nils-herrmann/clean_scirepeval huggingface dataset:
Effects of thickness on properties of high frequency piezoelectric ultrasonic transducers

Piezoelectric ultrasonic transducer is a device to realize the conversion between electric energy and mechanical energy. The core element of the transducer is piezoelectric material, which directly affects the performance of transducer. High frequency ultrasonic transducers have higher resolution, and can recognize smaller size targets. The performances of the transducer are dependent on the frequency characteristics. The results show that the relative permittivity, piezoelectric strain constant, piezoelectric voltage constant and mechanical quality factor of the piezoelectric transducer increase with increasing thickness of piezoelectric material, and the thickness electromechanical coupling properties and resonant frequency decrease with increasing thickness. In the pulse response test of the transducers, with increasing thickness of the piezoelectric material, the transmitted time and peak-peak value of the ultrasonic wave received by the transducer increase, and the dominant frequency shows the decreasing trend.
A solution to blind separation of convolutive communication mixtures in frequency domain

In this paper, an efficient algorithm to deal with convolutive blind source separation of communication signals in frequency domain is presented. The classical JADE algorithm is adopted to perform linear complex-valued ICA in each frequency bin. To solve the permutation ambiguity problem, a new permutation technique based on high-order statistics is proposed. Then, a post processing procedure called CMA is added to compensate for signal distortion. Simulations are included to demonstrate the effectiveness of the proposed algorithms.
Application of cloud detection algorithm in the Arctic region based on AVHRR satellite data

The visible and near-infrared bands of AVHRR radiometer on the NOAA satellites can be used to monitor the Arctic sea ice cover. It is well known that Earth's surface characters in the cloud-covered regions could not be monitored exactly by the visible and near-infrared remote sensing. Therefore, the cloud detection is a fundamental process for sea ice parameters inversion. For the Arctic regions, the cloud detection algorithm has to focus on discrimination of sea ice and cloud. In this paper, the cloud detecting experiments for Arctic regions were conducted using the visible data of NOAA-19 AVHRR. The statistical characteristics of the different objects were analyzed as well. The results show that the cloud detection algorithm suit for land and ocean discrimination could not be used directly here. This is due to the similar radiation properties of sea ice and cloud. In the Arctic, on the basis of a large number of statistic analyses, the discrimination algorithm were re-screened with the thresholds being determined and revised, and then the preliminary cloud-ice discrimination algorithm for Arctic regions is obtained. This study can provide a basis for sea ice parameters inversion in Polar region, and then serve the polar sea ice monitoring.
Joint power and timeslot allocation based on delay priority for multi-beam satellite downlinks

This paper investigates the joint power and timeslot allocation for multi-beam satellite downlinks. Users with real-time and non-real-time services under different channel conditions are considered to be satisfied with limited power and timeslots. To guarantee the fairness among different users, the delay priority is introduced for optimization, while the delay constrain is used to avoid delay deterioration of real-time users. Based on this, a joint power and timeslot allocation problem is formulated to maximize the weighted sum throughput. With convex optimization theory, the optimal power and timeslot allocation is derived, and a joint allocation algorithm based on subgradient method is proposed to determine the optimal solutions. Simulation results show that the proposed algorithm realize the trade-off between throughput and loss probability with delay fairness guarantee.
Design and In-Orbit Test of the Integrated Electronic System Based on General Cell

Based on the General Cell concept, proposed a satellite system which integrated on-board computer, attitude and orbit control system and TT&C system into an integrated electronic system, and had carried out In-orbit test on Test Satellite III. The composition mainly includes the processor unit and RF unit. This scheme adopts embedded systems technology, SoC technology and RFIC technology as the core technology of the processor unit and RF unit which composed the integrated electronic system. The integrated electronic system which use the multi-processor have enhanced computing and management ability to manage the attitude measurement unit through the CAN bus to accomplish attitude calculation, and use the LNA and PA to improve the RF unit communication reliability. These methods greatly enhance the functional density of electronic systems to achieve the formation platform and high functional density communications payload design. Experiments on Test Satellite III verify the integrated electronic system has a powerful computing, processing capacity and reliable inter-satellite communication capacity. The integrated electronic system can act as a universal spacecraft micro-platform for formation flying satellite payload. This work greatly promotes the development of the miniaturization of spacecraft and formation flying communications technology.
An Operable Matching Algorithm for Bigraphs

