nils-herrmann/clean_scirepeval huggingface dataset:
Research of efficient FEM algorithm with precise and parallel computing

A FEM platform is developed to support high precision electric field computing and data analysis. For the precise computing of 550kV SF6 arc quenching chamber, a solve regions division project is presented to improve meshes quality and computation efficiency. At the same time, approach regular triangle algorithm is realized by combing the uniform and gradient disperse for boundary, constraint condition of maximize minimal native angle, and ripple model about mesh optimizing. By calculation, it can be obtained that the ratio of high quality messes approach regular triangle degree γ≥0.8 is about 87%, and ratio of high quality messes that minimum native angle is not less than 40° is about 95%. The parallel computing algorithm about coefficient matrix is designed based on the dynamic compressing storage structure and multi-thread technology. The calculated instances analysis show that the errors of this algorithm are smaller than by ANSYS software, the efficient of matrix calculation solution raises 30%∼40% than general method for this model, and this algorithm consumes less memory.
Study on the bifurcation of the shock wave in SF6 circuit breaker

For studying the effect of the pressure on the breaking performance during the cold gas interruption of a SF6 circuit breaker (CB), 1D compressive gas flow field mathematical model was deduced by replacing the mass equation with the pressure equation based on the mathematic transformation. And the distribution of Mach number in gas flow field under different opening strokes were simulated using finite volume method (FVM), and the density, the pressure, the velocity, and the temperature distribution of the gas flow were obtained and especially the above gas flow parameter variations at the region of the shock wave formed have been calculated. And the fundamental solution of the equations describing the gas flow in the SF6 CB has been resolved using separation of variables method, and 1D differential equations with constant coefficient were derived. Based on the proposed model, the bifurcation diagrams at different opening strokes have been calculated. The results show that for the gas flow with different velocity, the system exhibits periodic, quasi-periodic or even chaotic behavior in the arc quenching chamber. And the instability of the shock wave may be one of the origins of the complex phenomena.
Face Alignment Across Large Poses: A 3D Solution

Face alignment, which fits a face model to an image and extracts the semantic meanings of facial pixels, has been an important topic in CV community. However, most algorithms are designed for faces in small to medium poses (below 45), lacking the ability to align faces in large poses up to 90. The challenges are three-fold: Firstly, the commonly used landmark-based face model assumes that all the landmarks are visible and is therefore not suitable for profile views. Secondly, the face appearance varies more dramatically across large poses, ranging from frontal view to profile view. Thirdly, labelling landmarks in large poses is extremely challenging since the invisible landmarks have to be guessed. In this paper, we propose a solution to the three problems in an new alignment framework, called 3D Dense Face Alignment (3DDFA), in which a dense 3D face model is fitted to the image via convolutional neutral network (CNN). We also propose a method to synthesize large-scale training samples in profile views to solve the third problem of data labelling. Experiments on the challenging AFLW database show that our approach achieves significant improvements over state-of-the-art methods.
A Posteriori Error Estimation and Adaptive Mesh Refinement Controlling in Finite Element Analysis of 3-D Steady State Eddy Current Fields

Several methods of a posteriori error estimation and adaptive refinement controlling in finite element analysis of 3-D steady-state eddy current field are described in this paper. An improved Z-Z method and a more efficient method of CIL are presented. The numerical models of TEAM Workshop Problem 7 and 21A are used to verify the validity of the presented method.
Multi-objective optimization design of commutation circuit in DC vacuum circuit breaker

Modeling DC vacuum circuit breaker (DC VCB), based on Kirchhoff's law, using the method of changing high order equation into a first-order equation, combining with variable step fourth order Runge-Kutta method, the numerical calculation and analysis of DC VCB in various stages during interruption are taken. And the absolute value of the product of the decline rate of current before current zero (CZ) and the rise rate of the recovery voltage after CZ is used to measure the arc extinguishing capacity of the main circuit breaker. Moreover, the product of DC VCB commutation capacitance value and square of its rated voltage is used to evaluate the cost of DC VCB. And the post-arc vacuum dielectric recovery characteristics is considered by the sheath development based on the continuous transition model. The most reliable breaking operation, the lowest cost and the shortest sheath development time are taken as the optimization objective respectively. Using genetic algorithm (GA), the optimization of commutation circuit parameters (CCPS) is proposed. The optimization results provide reference for selecting the commutation inductance (CL) and commutation capacitor (CC), according to the commutation circuit design for different practical conditions and different requirements.
Research of Ship Grounding Prediction Based on Fuzzy Theory

In view of the inefficiency of ship grounding alert, a novel approach for ship grounding prediction was described in this paper, in which the vector data of the hazardous zones was extracted from ENC(electronic navigational charts) database, an geometry model for the ship and hazard area was established and the grounding risk index (GRI) based on fuzzy theory calculated. The experimental results demonstrated that GRI could accurately reflect the grounding danger along one ship's instantaneous track and showed that it was feasible and effective.
Quantum-inspired genetic algorithm based on phase encoding

