nils-herrmann/clean_scirepeval huggingface dataset:
Autonomous fault-tolerant time-varying attitude tracking control of uncertain flexible satellite

The problem of time-varying attitude tracking for a flexible satellite which is nonlinear in dynamics with moment-of-inertia uncertainty, flexible appendage dynamics, space disturbances and even the actuator faults is investigated in this paper. The quaternion description is adopted to formulate the kinematical representation, and the uncertain flexible satellite dynamics is described. Moreover, an adaptive updating law is proposed to estimate the upper boundary of the total uncertainty, which can guarantee the state variable of the closed-loop system to track the desired position. Furthermore, the fault detection and isolation (FDI) mechanism is not required to on-line diagnose the actuator faults in the proposed controller. Finally, numerical results are presented to verify the effectiveness of the proposed autonomous controller compared with two nominal sliding mode control schemes.
Research on ramp optimization metering strategy in urban expressway

Taking Beijing urban expressway as research object, the control strategy with the measure of ramp metering is sought to deal with traffic congestion. The ramp metering methods, i.e. the local ramp optimization metering and the congestion dissipation control on urban expressway are put forward. The control strategy is not only to alleviate traffic congestion situation on mainline of urban expressway, but also to avoid the block of the surface streets owing to the serious queue. The examples denote that the methods are feasible and can offer reference for the theory of ramp control, and can be applied to engineering practices.
Damage localization for offshore platform by neural networks

In this paper, a damage localization approach for offshore platform by artificial neural networks is proposed. The members of offshore platform structure are classified and separated into several layers. The decision system for the kind and layer of damaged members is established using the back-propagation networks. When inputting the change rate of normalized frequency into the decision system, the kind and layer of damaged members are determined. The decision system for the location of damaged members is established using the probabilistic neural networks. When inputting the normalized damage-signal index into the decision system, the location of damaged member is determined. Numerical simulations demonstrate that the approach can localize the damage of offshore platform with good robustness.
An Investigation and Analysis of the Satisfaction Degree of Administrative Staff in the Service Industry--On the Basis of Human Resources Research of the Headquarters of New Century Tourism Group

Employee satisfaction is a key indicator of measuring the success of human resource management in modern hotels. Adopting SPSS15.0, this article has a descriptive analysis of the issues of the employees' being satisfied or not, the most satisfying factors, the most dissatisfying factors, the impact of gender on satisfaction, the impact of work experience on the turnover intention and so on. After this, the article also gives some suggestions on how to improve the employees' satisfaction.
Notice of RetractionStudy of Entropy Weight Theory in EPC Owner Risk Decision

With international practice and needs of business own development, it's has become more and more common to carry out EPC project in enterprises' contract. Comparing with the traditional patterns of contract, the owners will not involve in the specific process of project in EPC model, so the decision risk of the owners is increased. Through analyzing of EPC contract model, to the ambiguity and uncertainty of risk assessment information, entropy weight theory is introduced into risk decision of EPC project. In the absence of index weight given by experts, multiple EPC schemes are evaluated and ranked sequence with risk level closeness degree effectively by the entropy weight model, and the optimum scheme is obtained definitely.
Development of the 40 V hybrid super-capacitor unit

A newly hybrid super-capacitor for the power source of electromagnetic (EM) launch system is developed. By the optimization of combined structure, the hybrid super-capacitor unit can be charged and discharged at the working voltage of 40 V. Compared with other super-capacitors, the working voltage gets raising actually. According to the electricity performance test, it shows that the capacitor has the high energy density and the ability of quick charging and discharging. And the analysis of electrical impedance spectroscopy (EIS) shows that it has good characteristics of impedance and frequency. The analysis method of equivalent circuit for the capacitor with impedance characteristic is meaningful for the comprehension of the process and determination of the production processes.
TSP problem based on dynamic environment

Many real world optimization problems are related with time and some of them can be modeled by the Dynamic TSP(DTSP). A DTSP is harder than a general TSP, which is a NP-hard problem, because the city number of the DTSP is time varying. We have first given a mathematical model for DTSP. Then we have discussed the GT algorithm which is a algorithm solve static TSP problem. Based on GT algorithm, we have proposed an evolutionary algorithm, which can solve DTSP problem, given its details, analyzed its character and have given a graph of CHN144+1 problem. In the end, we have given the research area in future.
Performance analysis of Norm Constrained Capon Beamforming