We use bigraph to represent each state in the bigraphical reactive systems (BRS) in which the problem of matching for bigraphs is extremely important. This problem has been referred in many papers, but in these papers only bigraphs with simple structure (i.e. a bigraph has no sites, outer names or inner names) were given as example, what's more, they gave no a specific algorithm. So, they do not make it clear how to match a general bigraph. In order to solve this problem and get a generally applicable algorithm for matching, we should get the appropriate algebraic expression of bigraph first. Then, we make some improvements on the algebraic expression of bigraph so as to model a general bigraph and propose an operative matching algorithm for bigraph. Moreover a specific instance of matching is presented to illustrate this algorithm is effective in this paper.
A novel evolution learning for recurrent wavelet-based neuro-fuzzy networks

This study presents a recurrent wavelet-based neuro-fuzzy network with dynamic symbiotic evolution (RWNFN-DSE) model which combines the traditional Takagi-Sugeno-Kang (TSK) fuzzy model and the wavelet neural networks (WNN). The proposed RWNFN-DSE is used to dynamic system processing. A novel evolution learning called dynamic symbiotic evolution (DSE) is used to tune the parameter of the RWNFN-DSE model. Better chromosomes will be initially generated while the better mutation points will be determined for performing dynamic-mutation. Simulation results have shown that the proposed RWNFN-DSE model obtains better performance than other existing models
Analysis of frequency splitting phenomena for magnetic resonance wireless power transfer systems

A mutual coupling theory is used to analyze the frequency splitting phenomena in magnetic resonance wireless power transfer (WPT) systems, along with a derivation of the critical coupling point (maximum operating distance at which maximum power-transfer efficiency is still achievable). Theoretical analysis and simulation results show the clearly visible frequency splitting phenomena, and reveal that the critical coupling point represents the farthest distance at which the power-transfer efficiency remains the maximum. A derivation of the resonance frequency function of WPT system reveals that the quality factors of receive coil plays a tremendous role in system performance. The study and test results can provide a theoretical support for the design of high power-transfer efficient WPT system based on magnetic resonance.
A FNN control of underwater vehicles based on ant colony algorithm

For the particular controlled object AUV, a novel controller based on the fuzzy B-Spline neural network is presented, which embodies the merits of qualitative knowledge representation capability of fuzzy logic, quantitative learning ability of neural networks, as well as the excellent local controlling ability of B-Spline basis functions. However, to overcome the inherent deficiencies in the fuzzy neural network, including the structure hardly to be fixed, slow-speed training with the tendency to be involved in local convergence, and the quality of training results dependent upon the initial conditions of the network as well, some optimizing efforts are carried out in this investigation. The improved dual ant algorithm is employed for offline optimization, which can efficiently avoid the phenomenon of precocity and stagnation during the evolution. Meanwhile, the expert experience is introduced to simplify the number of optimizing parameters, and then the controller is further improved with the hybrid training by adopting the BP algorithm proceeding online adjustment. The simulation of the AUV motion control demonstrates the feasibility and validity of the present method.
Hash-Based Block Matching for Screen Content Coding

By considering the increasing importance of screen contents, the high efficiency video coding (HEVC) standard includes screen content coding as one of its requirements. In this paper, we demonstrate that enabling frame level block searching in HEVC can significantly improve coding efficiency on screen contents. We propose a hash-based block matching scheme for the intra block copy mode and the motion estimation process, which enables frame level block searching in HEVC without changing the HEVC syntaxes. In the proposed scheme, the blocks sharing the same hash values with the current block are selected as prediction candidates. Then the hash-based block selection is employed to select the best candidates. To achieve the best coding efficiency, the rate distortion optimization is further employed to improve the proposed scheme by balancing the coding cost of motion vectors and prediction difference. Compared with HEVC, the proposed scheme achieves 21% and 37% bitrate saving with all intra and low delay configurations with encoding time reduction. Up to 59% bitrate saving can be achieved on sequences with large motions.
Improved mammographic mass retrieval performance using multi-view information

Breast cancer is the most common malignant disease in women. Mammographic mass retrieval system can help radiologists to improve the diagnostic accuracy by retrieving biopsy-proven masses which are similar with the diagnostic ones. However, although screening mammograms usually consists of two-view(MLO and CC) mammography of the same breast, most breast CAD systems incorporate with image retrieval techniques are based on a single-view principle where query ROI within a view is analyzed independently. In this paper, a mammographic mass retrieval approach based on multi-view information is proposed. In this work, the query example is a multi-view(MLO and CC) mass pair instead of the single view mass in the traditional image retrieval framework. In the experiments, several visual features are used for retrieval evaluation. Both distance similarity measures, such as Euclidean distance, and k-NN regression model based non-distance similarity measures are used for comparison. Experimental study was carried out on a database with 126 biopsy-proven masses(63 mass pairs). Preliminary results showed that multi-view based retrieval approach achieves better retrieval accuracy than single-view based one, especially for the k-NN regression model based similairy metric.
Intra-predictive transforms for image coding

