nils-herrmann/clean_scirepeval huggingface dataset:
A Novel Off-line Signature Verification Based on One-class-one-network

This paper proposes a novel off-line signature verification method based on one-class-one-network classification, using four groups features. The features include direction features, texture features, dynamic features and complexity index. At last, one-class-one-network classifier is used to verify the signatures. The signature verification system was experimented on real data sets and the results show the system is effective with the average error rate can reach 1.8%, which is obviously satisfactory.
An novel image segmentation framework by cooperative learning and evolutionary two-objective kernel clustering

This paper aims to present two novel techniques in synthetic aperture radar (SAR) image segmentation by cooperative competition, cooperative learning and evolutionary multi-objective clustering in kernel mapping thereof. First, we introduce an efficient implementation of cooperative/competition evolution by using two parallel implemented populations, which are divided by the Pareto domination and local density information. Second, two conflicting fuzzy clustering validity indices are incorporated into this framework and optimized in kernel distance measure simultaneously and. Finally, the proposed algorithm is tested on two complicated SAR images. Compared with four other state-of-the-art algorithms and our method achieve comparable results in terms of convergence, diversity metrics, and computational time.
Design of logistics data collection system based on RFID&ZigBee technology

Based on RFID and ZigBee technology a novel logistics data collection system is proposed, in which the data collection terminal with data graphics management, multi-thread task scheduling and interrupt scheduling is designed. In the simulation studies, communication characteristic test & analysis are given. The experimental results demonstrate that our proposed system is feasible and the system functions such as RF-Information collection, wireless transmission and information real-time trace are realized.
A novel track and hold circuit with offset and gain calibration

A novel track and hold circuit in 0.18μm SiGe BiCMOS process is presented, whose offset and gain can be digitally calibrated, and which can be used in a time-interleaved ADC to improve its performances. The simulated results show that the proposed track and hold circuit can sample a signal at a rate of 1.25GHz, while consuming just 50mW. The offset calibration can get a range of 26.6mW with a step of 0.1mW, while the gain calibration gets a range of 33.28dB with a step of 0.13dB.
A teleoperation system for mobile robot BCAR-01 with multiple viewpoints virtual scene

To control mobile robot BCAR-01 remotely, a teleoperation system is presented with a multiple viewpoints virtual scene of the robot and its worksite. The constructed scene is used to get knowledge of the robot and its working environment, besides the real video feedback from the robot vision system. It can present images in multiple person viewpoints. In a complex task, operators can conveniently select different viewpoints to get the information of the robot status or target for different task process. Finally, the effectiveness of the teleoperation system is illustrated by experiments that the operator manipulates mobile robot BCAR-01.
An Integrated Nine-Switch Power Conditioner for Power Quality Enhancement and Voltage Sag Mitigation

A nine-switch power converter having two sets of output terminals was recently proposed in place of the traditional back-to-back power converter that uses 12 switches in total. The nine-switch converter has already been proven to have certain advantages, in addition to its component saving topological feature. Despite these advantages, the nine-switch converter has so far found limited applications due to its many perceived performance tradeoffs like requiring an oversized dc-link capacitor, limited amplitude sharing, and constrained phase shift between its two sets of output terminals. Instead of accepting these tradeoffs as limitations, a nine-switch power conditioner is proposed here that virtually “converts” most of these topological short comings into interesting performance advantages. Aiming further to reduce its switching losses, an appropriate discontinuous modulation scheme is proposed and studied here in detail to doubly ensure that maximal reduction of commutations is achieved. With an appropriately designed control scheme then incorporated, the nine-switch converter is shown to favorably raise the overall power quality in experiment, hence justifying its role as a power conditioner at a reduced semiconductor cost.
An Enhanced Adaptive Filtering Method for Suppressing Cardiopulmonary Resuscitation Artifact.

