotting task on cuneiform tablets. Our approach proceeds in three stages: (i) We compute a local surface feature with Multi-scale Integral Invariants (MSII), (ii) for each vertex we extract radial geodesic patches which are embedded locally into a polar coordinate system, (iii) a rectangular sampling scheme converts these patches into raster image patches that are accessible to 2D image descriptors. For the symbol spotting task we compute Histogram of Oriented Gradients (HOG) and Oriented FAST and Rotated BRIEF (ORB) descriptors on the query mesh and document mesh for each vertex. Similar symbols are retrieved by sliding a geodesic patch along the document mesh. Like in many other Cultural Heritage applications we have to consider the lack of any ground-truth. Therefore we provide a qualitative analysis of the spotting results showing that a query mesh is reliably found on the document mesh.
Predicting the Top-N Popular Videos via a Cross-Domain Hybrid Model

Predicting the top-N popular videos and their future views for a large batch of newly uploaded videos is of great commercial value to online video services (OVSs). Although many attempts have been made on video popularity prediction, the existing models has a much lower performance in predicting the top-N popular videos than that of the entire video set. The reason for this phenomenon is that most videos in an OVS system are unpopular, so models preferentially learn the popularity trends of unpopular videos to improve their performance on the entire video set. However, in most cases, it is critical to predict the performance on the top-N popular videos, which is the focus of this study. The challenge for the task are as follows. First, popular and unpopular videos may have similar early view patterns. Second, prediction models that are overly dependent on early view patterns limit the effects of other features. To address these challenges, we propose a novel multifactor differential influence prediction model based on multivariate linear regression. The model is designed to improve the discovery of popular videos and their popularity trends are learnt by enhancing the discriminative power of early patterns for different popularity trends and by optimizing the utilization of multisource data. We evaluate the proposed model using real-world YouTube data, and extensive experiments have demonstrated the effectiveness of our model.
Optimization of Power Plant Operation Parameters for Efficiency Improvement through Data-Driven Relevance Vector Machine Regression Algorithm

In this paper, we will discuss about power generation efficiency improvement program (EIP) for saving fuel cost of electrical energy production. EIP will be focused on the embedding and enhancing operation culture by setting the operation parameters quality control chart as guidance for the power plant frontline operation. The data sources are limited to the controllable operation parameters acquired by Distributed Control System (DCS). New methodology that is algorithm as one of artificial intelligence tools will be proposed to be applied on the EIP. The new methodology consists of 5 steps: 1) collect operation parameter data acquisition, 2) select main operating indicator, 3) develop relevance vector machine (RVM) regression algorithm used for regression process, 4) define operation parameter quality control chart, 5) frontline operation optimization process. The operation parameter quality control chart is derived from statistical data acquired with the RVM regression algorithm. The mean regression curve achieved is proposed as a reference for maximum tolerable limit of operation parameter range and from the practical reference the efficient operation limit curve was set at 5% below it. The results show that RVM technique capable to produce an operation parameter regression curves from the sparse prior operation parameter data. This quality control chart can be applied as a helpful guidance for frontline operation in purpose for leading the change the operator behavior to become a new efficient mindset culture. Originality of the proposed methodology in this paper is the operation parameter quality control chart which derived by application of RVM regression algorithm.
Dynamic on-State Resistance Test and Evaluation of GaN Power Devices Under Hard- and Soft-Switching Conditions by Double and Multiple Pulses

The dynamic <sc>on</sc>-state resistance (<italic>R</italic><sub>DSON</sub>) behavior of commercial GaN devices is very important for a GaN-based converter. Since the zero-voltage switching techniques are popular in high-frequency power conversion, a dynamic <italic>R</italic><sub>DSON</sub> test board integrating both hard- and soft-switching test circuits is built in this study. Two types of commercial GaN devices are tested and compared under hard- and soft-switching conditions by double-pulse and multipulse test modes, respectively. It has been found that their dynamic <italic>R</italic><sub>DSON</sub> exhibit different behaviors depending on the <sc>off</sc>-state voltage and frequency under hard- and soft-switching conditions due to different device technologies, which should be taken fully into account for GaN-based converter design and loss estimation. In order to simulate the <italic>R</italic><sub>DSON</sub> behavior in a steady-state operating converter, a multipulse measurement has been implemented, the results of which are compared with that of double-pulse test. Furthermore, the primary trapping mechanisms responsible for dynamic <italic>R</italic><sub>DSON</sub> increase under different switching conditions are identified and verified by the numerical device simulation using Silvaco TCAD tool.
Eccentric Design of Fabry-Perot Interferometer for High Sensitivity and Broadband Ultrasound Sensing

