nils-herrmann/clean_scirepeval huggingface dataset:
Simultaneous alignment and clustering for an image ensemble

Joint alignment for an image ensemble can rectify images in the spatial domain such that the aligned images are as similar to each other as possible. This important technology has been applied to various object classes and medical applications. However, previous approaches to joint alignment work on an ensemble of a single object class. Given an ensemble with multiple object classes, we propose an approach to automatically and simultaneously solve two problems, image alignment and clustering. Both the alignment parameters and clustering parameters are formulated into a unified objective function, whose optimization leads to an unsupervised joint estimation approach. It is further extended to semi-supervised simultaneous estimation where a few labeled images are provided. Extensive experiments on diverse real-world databases demonstrate the capabilities of our work on this challenging problem.
Numerical analysis on electric field of three phase outdoor vacuum circuit breaker

The electric field in three phase outdoor vacuum circuit breaker with different instant are calculated and analyzed by finite element method (FEM), taking the effects of floating shield, porcelain casing and silicon rubber insulation on the electric field distribution into account. The distributions of the electric potential and the equal electric field strength of whole domain with different instant are obtained. The electric field simulation of three phase outdoor vacuum circuit breaker is achieved. From the study on distributions of electric potential and equal electric field strength of three phase vacuum circuit breaker, the electric field influence between phases is reflected clearly.
An Adaptive Synchronization of a Chaotic System with Unknown Parameters

The sign of unknown input coefficients is assumed to be known in most papers about the input uncertainties. In this paper, a Nussbaum gain method is adopted to cope with the situation that both the sign and the value of input are unknown. And the unknown parameters can be estimated under the situation of unknown sign of control. At last, numerical simulations are done to show the effectiveness of the proposed method.
Microbubbles for High-Speed Assembly of Cell-Laden Vascular-Like Microtube

Vascular-like microtube takes an important role in delivering oxygen and nutrient to keep cell alive in the generated tissue. In this paper, we present an automated micromanipulation system to assemble 2-D gel micro-rings to vascular-like microtubes by means of generating and controlling microbubbles. The detailed automated assembly process is described. To enable the automated assembly, real-time image processing has been utilized to detect end-effectors and gel micro-rings in 2-D X-Y plane. Additionally, we can acquire an estimated depth information by implementing the optimized template match. The motion model of the microbubbles is analyzed and applied to control the microbubbles. As a preliminary test, a cell-laden microtube consisting of 33 layers gel micro-rings is fabricated. Experimental results show that the bubble-based assembly method and the automated micromanipulation system allow high efficiency and high success rate for the assembly of microtubes.
A simple algorithm for gain spectrum adjustment of backward-pumped distributed fiber Raman amplifiers

In this letter, a simple algorithm for the gain spectrum adjustment of backward-pumped distributed fiber Raman amplifier (B-DFRA) is demonstrated both theoretically and experimentally. It is shown that the change in pump power and corresponding change in gain spectrum are approximately related through a linear matrix, while the elements of the matrix can be easily measured. Feasibility of this algorithm is approved by experiment: a gain ripple of less than 1.2 dB across the C + L band is achieved during net gain adjustment from -15 dB to -9 dB of a 160-channel B-DFRA by varying the launched power of four pumping LDs.
Arc fault diagnosis and analysis based on wavelet neural network

Research on the external characteristic of the switch with contact is an important subject in breaking techniques nowadays. In this paper, based on the proposed experimental platform covering the arc fault diagnosis, load selection and wavelet neural network (WNN) design, a combination method of the experiment and simulation of the actual lines for the arc fault testing system is presented. And the external parameters of the series arc fault has been obtained under different loads, such as the resistance-reluctance loads and a series of electrical loads. By using the wavelet packet transform, frequency bands subdivision of experiment data and energy statistics under different frequency band are accomplished. And the current energy distributions for different loads under fault condition have been obtained and figured out. Additionally, the proposed energy criterion is applied as the input and the trained relax-model WNN can identify the arc fault effectively. By analyzing the arc faults of different loads for the demonstrated cases, the feasibility and the validity of the proposed scheme for arc fault diagnosis is verified.
Optimization of SF/sub 6/ circuit breaker based on chaotic neural network

The chaotic mechanism has been introduced to optimize the electric apparatus in this paper. By combining the chaotic mechanism and artificial neural network (ANN), the chaotic Hopfield neural network (CHNN) has been established, and applied to solve the optimum problem of the demonstrated examples. From the simulation results, it can be found that the proposed CHNN can be employed to solve the optimization problems with multivariables and complex energy function. Furthermore, a novel optimum algorithm for optimizing the electric apparatus has been provided
Design and implementation of code security inspection system based on SVN

