nils-herrmann/clean_scirepeval huggingface dataset:
Design of high precision detecting system for Vacuum Circuit Breaker

With the increasing of used quantity and voltage label of vacuum circuit breaker (VCB), the stability and reliability of VCB have very important significance for the reliable running of transmit electricity system. How to detect the mechanism characteristics of VCB, and obtain the characteristic parameters through the detecting data, and obtain the regularity of status examine and repair of VCB through the characteristic parameters, becomes more and more focus of research. Based on the prophase research, a high-precision and high-speed detecting system for mechanism characteristic and electric characteristic of VCB is designed in this paper. The detecting system includes two parts, one is the high-speed data sampling system, the other is the data disposing system. The high-speed data sampling system is made of DSP that achieves sample to various high speed signals, and uploads the sampled data to data disposing system through the way of data bus. Through the analysis of the uploaded data, the characteristic parameters are obtained in the data disposing system. The mechanism status is obtained through the characteristic parameters. So it carries out the exactly analyze of running status and also develops the steadily running of power transmission system.
Computation of coupled current-magnetic field for vacuum interrupter

A coupled model of current conduction and static magnetic field is proposed, according to three dimensional (3D) axial magnetic fields (AMF) of two and three segments coil-type contact for a 72.5 kV/31.5 kA vacuum interrupter (VI). And the distributions of current density and electric potential are obtained using finite element method (FEM). Moreover, the conductor resistance and the characteristics of AMF are also investigated. The results show that the conductor resistance, the arc voltage and AMF generated by two segments coil-type contact is relatively larger than that that of the three segments coil-type contact.
Automated bubble-based assembly of cell-laden microgels into vascular-like microtubes

Fabrication of artificial blood vessels in micro scale significantly benefits the regeneration of functional human vascular networks. In this paper, we develop an efficient multi-microrobotic system with an innovative motorized sample holder (MSH) and two manipulators. Air is injected into the solution through a glass pipette fixed on one manipulator to create bubbles. These bubbles conduct a regular rising movement, which is utilized to assemble the 2D ring-shaped microgels fabricated in a simple micro fluidic device. With this novel bubble-based method and the robotic system, we achieve the automation of the assembly. A 1.2 mm long vascular-like microtube with an outer diameter of 200 μm is fabricated. The whole process of the bubble-based assembly is visually observed and analyzed with side view. Key parameters are characterized to improve the assembly. Results show that the automated bubble-based assembly success rate is 100% and average time cost of assembling every microgel is as low as 3.25s.
Optimal gradient pursuit for face alignment

Face alignment aims to fit a deformable landmark-based mesh to a facial image so that all facial features can be located accurately. In discriminative face alignment, an alignment score function, which is treated as the appearance model, is learned such that moving along its gradient direction can improve the alignment. This paper proposes a new face model named “Optimal Gradient Pursuit Model”, where the objective is to minimize the angle between the gradient direction and the vector pointing toward the ground-truth shape parameter. We formulate an iterative approach to solve this minimization problem. With extensive experiments in generic face alignment, we show that our model improves the alignment accuracy and speed compared to the state-of-the-art discriminative face alignment approach.
Injection-Locking Frequency Divider based dual-modulus prescalers with extended locking range

A new Injection-Locking Frequency Divider (ILFD) based dual-modulus prescaler with extended locking range is presented in this paper. The tuning capacitor inserted into the ring oscillator loop can widen the common locking range of two operating modes of the prescaler. A dual-modulus prescaler using the proposed method is designed and simulated in a 65nm CMOS process. Simulation results show that the locking range of the divide-by-4/5, from 11.5 GHz to 19.1 GHz, is extended by more than 40 % compared with from 14 GHz to 19.4 GHz using the conventional design.
Articulated human body pose tracking by suppression based immune particle filter

Particle filter is a popular stochastic tracker for object tracking. In articulated human body pose tracking, lots of work focuses on increasing sampling efficiency by incorporating optimization algorithm into particle filter. In this study, we propose a modified optimization based particle filter algorithm for pose tracking. The new algorithm can maintain the diversity of particle set by using a suppression scheme. Experimental results show that the proposed method can cope with multi-modality and can obtain more accurate estimation than other optimization based particle filter methods.
Generation of swirl flow for non-contact rotation of micro objects by vibrating glass needle

In micromanipulation, a few of methods can be applied in the rotation of micro objects, which is very important for single cell injection, observation of micro objects and assembly of complex structures. In this paper, we present a novel method to realize the non-contact rotation of the micro objects by the swirl flow which is generated through vibrating glass needle in the fluid. Experiments of rotating micro bead have been carried out to demonstrate that the rotation is effective and efficient.
The design and manufacture of a high frequency CATR

