nils-herrmann/clean_scirepeval huggingface dataset:
An approach for generating high velocity and high acceleration trajectories of industrial robots

For fast-motion industrial robots, the limits of the velocity and the acceleration vary over the whole work-space. To make industrial robots move with fully high velocity and high acceleration along the specified trajectory in the entire workspace, a trajectory generation technique for fast-motion industrial robots is presented in this paper. The maximum possible values of the velocity and the acceleration along the specified trajectory are firstly investigated, in consideration of the speed and torque limits of the actuators. Then, based on these maximum velocity and maximum acceleration, the proposed technique generates various motion profiles by using coefficients which are determined by the acceleration and deceleration characteristics. Finally, the experiment is conducted to confirm the proposed technique by commanding a two-degree-of-freedom (2-DOF) direct-drive planar parallel robot to move along the trajectories with the unsymmetrical smooth motion profile generated by the proposed technique.
A computational study of dopant-segregated Schottky barrier MOSFETs

Recently a novel device structure called dopant-segregated Schottky barrier MOSFETs (DSS SBTs) has been proposed where the Schottky barrier height can be significantly reduced thus achieving much larger drain currents. Although quite a few experimental studies have been performed on this structure, further investigation on the carrier transport mechanism is required for the optimization of device design. In this work we investigate the 45-nm SOI dopant-segregated SBTs by Monte Carlo method. The feature that DSS structure can improve on-current is revealed. The influence of the DSS parameters on devices performance is also investigated.
A practical control strategy to improve unloading transient response performance for buck converters

In this paper, a practical control strategy is presented which is capable of controlling a 12V–1.5V Buck converter and an auxiliary converter to achieve significantly improved unloading response performance. The auxiliary circuit is controlled by peak current mode method for a predictable number of auxiliary switching, while the charge balance controller minimizes the settling time of the Buck converter. In the proposed strategy, a good tradeoff has been made (between the trends to further suppress the voltage overshoot and reduce the power loss). Furthermore, analysis of the auxiliary circuit power loss and the improved output voltage overshoot has been conducted as a design guideline. Finally, simulation and experimental results are provided to verify the proposed scheme on a 12V–1.5V 10A Buck converter prototype.
Application Research of Vibration and Noise Test and Analysis System in High Speed Railway Passenger Car

The railway passenger car speed enhancement and car body lightweight development could cause insufficient stiffness and poor sound insulation of the railway passenger car body. Thus, the passengers ride comfort decreases. The vibration tests of the high speed railway passenger car are completed using the HEAD acoustics multi-channel vibration test and analysis system. The vibration characteristics of the different test points of the railway passenger car under different speeds are obtained. When the passenger car speed is 200 kilometers per hour, the vibration of the side wall in the middle of the car body is higher than that of the side wall in the end of the car body and the peak frequency are near 70 Hz. The car’s snake movement increases with the speed goes up and the transverse vibration appears. The conclusions provide the bases for noise and vibration research and control of the high speed railway passenger car.
Chaotic Parallel Genetic Algorithm with Variable-Scale Learning and Balancing Strategy of Ranking Individuals

Keeping balance between the diversity of population and the convergence of evolution for genetic algorithm remains a work of art. It is well known that the chaotic mapping helps to maintain good diversity for population and Baldwin effect based posterior learning promotes evolution along the right direction, thus forming chaotic parallel genetic algorithm with Baldwin learning (CPGABL). In this paper, two critical improvements are introduced into our previous works about CPGABL: first, balancing strategy of ranking individuals is adopted to guarantee first the diversity of population and then the convergence of algorithm; second, rearrangement to chaotic sequences is redesigned to maintain both good diversity and appropriate computational complexity. Performances of this enhanced CPGABL and our previous works are compared on a benchmark constrained nonlinear optimization problem.
A Unified Approach to Adaptive Neural Control for Nonlinear Discrete-Time Systems With Nonlinear Dead-Zone Input

