nils-herrmann/clean_scirepeval huggingface dataset:
Dehazing with improved heterogeneous atmosphere light estimation and a nonlinear color attenuation prior model

In this paper, we propose an improved heterogeneous atmosphere light estimation method and a novel depth estimation algorithm with Color Attenuation Prior (CAP) to dehaze single image. Firstly, it estimates the atmosphere light with mean-pooling on the illuminance component from HSV color space. The estimated atmosphere light is more robust because of its independence of a specified pixel. Secondly, the scene depth is estimated by a nonlinear CAP model which can overcome the defects of the occurrence of negative scene depths from the linear CAP model. Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art methods in dehazing images.
Enhancing Secured Coverage With CoMP Transmission in Heterogeneous Cellular Networks

This letter addresses the problem of secured coverage under the concept of physical layer security in heterogeneous cellular networks operating with coordinated multipoint transmission (CoMP). A dynamic CoMP scheme for the legitimate users is proposed to enhance secured coverage. A performance analysis of secured coverage probability (SCP) is conducted for the proposed scheme, considering co-channel interference and the most threatening eavesdroppers. Numerical and simulation results are provided along with the no-CoMP scheme. It is revealed that with a proper base station selection threshold, the proposed CoMP scheme improves the SCP performance compared with the no-CoMP scheme (23.5% on average according to simulation results), and shows superiority in resisting more eavesdroppers as well.
Statistical models for microwave GaN HEMTs

Statistical model of semiconductor field effect device is important for yield analysis. In this paper, the large signal statistical characterization of GaN HEMTs is modeled based on empirical equivalent circuit model. First, the parameters of small signal and large signal equivalent circuit model are extracted by in-house extraction program based on 10 batches GaN HEMTs. Then, the statistical model is fulfilled by combining principal component analysis, factor analysis, and multiple regressions modeling techniques. Finally, the statistical model is implemented in Agilent-ADS and validated by comparison between Monte Carlo simulation and measurement results. Furthermore, two S-band GaN HEMT power amplifiers are designed by using the established statistical model for demonstration purpose. The results show that good accuracy has been achieved between measurement results and Monte Carlo simulation results. The proposed method will be useful for GaN device yield optimization.
The construction of the specialty of information management and information system based on CDIO mode

CDIO is an innovative mode of higher engineering education at home and abroad in recent years, giving twelve operational standards concerning cultivation of abilities, implementation in all aspects and assessment, which will be a very good reference to the existing education in colleges. This article is guided by the mode of CDIO, discussing the reform in the construction of the specialty of information management and information system from teaching philosophy, teaching objectives, curriculum system, teaching methods and assessment.
Kinematics modeling and step climbing study of an all-terrain wheeled mobile robot on uneven terrains

In this paper, a study of an all-terrain wheeled mobile robot which is a complex multi-body mechanism is presented. An effective approach for kinematics modeling of the robot traversing uneven terrain has been proposed. Denavit-Hartenberg algorithms and differential kinematics are derived for the individual wheel motions in contact with the terrain. The resulting equations of the individual wheel motions are then combined to form the composite equation for the rover motion. The motion study of the rover for step climbing is also presented. Simulation and experimental results have been employed to verify the rover mobility.
A Mesh Deformation Method for Aeroelastic Simulation

A simple and efficient mesh deformation method is proposed for time-based nonlinear aeroelastic simulation via CFD/CSD coupling in this paper. With concerned characteristic of multi-structured block, the part of multi-block deformation is studied. A grid deformation technology is developed to fit for the calculation of complex aircraft configuration structure response to nonlinear aeroelastic. The position of structure deformation and large structure deformation of complex aircraft configuration is studied. The results indicate that the application of the technology used in complex aircraft configuration time-based aeroelastic simulation is an effective way to simulate the unsteady flow problems due to boundary deformation.
State Assessment System of Power Transformer Equipments Based on Data Mining and Fuzzy Theory

The state assessment system of power transformer equipments based on data mining and fuzzy theory is introduced briefly in this article. The statistics-based association rule mining will be used as data preprocessing method. Assess model of power transformer equipments is created according to standards of Transformation Condition-Based Maintenance equipment which is carried out by State Power Grid on May 1, 2005, test data are treated with fuzzy comprehensive evaluation, then a software platform that includes functionality to collect and store experimental data, analyze data and trend, generate assessment report and put forward suggestions on repairing of transformer equipment status is built.
A novel compact Ka band fourth-harmonic image rejection mixer