Cardiopulmonary resuscitation (CPR) must be interrupted for reliable rhythm analysis in current automatic external defibrillators because of artifacts produced by chest compressions. However, interruptions in CPR adversely affect the restoration of spontaneous circulation and survival. Suppressing CPR artifacts by digital signal processing techniques is a promising method to enable rhythm analysis during chest compressions, which would eliminate CPR interruptions for rhythm analysis. Although numerous methods have been developed to suppress CPR artifacts, the accuracy of rhythm analysis is still inadequate due to the residual artifact components in the filtered signal. This study proposes an enhanced adaptive filtering method to suppress CPR artifacts. A total of 183 shockable and 453 nonshockable segments of ECG signal, together with CPR-related reference signal, were extracted from 233 out of hospital cardiac arrest patients. The method was optimized on a training set with 85 shockable and 211 nonshockable segments, and evaluated on a testing set with 98 shockable and 242 nonshockable segments. Compared with artifact corrupted ECG signals, the signal-to-noise ratio (SNR) increased from -9.8 ± 12.5 to 11.2 ± 11.8 dB, and the accuracy was improved from 74.1% to 92.0% after filtering with the proposed method. Compared with the traditional adaptive filter, the SNR was improved by 1.7 dB and the accuracy was improved by 5.6 points. These results indicated that the proposed method could effectively suppress the chest compression related artifacts and improve the accuracy of rhythm analysis during uninterrupted CPR.
Cooperative resource allocation with QOS support in multi-cell cognitive vehicular networks

Cognitive vehicular network (CVN) is proposed to improve the spectrum efficiency and enhance the Quality of Service (QoS) performance of diverse intelligent transportation service (ITS) applications. The road traffic jams and accidents will result in heavy communication load and QoS degradation in the hot cells, and then bring about asymmetric bandwidth requirements among the cells. In order to formulate the inter-cell asymmetric resource allocation in CVNs, two alternative bargaining solutions, such as Generalized Nash Bargaining Solution (GNBS) and Generalized Raiffa-Kalai-Smorodinsky Bargaining Solution (GRKSBS), are proposed to achieve a good tradeoff between efficiency and weighted fairness. Then, GNBS-S and GRKSBS-S schemes are proposed to guarantee the QoS of safety services in the heavy load case, where the bandwidth demand and supply can not be matched well. In these resource allocation schemes, a two-band partition algorithm is developed to reduce complexity. Furthermore, the primary user activity (PUA) which can cause rate loss to secondary users is also considered to alleviate its influence to fairness. Simulation results indicate that the proposed schemes outperform both the Max-min and Max-rate schemes, and they can also improve the communication reliability of safety service considerably in CVNs.
Cycle slip detection base on common reference clock GNSS dual antenna receiver

In GPS measurement, the existence of cycle slip directly affects the ultimately positioning accuracy. In order to obtain high positioning accuracy, cycle slip in carrier phase observations must be detected and repaired. So detecting and repairing of cycle slip has become one of the most important parts of GPS phase data processing. This paper presents our investigation of the cycle slip detection and repair methods suited for common reference clock GNSS dual antenna receiver. Through inter-station single difference module, the variation ratio of the difference in the carrier phase observation values between two observation stations can be regarded as a detection, this detection amount with good smoothness and strong sensibility to cycle slip, which can be used in the studies of the cycle slip repairing. After the experimental certification, for common reference clock GNSS dual antenna receiver, this method is correct and effective.
Design of portable universal bus tester for armoured vehicles

This paper analyzes the technical characteristics of the integrated electronic system, and pointed out that the existing problems in fault diagnosis of new armoured vehicles under the condition of informatization, and describes a method of the portable armored vehicle bus testing system design and realization. Based on database technology, software multi-threading technology, as well as DMA technology, the tester has been achieved successfully. Via the validation of the real vehicle, the tester applies to integrated electronic system on armoured vehicles for online information recording, signal electrical characteristics testing and information analysis, with good reliability and feasibility.
Dipole Source Localization in Magnetocardiography