Due to frequent decoding operations, the efficiency of optimization is severely reduced when the binary quantum genetic algorithm based on qubits measure is applied to the continuous space optimization. To solve this problem, a quantum genetic algorithm based on phase encoding is proposed in this paper. In this method, the chromosomes are encoded by the phase of qubits, evolved by quantum rotation gates, and mutated by quantum Pauli-Z gates. As the optimization process is performed in [0, 2π], which has nothing to do with specific issues, therefore, the proposed method has good adaptability for a variety of optimization problems. With application of function extremum optimization, the simulation results show that the approach is superior to common quantum genetic algorithm and simple genetic algorithm in both search capability and optimization efficiency.
Calculation of electric field in vacuum circuit breaker using optimized and traditional CSM

In this paper, a combined method of traditional and optimized charge simulation method (CSM) based on the genetic algorithms (GA) is presented for calculating electric field. Based on the well studied and analyzed traditional CSM, the optimized charges locations and quantities have been realized using GA as the optimization method. The feasibility and practicability of the combined method are verified by calculating the electric field of a 35 kV vacuum interrupter (VI).
Design and research of asymmetric micro-channel cooling system in MEMS-based Microstrip antenna

The microstrip antenna manufactured by MEMS has a few good features, such as small size and light weight. However, the substrate and feeder often have lager energy consumption and the antenna thermal area is small. When the antenna reaching normal power demand worked for 15 seconds, the peak temperation will reach 105°C and could not continue to work properly. This paper simulated the antenna structure and its power consumption to look for the peak temperature region, and designed asymmetric micro-channel cooling structure which is based on the Microstrip antenna array and the experimental data. Simulation indicated that peak temperature decreased by 9% by asymmetric structure cooling system driven by 1.2*10−5W micro-pump power. And antenna can guarantee work normally under 61.6°C.
Face anti-spoofing using patch and depth-based CNNs

The face image is the most accessible biometric modality which is used for highly accurate face recognition systems, while it is vulnerable to many different types of presentation attacks. Face anti-spoofing is a very critical step before feeding the face image to biometric systems. In this paper, we propose a novel two-stream CNN-based approach for face anti-spoofing, by extracting the local features and holistic depth maps from the face images. The local features facilitate CNN to discriminate the spoof patches independent of the spatial face areas. On the other hand, holistic depth map examine whether the input image has a face-like depth. Extensive experiments are conducted on the challenging databases (CASIA-FASD, MSU-USSA, and Replay Attack), with comparison to the state of the art.
Audio zero-watermark scheme based on discrete cosine transform-discrete wavelet transform-singular value decomposition

Traditional watermark embedding schemes inevitably modify the data in a host audio signal and lead to the degradation of the host signal. In this paper, a novel audio zero-watermarking algorithm based on discrete wavelet transform(DWT), discrete cosine transform(DCT), and singular value decomposition(SVD) is presented. The watermark is registered by performing SVD on the coefficients generated through DWT and DCT to avoid data modification and host signal degradation. Simulation results show that the proposed zero-watermarking algorithm is strongly robust to common signal processing methods such as requantization, MP3 compression, resampling, addition of white Gaussian noise, and low-pass filtering.
ACP-Based Management and Control for Urban Passenger Transportation Hubs

Accurate assessment and effective control of urban passenger transportation hub operations are an area that traditional methods have yet to address satisfactorily. This article presents a framework for parallel management and control based on the artificial societies, computational experiments, and parallel execution (ACP) paradigm. The authors first introduce the components, internal interactions, and support mechanism of artificial transportation hubs. They then describe an agent-based model for the hub including the computational experiments and responsibilities of parallel execution in active hub management and control. Thy also present an implementation of the framework through field tests. The framework can improve operational efficiency and service quality of urban passenger transportation hubs.
Orthogonal Neighborhood Preserving Embedding for Face Recognition

In this paper, we propose a new algorithm called Orthogonal Neighborhood Preserving Embedding (ONPE) for face recognition. ONPE can preserve local geometry information and is based on the local linearity assumption that each data point and its k nearest neighbors lie on a linear manifold locally embedded in the image space. ONPE is based on Neighborhood Preserving Embedding (NPE), but overcomes the metric distortion problem of NPE, while metric distortion usually leads to performance degradation. Besides, we propose a classification method (ONPC) based on the ONPE, which use local label propagation method in the reduced space for face recognition. ONPC is based on the natural assumption that the local neighborhood information is also preserved in reduced space, and the label of a data point can be obtained in the reduced space by the labels of its neighbors. Experimental results on two face databases demonstrate the effectiveness of our proposed method.
Particle simulation of argon electrons in direct current discharge