The performance of the Standard Capon Beamforming (SCB) will become worse than Conventional Beamformer (CBF) in the case of small-sample errors, the steering vector errors and so on. Recently, many robust approaches to overcome the above problems are studied, such as Linearly Constrained Minimum Variance (LCMV), Diagonal Loading (DL) and so on. Among them, Norm Constraint Capon Beamforming (NCCB) is most popular and has a clear physical meaning. In this paper, we transform the original formulation of NCCB into Second Order Cone Programming (SOCP) form, and give a complete performance analysis of NCCB approach. Simulation results show that NCCB is more robust against the steering vector errors, and has a better power estimation of the Signal of Interest (SOI) and output Signal Interference Noise Ratio (SINR).
An optimal condition based maintenance strategy using inverse-Gaussian degradation process

Condition based maintenance (CBM) is a practical and effective way to guarantee the product availability. Recent years the optimization strategy of CBM is widely studied by researchers. For product with measurable degradation performance, degradation modeling plays an important role in CBM. Inverse Gaussian process has many superb properties in dealing with covariates and random effect. In this paper, a new CBM optimization model is developed basing on the nonlinear inverse Gaussian degradation model. With the constraint of cost, the optimal CBM strategy is obtained by maximizing availability of product. Specifically, we consider imperfect preventive maintenance and proposed a way to describe its influence. Finally, the proposed model is demonstrated by a numerical example.
Cloud rainfall estimation with multi-attribute typhoon data and edge extraction

Quantitative estimation of the typhoon rainfall is one of the focus in the typhoon research field. In this paper, in order to improve estimation accuracy in the scope and rainfall, the authors use the cloud classify rainfall forecast model based on edge extraction with multi-attribute typhoon data such as infrared data, water vapor data and temperature of brightness blackbody(TBB) data etc. First of all, we use the edge extraction to get the outline of the rainfall, then use the cloud classify rainfall estimation model to obtain the predicted rainfall in the inner area. At last, authors take "Phoenix" typhoon, in 2008, as an example to improve the estimation accuracy in rainfall distribution as well as the cloud rainfall by using the method of cloud rainfall estimation with multi-attribute typhoon data and edge extraction.
Study on automatic creating method of public transportation dispatching form based on BP neural network

Public transportation intelligent dispatching system (PTIDS) is the most important subsystem in advanced public transportation system (APTS). In order to realize intelligent dispatching, the dispatcher must determine the headway and dispatching form for a certain transit vehicle. As we know, the headway is relatively stable for some certain time period since the passenger flow changes according to regularity. However, the dispatching form must be determined according to the real time passenger flow. This paper proposes that the principle of automatic creating of a transit vehicle's dispatching form for the first time. Then, a new automatic creating method based on BP (backpropagation) neural network is introduced, which can make sure that the dispatching form can be created in a short time. The case study in Line 306 of Changchun, a metropolitan city of China, has proved that the method proposed In this paper is application.
A study on the framework of urban traffic control system

Based on the complexity of the Urban Traffic Control (UTC) system, this paper presents a new framework of hybrid control system for UTC in which any optimal control strategy can be adopted. By the interface D-S and interface C-S namely cooperation model, the hybrid system of UTC is divided into three layers including digital control loop, discrete event module, and Group Decision-making Support System (GDSS). Using GDSS consisted of central agent and intersection agents, real time control and coordinate control with the characteristics of self-decision, cooperation, and intelligence are realized.
Large dynamic range high resolution digital delay generator based on FPGA

A novel digital delay generator (DDG) based on FPGA was designed with 4.4ms range and 65ps resolution. The time-to-digital conversion (TDC) utilizing dual tapped delay lines was implemented in the FPGA to accurately measure the time interval between the rising edge of the FPGA global clock and the input trigger pulse. And the time interval was compensated in the following circuits by a AD9501 chip. The counter in the FPGA delays coarse time and another AD9501 chip delays fine time. To increase the accuracy, self-test block was developed in the FPGA to avoid the deviation induced from bad INL and DNL of AD9501 chips. Finally, the jitter of the system tested by TEK (TDS7404) oscilloscope was 400ps.
cDNA, Genomic Sequence Cloning and Sequences Analysis of the fau Gene from the Giant Panda (Ailuropoda melanoleuca)

fau gene is the cellular homolog of the fox sequence in the Finkel-Biskis-Reilly murine sarcoma virus (FBR-MuSV). It encodes a fusion protein consisting of the ubiquitin-like protein FUBI at the N-terminus and ribosomal protein S30 at the C-terminus. Here we have cloned the cDNA and the genomic sequence of fau gene from the giant panda (Ailuropoda melanoleuca) using RT-PCR technology and Touchdown-PCR, respectively. The length of of cDNA fragment cloned contains an open reading frame of 414 bp encoding 133 amino acids which estimated molecular weight of the fau is 14.4277 kDa with an isoelectric point (pI) of 10.17 and the length of the genomic sequence is 1143 bp, containing four exons and three introns. Alignment analysis revealed that the nucleotide sequence and the deduced protein sequence are highly conserved to other five species studied, including Mus musculus, Rattus norvegicus, Bos taurus, Sus scrofa, and Homo sapiens. The homologies for nucleotide sequences of giant panda fau to that of these species are 89.80%, 89.55%, 91.29%, 92.79%, and 91.79%, respectively, and the homologies for amino acid sequences are 96.99%, 97.74%, 96.99%, 98.50%, and 96.99%, respectively. Topology prediction showed that there are one cAMP- and cGMP-dependent protein kinase phosphorylation site, two Protein kinase C phosphorylation sites, four Casein kinase II phosphorylation sites, and one Amidation site in the fau protein of the giant panda.
Reconstruction of pitch for whisper-to-speech conversion of Chinese

