nils-herrmann/clean_scirepeval huggingface dataset:
Analysis of Bound-Soliton States in a Dual-Wavelength Mode-Locked Fiber Laser Based on Bi2Se 3

Wavelength switchable and dual-wavelength soliton operations are demonstrated in an erbium-doped fiber laser with three pieces of TI Bi<sub>2</sub>Se<sub>3</sub> polyvinyl alcohol (Bi<sub>2</sub>Se<sub>3</sub>-PVA) film. Wavelength switchable operation from 1532 to 1557 nm could be achieved just by adjusting the pump power. With the appropriate settings of PC and pump power, a novel dual-wavelength soliton operation was observed. The dual-wavelength pulses operate at different mode-locked states. One is the single pulse mode-locking operation at 1532 nm, and the other one is the bound-soliton states at 1557 nm. However, the dual-wavelength soliton operation cannot be stable for a long time. The numerical results demonstrate that the separations of bound pulses have small variation and that the phase difference of bound pulses appear jumping change of <inline-formula><tex-math notation="LaTeX">$\pi $</tex-math></inline-formula>.
Research on Improved Function Block Based Redundancy

An improved function block based redundancy approach is proposed in this paper. The structure, link organization and data synchronization of improved function block are described. Furthermore, the non-redundancy model, the corresponding device-level redundancy model and improved function block based redundancy model are analyzed in quantitatively. For 1-0-2 type system, improved function block based redundancy model can achieved significantly higher reliability than non-redundant system.
VLSI passive switched capacitor signal processing circuits: Circuit architecture, closed form modeling and applications

A VLSI switched capacitor signal processing circuit modeling method is presented. Such technique provides capability to effectively develop closed form signal transfer functions for various practical VLSI SC circuits. Application to the VLSI switched capacitor charge pump DC/DC converter circuit implementation demonstrated consistent results between the model and measurement of the fabricated circuit based on a 0.13 mum CMOS process technology.
Intracavity frequency doubling of PPKTP-based optical parametric oscillator

A ring-cavity synchronously-pumped optical parametric oscillator was investigated, which was pumped by a self-mode-locked Ti:sapphire laser. A periodically poled KTiOPO4 crystal was used in the oscillator, and the parametric operation was obtained. The wavelength of the signal wave covered from 1000 nm to 1500 nm. The signal wave was successfully frequency doubled by inserting a nonlinear BBO crystal in the cavity. The wavelength of second harmonic could be tuned from 550 nm to 650 nm freely by cavity-length tuning. The loss of the cavity and the threshold of the pump power, a thin glass substrate is inserted into the cavity to couple output the light, then the output power is measured for varying pump power, based on the measurement the loss in the cavity was discussed. Furthermore, the characteristic of output pulses is also measured.
High-Performance Ge p-n Photodiode Achieved With Preannealing and Excimer Laser Annealing

A germanium (Ge) n+/p shallow junction photodiode fabricated by a combination of low-temperature preannealing and excimer laser annealing of the phosphorus-implanted p-type Ge is demonstrated. The Ge photodiode shows a high responsivity of 0.48 A/W at the 1.55-μm wavelength and an extremely low leakage current density of 1 pA/μm2 at room temperature, over two orders of magnitude lower than that of diodes formed by the rapid thermal annealing process. In addition, the reverse leakage current is close to the theoretical limitation of Ge diodes dominated by the ideal carrier diffusion model. The well-controlled dopant profile of the Ge shallow junction should be beneficial for improving the performance of the diodes, which may also be used in making the source and drain of scaled Ge nMOSFET.
A kernel logistic neural network based on restricted Boltzmann machine

A multi-class classification technique which combines kernel logistic neural network (KLNN) and restricted Boltzmann machine (RBM), called KLNN-RBM, is designed. The principal component analysis (PCA) is applied to determine the dimension of the kernel function. The initial weights and thresholds of this model are obtained by RBM. Then, the maximum likelihood estimate with a ridge regularization term and a new stochastic gradient descent method with a scaling factor are used to optimize the parameters in order to realize the multi-class classification. Some numerical simulations illustrate the validity of the proposed method.
Calculation of ytterbium-doped double-cladding CW fiber amplifiers

With 4th-order Runge-kutta method and relaxation method, we obtain the power distribution of pump light and signal light along fiber by solving the steady-state rate equations in ytterbium-doped double-cladding fiber amplifier. The relationships between the output power and the fiber length are discussed with different pump power and different doped concentrations of the fiber. The change of the output power versus the pump power is calculated. The power distribution along fiber and the relationship between output power and input power are analyzed when the signal is injected from z=L and z=0 respectively.
Linear Cofactor Difference Extrema of MOSFET's Drain–Current and Application to Parameter Extraction

