nils-herrmann/clean_scirepeval huggingface dataset:
A Study on Pseudo Labeled Document Constructed for Document Re-ranking

Document re-ranking is a middle module in information retrieval system. It’s expected that more relevant documents with query appear in higher rankings, from which automatic query expansion can benefit, and it aims at improving the performance of the entire information retrieval. In this paper, we construct a pseudo labeled document based on pseudo-relevance feedback principle, and discuss about the relationship between performance of document re-ranking and the number of top documents in initial retrieval, the number of key terms from the top documents when constructing a pseudo labeled document. Experiment shows our approach of a pseudo labeled document constructed is greatly helpful to document re-ranking. It is the main contribution in the paper. Moreover, experiment shows the performance of document re-ranking is decreasing as the number of top documents increases; and increasing as the number of key terms from these documents increases.
High-Peak Power Passively Q-Switched 2-μm Laser With MoS2 Saturable Absorber

The passive Q-switching characteristics of a diode-pumped Tm,Ho:YAP laser at 2 μm based on a MoS2 saturable absorber (SA) is presented for the first time. Pulses as short as 435 ns under a repetition rate of about 55 kHz were generated at the incident pump power of 8.4 W, corresponding to the pulse peak power up to 11.3 W. This is, to the best of our knowledge, the highest pulse peak power, ever obtained from MoS2 based passively Q-switched 2-μm lasers. The experimental results sufficiently validated the feasibility of MoS2 as SA for solid-state 2-μm lasers.
Microspacecraft general cell research

This paper introduces our research that is to conceive and design a micro-platform of spacecraft that we call general cell (GC). The cell is an enabling technology of microspacecraft, and fully adapts to the rapidly developing demands of distributed spacecraft system (DSS). This paper gives detail depictions of characteristics of GC at system level, and a logically hierarchical architecture of DSS is proposed by discussing an improved leader election algorithm briefly. Up to now, a prototype used to demonstrate the cell is preliminarily designed, which comprises information processing unit (IPU) and sensors and actuators units (SAU). IPU, which integrates on-board computer (OBC), attitude control system (ACS), IO subsystem, and telemetry and telecommand subsystem together, is 200 mm times 28 mm times 138 mm, and its dry mass is 640 g. SAU is built with hardware-in-the-loop simulation by dSPACE real-time simulation platform. The two sets of GC have implemented autonomous attitude control and simple formation flying
An Exploring Study of Multi-Scale Complexity Texture Descriptors for Medical Image Retrieval

Since texture describes the local information of pixels' intensity variation, which can be regarded as the non-linear signals, non-linear signal analysis methods may be applied to texture analysis. Complexity analysis, as a popular non-linear signal analysis approach, is widely used for biological and clinical data analysis. In this paper, for exploring study purpose, a two-dimensional structure complexity measure called 2D-C0 was used for texture analysis and feature extraction. Two texture features, called multi-scale complexity texture descriptors, based on 2D-C0 and multi-resolution image analysis are presented for medical image retrieval. One is multi-resolution complexity histogram and the other is wavelet-based multi-scale complexity feature. In order to compute the multi-resolution complexity histogram, a two-dimensional complexity map with the same size as the original image that encodes complexity at every location in the image should be computed and quantized. Detail algorithm about it was discussed. Preliminary experiments showed that the proposed Db2 wavelet-based multi-scale complexity feature can achieve comparable results to Gabor feature.
Co-media: Creating active interactions for localized community with social media

We present Co-Media, a system designed to enhance offline and online social connections among individuals. Co-Media discovers localized communities from the social media (Sina Weibo), collects the media content, and detects popular topics among community members. The system exploits the common interests, so that community members could develop further discussions and strengthen their interactions. Through a-year running of Co-Media, the system is validated and our method worked effectively. We also demonstrate that most topics have strong relevance to the community beyond its localization property.
A two-stage stochastic programming model for resource allocation in project management