Whispers are a common and necessary secondary vocal communications mechanism for natural human-to-human dialogue. They are also the primary communications mechanism for many suffering from aphonia, such as laryngectomees. For typical speakers, whispering is a predominantly contextual activity, prompted by either the sensitive nature of information being conveyed or in response to environmental considerations. Given the importance of whispers, especially for tonal languages like Chinese, and the fact that many communications systems assume vocalised speech, much work has been directed towards the conversion of whispers into natural sounding speech. Since pitch information is largely absent in whispers, it is this key f0 information which needs to be supplied during the regeneration process, and which is the focus of much research. GMM-based reconstruction techniques have proven effective at whisper reconstruction, and some recent work has proposed the use of artificial pitch derived from formant harmonics as an alternative. This paper describes a new formulation of the formant-harmonic f0 method, and compares this directly against a novel GMM-based f0 estimator, as well as known correct pitch excitation for parallel utterances.
The research of calculation model of QoS for service composition based on 0-1 programming

Web Service is the best realization of SOA, which plays an important role in service computation. With the continuous development of service composition and increasing diversification of business demands, there are more than one solution can be proposed to provide the similar service. Under such circumstances, how to measure the quality of solution quantitatively becomes the research focus of service composition field. In this paper, we analyze the key factors of composite service from domain and runtime angle and classify the elements into three types by using HTN planning, besides this, an calculation model for value of composite service quality is constructed based on the 0-1 programming and implement an instance of service composition with this methodology.
Double-Density Dual-Tree Wavelet Transform Based Texture Classification

Texture classification plays an important role in image analysis. The wavelet transform is a very efficient multiscale analysis method that has been successfully applied to describe the texture. The double-density dual-tree wavelet transform can simultaneously possess the properties of the double-density discrete wavelet transform (DWT) and the dual-tree DWT. In this paper, the texture feature based on the double-density dual-tree wavelet transform are derived from the subbands and tested in two benchmark texture databases. The experimental results suggest the potential capacity of the double-density dual-tree wavelet transform in texture analysis.
Automatic video annotation based on co-adaptation and label correction

As there is a large gap between high-level semantics and low-level features, it is difficult to obtain high-accuracy video semantic annotation through automatic methods. In this paper, we propose a novel automatic video annotation method, which greatly improves the annotation performance by learning from unlabeled video data, as well as exploring temporal consistency of video sequences. To effectively learn from unlabeled data, a scheme called co-adaptation is proposed to progressively refine two pre-trained complementary classifiers, and then a minimum entropy based method is applied to sufficiently explore the video temporal consistency, which further improves the annotation accuracy. Experiments show that the proposed automatic video annotation method performs superior than both general learning-based and co-training-based methods
Side-scan sonar image segmentation based on gray level co-occurrence matrices and unsupervised extreme learning machine

Side-scan sonar image segmentation is an important part in marine surveys, especially when we need to get the topographic features of the seabed. Actually, due to the complexity of the geomorphological characteristics in the seabed, we can't obtain any prior knowledge. Therefore we need an unsupervised system to segment side-scan sonar images automatically. In this paper, a novel segmentation system for side-scan sonar image based on Gray Level Co-occurrence Matrices (GLCM) and Unsupervised Extreme Learning Machine (US-ELM) is proposed. Experimental results demonstrate that the proposed method can get good segmentation.
A new architecture of grid security system construction

Due to the complexity of grid computing, many new security problems have appeared in grid, and so the traditional network security practices can not meet the security demand of grid. As a result, the study of security problems in grid is important, complicated and arduous. In this paper, we propose a new approach to construct grid security systems, and analyze both the disadvantages of current existing grid security systems. Our grid security system framework is positioned as an alternative to the security framework of open grid service architecture (OGSA). Based on our analysis, we conclude that a security system in grid should be composed of two parts: security rule definitions and security rule implementation. We also discuss the advantages of our new security system architecture
Research on Optimal Operation Policy for Water Resource System During Drought

