nils-herrmann/clean_scirepeval huggingface dataset:
Application of TCFM cloud motion wind data in the analysis study of Typhoon Morakot(0908)

TCFM cloud motion wind technique is a new technique for tracking cloud with combination of Fourier phase analysis and maximum correlation (TCFM) to improve the precision of cloud tracking. In this article, TCFM technique is employed to retrieve cloud motion vectors for severe tropical storm “Morakot” from geostationary meteorological satellite FY-2C image series with a 30min interval on August, 2009. The retrieved data are assimilated at 1h interval into the numerical model ARPS (the Advanced Regional Prediction System) by means of its data analysis system ADAS for forecasting, and the first six hours before landing process of Typhoon “Morakot” was simulated. By comparison the result with sounding data assimilated into the initial field, concluded that the simulation result of continuous assimilation of the TCFM data shows a strong advantage in the forecast of storms and precipitation in the typhoon eye wall region.
An Incremental Boundary Element Method for the Variation-Aware Library-Building Procedure of Capacitance Extraction

The variation of process parameters makes the number of geometry patterns in capacitance extraction increase for magnitudes, which brings a heavy burden to the library-building procedure. An incremental BEM solver is proposed for the variation-aware library-building. This method reuses the coefficient matrix and solution of the original pattern for the sequent computations for varied patterns. Numerical results show the proposed method is five times faster than the method just repeats the computation for all patterns, while preserving high accuracy
A study of damp-heat syndrome classification using Word2vec and TF-IDF

With people's increasing concern about health, judging people's health through medical record is becoming a potential demand. Most of preview disease analysis researches were conducted on structured dataset, which usually ignored the relationship between different symptoms, and the dataset was expensive to get. In this paper, we proposed a novel model based on Word2vec and Terms Frequency-Inverse Document Frequency (TF-IDF), which could be used to detect damp-heat syndrome on unstructured records directly. Firstly, we adopt ICTCLAS system combined with corpus collected in the field of Traditional Chinese Medicine (TCM) to segment the clinical records into words. Secondly, Word2vec tool was used to train word vector. Then, we constructed the record representation vector according to word vector and TF-IDF. The record representation method was named Word2vec+TF-IDF. In order to verify the effectiveness of the proposed method, we compared our record representation method with other text representation methods under four different classifiers. The experiment was conducted on the dataset collected from over 10 Chinese Medicine hospitals. And the experimental results show that our model perform better than the state-of-the-art methods such as LSA and Doc2vec.
Comparative Study on the Sedimentation Rules of Flotation Tailing and Natural Clay

Sedimentation column test is adopted to study the natural sedimentation rules of floatation full tailing and dredged sediment at storage yard. The study shows that, the double logarithmic coordinates of sedimentation speed and time could be used to divide the sedimentation process of tailing and dredged sediment into the stage of natural sedimentation and the stage of consolidation under deadweight; and at the stage of natural sedimentation, the duration is 3h and 4h respectively. Along with the extension of sedimentation time, the water content and void ratio of tailing and dredged sediment will decrease gradually, and then tend to be stable; however, things are the contrary for density. Meanwhile, the sedimentation column test proves that tailing and dredged sediment have similar sedimentation property.
A Mixed Representation-Based Multiobjective Evolutionary Algorithm for Overlapping Community Detection

Designing multiobjective evolutionary algorithms (MOEAs) for community detection in complex networks has attracted much attention of researchers recently. However, most of the existing methods focus on addressing the task of nonoverlapping community detection, where each node must belong to one and only one community. In fact, communities are often overlapped with each other in many real-world networks, thus it is necessary to design overlapping community detection algorithms. To this end, this paper proposes a mixed representation-based MOEA (MR-MOEA) for overlapping community detection. In MR-MOEA, a mixed individual representation scheme is proposed to fast encode and decode the overlapping divisions of complex networks. Specifically, this mixed representation consists of two parts: one represents all potential overlapping nodes and the other delegates all nonoverlapping nodes. These two parts evolve together to detect the overlapping communities of networks based on different updating strategies suggested in MR-MOEA. We verify the effectiveness of the proposed algorithm MR-MOEA on ten real-world complex networks and the experimental results demonstrate that MR-MOEA is superior over six representative algorithms for overlapping community detection.
An Algorithm for Mining Fuzzy Association Rules Based on Immune Principles

In this paper, an algorithm was proposed for mining fuzzy association rules based on natural immune principles. The proposed algorithm is mainly inspired by the clonal selection principle of biological immune systems. It was employed to optimize the number of fuzzy association rules that satisfy the specified thresholds by adjusting the parameters of fuzzy sets for each quantitative attribute. The performance of our algorithm has been compared with other relevant algorithms and the experimental results showed the effectiveness of our algorithm.
A new PD type iterative learning control in active control for vibration

