nils-herrmann/clean_scirepeval huggingface dataset:
A 60GHz quadrature LO synthesizer with 1.2° phase error and over 17% tuning range for IEEE 802.11ad applications

This paper proposes a 60GHz quadrature LO synthesizer with wide tuning range and low phase noise performance. The synthesizer is implemented by a 20GHz quadrature PLL and a 60GHz wideband tripler. The 20GHz PLL achieves an excellent phase noise performance of -107dBc/Hz@1MHz offset while showing a tuning range of over 17%. A 4-bit switched capacitor array is used to cover the four prescribed channels of the IEEE 802.11ad standard. The proposed 60GHz tripler mixes the fundamental frequency and second-order harmonic of the 20GHz PLL output. The total phase noise is -95dBc/Hz@1MHz offset at 60GHz. A buffer is used to drive the 50Ω load off-chip, achieving a 0dBm output power. The LO synthesizer is designed by 90nm CMOS process with 1.2V supply. The total power consumption of the PLL is 39mW while the tripler only consumes 12.6mW.
Data synchronization algorithm for IoT gateway and platform

Data synchronization is widely used in many fields such as database, cloud computing and distributed system. However, for Internet of Things (IoT) system, the existing synchronization algorithms are not very efficient because the data in IoT system have different characteristic like real-time and mutability. To resolve the problem, this paper proposes a new data synchronization algorithm for IoT system using timestamp and bitmap, which can improve the efficiency of network transmission in data synchronization and apply to IoT system better.
An associative saliency segmentation method for infrared targets

Automatic infrared (IR) target segmentation plays an important role in IR image analysis. Recent works have shown that exploiting visual attention model can improve target segmentation performance in visible images. However, when directly applied to IR images, those methods cannot guarantee the effectiveness due to the low contrast between targets and background, high noise, etc. To address above problem, a novel associative saliency-based visual attention model for IR images is proposed in this paper. First, an IR image is decomposed into assemble of homogeneous regions. With those regions, saliency based on region and edge contrast is constructed, respectively. Then associative saliency, generated from those two kinds of saliency, is used to extract IR target from background. The superiority of the proposed method is examined and demonstrated through a large number of the experiments using IR images.
Development and realization of digitalized Campus based on Mifare-1 Radio Frequency card

Aiming at the work principle of the Mifare-1 Radio Frequency card, combining with the specific condition of Henan Mechanic and Electric Engineering College, the paper applies the intelligent Mifare-1 Radio Frequency card into Campus' Multi-function Card System and achieves the connection with campus card system using interface subsystems. The practices show that the application of this system is convenient for students.
Association Classification Based on Compactness of Rules

Associative classification has high classification accuracy and strong flexibility. However, it still suffers from overfitting since the classification rules satisfied both minimum support and minimum confidence are returned as strong association rules back to the classifier. In this paper, we propose a new association classification method based on compactness of rules, it extends Apriori Algorithm¿which considers the interestingness, importance, overlapping relationships among rules. At last, experimental results shows that the algorithm has better classification accuracy in comparison with CBA and CMAR are highly comprehensible and scalable.
Building a Self-Adjusted Map for Mobile Robot Navigation

An accurate map is essential to autonomous mobile robots. Two of the most popular map types are Occupancy Grid Map (OGM) and Topological Map (TM). However, the OGM is inefficient since it requires a large amount of memory to represent the environment. The TM, on the other hand, is difficult to apply to accurate navigation and location because it lacks environmental information. In this paper, a self-adjusted mapping method is proposed with integrating the two map types. It navigates the robot more efficiently than an OGM, and more accurately than a TM. With this new map type, a reliable path could be obtained in real-time. Simulation experiments validate its efficiency and reliability.
Control Scheme for Stable Bilateral Teleoperation with Time Delay

In teleoperation system, the tracking ability is reduced due to the existence of time delay in communication channel, as communication delay can degrade the performance and destabilize the system. In this paper, a particular control scheme, the quasi-linear minimal order feedback controller have been proposed to control bilateral teleoperation, which is subjected to communication time delay. The designed controller not only guarantees fast tracking properties, but also provides a smooth approximation of possibly discontinuous reference trajectory. The goal of our approach is to make both the master and slave manipulators stable and retaining passivity of communication channel, so that stability of overall telerobotic system with any communication delay can be ensured. The method stated in the paper is helpful in practical application in the design of bilateral teleoperation with communication delay. Simulation results show the validity of the proposed control scheme with one DOF master/slave system.
Discriminative learning of iteration-wise priors for blind deconvolution