Ultrasound sensing with broadband and high sensitivity enables high resolution and large penetration in ultrasound imaging such as photoacoustic imaging and nondestructive testing. Traditional piezoelectric ultrasound transducers suffer from limited bandwidth and sensitivity. On the contrary, fiber-based Fabry-Perot (F-P) interferometer exhibited very high sensitivity on vibrations, which potentially acted as a high sensitivity ultrasound sensor. However, due to the high quality factor of silica in fibers, its reverberation lasts a long time, leading to a narrow bandwidth and a high noise level. In this research, we designed a multi-core fiber sensor with the eccentric cores. The diameter of the fiber was investigated while the distance between the core and the fiber surface remained 40 μm for optical signal integrity. Finite element modeling demonstrated that a 500 μm fiber provides reasonable signal to noise ratio. At eccentric positions, the actual sensing signal is almost identical as that at the center, whereas the reverberating noise decreased from −1 dB to −28 dB. The proposed F-P sensor based on thick optical fiber with eccentric cores exhibited high sensitivity and broadband response compared to either piezoelectric sensors or conventional fiber sensors, pioneering a promising future of ultrasound sensing.
A Comparative Study on Camera-Radar Calibration Methods

Camera-radar fusion has been applied in obstacle detection or moving object tracking for autonomous vehicles and advanced driver assistance systems. When utilizing multiple sensors, their calibration is not only essential but also important because it gives great impacts on subsequent procedures. Nonetheless, camera-radar calibration methods have not been compared in the literature qualitatively or quantitatively. In this paper, we compare three types of the calibration methods presented in previous studies on fusing camera and radar in terms of calibration accuracy. Especially, the comparison is conducted in the situation of varying the number of radar-image data pairs used in their calibration. Experimental results show that one type of the methods is not appropriated to the camera-radar calibration, and the methods belonging to the other types provide quite similar accuracy.
Exploration on the value innovation of Energy Internet demonstration park

With the rapid development of Energy Internet, Energy Internet demonstration park has become the focus of international academy and industry. In this paper, main characteristics and objectives of Energy Internet demonstration park are analyzed and the architecture of Energy Internet demonstration park composed of the physical layer, information layer, and operation layer has been proposed. Moreover, both the old and new value of multi-energy complementary is summarized and discussed. Finally, numerical analysis of the demonstration Park is used to explore the value innovation mentioned above.
Design and Research of Automated Demand Response Simulation System

Demand response is an important part of smart grid construction and an important way to link demand side management. The research on the hardware-in-the-loop simulation of demand response is conducive to guiding the development of demand response from the theoretical level and solving the problem of insufficient experience in the pilot application. Under the situation of open-loop power supply, new business and service modes of automatic demand response have emerged. The application of automatic demand response simulation system has important guiding significance for practical engineering.
The Evaluation of the Verticality Test in SIAS by Using a Depth Sensor

When a person gets a stroke including brain disease (e.g. cerebral bleed, cerebral infarction, subarachnoidal bleeding, etc.), the body function become worse by the hemiplegia paralysis, muscle weakness, sensory disorder, and so on. SIAS (Stroke Impairment Assessment Set) has a capability to evaluate these bodies with disabilities from multiple points of view at rehabilitation. However, the tests such as SIAS are usually evaluated by inaccurate visual observation and the results depend on the examiner. To overcome this problem, the authors have been developing a total system to get a unified decision for numerous SIAS tests by using depth sensors. In this paper, we develop the Verticality test in SIAS. This test is to evaluate the incline of trunk to lateral directions, and our system automatizes the evaluation by using Microsoft Kinect. By conducting experiments with 20 adults, we show that this system has a possibility to be used as an automatized Verticality test.
Core Loss Calculation in a Variable Flux Permanent Magnet Machine for Electrified Transportation

The paper is focused on the modeling and measurement of core losses in an AlNiCo-based variable flux permanent magnet machine. The application of AlNiCo as a low coercivity magnet provides the ability of the magnet flux control using short-time $d$ -axis current pulses. This allows a reduction in the machine core losses under high-speed conditions, thus improving the machine efficiency. In order to identify the machine efficiency gains, the core losses have to be accurately modeled at different magnetization levels. An advanced core loss model for the variable flux machine (VFM) is first presented. This model is based on the calculation of an equivalent sinusoidal waveform of nonsinusoidal magnetic flux density. The model is then utilized to calculate the core losses in a tangentially magnetized VFM using finite-element simulation. In order to validate the developed model experimentally, a measurement method is developed to segregate the mechanical losses and the no-load core losses at different speeds and magnetization levels for a 5-hp VFM. Finally, the proposed model accuracy is verified through a comparison with the experimentally measured core losses under a no-load condition.
Online Japanese Handwriting Recognizers using Recurrent Neural Networks