In order to enhance learning efficiency and to deal with the periodic vibration sources, a proposition difference type iterative learning control algorithm is proposed. The PD ILC in the two degree ldquomass spring dampingrdquo mount active solution is vestigated to instead the passive solution. With the method, the performance at low frequencies has been improved specifically. Simulation shows that the displacement could converge to zero fast and that the PD type iterative learning control in active method can achieve vibration isolation excellently.
Control strategy of hot blast stove's combustion system - fuzzy self-adaptive control

Based on the existing situations and problems in hot blast stoves, in combustion systems, new research direction and methods of automatic control were introduced here. This includes online computation and adjustment of the ratio of air to fuel with the help of gas analyzer, and self-adapted fuzzy control with adjusting parameters of hot blast stove combustion systems. According to the result of preliminary running and simulation, less BFG (blast furnace gas) was used, the efficiency of heat transfer was made better, the temperature of hot gas was increased, and air pollution was decreased. The proposed method met the requirements of techniques and could improve the economic benefits and social benefits as well.
Channel capacity and correlation analysis for distributed spaceborne SAR system

Distributed spaceborne SAR system is composed of several small satellites each has a transmit antenna and a receive antenna. There are multiple antennas at the earth station, and this constitutes a generalized MIMO system. According to 3GPP TR25.996 specification, we propose a distributed MIMO channel model in spaceborne SAR system. We analyze the channel capacity its correlation, and complement simulations with matlab.
An ultra high-speed 8-bits analog-to-digital converter design

In this paper, an ultra high-speed 8-bits analog-to-digital converter with digital foreground calibration in 0.18-µm CMOS technology is presented. The spice simulation and the measured results show the folding and interpolating ADC produces 5.9 ENOB with calibration disabled and 7.2 ENOB with calibration Enabled at Nyquist.
An efficient method to enhance Bitcoin wallet security

With widely adoption of Bitcoin, Many malicious software trying to steal bitcoins through network has emerged in a large scale. Bitcoin makes heavy use of elliptic curve digital signature algorithm to guarantee transactions security. Each user can have lots of addresses hashed from his public keys to receive coins, and need private keys associated with these addresses to authorize spending those coins. A Bitcoin wallet give a good assistance to manage and preserve all private keys belong to its owner. However, saving complete private keys on local storage meets a big challenge in case of theft. For the purpose of securing user's private keys, we propose an efficient method to enhance Bitcoin wallet security. We combine random seeds and a passphrase for user easy to keep in mind to generate private keys whenever needed. It is only need to reserve a list of random seeds on local storage instead of complete private keys. Nobody could generate the whole private keys just relying on random seeds without the passphrase. Therefore, our method increases the difficulty for attackers to steal bitcoins. We also introduce a key recovery approach in case of the passphrase being forgotten. Our method does not incur any additional operations and is convenient to use by a common customer without professional knowledge.
A Robust Motion Compensation Approach for UAV SAR Imagery

Unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) is an essential tool for modern remote sensing applications. Owing to its size and weight constraints, UAV is very sensitive to atmospheric turbulence that causes serious trajectory deviations. In this paper, a novel databased motion compensation (MOCO) approach is proposed for the UAV SAR imagery. The approach is implemented by a three-step process: 1) The range-invariant motion error is estimated by the weighted phase gradient autofocus (WPGA), and the nonsystematic range cell migration function is calculated from the estimate for each subaperture SAR data; 2) the retrieval of the range-dependent phase error is executed by a local maximum-likelihood WPGA algorithm; and 3) the subaperture phase errors are coherently combined to perform the MOCO for the full-aperture data. Both simulated and real-data experiments show that the proposed approach is appropriate for highly precise imaging for UAV SAR equipped with only low-accuracy inertial navigation system.
A new method about placement of the branch cut in two-dimensional phase unwrapping

Phase unwrapping is one of the key problems in data processing of interferometric synthetic aperture radar (InSAR). One of the classic unwrapping algorithms is the path-following approach based on placement of branch cut. In this paper, we prove that existence of residues is a sufficient but unnecessary condition for the original phase discontinuity and the true placement of the branch cut is unique. Then a modified method of placing branch cuts which is guided by improved quality map is proposed. The simulation examples show that the modified method is more effective and practicable.
A C-band microwave rectifier based on harmonic termination and with input filter removed