The linear cofactor difference extrema due to the nonlinearity of the MOSFET drain-current and their application to extract MOSFET parameters are presented in this brief. The extrema of drain-current are obtained by applying the linear cofactor difference operator to the drain-current versus gate voltage curve in the linear region. These extrema are directly used to find the threshold voltage and the mobility of a MOSFET. This method has been tested using data from experimentally fabricated MOSFETs and by simulating results through the device simulator DESSIS-ISE. The results agree well with those obtained by the standard second-derivative approach, which demonstrates the validity of the method presented. The advantages and disadvantages of this method are also discussed
The Study of Electric Field of High-Power Supercapacitors

The supercapacitor has large potential on electric cars, the power supply of electromagnetism launch system as a new type storage energy element. In this work, it is intended to discuss the charge and electric field distributing models of two kinds of supercapacitors: the double layer of porous electrode and the hybrid supercapacitor that is composed of anodes of electrolytic capacitors, cathodes of electrochemical capacitors, and 38 wt% H2SO4 electrolyte solution. It explores the factors of thickness, pore distributing, and permittivity influenced on the electric field of supercapacitors by ANSYS and reveals the distributing charge of supercapacitors. On the basis of the discussion and analysis, the result shows that changing physical parameters, such as electrode structure and material, and the electric parameters can optimize the structures and performance of supercapacitors to improve the energy density and the power density, and increase the instantaneous discharge current.
Concurrence-Aware Long Short-Term Sub-Memories for Person-Person Action Recognition

Recently, Long Short-Term Memory (LSTM) has become a popular choice to model individual dynamics for single-person action recognition. However, existing RNN models only focus on capturing the temporal dynamics of the person-person interactions by naively combining the activity dynamics of individuals or modeling them as a whole. This neglects the inter-related dynamics of how person-person interactions change over time. To this end, we propose a novel Concurrent Long Short-Term Memories (Co-LSTM) to model the long-term inter-related dynamics between two interacting people on the bonding boxes covering people. Specifically, for each frame, two sub-memory units store individual motion information, while a concurrent LSTM unit selectively integrates and stores inter-related motion information between interacting people from these two sub-memory units via a new co-memory cell. In experiments, we show the superior performance of Co-LSTM compared with the state-of-the-arts methods.
The Analysis of the Synchronization Condition of Linearly Coupled Chaotic System

Describe the problem of chaos synchronization with precise mathematic theory, and in addition convert it to the analyze on the stability of the differential equations. Chen's system which is attached to the Lorenz's group has been introduced as the typical system, at the same time discusses the stability of the linear coupled chaotic system. Moreover a theorem which consists of the sufficient qualification attaining to the chaotic synchronization has been presented and in spite of this the paper also gives the detailed prove of the theorem. Avail the qualification discussed above, a method of identifying the coupled parameter is also given. Eventually, the conclusion of the simulation proves the valid of the theorem, besides, demonstrates the synchronization phenomenon of coupled system under different ways
The analysis and design of low velocity estimation based on observer

Low velocity servo system needs precision velocity estimation. An observer for low velocity estimation was proposed in this paper. First, the source of low velocity estimation errors and the shortcomings of the single period difference were analyzed. The relationship between the estimation accuracy and estimator's frequency characteristics was concluded. Then, the structure of the observer was proposed. Frequency characteristics were used to design the compensator which can stabilize the observer. The stability of the observer was also discussed. At last, the observer's estimation accuracy was evaluated through a quantitative comparison. The results of simulation and experiment have shown that the quantized error in velocity estimation decreases dramatically when a velocity observer is used. Compared with some commonly-used estimators, the phase lag accompanying the observer is much less.
Robust object tracking using color and depth images with a depth based occlusion handling and recovery

Object tracking has always been a challenging problem in the field of computer vision. Most previous works used only the color images for this problem, which may suffer from changing environments, such as illumination variations, partial occlusion and background clutters, resulting in the socalled model drift problem. As depth images contain spatial information, depth images encode important clues for these problems. In this paper, we utilize depth images, which are provided by the Microsoft Kinect, to improve the traditional tracking methods. Firstly, we adopt the harr-like features extracted from both the color and depth domains with a naive Bayesian classifier to reduce model drift. Secondly, to handle the occlusion problem, we utilize the depth histogram to decide whether occlusion occurs. Thirdly, to recover from heavy occlusions, we design a detection module to search for the occluded object and use the depth-based segmentation to find the object. We carry out experiments on the Princeton RGBD tracking dataset, and the results demonstrate the effectiveness of the proposed method, especially under occlusion conditions.
Lane marking detection based on adaptive threshold segmentation and road classification

