nils-herrmann/clean_scirepeval huggingface dataset:
Learning Discriminative Subspaces on Random Contrasts for Image Saliency Analysis

In visual saliency estimation, one of the most challenging tasks is to distinguish targets and distractors that share certain visual attributes. With the observation that such targets and distractors can sometimes be easily separated when projected to specific subspaces, we propose to estimate image saliency by learning a set of discriminative subspaces that perform the best in popping out targets and suppressing distractors. Toward this end, we first conduct principal component analysis on massive randomly selected image patches. The principal components, which correspond to the largest eigenvalues, are selected to construct candidate subspaces since they often demonstrate impressive abilities to separate targets and distractors. By projecting images onto various subspaces, we further characterize each image patch by its contrasts against randomly selected neighboring and peripheral regions. In this manner, the probable targets often have the highest responses, while the responses at background regions become very low. Based on such random contrasts, an optimization framework with pairwise binary terms is adopted to learn the saliency model that best separates salient targets and distractors by optimally integrating the cues from various subspaces. Experimental results on two public benchmarks show that the proposed approach outperforms 16 state-of-the-art methods in human fixation prediction.
On computing three-finger force-closure grasps of 2-D and 3-D objects

In this paper, we present a novel algorithm for computing three-finger force-closure grasps of 2D and 3D objects. In the case of a robot hand with three hard fingers and point contact with friction, new necessary and sufficient conditions for 2D and 3D equilibrium and force-closure grasps have been deduced, and a corresponding algorithm for computing force-closure grasps has been developed. Based on geometrical analysis, the algorithm is simple and only needs a few algebraic calculations. Finally, the algorithm has been implemented and its effectivity has been demonstrated by two examples.
Greedy Orthogonal Matching Pursuit algorithm for sparse signal recovery in compressive sensing

The sparse signal recovery problem has been the subject of extensive research in several different communities. Tractable recovery algorithm is a crucial and fundamental theme of compressive sensing (CS), which has drawn significant interests in the last few years. In this paper, we firstly analyze the iterative residual in Orthogonal Matching Pursuit (OMP) algorithm. Secondly, a greedier algorithm is introduced, which is called Greedy OMP (GOMP) algorithm. This algorithm iteratively identifies more than one atoms using greedy atom identification, and then discards some atoms, which are of high similarity with the optimal atom. Compared with OMP algorithm, the experiments conducted on Gaussian and Zero-one sparse signal demonstrate that the proposed GOMP algorithm can provide better recovery performance. Finally, we experimentally investigate the effect of greedy constant in GOMP upon the recovery performance.
Combination forecasting based on Support Vector Machine and its application

In this paper, we first introduce the principles and methods of Support Vector Machine (SVM), then give the methods of determining weights of combination forecasting using Support Vector Machine. This method can overcome the shortcoming of the other combination forecasting, which keeps smaller fitting error and higher forecasting accuracy, therefore the effect of forecasting is greatly promoted. At last, this method is applied to forecast the total number of health personnels of Hebei province. Contrast trial indicates that this method possesses fast operation velocity and good generalization performance.
In-Band RCS Reduction and Gain Enhancement of a Dual-Band PRMS-Antenna

In this letter, a novel dual-band polarization rotation metasurface (PRMS) antenna with in-band radar cross section (RCS) reduction and gain enhancement is designed and analyzed. The dual-band PRMS-antenna consists of a slot patch for radiation and a PRMS configuration surrounding the patch for in-band RCS reduction. The gain enhancement is achieved by strong coupling between radiation patch and PRMS, and the in-band RCS reduction is realized by the phase cancellation of reflected polarized waves. The simulated results indicate that the boresight gain of the proposed PRMS-antenna is enhanced to 7.9 and 6.3 dBi at 5.2 and 10.4 GHz, respectively. Meanwhile, the dual-band 6 dB RCS reduction is from 5.2 to 5.4 GHz and from 10.1 to 11.4 GHz, covering the operation band of the proposed antenna. The measurements agreed well with the simulations.
Mandarin Emotional Speech Recognition Based on SVM and NN

The exploration of how we as human beings react to the world and interact with it and each other remains one of the greatest scientific challenges. The ability to recognize emotional states of a person perhaps the most important for successful inter-personal social interaction. Automatic emotional speech recognition system can be characterized by the used features, the investigated emotional categories, the methods to collect speech utterances, the languages, and the type of classifier used in the experiments. In this paper, we used SVM and NN classifiers and feature selection algorithm to classify five emotions from Mandarin emotional speech and compared their experimental results. The overall experimental results reveal that the SVM classifier (84.2%) outperforms than NN classifier (80.8%) and detects anger perfectly, but confuses happiness with sadness, boredom and neutral. The NN classifier achieves better performance in recognizing sadness and neutral and differentiates happiness and boredom perfectly
Bias-compensated LMS algorithm for sparse systems over adaptive network

