nils-herrmann/clean_scirepeval huggingface dataset:
Algorithmic inferencing of aesthetics and emotion in natural images: An exposition

Initial studies have shown that automatic inference of high-level image quality or aesthetics is very challenging. The ability to do so, however, can prove beneficial in many applications. In this paper, we define the aesthetics gap and discuss key aspects of the problem of aesthetics and emotion inference in natural images. We introduce precise, relevant questions to be answered, the effect that the target audience has on the problem specification, broad technical solution approaches, and assessment criteria. We then report on our effort to build real-world datasets that provide viable approaches to test and compare algorithms for these problems, presenting statistical analysis of and insights into them.
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach

Automatic linguistic indexing of pictures is an important but highly challenging problem for researchers in computer vision and content-based image retrieval. In this paper, we introduce a statistical modeling approach to this problem. Categorized images are used to train a dictionary of hundreds of statistical models each representing a concept. Images of any given concept are regarded as instances of a stochastic process that characterizes the concept. To measure the extent of association between an image and the textual description of a concept, the likelihood of the occurrence of the image based on the characterizing stochastic process is computed. A high likelihood indicates a strong association. In our experimental implementation, we focus on a particular group of stochastic processes, that is, the two-dimensional multiresolution hidden Markov models (2D MHMMs). We implemented and tested our ALIP (Automatic Linguistic Indexing of Pictures) system on a photographic image database of 600 different concepts, each with about 40 training images. The system is evaluated quantitatively using more than 4,600 images outside the training database and compared with a random annotation scheme. Experiments have demonstrated the good accuracy of the system and its high potential in linguistic indexing of photographic images.
A compact dual-mode bandpass filter for GPS, Compass (Beidou) and GLONASS

A dual-mode bandpass filter with compact size is proposed by using a new type of rotational symmetric dual-mode rectangular resonator. Due to the feed structure, two transmission zeros are generated near the lower and upper passbands to improve the skirt-selectivity of the filter. By adjusting the mutual coupling between the loading meander-line loop resonators, one transmission pole and neighboring transmission zero can be controlled. Two capacitors are added between each meander-line loop resonator and feedline to improve in-band performance. Based on this topology, a compact filter for GPS/Compass (BeiDou)/GLONASS applications has been designed, analyzed and fabricated. Measured results verified the validity of this design methodology. This proposed filter exhibits the small size of 0.11 λg×0.10 λg.
Development of grid-connected inverters for micro-grid

As an important part of the smart grid, the micro-grid contains distributed energy sources, loads, and control devices. An energy storage system and a doubly fed induction generator based wind turbine associated with an ultracapacitor are the main micro grid sources in this paper. Both the energy storage system and the dual-fed induction generator systems are connected to the micro-grid via grid-connected inverters and an LCL filter. Decoupled q-d control strategies for different operating conditions of the systems are demonstrated in this paper. Matlab/Simulink is employed to investigate the performance of these energy sources and inverters.
Detection of Impact Induced Stress Waves Using a Novel Optical Fiber Fabry-Perot Sensor

a novel optical fiber Fabry-Perot(F-P) sensor for the detection of impact induced stress wave is reported. The multi-beam interference model of low finesse F-P cavity is established considering the spectrum of incident beam obeys a Gaussian distribution. In addition, by analyzing the action mechanism between the optical fiber F-P sensor and tress waves generated by the impact, the sensing model of the optical fiber F-P sensor is established. Ball-on-ball impacts show that the developed F-P sensor can successfully detect the stress wave signals induced by the impact, and the sensitivity of sensor has the directivity.
A fast automatic interpretation of 3D potential-field image

We present a filter to detect the edge of potential-field image. The filter is computed in the space domain using a simple nine-point convolution filter basing on the ratio the total horizontal gradient and the total gradient. The filter is to apply edge-detection as a useful tool for potential field interpretation on synthetic data. Finally, the proposed filter is applied to a field example from the Finger Lakes region of State of New York, where the results are in good agreement with previous results and present new structural features.
Learning from Noisy Labels with Distillation

The ability of learning from noisy labels is very useful in many visual recognition tasks, as a vast amount of data with noisy labels are relatively easy to obtain. Traditionally, label noise has been treated as statistical outliers, and techniques such as importance re-weighting and bootstrapping have been proposed to alleviate the problem. According to our observation, the real-world noisy labels exhibit multimode characteristics as the true labels, rather than behaving like independent random outliers. In this work, we propose a unified distillation framework to use “side” information, including a small clean dataset and label relations in knowledge graph, to “hedge the risk” of learning from noisy labels. Unlike the traditional approaches evaluated based on simulated label noises, we propose a suite of new benchmark datasets, in Sports, Species and Artifacts domains, to evaluate the task of learning from noisy labels in the practical setting. The empirical study demonstrates the effectiveness of our proposed method in all the domains.
On the BER performance of pulse-position-modulation UWB radio in multipath channels