In a large-scale construction project, the project manager needs to allocate many resources, including numerous workers, various kinds of materials, and a lot of cash. Therefore how to allocate resources and to control cash flow ahead of time is particularly important. The general contract and material price fluctuation make the project manager to take great risk. In this paper, we establish a two-stage stochastic programming model which takes price fluctuation, working capital and other necessary constraints into account. We employ a sample-based heuristic to study how price fluctuation affects the progress schedule of the project. We also conduct sensitivity analysis on the important parameters, including working capital and labor cost.
An economic forecasting system based on recurrent neural networks

Many methods for economic forecasting have been developed, and most of them are based on statistical techniques. To increase the capability of describing economic processes and the accuracy of economic forecasting, some efforts for applying artificial neural networks to economic forecasting have been made, which are mostly based on multilayered feedforward network (MFN). Compared with MFN, recurrent neural networks have the ability to consider the historical deviation for further modification of the forecasting model. In this paper, a forecasting system based on recurrent neural networks is presented for economic forecasting and business cycle prediction. To speed up the training process, an improved backpropagation algorithm is embedded in the system. This system has some attractive properties and is now being used by the city government for supporting their policy making.
Maintaining the Diversity of Michigan-Style Approaches for Construction Fuzzy Classification System

Michigan-style genetic algorithms are usually used for learning fuzzy classification rules from numerical examples. In these approaches, each rule is encoded as a chromosome, and then builds up the classification rule set by these chromosomes. So the fitness value can only assign to a single rule rather than a whole rule set. This makes some chromosomes characterized by the minority of instances may be lost from the gene pool, and the approaches can only learn from small subset of the search space. In this paper, we first define the similarity level of one fuzzy rule from another rule using similarity measure. With the similarity level, we then balance the fitness values of different chromosomes by using fitness sharing method, and maintain the diversity of population. So the approaches can not only learn from the major instances, but also to learn from the minor instances. Furthermore, we cache the similarity value of different antecedent fuzzy sets for reducing the computing load when the similarity value are calculated. Finally, experimental results on benchmark classification problems demonstrate that our method is able to efficiently achieve accurate performance.
Factors effect on Hilbert fractal antenna performance

As effective solution on the design of miniature antennas, Hilbert fractal antenna has attracted much attention since it was advanced. Because of the characteristics of large fractal dimension, high miniature extent, good self-filled ability etc, the Hilbert curve is used in many new-designed antennas which are proposed in recent scientific papers. However, the current research on this antenna type home and abroad is mainly focused on how to improve the performance itself, but a certain extent ignores the other actual engineering-oriented factors, which will slower the antenna application course. So, this paper researches the impacts of feed point, medium backboard and ground plane on the Hilbert fractal antenna respectively, analysis the relation between them and the main antenna parameters, for instance working frequency, VSWR, bandwidth, and expatiate its general law. Also, this paper proposes design method of the Hilbert fractal antenna which is beneficial to its application.
Analysis and design of power hardware-in-the-loop testing for 400-Hz inverters

For the testing of 400-Hz inverters, a power hardware-in-the-loop (PHIL) platform is presented. However, the selections of power interface circuit parameters, such as filter of hardware interface (HI) and operating DC bus voltage of power amplifier (PA), remarkably affect the performance of the PHIL system. To solve this problem, an analytical and quantitative design method for power interface of PHIL is proposed. With the proposed design method, the relationships of the power interface circuit parameters and the PHIL system performances can be sufficiently taken into account and intuitively illustrated on a graph. Hence, the choices and optimizations of these parameters can be convenient and explicit. Moreover, a PHIL setup is built for testing a 400-Hz inverter to verify the effectiveness of the design method. Simulation and experimental results indicate that the setup achieves good performance.
0.1- $\mu \text{m}$  InAlN/GaN High Electron-Mobility Transistors for Power Amplifiers Operating at 71–76 and 81–86 GHz: Impact of Passivation and Gate Recess

