nils-herrmann/clean_scirepeval huggingface dataset:
Searching for Time Optimal Periodic Orbits Near Irregularly Shaped Asteroids by Using an Indirect Method

Periodic orbits over irregularly shaped asteroids and comets are fundamental for understanding vicinal dynamical behaviors and space explorations. In this paper, a new method is proposed to obtain natural periodic orbits, which is based on the optimal control framework with respect to a general form of the irregular gravitational field. Natural elongated asteroids are taken as representatives, whose potentials are approximated by the rotating mass dipole with appropriate parameters. An indirect method is used to transform the optimal control model into a two-point boundary value problem, which can be solved by using a shooting method. Numerical simulations are performed to validate the effectiveness of the proposed method regarding the asteroid 951 Gaspra. Three types of periodic orbits are identified, including the Lyapunov orbit around the collinear equilibrium point, the equatorial retrograde orbit, and the inclined orbit. The connection between the latter two types of orbits is also briefly discussed via numerical continuation.
Demonstrate high Roff/Ron ratio and forming-free RRAM for rFPGA application based on switching layer engineering

The application of reconfigurable architectures in field programmable gate array (FPGA) has been addressed great concern by academic and industrial. However, fabricating a nonvolatile device for circuit routing configuration in connection block is still a great challenge. In this paper, a forming-free RRAM technology with high resistance R<inf>ON</inf>/R<inf>OFF</inf> ratio (∼10<sup>6</sup>) is developed for reconfigurable circuits connecting. The demonstrated RRAM with switching layer engineered Pd/Al<inf>2</inf>O<inf>3</inf>/HfO<inf>2</inf>/NiO<inf>x</inf>/Ni structure shows excellent performance, such as low variation, good retention (>10 years@85°C) and large drive current (>1mA). In addition, corresponding switching mechanism and how to improve RRAM's resistance R<inf>ON</inf>/R<inf>OFF</inf> ratio by material engineering and device structure optimization are also discussed.
Sentiment and sentimental agent identification based on sentimental sentence dictionary

This paper presents a method of sentiment and sentimental agent identification based on Chinese sentimental sentence dictionary. Our method can identify eight kinds of sentiment (including joy, sorrow, love, disgust, surprise, anxiety, anger and hate), and the main sentimental agent. Sentimental sentence dictionary is composed by some sentimental sentence patterns. And the sentiment of a candidate sentence is identified by calculating the consistency with the sentimental sentence patterns. Especially, using the sentimental sentence dictionary, we can get rid of the sentences without sentiment, but have sentimental words. According to sentiment words and expressions, the sentences which are not appeared in the sentimental sentence dictionary also can be identified. The experiments show that we can get precision of 84% for sentiment identification, and precision of 69% for sentimental agent identification.
Specific boosting method for scientific discovery

In this paper we present a specific boosting method for decision trees (SBMDT) in the field of scientific discovery. Ensemble classification methods have been shown to lead to reduce classification error on unseen cases. However, a high accuracy ratio of prediction sometimes requires complicated predictors, and makes it hard to understand the simple laws affecting the values of the attribute of interest in the field of scientific discovery. We first propose using attribute weights and attribute weights information gain in SBMDT that make boosting method useful for decision trees in the field of science discovery. The result of experiments on microporous aluminophosphates database about inorganic chemistry is exciting. A new template diethanolamine was found to synthesize aluminophosphates with 12-membrane ring channel structure for the first time in the world.
A design method of MMC-HVDC physical simulation system

For the growing power rating and voltage level, modular multilevel converter (MMC) is a feasible solution in the application of voltage sourced converter based high voltage direct current(VSC-HVDC) transmission. However, due to its numerous independently controlled sub-modules(SMs), it is very difficult to represent the complete internal transient process of MMC or accomplish the hardware-in-loop (HIL) test of valve based controller (VBC) using digital simulation platform. Therefore, this paper deduces the similarity criterions and the parameter calculation method for the design of low-voltage physical simulation system. Taking the Xiamen ± 3 20kV/1000MW MMC-HVDC project in China as a simulation prototype, a physical simulation system is built, based on which the type test of VBC and system operation analysis are completed. Experiment results verify the correctness of the proposed calculation method and the designed system.
Model predictive control algorithm of flexible load in consideration of both electricity cost and comfort

This paper proposes a novel model predictive control algorithm based on intelligent terminal, which considers both the economic benefit and the customer comfort. In this algorithm, novel models for air-conditioner and water-heater are created, which obviously simplify the algorithm. In the new models, the multivariable thermodynamic process is separated into several independent univariate sub-processes, which can be solved easily. In addition, the algorithm obtains the model parameters by parametric regression from history data. By this way, the optimal results are independent of the outdoor temperature and other confounding factors. Thus, the complexity of the algorithm is significantly reduced. More, considering both electricity cost and customer satisfaction, a dual-objective optimization algorithm is implemented to get the control strategy, which is solved by particle swarm optimization (PSO) and linear programming. At last, a simulation result on MATLAB shows the economic benefits and load shifting effect.
Automatic Time Gain Compensation in Ultrasound Imaging System