We present a design of a Compact Antenna Test Range (CATR) designed to operate from 50 up to 500 GHz, suitable for measuring high gains antennas, such as those required for mm-wave atmospheric remote sensing satellites. Drawing on experience from the QMUL CATR designed a decade ago, the team has electromagnetically and mechanically designed a CATR with a 1 metre spherical dish and two small aspheric feeding mirrors. The CATR will be set up in BUPT after validation in QMUL.
A Pairwise Covariance-Preserving Projection Method for Dimension Reduction

Dimension reduction is critical in many areas of pattern classification and machine learning and many discriminant analysis algorithms have been proposed. In this paper, a Pairwise Covariance-preserving Projection Method (PCPM) is proposed for dimension reduction. PCPM maximizes the class discrimination and also preserves approximately the pairwise class covariances. The optimization involved in PCPM can be solved directly by eigenvalues decomposition. Our theoretical and empirical analysis reveals the relationship between PCPM and Linear Discriminant Analysis (LDA), Sliced Average Variance Estimator (SAVE), Heteroscedastic Discriminant Analysis (HDA) and Covariance preserving Projection Method (CPM). PCPM can utilize class mean and class covariance information at the same time. Furthermore, pairwise weight scheme can be incorporated naturally with the pairwise summarization form. The proposed methods are evaluated by both synthetic and real-world datasets.
Joint Multi-Leaf Segmentation, Alignment, and Tracking for Fluorescence Plant Videos

This paper proposes a novel framework for fluorescence plant video processing. The plant research community is interested in the leaf-level photosynthetic analysis within a plant. A prerequisite for such analysis is to segment all leaves, estimate their structures, and track them over time. We identify this as a joint multi-leaf  segmentation, alignment, and tracking problem. First, leaf segmentation and alignment are applied on the last frame of a plant video to find a number of well-aligned leaf candidates. Second, leaf tracking is applied on the remaining frames with leaf candidate transformation from the previous frame. We form two optimization problems with shared terms in their objective functions for leaf alignment and tracking respectively. A quantitative evaluation framework is formulated to evaluate the performance of our algorithm with four metrics. Two models are learned to predict the alignment accuracy and detect tracking failure respectively in order to provide guidance for subsequent plant biology analysis. The limitation of our algorithm is also studied. Experimental results show the effectiveness, efficiency, and robustness of the proposed method.
Multi-Frame Super-Resolution for Face Recognition

Face recognition at a distance is a challenging and important law-enforcement surveillance problem, with low image resolution and blur contributing to the difficulties. We present a method for combining a sequence of video frames of a subject in order to create a super-resolved image of the face with increased resolution and reduced blur. An Active Appearance Model (AAM) of face shape and appearance is fit to the face in each video frame. The AAM fit provides the registration used by a robust image super-resolution algorithm that iteratively solves for a higher resolution face image from a set of video frames. This process is tested with real-world outdoor video using a PTZ camera and a commercial face recognition engine. Both improved visual perception and automatic face recognition performance are observed in these experiments.
3D dynamic monitoring of collapse area based on CMS-Surpac

Combine the actual situation of stope collapse area 56-7# of Dongguashan Copper Mine in china, three-dimensional dynamic monitoring the collapse area twice using Cavity Monitoring System (CMS), taking collapse area measured data as foundation, collapse area three-dimensional model created using Surpac and gain three-dimensional configuration and the actual boundary of the collapse area accurately. Then the bottom structure of stope, the designed stope and ore heap models are established according to the stope design data. Finally, the actual boundary, volume, roof exposure area, collapse range and ore remains of the collapse area are calculated accurately through Boolean operation among the models, a new visible calculation method of integrated information visible calculation for large-scale collapse area is realized effectively. The results show that the longer of the collapse area stay is, the greater of the scope, volume and roof exposure area is. So, it is essential to suspend the blasting around the collapse area and continue to reclaim ore remains. Then backfilling the collapse area and Make plans for reclaim ore body remains.
Novel Corrugated Matched Feed for Cross-Polar Cancellation in Tri-Reflector Compact Range

The concept of conjugated field match has been extended to the proposed offset tri-reflector compact range, and a novel tri-slot tri-mode corrugated matched horn has also been developed in this letter. First, the analysis on the field in the focal region of the proposed tri-reflector compact range has been carried out, and a matched aperture field for a multimode corrugated horn is constituted, which shows that the cross-polar component of the CR can be compensated by high-order asymmetrical waveguide mode, such as HE21 mode. Then, a novel tri-slot tri-mode corrugated horn was designed to compensate the cross-polar component of the quiet zone in the proposed CR. Numerical results show that the cross-polar field of the offset tri-reflector CR is compensated by the designed corrugated matched horn successfully. The extended concept of conjugated match and the proposed corrugated horn could be very useful in other offset reflector systems.
Video-based face recognition using adaptive hidden Markov models

