nils-herrmann/clean_scirepeval huggingface dataset:
An Efficient User-to-User Authentication Scheme in Peer-to-Peer System

In peer-to-peer environment, information is directly exchanged between nodes instead of forwarding by a central server, hence user-to-user authentication becomes a critical security issue in such environment. Existing solutions are based on public-key cryptosystem. The main concerns in a public-key cryptosystem include authenticity of the public key and lack of efficiency. A trusted third party is also involved in a public-key environment. This paper proposed an efficient one-way hash function based user-to-user authentication scheme with smart card in peer-to-peer system. In the proposed scheme, the system and peers do not have to maintain verification tables, and a trusted third party is not needed in the run time. The proposed scheme achieves mutual authentication at very low computational cost, but also provides good security strength.
3D Adjacency: A Communication-Aware Online Scheduling Algorithm for 2D Partially Reconfigurable Devices

One main issue of partial reconfigurable devices to be solved is the hardware task scheduling and placement. This paper presents an online 3D maximum adjacency surface (3DMAS) algorithm taking data communication between tasks into consideration. This algorithm using 3D adjacency area as cost function aims at reducing the distance between dependency tasks while scheduling. The experimental results show that 3DMAS affords a considerable decrease in communication cost and a better placement.
Dynamic Neural Mechanisms for Recognizing Spike Trains

Dynamic neural networks are designed to discuss how the dynamic mechanisms in the neurons and synapses work in recognizing interspike intervals (ISIs). The threshold integration of post-synaptic membrane potentials, the refractory period of neurons, together with the spike-time-dependent plasticity (STDP) learning rule are discussed. Based on these dynamic mechanisms, the input inter-spike interval sequences are decomposed into isolated spikes. The synaptic delay times modulated by STDP learning rule is the key mechanism in the ISIs recognition, based on which the ISIs are learned and saved in the delay times. After learning, the neural networks could recognize whether different input sequences include the same consecutive ISIs.
An Empirical Research on the Competency Model of Professional Managers in Tourism Hotel Industry

The objectiveness of this research is to establish and make an empirical analysis of a five factor model of the competency of professional managers in tourism hotel industry, which namely, professional ability, administrative skills, innovation quality, morality accomplishment, and knowledge experience. Forty six hotels with different stars in different cities are chosen to be the objects of experimental research and a sample data of 446 actual members is collected. With SPSS15.0 and AMOS7.0, the sample data are used for exploratory factor analysis and confirmatory factor analysis.
Clutter-Cancellation-Based Channel Phase Bias Estimation Algorithm for Spaceborne Multichannel High-Resolution and Wide-Swath SAR

When combined with digital beam-forming (DBF) techniques, multichannel synthetic aperture radar (SAR) systems can achieve high-resolution and wide-swath SAR imaging. However, inevitable channel biases will degrade the performance of DBF in practice. To address this problem, a novel channel phase bias estimation algorithm is proposed in this letter. Theoretical analysis reveals that the signal of the first channel, which is considered as the reference channel, can be reconstructed from the signals of other channels, regardless of noise and signals outside the Doppler bandwidth. In the presence of phase biases, there is a reconstruction error after the cancellation by subtracting this reconstructed signal from the original signal. However, by minimizing the reconstruction error, the channel phase biases can be precisely estimated. The effectiveness of the proposed algorithm is validated by the experimental results.
Coupling Characteristics of Selective-Infiltration-Based Locally Tapered Photonic Crystal Fiber

We have proposed and experimentally demonstrated a novel compound structure based on selectively infiltrating of a local tapered photonic crystal fiber (TPCF). Theoretical and experimental investigations indicate that tapering photonic crystal fiber (PCF) can change the material refractive index (RI) of silica core, and the RI change can be revealed and proved to influence the effective RI curve of the PCF core mode, which results in the shifting of the phase matching point. Moreover, strong coupling can occur in the infiltrated TPCF due to the increased overlap integral of the involved coupled modes. As application, the proposed configuration based on TPCF has huge potential use in microfluidic, RI, and dual-parameter sensing with high sensitivity, such as ultrahigh strain sensitivity of –139.78 nm/N (–167.74 pm/μϵ).
Application of Rough Sets and Grey Clustering in Frequency of Wireless Railway Systems

Frequency planning of wireless system is the ubiquitous and urgent key problem due to limited frequency spectrum. This paper presents a frequency planning method according to the characteristics of GSM-R. Rough Sets (RS) theory and Grey Clustering (GC) theory are applied in frequency planning and the factors that affect on frequency planning and their proper thresholds are discussed. Then, the optimal plan is given by means of the GC assessment. Moreover, we compare different frequency planning methods by simulations. Finally, the derivation and simulation results show that the frequency planning based on RS and GC theory is more precise than other algorithms.
A novel EMI filter design method for switching power supplies