According to basic connotation of the indexes for expressing reservoir water-supply risk during drought: reliability, resilience and vulnerability of reservoir water supply, and mathematical programming principles, the multi-objective mixed integer programming model was set up, which was able to consider the priority of urban water-supply and agricultural water-supply, and operation rule of reservoir-group system for successive drought periods. The model-solving procedures and lattice work-search method was proposed based on characteristics of the model structure. The concept of technique is clear to understand and convenient to write computer program, therefore, the large-scale and complicated mixed programming model become easy to solve. The application example verifies rationality of the model technique and it has the practical value for multi-reservoir water-supply system operation policy analysis during drought.
Tests on Symmetry and Continuity between BSIM4 and BSIM5

This paper presents the test results on the CMOS model symmetry and continuity characteristics between BSIM4 and BSIM5 from University of California at Berkeley. It is shown that the industry standard model BSIM4 has a series of the shortcomings of the continuity and symmetry, such as the charge, high-order current derivatives, and the trans-capacitances while new generation BSIM MOSFET compact model, BSIM5, demonstrates all necessary continuity and symmetry characteristics, which are very important for analog and RF circuit design
A Novel Calibration System for a Space Manipulator

It is important to calibrate the position and attitude precision for space manipulator in laboratory environment. The construction goal of the calibration system for a space manipulator is to simulate the microgravity environment in space, to counterbalance the impact of gravity on manipulator and to realize the test of 3D position precision, attitude and trajectory precision in the terrestrial environment. This paper introduces a novel calibration system. Based on the definitions of five kinds of reference frames, this paper illustrates the relationships among the reference frames and the coordinate transformation method between the relevant reference frames. Furthermore, the paper defines four calibration items. Finally, a calibration case study is presented in detail, which verifies the availability of mechanical interface, air-bearing test-bed and air-bearing feet
i-vector representation based on bottleneck features for language identification

An i-vector representation based on bottleneck (BN) features is presented for language identification (LID). In the proposed system, the BN features are extracted from a deep neural network, which can effectively mine the contextual information embedded in speech frames. The i-vector representation of each utterance is then obtained by applying a total variability approach on the BN features. The resulting performance of LID has been significantly improved with the proposed BN feature based i-vector representation. Compared with the stateof- the-art techniques, the equal error rate is relatively reduced by about 40% on the National Institute of Standards and Technology (NIST) 2009 evaluation sets.
Supercontinuum generation in tapered fibers

Here we demonstrate a supercontiuum spectrum generated in a tapered fiber pumped by a Ti sapphire laser with 130fs pulse width at 800nm centre wavelength. The tapered fiber with the diameter of 1.25 μm and the length of 16cm was made by using a tapered machine. The supercontiuum range is from 500nm to 900nm. We simulated the supercontinuum with the nonlinear Schrodinger Equation and discussed the affecting factors. In some conditions, the experimental results are agreed very well with the theoretical analyses.
Threat Analysis Based on Group Decision-making

Threat analysis is an important field to promote enterprises' core competitive abilities and to keep continuous development. It is not a crisis before some sudden changes happen to bring enterprises loss and it is only a threat. Threat is a potential crisis in some degree, however not all threats will grow up to become crises. Before loss can be seen, they look just like common and necessary parts in an organization and in normal operating procedure. This paper takes these parts as threats indicated in many managing books. Here, group decision-making strategy is used to deal with threats based on the characteristics of the decision-making procedure. Advantages of group decision-making strategy are also concluded. To make a decision, AHP is considered to get a meaningful and credible result. To exhibit the role of managers, system cluster is used to classify experts involved in decision-making procedure. An event of a key engineer's dismissing is analyzed to illustrate the decision-making procedure. It proves the efficiency of this idea and AHP method too
How unsupervised learning affects character tagging based Chinese Word Segmentation: A quantitative investigation

Integrating global information of unsupervised segmentation into Conditional Random Fields (CRF) learning has been proved effective to enhance the performance of the character tagging based Chinese Word Segmentation. By comparing CRF models with and without unsupervised learning enhancement, we investigate how unsupervised learning affects the performance. Especially, two kinds of segmented words, in-vocabulary and out-of-vocabulary words, are separately analyzed case by case to see what part of those words are affected by unsupervised learning. In addition, the cost of the additional features derived from unsupervised segmentation are also taken into account and evaluated.
Image fusion quality metrics by directional projection

Image fusion has been over-studied recently. Nevertheless, few works aim to how to evaluate the performance of image fusion algorithms. In this paper, we extend the work in image quality evaluation  to a novel metric for objective evaluation of image fusion. Firstly the input images and the result image are converted into local sensitive intensity (LSI) by Radon transform. Then we use the sensitive intensity to measure how many information have been transferred from each source into the fused result by the difference of LSI. Finally all the LSI pairs are incorporated into the expression according to Weber-Fechner law. Experimental results demonstrate that our proposed metric is compliant with subjective evaluations and outperforms other recently developed objective metrics of image fusion.