nils-herrmann/clean_scirepeval huggingface dataset:
Modeling temporal information using discrete fourier transform for recognizing emotions in user-generated videos

With the widespread of user-generated Internet videos, emotion recognition in those videos attracts increasing research efforts. However, most existing works are based on framelevel visual features and/or audio features, which might fail to model the temporal information, e.g. characteristics accumulated along time. In order to capture video temporal information, in this paper, we propose to analyse features in frequency domain transformed by discrete Fourier transform (DFT features). Frame-level features are firstly extract by a pre-trained deep convolutional neural network (CNN). Then, time domain features are transferred and interpolated into DFT features. CNN and DFT features are further encoded and fused for emotion classification. By this way, static image features extracted from a pre-trained deep CNN and temporal information represented by DFT features are jointly considered for video emotion recognition. Experimental results demonstrate that combining DFT features can effectively capture temporal information and therefore improve emotion recognition performance. Our approach has achieved a state-of-the-art performance on the largest video emotion dataset (VideoEmotion-8 dataset), improving accuracy from 51.1% to 55.6%.
A wave energy conversion mechanism applied in robotic fish

Multi-joints robotic fish can provide great help for humans in river and sea for their excellent maneuverability and high propulsion efficiency. However, the energy problem has limited its applications severely because most developed robotic fish can only swim continuously for several hours with the storage energy itself. Fortunately, the ocean has enormous wave energy which could be captured and converted to electricity. Based on the structure of the multi-joints robotic fish, a reversible energy conversion mechanism is proposed. The mechanism not only can work as drive unit but also can work as power take-off (PTO) unit which is able to capture wave power for the robotic fish. In this paper, the PTO unit is investigated analytically and verified by experiments. Firstly, the hydrodynamic behavior of the PTO unit was analyzed and calculated with linear water wave theory. Secondly, a wave generating system and a PTO unit prototype were designed and manufactured according to the theoretical analysis. Finally, experiments on the energy conversion mechanism were conducted. The results demonstrate that the developed PTO unit is able to convert wave energy to electricity with a relative high efficiency, which provides a practical solution for the energy problem of the bionic underwater robots.
Fault Diagnosis of Complex Systems Based on Multi-sensor and Multi-domain Knowledge Information Fusion

This paper presents a framework for fault diagnosis of complex systems by proposing a new multi-sensor and multi-domain knowledge information fusion (MSMDK) model. In the model, the multi-domain case, rule and model knowledge are adopted for multi-sensor information reasoning, and then the advanced Dempster-Shafter (D-S) evidence theory is proposed for overall fusion, which has the advantage of avoiding the evidence conflict by defining the evidence preference weight (EPW). In addition, the basic belief assignment (BBA) methods of the three different domain knowledge are brought forward for entire fusion process. The experiments of fault diagnosis of helicopter autopilot are carried out and demonstrate that the proposed method can serve as an effective method for the fault diagnosis of complex dynamic systems.
Analysis of three-phase inverter with wavelet PWM technique

This paper presents the principle and implementation of the wavelet PWM (WPWM) technique based on non-dyadic type multi-resolution analyses (MRAs) for three-phase inverters, analyses and gives the impacts of the initial values of scales by WPWM on the three-phase full-bridge and half- bridge inverter's output features, which is beneficial to choose suitable initial values of scales. Finally, the performances of WPWM technique are compared with those obtained using SPWM and SVPWM technique under same conditions. Simulation results show that the WPWM technique can get smaller THD and more disperser spectrum than SPWM and SVPWM technique, which provide theoretical basis for the application of the WPWM efficiently in practice.
Face Verification Based on Feature Transfer via PCA-SVM Framework

Face verification is a task to determine whether a pair of given facial images belong to the same person. In unconstrained real applications, inter and intra variations, including illumination, pose, occlusion, and expression, will seriously decrease the verification performance. Due to the lack of annotated data for face verification, extended datasets for face recognition with large samples are used to assist learning a robust feature representation generally. However, the extended data for face recognition is different from face verification on distribution and task. In this paper, a transfer learning based on PCA-SVM is proposed to alleviate above problem. The original feature representation is learnt from a deep convolutional neural network by face classification. Then a PCA-SVM based transfer method is used for feature reprojection from the source domain (face recognition) to the target domain (face verification), which reduces the divergence of feature distribution and task inconsistency. The proposed framework yields comparable results and the accuracy is 98.5% on LFW dataset.
An Improved Procedure for Nonlinear Aeroelastic Analysis