The maximum a posterior (MAP)-based blind deconvolution framework generally involves two stages: blur kernel estimation and non-blind restoration. For blur kernel estimation, sharp edge prediction and carefully designed image priors are vital to the success of MAP. In this paper, we propose a blind deconvolution framework together with iteration specific priors for better blur kernel estimation. The family of hyper-Laplacian (Pr(d) ∝ e-∥d∥pp/λ) is adopted for modeling iteration-wise priors of image gra- dients, where each iteration has its own model parameters {λ(t), p(t)}. To avoid heavy parameter tuning, all iteration-wise model parameters can be learned using our principled discriminative learning model from a training set, and can be directly applied to other dataset and real blurry images. Interestingly, with the generalized shrinkage / thresholding operator, negative p value (p <;0) is allowable and we find that it contributes more in estimating the coarse shape of blur kernel. Experimental results on synthetic and real world images demonstrate that our method achieves better deblurring results than the existing gradient prior-based methods. Compared with the state-of-the-art patch prior-based method, our method is competitive in restoration results but is much more efficient.
Development of Foundation Pit Leakage Detector based on Flow-field Fitting Method

Flow-field Fitting Method is a brand-new physical detection technology which is put forward by Academician He Jisan of Central South University.This paper gives a detailed introduction to Foundation Pit Leakage Detector based on Flow-field Fitting Method,which mainly includes transmitter,receiver and host computer control software. The transmitter transmits 3-12V adjustable amplitude bipolar square wave, the receiver uses FPGA + MCU frame.After amplification and acquisition, the signal is processed by fast fourier transform (FFT) in FPGA.The result is stored in FPGA provisionally and finally fetched by MCU,effective data are selected by Zigbee wireless communication system to upload to the host computer. By using the drawing software Surfer to draw potential contour map of harmonics under every frequency. The location of leakage could be ascertain through the distribution of potential. Through laboratory simulation and building field measurement, the reliability and stability of Foundation Pit Leakage Detector are verified.
Attitude estimation of space targets by extracting line features from ISAR image sequences

In this letter, an attitude estimation method is presented for space targets by using an inverse synthetic aperture radar (ISAR) image sequence. The line structures, like the boundaries of planar payloads, are extracted from the ISAR image sequence and associated from frame to frame. With the accommodation of the radar looking angle information from the trajectory, the threedimensional attitude of the target is achieved by solving an object-to-Range-Doppler (RD) projection optimization. Detailed image processing is provided for line structure extraction, orientation estimation and association. Experiment confirms the effectiveness of the proposal.
Binary Software Vulnerability Analysis Based on Bidirectional-Slicing

Tradition reversing engineering technology is widely used to find security vulnerabilities of binary programs. However, it calls for human participation and relies on the analyzers' experience. In this paper, we propose a fault localization method based on bidirectional-slicing technology to help find the codes that cause the exception. This method develops novel optimizations on the traditional dynamic slicing and can obtain the key instruction sequences that lead to the exception efficiently. This method is proved to be efficient by both known and unknown vulnerabilities.
Brain potentials reveal audiovisual integration in bilinguals on arithmetic fact retrieval

There is an increasing number of empirical evidence claiming that internal finger-based number representations affect numerical and arithmetical processing in both children and adults. However, relatively little is known about the online integration between explicit finger-based number representations and verbal number words during calculation. To explore such integration in Chinese monolinguals and Chinese-Spanish bilinguals, we designed an arithmetical correctness judgment paradigm with multimodal inputs where finger representations were either in symbolic form or in iconic form. Data from event-related potentials revealed that in both groups, symbolic finger representations were tightly attached to Chinese during the access to arithmetic facts. Furthermore, iconic finger representations were integrated into both Chinese and Spanish in bilinguals, thus serving the retrieval of arithmetic facts. The present results provide complementary evidence to the multisensory integration in the context of numerical cognition.
Detection of meteor burst and its channel modeling simulation

Combining the existing theories with the limited measurement data, we propose a method of determining whether a meteor burst exists or not and getting the corresponding distribution rule of meteor burst arriving interval, and simulate the whole process with C++. We judge the type of the meteor and give statistic results of the times of meteor, and get the curve of the received signal power. Based on the above work, we set up a channel model using the measurement data. The probability density function of the received signal power generated by our model is similar to that of the actual measurement data.
A security assessment scheme for interdependent cyber-physical power systems

A security assessment scheme for interdependent cyber-physical power systems is proposed. The focus of the scheme is to assess the impact of node failures in the communication network on the total power system. A contingency set is formed by failures of each node in the communication network, which is ranked according to the node importance. Two mechanisms to trigger cascading failures of the power network are considered including re-routing of power flow and hidden failures of protection following the initial random event. After the contingency set is enumerated, the N-1 security assessment for the interdependent cyber-physical power system is completed. The impact of each contingency is measured by the resulting load loss of the power system. Simulation results of New England 10-machine 39-bus test system demonstrate the effectiveness of the proposed scheme.
Data Independent Method of Constructing Distributed LSH for Large-Scale Dynamic High-Dimensional Indexing

