nils-herrmann/clean_scirepeval huggingface dataset:
A Generalized Precharging Strategy for Soft Startup Process of the Modular Multilevel Converter-Based HVDC Systems

The modular multilevel converter (MMC) has become the most attractive converter technology for medium/high-power applications, specifically for high-voltage dc (HVdc) transmission systems. One of the technical challenges associated with the operation and control of the MMC-based system is to precharge the submodule (SM) capacitors to their nominal voltage during the startup process. In this paper, considering various SM circuits, a generalized precharging strategy is proposed for the MMC-based systems, which can implement soft startup from the dc or ac side. The proposed precharging strategy can be applicable for various SM circuits and MMC configurations. The proposed startup strategy does not require extra measurements and/or auxiliary power supplies. The charging current is controlled by adjusting the changing rate of the number of blocked and bypassed SM capacitors. Based on the proposed startup strategy, the startup processes of MMC/MMC-HVdc systems with various SM circuits are analyzed and a generalized startup procedure for various MMC-HVdc systems is proposed. In addition, the uncontrollable steady-state SM capacitor voltages of various MMC-based systems are analyzed and the associated precharging time is also investigated. Performance of the proposed strategy for various MMC-HVdc systems is evaluated based on time-domain simulation studies in the PSCAD/EMTDC software environment and experimental results are based on a scaled-down prototype.
A novel trench shielded MOSFET with buried field ring for tunable switching and improved ruggedness

In this paper, a novel trench shielded 600V MOSFET with buried field ring is proposed and demonstrated. The proposed structure achieves an active area die shrink of 35-55% compared to a conventional 600V planar MOSFET. Furthermore, it almost doubles the Unclamped Inductive Switching (UIS) rated current and improves 0.3% of the efficiency compared to the Superjunction device. It also shows better diode reverse recovery performance than Superjunction device.
Artificial neural network model-based design and fixed-point FPGA implementation of hénon map chaotic system for brain research

This paper presents an artificial neural network (ANN) model based design for Hénon chaotic systems, and its equivalent hardware model for hardware co-simulation using Field Programmable Gate Arrays (FPGA). Chaotic generators can be used for the study of chaotic behaviors of brain activities captured by Electroencephalogram (EEG). The ANN model is designed with different fixed-point data format and evaluated using MATLAB and Simulink simulation. The chaotic level is measured by calculating the Lyapunov exponent over a certain range of selected system parameters. The ANN models are designed with the consideration of hardware implementation on Field Programmable Gates Array (FPGA) device using fixed-point data format.
An odometry estimation method for micro indoor flying robot with lightweight sensors

Micro-quadrotor usually equips with lightweight sensors due to its limited payload. In this paper, an odometry estimation method based on 2D laser scanner and monocular vision is proposed to solve the pose estimation problem of micro-quadrotor flying robot in indoor environments. This method firstly detects and matches image features of current and previous frames to get all feature correspondences to calculate the monocular odometry. Then, laser scans are transformed into image coordinate system using sensor calibration parameters. After that, the unknown translation scale of monocular odometry is determined by using triangulation. At the same time, line features of laser scans are extracted and the line angle histogram is computed. If the angle distribution is wide enough, which means it is likely to be in a structural environment, a scan matching algorithm is used to calculate the laser odometry. Finally, estimation results based on the two different sensors are fused by using weighted average method. Experiment results show that the proposed method can recover the trajectory of the robot robustly and accurately. The close loop error is less than 1% for a 64 m loop around indoor corridor.
Automatic 3D reconstruction for face recognition

An analysis-by-synthesis framework for face recognition with variant pose, illumination and expression (PIE) is proposed in this paper. First, an efficient 2D-to-3D integrated face reconstruction approach is introduced to reconstruct a personalized 3D face model from a single frontal face image with neutral expression and normal illumination. Then, realistic virtual faces with different PIE are synthesized based on the personalized 3D face to characterize the face subspace. Finally, face recognition is conducted based on these representative virtual faces. Compared with other related works, this framework has the following advantages: 1) only one single frontal face is required for face recognition, which avoids the burdensome enrollment work; 2) the synthesized face samples provide the capability to conduct recognition under difficult conditions like complex PIE; and 3) the proposed 2D-to-3D integrated face reconstruction approach is fully automatic and more efficient. The extensive experimental results show that the synthesized virtual faces significantly improve the accuracy of face recognition with variant PIE.
A position estimation for switched reluctance motor using full cycle envelope