We have developed 0.1-μm gate-length InAlN/GaN high electron-mobility transistors (HEMTs) for millimeterwave (MMW) power applications, particularly at 71-76 and 81-86 GHz bands. The impacts of depth and width of the gate recess groove on electrical performance have been analyzed and compared. Competing passivation technologies, atomic layer deposition (ALD) aluminum oxide (Al2O3) and plasma-enhanced chemical vapor deposition (PECVD) SiN, have also been assessed in terms of dc, pulsed-IV, and high-frequency characteristics. It has been found that while PECVD SiN-passivated HEMTs and the monolithic microwave integrated circuits slightly underperform their ALD Al2O3-passivated counterparts, their MMW power performance can be further boosted with the gate recess due to the improved aspect ratio and scaling characteristics. When biased at a drain voltage of 10 V, a first-pass two-stage power amplifier design based on recessed PECVD SiN-passivated 0.1-μm depletion-mode devices has demonstrated an output power of 1.63 W with a 15% power-added efficiency at 86 GHz.
Effect of Sand and Dust Storms on Microwave Propagation

The general formulas of the wave propagation constant through sand and dust storms are developed in this paper, which is based on the forward scattering amplitude of particle under the Rayleigh approximation. Expressions for attenuation and phase shift coefficients for a medium with sand and dust particles are derived in terms of visibility and frequency. Computations show that the predicted values from the given mathematical expressions are an excellent agreement with the values by Goldhirsh's formula. Expressions for the differential attenuation and differential phase shift are also derived for both vertical and horizontal polarizations. Obtained results of the attenuation of horizontal and vertical polarization wave are compared with those obtained by Wenyan 's formula and Ghobriel 's formula, respectively. It is found that the attenuation obtained by our proposed formula and Ghobrial 's formula show close agreement. The cross-polar discrimination is calculated and discussed.
Data driven control of underflow slurry concentration in deep cone thickener

Deep cone thickener control problem is a key point of Tailings paste fill (TSF). This paper presents a new method to extract inherent and practical parameters of the thickener, and determine control strategy based on thickening process data mining. Bypassing difficulty in deep cone thickener modeling, the proposed method could obtain practical control rules, also has good adaptability to different thickener structures and backfilling materials.
Design of a fault-tolerant voter for safety related analog inputs

This paper introduces a voting scheme for safety-related analog input module to arbitrate between the results of redundant channels in fault-tolerant system. The design approach is a distributed system using a sophisticated form of duplication. For each running process, there is a backup process running on a different CPU. The voter is responsible for checkpointing its state to duplex CPUs. In order to increase the dependability for safety-related controllers, the I/O modules use redundancy to reduce the risk associated with relying upon any single component operating flawlessly. The 1oo2D voting principle is commonly used in fault tolerant I/O modules to provide passive redundancy for masking runtime faults at hardware and software levels, respectively. A dual architecture (1oo2D) which provides high safety integrity to a rating of SIL 3 is presented. The outputs from two identical channels operating in parallel with the same inputs are supplied to a voting unit that arbitrates between them to produce an overall output. Based on the hardware logic model and FPGA technique, the study adopts the hardware voter which has much more advantage in the velocity and reliability. Finally, using modelsim simulations, we verify the effectiveness of the proposed voter design in preserving the hazard-free property of the response of an analog inputs module.
Medical Image Retrieval Based on Bidimensional Empirical Mode Decomposition

An approach of medical image decomposition and texture feature extraction based on the bidimensional empirical mode decomposition(BEMD), which can decompose the image into a set of functions denoted intrinsic mode functions (IMF) and a residue, was presented. Features extracted were the mean and standard deviation of the amplitude matrix, phase matrix and instantaneous frequency matrix of the IMFs and their Hilbert transformations. The extracted features were used for medical image retrieval. Moreover, according to the spatial relationship between local extrema points, a new boundary processing method based on clustering algorithm was proposed. In order to evaluate the proposed BEMD-based feature, we also presented a new multiscale fractal dimension feature. Preliminary comparison experimental results showed that the retrieval results of the BEMD-based feature were encouraged.
Improved hybrid ARQ scheme using adaptive modulation in cooperative relay networks