Dipole source localization (DSL) is complicated as it involves solving electromagnetic inverse problems in Magnetocardiography (MCG). The accuracy of the inverse solutions depends upon the adequacy of the forward model and the DSL algorithm used. We have developed two simplified models based on double magnetic dipoles source and a single current dipole source respectively. In this paper, the inverse solutions of DSL using Levenberg-Marquart (LM) algorithm and Nelder-Mead algorithm (NM) were discussed. Numeral simulations were performed using the MCG data generated from two different graphical models, which were reconstructed in terms of the parameter character of the real MCG measurements. An analysis of the average localization error in the ST-T segment at different noise levels and with different initial values was given. Our results indicated that the NM algorithm for both models works effectively in the case of initial values having 10% random noise. Furthermore, the localization accuracy less than 1 mm has been achieved in our research.
2D and 3D upper body tracking with one framework

We propose a Dynamic Bayesian Network (DBN) model for upper body tracking. We first construct a Bayesian Network (BN) to represent the human upper body structure and then incorporate into the BN various generic physical and anatomical constraints on the parts of the upper body. Unlike the existing upper body models, ours aims at handling physically feasible body motion rather than only some typical motion patterns. We also explicitly model part self-occlusion in the DBN model, which allows to automatically detect the occurrence of self-occlusion and to minimize the effect of measurement errors on the tracking accuracy due to occlusion. Moreover, our method can handle both 2D and 3D upper body tracking within the same framework. Using the DBN model, upper body tracking can be achieved through probabilistic inference over time.
A networked teleoperation system for a mobile robot with multiple viewpoints virtual scene

This paper presents a teleoperation system to control mobile robot remotely. The system architecture is based on network technology. To get a synthetical knowledge of the robot and its working environment, besides the real video feedback from the robot vision system, a multiple viewpoints virtual scene of the robot and its worksite is constructed. It can present images in first person and third person viewpoints. To complete a complex task, operators can conveniently select different viewpoints to monitor the robot or target for different task process. Multiple input devices such as keyboard, mouse and joystick are adopted to input the commands, and different operational modes are designed to control the robot in different task. Finally, the effectiveness of the teleoperation system is illustrated by experiments that the operator manipulates mobile robot.
A New GPS Dynamic Filter Algorithm Based on Stationary Wavelet Transformation

Through analyzing the properties of vehicle GPS navigation system signal’s observation gross error and random noise, this paper presents a new dynamic filter algorithm, which based on stationary wavelet transformation (SWT). Firstly, the algorithm decomposes the vehicle GPS navigation signal with stationary wavelet function. Then, the algorithm detects, eliminates and corrects the signal’s observation gross error at different resolution levels with statistic theory, and the signal’s random noise is de-noised at different resolution levels with improved soft-threshold de-noising method. Finally, the algorithm provides precise positioning information for the vehicle GPS navigation system through reconstructing the de-noised SWT coefficients. The simulation result shows that the algorithm is better than Kalman filter, and is available for the vehicle GPS navigation system.
A stochastic scattering particle swarm optimizer

The particle swarm optimization (PSO) algorithm is a swarm intelligence technique, which has exhibited good performance on finding optimal regions of complex search spaces. However, the basic PSO (bPSO) suffers from the premature convergence in multi-modal optimization. This is due to a decease of swarm diversity that leads to the global implosion and stagnation. It is an acceptable hypothesis that maintaining a high diversity produces a good effect on the search performance of the PSO algorithms. In this paper, we propose a novel optimizer, called the stochastic scattering particle swarm optimizer (SSPSO), which tries to overcome the premature convergence through scattering the swarm stochastically, with a new and simple diversity measure. The performance of the SSPSO is compared with the bPSO on a set of benchmark functions. Experimental results show that, the SSPSO not only prevents the premature convergence to a high degree, but also keeps a rapid convergence rate. Thus, it is clearly a better substitute for the bPSO and other repulsion-based PSO algorithms.
Context-Aware Entity Disambiguation in Text Using Markov Chains

