nils-herrmann/clean_scirepeval huggingface dataset:
ExaGeoStat: A High Performance Unified Software for Geostatistics on Manycore Systems

We present <italic>ExaGeoStat</italic>, a high performance software for geospatial statistics in climate and environment modeling. In contrast to simulation based on partial differential equations derived from first-principles modeling, <italic>ExaGeoStat</italic> employs a statistical model based on the evaluation of the Gaussian log-likelihood function, which operates on a large dense covariance matrix. Generated by the parametrizable Matérn covariance function, the resulting matrix is symmetric and positive definite. The computational tasks involved during the evaluation of the Gaussian log-likelihood function become daunting as the number <inline-formula> <tex-math notation="LaTeX">$n$</tex-math><alternatives><inline-graphic xlink:href="abdulah-ieq1-2850749.gif"/> </alternatives></inline-formula> of geographical locations grows, as <inline-formula><tex-math notation="LaTeX"> ${\mathcal O}(n^2)$</tex-math><alternatives><inline-graphic xlink:href="abdulah-ieq2-2850749.gif"/></alternatives> </inline-formula> storage and <inline-formula><tex-math notation="LaTeX">${\mathcal O}(n^3)$</tex-math><alternatives> <inline-graphic xlink:href="abdulah-ieq3-2850749.gif"/></alternatives></inline-formula> operations are required. While many approximation methods have been devised from the side of statistical modeling to ameliorate these polynomial complexities, we are interested here in the complementary approach of evaluating the exact algebraic result by exploiting advances in solution algorithms and many-core computer architectures. Using state-of-the-art high performance dense linear algebra libraries associated with various leading edge parallel architectures (Intel KNLs, NVIDIA GPUs, and distributed-memory systems), <italic>ExaGeoStat</italic> raises the game for statistical applications from climate and environmental science. <italic>ExaGeoStat</italic> provides a reference evaluation of statistical parameters, with which to assess the validity of the various approaches based on approximation. The software takes a first step in the merger of large-scale data analytics and extreme computing for geospatial statistical applications, to be followed by additional complexity reducing improvements from the solver side that can be implemented under the same interface. Thus, a single uncompromised statistical model can ultimately be executed in a wide variety of emerging exascale environments.
A Coordination Control Strategy of Voltage-Source-Converter-Based MTDC for Offshore Wind Farms

Similar to other major electrical apparatuses, the reliability and stability of the dc network is becoming the most important issue when using the voltage-source-converter-based multiterminal dc (VSC-MTDC) system for offshore wind power integration. A coordinated control strategy of VSC-MTDC named master-auxiliary is proposed by combining the advantages of the voltage margin and voltage droop control. This strategy has three advantages. First, the master converter station with the constant dc voltage control can provide reference to the system dc voltage and is helpful for the stabilization of dc voltage. Second, the integrated control of the dc voltage in both master and auxiliary converter stations are helpful for providing adequate active power control (APC) and restraining large power variation. Third, the APC converter station can serve as a backup for the dc voltage control in abnormal conditions. In order to guarantee the reliability and stability of the system under various operating conditions, this paper introduces the priority of dc voltage control to the coordination control strategy. Moreover, a parameter optimizing method of controllers for this strategy is also proposed. Finally, the effectiveness of the master-auxiliary control is verified by simulations under normal and abnormal conditions.
Monte Carlo studies of hot electron transport and high field degradation

The problem of hot electron transport and energy loss at high electric fields in insulators is of considerable interest in the context of dielectric breakdown and hot carrier induced degradation. Hot electron transport is discussed in terms of electron-phonon scattering in polymeric dielectrics. Monte Carlo (MC) simulation provides the basis for study of hot electron transport in thin polyethylene (PE) films. Electron trajectories and spatial evolution of the electron energy distribution are presented. Possible molecular degradation mechanisms are discussed.
A Study on the Marine Ecological Carrying Capacity in Qingdao Based on Principle Component Analysis and Entropy

Ocean exploitation continues to be a major international growth area. In term of achieving marine sustainable development it is, therefore, the marine ecological carrying capacity influenced by many factors, need to be analyzed, addressed and monitored. The concept and influencing factors of marine ecological carrying capacity were discussed, and a method based on principle component analysis (PCA) and entropy was proposed to quantitatively reveal the change of marine ecological carrying capacity in this paper. Taking Qingdao City as an example, three principal components were extracted from 10 influencing factors by PCA, whose weights were assigned by entropy method. The results show that the marine ecological carrying capacity in Qingdao decreased firstly and then increased from 1998 to 2005, and the value is smallest in 2000. The amount of marine fishery resources, social economic development level and environmental pollution treatment are the three main supporting factors, the economic development and environmental pollution are the two main pressure of marine ecological carrying capacity, which have decreased year by year.
Visual-to-Tactile Interface to Detect Motions in Real-time for Persons with Visual Impairments

