nils-herrmann/clean_scirepeval huggingface dataset:
Simulative Measurement on Conductivity and Permeability Distribution in Sensing Field of Electromagnetic Tomography

Electromagnetic tomography is one kind of electrical impendence tomography which develops faster in recent years. The relation map between Electromagnetic field and measuring electric potential provides adequate prior information and consequently is crucial to image reconstruction of Electromagnetic Tomography (EMT). Firstly the forward problem of EMT is studied in this paper and a new 2-D model of eight homogenous coils is set up in simulative software named COMSOL Multiphysics, finite element method (FEM) is practiced in the solution of forward problem. The simulation on characters of object position, conductivity, and permeability in sensing field is carried out and seriously analyzed. The relation between conductivity of materials and detective electric potential are discussed, revealing that material distribution is mainly presented in the real part of the electric potential. The investigation on object field of EMT is beneficial not only to future reconstruction work but also to optimum design of sensor system.
Multi-Direction Guidance Motion Tracking for Real-Time Ultrasound Strain Imaging

The axial- and the lateral- guidance motion tracking are efficient approaches for real-time strain imaging; however, they are suffering from error propagation. This paper introduces a novel multi-direction guidance (MDG) motion tracking algorithm which selects higher quality previous estimations from multi-directions as seed displacement of the next estimated location. Experiment results show that this presented algorithm can efficiently avoid error propagation and obtain much higher strain signal-to-noise ratio (SNRe) than that from the axial and lateral guidance.
Potential of Partially Superconducting Generators for Large Direct-Drive Wind Turbines

This paper aims at assessing the potential of partially superconducting generators for 10 MW direct-drive wind turbines by investigating their performance for a very wide range of excitation currents. Performance indicators such as shear stress and efficiency and other generator characteristics are compared for 12 different generator topologies. To be sufficiently attractive, superconducting generators must have significant advantages over permanent magnet direct-drive generators, which typically have shear stresses of the order of 53 kPa and efficiencies of 96%. Therefore, we investigate what excitation is required to obtain a doubled shear stress and an efficiency of 98%. To achieve this, the different topologies require a range of excitation from 200 to 550 kAt (ampere-turns) with a low armature current density of 2 A/mm<inline-formula><tex-math notation="LaTeX">$^2$</tex-math> </inline-formula>. The more iron that is used in the core of these topologies, the easier they achieve this performance. By examining the maximum magnetic flux density at the location of the superconducting field winding, feasible superconductors can be chosen according to their engineering current density capabilities. It is found that high- and low-temperature superconductors can meet the performance criteria for many of the topologies. MgB <inline-formula><tex-math notation="LaTeX">$_2$</tex-math></inline-formula> superconductors are feasible for the fully iron-cored topology with salient poles but need cooling down to 10 K.
Design of a novel high resolution holography concave grating spectroscopy for tongue coating analyzer

The tongue coating diagnosis is an important part in the traditional Chinese medicine (TCM). TCM usually uses the visual method to determine the severity of the disease, but this method mainly relies on the experience of doctor and will not avoid generating the error. In addition, the application of the method based on the digital image processing is restricted by the complicated algorithm, expensive cost and slow processing rate, etc. So, a novel tongue coating analyzer(TCA) based on the spectrum analysis is developed in this paper. And, the holography concave grating spectroscopy (HCGS) is the critical unit in the TCA, a high resolution custom-built HCGS for TCA based on the linear CCD and virtual instrument is designed. In the HCGS, the holography concave grating is used as the dispersion device instead of the plane grating, high resolution linear CCD with combined high-speed PCI data acquisition(DAQ) card are used to design the tongue coating(TC) spectrum acquisition, measurement and analysis system. In addition, the virtual instrument (VI) technology based on LabVIEW is used to design a virtual-HCGS for TCA software platform to control the TC spectrum acquisition and data analysis. Experimental results show that the spectral range of the HCGS for TCA can reach 300–1000nm, its wavelength resolution can reach 1nm, and it uses the back-split-light technology and 8-channel parallel analysis. Compared with other same types, this HCGS for TCA has many advantages, such as, more compact volume, simpler algorithm, higher accuracy, cheaper cost and fewer stray-light and higher imaging quality, etc. Therefore, the TCA based on HCGS will have the greatly potential values in the fields of the TCA for TCM.
Study of the Input RF noise of a THz superconductor-insulator-superconductor receiver

The receiver noise temperature of THz superconductor-insulator-superconductor (SIS) receivers is composed of several contributions, in which the input RF noise is usually not negligible. In this paper, we investigate the input RF noise (Trf) of a waveguide superconducting niobium nitride (NbN) SIS receiver operating at 0.5THz. In particular, the input RF noise is measured for two respective cases of a small beam aperture surrounded by an aluminum plate and a blackbody, which is located just in front of the 0.5THz NbN SIS receiver. Detailed measurement results will be presented.
Marking process analyze in plate marking machine