Wth the commercial 0.15-μm pseudomorphic high electron mobility transistor (pHEMT) process, a novel compact Ka-band fourth-harmonic image rejection resistive FET mixer is designed in this paper. A compact Balun with two scale-down Lange couplers used for the impedance transformation is proposed for LO signal pump. The results show that less than 19.5 dB Conversion Loss (CL) in 32~38 GHz, more than 21 dB Image Rejection Ration (IRR) in 32~36.5 GHz, and better than 30 dB and 42 dB high isolation, from LO to RF and 4LO to RF, respectively, can be achieved by the proposed configuration. The chip size is minimized to 1.8 mm×1.4 mm.
A Multiproduct Duopolistic Pricing Model in Network Convergence

In order to solve the multiproduct pricing problem of telecommunication operators in network convergence, a duopolistic model is used in this paper. We introduce a two dimensional Bertrand duopoly game model to discuss multiproduct pricing problem in the case that two operators offer two kind of alternative products who have full overlay networks, and consider the impact of network externalities on pricing. Our research shows that multi-product operators who jointly consider the multi-product pricing will earn more than separately considering the single market during the course of making pricing decisions, especially when network externalities exist. Taking network externalities into account, the two dimensional Bertrand model can effectively solve the multiproduct pricing problem in network convergence, which provides a theoretical basis for telecommunication operators to make multiproduct pricing decisions.
Intelligent flight for UAV via integration of dynamic MOEA, Bayesian network and fuzzy logic

Intelligent flight is a key technology for an unmanned aerial vehicle (UAV) to react to the changing environment. Online path planning (OPP) is a basic issue for intelligent flight and is indeed a dynamic multi-objective optimization problem (DMOP). In this paper, we use an OPP scheme in the sense of model predictive control to continuously update the environmental information for the planner. This method is in fact a DMOP. For solving the problem at hand we propose a dynamic multi-objective evolutionary algorithm based on linkage and prediction (LP-DMOEA).Within this algorithm the historical Pareto sets are collected and analyzed to enhance the performance. For intelligently selecting the best path from the output (a set of Pareto solutions obtained by the LP-DMOEA) of the OPP, the Bayesian network and fuzzy logic are used to quantify the bias to each optimal objective. The experimental results show the LP-DMOEA works more effectively for OPP in contrast to the restart method and the intelligent methods for solution selection can automatically assess the changing environment and adapt the path planner.
High frequency noise performance of AlGaN/InGaN/GaN HEMTs with AlN interlayer

A systematic physical model of AlGaN/InGaN/GaN heterojunction high electron mobility transistors (HEMTs) is established, and a novel AlGaN/InGaN/GaN HEMT structure with AlN interlayer is proposed in this paper. Polarization effect, interface state, surface state, and traps are considered, and the 2D-numerical simulation results of AlGaN/InGaN/GaN HEMT fit the measured results well. The high frequency noise performance of AlGaN/AlN/InGaN/GaN HEMTs are studied based on the established model. The results show that, because of the enhancement of carrier confinement by inserting AlN layer, the minimum noise figure improved 0.5 dB at 8 GHz, the noise conductance reduced about 50%, and the cut-off frequency increased about 17%.
Level sets with one dot fuzzy initialization for marine oil spill segmentation

Image segmentation techniques are widely used for identifying marine oil spill regions in SAR images, with one representative technique being level set evolution. The accuracy of level set evolution highly relies on a proper initial level set function which roughly captures the marine oil spill layouts in a SAR image. However, marine oil spill regions are always complicatedly shaped, and it is time-consuming and impractical to manually devise precise initial level set functions for various marine oil spill shapes. In order to address this problem and achieve efficient and robust segmentation, we develop a one dot initialization scheme for level set evolution. Our method just requires an arbitrary pixel within one marine oil spill region as initialization. It exploits fuzzy connectedness between pixels such that consistent initial level set functions can be established via arbitrary initial dots within the marine oil spill region. Experimental results validates the robustness of our strategy.
A Research and Design of Ethernet Real-Time Application Bus Based on FPGA

The design scheme of hard real-time bus CANNet based on IEEE802.3 and CAN bus is proposed for the request of multi point high broadband information interchange in the distribution intelligent control system module interconnection.The CAN arbitration mechanism is added in the physical layer of ethernet network. Thus the CANNet bus not only hasEthernet network ,but also has the property of CAN buscompatible non-destroy formal bus arbitration and communication frame prior to race to control. The soft andhard testing platform of CANNet baset FPGA has been bulitup and the system has been tested, which verifies the feature of real-time and strong anti-interference ability of CANNet. The connection of real-time and non-real-time can be not only performed by using the uniform CANNet bus, but also used for the uniform standard interface of control module. It is of high practical value.
Incidence prediction of communicable diseases after the Wenchuan earthquake using remote sensing