A microscopic model is based in our study which adopted the particle-in-cell and Monte Carlo methods to simulate the behavior of the electrons at the beginning of the discharge. The distance between the plane electrodes in our study is 64 mm. The gas temperature is 300 K and the DC voltage applied to the electrode is 1000 V. We trace the motions of a large amount of the electrons and assembled average which makes us acquire the macroscopic energy distributions. The elastic collision, ionization and electronic excitation between electrons and neutral atoms are considered here and at the same time the relationships between the energy and cross section of the electrons are also considered here. According to our study, the energy distributions of the electrons and the impacts of the pressure are acquired. The phenomena that the electrons with low energy are absorbed by the electrodes at the beginning of the discharge and the multiplication of the high energy electrons by the function of the electric field can also be explained well.
Study on noise characteristic of gain-clamped erbium-doped fiber-ring lasing amplifier

A simplified method to estimate the noise figure of the optically gain-clamped erbium-doped fiber amplifiers (EDFA's) is proposed. The simulation results indicate that the population inversion level at the signal input end dominates the noise performance of the entire amplifier. For a gain-clamped EDFA with ring-lasing configuration, the effects on the noise figure of the amplifier by the distributions of the pumping and lasing powers as well as the lasing wavelength are analyzed theoretically. The suggested noise-optimum configuration is co-pumping and co-traveling lasing oscillation at 1531 nm. Near quantum limit internal noise figure of 3.6 dB is achieved in the experiments under the best arrangement. The experiment results show perfect accordance with the theoretical analysis.
Experimental study on the dielectric-deformation behavior of SIO2 in a sandwich structure

The ANSOFT software and its applation to electrical fields simulation were briefly introduced. In combination with forced-air cooling isolated-phase bus (IPB), the numerical simulation of electrical fields inside IPB was given. The simulation results indicate that the structure inside IPB mainly influence on the electrical field distribution. Based on numerical simulation analysis of ANSOFT, it is helpful for insulation design and optimization design of IPB.
Discriminative Face Alignment

This paper proposes a discriminative framework for efficiently aligning images. Although conventional Active Appearance Models (AAMs)-based approaches have achieved some success, they suffer from the generalization problem, i.e., how to align any image with a generic model. We treat the iterative image alignment problem as a process of maximizing the score of a trained two-class classifier that is able to distinguish correct alignment (positive class) from incorrect alignment (negative class). During the modeling stage, given a set of images with ground truth landmarks, we train a conventional Point Distribution Model (PDM) and a boosting-based classifier, which acts as an appearance model. When tested on an image with the initial landmark locations, the proposed algorithm iteratively updates the shape parameters of the PDM via the gradient ascent method such that the classification score of the warped image is maximized. We use the term Boosted Appearance Models (BAMs) to refer to the learned shape and appearance models, as well as our specific alignment method. The proposed framework is applied to the face alignment problem. Using extensive experimentation, we show that, compared to the AAM-based approach, this framework greatly improves the robustness, accuracy, and efficiency of face alignment by a large margin, especially for unseen data.
Dynamical gain control in the serial structure C+L wide-band EDFA

The dynamic gain properties of a serial structure of C+L wide-band EDFA are investigated. It is found out that changing of C band (L band) signal has almost no effect on the gain spectra of L band (C band), so that dynamical gain control can be realized by mature fast linear pump control via monitoring of C band and L band input signal respectively. The method was demonstrated experimentally for the first time.
Spatio-Temporal Alignment of Non-overlapping Sequences from Independently Panning Cameras

This paper addresses the problem of spatio-temporal alignment of multiple video sequences. We identify and tackle a novel scenario of this problem referred to as Nonoverlapping Sequences (NOS). NOS are captured by multiple freely panning handheld cameras whose field of views (FOV) might have no direct spatial overlap. With the popularity of mobile sensors, NOS rise when multiple cooperative users capture a public event to create a panoramic video, or when consolidating multiple footages of an incident into a single video. To tackle this novel scenario, we first spatially align the sequences by reconstructing the background of each sequence and registering these backgrounds, even if the backgrounds are not overlapping. Given the spatial alignment, we temporally synchronize the sequences, such that the trajectories of moving objects (e.g., cars or pedestrians) are consistent across sequences. Experimental results demonstrate the performance of our algorithm in this novel and challenging scenario, quantitatively and qualitatively.
Disentangled Representation Learning GAN for Pose-Invariant Face Recognition