While traditional face recognition is typically based on still images, face recognition from video sequences has become popular. In this paper, we propose to use adaptive hidden Markov models (HMM) to perform video-based face recognition. During the training process, the statistics of training video sequences of each subject, and the temporal dynamics, are learned by an HMM. During the recognition process, the temporal characteristics of the test video sequence are analyzed over time by the HMM corresponding to each subject. The likelihood scores provided by the HMMs are compared, and the highest score provides the identity of the test video sequence. Furthermore, with unsupervised learning, each HMM is adapted with the test video sequence, which results in better modeling over time. Based on extensive experiments with various databases, we show that the proposed algorithm results in better performance than using majority voting of image-based recognition results.
Computation and insulation analysis of 3-D electric field of high voltage SF/sub 6/ current transformer

In view of the complex structure of high voltage SF6 current transformer (HV SF6 CT), the generation of 3-D grid using finite element method (FEM) is applied to calculate the whole electric field. In computing, multi dielectric medium, such as the SF 6 insulation gas, porcelain casing and air has been into consideration. The equal potential and electric field strength distribution of different profiles are obtained and figured out. And the comparison of the numerical computation results between 3D and 2D model has been performed. Moreover, the insulation performance under different operating conditions has been obtained and analyzed. The theoretical basis for designing and optimizing the HV SF6 CT has been provided
Optically controlled frequency selective surface for millimeter-wave applications

In this paper, an optically controlled millimeter-wave frequency selective surface using high resistivity silicon as tunable substrate is designed and tested. It is shown from measured results, the transmission performance of FSS at resonant frequency is tuned from -1.02dB to -16dB by light illumination. The photoconductive characteristic of silicon in millimeter wave region is studied. It is shown from the measured results that the insertion loss of silicon at 110GHz is 0.0005dB without light illumination. However, its transmission coefficient decreases to -25dB at 110GHz and -45dB at 320GHz under 500mW IR light illumination.
Denoising Algorithm for Jacquard Image Using Beltrami Manifold Technique

Jacquard image denoising is an active research field in jacquard image processing and has attracted much attention in the past years. In this paper, we present a novel denoising algorithm within the framework of variational schemes and Beltrami manifold technique. Variational schemes for image denoising consist of minimizing a functional which incorporates both the data and a Beltrami flow term. The main advantage of the proposed algorithm is that it has both good noise reduction and edge protection capabilities. Experimental results show that the proposed method offers effective noise removal in real noisy jacquard images while maintaining fine structure of patterns.
Digital spur calibration of multi-modulus fractional frequency LO divider utilizing most correlated comparison algorithm

In this paper, a digital calibration scheme is proposed to correct phase mismatch among the multi-phase inputs of the pulse combiner to suppress the spurs at the output of the multi-modulus fractional frequency local oscillator divider. Compared with the conventional design, the proposed calibration scheme utilizes most correlated comparison algorithm to reduce convergence time significantly. The proposed calibration scheme is implemented by digital logic, and simulation results show that for all division ratios at maximum output frequency of 6 GHz, average convergence time is reduced by at least 68% compared to the conventional design.
A Framework for GPS/INS based Portable Positioning System

In this paper, we describe a framework for GPS/INS based Portable Positioning System. The framework includes two main components: receiving terminal and monitoring center. In the receiving terminal, the digital compass and the GPS modules are both connected with an I/O interface in a FPGA to provide an integrated positioning solution. This integrated positioning algorithm can solve the problems arising both in standalone modes and in traditional integrated measurements. In the monitoring center, several improvements have been discussed to ensure runtime efficiency and the robustness of the PPS. The experimental results from two positioning modes validate the effectiveness of the proposed algorithm.
Average neighborhood margin maximization projection with smooth regularization for face recognition

Dimensionality reduction is among the keys in many fields, most of the traditional method can be categorized as local or global ones. In this paper, we consider the dimension reduction problem with prior information is available, namely, semi-supervised dimension reduction. A new dimension reduction method that can explore both the labeled and unlabeled information in the dataset is proposed. The labeled data points are used to maximize the separability between different classes and the unlabeled data points are used to estimate the intrinsic geometric structure of the data. Specifically, we aim to learn a discriminant function which is as smooth as possible on the data manifold. The target optimization problem involved can be solved efficiently with eigenvalue decomposition. Experimental results on several datasets demonstrate the effectiveness of our method.
A Physical-network-coding-based amplify and forward cooperation scheme