In this paper, an effective adaptive control approach is constructed to stabilize a class of nonlinear discrete-time systems, which contain unknown functions, unknown dead-zone input, and unknown control direction. Different from linear dead zone, the dead zone, in this paper, is a kind of nonlinear dead zone. To overcome the noncausal problem, which leads to the control scheme infeasible, the systems can be transformed into a $m$ -step-ahead predictor. Due to nonlinear dead-zone appearance, the transformed predictor still contains the nonaffine function. In addition, it is assumed that the gain function of dead-zone input and the control direction are unknown. These conditions bring about the difficulties and the complicacy in the controller design. Thus, the implicit function theorem is applied to deal with nonaffine dead-zone appearance, the problem caused by the unknown control direction can be resolved through applying the discrete Nussbaum gain, and the neural networks are used to approximate the unknown function. Based on the Lyapunov theory, all the signals of the resulting closed-loop system are proved to be semiglobal uniformly ultimately bounded. Moreover, the tracking error is proved to be regulated to a small neighborhood around zero. The feasibility of the proposed approach is demonstrated by a simulation example.
Adaptive Fuzzy Output Feedback Control for a Class of Nonlinear Systems With Full State Constraints

In the paper, the adaptive observer and controller designs based fuzzy approximation are studied for a class of uncertain nonlinear systems in strict feedback. The main properties of the considered systems are that all the state variables are not available for measurement and at the same time, they are required to limit in each constraint set. Due to the properties of systems, it will be a difficult task for designing the controller and the stability analysis. Based on the structure of the considered systems, a fuzzy state observer is framed to estimate the unmeasured states. To ensure that all the states do not violate their constraint bounds, the Barrier type of functions will be employed in the controller and the adaptation laws. In the stability analysis, the effect caused by the constraints for all the states can be overcome by using the Barrier Lyapunov functions. Based on the proposed control approach, it is proved that the system output is driven to track the reference signal to a bounded compact set, all the signals in the closed-loop system are guaranteed to be bounded, and all the states do not transgress their constrained sets. The effectiveness of the proposed control approach can be verified by setting a simulation example.
Black start scheme formation considering dynamic wind power penetration limit

While the modern electric power system benefits a lot from the large-scale interconnection, it takes the potential risk of massive outages coming from natural disasters, equipment failures and maloperations. The large-scale wind power integration of new energy has exacerbated the risk, which increases the demand of designing Black Start (BS) schemes in advance to reduce the outage loss. However, the traditional BS units, such as hydraulic turbine and gas turbine, are decreasing with the growing permeability of the new energy in the power system. In order to explore the BS capability of the power system containing renewable energy, we study the application of wind power in BS. First, the concept of Dynamic Wind Power Penetration (DWPPL) is proposed, which can represent the maximum capacity of system to accommodate wind power at a certain moment in BS process; Then, the mathematical model and Chance Constrained Programming (CCP) method for solving DWPPL are presented, and the BS scheme based on DWPPL is established; At last, the IEEE 14-bus system with wind-storage module is constructed on the PSCAD simulation platform, which verifies the feasibility and value of the above method.
A study of application of color — Based upon GUI

With the popularization of digital products in modern society, the present popular software interface cannot meet individualized needs of customers. So the customization of the interface image has become a new trend. This paper will conduct a systematic study of graphic interface from the viewpoint of user's experience by employing chart analysis and color vision-related theories, elaborate the interactive function and principles of application of color-matching law in the GUI design in hope to provide theoretical support for the color development of GUI designers.
Characteristics of different structure sub-100nm MOSFETs with high-k gate dielectrics

The extensive simulations are carried out to study impact of high K dielectric both on the channel and the source/drain extension region of a typical 70nm MOSFET by the two dimensional device simulator ISE. The key factors affecting the device characteristics are investigated. The different structures of high K gate dielectric MOSFETs including SOI MOSFET and recess channel MOSFET are also simulated.
Application of Pre-corrected FFT in Statistical Power Analysis considering spatial correlations

