nils-herrmann/clean_scirepeval huggingface dataset:
Rhythmic Brushstrokes Distinguish van Gogh from His Contemporaries: Findings via Automated Brushstroke Extraction

Art historians have long observed the highly characteristic brushstroke styles of Vincent van Gogh and have relied on discerning these styles for authenticating and dating his works. In our work, we compared van Gogh with his contemporaries by statistically analyzing a massive set of automatically extracted brushstrokes. A novel extraction method is developed by exploiting an integration of edge detection and clustering-based segmentation. Evidence substantiates that van Gogh's brushstrokes are strongly rhythmic. That is, regularly shaped brushstrokes are tightly arranged, creating a repetitive and patterned impression. We also found that the traits that distinguish van Gogh's paintings in different time periods of his development are all different from those distinguishing van Gogh from his peers. This study confirms that the combined brushwork features identified as special to van Gogh are consistently held throughout his French periods of production (1886-1890).
A procedure for InSAR raw data simulation of complex radar scenes

Based on three-dimensional (3-D) modeling technique, a procedure for interferometric synthetic aperture radar (InSAR) raw data simulation of complex radar scenes is proposed. 3-D models are used to describe the geometries of the scene as well as the distribution of the different scattering characteristics of targets in the scene. A modification to conventional processing of shadowing is made to adapt the irregular grids of the 3-D models. Numerical simulation results demonstrate the validity and usefulness of the proposed technique.
A Novel Probability Evaluation Method for Selective Forwarding Routing in Wireless Sensor Network

Selective forwarding is one of the routing methods that if more than one downstream node are available at either the source or an intermediate node, the packet is forwarded along only one downstream link based on local conditions. In the paper, the selective forwarding probability based on the node degree and link loss is presented to increase the reliability of selective forwarding. The performance is analyzed through regular square network topology qualitatively and the simulation results show the effects of the parameters on our methods
Aliveness of Fuzzy Dynamic Petri Net Systems

Fuzzy Petri net system is an important tool to analyze the behavior of concurrent systems. With a formal definition of fuzzy dynamic Petri nets, the concept of fuzzy Petri net language is first proposed in this paper. Based on the analysis of fuzzy Petri net language, the aliveness and the blocking of fuzzy Petri net are studied afterwards. Further, the relationship between the aliveness of language and blocking of the system is proposed. Finally, an example is given to illustrate the importance of aliveness analysis based on fuzzy Petri net Language.
Characterizing the Footprint of Eddy Covariance System and Large Aperture Scintillometer Measurements to Validate Satellite-Based Surface Fluxes

To validate satellite-based surface fluxes by ground measurements properly, several numerical simulations were carried out at a homogeneous alpine meadow site and mixed cropland site, considering various atmospheric conditions and different land cover distribution types. By comparing various pixel selection methods, the results showed that footprint was significant in insuring a consistent spatial scale between ground measurements and satellite-based surface fluxes, particularly for heterogeneous surface and high-resolution remote sensing data. Because large aperture scintillometer measurements cover larger areas than eddy covariance (EC) system measurements, the spatial heterogeneity at a subpixel scale in complicated surface should be further considered in validating coarse satellite data. Thus, more accurate validation data and scaling methods must be developed, such as measuring surface fluxes at the satellite pixel scale by a flux measurement matrix or airborne EC measurements.
RACCOON: a peer-based system for data integration and sharing

Recent database applications see the emerging need to support data integration in distributed, peer-to-peer environments, in which autonomous peers (sources) connected by a network are willing to exchange data and services with each other. To address related research challenges, we are developing a system called "RACCOON", which allows different sources to integrate and share their data. We use an application to show several important features of the RACCOON system. The system also suggests semantic mappings for the user to choose. We show the two different querying modes, particularly how a query is expanded using the semantic mappings in the extended querying mode to compute as many answers to the query as possible.
Research on optimization of fuzzy control rules based on particle swarm optimization algorithm

In order to avoid the complex adjustment of scaling factor and quantization factor in the design of fuzzy controller and the shortcomings that the fuzzy control rules can not be changed once identified, a fuzzy controller with self-optimizing rules is adopted . Particle swarm optimization (PSO) algorithm is used to optimize the parameters of fuzzy controller. A new evaluation function including the system adjusting time, rise time, over-shoot, and steady-state error is defined. A group of parameters of the fuzzy controller that minimize the evaluation function is calculated rapidly by searching in the given controller parameters area. Numerical simulations show that the controller can easily be applied to the first-order and second-order system with time delay, no overshoot, and its performance is also better than the classic PID optimized by PSO.
Compact quasi-elliptic function filter based on defected ground structure