The large pose discrepancy between two face images is one of the key challenges in face recognition. Conventional approaches for pose-invariant face recognition either perform face frontalization on, or learn a pose-invariant representation from, a non-frontal face image. We argue that it is more desirable to perform both tasks jointly to allow them to leverage each other. To this end, this paper proposes Disentangled Representation learning-Generative Adversarial Network (DR-GAN) with three distinct novelties. First, the encoder-decoder structure of the generator allows DR-GAN to learn a generative and discriminative representation, in addition to image synthesis. Second, this representation is explicitly disentangled from other face variations such as pose, through the pose code provided to the decoder and pose estimation in the discriminator. Third, DR-GAN can take one or multiple images as the input, and generate one unified representation along with an arbitrary number of synthetic images. Quantitative and qualitative evaluation on both controlled and in-the-wild databases demonstrate the superiority of DR-GAN over the state of the art.
Research on Topic Relevancy of Sentences Based on HowNet Semantic Computation

In Automatic Question Answering System, topic identification is usually based on relevancy computation of sentences. This paper introduces an approach to compute topic relevancy. Using the semantic computation in HowNet, the relevancy of sentences can be calculated. The topic relevancy of sentences can be calculated through the computation of relevancy between words of sentence and subject words. Experimental results show the effectiveness of the method.
Prioritizing Default Rules Embedded in Description Logic Knowledge Base

Description logic based semantic query needs complete information from sources of knowledge where available information is often incomplete. To solve such incomplete reasoning problem, this paper embedded default logic into the description logic knowledge base, meanwhile prioritized the default rules, which preferred more specific default rules over more general ones. Then, an original incomplete query could be transformed into a complete query relative to the extended knowledge base, by checking default satisfiability of complex concept in accord with the query. Furthermore, the default satisfiability can be detected through a new extended tableau algorithm.
Research on rotary-gas high voltage SF6 circuit breaker with novel blade nozzle Part II: Motion behavior analyses under cold flow interruption

A 252kV single-break SF6 circuit breaker (CB) is taken as the investigation model in this paper, and six different nozzles with different blade contour and 3D gas flow field model are presented based on N-S equations. And the variations of the cold flow field parameters in arc-quenching chamber with different nozzles have been obtained using finite volume method (FVM) during the interrupting. The influences of blade contour on the gas flow parameters, such as velocity, pressure-temperature ratio and pressure are analyzed by changing the angle, number and the height of the blade. And the reasonable nozzle blade structure of the rotary-gas CB is obtained.
Investigation on three-dimensional magnetic field between axial magnetic contacts for revolving are type vacuum circuit breaker

In the short current breaking process, the magnetic field distribution between the axial magnetic contacts of vacuum circuit breaker directly influence the arc form, arc variation, arc blow velocity and so on. Thus, it plays an important part in dielectric recovery characteristic during the breaking process. In this paper, taking the actual current flow path in the contacts into consideration, the three-dimensional (3D) magnetic field distribution between the axial magnetic contacts of the revolving arc type vacuum circuit breaker has been calculated. The magnetic induction strength distributions on the different space profile including the contacts surface have been obtained and their graphics processing are figured out. The simulation results show that this axial magnetic field distribution is beneficial to the vacuum arc quenching.
An image enhancement technique in the DCT domain for cancer detection

In this paper, we develop an image enhancement technology in the DCT domain for radiologists to screen mammograms. The proposed algorithm is an improved version of the algorithm developed. The improved algorithm overcomes the shortcomings of the old algorithm which requires manual adjustment of multiple parameters to realize non-uniform enhancement in different frequency bands. The proposed image enhancement algorithm is expressed as an optimization problem. In the optimization problem, the optimal local enhancement factors are found so that the target global contrast value is achieved which is specified by a user. Because it's a multi-variable optimization problem, genetic algorithm is used to search the optimal parameters. The experimental results show that the algorithm is progressive.
Free-space nano-optical devices and integration: Design, fabrication, and manufacturing

Lithographically defined optical nanostructures can be used to design various fundamental optical functions, including polarization, phase, refraction, and wavelength management. This paper describes the design, fabrication, and manufacturing of free-space discrete and integrated optical devices based on optical nanostructures. These devices are fabricated using a nanomanufacturing platform based on wafer-level nanoreplication with mold and nanopattern transfer by means of nanolithography. The nanoreplication process, based on imprinting a single-layer spin-coated ultraviolet (UV)-curable resist, achieved excellent nanopatterning fidelity and on-wafer uniformity with high throughput. It also achieved excellent wafer-level performance and yield. Nano-optical devices (NODs) (e.g., infrared polarizers and true zero-order quarter waveplates) and integrated NODs (e.g., monolithically integrated semi-isolators and visible circular polarizers) may be fabricated using the nanomanufacturing platform. The developed technology is suitable for the high-throughput and low-cost manufacturing needed to commercialize nanostructure-based optical devices and integrated optical devices. The success of the developed nano-engineering technology will lead to a redefinition of optical device manufacturing and integration and the functional and economic displacement of traditional bulk-optics devices.