The impact of multipath propagation on ultra wide band (UWB) radio, which is carrier free, is quite different from that on conventional radio. This paper presents a theoretical analysis of the bit error rate (BER) performance of binary pulse-position-modulation (PPM) UWB radio in multipath channels. The BER formula is derived. Particular attention is paid to the effect of the propagation time-delay on the BER performance. It is also noted that, for the PPM scheme, the multipath propagation time-delay may lead to unbalanced BERs over "0"-"1" in some particular multipath channels.
Prediction of compression bound and optimization of compression architecture for linear decompression-based schemes

On-chip linear decompression-based schemes have been widely adopted by industrial circuits nowadays to effectively reduce the ever increasing test data volume and test time. Though they can easily achieve relatively high compression ratio, there is a bound of effective compression ratio for these compression schemes. Prior work tried to address this problem by trying different compression architectures to identify this compression bound. However, they can not predict this compression bound efficiently. In this paper, we will first analyze the correlation between the effective compression ratio and the compression architecture, thus to predict that compression bound efficiently. In addition, this paper will also propose how to design the compression architecture for target effective compression ratio with one-pass calculation, which was usually done by a time-consuming try-and-error process as well in the current DFT flow. Experimental results show the accuracy of the prediction and the effectiveness of the compression architecture design.
Model contest and portfolio performance: Black-Litterman versus factor models

The aim of this article is to discuss and compare four models: single index model, Fama French three-factor model, Carhart four-factor model and the Black-Litterman model in the context of twenty largest capitalization stocks listed on NASDAQ and NYSE. It was found that among the three factor models, the Carhart four-factor model produced the best fitness of data with the highest adjusted R2. When testing the portfolio performance built on the four models across the testing periods, the Black-Litterman model was superior to all other three models. The portfolio constructed based on the Black-Litterman framework generated relatively higher return with relatively lower risk than other models with a Sharpe ratio of 0.4437. Several recommendations can be made to improve the performance of portfolios. Firstly, Black-Litterman Model is favored when constructing portfolio rather than traditional optimization approach. Secondly, view return and view covariance matrix should be generated based on thorough equity research rather than merely quantitative method such as data mining. Finally, parameters involved in the Black-Litterman framework should be generated with care; in particular, τ and c can be combined into one parameter.
High-Energy Single-Frequency Millisecond 1336.630-nm Nd:LGGG Amplifier (April 2017)

We demonstrate a high-energy, single-frequency, and millisecond (ms) 1336.630-nm amplifier with high beam quality and narrow-linewidth simultaneously based on the Nd<sup>3+</sup>:(Lu<sub>x</sub>Gd<sub>1-x</sub>)<sub>3</sub>Ga <sub>5</sub>O<sub>12</sub> (Nd:LGGG) disordered crystal for the first time. The amplifier system consists of a polarized single-frequency 1336.630-nm LD oscillator, two-stage Raman fiber preamplifier, and four-stage Nd:LGGG main amplifier. The seed laser pulse energy is amplified up to a record high pulse energy of 2.05 J at a repetition rate of 5 Hz and a pulse duration of 1 ms with linewidth as narrower as 0.5 pm. The beam quality factor is <inline-formula><tex-math notation="LaTeX">${\rm{M}}^{2}\,= \,1.46$</tex-math></inline-formula>. The wavelength of the single-frequency amplifier can be tuned from 1336.600 to 1336.660 nm. All results indicate that the Nd:LGGG is high performance 1.3-μm laser amplification medium, especially for generating the specific wavelength at 1336.630 nm. Moreover, such laser source with the specific wavelength at 1336.630 nm is promising for the development of a high accuracy <sup>27</sup>Al<sup>+</sup> ion optical clock.
Emergency fault diagnosis for wind turbine nacelle

Many sets of wind turbines of the wind farm in Shan Xi province run above the rated wind speed, especially in the condition of wind speed 17m/s or above, wind turbine nacelle occurs vibration in the vertical direction of transmission chain which is characterized emergency, intermittent, accidental, and distinctive. Moreover, vibration cycle is not obvious and vibration strength is large. Severe vibration does harm to wind turbine that then will be able to lead wind turbine halt. According to this phenomenon, a method of emergency fault diagnosis for wind turbine nacelle based on empirical mode decomposition (EMD) is presented in this paper to discriminate a variety of factors carefully that have led to excessive vibration. In particular, the results are shown in this paper that strong tower shadow effect may cause excessive vibration of wind turbine nacelle, and then gives rise to shut down. In the meantime, curve theory analysis of the blade's aerodynamic characteristics is deduced in this paper. It demonstrates that the proposed method EMD works well in the face of fault diagnosis for wind turbine nacelle with a better overall performance.
Millimeter-Wave UWB Signal Generation Via Frequency Up-Conversion Using Fiber Optical Parametric Amplifier