A full cycle pulse current peak envelope sensorless technique is presented in the paper, using the pulse injected and the chopper control mode with fixed chopping falling time for the rotor position detected. The high frequency pulse injected in the non conducting region, the chopper control mode in the conducting region, the discrete peak values of the pulse current are detected, the full cycle pulse current peak envelope are formed by the fitting mathematical technique. Based on the relationship of the variation of phase current with the inductance, the rotor positions are estimated by comparing the pulse current peak envelopes. The simulation results show that the proposed method is sufficiently accurate and works effective.
An Improvement of PSWF Pulse Generator Based on Difference Quantitation

In order to improve the accuracy of Prolate Spheroid Wave Function (PSWF) pulse generator and reduce the number of bits needed in quantization, by analyzing the problem of amplitude quantization error in the traditional PSWF generator based on the Direct Digital Waveform Synthesis (DDWS), an improvement of PSWF pulse generator based on difference quantitation is proposed. Theoretical analysis and simulation results show that: While the Over Sampling Rate (OSR) is greater than, using the difference quantitation method instead of direct one will be helpful to meliorate the noise spectrum and get higher quantitation accuracy with less number of quantitation bits. The noise spectrum will meliorate 6dB every time when the over-sampling rate is doubled, which is 3dB more than the direct quantitation method. PSWF pulse generator based on the difference quantitation is much more suitable for high-precision and high sampling rate PSWF signal generation.
Applying LBP Operator to Gabor Response for Palmprint Identification

We proposed in this paper an accurate and efficient approach for palmprint identification. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where LBP is then applied to code the relation among the magnitude of wavelet response at central pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. In the experiment, 3864 test images are identified by the proposed method against the 1158 templates. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. Our approach could identify a palmprint image within 200 ms.
An improved back propagation neural network in objects recognition

The Back Propagation Neural Network(BPNN) has been used widely in objects recognition, but in fact, the BPNN can easily be trapped into a local minimum and has slow convergence. Moreover, the number of neural cells for hidden layer in the BPNN is hard to determine. For this reason, this paper proposes a novel method to improve the performance from the structure and the algorithm. The improved BP algorithm has some advantages in fast convergence speed and short running time. It is applied to objects recognition and has a favorable result. The validity of the improved methods is proved by a series of simulation experiments in the paper.
A GMR biosensing system with sub-50ppm sensitivity

We propose a complete system solution for a GMR biosensing and detection assay, including the design and fabrication of GMR biosensor, frontend for small signal extraction, data conversion, and the backend for signal processing. The overall system was evaluated comprehensively by experiment, and a sensitivity of sub-50ppm has been achieved. This sensitivity is equivalent to about 30 magnetic particles on a 120μm × 120μm sensor and among the best of published results in literature.
Construction of national clinical research data center of Traditional Chinese medicine

Traditional Chinese medicine (TCM) is developed from clinical practice. Rich information can be obtained from the medical record of TCM. National clinical research data center of TCM is constructed to collect the clinical medical data of TCM from hospitals all over the country. The construction framework of national clinical data center of TCM includes infrastructure construction, software construction, local branch data center construction and institutional framework. In the mean time, a series of measures is implemented to guarantee the normal running of the national clinical data center of TCM. The construction of national clinical data center of TCM may promote the development of TCM and improve the level of medical care in China.
Allocating Indivisible Objects With a Parallel Method Insensitive to Identities

Sequential allocation is a decentralized mechanism for allocating indivisible objects to agents, in which agents sequentially pick their favorite objects among the remainder based on a pre-defined priority ordering of agents (a sequence). The problem of choosing the “best” sequence of agents to achieve the optimal social welfare has been investigated and conjectured to be NP-hard. We propose a simple parallel allocation protocol that is insensitive to agents’ identities. In every round of the parallel allocation process, every agent asks for an object among those that remain, and every reported object will be allocated randomly to an agent reporting it. Supposing additive utilities and independence between the agents, we compare the average (and worst-case) social welfare achieved by a parallel protocol and a sequential protocol. Theoretical and empirical results show that parallel protocol outperforms a sequential protocol (even when the best sequence of agents is applied). We also show that under the parallel mechanism, some manipulation problems (e.g., finding a successful strategy for a target set and finding an optimal strategy under some scoring function) can be solved in polynomial time.
A log data transmission algorithm based on file splitting and cache matching

The log file for recording events in a cloud platform is maintained by a computer server and generally contains large amounts of data. As networks and transmission are becoming increasingly important for computational science, we are working on proposing a log file transmission algorithm. This new algorithm focuses on optimizing the performance of log file transmission, which is independent of transport protocols. Our approach includes two components: the file splitting and buffer match. The file splitting performs file compression and redundancy elimination, and the buffer memory match avoids transferring the redundant data. Experimental results verify that the log file transmission algorithm can effectively eliminate the redundancy in the log file and reduce the amount of data transmission by 90%.
An Active-gm-RC Structured CMOS Analog Filter with Time Constant Auto-Tuning