Hybrid ARQ has been shown to be an effective strategy to improve the performance and capacity in wireless networks. In this paper, we present novel and simple feedback hybrid ARQ schemes with adaptive modulation for cooperative wireless networks. The proposed scheme combines the retransmission mechanisms, incremental relay and adaptive modulation. For more tractable analysis, we derive closed-form expressions with the combined singal noise ratio at the destination for Rayleigh fading conditions. Verified by simulations, the scheme can obtain significant spectral plus by the strategy in low average SNR region and the performance can further improve when more relays are selected.
Diversity guided immune clonal quantum-behaved particle swarm optimization algorithm and the wavelet in the forecasting of foundation settlement

In dealing with the problem of the quantum-behaved particle swarm optimization algorithm (QPSO) easy falling into the local optima, we proposed the diversity guided immune clonal QPSO. In this algorithm the swarm was defined two states: attraction and expansion. During the optimization process the swarm transferred between the two states repeatedly reference to the swarm diversity. When in the attraction state if the diversity is less than the pre-established value, we will carry the immune clonal algorithm to do the local searching. And we used this algorithm with wavelet to forecast the foundation settlement, and also made a compare with standard quantum-behaved particle swarm optimization with wavelet. The experiment indicated that this improved method had a better ability of searching global and local optima and high forecasting precision.
Influence of element shape on performance of patch array as frequency selective surface

The authors compare the reflection performance of a circular patch array with that of a cross dipole array. It is shown that the circular patch array provides a wider reflection band with a relatively slowly varing curves. This can be also deduced from the fact that the reflection band width increases with the width of cross dipole. So cross dipole array is preferred in use as the subreflector of a Cassegrain antenna. Experimental transmission coefficients are compared with the calculated results of modal analysis.<<ETX>>
0.1- $\mu \text{m}$  Atomic Layer Deposition Al2O3 Passivated InAlN/GaN High Electron-Mobility Transistors for E-Band Power Amplifiers

High-performance 0.1-μm InAlN/GaN high electron-mobility transistors (HEMTs) have been successfully developed for power amplifiers operating at E-band (targeting 71-76 and 81-86-GHz bands). High maximum drain current of 1.75 A/mm and maximum extrinsic transconductance of 0.8 S/mm have been achieved for depletion-mode devices. Enhancement-mode HEMTs have also shown maximum drain current of 1.5 A/mm and maximum extrinsic transconductance of 1 S/mm. The selection of atomic layer deposition aluminum oxide (Al2O3) for device passivation enables a two-terminal breakdown voltage of ~25 V, excellent subthreshold characteristics as well as the pulsed-IV featuring little current collapse for both types of HEMTs. When biased at a drain voltage of 10 V, a first-pass two-stage power amplifier design based on 0.1-μm depletion-mode devices has demonstrated an output power of 1.43 W with 12.7% power-added efficiency at 86 GHz, a level of performance that has been attained previously only by state-of-the-art counterparts based on AlGaN/GaN HEMTs at a much higher drain bias and compression level.
Development of a Novel Settlement Monitoring System Using Fiber-Optic Liquid-Level Transducers With Automatic Temperature Compensation

A novel monitoring system using innovative fiber-optical liquid-level transducers is proposed for continuously monitoring the settlement of geotechnical infrastructures. Each fiber-optical liquid-level transducer has two fiber Bragg gratings (FBGs) embedded in an elongated cantilever beam such that the temperature effect of the FBGs is automatically compensated and the Bragg’s wavelength shift indicates a liquid-level change. The operating principles of an individual transducer and a settlement monitoring system consisting of multiple transducers are described in detail. Four fiber-optical liquid-level transducers were fabricated in the laboratory. The measurement range was ±75.61 mm, and the designed sensitivity was  $0.089~\mu \varepsilon $ /mm and was then updated through a calibration test. A settlement monitoring system was formed by connecting the four transducers with a water tank as an automatic level controller. A demonstration test of the system showed that its relative measurement error is within 4%, confirming the feasibility of the system for in situ applications.
Discovering ISO relations among synsets in a flat thesaurus automatically