This work introduces an improved and simplified method to design electromagnetic interference (EMI) filters for both dc-dc and ac-dc switching power supplies. This method uses the practical approach of measuring the power supply noise spectrum and using the data to calculate the maximum possible magnitude and minimum possible magnitude of the differential mode and common mode noise impedances. The noise impedance magnitude information aids the design of the EMI filter. Phase information for the noise impedance is not required. In addition, information about the topology and control method of the power supply is not needed. This method solves the limitations of existing EMI filter design methods, which are either too complicated to use, or are based on ideal cases that neglect the noise impedance. The analysis and experimental results show that this method can guarantee that the required attenuation can be achieved, especially at low frequencies.
An Extended CMOS ISFET Model Incorporating the Physical Design Geometry and the Effects on Performance and Offset Variation

This paper presents an extended model for the CMOS-based ion-sensitive field-effect transistor, incorporating design parameters associated with the physical geometry of the device. This can, for the first time, provide a good match between calculated and measured characteristics by taking into account the effects of nonidealities such as threshold voltage variation and sensor noise. The model is evaluated through a number of devices with varying design parameters (chemical sensing area and MOSFET dimensions) fabricated in a commercially available 0.35-μm CMOS technology. Threshold voltage, subthreshold slope, chemical sensitivity, drift, and noise were measured and compared with the simulated results. The first- and second-order effects are analyzed in detail, and it is shown that the sensors' performance was in agreement with the proposed model.
Design of a high power MEMS relay with zero voltage switching and isolated power and signal transfer

This paper proposes a MEMS relay circuit by paralleling an auxiliary MOSFET with a MEMS switch. During the turn-on and turn-off transition, MOSFET is turned on at first to guarantee the switching voltage of MEMS switch is almost zero; for normal switch-on condition the MEMS switch with low on-resistance is turned on and the MOSFET is turned off. To meet the requirement of isolation between control side and power side, a transformer is designed in the control circuit and this single transformer achieves both power transfer and on-off control signal transfer. Thus the size of MEMS relay is reduced. Finally, a prototype was built and it validates the design of MEMS relay structure and single transformer circuit. Superior switching performance, fast response, low on-resistance and small size are achieved by the MEMS relay.
Edge-content based community detection algorithm on email network

As email playing an increasingly important role in the online world, analyzing and mining on email communication network draw more and more attention, in which community detection is one of the most key technologies and applications. Based on the intuition that the edge topic is more focused than the node topic in a short period, this paper proposes an edge-content based email network community detection using clustering algorithm. First extract the related emails on the edges, and feature terms are extracted from those emails in combination with mail body and subject to label the edge-content. Express the edges of a network with Vector Space Model (VSM), and then cluster the edges according to their contents by an advanced k-means algorithm to obtain community. Afterwards the obtained communities are described and evaluated. Experiments show that the proposed method is promising.
An illumination-robust algorithm based on visual background extractor for moving object detection

Aiming at the problem that ViBe (Visual Background extractor) algorithm is sensitive to illumination variation, an improved ViBe algorithm is proposed in this paper. First, a brightness reference image is build, which represents the brightness level of background. Second, adjust the brightness of current frame, which is changed by illumination variation, back to the reference images brightness level adaptively by using image intensity normalization method based on histogram statistics. With this method, the influence of illumination variation can be basically eliminated. At last, a morphology postprocessing is used to filter the results of binary image, remove the noise in the background, fill small voids within the object, and suppress the influence of dynamic background. The experimental results show that compared with several existing algorithms, the proposed algorithm has higher detection accuracy and is robust for illumination variation.
A distributed localization and synchronization algorithm for full-duplex transmission systems

The emergence of full-duplex (FD) communication technology can enable the efficient network localization and synchronization. In this paper, we develop a distributed algorithm for localization and synchronization using FD two-frame transmission. Based on the sparse structure of the wireless channels, arrival times of different signals are estimated by an iteration method. Then, the positions and clock offsets of agents are determined by the weighted least squares and semidefinite programming (SDP) method. Our simulation results demonstrate the effectiveness and performance of the distributed algorithm in the network localization and synchronization.
A systematic method to synthesize new transformerless full-bridge grid-tied inverters

Many inverter topologies have been proposed to eliminate the leakage current of transformerless Full Bridge Grid-Tied photovoltaic (PV) inverters. These include implementations such as the H5, H6, and HERIC topologies, among others. In this paper, a new full bridge topology synthesis method, called the MN synthesis method, is proposed. The MN method introduces two criteria that can be used to synthesize all of the possible topologies, including the existing topologies as well as new simplified topologies. This method concludes that there are only 15 simplified topologies available. Most simplified topologies from MN method have been verified by existing papers and patents.
CrowdSafe: Detecting extreme driving behaviors based on mobile crowdsensing