In recent years, the amount of entities in large knowledge bases has been increasing rapidly. Such entities can help to bridge unstructured text with structured knowledge and thus be beneficial for many entity-centric applications. The key issue is to link entity mentions in text with entities in knowledge bases, where the main challenge lies in mention ambiguity. Many methods have been proposed to tackle this problem. However, most of the methods assume certain characteristics of the input mentions and documents, e.g., only named entities are considered. In this paper, we propose a context-aware approach to collective entity disambiguation of the input mentions in text with different characteristics in a consistent manner. We extensively evaluate the performance of our approach over 9 datasets and compare it with 14 state-of-the-art methods. Experimental results show that our approach outperforms the existing methods in most cases.
Analytical model of electromagnetic vibration of salient permanent magnet motors with time harmonics

In this paper, a new analytical model of electromagnetic vibration has been proposed to research the method of vibration and noise reduction. Vibration and acoustic noise characteristics of two typical motors at high speed are also measured and numerically analyzed. Moreover, the influence on the motor vibration characteristics exerted by current harmonics which are generated by the carriers at different frequencies are researched. The results have validated the good consistency among the electromagnetic vibration model, modal analysis and experiments.
DASE: Document-Assisted Symbolic Execution for Improving Automated Software Testing

We propose and implement a new approach, Document-Assisted Symbolic Execution (DASE), to improve automated test generation and bug detection. DASE leverages natural language processing techniques and heuristics to analyze program documentation to extract input constraints automatically. DASE then uses the input constraints to guide symbolic execution to focus on inputs that are semantically more important.We evaluated DASE on 88 programs from 5 mature real-world software suites: COREUTILS, FINDUTILS, GREP, BINUTILS, and ELFTOOLCHAIN. DASE detected 12 previously unknown bugs that symbolic execution without input constraints failed to detect, 6 of which have already been confirmed by the developers. In addition, DASE increases line coverage, branch coverage, and call coverage by 14.2 -- 120.3%, 2.3 -- 167.7%, and 16.9 -- 135.2% respectively, which are 6.0 -- 21.1 percentage points (pp), 1.6 -- 18.9 pp, and 2.8 -- 20.1 pp increases. The accuracies of input constraint extraction are 97.8 -- 100%.
A novel high-sensitivity cardiac multi-biomarkers detecting system based on microfluidic chip and GMR sensor

Giant magnetoresistance (GMR) is a quantum mechanical magnetoresistance effect observed in thin-film structures composed of alternating ferromagnetic and non-magnetic conductive layers. Today GMR has been used in various fields including detecting DNA hybridization and pathogenic microorganism[1], screening diagnostic biomarkers[2], detecting HBV genotypes[3], and so on. NT-proBNP is an established risk factor in patients with heart failure or coronary disease. cTnI is considered the standard biomarker for acute myocardial infarction(AMI). The combined detection of NT-proBNP and cTnI could improve the sensitivity and specificity in clinical diagnosis of myocardial injury.
A Novel High-Sensitivity Cardiac Multibiomarker Detection System Based on Microfluidic Chip and GMR Sensors

We have developed a novel cardiac multibiomarker detection system, wherein cardiac biomarkers NT-proBNP and cTnI could be detected simultaneously in 20 min. The lower limits of detection of NT-proBNP and cTnI were 0.33 and 1.43 pg/ml, respectively. Furthermore, based on a microfluidic chip and a giant magnetoresistance sensor, the detecting system was realized in a small platform to decrease the manufacturing cost and the difficulty of operation. In addition, owing to the usage of the superparamagnetic nanoparticles of suitable diameter and bovine serum albumin blocker in nanoparticles solution, the system achieved a high signal-to-noise ratio in the whole dynamic range. This magnetic immunoassay system can be adapted to detect a variety of clinically important biomolecules in human samples and provide accurate information to diagnose human diseases.
Channel Equalization and Interference Analysis for Uplink Narrowband Internet of Things (NB-IoT)