In this paper, we introduce the Pre-corrected FFT (PFFT) algorithm in Statistical Power Analysis of CMOS ICs. We implemented PFFT to compute the Matrix Vector Product (MVP), resulted from the process of deducing the standard deviation of leakage current. To analyze power consumption statistically in a chip of N gates, the application of PFFT can reduce the computation complexity from O(N2)to O(Nlog2N). While maintaining an acceptable errors (less than 1%), the proposed method can dramatically accelerating the computation.
A study on stochastic determination model in optimal water resources allocation for irrigation district

Jinghuiqu Irrigation District is a typical irrigation district using both wells and canals to irrigate crops. In recent years, the groundwater level presents a declining trend because of unreasonable utilization, which leads to a series of environmental geological problems. Therefore, it is significant to study how to develop and utilize groundwater resources rationally as well as to optimize allocation of irrigating water for irrigation area with the application of well-canal combination. According to the hydro-geological conditions of irrigation district, the paper sets up a groundwater stochastic-determination model (GSDM) using Visual Modflow. In the model, groundwater level are predicted and analyzed. Based on above analysis results, the paper performs further study on the pattern of water utilization in irrigation district. The results provide a basis for sustainable development and utilization of groundwater and optimal allocation of water resources in irrigation districts.
Compact Model of HfOX-Based Electronic Synaptic Devices for Neuromorphic Computing

HfOx-based resistive switching device has been explored as one of the promising candidates for the electronic synapses of neuromorphic computing systems due to its high performance, low cost, and compatibility with CMOS technology. To meet the codesign requirement of HfOx-based electronic synapses with CMOS neurons in the neuromorphic computing systems, a compact model that can capture the synaptic futures of HfOx-based resistive switching device is developed. The developed model can accurately describe the multilevel conductance transition behaviors during RESET process for depression learning as well as the binary stochastic transition behavior during SET process for potentiation learning. After the verification with experimental data, the model is used to simulate a winner-take-all neural network to classify patterns with unsupervised competitive learning algorithm. Simulation results imply that the average recognition accuracy would decrease with the increase of the resistance variation of low resistance state (LRS) due to the “trap” effect. Guided by the simulation, a synapse cell consisted of a HfOX-based device and a fixed resistor series connection is proposed to achieve almost 100% recognition accuracy even if the resistance variation of LRS is 50%.
Convergence characteristics of PI-type iterative learning control for linear time-invariant systems

The paper exploits the convergence characteristics of the first- and second-order PI-type iterative learning control (ILC) schemes for linear time-invariant (LTI) systems with direct-through terms. The aim is to investigate the effects of the integration embedments into the conventional P-type ILC rule. In the exploitation, the tracking errors are assessed in the form of the Lebesgue-p norm and the convergences are derived in virtue of the generalized Young inequality of convolution integral. The derivations convey that the convergence monotonicities are guaranteed for the first-order PI-type ILC. At the same time, the convergence is ensured for the case when the second-order PI-type ILC is implemented on the systems. Numerical simulations testify the validity and of the proposed schemes.
A new current-source gate driver for a buck voltage regulator

A new current-source gate drive circuit is proposed for a synchronous buck voltage regulator (VR). The proposed driver can drive two MOSFETs independently with different drive currents for optimal design. Furthermore, the new drive circuit can achieve 1) significant switching loss reduction; 2) gate energy recovery; 3) reduced body diode losses and reverse recovery losses; 4) ZVS of all the drive switches. The improved driver using integrated inductors is also presented for a buck VR to reduce the number of magnetic cores and the core loss. The experimental results prove that a significant efficiency improvement has been achieved. At 1.5V output, the new driver improves the efficiency from 84% using a conventional driver to 87.3% (an improvement of 3.3%) at 20 A, and at 30 A, from 79.4% to 82.8% (an improvement of 3.4%). Overall, the new driver approach is very attractive from the standpoints of both performance and cost-effectiveness.
A Neural Network Model for Concept Formation