With the popularity of vehicles, high traffic accident frequency has become a serious social problem in many countries. Thereby, it is of great value to detect driving behaviors and forecast dangerous situations. Specifically, with the recent surge of smart phones, there have been researchers who attempt to deal with this issue based on smart phone sensing. However, these existing studies have neither considered the phone's relative positions in the vehicle nor the phone's placements. In this paper, we propose CrowdSafe, which leverages the aggregated power of passengers to enhance the detection of extreme driving behaviors in public transports. First, we propose a multi-sensor fusion approach that can automatically locate passengers in a vehicle. Second, we investigate the impact of different in-vehicle locations on the performance for different extreme driving behavior detection. Finally, group decision making strategies based on the Bayesian voting theory is proposed to deal with the situations when there are conflicts among the reports from different passengers. Experimental results show that passenger positions and ways of carrying mobile phones have significant influence on the detection of extreme driving behaviors, and the improved voting method can achieve an accuracy of about 90%.
Anomalous Negative Bias Temperature Instability Degradation Induced by Source/Drain Bias in Nanoscale PMOS Devices

The effect of source/drain (S/D) bias on the negative bias temperature instability (NBTI) of pMOSFETs is studied. The anomalously enhanced NBTI under S/D bias conditions is observed, which cannot be explained by the conventional reaction-diffusion model. A new mechanism based on the enhanced interfacial dissociation of equivSi-H bonds induced by the energetic holes (the hole energy Eh is higher than the reaction activation energy Ea of equivSi-H bond dissociation) is proposed to address the observed degradation behaviors. Monte Carlo simulations are used to identify the validity of the new mechanism.
Digital adaptive Current Source Driver for interleaving Boost PFC converters under Critical Conduction Mode

Digital adaptive Current Source Drivers (CSDs) are proposed for interleaving Boost PFC converters. The adaptive drive current is achieved for the CSDs to optimize the switching loss and gate loss according to different load conditions in a wide load range. Compared to the adaptive CSD with the linear regulator, the digital adaptive control is able to eliminate the additional loss and cost introduced by the linear regulator. At the same time, the proposed digital CSD is compatible with digital control technique. The presented digital CSDs are applied to the interleaving parallel Boost PFC converters under Critical Conduction Mode (CRM) to reduce high turn-off and gate drive loss. A 110-VAC input, 380-V/ 400-W output interleaving Boost PFC converters were built to verify the functionality and advantages of the digital CSD.
Burst Spike Trains Recognition Based on the Dynamic Properties of Hodgkin-Huxley Neurons and Synapses

The functions of neural system, such as learning, recognition and memory, are the emergences from the elementary dynamic mechanisms.To discuss how the dynamic mechanisms in the neurons and synapses work in the function of recognition, a dynamic neural circuit is designed. In the neural circuit, the information is expressed as the inter-spike intervals of the spike trains. The neural circuit with 5 neurons can recognize the inter-spike intervals in 5-15ms. A group of the neural circuits with 6 neurons recognize a spike train composed of three spikes. The dynamic neural mechanisms in the recognition processes are analyzed. The dynamic properties of the Hodgkin-Huxley neurons are the mechanism of the spike trains decomposition. Based on the dynamic synaptic transmission mechanisms, the synaptic delay times are diverse, which is the key mechanism in the inter-spike intervals recognition. The neural circuits in the group connect variously that every neuron can join in different circuits to recognize different inputs, which increases the information capacity of the neural circuit group.A neural circuit is designed. The input burst spike trains are decomposed by the selectively responding properties of neurons and the intra-burst periods are learned by the neurons. Then the synaptic delay times are modulated by STDP learning rule, and the inter-spike periods are learned and saved in the delay times. After learning, the specifical neural connection structures are formed to the certain input spike trains and the recognition is finished.
An MAODV-Based Energy Saving Multicast Routing Algorithm

The wireless ad hoc networks (WANET) is an open system that is constituted by fix or mobile nodes. In WANET, each node can be a router or a host. Considering that most nodes may use battery as its energy, it is necessary to improve on energy-saving method. Based on the MAODV protocol, we bring forward a new method called PPEF that uses both hops and energy consumption level of each node together for multicast routing. The simulation results show that our approach is effective.
Design of vineyard production monitoring system based on wireless sensor networks