This paper proposes a code security inspection system based on the Subversion, which aims to avoid the submission of risk codes that contain vulnerabilities such as SQL injection, XSS (Cross Site Script) attacks and CSRF (Cross-site request forgery) to SVN repositories. In the proposed system, the submitted code will be scanned and checked and then the results will be sent to the SQA (Software Quality Assurance) units to ensure the product's safety. The system mainly adopts dependency injection and inversion of control used in the spring framework, and thus it has high scalability and maintainability. The system is also practical, independent, and highly configurable which can meet the needs of different users.
Image congealing via efficient feature selection

Congealing for an image ensemble is a joint alignment process to rectify images in the spatial domain such that the aligned images are as similar to each other as possible. Fruitful congealing algorithms were applied to various object classes and medical applications. However, relatively little effort has been taken in the direction of compact and effective feature representations for each image. To remedy this problem, the least-square-based congealing framework is extended by incorporating an unsupervised feature selection algorithm, which substantially removes feature redundancy and leads to a more efficient congealing with even higher accuracy. Furthermore, our novel feature selection algorithm itself is an independent contribution. It is not explicitly linked to the congealing algorithm and can be directly applied to other learning tasks. Extensive experiments are conducted for both the feature selection and congealing algorithms.
Fusing Geometric Features for Skeleton-Based Action Recognition Using Multilayer LSTM Networks

Recent skeleton-based action recognition approaches achieve great improvement by using recurrent neural network (RNN) models. Currently, these approaches build an end-to-end network from coordinates of joints to class categories and improve accuracy by extending RNN to spatial domains. First, while such well-designed models and optimization strategies explore relations between different parts directly from joint coordinates, we provide a simple universal spatial modeling method perpendicular to the RNN model enhancement. Specifically, according to the evolution of previous work, we select a set of simple geometric features, and then seperately feed each type of features to a three-layer LSTM framework. Second, we propose a multistream LSTM architecture with a new smoothed score fusion technique to learn classification from different geometric feature streams. Furthermore, we observe that the geometric relational features based on distances between joints and selected lines outperform other features and the fusion results achieve the state-of-the-art performance on four datasets. We also show the sparsity of input gate weights in the first LSTM layer trained by geometric features and demonstrate that utilizing joint-line distances as input require less data for training.
Planar High-Gain Circularly Polarized Element Antenna for Array Applications

This paper proposes a planar high-gain circularly polarized element antenna that can be used for array applications. The substrate-integrated waveguide (SIW) cavity is designed to support dual-resonant modes, the TE120-like and TE210-like modes, for the implementation of circularly polarized radiation performance. Four rectangular radiation slots and a large perturbation, introduced by inserting a metallic via-brick into the SIW cavity, are deployed to achieve a high simulated gain of 10.28 dBi at 6.65 GHz for the proposed element. As a demonstration of an array application, a 4 × 4 array antenna is designed using the proposed element with a compact beam-forming network. Experiments are carried out to verify the designed prototypes. The measured peak gains of the designed element and array antennas are 9.6 and 20.1 dBi, respectively, which include the loss from SMA connectors. Good agreement between simulated and measured results is obtained.
Numerical analyses on the interaction of arc and flow field for SF/sub 6/ circuit breaker

Combined electric field and flow field are numerically simulated based on the computation of the N-S equation and turbulent model, taking the influence of temperature, pressure, and the effect of gas flow on the dynamic arc into consideration. In computing, self-adaptive adjustment of the current has been considered for reflecting the variation of the dynamic arc during the whole interrupting course. Moreover, the gas flow field of high voltage SF6 circuit breakers (HVCBs) with complex flow path, supersonic nozzle, source, viscous, compressible and variable boundaries has been solved. Consequently, the interaction of dynamic arc and gas flow has been simulated. The feature of dynamic arc-gas flow interaction has been numerically analyzed, and the arc choke varying with the pressure of gas flow, velocity, and the flow flux has been simulated. The theoretical foundation for further studying the utilization of arc energy and improving interrupting performance has been established
Circularization and collimation of elliptical Gaussian beam based on kinematic and dynamic ray tracing

A dual shaped reflector system based on kinematic and dynamic ray tracing technique is developed to achieve a circular, collimated, and uniform beam from an elliptical Gaussian beam generated by the Quantum Cascade Laser(QCL) applied in terahertz holographic image system. Simulation result shows that the system has achieved ±0.7dB amplitude ripple and ±7 degree phase vibration for the output beam profile.
Chaotic analysis of High Voltage SF6 circuit breaker during breaking process Part I: Electric field chaos of the arc quenching chamber