Wenchuan in Sichuan Province, China, was hit by an 8.0 magnitude earthquake on 12 May 2008. Thousands of buildings were destroyed and thousands of people were hurt. History tells us that after earthquakes, floods and other natural disaster, infectious diseases often outbreaks. In this study, with the help of spatial information technologies including remote sensing and geography information system, we acquired environmental factors including population, earthquake intensity, route distance, direct distance, Normalized Difference Vegetation Index, Normalized Difference Water Index, and Digital Elevation Model for each township in Anxian after earthquake. Then we constructed a Back Propagation Neural Network to train environmental factors and incidence of communicable diseases, and predicted the incidence of communicable diseases. The results showed that incidence of communicable diseases after earthquake could be predicted using remote sensing to some extent.
Research on real-time quality inspection of PET bottle caps

Online quality inspection is an effective way to guarantee the quality of PET bottles packaging on the high-speed filling production line. This paper focused on studying and developing a machine vision inspecting system for on-line defects detection of PET caps without support rings. An image processing algorithm was proposed to detecting the serious defects such as surface foreign matters and link ring broken of the PET caps. For detecting the defect of surface foreign matters, the algorithm employed a mean filtering to estimate the background, then compared the inspected image with the background image by using dynamic threshold, as a result, the crack region was extracted. As to defect of link ring broken, the uneven gray-scale distribution in the RGB color space was extremely improved by HSV color space transform. Compared three components of HSV images, the gap feature between the cap and the link ring was more obvious in the saturation image. Hence, the gap region was extracted through segmenting the saturation image. Experiments demonstrate that the designed inspection system has an accuracy up to 97% and the speed up to 34000 bottles per hour.
Experimental Research on Mode Transitions of Atmospheric Pressure Helium Dielectric Barrier Discharge

The discharge mode transitions and the characteristics of atmospheric pressure dielectric barrier discharge in pure helium (He-DBD) are studied. Different discharge modes of He-DBD are clarified, including filament-diffuse mixed mode, filamentary mode, diffuse mode, and multichannels coupled mode. The transitions of different modes are explored by changing the gap width and applied voltage. According to the luminous structure of discharge [short exposure (100~300 ns) image], it is found that there should be only Townsend-like and glow-like discharges that appear in the above modes. In Townsend-like discharge, the secondary electron emission coefficient (SEEC) of dielectric is estimated. Based on which, a fluid model coupled with an external circuit is built to explain the He-DBD mode transitions mechanism and the applied voltage drop's influence on He-DBD. Through the temporal evolution of a luminous structure, a discharge filament is believed to be a contractive state of discharge channel, which should be an unstable glow-like discharge. The radius of discharge channel, changing with gap width and applied voltage, is measured. The discharge contraction is attributed to the nonlinear relationship between Townsend ionization coefficient and electric field. The enhancing interaction between different discharge channels inhibits the appearing of diffuse discharge around discharge filament, leading to the transition from mixed mode to filamentary mode. In the end, the multichannels coupled mode is proven to be glow-like discharge, and its formation mechanism is explained by the overlap of discharge channels.
The modeling of big traffic data processing based on cloud computing

The research progress of data acquisition technology and large data processing model has an important contribution to the development of urban traffic data. The control of urban transportation depends on the effective processing of real-time traffic observation data, which is usually the nature of data intensive. We study a large number of floating car data processing (FCD) traffic control in the cloud computing environment, to solve the problem of the new cloud computing technology to solve the problem of urban traffic control system. The experimental results show that the cloud computing technology such as HBase and MapReduce can provide big data flow calculation of substantial utility, such as scalability and real-time calculation performance can be accurately by our proposed data storage, management and parallel processing model. The applicability and practicability of cloud computing are evaluated for two typical data calculation tasks of urban traffic monitoring, namely FCD query, FCD map matching.
A general formulation of 2nd-order Polynomial Smooth Support Vector Machines

A class of 2nd-order smooth polynomial function is derived in a common interval. With such functions, a general formulation, 2nd-order Polynomial Smooth Support Vector Machine (2PSSVM) is developed. This general formulation includes all 2nd-order polynomial smooth support vector machines. The research shows that the previous 2nd-order polynomial smooth support vector machine is a special case of this general formulation. The convergence of this general formulation is also proved. The experiments show that this general formulation yields the best results in symmetric intervals. Hence this paper has solved the problem for a general formulation of 2nd-order polynomial smooth support vector machines.
Attitude Estimation of MAV Based on Fusion Algorithm