A new robust lane marking detection algorithm for monocular vision is proposed. It is designed for the urban roads with disturbances and with the weak lane markings. The primary contribution of the paper is that it supplies a robust adaptive method of image segmentation, which employs jointly prior knowledge, statistical information and the special geometrical features of lane markings in the bird's-eye view. This method can eliminate many disturbances while keep points of lane markings effectively. Road classification can help us extract more accurate and simple characteristics of lane markings, so the second contribution of the paper is that it uses the row information of image to classify road conditions into three kinds and uses different strategies to complete lane marking detection. The experimental results have shown the high performance of our algorithm in various road scenes.
Thermodynamic simulation of exhaust gas recirculation coolers used on diesels based on finite element method

The thermodynamics of exhaust gas recirculation (EGR) coolers plays a very important role for reducing oxides of nitrogen (NOX) emissions of diesel engines. Using the ANSYS software, some fluid thermodynamic models of EGR coolers were established by using the finite element method (FEM); and the temperature fields of gas fluids in the EGR coolers were simulated and verified by comparing the experimental results from some literatures. Based on the FEM models, furthermore, cooling efficiencies of the EGR coolers with different diffuser structures and different numbers of cooling tubes were analyzed and discussed. The comparison results show that, for the same dimension of EGR coolers, their cooling efficiencies can be increased up to five or thirteen percents by replacing their column diffusers with cone diffusers or by properly selecting the tube numbers of the EGR coolers.
Combined RGBD-inertial based state estimation for MAV in GPS-denied indoor environments

This paper presents a integrated navigation approach for state estimation of a micro aerial vehicle (MAV) that is capable of autonomous flight in GPS-denied, indoor environments. The solution combines RGB-D sensor and inertial sensors in a tight-coupling navigation manner. Motion estimates from RGB-D visual odometry and inertial measurements are fused using an improved Extended Kalman Filter-based fusion algorithm to provide an accurate estimate of the relative position, velocity and attitude. Instead of using a global reference frame, a view-based map is employed and the algorithm maintains the position and heading relative to the current map node in the fusion algorithm. In addition, a closed-form covariance is developed to qualify the uncertainty of the RGBD visual odometry measurements, which is utilized for state update of the navigation filter. Our approach allows efficient measurement updates and enables the incorporation of RGBD visual odometry uncertainty. Experimental results of a quadrotor MAV flying in a GPS-denied indoor environment demonstrate the performance of the proposed approach. Comparisons of state estimates with ground truth measurements are also provided.
Estimation of dissolved oxygen via PLS and neural networks

Dissolved oxygen is one of the most important dependent factors in the process of aquaculture. In this article, a new on-line soft sensing method is proposed for estimation of dissolved oxygen in aquaculture. Based on the characters of process data, two advance techniques are used which is PLS (Partial Least Squares) and neural networks. With this method, real-time control and optimization can be realized in aquaculture. An industrial experimental study is described, and the results show that the proposed soft sensing algorithm is effective.
High-efficiency model-based control of 6-DOF parallel robot using position measurement only

The trajectory tracking problem for the 6- degree-of-freedom (DOF) parallel robot is analyzed in this paper, which is a typical multi-input multi-output (MIMO) systems control issue. A novel high-efficiency model-based control scheme is proposed based on the off-line multi-body dynamics of the parallel robot, which extensively enhances the on-line computation efficiency. Moreover, the velocity signals are not required in the proposed feedback control scheme by introducing the extended state observer (ESO), which solves the performance degradation caused by the measurement noise of velocity signals in practice. Finally, an electrical 6-DOF parallel robot is employed to verify the advantages of the proposed controller in comparison with the enhanced PID controller.
Research and implementation of network access control policy based on NDIS

This paper proposes an optimization method of network access control policy based on NDIS data packet filtering techniques, and then a solution is developed to design network access control system. Based on this scheme, the program running on the interconnect device which supports media access control layer and network layer could capture, transmit or discard data packets with the access control rules which involved MAC, IP and access level. The system acquires and maintains dynamic access control information to ensure the flexibility of accessing Internet. Experimental results show the system has well capability and robust.
An Automatic Video Semantic Annotation Scheme Based on Combination of Complementary Predictors

Given a large set of video database, how to connect video segments with a certain set of semantic concepts with least manual labors is an elementary step for video indexing and searching. Due to the large gap between high-level semantics and low-level features, automatic video annotation with high accuracy is a challenging task. In this paper, we propose a novel automatic video annotation framework, which improves the annotation performance by learning from unlabeled samples and exploring temporal relationship in video sequences. To effectively learn from unlabeled data, a sample selection scheme based on combining a set of complementary predictors is proposed, which iteratively refines the performance of the initial predictors. A filtering-based method is applied to further improve the annotation accuracy as well, in which video temporal relationship is sufficiently exploited. Experiment results show that the proposed automatic video annotation method performs superior to general supervised learning methods and co-training
Designing electronic circuits using Cultural Algorithms

