nils-herrmann/clean_scirepeval huggingface dataset:
Active Profiling of Physical Devices at Internet Scale

Nowadays, more and more physical devices embed computing and networking capabilities and are visible on the Internet. These devices include webcams, net-printers, and industrial control equipments, etc. Collecting information about these devices is crucial to preserve cyber-security and facilitate security auditing for system administrators. In this paper, we propose a scalable framework for physical device profiling. It leverages banner grabbing to identify device types and running services, and uses clock skew to determine a device ID. Our framework scales well. We implement a prototype system and use it to profile Webcams and industrial control device. The results show that our system can effectively profile and identify Webcams in real time. We deploy it on the cloud server and use it to detect 4 billion IP addresses to profile 1.2 million Webcams and more than 60 thousand industrial control devices in 20 hours.
A Static Axial Strain Fiber Ring Cavity Laser Sensor Based on Multi-Modal Interference

A novel and simple static strain fiber ring cavity laser sensor based on all-fiber single-mode-multimode-single-mode (SMS) structure filter is proposed and experimentally demonstrated. When an axial strain is applied on the SMS filter, the pass-band varies, resulting in shifts of the lasing central wavelength. Thus, the value of axial strain imposed on the structure can be calculated by the monitored central wavelength of the system via the function relationship between these two parameters. Compared with the conventional axial strain sensing system based on an SMS fiber structure, the proposal exhibits additional advantages in terms of high optical signal to noise ratio (~ 50 dB) and narrow 3 dB bandwidth apart from simple fabrication and low cost. A good linearity is obtained between the axial strain applied on the SMS filter and central wavelength of the proposed laser sensing system with R2 of 0.99954, and high sensitivity of 2.3 pm/με in the range 0-2333 με is successfully achieved.
Adversarial Plan Recognition and Opposition Based Tactical Plan Recognition

Adversarial plan exists widely in information field at present. This paper firstly introduces adversarial plan, adversarial gene, etc. Then it applies tactical plan recognition to design adversarial plan recognition system, judging and recognizing in dynamic world, at the same time we give an algorithm. Later we study the oppositional problem of adversarial plan. It consists two parts - certain oppositional plan and uncertain oppositional plan. On the basis of that, we design the model and algorithm. Furthermore, the paper primarily attempts to apply immunity theory in plan field, and based on the theory we propose the model of adversarial plan recognition and opposition system. With the information increasing, it is necessary to study adversarial plan including hacker, virus and information spy
A novel 2-DOF planar parallel robot with high accelerate / high precision

Orient to urgently demand for high speed and high precision robot of advanced manufacture fields such as packaging and assembly of micro-electronic manufactures, a novel 2-DOF planar parallel robot is presented, which is driven directly by linear voice coil motors. Firstly, the optimum configuration is obtained based on conditioning index of Jacobian. Then optimal dimension design is performed based on the proposed comprehensive performance evaluation index, which integrating kinematic dextrous with dynamic manipulability together. The distribution of conditioning index, dynamic manipulability and acceleration over the workspace is analysed respectively according to optimal structure. Lastly experimental results demonstrated that the novel robot allows a workspace of 55times55 mm2 and an acceleration exceeding 12 g with repeatability better than 1.5 mum. The obtained technical characteristics indicate that the robot can satisfy the proposed application.
Dual channel current-source gate drivers for high-frequency dc-dc converters

In this paper, resonant gate driver techniques for power MOSFETs are reviewed at first. To solve the exiting problems of the drive circuits previously proposed, new dual channel current-source gate drivers are presented here. The new drive circuits can achieve quick turn-on and turn-off transition time to reduce the switching loss of power MOSFETs significantly by constant gate drive currents due to the parasitic inductance, especially the common source inductance. A 12 V synchronous buck VR prototype at 1 MHz switching frequency was built to demonstrate the advantages of the new drive circuits. A significant efficiency improvement over the conventional gate voltage driver is achieved.
Convergence of Optimal Solutions about Approximation Scheme for Fuzzy Programming with Minimum-Risk Criteria

Two-stage fuzzy minimum-risk problems (FMRPs) include fuzzy variable parameters defined through a possibility distribution, they are inherently infinite-dimensional optimization problems that can rarely be solved directly. Therefore, algorithms to solve such optimization problems must rely on intelligent computing as well as approximating scheme, which results in approximating finite-dimensional FMRPs. The purpose of this paper is to establish conditions under which the optimal objective value and optimal solution of such approximating two-stage FMRP converges to the optimal objective value and optimal solution of the original two-stage FMRP, respectively.
Direct adaptive fuzzy control for nonlinear systems with supervisory control performance