This paper presents a new transform framework, intra-predictive transforms, for block-based image coding. The proposed framework unifies cross-block prediction and transforms within a block. Thus, it can exploit both the intra- and inter- block correlations. The intra-prediction in H.264 can be viewed as a special case of intra-predictive transforms. The new framework provides more flexibility to design new transform for coding. As an example, a new intra-predictive transform based on frequency domain prediction is also presented to show the advantages of the proposed framework.
Evidence based decision analysis and support

The evidential reasoning (ER) approach was developed to support multiple criteria decision analysis (MCDA). It is based on the Dampster's combination rule for criteria aggregation and belief function for treating ignorance. In the original ER approach, however, alternative ranking depends on the accurate estimation of a value function, which may be difficult in certain decision environments. In this paper, the link and difference between the ER algorithm and Dampster's combination rule are analysed first. A new alternative ranking method is then investigated as an integrated part of the enhanced ER approach.
Graph embedding: a general framework for dimensionality reduction

In the last decades, a large family of algorithms - supervised or unsupervised; stemming from statistic or geometry theory - have been proposed to provide different solutions to the problem of dimensionality reduction. In this paper, beyond the different motivations of these algorithms, we propose a general framework, graph embedding along with its linearization and kernelization, which in theory reveals the underlying objective shared by most previous algorithms. It presents a unified perspective to understand these algorithms; that is, each algorithm can be considered as the direct graph embedding or its linear/kernel extension of some specific graph characterizing certain statistic or geometry property of a data set. Furthermore, this framework is a general platform to develop new algorithm for dimensionality reduction. To this end, we propose a new supervised algorithm, Marginal Fisher Analysis (MFA), for dimensionality reduction by designing two graphs that characterize the intra-class compactness and inter-class separability, respectively. MFA measures the intra-class compactness with the distance between each data point and its neighboring points of the same class, and measures the inter-class separability with the class margins; thus it overcomes the limitations of traditional Linear Discriminant Analysis algorithm in terms of data distribution assumptions and available projection directions. The toy problem on artificial data and the real face recognition experiments both show the superiority of our proposed MFA in comparison to LDA.
A novel formal framework for secure dynamic services composition

There is a pressing need for secure services composition in agenda transactions. Orchestration and choreography language provide basic services and interaction, collaboration, and negotiation standards among services, but they don't give any secure manners or secure operation styles and specifications. Despite the interest of such security mechanisms, a formal module of them is still lacking. For giving a general guide to implement secure orchestration and secure choreography, we give a formal approach for carrying out this goal. To those targets, we address those by designing an extension of the Spi calculus with Secure Global Calculus. The Spi calculus precisely identifies orchestration secure properties of each principal from a local viewpoint. The secure global calculus describes an interaction secure choreography scenario from a vantage point of view. We called our framework SpiG4WSC calculus. We believe that the combination of strong practical needs for dynamic secure Web services composition and the theoretical foundations will lead to a bridge between practice and theories.
Distributed relay assignment and power control for energy efficient bidirectional relaying

This paper addresses an optimal energy-efficiency problem subject to a desired service quality constraint for an amplify-and-forward bidirectional relaying network. Unlike most of the existing works, both the transmit and circuit energy consumptions are considered and especially the circuit energy consumption is modeled as a function of the data rate, rather than as a constant. In order to simplify its solution, the optimal energy-efficiency problem is transformed into a two-stage problem, stage 1: optimal power allocation of terminals; and stage 2: distributed relay assignment. Summarizing the results achieved at stages 1 and 2, a distributed relay assignment and power control technique is proposed for optimal energy-efficiency. Simulation results demonstrated that our proposed technique can significantly enhance the energy efficiency, while ensuring the desired service quality of the network.
Combinative presentation of body surface distribution and time variation of cardiac potential

In this paper we propose a new method for presentation of the data from body surface potential mapping (BSPM) by constructing isopotential maps on a plane with two coordinates of time and space. A high performance BSPM system was constructed for our study. 50 normal subjects and 10 patients with myocardial infarction were involved. Results demonstrate that the proposed space-time potential map is an effective method to quantitatively present the global features of the space-time distribution of ECG and make up the deficiency of the isopotential map and the isochrone map. This method provides visually a description of the space dispersion of the time when T wave ends. It is a useful method to differentiate U wave distribution from T wave.
FaLRR: A fast low rank representation solver