Aiming at low management automation level, heavy workload and other problems that exist in traditional vineyard production, a vineyard production monitoring system is designed based on wireless sensor network technology. The system includes 54 sensor nodes, 3 cluster-head nodes, a sink node and monitoring center. It is free to customize automatic acquisition, processing, transmission, storage of soil moisture rate that from three soil layers separately buried apart from surface 0–20, 20–40, and 40–60 cm, the change of soil temperature and illumination intensity. Each node employs JenOS operation system, and the communication between nodes follows ZigBee protocol. Comprehensively considering the cost, energy consumption, usability and other factors, this system selects the TP-ST series sensors. Experiments of data package transmission rate in budding leafing stage and fruit rapid-expanding stage are taken. Six out of ten sensor nodes have the data package transmission rate above 90%, two sensor nodes below 35%. The reason is that the energy consumption of one solar energy power circuit is excessive, and the other node is deployed where the grape trellis blocking is serious. In addition, the data package transmission rate of fruit rapid-expanding stage is generally lower than that of grape budding leafing stage. This phenomenon shows that the density of branch and fruit has certain influence on the transmission of wireless signal.
Adaptive Fuzzy Asymptotic Control of MIMO Systems With Unknown Input Coefficients Via a Robust Nussbaum Gain-Based Approach

This paper proposes an adaptive fuzzy asymptotic control method for multiple input multiple output (MIMO) nonlinear systems with unknown input coefficients, with a focus on handling unknown input nonlinearities and control directions. For all the existing Nussbaum gain-based approaches, it is difficult to investigate unknown input coefficients problem since multiple time-varying coefficients and disturbances coexist and should be simultaneously tackled in the stability analysis. To overcome the above difficulty, we propose a robust Nussbaum gain-based approach for the adaptive fuzzy asymptotic control of MIMO nonlinear systems. Benefiting from the proposed Nussbaum gain-based approach, bounded disturbances including unmodeled system dynamics and universal approximation errors are handled. Furthermore, the proposed approach helps extend the bounded fuzzy control result to the asymptotic convergence. Hence, both the control robustness and control accuracy are prompted within the frame of the developed Nussbaum gain approach. Finally, a simulation example is carried out to illustrate the effectiveness of the proposed control method.
A hierarchical active balancing architecture for Li-ion batteries

This paper proposes a hierarchical battery balancing architecture for the series connected lithium-ion batteries. The battery cells are grouped into different packs and the bottom layer is the Adjacent Cell-to-Cell structure consisting of the packs. The top layer is connected to different packs and can deliver the energy from one pack to any other pack bi-directionally, leading to high flexibility. A multi-directional multi-port converter is proposed to serve as the top layer. With the hierarchical architecture, the balanced energy transfer of the cells in different packs can be decoupled, which avoid the repeated charging and discharging during the balancing process. This is beneficial for lengthening the battery lifetime and increasing the State-of-Health (SOH). Moreover, the proposed architecture can lower the current rating of the balancing circuits, which helps decrease the required cost and improve the system efficiency. The experimental results verified the benefits of the proposed architecture.
A kind of multivariable PID design method for chaos system - using H/sub /spl infin// loop shaping design procedure

The problem of stable control for chaotic nonlinear system is studied. The H/sub /spl infin// controller is designed by H/sub /spl infin// loop shaping theory, and provides the method for selecting the parameters of compensator. Because the H/sub /spl infin// controller is a high-order controller, it is difficult to realize, we simplify it to a multivariable PID controller. Tested by controlling Lorenz system and the simulation results show the validity of the scheme.
A New ZVS Non-Isolated Full-Bridge Voltage Regulator Module with Gate Energy Recovery

In this paper, a novel self-driven zero-voltage-switching (ZVS) non-isolated full bridge (FB) converter is presented for 12V input VRM application. Existing multiphase buck controller and buck driver can be directly used in the proposed converter. The advantages of the proposed converter are: 1) duty cycle extension; 2) significant switching losses reduction due to ZVS of all the control MOSFETs; 3) reduced reverse recovery loss and lower voltage rating synchronous rectifier (SR) MOSFET with lower RDS(on); 4) high drive voltage to reduce RDS(on) and the conduction losses of SRs due to gate energy recovery capability; 5) reduced body diode conduction and no external drive IC chips with dead time control needed for SRs due to the inherent current source gate drive circuit structure. The experimental results verify the principle of operation and significant efficiency improvement. At 12V input, 1.3V output and 1MHz switching frequency, the proposed VRM improves the efficiency from 80.7% using the buck converter to 83.6% at 50A, and from 77.9% using the buck converter to 80.5% at 60A.
Document copy detection based on kernel method

We present semantic sequence kernel (SSK) to detect document plagiarism, which is derived from string kernel (SK) and word sequence kernel (WSK). SSK first finds out semantic sequences in documents, and then it uses a kernel function to calculate their similarity. SK and WSK only calculate the gap between the first word and the last one. SSK takes into account each common word's position information. We believe SSK contains both local and global information so that it makes a great progress in small partial plagiarism detection. We compare SSK with relative frequency model and semantic sequence model, which is a word frequency based model. The results show that SSK is excellent on nonrewording corpus. It is also valid on rewording corpus with some impairment on the performance.