Amplify and forward is a classical basic user cooperation scheme. In this paper, we propose a Physical-network-coding-based amplify and forward scheme. In time slot 2, users transmit the combinations of the partner's message and their own message through pseudo physical-layer network coding. This is the greater different from the classical scheme, where the user only transmits the partner's bits in cooperation. An outage probability analysis showing the improved performance is carried out, and computer simulations results are shown to agree with the analytical results.
Design and implementation of content-based medical image retrieval system on mammograms

This paper designs and realizes a content-based medical image retrieval (CBMIR) system on mammograms. The main functions of the system which include query module, feature extraction module, matching module, display module are also introduced. The system adopts Euclidean distance as similarity measurement of image, uses the gray level cooccurrence matrix (GLCM) for extracting texture feature. The averages of precision are 58% by the experiment.
Adaptive Edge Detection Based on Multiscale Wavelet Features

This paper presents a novel edge detection method based on multiscale wavelet features and genetic fuzzy clustering algorithm (Yunying Dong et al., 2005), which can perform image edge detection in an automatic way. Firstly, an effective feature extraction algorithm using wavelet transform is proposed to extract classification features, thus the feature vector for each pixel is gained, which contains the gradient information in various directions; and then, these vectors are used as inputs for the genetic fuzzy clustering algorithm, which result in an automatic classification; finally, make a binary map according to the classification results, and the obtained binary map is the edge map we obtain by proposed method. Some comparisons with classical edge detection algorithms are given in this paper. Experimental results demonstrate the effectiveness of the proposed method. In addition, due to the multiscale wavelet features, the proposed method has better visual quality than the other edge detection algorithms
Pose-Invariant 3D Face Alignment

Face alignment aims to estimate the locations of a set of landmarks for a given image. This problem has received much attention as evidenced by the recent advancement in both the methodology and performance. However, most of the existing works neither explicitly handle face images with arbitrary poses, nor perform large-scale experiments on non-frontal and profile face images. In order to address these limitations, this paper proposes a novel face alignment algorithm that estimates both 2D and 3D landmarks and their 2D visibilities for a face image with an arbitrary pose. By integrating a 3D point distribution model, a cascaded coupled-regressor approach is designed to estimate both the camera projection matrix and the 3D landmarks. Furthermore, the 3D model also allows us to automatically estimate the 2D landmark visibilities via surface normal. We use a substantially larger collection of all-pose face images to evaluate our algorithm and demonstrate superior performances than the state-of-the-art methods.
Architectural distortion recognition based on a subclass technique and the sparse representation classifier

Architectural distortion is the third most common sign of breast cancer in mammograms. The accurate recognition is important for computer aided diagnosis of breast cancer. However, due to the subtle symptom and complex structures in the mammogram images, it is difficult to recognize whether a region of interest (ROI) is truly an architectural distortion. In this paper, we proposed a new method for architectural distortion recognition. In the proposed method, several texture features are extracted for each region of interest, including features from GLCM matrix, spiculated related features, entropy features, etc. Feature selection is obtained by a sub-classes clustering based multi-task learning method (SMTL), which can utilize the discriminative label information and reflect the multi-clustering characteristic of the data samples. Finally, the powerful sparse representation based classifier is used for the classification of AD or non-AD. The proposed method has been tested on DDSM dataset and compared with several other methods, the experimental results showed the effectiveness of the proposed method.
Automated Fluidic Assembly of Microvessel-Like Structures Using a Multimicromanipulator System

There is currently a need for a high-throughput flexible assembly method to fabricate artificial microvessels from micro annular modules. In this paper, a novel bubble-assisted fluidic assembly method is presented and a multimicromanipulator system is set up to enable automation. To excite a microflow for assembly, microbubbles are generated by injecting air into the fluid via a glass pipette. The microflow is used to drive the annular module to move up along another glass pipette that passes through the center of the modules. A multimicromanipulator system is used to separately position the two pipettes and the annular modules through a visual servoing control. An adaptive Hough transform is used to detect the annular modules and optimized template matching is developed to obtain the three-dimensional positions of the two glass pipettes. Motion analysis of the annular module and the microbubble is performed to explain the theoretical principles of this method, and key parameters influencing the assembly are analyzed and identified. These parameters are further tested by experiments to improve the success rate and efficiency. Finally, microvessel-like structures with varying outer diameters are fabricated to demonstrate flexibility. Fully automated assembly of a 2.2 mm long microtube with 100% success rate is achieved and the average assembly time consumption per annular module is as low as 2.1 s.