A direct adaptive fuzzy control approach with supervisory control performance for a class of uncertain MIMO nonlinear systems is proposed. In this novel method, the proposed controllers consist of two parts: the direct fuzzy control term and the supervisory control term. Compared with the existing research results with respect to the adaptive fuzzy control of uncertain MIMO nonlinear systems, this novel method has the supervisory control performance, and then the adaptive fuzzy control theory is further developed. Based on the stability Lyapunov theory, it can be ensured that all signals in the closed-loop system are bounded, and the tracking errors converge to a small neighborhood around zero. Simulation results indicate the effectiveness of the proposed approach.
Distortion identification technique in video stabilization

For non-stationary displacement sequence of the real-world image sequence, this paper presents a distortion identification technique based on Hilbert Huang Transform (HHT) to identify the distortion model and distortion frequency of the displacement sequence. Experiment results show that this technique can identify the distortion model and distortion frequency of the displacement sequence accurately and quickly. Based on these identification results, we can realize the video stabilization effectively.
An integrated updating Algorithm for mining maximal frequent patterns

The problem of mining maximal frequent patterns plays an essential role in mining association rules. In order to discover more useful maximal frequent patterns, users may adjust the minimum support while database changes. Therefore, we present a novel algorithm IUMFPA that makes use of improved FP-Tree structure and bit object for data expression. It can also utilize the former FP-Tree and the mined results sufficiently. The experimental results indicate that IUMFPA performs efficiently.
Digital implementation of load sharing method for interleaved LLC converters

LLC converter has been found advantageous in isolated DC-DC applications due to its high efficiency and low cost. However in high-power high-current applications, the high component stress and high conduction loss limit the maximum power capacity and reduce the efficiency. Interleaving technique can be employed to solve this problem, but the component tolerances of the resonant tanks will cause severe load sharing problem. This paper describes digital implementations of switch-controlled capacitor (SCC) modulated multiphase LLC converters (SCC-LLC) to achieve load sharing. A 600W two-phase interleaved SCC-LLC prototype is built to demonstrate the feasibility and advantages.
32-Channel ultra-low-noise arbitrary signal generation platform for biopotential emulation

This paper presents a multichannel, ultra-low-noise arbitrary signal generation platform for emulating a wide range of different biopotential signals (e.g. ECG, EEG, etc). This is intended for use in the test, measurement and demonstration of bioinstrumentation and medical devices that interface to electrode inputs. The system is organized in 3 key blocks for generating, processing and converting the digital data into a parallel high performance analogue output. These blocks consist of: (1) a Raspberry Pi 3 (RPi3) board; (2) a custom Field Programmable Gate Array (FPGA) board with low-power IGLOO® Nano device; and (3) analogue board including the Digital-to-Analogue Converters (DACs) and output circuits. By implementing the system this way, good isolation can be achieved between the different power and signal domains. This mixed-signal architecture takes in a high bitrate SDIO (Secure Digital Input Output) stream, recodes and packetizes this to drive two multichannel DACs, with parallel analogue outputs that are then attenuated and filtered. The system achieves 32-parallel output channels each sampled at 48kS/s, with a 10 kHz bandwidth, 110 dB dynamic range and μV-level output noise.
A general synchronization approach for fuzzy chaotic systems based on impulsive differential theory

This paper provides a novel general impulsive synchronization scheme for fuzzy chaotic systems in the form of T-S models. Based on the impulsive differential theory and Lyapunov stability theory, the criteria for the exponential and asymptotical stability of the synchronization error system at the origin are derived. The proposed impulsive synchronization scheme has a simple control structure and need less control energy than other continuous ones for the synchronization of T-S fuzzy chaotic systems. Furthermore, it is suitable for the synchronization problem of most kinds of chaotic or hyperchaotic systems. Simulation results demonstrate the effectiveness of the proposed synchronization method.
Compatibility between RFID and STL

China has issued document to assign the frequency band 840~845 MHz and 920~925 MHz for RFID application on April 23, 2007. However, as the frequency 920~925MHz was originally used by stereo transmit link (STL) service, the power emitted by RFID system will probably cause interference to STL system. This paper presents the methods of conduct measurement and field test to exhibit in what condition a RFID system will not cause performance degradation on STL system.
Design of reference voltage source integrated in LCoS chip

This paper proposes the design of programmable multi-channel reference voltage source integrated in LCoS chip, analyses the role of reference voltage in LCoS display system. Emphasis was placed on the design of analog circuits which consist of dual ladder resistor D/A converter and constant gm rail-to-rail operational amplifier. The reference voltage source for gamma correction of LCoS display is taped out by Chartered 0.35μm CMOS 2P4M Mixed-mode process, and the chip was tested. The test results indicate that the output of the chip can completely meet requirements of the common electronic field-inversion field sequential LCoS display system, and the setup time and accuracy of output voltage achieve the expected target.
Design of multi-permeability distributed air-gap inductors