This paper presents a C-band rectifier employing a third harmonic termination which is realized by a λg/12 short-ended microstrip transmission line. The proposed harmonic termination balances the capacitive impedance of the diode at the fundamental frequency and blocks harmonic current of the diode. The input low-pass filter or matching circuit is removed and the bandwidth of rectifier is enhanced. Theoretical analysis and experiments are carried out. The results show that the proposed topology can realize high efficiency with a wide input frequency range. The fabricated rectifier has a compact dimension of 14mm by 22mm. A maximum RF-DC conversion efficiency of 75.6% at 13 dBm input power is observed. The measured efficiency remains above 70% with the operating frequency form 5.2 GHz to 6 GHz.
A Generic Communication Architecture for End to End Mobility Management in the Internet

The proliferation of laptops, cellular phones, and other mobile computing platforms connected to the Internet has triggered numerous research works into mobile networking. The increasingly dense set of wireless access networks that can be potentially accessed by mobile users open the door to an era of pervasive computing. However, the puzzle of wireless access networks that tends to become the natural access networks to the Internet pushes legacy "wire- oriented" communication architectures to their limit. Indeed, there is a critical gap between the increasingly used stream centric multimedia applications and the incapacity of legacy communication stacks to insure the continuity of these multimedia sessions for mobile users. This paper proposes a generic communication architecture (i.e. not dedicated to a specific protocol or technology) that aims to fill the gap between the application layer continuity needs and the discontinuity of the communication service inherent to the physical layer of wireless mobile networks. This paper introduces an end to end communication architecture that preserves efficiently session continuity in the context of mobile and wireless networks. This architecture is mainly based on end to end mechanisms that could be integrated into a new generation reconfigurable transport protocol. The proposed contribution efficiently satisfies mobility requirements such as efficient location management, fast handover, and continuous connection support.
Design of MEMS on-chip helical antenna for THz application

In this work, a novel design tor a tully on-chip 3D antenna operating at 4 THz that can be fabricated by a novel MEMS (micro electro mechanical systems) technology directly realized on a silicon substrate is presented. The antenna includes two parts, the metallic helix and the microstrip on the substrate for feed. The proposed antenna structure is well suitable designed by MEMS technology, the fabrication of the structure needs only one wafer, and the antenna can be easily integrated with other parts of on-chip circuits. The antenna is characterized by high gain (17.6 dBi) and wide relative bandwidth (44%) from 2.8THz to 4.4THz. There are many tunable parameters of the helix, so that high performance THz antenna can be achieved by optimizing these parameters. The proposed antenna can be manufactured by MEMS processing with low fabrication cost, suitable for many THz systems.
A two-level framework for coalition formation via optimization and agent negotiation

We present a two-level coalition formation approach based on a centralized optimization model on the upper level, and a distributed agent-negotiation model on the lower level. This approach allows us to balance agent self-interests against a high joint utility. Experimental results show that the two-level coalition formation mechanism increases not only the overall utility of the coalition, but also the individual utility of most participating agents. The results also suggest it is better for the agents to be partially cooperative rather than either fully cooperative or self-interested in our setting.
Characterization and modeling of frequency dispersion in RF LDMOS transistors

This paper characterises the effects of frequency dispersion in laterally diffused metal-oxide semiconductor (LDMOS) from pulsed-S-parameter measurements. Using the calculated high-frequency drain current from measured data, we demonstrate that length of the lightly doped drain extension is directly proportional to the amount of current collapse at high frequency. To capture the frequency dispersion in a nonlinear model, a frequency-domain mapping is proposed to augment quasi-static nonlinear electrothermal models. The importance of including the dispersiveness is demonstrated through comparing a standard quasi-static model, the newly augmented model, and on-wafer load-pull measurements. For a 5-mm, 500 μm unit-gate-width transistor, we demonstrate that the quasi-static model over predicts the drain efficiency during large signal drive at P3dB by 9%. The new augmented model is able to predict the efficiency within 2% of the measured value.
A High Reliable and Performance Data Distribution Strategy: A RAID-5 Case Study

With the development of the storage medium, such as the emerging of the SSD, the tradition way of data distribution can't keep up with the pace of the storage device development. Specifically, for example, Traditional RAID only enhanced the performance or reliability in the single storage medium and all the data are distributed in the same storage medium. But with the wide range of using raid, the problem of RAID data adventure has come to the surface gradually. Furthermore, under the mode of RAID-5 read modify-write (R-M-W), operation system collapse or the storage medium write error would lead to the damage of data, which could not be recovered and this problem is named write hole. According to the above problem, this paper proposes a new data distribution strategy, which is called high reliable and performance data distribution strategy (RPDD). RPDD use the high performance storage medium as a cache which is named storage cache. The most of the data is wrote to the storage cache and then distribute the data to the other logic relationship storage medium. As a result, the data is distributed in a hybrid storage medium. In order to take a better analysis of the RPDD in the next, we have combined RPDD in the RAID-5, which is named RAID-5-RPDD. RAID5-RPDD employs the dynamic scheduling mechanism, data transfer and hybrid consistency mechanism between the SSD and magnetic media storage devices to resolve the problem. In consequence, it can protect the RAID stripe data consistency under the condition of R-M-W and increase the I/O performance without the impact of the cost. In addition, it can improve the reliability of the RAID-5. The simulation test results show that RAID-5-RPDD I/O performance increase at the range of 9% with little penalty of the resource consumption.
A Simulation and Monitoring System for the Humanoid Robot BHR-02 Teleoperation