A novel defected ground structure (DGS) is investigated for filter applications. With this structure, the basic resonant element exhibits the quasi-elliptic function responses. A new equivalent lumped L–C circuit model is presented and its corresponding L–C parameters are extracted by using parametric relationships, which has quasi-elliptic characteristics. The theoretical analysis for the effect of different design parameters has been carried out, which provides effective guidance in designing DGS. The performance of the new filter is also compared with the characteristic of the dumb-bell DGS filter to highlight the advantages of the proposed DGS. Based on the equivalent circuit model, a three-pole quasi-elliptic lowpass filter (LPF), using two DGS units cascaded, is optimally designed and implemented; experimental results show good agreement with theoretical ones.
Fuzzy boundary layer adaptive sliding mode controller design for a hypersonic vehicle based on tangent reaching law

Due to the problem of serious nonlinear, strong coupling, uncertain parameters existed in the process of hypersonic vehicle's flight, this paper designs a fuzzy boundary layer adaptive sliding mode controller based on tangent reaching law. Firstly, the longitudinal model is linearized exactly, and then by introducing a parameters adjusted by online fuzzy logic system as sliding boundary layer, quasi-sliding mode control based on tangent reaching law is applied to the outside of the boundary layer, so the system states can reach the sliding boundary layer quickly. When the system states reach the boundary layer, inputs transform smoothly to the improved boundary control law designed with a saturation function. The system states are ensured to reach the sliding surface in a finite time, and the high frequency chattering is lowered. Simulation results illustrate the effectiveness of the control algorithm.
Radiated EMI coupling analysis between high-speed modules and receiving antennas of mobile devices

This study mainly investigates the impact of high-speed digital modules' radiated EMI noise on receiving performance of wireless mobile device via built-in antenna coupling. We began with designing dipole and loop antenna to represent the routing and trace pattern for common- and differential- mode current flowing inside digital modules installed in mobile devices(such as Tablet, Notebook computers, and smart phones), and then observed the coupling effect of their EMI noise on receiving antenna ports. Utilization of EMI measuring equipment described in this paper not only can obtain the interference power corresponding to the frequencies and levels of noise from device under test (DUT), we can also derive the radiation patterns related to common- and differential-mode radiation from surface scanning results. We would then further establish the relationship between the DUT characteristics and noise locations to find the optimal placement for noisy DUT and antennas. The result of this study can help to establish the preliminary noise budget for those components built in the wireless communication platforms.
A Heuristic Reinforcement Learning for Robot Approaching Objects

Autonomous approaching objects for an arm-hand robot is a very difficult problem because the possible arm-hand configurations are numerous. In this paper, we propose a modified reinforcement learning algorithm for a multifingered hand approaching target objects. The proposed approach integrates the heuristic search information with the learning system, and solves the problem of how an arm-hand robot approaches objects before grasping. In addition, this method also overcomes the problem of time consuming of traditional reinforcement learning in the initial learning phase. The algorithm is applied to an arm-hand robot to approach objects before grasping, which can enable the robot to learn approaching skill by trial-and-error and plan its path by itself. The experimental results demonstrate the effectiveness of the proposed algorithm
Characterizing elegance of curves computationally for distinguishing Morrisseau paintings and the imitations

Computerized analysis of paintings has recently gained interest. The rapid technological advancements and the expanding interdisciplinary collaboration present us a promising prospect of computer-assisted authentication. We focus on the characterization of curve elegance. Specifically, we propose measures of curve steadiness and neighborhood coherence from brushstrokes. The technique has been applied to the paintings of renowned aboriginal Canadian artist Norval Morrisseau. Through computerized analysis of his authentic works and the imitations, it is revealed that the curves in his authentic paintings exhibit his commanding painting skills. The smooth and steady flow of the curves show less hesitancy of the artist than the authors of counterfeit works. The tangent angles tend to be more consistent along curves in the authentic paintings than in the imitations.
Fault detection method for the rolling bearings of metro vehicle based on RBF neural network and wavelet packet transform

To detect the rolling bearings fault of metro vehicle, a method combined wavelet packet with RBF neural network is proposed in this paper. Firstly, wavelet denoising is performed for the vibration signal to remove invalid signal. And then, energy characteristic vectors of the fault signals are extracted by wavelet packet decomposing to train the RBF neural network. Finally, the trained RBF neural network is used for fault classification. The diagnostic results show that the proposed method can be used to detect fault types of the metro vehicle rolling bearings precisely.
Reconstrucion and visualization of 3D surface model from serial-sectioned contour points