We propose and demonstrate a novel approach to generate millimeter-wave (MMW) ultra-wideband (UWB) signal via frequency up-conversion using fiber optical parametric amplifier (OPA). The baseband UWB signal is amplified by a high-repetition-rate pulsed pump and generates many sidebands separated by the modulation frequency of the pump. By selecting two or three of the sidebands and beating in the photodetector, we can obtain an up-converted signal in the MMW band. In our experiment, we have successfully demonstrated UWB signal up-conversion from 3 to ~ 19 GHz with 18-dB optical gain using fiber OPA.
Diffusion bias-compensated LMS estimation for multitask adaptive networks

In this paper, we study the problem of the least mean-square algorithm based on bias compensation in multitask diffusion adaptive networks. Nodes in networks are divided into different clusters and the nodes in the same cluster cooperatively estimate a common parameter. When regressors are corrupted by additive white noise, the estimate results of the traditional multitask diffusion least mean-square (Multi-LMS) algorithm are biased. In order to obtain the unbiased estimation, we propose two multitask diffusion bias-compensated least mean-square (Multi-BCLMS) algorithms by achieving the real-time estimation of the input noise variance, which can be denoted by Multi-BCLMS-A and Multi-BCLMS-B respectively. Simulation results show that the two algorithms perform better than the Multi-LMS algorithm in estimation accuracy and mean-square error. Furthermore, the second algorithm (Multi-BCLMS-B) is simpler to implement and the transient is faster than the first one (Multi-BCLMS-A).
A Stochastic Approach to 3-D Image Modeling

Statistical modeling methods have been successfully used to segment, classify, and annotate digital images, over the years. In this paper, we present a 3-D hidden Markov model (HMM) for volume image modeling. The 3-D HMM is applied to volume image segmentation and tested using synthetic images with ground truth. Potential applications to 3-D biomedical image analysis are also discussed
Quantitative /sup 131/I SPECT with triple energy window Compton scatter correction

In this work accuracy of quantitative /sup 131/I SPECT with triple energy window (TEW) scatter correction is evaluated by phantom measurements. The TEW method is a pixel by pixel correction where the scatter fraction in the photopeak window is estimated by linear interpolation between two adjacent narrow sub-windows. Quantification procedure includes marker based X-ray CT-SPECT image fusion to determine object boundaries and to generate attenuation maps. TEW scatter correction significantly reduces the effect of background activity on reconstructed counts within an object, but it still exists due to the finite position resolution of the system. Therefore, a background dependent calibration factor was used for quantification. Quantitative accuracy with TEW correction was 5% and 14% for a tumor and lung respectively of a physical phantom with non-uniform activity and non-uniform scattering medium.
Edge detection based on decision-level information fusion and its application in hybrid image filtering

A new edge detection method, based on decision-level information fusion, is proposed to classify image pixels into edge and non-edge categories. Traditional edge detection algorithms make the detection decision under a single criterion, which may perform inefficiently with a change of noise model. We use fusion entropy as a criterion to integrate decisions from different classifiers in order to improve the edge detection accuracy. The proposed decision fusion based edge detection method is applied to image filtering and leads to a weighted hybrid-filtering algorithm. Simulation results show that the new edge detection method has better performance than the single criterion edge detection methods.
Influences of Calcination Temperature on Densification and Magnetic Properties of Bi-Modified NiCuZn Ferrites

The influences of calcination temperature on the densification, microstructures, and magnetic properties of low-temperature-fired Bi-modified NiCuZn ferrites have been investigated in order to adapt the development of low-temperature cofired ferrites technology and produce high-frequency devices with a multilayer process. It is found that with increasing calcination temperature, some Bi3+ ions enter into the spinel lattice gradually, and consequently improve the microstructural uniformity and densification. Thus, the quality factor increases observably while the real permeability decreases a little. Optimized magnetic properties and linear sintering shrinkage can be obtained for Bi-modified NiCuZn ferrites calcined at proper temperature due to uniform microstructures with small grain size, and higher sintering density.
Intelligent simulation system for Guangzhou-Shenzhen railway operation

By analyzing the state transfer of the Guangzhou-Shenzhen railway operation system and using an expert system technology method, an intelligent simulation model for this complex hybrid system is presented. With the help of expert system shell tool G2, this intelligent simulation system is set up in a Windows NT environment. It provides an experiment tool for the simulation research of Guangzhou-Shenzhen railway operation and transport organization, and can be easily applied to other railway lines and other rail transportation systems.
OFDM preamble design for synchronization under narrowband interference