Based on coupling and low damp ratio of the marking process, this paper presents a new approach for modeling system by dividing the whole process into several periodic dynamic processes, in which the new methods decouple the pressure system and position servo system and raise the damp ratio of pressure system and lower the inner-influence of paint guns. A theoretic analyses and digital simulation about the system of marking process are made at different paint pressure and different servo speed using Matlab. The simulate results give a better group of system parameters for marking machine in BaoSteel, which has good actual performance and the methods for improving the marking characteristic are given.
Infrared face recognition based on radiative energy and sub-block DCT in wavelet domain

A novel infrared face recognition method is proposed in this paper. In this method, according to Stefan-Boltzmann's law, the raw thermal images are transformed to the radiative energy images, and they are decomposed using two scales' discrete wavelet transform. The components of low frequency sub-bands are partitioned into sub-blocks, then, they are transformed by DCT. Each face is represented by the coefficients extracted from the sub-blocks in DCT domain. Finally, according to the discriminative power, different sub-blocks in DCT domain can be assigned different weights. Experiments demonstrate the method proposed perform very well on recognition rates as compared to other methods.
Research on Battlefield Target Tracking in Wireless Sensor Networks

Due to uncertainties in target motion and limited sensing regions of sensors, collaborative target tracking in wireless sensor networks (WSNs) suffers from low tracking accuracy and lack of reliability when a target cannot be detected by a scheduled sensor. Generally, actuating multiple sensors can achieve better tracking performance but with high energy consumption. Tracking accuracy, reliability, and energy consumed are affected by the continuous sensing and transmission and coding method. In this paper, an optimized energy-efficient multisensor scheduling scheme is proposed for collaborative target tracking in WSNs. Simulation results show that, compared with existing scheduling mechanism the proposed scheme can achieve superior energy efficiency and tracking reliability while satisfying the tracking accuracy requirement. It is also robust to the uncertainty of the process noise.
Research on Cutting Temperature Using FEM Method while Machining Titanium Alloy TC4

Titanium alloys are widely used in aerospace industry due to their excellent mechanical properties. Because of their low thermal conductivity, high chemical activity, large friction coefficient and so on, such problems occur during the cutting process as high cutting temperature, large specific cutting force and serious tool wear, leading to low machining efficiency. The titanium alloys classified as difficult machining materials. The finite element method is the new method to study the machining process. The FEM method was used to simulate the cutting temperature while machining titanium alloy TC4. The temperature of cutting zone was measured by natural thermocouple and compared with the simulated results.
Semi-Supervised Community Detection Based on Distance Dynamics

Community detection methods that are based entirely on the topology of the network do not always achieve higher accuracy. This implies that the topological information alone is insufficient to accurately uncover the community structures of networks. Recently, some methods were proposed that used prior information to improve the performance and accuracy of community detection. However, most of these methods have high time consumption and are not suitable for dealing with large-scale networks. In this paper, we propose a fast semi-supervised community detection method called SemiAttractor that integrates the prior information into the distance dynamics model. Experimental results from both artificial and real-world networks show that the proposed method can effectively improve the accuracy of community detection and reduce the time costs.
A Mixture Distribution Based System in BitTorrent-Like P2P Networks

In this paper, we develop a novel file sharing system based on a mixture distribution model working in the BitTorrentlike p2p networks. The BitTorrent's built-in “tit-for-tat” unchoking mechanism delays the initial file sharing process for newly joined peers as well as brings the problem of free-riding that peers only download from others but never contribute to the network. We demonstrate a file sharing mechanism which allows peers to share pieces according to different mixture distributions. The mechanism utilizes the historical contributions of peers in the network to inspire cooperation among peers, Along with the mixture distribution model, the peers can only obtain the whole file by contributing to the network continuously which deters the free-riding behaviors. We theoretically prove that the peers take the truthful revealing as their dominant strategy and our system can speed up the initial process of file sharing. The experiments show that the proposed system performs well and has good scalability, as well as prevents the free-riding problem elegantly.
A knowledge-based automatic cephalometric analysis method

In this paper, a new analysis method based on the clinical knowledge is proposed and described for the automatic identification of cephalometric landmarks in digital cephalometric radiographs. A layer algorithm for image enhancement is also developed according to the gray-level distribution of the objects and the backgrounds. The experimental results have demonstrated that the proposed method performs better than the existing methods do in terms of their identifiability, accuracy, and dynamic range of images.
Experiment results of the unwanted influence of a probe fixture in transient electromagnetic field