We derive the uplink system model for In-band and Guard-band narrowband Internet of Things (NB-IoT). The results reveal that the actual channel frequency response (CFR) is not a simple Fourier transform of the channel impulse response, due to sampling rate mismatch between the NB-IoT user and long term evolution (LTE) base station. Consequently, a new channel equalization algorithm is proposed based on the derived effective CFR. In addition, the interference is derived analytically to facilitate the co-existence of NB-IoT and LTE signals. This letter provides an example and guidance to support network slicing and service multiplexing in the physical layer.
ANFIS implementation in FPGA for power amplifier linearization with digital predistortion

This paper presents a hardware implementation of an adaptive neuro-fuzzy inference system (ANFIS) in FPGA for power amplifier linearization with digital predistortion. The proposed approach approximates the inverse AM/AM and AM/PM characteristic of power amplifiers (PA) with two equivalent ANFIS of a first-order Sugeno FIS. The parameters of the ANFIS are obtained by an offline training process with neural networks algorithms. The linearity performance of the power amplifier is improved significantly with this technique. Experimental results show that about 5 to 10 dB ACPR reduction could be achieved for 3.75 MHz 16-QAM signals.
An improved event processing approach for RFID stream data and its application

Radio frequency identification (RFID) technology has been widely used in various fields. How to deal with and make use of the data to serve for enterprises is a great challenge we are facing, and RFID event processing technology can help us solve the problem. In this paper, we will do an in-depth investigation on RFID event processing technology and test its performance in the application of SCM (Supply Chain Management). To the RFID simple event, an improved RETE algorithm will be proposed; to the complex event, a novel Petri Net approach will be adopted. The experiment is carried out in the scene of Beer Game, which demonstrates that RFID event processing technology can mitigate the effects of the Bullwhip in supply chain.
Characterization of low-dielectric-constant SiCON films grown by PECVD under different RF power

In this paper, we report the influence of RF power on carbon- and nitride-doped silicon oxide (SiCON) films deposited by PECVD using SiH<sub>4</sub>, N<sub>2</sub>O and C<sub>2</sub>F<sub>6</sub> precursors. The deposited films are characterized by means of FTIR and XPS, revealing the coexistence of both ring and network frameworks as well as Si-C, Si-N, C-N, C-H and Si-O bonds. The dielectric constant (k) and deposition rate of the SiCON film decrease with increasing the RF power. In the present experiment, a k value of 2.35 is achieved while retaining a low leakage current of 2.7×10<sup>-7</sup>A/cm<sup>2</sup> at 7.8MV/cm.
A wideband digital pre-distortion platform with 100 MHz instantaneous bandwidth for LTE-advanced applications

In this paper, a digital pre-distortion platform is designed for linearization of wideband power amplifier with nonlinearity and memory effect. The proposed platform consists of digital signal processing (DSP), field-programmable gate array (FPGA), analog to digital converter (ADC) and digital to analog converter (DAC) which are all operating under a high speed of 400MHz. The platform covers a frequency band from 1.9 GHz to 3.5 GHz and supports a bandwidth up to 100 MHz PTE-Advanced application. Experimental validation is carried out on a 1.95 GHz Gallium-Nitride(GaN) Doherty power amplifier (DPA) driven by a LTE-Advanced signal with bandwidth of 100 MHz and peak-to-average power ratio(PARP) of 9.8 dB. The testing DPD results show that adjacent channel leakage ratio (ACLR) reaches -50 dBc with about 15 dB improvement.
A Photovoltaic UV Sensor With a Ferroelectric Thin Film on Transparent Substrate

A photovoltaic ultraviolet (UV) sensor is designed with a unique structure comprising of an in-plane polarized ferroelectric lead lanthanum zirconate titanate (PLZT) thin film on a transparent silica substrate and with an interdigital electrodes on the top surface. Both the experimental measurements and theoretical analyses showed that the UV sensor exhibited significantly enhanced responses with the incident UV irradiation input from the silica substrate in comparison with that from the top surface of the PLZT film. The proposed device configuration leads to a cost-effective scratch- and moisture-proof UV sensor with a flip-chip package, which promises great robustness for UV monitoring in harsh conditions.