This work investigates the application of cultural algorithms in the field of evolutionary electronics. Cultural Algorithms is an evolutionary model inspired by the cultural evolution process which shows many excellent characteristics and has succeeded in solving some complicated problems. Based on the population space in which individual evolves, the belief space is constructed, in which effective implicit information during the evolution process are abstracted and utilized. We propose the new means for designing electronic circuits and introduce the encoding of the circuit as a chromosome, the genetic operators and the fitness function. For the case studies, this means has proved to be efficient and the experiment results show that the new means have got the better results.
Research on dynamic characteristics of Unified Power Flow Controller (UPFC)

Based on the basic principle of Unified Power Flow Controller circuit, give a simple analysis about the principle of power flow control of UPFC, and a detailed simulation model of UPFC considering the charging dynamics of its DC link capacitor is provided. Using the UPFC simulation model established in SIMULINK, a dynamic simulation tool in MATLAB, take a simple power system with UPFC as an example. the simulation test has been conducted on a simple system composed of synchronous generator and infinite capacity bus, the steady state and transient characteristics of UPFC in this system are researched. In the process of simulation, the control strategy of UPFC system is also discussed, its shunt side control the terminal voltage of the system and the firing angle of converter 1 the shunt part of UPFC, in order to keep the terminal bus voltage magnitude of UPFC and the DC capacitor voltage as constant, respectively. its series side control terminal voltage and firing angle of converter 2 the series part of UPFC, so as to keep the real power and reactive power of the line with UPFC device as constant or to act as a series compensator. Further analysis shows that all the active power of the series side is provided or absorbed by the DC capacitor presented among the two converters. The active power is provided by the shunt side convertor of the UPFC. that is to say, both converter is associated with the part of DC link, therefore, it is very necessary to consider the dynamic situation of the DC capacitor when establishment the mathematical of UPFC. The results from simulation and experiments show that by means of UPFC the power flow distribution among transmission lines can be give back rapidly and reposefully. The transient experiments proved that UPFC can improve the stability of power grid. Simulation results also confirm that UPFC can restrain the oscillation of power angle and power flow.
Modulation of Schottky Barrier Height of Metal/TaN/n-Ge Junctions by Varying TaN Thickness

This paper demonstrates experimentally the modulation of the Schottky barrier height (SBH) of metal/TaN/n-Ge junctions by varying the TaN thickness in a dual stacked metal layer. The effective SBH for the metal/TaN/n-Ge Schottky junctions, originally pinned at 0.53-0.61 eV, decays to 0.44 eV, the barrier height of TaN/n-Ge, with an increase in the TaN thickness from 0 to 10 nm, independent of the type of metal. Dipole formation at the TaN/Ge interface is proposed to alleviate the metal-induced gap states and shift the pinning level toward the conduction band. The modulation of the SBH can be ascribed to the interdiffusion between the cap metals (Al, Fe, and Ni) and TaN.
A Sample and Feature Selection Scheme for GMM-SVM Based Language Recognition

Discriminative training for language recognition has been a key tool for improving system performance. SVM-based algorithms (i.e. GMM-SVM, GLDS-SVM etc.) are important ones for language recognition. The core of these algorithms is to construct the kernel for comparing the similarity of two sequences. It is known that the mismatch between training and test condition will degrade the performance. In this paper, we proposed a novel sample and feature selection scheme under the GMM-SVM framework, which aims at alleviating the duration mismatch problem. The proposed method is evaluated on NIST 03 and 07 language recognition evaluation tasks with improvement over prior techniques.
A New Approach to Detect Soil Nutrient Content Based on NIR Spectroscopy Technique

The objective of this research was to evaluate the prediction ability of NIR to soil nutrient content. A total of 165 soil samples were obtained from the field and analyzed their spectra features. 135 samples spectra were used during the calibration and cross-validation stage, 30 samples spectra were used to predict N, P, K and OM concentration. NIR spectra and constituents were related using partial least square regression (PLSR) technique. The r between measured and predicted values of N and OM, were 0.92 and 0.93 respectively, demonstrated that NIRS have potential to predict accurately this constituents in this soil, not being this way in the prediction of P and K with r, 0.48 and 0.68 respectively, demonstrated a poorly for P and a less successfully for K prediction. The result also shows that NIR could be a good tool to be combined with precision farming application
Terahert detection analysis of nanowire gated field effect transistor

An analytical terahertz (THz) detection model of the Silicon nanowire MOSFET (NWFET) is developed in this paper. Beginning from the fundamental hydrodynamic transport equations, the expressions of the velocity spatial distribution and inversion charge transport are obtained. Under the reasonable boundary, an analytical model of the photoresponse of the NWFET is derived out. The comparison between analytical calculation and numerical results confirmed the proposed model. Moreover, the plasma wave transport behavior in the NWFET is analyzed in detail from the presented model and some significant characteristics are demonstrated.