Nonlinear aeroelasticity, caused by the interaction between transonic nonlinear fluid and geometrically nonlinear structure, is studied by coupling solution of the two fields. A predictor-corrector procedure with an approximately energy conservation is developed to obtain nonlinear structure response. Finite volume method with dual-time implicit technology is utilized to solve Reynolds averaged Navier-Stokes equation to achieve nonlinear unsteady aerodynamic load. The two solvers are coupled by a second order time marching scheme. With the application on a flexible wing for nonlinear aeroelastic response computation, the improved procedure presents a better stability and capacity than conventional method.
A Model for Web Services Composition Based on QoS and Providers' Benefit

To deal with the problems such as Web Services selection algorithm, availability of Web Services composition and QoS(Quality of Service) guarantee, presents a model for Web Services composition based on QoS and providers' benefit. In this model, the traditional UDDI is expanded to describe the QoS attributes of Web Services. A Service Proxy role is added into this model. All Web Services compositions requested by service consumers are fond, bound and invoked by the Service Proxy role. In order to maximize services providers' benefit, presents a Service Request Queue Scheduling algorithm in the Service Proxy role. This model meets the QOS requirements of service consumers, guarantees the availability of Web Services composition and maximizes service providers' benefit. Experimental results confirm the efforts of this model.
A Subspace Method for Fourier-Based Image Registration

Image registration is the process of estimating the misalignment between two images. Automatic image registration procedures are important in many remote-sensing applications. A popular approach for coarse registration is Fourier based. Fourier-based image registration is essentially a frequency estimation problem in the frequency domain of the image data. This letter studies the application of a subspace-based frequency estimation approach for the Fourier-based image registration problem. By employing the Multiple Signal Classifier algorithm, a more robust and accurate registration result is achieved at the expense of moderate computational complexity. In the examples considered, performance for registration of remote-sensing images using this method is comparable to a mutual information-based and a correlation-based registration algorithm but requires less computation.
A "flight data recorder" for enabling full-system multiprocessor deterministic replay

Debuggers have been proven indispensable in improving software reliability. Unfortunately, on most real-life software, debuggers fail to deliver their most essential feature - a faithful replay of the execution. The reason is nondeterminism caused by multithreading and nonrepeatable inputs. A common solution to faithful replay has been to record the nondeterministic execution. Existing recorders, however, either work only for data-race-free programs or have prohibitive overhead. As a step towards powerful debugging, we develop a practical low-overhead hardware recorder for cache-coherent multiprocessors, called flight data recorder (FDR). Like an aircraft flight data recorder, FDR continuously records the execution, even on deployed systems, logging the execution for post-mortem analysis. FDR is practical because it piggybacks on the cache coherence hardware and logs nearly the minimal thread-ordering information necessary to faithfully replay the multiprocessor execution. Our studies, based on simulating a four-processor server with commercial workloads, show that when allocated less than 7% of system's physical memory, our FDR design can capture the last one second of the execution at modest (less than 2%) slowdown.
Formation control of underactuated autonomous underwater vehicles in horizontal plane

In formation control, each autonomous underwater vehicle (AUV) needs to maintain a desired distance among others while following its predefine path. We divided the problem into two steps, one is path following of a single vehicle, and the other is coordinating the path parameter. We combine backstepping and Lyapunov method to derive the path following algorithm for each AUV, and then make each AUVpsilas path parameter synchronization to accomplish the formation task. Simulation results show the efficiency of the proposed control law, and in our algorithm, AUV needs to exchange the path parameter only, which decrease the communication requirement.
Research of path loss exponent and distance estimation based on Doppler effect and frequency diversity

With the need of localization based services increasing, many algorithms are proposed using distance between two points and path loss exponent of the environment. In this paper, we propose an algorithm using received signal strength, Doppler Effect and frequency diversity in vehicular networks. The algorithm can estimate the path loss exponent and distance dynamically in mobile communication environment. And the higher the relative speed of vehicles, the better performance of the propose technique. We evaluate the performance of the proposed algorithm in the simulation and discuss the corresponding results.
A realization of intelligent control for freedom surface modeling system

The freedom surfaces modeling technology is very important and widely applied. We discuss a realization technology of intelligent control for freedom surfaces modeling system. We firstly present the principle and realization algorithm of a surface produced by beta-spline curves. Secondly, on the basis of the coordinate projection of bibeta-spline surface, the automatic adjustment and display principle of graphics on the screen are discussed, and a specific algorithm is given. Finally, we focus on the basic thought and fast algorithm of hidden surface elimination. The algorithm puts each surface fragment in a small-to-big order according to the vision depth information, and outputs the quadrangles filled with colors on the screen. Applying the algorithm mentioned above to the freedom surface geometric modeling, we have got some satisfying results. The algorithm needs less computation and the results are reliable.
Open Identity Management Framework for SaaS Ecosystem