In three-dimensional accurate radiotherapy treatment planning system, one of the key steps in the whole planning is to reconstruct and visualize the surface model of tumor target and organs at risk (OAR) from a serial of cross-sectioned contour points rapidly and accurately. This study designed a fast 3D-reconstruction and visualization pipeline comprising the following four main steps: ©pre-processing of contour points dataset; ©extraction and simplification of Iso-surface; ©linear transformation of surface model; @ Smoothing the surface model. An open source Visualization Toolkit (VTK) was applied to implement this method and a friendly user interface was developed on the Visual C++ development platform. Several clinic patients' CT datasets were chosen for test data. The results show that this method could effectively avoid the “ladder effect” of standard marching cubes (MC) algorithm due to inconsistency between slice spacing and image resolution. The reconstruction surface is simplified to speed up the rendering time. Furthermore, it has been successfully integrated into domestic Accurate/Advanced Radiotherapy Treatment Planning System (ARTS) for clinical use.
Loading metamaterial perfect absorber method for in-band radar cross section reduction based on the surface current distribution of array antennas

A loading metamaterial perfect absorber (MPA) method is proposed to reduce the in-band radar cross section (RCS) and preserve the radiation characters for the guidewave slot array antennas in this study. The surface current distributions of the array antennas are divided into the strong current area and the weak current area. The metal surface with the strong current is retained to avoid the radiation deterioration, and the MPA is only loaded on the weak current area by the three layers MPA for RCS reduction. The RCS of a 1 × 10 guidewave slot array antennas is reduced using the method. Simulated S 11, radiation patterns, gain and RCS reduction of the array antennas are compared with measured results. Experimental results indicated that the in-band RCS of the array antennas loading the MPA has dramatically reduced with only about 0.73 dB gain reduction and the RCS reduction are not significant in out-of-band while the radiation characters is unchanged. The experimental results are in good agreement with the numerical simulations.
Aesthetics and Emotions in Images

In this tutorial, we define and discuss key aspects of the problem of computational inference of aesthetics and emotion from images. We begin with a background discussion on philosophy, photography, paintings, visual arts, and psychology. This is followed by introduction of a set of key computational problems that the research community has been striving to solve and the computational framework required for solving them. We also describe data sets available for performing assessment and outline several real-world applications where research in this domain can be employed. A significant number of papers that have attempted to solve problems in aesthetics and emotion inference are surveyed in this tutorial. We also discuss future directions that researchers can pursue and make a strong case for seriously attempting to solve problems in this research domain.
Genus-Zero Shape Classification Using Spherical Normal Image

A new method for three dimensional (3D) genus-zero shape classification is proposed. It conformally maps a 3D mesh onto a unit sphere and uses normal vectors to generate a spherical normal image (SNI). Unlike extended Gaussian images which have an ambiguity problem, the SNI is unique for each shape. Spherical harmonics coefficients of SNIs are used as feature vectors and a self-organizing map is adopted to explore the structure of a shape model database. Since the method compares only the SNIs of different objects, it is computationally more efficient than the methods which compare multiple 2D views of 3D objects. The experimental results show that the proposed method can discriminate collected 3D shapes very well, and is robust to mesh resolution and pose difference
Dynamic Programming of Maintenance Support Resources in the War

The scientific scheduling of maintenance support resources in the war is very important to accomplishing the task of maintenance support, but the finity of maintenance support resources has a demand that the commander of maintenance support must schedule maintenance support resources dynamically. The paper consideres total effect of maintenance support, and takes the current and latent need into account. It solves the problem of the dynamic programming of maintenance support resources in achieving task earliest and total least time with the nonlinear mixed-integer programming model. In the end an example is given to validate the feasibility of the method.
Energy Saving and Optimal Control of Gas Boiler Group

In order to achieve energy-saving and improve the quality of heat output, the optimize energy-saving control system based on the original boiler group was designed. This article is aimed to discuss the feed-forward control technology based on the optimal air-NG(natural gas) ratio combustion and the control strategy of the boiler group based on feedback and feed-forward compensation, what's more, system structure and backup redundancy technology are introduced in this article.
Mamdani Model Based Adaptive Neural Fuzzy Inference System and its Application in Traffic Level of Service Evaluation

Hybrid algorithm is the hot issue in Computational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classification method and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy Inference System (M-ANFIS) and weight updating formula in consideration with qualitative representation of inference consequent parts in fuzzy neural networks. M-ANFIS model adopts Mamdani fuzzy inference system which has advantages in consequent part. Experiment results of applying M-ANFIS to evaluate traffic Level of service show that M-ANFIS, as a new hybrid algorithm in computational intelligence, has great advantages in non-linear modeling, membership functions in consequent parts, scale of training data and amount of adjusted parameters.
An adaptive transport protocol for multimedia communication