Acquisition of abstract concept is the key step in human intelligence development, but the neural mechanism of concept formation is not clear yet. Researches on complexity and self organization theory indicate that concept is a result of emergence of neural system and it should be represented by an attractor. Associative learning and hypothesis elimination are considered as the mechanisms of concept formation, and we think that Hebbian learning rule can be used to describe the two operations. In this paper, a neural network is constructed based on Hopfield model, and the weights are updated according to Hebbian rule. The forming processes of natural concept, number concept and addition concept are simulated by using our model. Facts from real neuroanatomy provide some evidences for our model.
An adaptive current mode fuzzy logic controller for DC-to-DC converters

This paper introduces a new fuzzy logic controller (FLC) using inductor current feedback for significantly improving the dynamic performance of DC-to-DC converters. Inductor current plays an important role in high performance DC-to-DC converter control and FLC is suitable to deal with time-varying nonlinear nature of power converters. Based on the feedback of the inductor current, the new control method combines the merits of both the conventional FLC and current mode control. The dynamic performance of power converter system is improved. Furthermore, in order to enhance system robustness and adaptability, a new nonlinear configuration called extended state observer (ESO) is developed. By using ESO, the influence of load disturbances and parameter changes are precisely estimated and compensated without accurate knowledge of converter parameters. Simulation results have demonstrated that the proposed methods ensure good robustness and adaptability under modeling uncertainty and external disturbance, such as load current variation, supply voltage changes and converter parameter changes. It is concluded that the proposed topology produces substantial improvement of dynamic performances such as small overshoot, more damping and fast transient time under different operating conditions. In addition, small signal frequency response analysis demonstrates that by using the proposed FLC, the bandwidth and phase margin of the closed loop system have been significantly increased.
A Hybrid Markov Model Based on EM Algorithm

Order-k Markov model can be used in many fields such as natural language understanding, coding, mobile path prediction and so on to make prediction and then control. But the model has to face the problem of state space expansion. Taking the mobile path prediction as the research background, the paper firstly proposes a step-k Markov model and validates its feasibility. Secondly, a hybrid Markov predictor model is put forward based on the step-k Markov model. The complexity of the hybrid Markov model is O(N) while the order-k Markov model is O(N2 ). And the memory demand of the hybrid Markov model is O(N2 ) while order-k Markov model is O(N3). Finally, it is proved that the hybrid Markov predictor can get close performance with order-k Markov predictor at much lower expense by conditional entropy analysis and user mobility data analysis. Also it can alleviate the zero probability problem in order-k Markov model to some extent. The hybrid Markov predictor is more practical than order-k Markov predictor under WLAN
Automatic current-sharing method for multi-phase LLC resonant converter

An automatic current sharing method is proposed for multi-phase LLC resonant converter for high power application. There are two types, one is common inductor, and the other is common capacitor. Automatic current sharing is achieved by using a common component for all LLC resonant stages. The proposed method can automatically share the load current without any additional circuit and control strategy. The current share performance of the proposed method is analyzed under Fundamental Harmonic Analysis (FHA) assumption. A 600W two-phase LLC converter prototype based on the proposed method is built to verify the feasibility. Excellent current sharing performance has been achieved.
An approach to dynamic fingerprint image enhancement

A new algorithm of fingerprint enhancement is presented. Gabor filter and oriented filter are used to enhance the fingerprint images in two steps. First a dynamic 2-D Gabor filter is used to separate the conglutinated ridgelines, and then a well-defined oriented filter is used to joint the ruptured ridgelines and clean up the valleys. The new method is not sensitive to the offset and the rotation of fingerprint image, and easy to realize. The experiments show good performance.
Compact triple-band high-temperature superconducting filter using coupled-line stepped impedance resonator(C-SIR)