This paper presents an attempt to recognize online isolated handwritten Japanese characters as well as text lines by Recurrent Neural Networks (RNNs). Although there are some successful studies on online Chinese handwriting recognition using RNNs, it is difficult to achieve high accuracy for Japanese due to many different types of characters such as kanji and kana. Moreover, training RNNs usually requires a large number of samples for each class of character. Hence, we apply five different transformation operations on the original samples to generate artificial samples with various deformations. For online handwritten Japanese text, we use the Kondate database, but it does not cover the whole Japanese character set. Thus, we generate random text lines using the sentences from corpora and isolated characters from the Nakayosi and Kuchibue databases. Besides, we employ a robust process with some preprocessing steps and the state-of-the-art online features to extract invariant features from handwritten patterns because the handwritten samples are merged from the different databases collected on different devices with various resolutions. For the recognition model, we have implemented the different Bidirectional Long Short-Term Memory Networks (BLSTM networks) for isolated character classification (sequence classification task) and handwritten text recognition (transcription task). The best model of the sequence classification task achieves an accuracy of 97.91% on Nakayosi and 97.74% on Kuchibue. The best model of transcription task performs a character recognition rate of 86.31% on Kondate and 83.15% on the generated text lines.
A Sub-mW Fractional- ${N}$  ADPLL With FOM of −246 dB for IoT Applications

This paper presents a sub-mW fractional-<inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> all-digital phase-locked loop (ADPLL) with scalable power consumption, which achieves an figure of merit (FOM) of −246 dB. The proposed 10-b ultralow-power isolated constant-slope digital-to-time converter (DTC) achieves a 580-fs resolution and a measured integral nonlinearity (INL) of 870 fs with 0.14-mW power consumption at 52 MS/s. A narrow-range time amplifier (TA)-time-to-digital converter (TDC) with gain calibration minimizes both the in-band phase noise degradation and the loop-bandwidth variation. In addition, a coarse-DPLL is introduced with dead-zone function, which reduces the phase lock time to 4.2 <inline-formula> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula> at a 13-MHz frequency error. The coarse-DPLL monitors large frequency and phase jump in the background while consuming almost zero power. In an ultralow power mode, the proposed fractional-<inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> ADPLL consumes a 0.65-mW power with a 26-MHz reference. A rms jitter of 1.00 ps and −50-dBc in-band fractional spur are achieved with a −242-dB FOM. In high-performance mode, a reference doubler is utilized, the jitter and spurs can be improved to 535 fs and −56 dBc, respectively, while consuming 0.98 mW. The proposed ADPLL with scalable power and jitter performance can be utilized for Internet-of-Things (IoT) applications, such as Bluetooth low energy (BLE) and Wi-Fi networks.
Measured Results of Input Resistance of NMHA in a Body Phantom

In recent years, the development of healthcare monitoring devices require sensor antennas with high performance and small size. Normal-mode helical antenna (NMHA) can achieve high efficiency when antenna structure is designed self-resonant. However, when antenna was placed in a human body, it was reported that an antenna efficiency was decreased owing to increase of input resistance. To ensure the input resistance through experiment is important. In this paper, measurement is performed by using a human body phantom. Input resistance results of measurement and simulations agree rather well.
Quantitative Cardiac Output Assessment Using 4D Ultrafast Doppler Imaging: An in Vitro Study

Background, Motivation and Objective Echocardiography is routinely used in the clinic to evaluate the cardiac function. Anatomical indexes such as ventricular volume measurements or functional indexes such Cardiac Output are performed using standard echocardiography. However, 2D dimensional measurements induce inter-operator variability and standard 3D measurements do not have the sufficient volume rate to evaluate functional indexes. Moreover, the accuracy of flow velocity estimates is strongly reduced by the angular dependence of Doppler measurements. In this study, we propose to use 4D ultrafast Doppler to evaluate flow rates in a pipe to demonstrate the potentiality of performing Cardiac Output measurements without assumptions on the valve geometry and without angular dependence. Statement of Contribution/Methods An ultrasonic matrix array probe (central frequency 2.5MHz, 1024 elements, pitch 0.3 mm, bandwith 60%, Vermon, France) connected to a 1024 channels ultrasound scanner prototype was used to image the pipe output in three dimensions. 500 diverging waves (angular aperture 80°) were emitted at a volume rate of 2000 volumes/s during 250 ms. Color Doppler volumes (quantitative flow speed volumes) were computed by calculating the first moment of the Doppler spectrums in each voxel. The pipe flow rates (N=7) were calculated by integrating directly the flow speed over the cross section of the pipe. Results/Discussion The measured flow rates were found to be in a good agreement with the flowmeter values used as a gold standard (R2 = 0.96). The four dimensional nature of the acquisition has the potential to enable the calculation of the Cardiac Output in vivo in patients without the need of making any assumption on the valve geometry or the direction of the ultrasonic beam usually responsible for errors.