Based on TSMC 0.18μm 1P6M RF CMOS process, a 4th-order Butterworth analog low-pass filter (LPF) used in the transmitting link of 2.4GHz Wireless Sensor Network (WSN) radio frequency (RF) front-end is designed in this paper. In this design, active-gm-RC structure is derived, and it can achieve the same low consumption performance as the gm-C structure while have better linearity than that of the gm-C structure. Furthermore, a RC time constant auto-tuning circuit is also designed to automatically calibrate the RC time constant variation of the filter due to the variations of process corners, so the bandwidth precision of the filter is efficiently improved. The layout size of the whole filter with the auto-tuning circuit is 740μm×880μm. With 1.8V supply voltage, post-simulation results show that as the process varies, the cut-off frequency of the filter varies very little, which means that the tuning circuit effectively calibrates the bandwidth of the filter. The out of band attenuation rate is -80dB per decade frequency, and the operating current of the core circuit of the LPF is about 0.54mA. Post-simulation results achieve the specification requirements of IEEE802.15.4/ZigBee Wireless Sensor Networks.
Deep Development and Technology Application Based on Electric Big Data

The rapid development of extra-high voltage, smart power grid and energy internet leads to relative lagging of production management. This management strategy develops electric big data in depth and realizes an intelligent management platform with full life cycle management, standard defect closed-loop management, safety risk control, equipment state evaluation, etc. as its main carriers on the basis of key technologies of the Internet of Things, a cloud system, VR, etc. and in combination of substation operation and overhaul. In order to prevent data from leakage and illegal attack and improve the working efficiency of the platform, a multi-strategy safety protection system is put forward. After it is combined with all sub-module functions, a shared, effective and rapid integrated management platform is formed which effectively solves various kinds of operation and overhaul difficulties of power transformation equipment.
Compensation strategy of short-circuit fault for a single-winding bearingless switched reluctance motor

Due to all winding currents are controlled independently, the fault-tolerant control of single-winding bearingless switched reluctance motor (SWBSRM) is more flexible. In this paper, a compensation strategy for short-circuit fault in SWBSRM is investigated to improve the reliability of BSRM. Firstly, the mathematical model with compensation for short-circuit fault is established with consideration of two-phase coupling. Secondly, the validity of the proposed model is verified by the finite element method (FEM). Then a compensation strategy based on this model is proposed to realize rotor levitation in short-circuit fault mode. Finally, the proposed strategy is verified by simulation.
A new approach to inverse kinematic solution for a partially decoupled robot

Conventional D-H model based inverse kinematic solution algorithms have to hypothesize that d6 =0 at the end of the robot hand, or the joint variables of D-H based kinematic equations can hardly be isolated to be solved. In practical application, d6 ≠ 0 usually occurs, hence it is required for supplemental transformation between the last frame of the D-H models and real operation frame, which decreases the efficiency. In this paper, a new inverse kinematic solution without the hypothesis of d6 =0 is proposed. We found that the joint variables of the partially decoupled robot can be separated without great difficulty even though d6 ≠ 0. The new approach uses a new multiplication sequence of the inverse matrix for solving the variables of the kinematic equation of the robot. The inverse solution process is straightforward and computationally cheap. Last, some exemplifications are given to valid the accuracy of the proposed approach.
A Investigation into X-ray Radiation of VDMOS

In this study, the investigation into X-ray radiation of VDMOS is described. A radiation test of VDMOS was made by X-ray at various loads. The different radiation behavior of VDMOS was observed. The "rebound" of the threshold voltage shift of VDMOS at a larger load with X-ray radiation was larger than that without X-ray radiation, indicating that a radiation annealing effect happened to VDMOS at a powerful load. In terms of transconductance, all the radiated samples showed an increase in interface traps (Qit). At 9.84 X 105 rad (Si), the interface traps increments at a large load and at a small load were 6.3 X 1011cm2 and 5.12 X 1011/cm2, respectively. A timely annealing effect is a major factor contributing to the "rebound" of the threshold voltage shift, and caused by anneal of VDMOS weak inversion interface traps whose equivalent charge is -2.31 X 1011/cm2.
Class library design for DICOM in C++

A computerized data class library for the DICOM standard which supports DICOM image. Management and transfer over a network has been developed by using the Object-oriented language C++. The classes have been used to build a computed radiography archive system, and will be used in developing DICOM compatible medical imaging applications based on a variety of network protocols. The paper describes the data structures, implementation of various basic classes including Data Element classes, Composite Image IOD classes, DIMSE Service classes, and Message Classes. The class library defines the objects managed by DICOM application entities.
A modified joint trilateral filter based depth map refinement method