Constructing effective and efficient indexes for explosive growing multimedia data is a very challenging problem. To solve the problem, Haghani et al. provide a distributed similarity search method in high dimensions using Locality Sensitive Hashing. However, their method needs to estimate a global parameter on the whole dataset beforehand. It is impractical for a large-scale dynamical dataset. This paper proposes a novel constructing method of distributed LSH which does not need any priori knowledge about the dataset. Through generating the hash function with consistent output distribution, we get a data independent predicting model in theory which can guarantee a well load balance even if the dataset dynamically changes. Furthermore, we modify the query algorithm of the basic LSH to make the proposed model more practical. The experimental results on two open large-scale high-dimensional datasets show that the proposed method is more robust, scalable and practical than state-of-the-art.
Design of a Cigarette Sorting System Based on RFID Technology

This paper presents a design method to solve the problems of high failure rate and sorting inefficience in the current cigarette sorting system by integrating RFID technology with CAN BUS. Based on the features of high speed of data transmission, real-time and high reliability, CAN BUS intelligent node is designed. RFID technology enhances the speed and efficiency of cigarette identification. Meanwhile, using the LCD touch-screen and MCGS configuration software, the HMI operation is promoted and the visualization of monitoring processing can also be accomplished.
Analysis of multipath rejection performance in GNSS receiver using direct RF sampling technology

Multipath rejection performance is more and more important to modern GNSS receiver. Direct RF sampling technique is increasingly applied to GNSS receiver. Many researches have been focused on advantage of this new technology. However, analysis of multipath rejection performance is rare. In this paper, multipath rejection performance of GNSS receiver when using direct RF sampling technology is discussed. It is shown the performance could be highly enhanced with help of increased bandwidth by using direct RF sampling technology, especially referring to new GNSS signal based on BOC modulation.
Detection of ECG characteristic points using Biorthogonal Spline Wavelet

An algorithm based on Biorthogonal Spline Wavelet is developed for detecting ECG characters points. In the algorithm, the Biorthogonal Spline Wavelet Transform of the ECG signal is first calculated using Mallat Algorithm. And then the R-peak is located by finding the best modulus maximum pair of the wavelet transform in the scale of 23. A more robust method to find the modulus maximum pair is put forward in this paper. The methods finding the onsets and offsets of QRS complexes, P and T waves are also provided. The detection rate of QRS complexes for the algorithm is above 99.7% for MIT/BIH database and the processing time is considerably little.
A Linearized 2–3.5 GHz Highly Efficient Harmonic-Tuned Power Amplifier Exploiting Stepped-Impedance Filtering Matching Network

This letter presents the analysis, implementation and experimental results of a broadband highly efficient power amplifier (PA) using harmonic-tuned method for long-term evolution (LTE)-advanced application. Load-pull simulation has been employed to obtain the optimal load impedances, especially the second harmonic impedances, for high efficiency and output power over wide bandwidth. A stepped-impedance low-pass matching network was then designed to achieve the desired impedance transformation. Experimental results show that the PA achieves 64%-76% efficiency and higher than 40 dBm output power over the frequency band from 2 to 3.5 GHz. When driven by a 100 MHz LTE-advanced signal at an average output power of 33.5 dBm, the average efficiency of 33.8%, 34.9%, and 37.8% was measured at 2.15, 2.55, and 3.45 GHz, respectively. The corresponding adjacent channel leakage ratio can be linearized to about -48 dBc by using digital pre-distortion technique.
A frequency estimation algorithm based on spectrum correlation of multi-section sinusoids with the known frequency-ratio

Based on spectrum correlation of Multi-section Sinusoids with the Known Frequency-Ratio (hereinafter referred as MSKFR), a frequency estimation algorithm was proposed. This algorithm aims at improving frequency estimation of the short sinusoid at low Signal-to-Noise Ratio(SNR), and extending the applicable range of the multi-section signals fusion method. Firstly, an easy way to get MSKFR in application is introduced. Secondly, the frequency-ratio amend matrix is created to make spectra of MSKFR almost as the same as spectra of Multi-section Co-frequency Sinusoids (hereinafter referred as MCS). Thirdly, through weighted-accumulating spectra of MSKFR by the weighted factor, Optimization Weighted-Accumulation(OW-A) spectrum is gained. Fourthly, the correlation spectrum is constructed by correlation OW-A spectrum and the accumulation spectrum of MSKFR. Lastly, precise frequency estimation is obtained through spectral peak searching of the correlation spectrum. Simulation results demonstrate the superior performance of the proposed algorithm.
Avoidance of falling and collision for a stair-cleaning robot