We propose bias-compensated algorithms based on the RZA-LMS algorithm and diffusion RZA-LMS algorithm. Our proposed algorithms improve the accuracy of estimation under the situation that input of the adaptive filter contains noise. Estimation methods of the input noise' variance are given for implementing our single-node and diffusion bias-compensated algorithms. Simulation results show that the proposed algorithms have better accuracy than algorithms without bias-compensation and the estimation results are unbiased under different noise levels.
Calibrating human hand for teleoperating the HIT/DLR hand

Using human action to guide robot execution can greatly reduce the planning complexity. We calibrate a human hand model and map its motion to a four-finger dexterous robot hand. The parameters of human hand model are determined by open-loop kinematic calibration method based on a vision system. We analyze the kinematic difference between the human hand and dexterous robot hand, and present a modified fingertip mapping to solve the partial overlap of the fingertip workspaces. 3D graphic simulation and manipulation experiments show that the accuracy of the human hand model and the mapping method are sufficiently precise for teleoperation tasks.
Investigation on structural colours in wing scales of butterfly Papilio peranthus Fabricius

The microstructure and geometrical dimensions of the scales on a butterfly Papilio peranthus Fabricius wing are obtained using scanning electron microscopy and transmission electron microscopy. Two kinds of scales are found in a butterfly wing and the structural colour mainly comes from the cover scale. Different structural models of cover scale that are related to ridge and concavity are constructed and their corresponding optical properties are investigated using the finite-difference time-domain  method. It is concluded that the structural colour on the cover scale mainly comes from the sculpted multilayer structure and the ridge on the scale has few effects on the structural colour. When the curvature of the sculpted multilayer structure decreases, the dominant wavelength of colour will shift to a longer wavelength and move slower and slower. The two-dimensional planar multilayer model can be used to calculate the structural colour when the curvature exceeds a certain value.
Real-Time Video Detection of Road Visibility Conditions

For the growing number of accidents caused by poor visibility, visibility measurement which can alert drivers and inform traffic division managements when poor visibility occurs is a key parameter in driving assistance system. This paper is to implement a visibility measurement system that based on traffic video-surveillance system can both detect fog and estimate visibility distance. We propose a method to detect visibility distance by contrast of road surface with distance information. The method integrates the targets’ contrast and curve fitting to get visibility distance. The system is operative in every kind of weather in day-time. The experimental results in practical are uniform to human perception.
Optimizing Electrode Configuration for Electrical Impedance Measurements of Muscle via the Finite Element Method

Electrical impedance myography (EIM) is a technique for the evaluation of neuromuscular diseases, including amyotrophic lateral sclerosis and muscular dystrophy. In this study, we evaluated how alterations in the size and conductivity of muscle and thickness of subcutaneous fat impact the EIM data, with the aim of identifying an optimized electrode configuration for EIM measurements. Finite element models were developed for the human upper arm based on anatomic data; material properties of the tissues were obtained from rat and published sources. The developed model matched the frequency-dependent character of the data. Of the three major EIM parameters, resistance, reactance, and phase, the reactance was least susceptible to alterations in the subcutaneous fat thickness, regardless of electrode arrangement. For example, a quadrupling of fat thickness resulted in a 375% increase in resistance at 35 kHz but only a 29% reduction in reactance. By further optimizing the electrode configuration, the change in reactance could be reduced to just 0.25%. For a fixed 30 mm distance between the sense electrodes centered between the excitation electrodes, an 80 mm distance between the excitation electrodes was found to provide the best balance, with a less than 1% change in reactance despite a doubling of subcutaneous fat thickness or halving of muscle size. These analyses describe a basic approach for further electrode configuration optimization for EIM.
A New Limit Equation Based Stability Analysis of Linguistic Fuzzy Control System

Fuzzy control has always been an active discipline in fuzzy set theories and in fuzzy control the stability analysis is one of the most important issues and is also of great interest to scholars in this area. Many important results have been obtained in Tanaka-Sugeno fuzzy control system based on Lyapunov stability theory in the past ten years. Stability analysis in Mamdani fuzzy control system is still quite limited, though it is the first fuzzy controller of their kinds in literature. In this paper, stability analysis of Mamdani type fuzzy controller is studied based on a limit relation equation deduced from the generalized fuzzy control system. The structure and the solutions of the limit equation are closely related with the stability of the fuzzy system. The minimal solutions of the limit equation produce elementary stable matrix forms, which are useful to analyze the stability of closed loop fuzzy systems. An example from the level control of water tank illustrates the proposed method
Dielectric and Magnetic Properties of Co $_{2}$ O $_{3}$ Modified 0.4PZT ${+}$ 0.6NiCuZn-Ferrite Composites