Many automatic time gain compensations are proposed, but most of them depart from the assumption that ultrasound signals are homogenous attenuated across examined tissues, which is often violated. In real ultrasound system, the large attenuation variation between different types of tissues confused the attenuation compensation. In this paper, considering the frequency shift effect, we propose the quadratic least square fitting to estimate the attenuation profile. Further, as for the large attenuation variations in image, especially around the anechoic regions, we proposed a new algorithm by adding two power functions to control the gain range and reduce the affluence of overwhelming gain value caused by noise and edges around anechoic regions. Test results of phantoms and ultrasound images show the new algorithm could effectively adapt to the large attenuation variation and provide a desired uniform image.
A Method for Characteristic Extraction of Ultrasound Doppler Signal with Peak-valley Relationship under Heavy Noise

This paper proposes a real-time algorithm estimating clinical useful parameters from the maximum frequency curve of ultrasound Doppler spectrum. Traditional methods always apply some pre-calculations to the frequency waveform, for instance, filtering or scaling transformation, which have limitations on real-time features detection and waveform display. In this paper, we propose and maintain a process unit as a section of the waveform with the help of its phase information and the idea of the changeable scaling in the wavelet, to determine the Doppler waveform parameters in real time. From a set of in vivo Doppler waveforms, our proposed algorithm can pick up right parameters even in very noisy environment
Collaborative Filtering for Recommender Systems

Collaborative filtering (CF) predicts user preferences in item selection based on the known user ratings of items. As one of the most common approach to recommender systems, CF has been proved to be effective for solving the information overload problem. CF can be divided into two main branches: memory-based and model-based. Most of the present researches improve the accuracy of Memory-based algorithms only by improving the similarity measures. But few researches focused on the prediction score models which we believe are more important than the similarity measures. The most well-known algorithm to model-based is the matrix factorization. Compared to the memory-based algorithms, matrix factorization algorithm generally has higher accuracy. However, the matrix factorization may fall into local optimum in the learning process which leads to inadequate learning. CF approaches are usually designed to provide products to potential customers. Therefore the accuracy of the methods is crucial. In this paper, we propose various solutions to make a quality recommendation. First, we proposed a new prediction score model for the Memory-based method. Second, we proposed a differential model that considers the adjustment process after the training process in the existing matrix factorization methods. Third, a novel hybrid collaborative filtering is outlined to avoid or compensate for the shortcomings of matrix factorization and neighbor-based methods. In the end, we performed the experiments on Movie Lens datasets and the results confirmed the effectiveness of our methods.
A weighted infrared face recognition method based on block-DCT

A novel infrared face recognition method is proposed in this paper. In this method, to get the good performance of infrared face recognition from the biological feature, thermal images are converted into blood perfusion domain by blood perfusion model. Then, the blood perfusion images are partitioned into different sub-blocks. Each sub-block is represented by the coefficients extracted from block-DCT domain. Finally, according to the discriminative power, different sub-blocks can be assigned to different weights to get holistic features. Experiments demonstrate the method proposed outperforms other methods based on PCA.
Reliability analysis of phased-mission systems using Bayesian networks

The paper presents a Bayesian networks (BN) based method to analyze the reliability of phased-mission systems (PMS). The method includes three steps. Firstly, each phase of PMS is represented by a BN framework, named phase-BN. Then, in order to express the dependences across phases, all the phase-BN are combined by (1) connecting the root nodes that represent the same component but belong to different phases, and (2) connecting the leaf nodes of the phase-BN with a new node that represents the whole PMS mission. The new constructed BN is named PMS-BN. Lastly, the reliability analysis is performed by a discrete-time BN modeling acting on PMS-BN. Two examples are used to expatiate on the proposed approach. The PMS-BN based method provides a new way to analyze PMS, especially those with dynamic phases. Further, based on PMS-BN, fault diagnoses and sensitivity analysis can be performed easily.
Semi-implicit scheme based nonlinear diffusion method in ultrasound speckle reduction