A fusion algorithm for attitude estimation of MAV(Micro Aerial Vehicle) is presented. The algorithm use quaternion to represent rotation. Attitude quaternion errors and drift bias of gyros are selected to construct a Kalman filter state vector. The output of GPS is used to correct the accelerometer readings. The local earth magnetic and gravity are used to compute observation of Kalman filter by Levenberg-Marquardt algorithm. The algorithm can converge quickly to rotation attitude of small flight vehicle.
The stabilized biconjugate gradient fast Fourier transform method for electromagnetic scattering

An iterative method, the stabilized biconjugate gradient (BiCGSTAB) method, combined with the fast Fourier transform (FFT) for solving electromagnetic scattering problems is developed for 3-D volume electric field integral equation. It converges significantly faster than the conventional conjugate gradient (CG) and biconjugate gradient (BiCG) fast Fourier transform methods. With this BCGS-FFT method, we can solve a large-scale volume integral equation with 20 million unknowns on a single CPU workstation.
Modal Parameter Identification of Bridge Using Data-driven Stochastic Subspace Algorithm

One certain self-anchored suspension bridge model test is taken as the research background, combination data-driven stochastic subspace identification algorithm with improved stabilization diagram, the modal parameters of bridge structure under ambient excitation are identified effectively. For solving the problems of system order-determination in time-domain method, noise and the identification and elimination of false modal parameters, three-step method is adopted to identify modal parameters of bridge structure more accurately. The proposed method is verified by the experiment of one certain self-anchor suspension bridge model test. The modal parameters of this model bridge are identified from the measurand under different data acquisition, and the identified modal parameters are compared with the result of FEM and DASYLab. The validity, practicability and superiority of the proposal method are verified. The results show that the data-driven stochastic subspace identification algorithm can be used in the real bridge engineering to identify the modal parameters.
Phase change RF switches with fCO exceeding 10 THz

We report on an emerging class of non-volatile solid-state RF switch that can routinely achieve cutoff frequencies above 10 THz. The switch element is constructed of GeTe, a phase change chalcogenide that can be thermally cycled between a conductive and a resistive state. A resistive heater is located proximate the switch element, such that it is thermally coupled to the switch but electrically isolated. This structure affords excellent electrical isolation of the switch resulting in its high FCO. This paper will discuss the topology of the switch and various design tradeoffs for optimizing switch resistance, switching power, monolithic integration with CMOS and other design objectives. Published system-level demonstrations of using these switches to reconfigure real RF systems will be reviewed and an outlook for the future will be provided.
A High Performance InGaZnO Thin-Film Transistors Integrated Amplifier Circuit for Capacitance Sensing

An operational amplifier with indium-gallium-zinc oxide thin-film-transistors (InGaZnO TFTs) is proposed and investigated. The proposed amplifier features introduction of positive feedback with negative equivalent output resistance for high voltage gain. Biasing conditions for every TFTs and voltage gain are systematically discussed. In addition, influences of threshold voltage shift on both static and dynamic performances are discussed. Comparison results show that the voltage gain can be increased from 40 to 67 dB, and stability of the constant tail-current biasing is better than that of constant voltage biasing method. Further, an oscillating capacitance touch sensing circuit based on the proposed amplifier is shown, and sub-pF touching capacitance can be distinguished. The proposed InGaZnO TFTs integrated amplifier is promising for high performance system on panel designs.
A hierarchical public bicycle dispatching policy for dynamic demand

The dispatching policy of public bicycles during peak hours largely determines the sharing rate of bicycles and service level of public bicycle system. Firstly, a dynamic demand prediction model of public bicycle system is proposed considering reservation data and historical data. Secondly, a hierarchical dispatching policy and network partitioning method are discussed. Thirdly, an optimization model with time window to decide the number of bicycles that need to be dispatched is put forward considering the cost of dispatching and waiting time of passengers, and the method to decide the path of dispatching is also discussed. Finally, a case study in Guangzhou shows that the proposed policy could provide lower waiting time for passengers and better bicycle sharing rate of bicycles.
FPGA-Based Design and Implementation of Arbitrary Waveform Generator

This paper proposed a solution for arbitrary waveform generator (AWG), in which integrated DDS chip is engaged as the essential frequency variable clock source. DACs are driven to generate the waveforms by clock signals, which are obtained from the reshaping and shape lifting of output from DDS by clock distributor. The data to build waveform up are stored in cache and loaded into DACs continuously by FPGA. An embedded process was set up in FPGA and would interpolate data from envelope when output of whole system is required to be typical reference. AGC circuits then standardize signal out of DACs to a constant peak-to-peak value, and VGA is obliged to fit the amplitude of signal as same as settings. Finally, the signal flow out this generator via BNC over filtering. In author's practice, a demo with performance of 200Msps rate and 100MHz above analog bandwidth can be achieved.