In this paper we propose an assistive technology (AT) device for individuals with visual impairments. This device would extract motion information from images acquired from a capture device and present the information through a tactile interface. The algorithm utilized provides information about the amount of motion present in the field of view and the centroid of the motion. Depending upon the number of stimulators and the location of the active stimulators, the direction and size of the objects could be determined. Currently, a simulation ofthe operation is performed using a computer to process images captured from an inexpensive camera. The primary goal of this design is to provide an AT device that is practical, cost-effective, and useful for individuals with visual impairments.
Based on EEMD-HHT Marginal Spectrum of Speech Emotion Recognition

Hilbert-Huang Transform is a time-frequency analysis method that apply to the nonlinear and non-stationary signal analysis, and has good adaptability. And The empirical mode decomposition(EMD) is the core part of HHT. Traditional EMD decomposition exists mode mixing phenomenon. To overcome this phenomenon, a new noise-assisted data analysis (NADA) method, the Ensemble EMD (EEMD), is proposed, which defines the true IMF components as the mean of an ensemble of trials and each consisting of the signal plus a white noise of finite amplitude. Finally the amplitude feature of emotional speech signal marginal spectrum is extracted using SVM classifier on emotional speech recognition.
FPGA-based PV systems fuzzy MPPT control algorithm

After discussing analysis of existing photovoltaic system maximum power point tracking (MPPT) control method, FPGA-based fuzzy MPPT control algorithm is proposed, this method is simple, reliable, and can automatically adjusts with the changes of external environment. Its fast optimization capability makes the system stable at the maximum power point. The MATLAB simulation of fuzzy control proves its fast response and steady-state performance achieve expectation. And fuzzy MPPT algorithm is designed with verilog language and downloaded to the chip. Experiments proved the effectiveness of this method of photovoltaic power generation system. It lays the foundation for SoC(System on a Chip) control.
Identification of strain hysteresis model for giant magnetostrictive actuators using a hybrid genetic algorithm

This paper shows a hysteresis model of giant magnetostrictive actuator (GMA), and proposes a hybrid genetic algorithm (HGA) to identify the parameters of the model. In the HGA, the trust region algorithm (TRA) is taken as a local search operator which parallels to the selection, crossover and mutation operators of a float-coded genetic algorithm (FCGA). The HGA is paid attention to both the advantages of the TRA and the genetic algorithm. It not only has a rather high convergence speed, but also can find the best parameter with a rather large probability. The simulation and experimental results verify the effectiveness of the model and the HGA
Study on hybrid genetic algorithm for multi-vehicle and multi-cargo loading problem

This paper studies multi-vehicle and multi-cargo loading problem under the limited loading capacity. According to the characteristics of model, hybrid heuristic algorithm is used to get the optimization solution. Firstly, adopt hybrid coding so as to make the problem more succinctly. On the basis of cubage-weight balance algorithm, construct initial solution to improve the feasibility. Secondly, adopt partial arithmetical crossover to maintain the diversity of species evolution, adopt the improved non-uniform mutation so as to enhance local search ability of chromosomes. Finally, the example can be shown that the above model and algorithm is effective and can provide for large-scale ideas to solve practical problems.
Verification experiments for high-precision Above Ground Marking system

Magnetic Flux Leakage Detector is typically used in pipeline applications involving the use of a device that passes through the pipeline to collect various data with respect to the condition of the pipeline, such as crack, corrosion, and deformation. As a crucial part of the Magnetic Flux Leakage Detector, Above Ground Marking system eliminates accumulated errors caused mechanical construction, turning or slippage of the miles round of magnetic flux leakage detector. In this paper, high-resolution clock is used as common time base of the master clock and above ground marker (AGM) to improve the accuracy of defects location. Experiments were performed to test (1) influence on inspection data when AGMs were put along the pipe with different angles; (2) specification and stability of above ground marker and master clock system. Results showed that location error will occur when AGM was angular placed along the pipe.
Robust Estimation of Structured Covariance Matrix for Heavy-Tailed Elliptical Distributions