In order to improve the electromagnetic properties of 0.4PZT+0.6NiCuZn-ferrite composites for suppressing electromagnetic interference (EMI), Co2O3 was introduced. The effects of Co2O3 content on the electromagnetic properties of the composite materials were investigated. It was confirmed the existence of local induced anisotropy caused by ordering of Co2+ ions. Permeability spectra of the composites with different Co2O3 content had been resolved into contributions of domain wall resonance and spin rotation relaxation. The fitting results of permeability dispersion revealed the relationships among domain wall resonance, spin rotation relaxation mechanisms, and local induced anisotropy. This increase in local inducted anisotropy results in a decrease of initial permeability and an increase of Q-factor. Meanwhile, Co2O3 additive can improve the dielectric constant and the loss tangent (tandeltae) by increasing the oxygen vacancy concentration.
Dynamic Cluster Formation Game for Attributed Graph Clustering

Besides the topological structure, there are additional information, i.e., node attributes, on top of the plain graphs. Usually, these systems can be well modeled by attributed graphs, where nodes represent component actors, a set of attributes describe users’ portraits and edges indicate their connections. An elusive question associated with attributed graphs is to study how clusters with common internal properties form and evolve in real-world networked systems with great individual diversity, which leads to the so-called problem of attributed graph clustering (AGC). In this paper, we comprehended AGC naturally as a dynamic cluster formation game (DCFG), where each node’s feasible action set can be constrained by every cluster in a discrete-time dynamical system. Specifically, we carried out a deep research on a special case of finite dynamic games, named dynamic social game (DSG), the convergence of the finite Nash equilibrium sequence in a DSG was also proved strictly. By carefully defining the feasible action set and the utility function associated with each node, the proposed DCFG can be well related to a DSG; and we showed that a balanced solution of AGC could be found by solving a finite set of coupled static Nash equilibrium problems in the related DCFG. We, finally, proposed a self-learning algorithm, which can start from any arbitrary initial cluster configuration, and, finally, find the corresponding balanced solution of AGC, where all nodes and clusters are satisfied with the final cluster configuration. Extensive experiments were applied on real-world social networks to demonstrate both effectiveness and scalability of the proposed approach by comparing with the state-of-the-art graph clustering methods in the literature.
A fuzzy clustering based approach for generating interpretable fuzzy models

A systematic fuzzy modeling approach considering both accuracy and interpretability is developed in this paper. First, fuzzy clustering algorithm, combined with least square method, is used to obtain initial fuzzy model with excessive rules. Then rule reduction is performed by orthogonal least squares to obtain simplified fuzzy model with high interpretability. Finally, genetic algorithm is adopted to optimize the simplified fuzzy model to improve accuracy. The proposed approach is successfully applied to a real world coke-oven temperature system, and the result shows its effectiveness.
Detection efficiencies of parallel, fan and cone beam collimators for source distributions in an attenuating medium

Fan-beam (FB) and cone-beam (CB) collimators have been applied in SPECT due to their improved trade-off between spatial resolution and detection efficiency when compared with conventional parallel-hole (PH) collimators. However, the advantages have usually been evaluated in the absence of attenuation and scatter. In this study, the authors studied the detection efficiencies of the three collimator geometries in more realistic imaging situations. Theoretical formulations were derived for the detection efficiencies of the three collimators for point and line sources placed in air and inside attenuating media with attenuation effect only. The effects of scatter were investigated using Monte Carlo simulation methods. For primary photons with and without attenuation effect, theoretical predictions agreed with results from Monte Carlo simulations. They indicate that for a point source, the relative detection efficiencies of FB and CB with respect to PH collimator at different depths in an attenuating medium are the same as those without attenuation. For a line source placed along the central axes of the collimators, the relative detection efficiencies of the FB and CB collimators are lower with attenuation than without. This is due to the increased attenuation effect at greater depths outweighing the increase in geometric efficiency. The addition of scatter does not significantly change the relative efficiencies for a line source. Finally, the signal-to-noise ratios of the FB and CB are higher than that of the PH collimator and the differences increase with source depth. The understanding of the relative detection efficiencies is important in evaluating potential clinical applications of the FB and CB collimators.<<ETX>>
Metadata Specification of Railway Video Information and Its Application in Video Monitoring System for Qinghai-Tibet Railway