Although various stair climbing or cleaning robots have been proposed and developed, few of them can move on the tread to do cleaning. Hence, the avoidance of falling and collision for a stair-cleaning robot has not been thoroughly solved. In this paper, based on our newly developed stair-cleaning robot, several methods are proposed or introduced to solve three kinds of problems concerning the avoidance of falling and collision. The proposed methods solve the problem of no falling before and when the robot is climbing. The proposed methods can assure no falling and few slight collisions when the robot is moving on the tread. A new turning approach is proposed and solves the problem of successful turning on the tread of the stairs for a stair-cleaning robot. Experimental results show that our methods are effective and stable.
Cryptanalysis of a certificateless encryption scheme

Certificateless public key cryptography was introduced to address the heavy certificate management in traditional public key cryptography and the key escrow problem in identity-based public key cryptography. Two types of adversaries are considered in certificateless public key cryptography: Type I adversary (outsider) and Type II Adversary (honest-but-curious and/or malicious-but-passive key generation center). A secure certificateless encryption (CLE) scheme must be secure against both types of adversaries. In this paper, we illustrate a recently proposed threshold CLE scheme is insecure against Type I adversaries.
A 2.15–6.18 GHz transformer-based dual-mode LC-VCO with current-reuse technology

A dual-mode ultra-wideband VCO designed in a current-reused configuration is presented. By changing the coupling mode of the transformer tank, an ultra-wide frequency tuning range is achieved, while the current-reused topology is also incorporated to further lower the dc power consumption. Optimized in 90-nm CMOS technology, the proposed VCO attains a tuning range of 96.8% from 2.15 to 6.18 GHz, while consuming 3.8-4.5 mA of current from a 1.2 V supply. The phase noise at 1 MHz offset is from -124.7 dBc/Hz to -116.3 dBc/Hz over the entire frequency tuning range, which corresponds to a FoMT of between -201 and -204 dBc/Hz.
Activity Invariant Sets and Exponentially Stable Attractors of Linear Threshold Discrete-Time Recurrent Neural Networks

This technical note proposes to study the activity invariant sets and exponentially stable attractors of linear threshold discrete-time recurrent neural networks. The concept of activity invariant sets deeply describes the property of an invariant set by that the activity of some neurons keeps invariant all the time. Conditions are obtained for locating activity invariant sets. Under some conditions, it shows that an activity invariant set can have one equilibrium point which attracts exponentially all trajectories starting in the set. Since the attractors are located in activity invariant sets, each attractor has binary pattern and also carries analog information. Such results can provide new perspective to apply attractor networks for applications such as group winner-take-all, associative memory, etc.
Compensation for the NsRCM and Phase Error After Polar Format Resampling for Airborne Spotlight SAR Raw Data of High Resolution

When the range migration caused by motion error exceeds the range cell resolution, the performance of a conventional phase autofocus approach degrades. In this paper, a new adaptive motion compensation (MoCo) algorithm with the removal of the migration that is nonsystematic has been developed for airborne spotlight synthetic aperture radar (SAR) imagery with high resolution. In the algorithm, the relationship between nonsystematic range cell migration (NsRCM) and phase error was first explicitly revealed after the polar format algorithm resampling. The NsRCM could be readily calculated by coarse but reliable phase error estimation. Subsequently, the NsRCM and the bulk of the azimuth phase error were corrected. After the removal of the NsRCM, degradation of the conventional phase autofocus resulting from sidelobe increase as well as mainlobe broadening was avoided. Finally, a fine MoCo procedure was performed to remove the residual azimuth phase error satisfactorily. Through the analysis of the airborne spotlight SAR raw data with high-resolution and wide-swath illumination, a well-focused imagery was obtained. Quantitative assessment of the image quality was satisfactory. The MoCo algorithm was validated.
Applications of FESS in power system muti-mode oscillations

Applications of single Flywheel Energy Storage System (FESS) to suppress power system multi-mode oscillations is presented in the paper. Based on independent active power and reactive power control loops and damping torque analysis, the feasibility of damping power system multi-mode oscillations using single FESS is studied. Based on modal analysis, the effective control loops are determined to install auxiliary damping controllers in FESS and the effective feedback signals to select to suppress each oscillation mode. And the eigenvalue analysis and non-linear simulation results show that single FESS has ability of damping power system multi-mode oscillations by an example of four-machine power system with FESS-based stabilizers.
Design of Multi-channel Image Superimposition System Based on FPGA

A multi-channel image superimposition system is designed in this paper. It can superimpose white-light image on infrared thermal image to generate mixture image. The system is realized on a FPGA chip and is mainly composed of multi-channle DMA controller and image superimposition module. Multi-channel DMA controller can realize data exchange between image superimpositon module and memory independent of vehicle-loaded CPU. Image superimposition module adopts Alpha channel mixture algrithm to mix two-channel images. Equations of algrithm are modified to forms that can be easily designed on a FPGA chip. Due to using programmable chips and parallel processing technology, the system has high integration, good maintenance, quick image processing speed and strong real-time capability.