The semantic resources are very important for natural language processing (NLP). Constructing the semantic resources by hand can lead to good results, but costs a lot. This paper proposes an effective method to automatically construct a hierarchically organized resource based on a traditional flat thesaurus. With the method, we could enrich immediate super-ordinate (ISO) relations among synsets in the existing resources and make good use of them in the field of NLP. We also develop an automatic method to evaluate the semantic relations detected in our experiment with a machine-readable dictionary.
Large-Area In-Situ Oxide, GaN Interlayer-Based Vertical Trench MOSFET (OG-FET)

We present a large-area <italic>in-situ</italic> oxide, GaN interlayer-based vertical trench MOSFET (OG-FET) with a metal organic chemical vapor deposition regrown 10-nm unintentional-doped-GaN interlayer as the channel and 50-nm <italic>in-situ</italic> Al<sub>2</sub>O<sub>3</sub> as the gate dielectric. The threshold voltage of the device on bulk GaN substrate was 1 V measured at <inline-formula> <tex-math notation="LaTeX">$\text{I}_\mathrm {on}/\text{I}_\mathrm {off}= 10^{7}$ </tex-math></inline-formula>. The OG-FET with an area scaled to 0.2 mm<sup>2</sup> demonstrated a breakdown voltage (<inline-formula> <tex-math notation="LaTeX">$\text{V}_\mathrm {BR}$ </tex-math></inline-formula>) of 320 V and an on-state resistance (<inline-formula> <tex-math notation="LaTeX">$\text{R}_\mathrm {on}$ </tex-math></inline-formula>) of <inline-formula> <tex-math notation="LaTeX">$3.8~\Omega $ </tex-math></inline-formula> (specific on-state resistance: <inline-formula> <tex-math notation="LaTeX">$\text{R}_\mathrm {on,sp}= 7.6\,\,\text{m}\Omega \,\,\cdot $ </tex-math></inline-formula> cm<sup>2</sup>). For the single unit cell OG-FET from the same sample, <inline-formula> <tex-math notation="LaTeX">$\text{V}_\mathrm {BR}$ </tex-math></inline-formula> was as high as 700 V (measured at <inline-formula> <tex-math notation="LaTeX">$\text{V}_\mathrm {GS}=-10$ </tex-math></inline-formula> V), corresponding to a breakdown electric field of 1.4 MV/cm and <inline-formula> <tex-math notation="LaTeX">$\text{R}_\mathrm {on,sp}$ </tex-math></inline-formula> of 0.98 <inline-formula> <tex-math notation="LaTeX">$\text{m}\Omega ~\cdot $ </tex-math></inline-formula> cm<sup>2</sup>. On our control sample, which was grown on sapphire substrate, a 1-A current was measured as well. These results show the potential of the OG-FET in power conversion applications.
Event Recognition in Videos by Learning from Heterogeneous Web Sources

In this work, we propose to leverage a large number of loosely labeled web videos (e.g., from YouTube) and web images (e.g., from Google/Bing image search) for visual event recognition in consumer videos without requiring any labeled consumer videos. We formulate this task as a new multi-domain adaptation problem with heterogeneous sources, in which the samples from different source domains can be represented by different types of features with different dimensions (e.g., the SIFT features from web images and space-time (ST) features from web videos) while the target domain samples have all types of features. To effectively cope with the heterogeneous sources where some source domains are more relevant to the target domain, we propose a new method called Multi-domain Adaptation with Heterogeneous Sources (MDA-HS) to learn an optimal target classifier, in which we simultaneously seek the optimal weights for different source domains with different types of features as well as infer the labels of unlabeled target domain data based on multiple types of features. We solve our optimization problem by using the cutting-plane algorithm based on group based multiple kernel learning. Comprehensive experiments on two datasets demonstrate the effectiveness of MDA-HS for event recognition in consumer videos.