The lack of homogeneity in description elements and description method leads to video information sharing and management in the relative video application and management system for more management departments at all levels hampered. Based on the relevant metadata standards and the metadata technique, we put forward the railway video metadata specification, which consisted of mandatory elements, optional elements and extension elements, and the feasible method of key-frame and time- point. Then we apply the metadata specification in video monitoring system for Qinghai-Tibet railway. In this system, combined and matched the real-time video capture with the existing cataloging video, the video information is described accurately and displayed immediately. These works lay the foundation for building a normative video information management system and establish norms of video metadata cataloging to meet individual application requirements, improving the resource efficiency of the national railway video.
Optimizing Cosine Window Functions by Differential Evolution

This paper proposed an evolutionary method to optimizing the cosine window family by using Differential Evolution (DE). First, the classic cosine windows such as Hamming window and Blackman window are optimized. Results show better performance in terms of side-lobe level and roll-off ratio for the same main-lobe width. Then, a series of optimized six order cosine windows are provided and their performances are analyzed. The comparison proves that the proposed method is an effective approach for the design of window functions.
Discriminant local information distance preserving projection for text-independent speaker recognition

A novel method is presented based on a statistical manifold for text-independent speaker recognition. After feature extraction, speaker recognition becomes a sequence classification problem. By discarding time information, the core task is the comparison of multiple sample sets. Each set is assumed to be governed by a probability density function (PDF). We estimate the PDFs and place the estimated statistical models on a statistical manifold. Fisher information distance is applied to compute distance between adjacent PDFs. Discriminant local preserving projection is used to push adjacent PDFs which belong to different classes apart to further improve the recognition accuracy. Experiments were carried out on the NIST SRE08 tel-tel database. Our presented method gave an excellent performance.
Effect of environmental temperatures on flower morphology and fertility alternation of male sterile line 160S of Brassica napus

Comparison on the flower morphologic and pollen fertility alteration of male sterile line 160S in Brassica napus under natural temperature conditions were conducted. The results showed that the temperature was the main factors to flower morphologic and pollen fertility alteration. Under male sterile conditions, the anthers of 160S were all smaller than the normal ones and the pollens were completely male sterile, the ratio of pollen stained with TTC solution were nearly 0 and the self-pollenated pod-setting ratio was only 1.2%. The anthers of 160S were all normal, and there were no difference with the anthers of those two normal lines under fertile condition. The percentage of fertile pollen stained with TTC solution and the self-pollenated pod-setting ratio were all above 80%. The percentage of pollen fertility and the self-pollenated pod-setting ratio of 160S decreased along with temperature rising, and the fertility transformation direction was fertile, part fertile and then complete sterile. The study showed that 160S showed complete male sterility above 25°C while it showed complete normal fertility below 18°C.
Locating visual storm signatures from satellite images

Weather forecasting is a problem where an enormous amount of data must be processed. Severe storms cause a significant amount of damages and loss every year in part due to the insufficiency of the current techniques in producing reliable forecasts. We propose an algorithm that analyzes satellite images from the vast historical archives to predict severe storms. Conventional weather forecasting involves solving numerical models based on sensory data. It has been challenging for computers to make forecasts based on the visual patterns from satellite images. In our system we extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. Particularly, the algorithm extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts.
Research on band selection of MODIS data

MODIS belonged to the new generation of optical and thermal remote sensor that combines both images and spectrum is one of the most important sources for observing land surface change and analyzing the development of terrestrial biosphere. It is very important to determine the optimal band sets from its 36 bands according to specific application purpose for further management analysis and information extraction of multi-spectral dada. Based on the analysis of selection criteria, a subspace-division-based (SD) method was proposed after the comprehensive contrary of current modish methods. Then one swath MODIS data covered Beijing was disposed for supervised classification experiment to validate the suitability of this method. The validation demonstrated that the accuracy of land using cover classification using the 12 bands selected by SD method is 92.04% without other auxiliary data in medium-scale spatial resolution.
Research on systematic framework of China Railway Geographic Information System (RGIS)

Railway Ministry of China has started to research on how to set up China Railway Geographic Information System (RGIS). This paper researches the position of China RGIS in China Railway Informationization Plan, indicates that China Railway Informationization Plan is a hierarchical model and China RGIS should be the infrastructure and share platform for all China railway information systems. The whole framework of RGIS, including logic frame, data diagram, communication network structure and application modes, are studied in this paper. Based on the China railway industry's cooperative application mode and its distributive and hetero-structural characteristics of data and application, this paper puts forward a share platform with component mode and distributed cooperative structure to implement RGIS.