Field probes are used extensively in electromagnetic compatibility tests to measure magnitudes of electromagnetic field strength. To achieve accurate measurements in a certain space position, a probe (mounting) fixture or probe stand is always utilized to hold the field probe. The unwanted influence of a probe fixture in transient electromagnetic field is investigated by experiment in this paper. Considering the measurement uncertainty of the current measuring system, the preliminary experiment results are in accordance with the assessment by finite integration technique which has been carried out.
Robot behavior selection using salient landmarks and object-based attention

This paper proposes a vision-based behavior selection system using biologically-inspired visual attention selection mechanisms, i.e., Bottom-Up attention and Top-Down attention. We adopt purely Bottom-Up attention selection to identify conspicuous regions for obtaining the salient landmarks, while propose an object-based Top-Down attention method using low dimensional task-relevant feature for searching target. The autonomous behavior selection system utilizes the salient landmarks and topological map for localization and navigation based on position prediction of matched landmark pairs. The proposed system is evaluated using several tasks in indoor and office environments for mobile robot. The applicability and the usefulness of the developed method are validated by the results obtained in this manner.
The application of backtracking search algorithm in hierarchical time-extended Petri net model for power system restoration

The research on power system restoration (PSR) is attracting more and more attention. During the process of system restoration, a wide variety of control actions have to be performed on time within the operating constraints. In this paper, the actions and their relationship are modeled as a controlled hierarchical time-extended Petri net (H-EPN). In order to find a feasible sequence of actions quickly and automatically and to minimize the loss of the blackout, an algorithm based on best-first search algorithm is proposed. In addition to the classical heuristic rules, the backtracking search algorithm is employed to optimize the final solution. The result indicates that common heuristic rules cannot always find the optimal solution. The backtracking search algorithm is necessary when various heuristic rules are in collision or even with constraints. Test results on practical system are given to demonstrate the validity of the algorithm.
Configuration strategy of energy storage system in active distribution network based on area forecasting error

Global optimization of active distribution network (ADN) divided network into several control areas, it need the output power of control areas keep constant. Because of the difference between forecasting value and real value of uncontrollable distribution generations as well as loads, the output power will be deviated from optimization value. In ADN energy storage system (ESS) stabilizes the power of feeder, however the power and capacity will be large for the method. The cost of ESS is high and the economy will be low in project. Therefore based on area forecasting error (AFE) index and feeder control error (FCE) index using consistent exchanged power control mode, the paper proposes the strategy to control output power as well as configure the power and capacity of ESS. The strategy can stabilize the fluctuation from forecasting error and reduce the power and capacity of ESS.
Study of the Thermal Effectiveness of Laminar Forced Convection of Nanofluids for Liquid Cooling Applications

Recent theoretical studies show that the convective thermal performance of nanofluids in cooling applications depends crucially on the effective thermophysical properties and, if the performance comparisons are made under different flow constraints, contradictory conclusions can be drawn regarding the effectiveness of the same nanofluid. In this paper, an experimental study is reported on the laminar forced convection of Al2O3-water and Al2O3-polyalphaolefin nanofluids through a circular minichannel. With the experimental data, the thermal effectiveness of nanofluids is evaluated using various forms of figure of merit under three typical flow constraints, such as: 1) constant flow rate; 2) constant Reynolds number; and 3) constant pumping power. Although nanofluids enhance convective heat transfer, the results show that their thermal effectiveness is adversely offset by the combined effects of increased viscosity and lower specific heat. In particular, if a convective liquid cooling system is constrained by the constant pumping power condition, there will be essentially no difference in the overall effectiveness between nanofluids and the base fluid when both the thermal and hydrodynamic performances are considered.
Gapped sampled spectrum doppler estimation

Duplex and triplex transmit patterns that involve gaps in the spectrum Doppler samples allow pulse repetition frequency increases and/or frame rate increases that cannot be flexibly achieved by conventional uniformly sampled transmit schemes. We make two claims in this paper. First, previously reported nonparametric gapped sampled spectrum estimators are technically feasible for handling the duplex and triplex transmit patterns found in common medical ultrasound applications. Second, such estimators that coherently average within an axial/temporal 2-D window have superior SNR compared with their incoherent counterparts. Moreover, this fact extends to previously reported fully sampled incoherent estimators, which can be improved by using their coherent version. We verify the methods by steady-state flow phantom experiments and in vivo examples of the left clavicular artery and the ascending aorta. For the flow phantom experiments, we use the three quantitative metrics of SNR, root mean square error, and zero frequency peak full-width at half-maximum to evaluate robustness and resolution. Results indicate that through proper parameters, periodically gapped estimators can produce results similar to their fully sampled counterparts. Fourier synthesis of the spectral estimates produces the fully sampled time-domain audio signal, and we give stereo audio examples for the clavicular artery.
Modular multilevel converters based variable speed wind turbines for grid faults