We propose a novel approach for effectively supporting multimedia packet flows in an Internet environment. The following are the key contributions of the paper: (a) we propose a new transport protocol called HPF that supports multiple interleaved reliable and unreliable data substreams; (b) we decouple the congestion control and reliability mechanisms that are integrated in TCP-this allows us to provide congestion control for unreliable streams as well as reliable streams; and (c) we use priorities within substreams of a packet flow as application defined hints for the link level scheduler to drop packets during congestion. We show through performance measurements in our experimental testbed that our approach can provide effective support for heterogeneous packet flows in the presence of dynamic networking resources.
ABiRCNN with neural tensor network for answer selection

Answer selection is a very important task in domain question answering. However, because of the word variety between questions and answers, there exists the lexical gap between questions and answers, which is the major challenge in question answer matching. In this work, in order to overcome the lexical gap, we propose an attention based bidirectional gated convolution with neural tensor network (ABiRCNN+NTN), which can improve the representations for both questions and answers and model their interactions with a neural tensor network. We carry out large-scale experiments on answer selection dataset, InsuranceQA and achieve new state-of-the-art results on InsuranceQA dataset. The experimental results demonstrate that our model can effectively capture the complex semantic relations between questions and answers and encode them in a more effective way. The source code of our work can be obtained from https://github.com/paperstudy/AnswerSelection.
Conversion degree functions induced by qualitative mapping and fuzzy artificial neurons

Two definitions of qualitative mapping (QM) and conversion degree function (CDF) are presented in this paper. It is shown that, under the action of some special conversion degree functions, its qualitative criterion is turned into a fuzzy qualitative criterion. A fuzzy artificial neuron can be induced by an m-dimension weight conversion degree function (MWCDF) /spl eta/i(x), and two classifying algorithms based on MWCDF for two nonlinear patterns, XOR and two spirals, are given respectively.
QoMOR: A QoS-aware MAC protocol using Optimal Retransmission for Wireless Intra-Vehicular Sensor Networks

The paper proposes a MAC layer protocol called QoMOR (QoS-aware MAC protocol using optimal retransmission) that is designed to provide QoS in a decentralized network with multiple sensor (source) nodes that do not have the capability to receive acknowledgements from the sink node. A minimum data delivery probability between the sensor and sink nodes is achieved by allowing each source node to transmit each new packet an optimal number of times in every interval of time. The paper first discusses the single QoS class case and derives the maximum achievable frame delivery probability and then extends the concepts to the multiple QoS class case. It also addresses a few design optimization criteria. Simulation and numerical analysis results show that QoMOR can effectively provide QoS guarantees under distributed control without using conventional ARQ-based schemes.
Estimating Visual Saliency Through Single Image Optimization

This letter presents a novel approach for visual saliency estimation through single image optimization. Instead of directly mapping visual features to saliency values with a unified model, we treat regional saliency values as the optimization objective on each single image. By using a quadratic programming framework, our approach can adaptively optimize the regional saliency values on each specific image to simultaneously meet multiple saliency hypotheses on visual rarity, center-bias and mutual correlation. Experimental results show that our approach can outperform 14 state-of-the-art approaches on a public image benchmark.
Improved compact channel current model of power radio frequency SOI LDMOS for CAD tools

Based on a drift current model, along the channel current of MM20 model, an approved SOI LDMOS compact model is presented in this paper. A continued and concise expression of the presented model for easily analysis of harmonic balance, which considers the quasi-saturation effect of SOI LDMOS and short channel effect, are observed. Comparison of simulated results of DC I-V and transform characteristic for the presented model with measured data are made, which shows they are well agreed, and this model is verified.
Long-term optimal operation of micro-grid with micro-hydropower and energy storage

Micro-grid can either be interconnected with power grid or be disconnected and operate independently. Although there are many micro-hydro units in China, most of them are connected to the feeder of 10kV or below. So when a shortage of power occurs, and the feeder has to be pulled out, micro-hydro units connected to the feeder will fail to supply power, resulting in lack of electricity and a large amount of surplus water. This paper proposes to solve this problem by establishing micro-grids containing micro-hydropower, feeder loads, and a certain amount of storage facilities. In this paper, a long-term optimal operation model of micro-grid with micro-hydropower and energy storage devices is established. The type and capacity of storage facilities in the micro-grid are discussed. Finally the numerical example based on local feeder load and micro hydro units' data shows validity and effectiveness of the proposed model.