As Software-as-a-Service (SaaS) becomes more and more popular, the identity management and federation among SaaS applications also become an important factor impacting the growth of SaaS ecosystem. Typically, there are three major functions to be enabled in identity federation: 1) Single Sign-On across different services. 2) Account provisioning to different services. 3) Secure backend service call between services. Current SaaS delivery platforms provide these functions in an ad-hoc way, which might limit the growth of SaaS ecosystem. To overcome the limitations, this paper proposes an open identity framework, which leverages open identity protocol such as OpenID and OAuth. Moreover, an OAuth broker is proposed to mediate backend service calls among SaaS applications. The framework can bring benefits to all the roles involved in the ecosystem in a non-intrusive and user-centric way. Open is a good design principle, and it is also the attitude and sprit of collaboration. We think that a SaaS ecosystem based on open technologies could make the composition of services easier and accelerate the on-boarding of service providers. Moreover, more customers might also be attracted by the openness of the ecosystem.
A Ka-band cavity-backed patch antenna with parasitic strips using LTCC multilayer technology

This paper presents the design of a Ka-band cavity-backed patch antenna with parasitic strips using low temperature cofired ceramic (LTCC) multilayer technology. A cavity-backed structure consisting of a square ring of short-circuited metal plane is used to surround the microstrip patch antenna for alleviating the effect of the edge diffraction and reducing the backside radiation, hence, improving the radiation performance. Additionally, two groups of parasitic strips, mounted above two radiation side of the microstrip patch, act as directors to increase the gain, and also introduce resonant structures to broaden the bandwith. By the designed structure, a high maximum gain, about 8.3 dBi, is achieved; and the return loss better than −10dB bandwidth is over 23%, from 31 GHz to 39.3 GHz.
FSIW cavity filter and Derivative FSIW cavity and its filters with LTCC technology

A three order cross-coupling FSIW (Folded Substrate Integrated Waveguide) cavity filter with three TZs (Transmission Zeroes) is proposed firstly. By the merit of the LTCC (Low-Temperature Co-fired Ceramic) technology, the substrate area occupied by the filter is reduced by approximately 50% compared with the traditional SIW filter, and it still exhibits a sharp frequency selection performance. To further reduce the cavity area, a four order rectangular Derivative FSIW cavity filter is designed. Finally, a cylindrical Derivative FSIW cavity is proposed for the first time and a filter is constructed to prove its validity. The two types of Derivative FSIW cavities not only promises to reduce the substrate area, but also have the character of depressing some higher modes, which helps to realize large depression above and below the pass-band.
A High-Frequency Compact Model for Graphene Resonant Channel Transistors Including Mechanical Nonlinear Effects

This paper presents a physical-based high-frequency nonlinear model of graphene resonant channel transistors (G-RCTs), including a nonlinear electromechanical model of doubled clamped graphene mechanical resonators. To accurately describe the temperature-dependent modal dispersion, both bias- and temperature-dependent effects are considered. The temperature-dependent built-in strain, the bias-based electrostatic force, and the spring restoring force, including the nonlinear term upon deformation, are used to describe the mechanical motion of the suspended beam. The nonlinear model is validated by the measured results of G-RCTs, which indicate that our model can predict the experimental results well. Moreover, the nonlinear effects, including harmonic distortion, third-order intermodulation distortion, and the hysteresis and nonlinear behavior of G-RCTs, are also studied. The results show that the nonlinear physical model can predict the response of G-RCTs very well. These results also show that the mechanical nonlinearity has strong effects on nonlinear distortion for G-RCTs. The nonlinear equivalent circuit model could be useful for nanoelectromechanical system in the applications of high-frequency integrated circuits.
A Broadband Passive Monopulse Comparator MMIC

A broadband monopulse comparator MMIC (Monolithic Microwave Integrated Circuit) based on GaAs process is presented in this Letter. The comparator network constructed by three magic tees and one lumped power divider is proposed for one sum channel and two delta channels. The measurement results show that very wide frequency band from 15 to 30 GHz (66.7% relatively frequency bandwidth) with less than 2.5-dB loss can be achieved for the sum channel. And the null depth is more than 22 dB in 15–27GHz and 17 dB in 27–30 GHz for two delta channels. The total chip size is 3.4 mm 3.4 mm (<inline-formula> <tex-math notation="LaTeX">$0.26\lambda _{0}~0.26\lambda _{0}$ </tex-math></inline-formula> at the center frequency of 22.5 GHz).
A Support Vector Machine Method for Electrothermal Modeling of Power FETs