Low rank representation (LRR) has shown promising performance for various computer vision applications such as face clustering. Existing algorithms for solving LRR usually depend on its two-variable formulation which contains the original data matrix. In this paper, we develop a fast LRR solver called FaLRR, by reformulating LRR as a new optimization problem with regard to factorized data (which is obtained by skinny SVD of the original data matrix). The new formulation benefits the corresponding optimization and theoretical analysis. Specifically, to solve the resultant optimization problem, we propose a new algorithm which is not only efficient but also theoretically guaranteed to obtain a globally optimal solution. Regarding the theoretical analysis, the new formulation is helpful for deriving some interesting properties of LRR. Last but not least, the proposed algorithm can be readily incorporated into an existing distributed framework of LRR for further acceleration. Extensive experiments on synthetic and real-world datasets demonstrate that our FaLRR achieves order-of-magnitude speedup over existing LRR solvers, and the efficiency can be further improved by incorporating our algorithm into the distributed framework of LRR.
Dual-Band Electronically Beam-Switched Antenna Using Slot Active Frequency Selective Surface

This communication presents an a cylindrical active frequency selective surface (AFSS)-based electronically beam-switching antenna, which can operate at two different frequency bands. The antenna consists of a slot AFSS and an omnidirectional dual-band feed antenna. The p-i-n diodes of the AFSS can be switched on or off to reconfigure the AFSS as transparent or opaque to the incident electromagnetic waves, respectively. Thus, by controlling the dc bias voltages to different columns of p-i-n diodes, the directive beams of the antenna can be swept to cover the whole azimuth plane. To validate the design concept, the transmission coefficients of the active FSS sheet are experimentally examined. An antenna prototype operating at 2.5 and 5.3 GHz frequency bands is also fabricated and measured. Simulation and measurement results of the antenna are presented to verify the design principle. A comparison between this communication and other recent designs is provided. The antenna has advantages of low power, low cost, easy fabrication, and electronic beam switching covering a full 360° angular range.
DICOM Validation Sets: A DICOM Test Case Preparation Method for System Integration in Radiology

With the advances of DICOM standard, DICOM conformance test becomes more and more important. In real Radiology system integration test, because of the complexity and flexibility of the DICOM standard, the test cases are very complex and in most test situation the test case is not abundant. Sometimes some integration problems can not be found or be resolved only because the test case is not enough. Based on a detailed analysis of DICOM standard, this paper brings forward a DICOM validation sets method to prepare DICOM test case for system integration in radiology before test. To broaden the validation sets' accessibility, the extensible markup language (XML) is used to encode the validation sets. Two kinds of validation sets: flow validation sets and data validation sets are presented. For clearness, one use case: the DICOM validation system is firstly introduced.
Modeling and Simulation for Fuel Cell-Battery Hybrid Electric Vehicle

a model for the Fuel Cell-Battery Hybrid Electric Vehicle (FCHEV) power train in parallel configuration simulation based on the empirical formulation and MATLAB/Simulink blocks has been constructed with the power control strategy using logic threshold approach. Using accelerator pedal signal generated by the driving schedule as the primary input, the simulation implements difference power flow and management under the vehicle operating modes: start, cruise, accelerate and pause. It also incorporates regenerative braking for battery capacity recovery. Main control variables and three group threshold values are evaluated for the vehicle driven under the New Europe Driving Cycle (NEDC) schedule. The results indicate that this configuration of the FCHEV model has capability for battery state of charge (SOC) recovery while meeting vehicle speed and drive power request. The effect that the control thresholds impact on the power distribution and fuel consumption has also been simulated.
Comprehensive Analysis on Water Quality of Nihe River in Panji Mining Area of Huainan

Nihe River is the main natural water system in Panji mining area of Huainan. By setting points, sampling and monitoring different sections in different seasons, this paper roundly analyzes and appraises the water quality from the angles of physicochemical indexes, conventional ions, heavy metal elements and microorganism. The results show Nihe River is polluted that transparency is small, that DO is rich, that BOD and COD is higher than normal level and the water is weak basic. The river is polluted more seriously downriver than upriver. Conventional ions, heavy metal elements, microorganism and parts of physicochemical indexes are increasing from upriver to downriver and have accumulative effect. Compared with standard of environment quality of national surface water (GB3838-2002), heavy metal elements As, Se, Cr, Cu, Zn isn't beyond III standard, while Hg is beyond III standard and Cd, Pb is beyond V standard. Besides, the water has differences in different seasons and has seasonal variations. The theoretical basis about protection and comprehensive utilization of the river is provided through analysis and evaluation.