nils-herrmann/clean_scirepeval huggingface dataset:
A Flexible Power Control Method of VSC-HVDC Link for the Enhancement of Effective Short-Circuit Ratio in a Hybrid Multi-Infeed HVDC System

With the emerging use of voltage source converter high voltage direct current (VSC-HVDC) links, the hybrid multi-infeed HVDC (HMIDC) system that includes the line commutated converter (LCC) HVDC and the VSC-HVDC links is becoming a promising power transmission structure in the modern power systems. To evaluate the contribution of the VSC-HVDC link on the voltage stability of HMIDC system, this paper proposes an effective short circuit ratio (ESCR) calculation method. Through the calculation, the voltage support capability of the VSC-HVDC link can be quantitatively represented by the ESCR. Furthermore, based on the calculation results, a flexible power control strategy for the VSC-HVDC link is developed to provide maximum reactive power support under grid faults. The theoretical analysis of the HMIDC system is based on the Danish transmission grid, evaluated through PSCAD simulations under different grid fault conditions. Simulation results are presented to validate the expected performance of the proposed method.
A study of limit cycles and chaotic motions of a single-link robot manipulator during slow motion

In this paper, limit cycles and chaotic motion of a single-link robot manipulator moving at low speed are investigated. The dynamic model of the one-link robot manipulator is set up in which different joint friction is considered. By using the describing function of the nonlinear part of the robot control system, stable limit cycles are proven to exist. The chaotic motion is shown via a Poincare map. Numerical simulations identify the chaotic zone location near the imaginary axis of the complex plane.
An overall study of the asymmetrical half-bridge with unbalanced transformer turns under current mode control

An overall study of the asymmetrical half-bridge (AHB) with unbalanced transformer turns under current mode control is presented. An analysis is presented for the output filter, switch stress, and dynamics. In addition, key ideas of the AHB transformer design are presented. This is followed by a survey of the existing methods that the AHB uses to achieve zero voltage switching at turn-on, namely the series inductance method and the parallel inductance method. Following these, the auxiliary L-C-C circuit method is proposed for the AHB to further minimize switching loss. Experimental results are included for a 48 V/5 V prototype operating at 6 A load and 400 kHz.
Back-Gate Bias Dependence of the Statistical Variability of FDSOI MOSFETs With Thin BOX

The impact of back-gate bias on the statistical variability (SV) of FDSOI MOSFETs with thin buried oxide (BOX) is studied via 3-D “atomistic” drift-diffusion simulation. The impact of the principal sources of SV, i.e., random dopant fluctuations, line edge roughness, and metal gate granularity, on threshold voltage, drain-induced barrier lowering, and drive current is studied in detail. It is shown that reverse back-bias is beneficial in terms of reducing the dispersion of the off-current and the corresponding standby leakage power, whereas forward back-bias reduces the on -current variability. The correlation coefficients between relevant figures of merit and their trends against back-bias are also studied in detail, providing guidelines for the development of statistical compact models of thin-BOX FDSOI MOSFETs for low-standby-power circuit applications.
Design-level performance prediction of component-based applications

Server-side component technologies such as Enterprise JavaBeans (EJBs), .NET, and CORBA are commonly used in enterprise applications that have requirements for high performance and scalability. When designing such applications, architects must select suitable component technology platform and application architecture to provide the required performance. This is challenging as no methods or tools exist to predict application performance without building a significant prototype version for subsequent benchmarking. In this paper, we present an approach to predict the performance of component-based server-side applications during the design phase of software development. The approach constructs a quantitative performance model for a proposed application. The model requires inputs from an application-independent performance profile of the underlying component technology platform, and a design description of the application. The results from the model allow the architect to make early decisions between alternative application architectures in terms of their performance and scalability. We demonstrate the method using an EJB application and validate predictions from the model by implementing two different application architectures and measuring their performance on two different implementations of the EJB platform.
Discontinuous-Current-Source Drivers for High-Frequency Power MOSFETs

This paper proposes a new current-source driver (CSD) with discontinuous inductor current. Compared to other CSDs proposed in the previous work, the most important advantage of the proposed CSD is the small inductance (typically, 20 nH at 1 MHz switching frequency). This translates into the footprint reduction of as much as 90% compared with the continuous CSDs. Other features of the proposed CSD includes: 1) fast switching speed and reduced switching loss; 2) discontinuous inductor current with low circulating loss; 3) gate energy recovery; and 4) wide range of duty cycle and switching frequency. The experimental results verified the functionality of the proposed CSD. At 12 V input, 1.3 V output, and 1 MHz switching frequency, the new CSD improves the efficiency from 80.7% using a conventional driver to 85.7% at 25 A output, and at 30 A output, from 77.9% to 84.4%.
Effect of Plated Metal Film on the Performance of Helix TWT Slow-Wave Structure