Distributed air-gap inductors have the advantage of low fringing effect loss. However, the flux density uniformly distributes in the magnetic cores, which results in the magnetic material closer to conductor becoming saturated while the magnetic material far away from the conductor is still not fully utilized. This paper proposes a multi-permeability distributed air-gap inductor structure to increase inductance without the necessity of increasing the inductor volume. The discrete permeability values are investigated. Inductance variations versus number of permeability layers are obtained under the condition that the inductor thickness is constant. To evaluate the proposed method, a three-permeability inductor together with a single permeability inductor is fabricated. The measured results show that the three-permeability inductor has much higher inductance than the single-permeability inductor for the whole load range. Both inductors are tested in a 5V input, 3V output DC/DC converter to compare their performances. The results show the three-permeability inductor could further improve light load efficiency of high frequency DC/DC converters.
Adaptive Reinforcement Learning Control Based on Neural Approximation for Nonlinear Discrete-Time Systems With Unknown Nonaffine Dead-Zone Input

In this paper, an optimal control algorithm is designed for uncertain nonlinear systems in discrete-time, which are in nonaffine form and with unknown dead-zone. The main contributions of this paper are that an optimal control algorithm is for the first time framed in this paper for nonlinear systems with nonaffine dead-zone, and the adaptive parameter law for dead-zone is calculated by using the gradient rules. The mean value theory is employed to deal with the nonaffine dead-zone input and the implicit function theory based on reinforcement learning is appropriately introduced to find an unknown ideal controller which is approximated by using the action network. Other neural networks are taken as the critic networks to approximate the strategic utility functions. Based on the Lyapunov stability analysis theory, we can prove the stability of systems, i.e., the optimal control laws can guarantee that all the signals in the closed-loop system are bounded and the tracking errors are converged to a small compact set. Finally, two simulation examples demonstrate the effectiveness of the design algorithm.
A design and implementation of logistics management system of RFID based on FPGA

Nowadays, people pay more and more attention to logistics management. However, due to the global e-commerce supply chain information transfer is not timely; information distortion and system error, hundreds of billions of dollars every year have lost. In order to improve the efficiency of logistics management system and reduce the error rate, people put forward RFID logistics management system. At the same time, because the embedded technology has the advantages of flexibility, high integration and low price, the use of embedded technology to realize RFID becomes the mainstream. This paper, combining the two, designs a RFID logistics management system based on Nios II. The system consists of a Nios II embedded soft core, a FPGA, a LCD screen, a matrix keyboard etc. After test, it can read the information of goods in a certain range and show them on a LCD screen and users can use a keyboard to manage the warehouse. It also helps to improve the efficiency of logistics management and reduce the error rate.
Backstepping observer-based output feedback control for a class of coupled parabolic PDEs with the same diffusion

The objective of this paper is to extend the relaxed conditions on the existence of the backstepping controllers and observers obtained in a recent literature to the case of parabolic Partial Differential Equations (PDEs) with the same diffusion. Moreover, an observer-based output feedback controller is designed for the considered systems with the new conditions. Then, the corresponding exponential stability analysis is provided. Finally, the efficiency of the proposed method is shown by taking a simplified model of Chemical Tubular Reactor.
Application of accelerometers in vibration test of high voltage circuit breaker

MEMS (Micro-Electro-Mechanical System) piezoresistive accelerometer is proposed for the vibration measurement in the vicinity of vibration source inside high-voltage circuit breaker for mechanical fault diagnosis, which is verified from the theory as well as comparative test with piezoelectric accelerometer. The high voltage circuit breaker vibration test scheme based on MEMS piezoresistive acceleration sensor is presented in the paper.
Activity Based Data gathering protocol for Delay Tolerant Mobile Sensor Network

Delay Tolerant Mobile Sensor Network (DTMSN) is the network for pervasive information gathering. Traditional data information gathering approaches may not fit for DTMSN for its intermittent connectivity. This paper proposes an Activity Based Data gathering protocol (ABD). In DTMSN, activity of different sensors may vary since they are attached to different entities, the message replicated by the active sensors may exit more copies in the network and may reach the sink more easily and quickly, in view of that, the message transmission scheme and the redundant copies controlling technique are proposed. Simulation results show that ABD reaches a well tradeoff between the data delivery ratio/delay and the delivery overhead.
A Low Turn-Off Loss 4H-SiC Trench IGBT With Schottky Contact in the Collector Side