This paper considers the problem of robustly estimating a structured covariance matrix with an elliptical underlying distribution with a known mean. In applications where the covariance matrix naturally possesses a certain structure, taking the prior structure information into account in the estimation procedure is beneficial to improving the estimation accuracy. We propose incorporating the prior structure information into Tyler's M-estimator and formulating the problem as minimizing the cost function of Tyler's estimator under the prior structural constraint. First, the estimation under a general convex structural constraint is introduced with an efficient algorithm for finding the estimator derived based on the majorization-minimization (MM) algorithm framework. Then, the algorithm is tailored to several special structures that enjoy a wide range of applications in signal processing related fields, namely, sum of rank-one matrices, Toeplitz, and banded Toeplitz structure. In addition, two types of non-convex structures, i.e., the Kronecker structure and the spiked covariance structure, are also discussed, where it is shown that simple algorithms can be derived under the guidelines of MM. The algorithms are guaranteed to converge to a stationary point of the problems. Furthermore, if the constraint set is geodesically convex, such as the Kronecker structure set, then the algorithm converges to a global minimum. Numerical results show that the proposed estimator achieves a smaller estimation error than the benchmark estimators at a lower computational cost.
WLAN Indoor GA-ANN Positioning Algorithm via Regularity Encoding Optimization

To begin with, for indoor location system, the necessity of research on genetic neural network and its math model are introduced. Then, by analyzing principle of genetic optimized artificial neural network, an indoor location math model of genetic neural network is established. As for various coding types, regularity is taken as the measurement to determine the best coding type for parameter optimization. By analyzing theory of splicing/decomposable coding, the advantages of regularity for such coding type are proved. Finally, through simulation comparisons, to select a regularity coding type for GA-ANN can improve positioning accuracy for indoor environment effectively.
A Strong Designated Verifier Signature Scheme with Secure Disavowability

Designated verifier signature (DVS) is a cryptographic primitive, which allows a signer to convince a designated verifier of the validity of a signed statement and prevents the verifier from convincing any third party about the signature. As a variant of DVS, strong DVS (SDVS), which exhibits perfect non-transferability, does not accommodate secure disavow ability (or non-repudiation). It makes a SDVS more like a message authentication code rather than a digital signature. In this situation, the signer has to bear the responsibility of some "forged" signatures produced by the designated verifier. Therefore, it's interesting to construct a strong DVS scheme with secure disavow ability. In this paper, we address this problem with a novel construction of a SDVS scheme with secure disavow ability. The new scheme utilizes a chameleon hash function and supports the signer to have a complete control of his signature. Our scheme achieves unforgeability, non-transferability and secure disavow ability. Comparisons show that the new scheme outperforms the existing one in terms of computational efficiency and signature length.
A frequency diversity scheme for OFDM systems based on space-time block coding

In this paper, a frequency diversity scheme for space-time block coded orthogonal frequency division multiplexing (STBC-OFDM) systems is proposed. The upper bound of pairwise error probability (PEP) of the proposed scheme is analyzed. The coding and diversity gain is derived. The result shows that the scheme can simultaneously obtain frequency diversity and space diversity gain. Extensive simulations show that the proposed scheme with two transmit antennas and a single receive antenna almost has the same performance as STBC-OFDM systems with four transmit antennas and a single receive antenna. Under the same symbol error rate (SER) performance, the number of transmit antenna is not required to be increased because of using frequency diversity.
Solving large scale global optimization using improved Particle Swarm Optimizer

As more and more real-world optimization problems become increasingly complex, algorithms with more capable optimizations are also increasing in demand. For solving large scale global optimization problems, this paper presents a variation on the traditional PSO algorithm, called the efficient population utilization strategy for particle swarm optimizer (EPUS-PSO). This is achieved by using variable particles in swarms to enhance the searching ability and drive particles more efficiently. Moreover, sharing principals are constructed to stop particles from falling into the local minimum and make the global optimal solution easier found by particles. Experiments were conducted on 7 CEC 2008 test functions to present solution searching ability of the proposed method.
Non-fragile robust model predictive control for polytopic systems with packet dropouts

This paper is concerned with the non-fragile robust model predictive control (MPC) for a class of polytopic uncertain systems with packet dropouts. A novel system with respect to non-fragile controller and packet dropouts is investigated by MPC approach. A non-fragile controller is adopted with hope to deal with the controller perturbations and deviations, which might be a potential factor for system dynamic performance deterioration and instability. Moreover, a sufficient stability criterion is presented by using stochastic analysis and Lyapunov-like function approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimization subject to the convex constraint. Finally, some simulation examples are employed to show the effectiveness of the method.
The fault-tolerant framework of large-scale disasters based on continuity management: A case of power network infrastructure