The effect of the plated metal film on the heat dissipation capability and cold-test characteristics of the helix slow-wave structure (SWS) have been studied in several experimental tests and computer simulations. The thermal conduction and the power losses of the helix SWS were improved by using a plated helix. A brazed SWS with end-plated rods exhibits excellent heat dissipation capability. The side-plated rods affect the cold-test characteristics of the SWS.
A study on middle school chemistry teachers' self-regulated learning behavior sample from Handan

Taking a holistic approach to stratified sampling, this research tries to find out the status of Handan middle school chemistry teachers' self-regulated learning behavior. The results show that the status of behavior is diverse. The most common way of teachers' self-regulated learning are imitate study, study with a teacher and professional dialogue. However, lack of critical thinking. Difference research shows that the characteristics of self-learning behavior is same between male and female teachers, between junior high and high school teachers, between city and county teachers. But the young teacher self-learning behavior better than the old teacher.
A New Dual-Channel Resonant Gate Drive Circuit for Low Gate Drive Loss and Low Switching Loss

At high-frequency applications, the gate drive loss of the power metal oxide semiconductor field-effect transistor (MOSFET) becomes quite significant. A new dual-channel low side resonant gate drive circuit is proposed in this paper. The proposed drive circuit can provide two symmetrical drive signals for driving two MOSFETs. It charges and discharges the MOSFET gate capacitor with a constant current source. Both gate drive loss and, more importantly, switching loss can be reduced significantly. The proposed resonant gate drive circuit can be used to drive the synchronous MOSFETs in a current doubler or full-wave rectifier configuration. It can also be used to drive the primary MOSFETs in push-pull converters. Analysis, computer simulation, and experimental results show that significant power loss reduction is achieved by the proposed circuit.
A New Digital Control Algorithm to Achieve Optimal Dynamic Performance in DC-to-DC Converters

In this paper, a new control algorithm is proposed to achieve optimal dynamic performance for dc-to-dc converters under a load current change and for a given set of circuit parameters, such as the output inductor, output capacitor, switching frequency, input voltage, and output voltage. Using the concept of capacitor charge balance, the proposed algorithm predicts the optimal transient response for a dc-to-dc converter during a large signal load current change. During steady state operation, conventional current mode proportional-integral-derivative (PID) is used. During large signal transient conditions, the new control algorithm takes over. The equations needed to calculate the transient time and the required duty cycle series are presented. By using the proposed algorithm, the optimal transient performances, including the smallest output voltage overshoot/undershoot and the shortest recovery time, is achieved. In addition, since the large signal dynamic response of the power converter is successfully predicted, the large signal stability is guaranteed. Experimental results show that the proposed method produces superior dynamic performance over a conventional current mode PID controller.
A credibility method to fuzzy generalized data envelopment analysis

Data envelopment analysis (DEA) is an effective technique for measuring the relative efficiency of a set of homogeneous decision-making units (DMUs). The generalized data envelopment analysis (GDEA) model, which contains four basic DEA models, is an important DEA model. When calculating the efficiency of each DMU, the GDEA model requires crisp input and output data, which are often difficult to obtain in real-world problems. In this paper, we will employ the credibility theory and chance-constrained programming to evaluate the efficiency of each DMU in fuzzy GDEA (FGDEA) model. We first introduce the credibility GDEA (CGDEA) model, and then discuss its crisp equivalent form in some special cases. At last, a numerical experiment is given to illustrate the efficiency of the CGDEA model.
A Practical Switching Loss Model for Buck Voltage Regulators

In this paper, a review of switching loss mechanisms for synchronous buck voltage regulators (VRs) is presented. Following the review, a new simple and accurate analytical switching loss model is proposed for synchronous buck VRs. The model includes the impact of common source inductance and switch parasitic inductances on switching loss. The proposed model uses simple equations to calculate the rise and fall times and piecewise linear approximations of the high-side MOSFET voltage and current waveforms to allow quick and accurate calculation of switching loss in a synchronous buck VR. A simulation program with integrated circuit emphasis (Spice) simulations are used to demonstrate the accuracy of the voltage source driver model operating in a 1-MHz synchronous buck VR at 12-V input, 1.3-V output. Switching loss was estimated with the proposed model and compared to Spice measurements. Experimental results are presented to demonstrate the accuracy of the proposed model.
A comparison study of low-dose CT image reconstruction strategies by adapted weighted total variation regularization