A 252kV High Voltage SF6 circuit breaker (HV SF6 CB) is taken as an example in this paper, CC method and Wolf algorithm are applied to identify the chaotic characteristic of the electric field during the breaking process, and it is shown that the chaos phenomena exists in the variation of the electric field strength, especially each observation points exist chaos. And the distribution of the chaotic characteristic in the electric field has the consistency and uniformity feature. Compared with the gas flow characteristic during the breaking process, the prediction of the discharge possibility and insulation weakness is found.
Design and stationary characteristic analysis of magnetic system of small capacity permanent magnet DC contactor

Permanent magnet DC contactor has the advantages of simple structure, low energy consumption and low noise. A magnetic system structure applicable to DC contactor is presented in this paper. Based on the traditional structure of single coil and single stable position contactor, an auxiliary gas gap is added. By changing the size of the gas gap to change the attraction of permanent magnet, the whole magnetic system improves the reliability of breaking-closing operating. A mathematical model of the magnetic system is established, and the magnetic field and the stationary characteristic are calculated by using finite element method. According to the calculations, cooperation between attraction characteristics and counterforce characteristics is analyzed and the result indicates that the magnetic system, which has a advantages of strong electromagnetic actuation, reliable breaking, manual resetting without disassembly, can be used in industrial production.
Improving biometric identification through quality-based face and fingerprint biometric fusion

Multi-modal biometric fusion is more accurate and reliable compared to recognition using a single biometric modality. However, most existing fusion approaches neglect the influence of the qualities of the biometric samples in information fusion. Our goal is to advance the state-of-the-art in biometric fusion technology by providing a more universal and more accurate solution for personal identification and verification with predictive quality metrics. In this work, we developed score-level multi-modal fusion algorithms based on predictive quality metrics and employed them for the task of face and fingerprint biometric fusion. The causal relationships in the context of the fusion scenario are modeled by Bayesian Networks. The recognition/verification decision is then made through probabilistic inference. Our experiments demonstrated that the proposed score-level fusion algorithms significantly improve the verification performance over the methods based on the raw match score of a single modality (face or fingerprint). Furthermore, the fusion framework with both face and fingerprint image qualities achieves the best verification performance and outperforms all other baseline fusion algorithms tested including other straightforward quality-based fusion methods.
Analysis of focal region field of the offset tri-reflector for Compact Antenna Test Range

This paper presents the analysis of the focal region field of the proposed tri-reflector for Compact Antenna Test Range and the matched aperture field for a multimode corrugated horn. The analysis has been carried out by commercial software GRASP and the developed MATLAB program. Numerical results are presented, showing a good match between the two fields. This field can be used to design a matched corrugated horn to compensate the cross-polar field of the offset tri-reflector CATR.
Shipborne radar echo signal denoising based on improved threshold and shrinkage function

In order to denoise shipborne radar (9GHz pulse radar) echo signal in distortion-free, smooth, and less loss, A improved threshold and shrinkage function are proposed in this paper based on the Multi-analysis wavelet threshold denosing. The denoising effects of different shrinkage function for shipborne radar echo signal were compared. The results of experiment show that better SNR and similarity and smoothness and less loss can be reached by using the proposed function to shipborne radar echo signal.
MIMO Antennas for Mobile Handsets

This letter presents a pair of printed MIMO antennas for mobile handsets. With each antenna being a coupled fed monopole in a meandered shape, it is capable of covering GSM 1800/1900, UMTS, WLAN, and LTE frequency bands. The antennas are oriented diagonally at the nongrounded portion of the circuit board. The substrate used for the circuit board is FR4 with relative permittivity of 4.4 and loss tangent of 0.02. The overall volume of the circuit board is 110×65×0.8 mm3, with each antenna occupying an area of 24×14.5 mm2. To improve the isolation between antennas, dual decoupling structures consisting of ground slots and inverted L ground branches that extend into the nongrounded portion are etched diagonally on the bottom layer of the substrate. The isolation achieved is better than 15 dB over all the frequency bands covered by each antenna leading to an envelope correlation coefficient of less than 0.02. The simulation and measured results are in good agreement.
Compact Wideband Circularly Polarized Antipodal Curvedly Tapered Slot Antenna

A method to reduce one direction width of the circularly polarized antipodal curvedly tapered slot antenna, while maintaining the wide axial ratio (AR) and impedance bandwidth and endfire radiation, is proposed in this letter. In this method, the ridge structure in the broad wall of the slotted waveguide is used to increase the current path, which makes the antenna achieving the appropriate phase difference of orthogonal electric fields within narrow antenna width. To validate the proposed method, a prototype of the antenna was fabricated and measured. Experimental results show that the proposed antenna can achieve a bandwidth of 27.6% (50–66 GHz) for both AR < 3 dB and reflection coefficient S11<–10 dB and an average gain of 8.39 dBi.
Automatic Feeding Control for Dense Aquaculture Fish Tanks