Because of the presence of speckle noise in ultrasound image, the image resolution is not so desirable. Recently, a class of anisotropic diffusion based methods has been developed, which can reduce the speckle noise, and at the same time, preserve and enhance the edge/borders. speckle reducing anisotropic diffusion (SRAD) is an important representative of these methods. It is an explicit scheme based method with very slow processing speed due to the severe restriction in time step size (TSS), and it is sensitive to noise due to its small window size to calculate ratio of mean and variance. Using semi-implicit scheme (e.g., additive operator splitting AOS) method to discretize SRAD (called ASRAD), we could use large TSS for speed-up. However, artifacts brought by ASRAD degrade the image. In this paper, we aim to solve above problems. Our method could be generalized to solve other explicit scheme based nonlinear diffusion speckle reduction methods.
An integrated approach for detecting approximate duplicate records

detecting approximate duplicate records in database is a key problem related to data quality. Given two lists of records, the duplicate detection problem consists of determining all pairs that are similar to each other, where the overall similarity between two records is defined based on domain- specific similarities over individual attributes constituting the record. In this paper, we present a synthetic approach for recognizing clusters of approximate duplicate records of multi-language data. The key ideas are: (1) an efficient algorithm for pre-processing multi-language data consists of Chinese words segmentation and Chinese named entity recognition; (2) an efficient pair-wise comparison method based on domain- specific similarities, especially, the string kernel method; (3) using a priority queue of duplicate clusters and representative records strategy to respond adaptively to the data scale.
Slepian-Wolf Coding of Binary Finite Memory Source Using Burrows-Wheeler Transform

In this paper, an asymmetric Slepian-Wolf coding(SWC) scheme for binary finite memory source (FMS) is proposed. The a priori information about the source is extracted from the side information at the decoder by Burrows-Wheeler Transform (BWT). Such information is then utilized for the LDPC code based decoding. Benefiting from the universality of BWT, our coding scheme can be applied to any FMS. Experimental results show that our scheme performs significantly better than the scheme which does not utilize the a priori information for decoding.
An Efficient H.264 Rate Control Scheme with Accurate \theta Estimation

An efficient rate control scheme for H.264 encoding has been proposed, where p domain source modeling, which was first used in block-based DCT coding system such as H.263, MPEG-2 and MPEG-4, is introduced. For accurate rate control, parameter thetas, the slope of the linear function of bit rate R vs. p, should be estimated in advance for each frame. Least-Mean-Square (LMS) algorithm is adopted for the estimation of thetas, which is further refined by a new factor thetas-ratio for each frame. Simulation results for standard test sequences show that, compared with JVT-H017, the new algorithm achieves better coding performance, while the output bit rates are more accurate.
Analyses of climate change and response of alpine glacier-river runoff in Hailuogou basin, Mount Gongga, China, by using δ2H and δ18O

The climate changes and the associated Hailuogou glacier-river runoff were discussed by analysis of the existing available meteorological and hydrologic data in Hailuogou basin. To better assess the effect of climate change on the stream flow of this river, stable isotope composition was measured on different types of water samples, including meteoric water, stream water, ice-snow melt water and ground water in 2008–2009. The results of this work indicate that: (i) as the annual average temperature in Hailuogou basin rose by 0.5 °C in recent 20-years, the mean runoff increased by 2.1% annually. Analyses of meteorological and hydrologic data suggest that changes of the glacier river runoff have responded to climatic fluctuations; (ii) analysis of the measured isotopic data demonstrate that precipitation provides the main part of seasonal variations of runoff of the study river, the effect of change in temperature suggests a linear increase in ice-snow meltwater and total streamflow. (iii) ice-snow meltwater is the main source of this alpine glacier river. Using a δ18O based hydrologic model, we estimated that the annual contribution of ice-snow meltwater over the total stream flow varied from 81.9% to 85.57% in its upper reach. Quantitative evaluation of the relationship between climate fluctuation and the river runoff is difficult because of the limited available long-term meteorological and hydrologic data in the alpine area in the periphery of the Qinghai-Tibetan Plateau.
Research on probability distribution of container liners’ arrival

The vesselspsila arriving law is generally considered to obey Poisson distribution, and inter-arrival time is used to be considered to accord with negative exponential distribution, which fit general cargo transport mode well. However, it will induce significant error if we apply this law into vesselspsila arrival in container transport mode. Itpsilas because that general cargo transport is constitutionally different from container liner transport in shipping organization and management. The former is a kind of unorganized random behavior in shipping system, while the latter is a kind of organized and scheduled behavior. It can be proved that interfered by the interactions of unpredictable factors, such as subjective pointing of line schedule and the weather etc, arriving law of container vessels fluctuates between random distribution and fixed-length distribution. Based on statistical analysis on shipspsila inter-arrival time at certain container terminal in China, we discovered that its probability distribution obeys second-order Erlang distribution. Our further studies demonstrate that order of Erlang distribution will increase along with the promotion of container vesselspsila density and their punctuality. Theoretically, the order is to approximate infinite taking on fixed-length distribution with interference.
Current situation analysis and development strategies for distribution automation of guangdong grid