This paper aims to investigate the iterative reconstruction problem of low-dose computed tomography (LDCT) by adapted weighted total variation (AwTV) regularization. The motivation is based on the observation that statistical iterative reconstruction (SIR) has shown improvement of image quality in reconstruction from low-mA cone-beam CT (CBCT). More specifically, the iterative algorithm of projection onto convex set with total variation regularization (TV-POCS) has demonstrated the gains in image reconstruction from sparse angle projection data for LDCT imaging. Two approaches related to the sparse concept for LDCT imaging were investigated, one is AwTV constrained penalized weighted least-squares (AwTV-PWLS) and the other is AwTV-POCS. These two approaches were compared by experimental data from CatPhan® 600 phantom and anthropomorphic head phantom at the following conditions: (1) low-mA full view projection data, (2) normal-mA sparse view projection data, and (3) low-mA sparse view projection data. The comparison was based on the visualization evaluation and the quantitative measurements using the contrast-to-noise ratios (CNRs) merit and full-width at half-maximum measurement (FWHM) on selected regions-of-interest (ROIs) from the reconstructed images. The results indicated that the AwTV-PWLS approach can outperform the AwTV-POCS for condition (1) at 10 mA level, while the AwTV-POCS algorithm has advantages for condition (2) at 80 mA level. Under the condition (3) at 10 mA level, both approaches could not yield satisfactory images. These results concur with the expectation from the theoretical models of these two approaches. The AwTV-PWLS emphasizes the data fidelity term with weighted TV penalty and is more robust for data noise while the AwTV-POCS emphasizes the sparsity nature and requires good data constraints. While the AwTV-POCS seems to serve the purpose of weighted TV minimization, a remaining open question for AwTV-PWLS is whether the weighted TV penalty is an optimal choice for the PWLS minimization. Further evaluation is needed to answer this open question.
A Novel Reduction Method for Text-Independent Speaker Identification

SVM is a novel statistical learning method that has been successfully applied in speaker recognition. However, Extractive feature vectors from the speech are overlapped and noisy is included in the original data space, these problems can lead to experience difficulties, training complication during training SVM, and the result will be reduced during the recognition phase. In this paper, a novel method is proposed to reduce the noise and input vectors of the SVM. Firstly data dimensions are reduced and noise is removed by using PCA transform, secondly feature data are selected at boundary of each cluster as SVs by using Kernel-based fuzzy clustering technique. The training data, time and storage can be reduced remarkably compared with traditional SVM; the speaker identification system based on our proposed reduced support vector machine (RSVM) has better robustness compared with other reduced algorithms.
A 5s-time-constant temperature-stable integrator for a tuneable PID controller in LOC applications

In this paper, we present a novel, ultra-long-time-constant analogue integrator for a PID controller in Lab-on-Chip (LOC) applications. A time constant of up to 5 seconds is achievable using a capacitance of only 18pF by exploiting transconductance reduction techniques involving current splitting and gm-attenuated OTA. Additionally, this architecture provides the ability to digitally tune the time constant from 200ms to 5s with 4-bit programmability. The design achieves a temperature dependance of 1.2% over the range from 0°C to 100°C with micropower consumption.
A unified framework for automatic quality-of-experience optimization in mobile video streaming

Mobile video streaming is one of the fastest growing applications in the mobile Internet. Nevertheless, delivering high-quality streaming video over mobile networks remains a challenge. Researchers have since developed various novel streaming algorithms such as rate-adaptive streaming to improve the performance of mobile streaming services. However, selection or optimization of streaming algorithms is far from trivial and there is no systematic way to incorporate the tradeoffs between various performance metrics. This work aims at attacking the heart of the problem by developing a novel framework called Post Streaming Quality Analysis (PSQA) to automatically tune any streaming algorithms to maximize a given quality-of-experience (QoE) objective. We show that PSQA not only can be applied to optimize the performance of existing streaming algorithms, but also opens a new way for the exploration of new adaptive video streaming protocols and QoE metrics. Simulation results based on real network throughput traces show that PSQA can optimize existing and new streaming algorithms to achieve QoE that is remarkably close to the optimal achieved using brute-force method ex post facto.
Design and implementation of a Chinese character teaching system based on augmented reality interaction technology

In this paper, we design and realize an augmented reality interaction framework. A linear interpolation algorithm in an adaptive spatial grid is proposed to calibrate the magnetic tracker, and the calibrated data is used for registration of the user's viewpoint and the virtual objects. An optimized collision detection algorithm based on Vclip is adopted. Additionally, grasp gesture recognition algorithm based on rough sets theory is presented to capture and recognize the user's hand operation. In order to make it easier to learn the new Chinese characters, a Chinese character teaching system based on the framework is developed. The experimental results show that, in the teaching system, the user's immersion feeling is enhanced to a great extent by the accurate and natural human-computer interaction, which promotes the efficiency of learning new Chinese characters.
A comparison study on KL domain penalized weighted least-squares approach to noise reduction for low-dose cone-beam CT