This paper introduces an efficient visual signal processing system to continuously control the feeding process of fish in aquaculture tanks. The aim is to improve the production profit in fish farms by controlling the amount of feed at an optimal rate. The automatic feeding control includes two components: 1) a continuous decision on whether the fish are actively consuming feed, and 2) automatic detection of the number of excess feed populated on the water surface of the tank using a two-stage approach. The amount of feed is initially detected using the correlation filer applied to an optimum local region within the video frame, and then followed by a SVM-based refinement classifier to suppress the falsely detected feed. Having both measures allows us to accurately control the feeding process in an automated manner. Experimental results show that our system can accurately and efficiently estimate both measures.
A Benign and Malignant Mass Classification Algorithm Based on an Improved Level Set Segmentation and Texture Feature Analysis

In this paper, we investigate the classification of masses with texture features. We propose an improved level set method to find the boundary of a mass, based on the initial contour provided by radiologists. After the boundary of a mass is found, texture features from Gray Level Co-occurrence Matrix (GLCM) are extracted from the surrounding area of the boundary of the mass. The extracted texture features are used as the input of Linear discriminant analysis and a support vector machine to classify the mass as benign or malignant. Mammography images from DDSM were used in the experiments and the classification accuracy was evaluated using the area under the receiver operating characteristic (ROC) curve. In the proposed method the area under the ROC curve is Az =0.7. The experimental result shows the effectiveness of the proposed method.
PIC simulation of discharge in vacuum and influencing factors

There are great differences between vacuum discharge and common gas discharge. For short gap gas breakdown, the main reason can be explained as followings: electrons from the cathode emission are accelerated by the electric field and impact the anode which will release a lot of metal vapor. The ions produced by the collisions between metal vapor gas molecule and electron impact the cathode and secondary electrons emission will come into being. Based on the field emission theory in vacuum, particle in cell simulation method is used in our paper to trace the motion of electrons produced by cathode emission and ion produced by collision in time and space dimensions. Mont Carlo method is used here to cope with the collisions between electrons and neutral molecules. The cross sections of the collision which relate with the energy are all from the experiments. The secondary electron emission, exciting, elastic and ionizing collisions between electrons and metallic vapor molecules have been considered in our paper. The state parameters of charged particles at any position and time are recorded and the effect of vacuum degree on discharge voltage are simulated which can explain the mechanism of vacuum discharge from microscopic view.
Adaptive-weighted hidden Markov models based 3D model classification

This paper presents an adaptive-weighted hidden Markov models (AWHMM) method for classification of 3D models into a set of pre-determinated model classes. Two new features are proposed to capture model surface orientation information. In the method, each model class is represented by four HMMs corresponding to four type features. During the training process, for each type of feature, the feature statistics of each model class and the spatial dynamics are learned by an HMM. During the classification process, characteristics of the test model are analyzed by the HMMs corresponding to each model class. The likelihood scores provided by the HMMs are calculated, and the highest weighted sum score provides the class identification of the test model. Furthermore, with unsupervised learning, each HMM and type weight are adapted with test models, which results in better modeling over time. Based on experiments, the proposed algorithm achieves much better performance than a baseline method and better performance than HMMs using only two features with fixed weights method.
Adaptive 3D Face Reconstruction from Unconstrained Photo Collections

Given a collection of "in-the-wild" face images captured under a variety of unknown pose, expression, and illumination conditions, this paper presents a method for reconstructing a 3D face surface model of an individual along with albedo information. Motivated by the success of recent face reconstruction techniques on large photo collections, we extend prior work to adapt to low quality photo collections with fewer images. We achieve this by fitting a 3D Morphable Model to form a personalized template and developing a novel photometric stereo formulation, under a coarse-to-fine scheme. Superior experimental results are reported on synthetic and real-world photo collections.
Vortex-Driven Rotation for Three-Dimensional Imaging Under Microscopy

The noninvasive rotary motion of bio-objects for three-dimensional (3-D) observation and posture adjustment has been a great challenge in microrobotics. This letter reports a harmless noncontact 360° rotation method with a controllable velocity, which applied the vortex induced by vibrating the micropipette in an open fluidic environment. The micropipette was driven by a piezo actuator, which was mounted on a copper pillar. By generating a resonance between the copper pillar and the piezo actuator fed with sine wave of a specific frequency, we controlled the micropipette to vibrate circularly. The vibration-induced vortex around the micropipette could trap micro objects close to it, and then drive the trapped objects to rotate with the uneven drag force acting on their surface. Experiments of 360° rotation of the microbeads were carried out to demonstrate this method and analyze the rotation velocity. An application in 3-D imaging under optical inverted microscopy was achieved. The spheroids assembled by single cells were rotated, which enabled us to observe the different aspects of the cell spheroids and reconstruct its 3-D view.