We present a modified joint trilateral filter based method for depth map refinement. Seeded region growing algorithm and Euclidean distance transform(EDT) are involved for error pixels extraction. With the error information wiped out, a joint trilateral filter method is employed as a hole filling strategy to fill the values. Compared to the basic bilateral filter method, structural similarity index(SSIM) is added as the third lateral, while a threshold and an aberration condition are involved for modification to protect the edges and improve the confidence of the filling values. Both qualitative analysis and quantitative analysis are shown to testify the performance. Comparisons between our method and the other popular methods are provided.
Development of Automatic Visual Inspection Sensor in Robotic Tailored Blank Welding

This paper describes the development of a vision inspection sensor system for the automation of laser welding processes in heavy industries. The system consists of PC based vision camera and stripe type laser diode. Its structure, basic principle of this system and the mathematic model and error analysis are also deascribed. A mathematic model is established in order to analyse the influence on sensor error from the geometric parameters. The simulation results are shown the relationship between error and coordinate of image points. Finally, the experiments results illustrate the mismatch size, weld slope, convexity , concavity, overthickness. Undercut and the bead width of the weld for the butt joint. And the feasibility and effectiveness of automatic visual inspection sensor are proved.
A Fast BP Algorithm With Wavenumber Spectrum Fusion for High-Resolution Spotlight SAR Imaging

This letter presents the accelerated fast backprojection (AFBP) algorithm for high-resolution spotlight synthetic aperture radar (SAR) imaging. In conventional fast backprojection (FBP) algorithms, image-domain interpolation is employed in the subaperture (SA) fusion. However, in AFBP, by using a unified polar coordinate (UPC) system, the interpolation-based fusion is substituted by fusing the SA spectra in the wavenumber (WN) spectrum domain. The WN-domain SA fusion is efficiently implemented by fast Fourier transform and circular shifting. In this letter, an accurate impulse response function and the WN spectrum expression of the backprojected image in the UPC are explicitly derived, and furthermore, the implementations of AFBP are investigated in detail. Compared with conventional FBP algorithms, the AFBP can precisely focus on high-resolution SAR data with dramatically improved efficiency. Both simulation and real-measured data experiments validate the superiorities of AFBP by comparing it with the fast factorization backprojection (FFBP) algorithm.
A block-based inter-band lossless hyperspectral image compressor

We propose a hyperspectral image compressor called BH which considers its input image as being partitioned into square blocks, each lying entirely within a particular band, and compresses one such block at a time by using the following steps: first predict the block from the corresponding block in the previous band, then select a predesigned code based on the prediction errors, and finally encode the predictor coefficient and errors. Apart from giving good compression rates and being fast, BH can provide random access to spatial locations in the image. We hypothesize that BH works well because it accommodates the rapidly changing image brightness that often occurs in hyperspectral images. We also propose an intra-band compressor called LM which is worse than BH, but whose performance helps explain BH's performance.
Bayesian Inverse Synthetic Aperture Radar Imaging

In this letter, a novel algorithm of inverse synthetic aperture radar (ISAR) imaging based on Bayesian estimation is proposed, wherein the ISAR imaging joint with phase adjustment is mathematically transferred into signal reconstruction via maximum a posteriori estimation. In the scheme, phase errors are treated as model errors and are overcome in the sparsity-driven optimization regardless of the formats, while data-driven estimation of the statistical parameters for both noise and target is developed, which guarantees the high precision of image generation. Meanwhile, the fast Fourier transform is utilized to implement the solution to image formation, promoting its efficiency effectively. Due to the high denoising capability of the proposed algorithm, high-quality image also could be achieved even under strong noise. The experimental results using simulated and measured data confirm the validity.
Consistency Modification of Judgment Matrix Based on Genetic Algorithm in Analytic Hierarchy Process

Analytic hierarchy process is very extensive in decision-making of many objects and widely used in many fields as a classical multi attribute decision-making approach. But its judgment matrix is constructed only by decision-maker subjective judgment. Judgment matrix consistency is the core problem in the AHP. In this paper, a nonlinear programming model is proposed for improving the consistency of the judgment matrix. Then a genetic algorithm is designed to solve the nonlinear programming model to determine matrix consistency adjustments. The improved analytic hierarchy process is more objective, more logical and more compact.
An approach to grouping traffic signals for coordination using clustering methods

Signal coordination is one of the most widely employed strategies to efficiently operate signal plans in a network. The impact on a network varies depending on signal plans as well as the spatial shape of coordination groups. Improper coordination groups may worsen the traffic flow and level of service Finding ideal decomposition points of an arterial is critical in a system-wide perspective. This study aims to propose a grouping method that identifies ideal breaking points for signalized corridors to improve the performance while minimizing traffic operators' subjective decision.