Dose reduction is a major task for cone-beam computed tomography (CBCT) applications because of the potential side effect of X-ray exposure to the patients. One of the strategies to achieve low-dose is to lower the X-ray tube current and/or shorten the exposure time in CT scanners. However, the image quality from the low mAs acquisition is severely degraded due to excessive quantum noise. In this work, we investigated three implementations of Karhunen-Loeve domain penalized weighted least-squares (KL-PWLS) scheme to adaptively treat the noise in the low-mAs CBCT sinograms. The motivation is based on the observations that strong data correlation exists between neighboring views and neighboring slices in CBCT and the KL transform can de-compose the correlated signals for adaptive noise treatment. The three implementations were: (1) performing the KL transform among neighboring views and reduce the three-dimensional (3D) noise-treatment procedure into a series of 2D operations, (2) performing the KL transform among neighboring slices in the 3D space, and (3) performing the KL transform on a view-by-view manner along the slice direction for sparse data sampling which actually reduces the procedure into a series of 1D operations. The noise-treated sinogram data were then reconstructed by the analytical Feldkamp-Davis-Kress (FDK) algorithm. The effectiveness of the presented KL-PWLS noise reduction strategy was evaluated using two physical phantoms (CatPhan600® and anthropomorphic head). Noise in the reconstructed CBCT-FDK images from a low 10mA protocol was greatly suppressed without noticeable sacrifice of the spatial resolution compared with those from a high 80mA protocol, which implies a potential dose reduction by as high as a factor of 8 for the two phantoms. The noise-resolution tradeoff curves indicate that the KL-PWLS implementations considering the neighboring slices (implementation 2 and 3) outperform that considering the neighboring views (implementation 1) in better resolution preservation at the same noise level, which is probably due to the structural continuity among neighboring slices. For further dose reduction by sparse data sampling, implementation (3) can be a potential choice attributed to its computational advantages over the other two implementations.
An average current modulation method for single stage LED drivers with high power factor and zero low frequency current ripple

Conventional single-stage AC-DC LED drivers with a high power factor contain significant LED current ripple at twice the AC line frequency, and require large energy storage capacitors to limit the effect on LED light. Conventional designs and novel control techniques aim to power LED loads with a DC voltage to ensure a limited low frequency current ripple. This paper proposes an average current modulation method that is capable of driving LEDs from a voltage that contains significant AC ripple, while maintaining zero low frequency current ripple. This allows the energy storage capacitance of the PFC stage to be reduced, avoiding the need for electrolytic type capacitors, and prolonging the life of the LED driver. The average current modulation circuit requires a single low voltage MOSFET, a current sense resistor and a simple control circuit. By requiring no additional magnetic components, the cost of the average current modulation circuit is very low, and has minimal impact on the efficiency of the overall LED driver. A 25 W experimental prototype with a Flyback PFC converter has been built to verify the capability and excellent performance of the proposed driving technique.
Application of the Time-varying Outage Model of electric transmission and transformation equipment in Condition-based Maintenance

Condition-Based Maintenance (CBM) of the electric transmission and transformation equipments has been carried out gradually in the State Grid Corporation of China (SGCC). Equipments' risk assessment is a challenging work during implementing CBM, because the failure probabilities of equipments may vary with changes in the operating conditions, and hard to predict accurately. In this paper, the Time-Varying Outage Model (TVOM) of equipments is applied in the risk assessment to solve the above difficults. To demonstrate the necessity and efficiency of the TVOM, a numeral test on transformer was given to compare the result of the statutory method in SGCC standard and that of the time-varying outage model.
An Evolved Skeleton-Network Reconfiguration Strategy Based on Topological Characteristic of Complex Networks for Power System Restoration

The restoration of a power system following large-scale blackouts is a key issue to the safety of power systems. Reconstructing the reasonable skeleton-network is an effective means of establishing the main network and restoring loads quickly. Based on the topological characteristic of complex networks, an evolved skeleton-network reconfiguration strategy is proposed in this paper. Employing line betweenness as well as node importance degree and clustering coefficient, the evolved strategy refines the index named network reconfiguration efficiency, which aims to select key nodes and key lines into the target network while keeping its sparseness in order to alleviate the burden of reconfiguration. Then, discrete particle swarm optimization is used in realizing the evolved strategy. Application to the IEEE 57-bus power system verifies that skeleton network derived from the evolved strategy includes not only all critical nodes but also most critical lines thereby highlighting the main task of reconfiguration.