The technology of distribution automation is vital for the future of smart distribution. As for the appropriate development and implementation of distribution automation, not only it should adapt to the distribution network characteristics, but also depends on the relative technologies of smart gird, such as smart terminal units, advanced communication and energy management. In this paper, based on the actual situation of distribution automation in Guangdong grid, an advanced strategy of distribution automation development is proposed targeting nowadays unbalanced regional development and different development levels. The strategy mainly divides the distribution automation into 4 parts including master station, automation terminal, feeder automation and communication network, and standardize for each part respectively. Through the permutation and combination, the appropriate development pattern for delaminating and districting operation could be retrieved, theoretically provides proofs for the reasonable development planning in the future distribution automation.
The CFD-PBM coupling calculation of salt-out flow in the centrifugal pump

In order to further understand the salt-out two-phase flow in the centrifugal pump and to consider the actual dynamic behaviors, such as particle aggregation and breakage, the population balance model (PBM) coupled with CFD is loaded on the basis of traditional Euler model to calculate the salt-out flow in the centrifugal pump with different blade outlet angles. The influence of blade outlet angle on the internal flow field is analyzed. The calculation result shows that: in the impeller passage, solid particles tend to move towards blade suction surface, leading to that particle outlet angle is less than the blade outlet angle, so to reduce the blade outlet angle can reduce the particle collision with the blade pressure surface and improve the impeller life. By comparing the pressure distribution and solid particle volume concentration distribution in different impellers, it is concluded that: solid particles gather most in the inlet, and quantity in the pressure surface is less than the suction surface. Particles are lesser in the inlet, which is obvious in the pressure surface. When the blade outlet angle is bigger, more particles gather in the suction surface, causing more collision in the blade outlet. When blade outlet angle increases, the impeller outlet pressure will be increased.
Method of Improved Scatterer Size Estimation without Attenuation Known a Priori

Backscattered signals contain frequency-dependent information about tissue microstructures, but when using these signals to construct conventional ultrasound B-mode images, the frequency-dependent information will not be utilized. Scatterer size is an important parameter to differentiate diseased tissue from normal. To get the more correct estimation about scatterer size, the more correct assumption about attenuation must be learned. In most cases, the attenuation estimation must be known a priori, and then the scatterer size is computed by a minimal routine. In most case, the attenuation is known a priori. Any errors in the attenuation using the method will produce errors in the resulting scatterer size estimated. Though there are some methods to improve the scatterer size estimation, but most of them also need the attenuation which is known a priori. A new method is proposed in this paper by an analysis of the in vivo backscattered power spectrum, to improve scatterer size estimation. Here the attenuation and the scatterer size were estimated simultaneously, so the attenuation shouldn't be known a priori. The attenuation and scatterer size can be found by searching the attenuation and scatterer values while operating the minimal routine in the new method. Simulations were done to test the new method, the transducer had 8 MHz center frequency, 4 f-number and 5 cm focal length, the attenuation was 0.5 dB/cm/MHz. The result showed that the scatter size (error less than 20%) estimation could be found with large window length (6-12mm), and a better estimation could be found if concerning both total and local attenuation.
A novel approach to concepts via knowledge graph theory and AFS theory

In this paper we combine two approaches. One is the theory of knowledge graphs in which concepts are represented by graphs. The other is the axiomatic fuzzy set theory (AFS). In both theories concepts are studied and concepts can be set in correspondence. This enables to use algebraic results in the context of knowledge graph theory. As different interpretations lead to different knowledge graphs, the notion of fuzzy concept should be describable in terms of sets of graphs. This leads to a natural introduction of membership values for elements of graphs. We apply AFS theory to calculate fuzzy decision trees for the knowledge graph of the concepts “democracy”. Then the fuzzy rules derived from the obtained fuzzy decision tree were used to determine the most relevant elements of the concept. The results demonstrate that the proposed method can provide effective and human understandable fuzzy rules for the recognition of the important elements of the word graph of a concept.
Estimation and correction of ultrasonic wavefront distortion using pulse-echo data

Pulse-echo measurements from random scattering and from a point target were used to quantify the transmitter beam size effects, the isoplanatic patch size, and to evaluate the performance of different compensation techniques. Measurements were made using unperturbed transmit beams produced by a single-element transmitter with a diameter of 1/2", 1", or 2", each focused at 3". Scattered signals were received in a two-dimensional aperture after propagation through a specimen of abdominal wall, and b-scan images were formed with no compensation, with time-shift compensation in the receiving aperture, and with backpropagation followed by time-shift compensation. The investigation indicates that a tightly focused transmitter beam is necessary to create a scattered wavefront satisfactory for time-shift estimation, the isoplanatic patch is about twice longer in the range direction than in the azimuthal direction, and backpropagation followed by time-shift compensation provides better compensation of distortion than time-shift compensation alone.