The large-scale disaster has characteristics of complexity, uncertainty and dynamics, and leads to accident scene, so it has brought difficulties and challenges to the emergency management process. In order to response to the large-scale disaster effectively, according to business continuity management, this paper studies on the fault-tolerant planning framework with power network infrastructure as an example. In post-disaster restoration stage and disaster preparation stage, the fault-tolerant planning should be designed, which includes three types of fault-tolerant way, such as task approach, resource approach and process approach. In other words, within a certain range local government or emergency management department implements the fault-tolerant planning, and improves the necessity of redundancy appropriately, so as to promote the continuity of emergency rescue mission. Fault-tolerant approaches provide emergency decision makers a practical working method, help decision makers master rules and methods to response to accident scenario, which provide a new way for emergency management and promote the theory progress in the new field of emergency management.
Access control method based on multi-level security tag for distributed database system

An access control method for distributed database system is discussed in this paper. The method is based on multi-level security tag and mandatory access control policy. This paper designs Multi-level security system structure and defines the security tags of subjects and objects. It also presents definition rule of security tag and security tag table. Mandatory access control is achieved by modifying the user's query statement and using security tag table in distributed database system.
Research on shipborne TDRSS/SINS integrated navigation technology

This paper is to extend the applications of TDRSS and provide a new thread for the survey ship acquire the position. An algorithm of the shipborne TDRSS/SINS integrated navigation is proposed by using one-way Doppler autonomous navigation of TDRSS. The observation equation with the Doppler data received from TDRSS is deduced. The SINS state equation is deduced, then the algorithm of integrated navigation is proposed by using Kalman filter theory. The accuracy of the algorithm is analysed in the end. The result shows that the high accuracy algorithm of TDRSS/SINS integrated navigation can be deduced while the accuracy depends on the numbers of satellites that can be observed and the constellation; still it can be used as an emergency plan to substitute the GPS.
A Comprehensive 3-D Framework for Automatic Quantification of Late Gadolinium Enhanced Cardiac Magnetic Resonance Images

Late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR) can directly visualize nonviable myocardium with hyperenhanced intensities with respect to normal myocardium. For heart attack patients, it is crucial to facilitate the decision of appropriate therapy by analyzing and quantifying their LGE CMR images. To achieve accurate quantification, LGE CMR images need to be processed in two steps: segmentation of the myocardium followed by classification of infarcts within the segmented myocardium. However, automatic segmentation is difficult usually due to the intensity heterogeneity of the myocardium and intensity similarity between the infarcts and blood pool. Besides, the slices of an LGE CMR dataset often suffer from spatial and intensity distortions, causing further difficulties in segmentation and classification. In this paper, we present a comprehensive 3-D framework for automatic quantification of LGE CMR images. In this framework, myocardium is segmented with a novel method that deforms coupled endocardial and epicardial meshes and combines information in both short- and long-axis slices, while infarcts are classified with a graph-cut algorithm incorporating intensity and spatial information. Moreover, both spatial and intensity distortions are effectively corrected with specially designed countermeasures. Experiments with 20 sets of real patient data show visually good segmentation and classification results that are quantitatively in strong agreement with those manually obtained by experts.
Fuzzy Clustering Analysis on Performance of Listed Tourism Companies

This paper, on the basis of standardized data, uses the financial data of listed tourism companies and Euclidean distance method to build a fuzzy matrix. Then it figures out the fuzzy equivalent matrix by square method, and does fuzzy clustering under certain clustering level. By this means, we achieve the category of tourism companies. In conclusion, the financial condition and management performance can be reflected, providing the investors and managers more reliable and precise information.
Research on the Fuzzy Comprehensive Quality Evaluation Method of the Research Oriented Courses of the Higher Vocational Colleges

The paper firstly introduces the characteristics of higher vocational research oriented courses, and analyzes the deficiency of the common methods used for evaluating the quality of the courses at present. Based on this, more scientific, comprehensive and objective multi-level fuzzy comprehensive evaluation method based on fuzzy theory is brought forward. At the same time, aiming at the characteristics of higher vocational research oriented courses, evaluation index system and weight assigning scheme are designed, and course quality index evaluation matrix is established and put into utility.
50+ years of intrinsic breakdown

The basic quantum mechanical theory for intrinsic breakdown was developed by von Hippel and Fröhlich over 70 years ago, but only now can we exploit their ideas accurately through the use of computational quantum mechanics. As shown above, von Hippel's low energy criterion for intrinsic breakdown provides remarkably good agreement with measured data for a range of both ionic and covalently bonded materials. We can correlate intrinsic breakdown with both bandgap and phonon cutoff frequency, although the relationships differ for different groups of materials. The challenge going forward is to move from intrinsic breakdown to engineering breakdown through inclusion of effects caused by morphology, chemical impurities (impurity states in the bandgap), and defects such as nanocavities. We believe that inclusion of these phenomena is possible using Monte Carlo computations with parameters computed using first principles methods, and we are pursuing this approach.