A compact triple-band high temperature superconducting (HTS) filter using coupled-line stepped-impedance-resonator (C-SIR) has been proposed in this paper. The resonant characteristics of the C-SIR are investigated by the even/odd-mode analysis. Owing to the coupled-line feed-lines structure, multiple transmission zeros are created to improve the selectivity of the filter. The resultant filter shows a competitive merit in size miniaturization. For demonstration purposes, a triple-band filter operating at 1.57GHz (GPS band), 3.5GHz (WIMAX band), and 5.5GHz (WLAN band) is designed, fabricated, and measured. Good agreement between the simulated and the measured results is observed.
A dual-channel isolated resonant gate driver for low gate drive loss in ZVS Full-bridge converters

As the switching frequency increases, to reduce the gate drive loss combined with the Zero-Voltage-Switching (ZVS) technique is meaningful for the widely used Full-Bridge (FB) converters. A dual-channel isolated Resonant Gate Driver (RGD) is proposed in this paper. The proposed RGD is able to provide two isolated complementary drive signals for two power MOSFETs in one bridge leg. Furthermore, the proposed RGD reduces about 79% gate drive loss compared to the conventional Voltage Source Driver (VSD). In addition, the negative gate drive voltage provided by the proposed RGD prevents the false trigger problem. The optimum design of the proposed RGD is given in detail. A 200-VDC input, 48-V/20-A output and 500-kHz phase-shift ZVS FB converter with the proposed RGD was built to verify the advantage and efficiency improvement.
Echo Model Analyses and Imaging Algorithm for High-Resolution SAR on High-Speed Platform

The “stop-go” approximation is widely used for the processing of synthetic aperture radar (SAR) data, and the error brought by this assumption can be negligible for most SAR systems. However, for the SAR on a high-speed platform, with the increasing requirements on high-resolution imaging, the error may be intolerable for SAR imaging. In this case, the radar motion within a pulse repetition interval should be taken into account for the echo model and imaging algorithm. In this paper, according to the geometric configuration of the SAR working process, an accurate echo model is presented. By comparing the “stop-go” echo (which denotes the echo based on the “stop-go” approximation in this paper) with the accurate echo, the error brought by the “stop-go” approximation is introduced, and the intolerable error is shown in a reference system. A spotlight imaging algorithm based on the accurate echo is given and is well supported by the simulation results.
Cost-Effective Schottky-Barrier Diode Array With Ni–Silicidation Accessing Low Power Phase-Change Memory

A cost-effective fabrication of Schottky-barrier (SB) diode steering element for low power phase-change memory (PCM) application is realized. While superior drivability in conventional PN diode array, SB diode array with 0.0193- μm2 (5F2), performing higher switching speed, sufficient drive current density of ~ 26.30 mA/μm2, disturbance immunity, and lower power consumption has been manufactured under 40-nm standard complementary metal oxide semiconductor technology. Simultaneously, different performance specifications, including integration scheme, JON/JOFF ratio, temperature characteristics, and scalability have been studied in detail and compared in two categories of accessing diode arrays. It manifests that the scaled SB diode array is suitable for full operation of PCM.
An efficient scheme for analyzing unloading process

As the air bearing flying height (a few nanometer levels) and the deformation of suspensions (micro-or millimeter level) run at two different scales, a dual-scale model for head disk interface (HDIs) has been proposed to analyze the unloading behavior of a subambient pressure slider. With the scheme developed, the unloading process can be simulated efficiently. The nonlinear vibrations of the air bearing forces and moments were described with analytical expression obtained from a surface fitting scheme. Combined with a 3 degree of freedom (DOF) suspension model whose parameters were estimated from a comprehensive FEM and experiments are applied to verify the value. The results from the FEM and the experiments are comparable and acceptable for simulations.