An accurate electrothermal modeling method for power FETs is presented. The thermal models are setup by using Support Vector Machine Regression (SVR) approach, which is like artificial neural network (ANN) method leading a knowledge-based model. Unlike traditional ANNs, Support Vector Machine (SVM )method requires fewer samples in statistical learning and is free of local minima in optimization. A comparison among the SVM model, the empirical model and the measurement data of a GaAs power pHEMT are given out to validate the proposed approach.
Gradient-based high precision alignment of cryo-electron subtomograms

Whole cell cryo-electron tomography emerges as an important component for structural system biology approaches. It allows the localization and structural characterization of macromolecular complexes in near living conditions. However, the method is hampered by low resolution, missing data and low signal-to-noise ratio (SNR). To overcome some of these difficulties one can align and average a large set of subtomograms. Existing alignment methods are mostly based on an exhaustive scanning and sampling of all but discrete relative rotations and translations of one subtomogram with respect to the other. In this paper, we propose a gradient-guided alignment method based on two subtomogram similarity measures. We also propose a stochastic parallel optimization that increases significantly the efficiency for the simultaneous refinement of a set of alignment candidates. Results on simulated data of model complexes and experimental structures of protein complexes show that even for highly distorted subtomograms and with only a small number of very sparsely distributed initial alignment seeds, our method can accurately recover true transformations with a significantly higher precision than scanning based alignment methods.
Influence of gas flow on discharge mode in coaxial argon DBD under atmospheric pressure

Dielectric barrier discharge (DBD) under atmospheric pressure is usually characterized with a large number of streamer discharge filaments. So its applications are greatly limited due to the non-uniform discharge mode. Nowadays, most research efforts are being focused on how to achieve the uniform DBD, and results show that there are many ways to improve the non-uniformity of the discharge, one of which is the introduction of flowing gas into the discharge gap at controllable flow rates. However, the mechanism of gas flow on discharge mode on DBD is still not understood clearly. This paper presents a coaxial DBD plasma jet, in which a powered electrode covered by polytetrafluorethylene (PTFE) is fastened in the center of a quartz glass tube, and a copper strip as grounded electrode is wrapped outside the tube. The device is operated under atmospheric pressure with an intermediate frequency sinusoidal resonant power supply. Argon (99.999%) is employed as the working gas, and its flow rate is measured and controlled through a flow meter within the range of 0-25 L/min. The influence of different gas flow rates on the discharge mode is investigated and the mechanism is analyzed. From the discharge photos, it can be seen that the discharge is generated inside the tube and the plasma is blown out by the gas flow to form a plasma jet. When the flow rate is relatively slower, there are obvious discharge filaments near the tube nozzle, which can also be confirmed through the waveform of the discharge current characterized by many current pulses per half cycle of the applied voltage. The faster the gas flows, the fewer the discharge filaments are, and the more homogeneous discharge is obtained. At a certain gas flow rate, together with the lowest breakdown voltage value, the discharge mode presents a glow like state. It can be concluded that the faster flowing argon can take more heat generated in the discharge away, which can induce the thermal stability of discharges and prevent the transition the Townsend discharge to a filamentary discharge effectively. Besides, there is the distortion of applied electric field caused by the wall charge accumulated on the surface of dielectric and the space charge moving towards electrodes in the discharge gap. When the argon flows through the gap at different rates, the spatial distribution of wall charges and space charge is influenced. The faster the argon flows, the less wall charges and space charge accumulates, and the more homogeneous the discharge presents.
Registration of high-dimensional remote sensing data based on a new dimensionality reduction rule

Registration of remote sensing data often involves dimensionality reduction of high-dimensional data to yield an image from each data set followed by pairwise image registration. We develop a new rule for dimensionality reduction such that the the Cramér-Rao lower bound (CRLB) for the estimation of the transformation parameters is minimized. A hyperspectral data set and a multispectral data set are used to evaluate our proposed rule. The experimental results using Mutual Information (MI) based pairwise registration technique demonstrate that our proposed rule can select the image pair with more texture, resulting in improved image registration results.
A millimeter-wave high power combining circuit based on a waveguide-based lossless symmetric 180° 3-dB hybrid

This paper presents a millimeter-wave broadband high power combining scheme with a waveguide-based lossless symmetric 180deg 3-dB hybrid, in which completely match and isolation cannot be obtained simultaneously. And then with millimeter-wave high power MMIC PAs(TGA4517-EPU) integrated, a two-way high power combining circuit is fabricated. The CW output power measured is more than 35.8 dBm in 31- 35 GHz, and the maximal output power, 37.5 dBm is observed at 32 GHz. The corresponding combining efficiency is more than 78% in the working bandwidth of the devices adopted. This new millimeter-wave waveguide-based solid-state high power combining scheme has properties of compact structure, easy fabrication process, good heat sinking and high combining efficiency in a broad bandwidth, and has potential for millimeter-wave broad-band high power combination.