The modular multilevel converter (MMC) becomes attractive in the medium- and high-power application with high modularity. In this paper, the MMC is proposed to be applied in the variable speed wind turbine (VSWT) based on the full-scale back-to-back (BTB) power converter, where the generator-side converter is the three-level neutral-point-clamped (NPC) converter and the grid-side converter is the three-phase MMC. A control strategy is also presented for the MMC based VSWT for the second-order harmonic current elimination. The proposed MMC based VSWT and control not only mitigate the voltage ripple in the dc-link of the power converter to improve system performance, but also ensure the grid-side current balancing to increase the generated power of the wind turbine under the unbalanced grid fault, in comparison with the conventional VSWT based on BTB three-level NPC converters. The simulation studies of the proposed MMC based VSWT and control are conducted with a detailed PSCAD/EMTDC model, and the results show their effectiveness.
Electrical field adjustment for 500 kV optical metering unit

This work discusses our ongoing development of an AC 500 kV optical metering unit for use in a power system. The high voltage part of this unit is designed in a large size related to practical use. We review our test arrangement and present the experiment data demonstrating the results of different effects such as the vertical position and the height of the upper flange on the magnitude, sensitivity and linearity of the measurements of the optical voltage sensor. The results will be help of adjusting the electrical field in a designation of 500 kV optical metering unit for practical use.
Effect of Ti-Substitution on temperature dependence and magnetic disaccommodation of MnZn ferrites

Ti-Substituted MnZn ferrites were prepared by the conventional ceramic process. The effects of Ti-Substitution on temperature dependence and magnetic disaccommodation of MnZn ferrites were investigated. The experimental results show that the valley between peak I and Peak II of the μi-T curve initially becomes flatter with higher Titanium content. However, if increasing Titanium content continually, the valley becomes steep eventually. Furthermore, at the same temperature section of the valley, an initial decrease followed by a subsequent increase in the intensity of peak II of disaccommodation spectra is observed with the increase in Titanium content. The valley becomes flatter when the peak II of disaccommodation spectra goes down. MnZn ferrite with low peak II of disaccommodation spectra and high thermal stability is achieved when the substitution of Ti4+ is 0.1 mol%.
Hybrid control for micro-grid based on hybrid system theory

With the rapid increase in the rate of distributed generation ((DG) penetration depth, the issues of improving micro-grid transient become more significant. This paper investigates a two-level hierarchical hybrid control consists of continuous local controller for each DG unit at the first level coordinated by discrete supervisory control strategies at the secondary level for transients performance enhancement of micro-grid with various DG units following pre-planned or accidental switching events. The discrete supervisory control strategies are established based on information fusion technique by using wide-area measurements (WAM) in order to coordinate switching each DG subsystem into apposite operation mode following large disturbances. The continuous local controller for each DG unit is designed based on multiple Lyapunov stability theory incorporating linear matrix inequality (LMI) techniques in order to regulate the set point of each DG subsystem to reach the best performance and acceptable operation indexes. The effectiveness of the proposed hybrid control is demonstrated through simulation examples.
A feature-enhanced smoothing method for LDA model applied to text classification

Latent Dirichlet Allocation (LDA) is a generative model employing the symmetry Dirichlet distribution as prior of the topic-words' distributions to implement model smoothing. When LDA is applied to text classification, smoothing is essential to classification performance. In this paper, we propose a feature-enhanced smoothing method in the idea that words not appeared in the training corpus can help to improve the classification performance. The key point is fully considering the relativity between the new document and training corpus, and enhancing the document's class feature by regarding the words not appeared in the training corpus. Evaluations on 20newsgroups show feature-enhanced smoothing can significantly improve the performance in Bi-class text classification.
An attack decision method based on constraint condition correlation

The constraint condition affects the attack, but this impact is not considered by the existing decision algorithm. In order to make the decision algorithm more consistent with the actual situation, this paper gave an optimal attack decision method based on the correlation between vulnerability and constraint conditions. The method first establishes the attack logic graph according the attack template, and then uses the existing vulnerabilities and constraints to optimization the logic graph. The success probability and risk index of the atomic attack can be calculated based on the contribution rate of the constraint condition, and finally the optimal path can be obtained by using the maximum algorithm based on the utility of the attack path.
Approaches to Concept Lattice via AFS Theory

Formal concept analysis is a field of applied mathematics based on mathematical analysis of concept and conceptual hierarchy, AFS algebra was first proposed and studied by Xiaodong Liu 1998 (  Sets and Systems, vol. 95 ). In this paper, we explore the relationship between the AFS algebra and concept lattices, we get one structure from the other and some mathematical properties are indicated. We pave a way to explore concept lattice with AFS theory