In this paper, a 4H-SiC trench insulated gate bipolar transistor (IGBT) incorporating a Schottky contact in the collector side is proposed to reduce the turn-off energy loss. The proposed structure is explored and compared with the conventional IGBT using ATLAS. The simulation results have indicated that the reduction in turn-off energy loss is more than 88%, with a slight degradation in the <inline-formula> <tex-math notation="LaTeX">${I}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${V}$ </tex-math></inline-formula> characteristics. Concurrently, with the same on-state voltage drop, the turn-off loss is reduced by a figure of 84%.
A physical model of ovonic threshold switching effect for phase change memory based on the trap-to-band transition mechanism

A new physical conductivity model of amorphous chalcogenide is proposed, based on carriers transport theory including hopping transport and trap-to-band transition. A numerical simulator based on this model is developed, and the simulation results agree well with the measurement. The ovonic switch voltage and current with different active area and temperature are studied based on the simulator, and the results show a good consistence with the measurement.
An algorithm for Buck-Boost converter based on the principle of capacitor charge balance

In this paper, a novel non-linear control algorithm is applied to a Buck-Boost converter. Based on the concept of capacitor charge balance, the proposed algorithm predicts an improved transient response for a Buck-Boost converter during the large load-current step change. The equations used to calculate the improved transient time are presented. Some traditional control methods are introduced. The simulation of Buck-Boost converter based on the charge balance control mode and voltage mode control was done. Through the simulation results it can illustrate that the proposed controller had a superior performance when compared to the conventional voltage mode controller.
Broadband substrate integrated dielectric resonator antenna for millimeter-wave applications

A broadband substrate integrated dielectric resonator antenna (BSIDRA) is presented and investigated experimentally. The proposed BSIDRA consists of a substrate integrated dielectric resonator (SIDR) fed by a substrate integrated waveguide with an exciting slot. Dual resonances of the SIDR and the exciting slot radiator are merged to expand the antenna bandwidth. To validate the proposed concept, a prototype antenna is designed at Ka-band and fabricated with two different substrates using printed circuit board process. The return loss, radiation patterns, and antenna gain are studied, and good agreement between the measured and simulated results is observed. The proposed BSIDRA provides a bandwidth of about 25% around 35 GHz for 10 dB return loss and stable broadside radiation patterns with an average gain of 4.6 dBi across the band.
A Calculation of VaR Based on GARCH Model

This paper reviews the meaning and calculating methods of VaR and puts forward GARCH model to improve the estimation of VaR. GARCH model overcomes the defects of volatility without considering market factors in conventional analysis methods of VaR. We demonstrate that VaR based on GARCH model has good dynamics and accuracy. Finally, through the analysis of the actual data of Shanghai Securities Exchange and the test of likelihood ratio, we conclude that GARCH model precisely reflects the volatility of market factors and VaR based on GARCH properly reflects the risk level of finance market
A New Device to Study Fatigue Performance and Mathematical Model to Analyze Relationship between Textile Parameters and Fatigue of Textile Scaffold for Stent-Graft

Fatigue testing for twelve SG tubular fabrics with various textile parameters was performed under pulsatile pressure by a new fatigue tester designed and built by our own. Two time points as of 0, and 1.368 times 10 6 cycles were selected. The percentage change of tubular diameter, fabric count, porosity, and water permeability before and after the fatigue testing were used to characterize the fatigue performance. The mathematical model of quantification theory I was used to analyze the influence of various textile parameters on the fatigue performance of SG textile scaffold. It was found that the predicting results by quantification theory I for the fatigue resistance were relatively accurate and the contribution ratio of each textile parameter to the fatigue performance was also obtained. Different textile parameter has different contribution ratio if different parameters were used to characterize the fatigue performance. Woven construction, yarn size and yarn type had interactive influence on the fatigue performance. This can provide theoretical foundation for making better fatigue resistant SG tubular fabrics.
An Online-Offline Combined Big Data Mining Platform

Machine learning libraries are integral to a big data mining platform. There are three limitations on adopting current machine learning libraries in such a platform. First, these algorithms are not implemented for handling both online and offline big data analysis. Second, libraries exist in a variety of frameworks using different programming languages, which make it difficult in integrating several algorithms. Third, most machine learning libraries provides APIs for programming only, thus not user-friendly for those do not have a sufficient understanding of algorithms and those lack of programming skills. In this paper, we implement a comprehensive machine learning library including common algorithms and deep learning algorithms. We integrate this library at a platform level that allows both online and offline data analysis using this library. We further design a user-friendly portal that enables quick and agile data analysis practices. All of these form an Online-Offline Combined Big Data Mining Platform (OOBDP). We present a demonstration of big oil data analysis using this platform. We observe the that OOBDP can easily accommodate industrial requirement for adaptable data mining process, with personalized usage scenarios, and easy to use experiences.