In this paper, an OFDM-based preamble is proposed for improving timing and frequency synchronization in the power line channel with narrowband interference (NBI) as well as transmitting several bits of transmission parameter signaling (TPS). In the time domain, an additional scrambling operation is applied to the cyclic extension of an OFDM training symbol to reduce the impact of NBI. Compared to the conventional Schmidl's and Minn's methods, the proposed preamble could provide even sharper correlation peak and achieve better timing detection in both AWGN and power line multipath channels under NBI, with a moderate complexity increase because more correlation and multiplication operations are required. Furthermore, the proposed preamble could also convey several bits of TPS via the variable distance of two training sequences allocated in the frequency domain. Better synchronization results can be achieved through analyses and simulations with the proposed method.
Robust recovery of wideband block-sparse spectrum based on MAP and MMSE estimator

Indirect spectrum sensing mainly concerns the measurement and analysis of primary wideband analog signal. This paper proposes two robust algorithms based on maximum a-posteriori probability (MAP) and minimum mean-squared error (MMSE) estimators to recover wideband block-sparse spectrum and then detect the spectrum holes in compressive spectrum sensing (CSS). In each iteration of the referred Block-sparse Orthogonal Matching Pursuit based on iterative MAP (BOMP-IMAP) algorithm, one index of block is firstly identified to expand the estimated support. And then, wideband block-sparse spectrum can be recovered through approximating the MAP estimator. Finally, the residual is updated and put into next iteration. In order to approximate the MMSE estimator, the Random BOMP-IMAP (RandBOMP-IMAP) algorithm utilizes a randomized block identification of BOMP-IMAP algorithm to generate multiple solutions, which is followed by the fusion of them to obtain the final approximation. Numerical simulation results concerning probability of detection and detection time under certain noise level or measurement number validate the superiority of the proposed algorithms.
A framework of APSK constellation labeling design for satellite transmission

In this paper, the framework of amplitude phase shift keying (APSK) constellation labeling design for satellite transmission is proposed. It consists of two steps, the constellation design and the joint phase-labeling optimization. Both iterative and non-iterative demapping scenarios are considered in the design framework. The proposed APSK constellation labeling exhibits a low peak-to-average power ratio and achieves a considerable performance gain compared with its counterpart approved by the consultative committee for space data systems, as verified by both the mutual information analysis and bit error rate simulation.
Microstrip balanced filter and balun filter incorporating edge couplings and connected couplings based on artificial transmission lines

The balanced filter with quarter-wave resonators using both edge- and connected-coupling mechanisms is proposed in this study. Under differential-mode excitation, two types of coupled-resonator pairs constitute the odd-mode half-circuit filter. Among the two coupled pairs, the connected coupling is realized by artificial transmission line with compact size possessing lowpass response. As a result, the constructed balanced filter has relatively low insertion loss. Specifically, by appropriately terminating one of the ports of the balanced filter, a balun filter features wide differential-mode/common-mode stopbands, good passband CMRR, and simple structure.
Research on intrusion detection of SVM based on PSO

Intrusion detection plays more important role in network security today. This paper introduces a method, particle swarm optimization and support vector machine, to intrusion detection system, and presents a new design of ID Based on particle swarm optimization and support vector machine. This paper presents an optimal selection approach of the SVM parameters (regulation parameter C and the radial basis function width parameter sigma ) based on particle swarm optimization algorithm. The experiments show that the optimal parameter selection approach based on PSO is available and the research of intrusion detection based on particle swarm optimization and support vector machine is effective in reducing the number of alerts, false positive, false negative better.
On the relationship between BELS and IV methods

The bias eliminated least squares (BELS) method is one of consistent estimation methods for unknown parameters of transfer function in the presence of colored noise. In this paper, the BELS method is derived in a more general setting by introducing an auxiliary vector and a nonsingular matrix. With the help of matrix-partition technique and matrix analysis, the equivalence of BELS method and IV method under certain conditions is verified through theoretical analysis and simulation studies.
Complex-coupled wavelength-selectable dfb laser source for coarse WDM

A dual wavelength-selectable InGaAsP/InP distributed feedback (DFB) laser with a complex-coupled Bragg grating is presented. An n-doped reverse layer is buried periodically in the index-coupled Bragg grating, which causes a spatial modulation of the carrier concentration in the active region, and so induces the weak gain-coupled to the index-coupled grating. Two wavelengths of 1.51 um and 1.53 um are realized under different work conditions. The side mode suppression ratios (SMSRs) of both wavelengths reach 40 dB benefiting from the single-mode character of the complex-couple grating. This device can be used in coarse wavelength division multiplexer (CWDM) communication system as the light source because of its low-cost and convenience.