Most existing teleoperation system for humanoid robot by using the video camera does not fit to the poor visibility situation. Also a visual instruction prediction interface can give operators the preview of the operation instruction result which is useful for the complex task and the operator training. This paper presents a method to reconstruct the virtual scene of the humanoid robot teleoperation. A virtual robot interface is built to render the data of the humanoid robot BHR-02. It has the same DOF configure and the same size scale as the real robot. Based on the virtual interface, a simulation and monitoring system is built for the humanoid robot teleoperation. As a simulator, the interface can render data of the teleoperation instructions. As a monitor, the interface can render the multiple real-time feedback data from the robot. Some experiments are done to confirm the effectiveness of the system
A new range-based localization algorithm for wireless sensor networks

The problem of find the location of a node in wireless sensor networks has been a research interest in recent years. However, traditional range-based localization methods for wireless sensor networks usually can not achieve high localization accuracy, when the number of labor anchor is less than three. In this paper, we propose a novel rang-based distributed localization algorithm based on genetic algorithm. The algorithm is divided into two stages: use sampling method to obtain initial location and refines the initial location based on genetic algorithm. Simulation results show our algorithm achieves high localization accuracy when anchor ratio is less. Compared with similar method, our algorithm obtains higher localization accuracy.
A new dynamic address solution for moving target defense

The dynamic address techniques that dynamically change network properties including protocols and addresses have been a major focus area of moving target defense. Current dynamic address proposals have a common limitation that the changing scope of a certain terminal host is limited to its corresponding subnet in the process of address dynamically changing. A new dynamic address solution is proposed based on software defined network to enlarge the changing scopes of terminal hosts. The effectiveness of proposed solution is evaluated by an experimental network created by mininet. The experiment results show that the proposed solution could effectively manage the dynamically changing process and extend the terminal hosts' changing scopes to a great extent.
Behavioral Modeling of Power Amplifiers With Dynamic Fuzzy Neural Networks

In this letter, dynamic fuzzy neural networks (D-FNN) are applied to model power amplifiers (PAs) with memory effects. The D-FNN model implements Takagi-Sugeno-Kang (TSK) fuzzy systems based on extended radial bias function (RBF) neural networks. The parameters of the model are trained by the online self-organized learning algorithm, in which the neurons can be recruited or deleted dynamically according to their significance to system performance, and the over fitting or over training problems can be avoided. The D-FNN model is validated in our test bench in which a Doherty PA is excited with 10 MHz and 20 MHz worldwide interoperability for microwave access (WiMAX) signals. Experimental results show that the D-FNN model can give an accurate approximation to characterize the wideband PAs with memory effects.
Design of a cloud robotics middleware based on web service technology

In the process of robotics applications development, Robot Operating System (ROS) has been a defactostandard tool. However, ROS nodes always run at the on-board computer. Limited resources of CPU and storage restrict the ability of robotics when performing a task. A good solution is to transfer the computing-intensive tasks to the Cloud. In view of this, we deploy ROS packages in Cloud virtual machines and encapsulate them as web services. Meanwhile, we design a middleware based on web service technology. As the core of the whole Cloud Robotics system, the middleware is responsible for parsing the Cloud Robotics task request and schedule ROS nodes in a distributed network. Experiments have been performed to validate the reliability of the middleware.
Curvature and singularity driven diffusion for oriented pattern enhancement with singular points

Oriented patterns, e.g. fingerprints, consist of smoothly varying flow-like patterns, together with important singular points (i.e. cores and deltas) where the orientation changes abruptly. Gabor filters and anisotropic diffusion methods have been widely used to enhance oriented patterns. However, none of them can well cope with regions of varying curvatures or regions surrounding singular points. By incorporating the ridge curvatures and the singularities into the diffusion model, we propose a new diffusion method to better exploit the global characteristics of oriented patterns. Specifically, we first locate the singular points, and regularize the estimated orientation field by using a singularity driven nonlinear diffusion process. We then enhance the oriented patterns by applying an oriented diffusion process which is driven by the curvature and singularity. Experiments on synthetic data and real fingerprint images validated that the proposed method is capable of consistently enhancing oriented patterns while well preserving the ridge structures in singular regions.