nils-herrmann/clean_scirepeval huggingface dataset:
Exploring the influence of feature representation for dictionary selection based video summarization

Dictionary selection based video summarization (VS) algorithms, in which keyframes are considered as a dictionary to reconstruct all the video frames, have been demonstrated to be effective and efficient for video summarization. It has been noticed that the feature representation of video plays a great impact of the performance of VS. In this paper, the influence of feature representation of video frames on the performance of dictionary selection-based VS is for the first time investigated. In addition to the traditional hand-crafted features used in VS, such as color histogram, the deep features learned through deep neural networks are firstly used to represent video frames for dictionary selection-based VS. The impact of dimensionality reduction to the high-dimensional deep learning features on VS is further discussed. Experimental results on a benchmark video dataset demonstrate that deep learning features are able to achieve better performance than traditional hand-crafted features for dictionary selection-based VS. Moreover, the dimensionality of deep learning features can be reduced to decrease the computational cost without the degradation of VS performance.
Research on characteristics of conductor surface electric field considering downward lightning leader

Shielding failures of lightning is a key problem for the reliable operation of transmission lines. The Leader Progression Method (LPM), based on the theory of long air gap discharge, is an advanced method to evaluate the shielding failure probability of transmission line nowadays. The calculation of surface electric field on phase conductors and ground wires is the key factor that influences the upward leader inception. In this paper, the operation voltage of transmission line, the distance between adjacent check points set on the surface of transmission lines and some other factors that influence the surface electric field were analyzed. The influence of these factors on surface electric field was presented in this paper.
Spatial context for visual vocabulary construction

The bag-of-visual-words model has been widely used in many applications, such as object recognition, image categorization, and visual information retrieval. However, most existing approaches construct a visual vocabulary by simply clustering image regions represented with low-level visual features, where spatial context of image regions has not been well utilized. In this paper, we present two techniques to take such a context into account. One is based on the Self-Organizing Map for Adaptive Processing of Structured Data (SOM-SD), and the other is based on our proposed Hierarchical Fuzzy C-means with Spatial Constraints (FCM-HS). We have employed these two methods together with language modeling for image categorization. Experimental results obtained on Caltech dataset have demonstrated that these two methods can achieve better classification performance than those without considering spatial context. The comparison of these two methods is also discussed in this paper.
Improving Spatial–Spectral Endmember Extraction in the Presence of Anomalous Ground Objects

Endmember extraction (EE) has been widely utilized to extract spectrally unique and singular spectral signatures for spectral mixture analysis of hyperspectral images. Recently, spatial-spectral EE (SSEE) algorithms have been proposed to achieve superior performance over spectral EE (SEE) algorithms by taking both spectral similarity and spatial context into account. However, these algorithms tend to neglect anomalous endmembers that are also of interest. Therefore, in this paper, an improved SSEE (iSSEE) algorithm is proposed to address such limitation of conventional SSEE algorithms by accounting for both anomalous and normal endmembers. By developing simplex projection and simplex complementary projection, all the hyperspectral pixels are projected into a simplex determined by the normal endmembers extracted in conventional SSEE algorithms. As a result, anomalous endmembers are identified iteratively by utilizing the l2∞ norm to find the maximum simplex complementary projection. In order to determine how many anomalous endmembers are to be extracted, a novel Residual-be-Noise Probability-based algorithm is also proposed by elegantly utilizing the spatial-purity map generated in the previous SSEE step. Experimental results on both synthetic and real datasets demonstrate that simplex projection errors can be significantly reduced by identifying both anomalous and normal endmembers in the proposed iSSEE algorithm. It is also confirmed that the performance of the proposed iSSEE algorithm clearly outperforms that of SEE algorithms since both spatial context and spectral similarity are utilized.
Monobit Digital Receivers for QPSK: Design, Performance and Impact of IQ Imbalances

Future communication system requires large bandwidths to achieve high data rates, thus rendering analog-to-digital conversion (ADC) a bottleneck due to its high power consumption. In this paper, we consider monobit receivers for QPSK. The optimal monobit receiver under Nyquist sampling is obtained and its performance is analyzed. Then, a suboptimal but low-complexity receiver is proposed. The effect of imbalances between In-phase (I) and Quadrature (Q) branches is carefully examined. To combat the performance loss due to IQ imbalances, monobit receivers based on double training sequences and eight-sector phase quantization are proposed. Numerical simulations show that the low-complexity suboptimal receiver suffers 3dB signal-to-noise-ratio (SNR) loss in additive white Gaussian noise (AWGN) channels and only 1dB SNR loss in multipath channels compared with matched-filter monobit receiver with perfect channel state information (CSI). It is further demonstrated that the amplitude imbalance has essentially no effect on monobit receivers. In AWGN channels, receivers based on double training sequences can efficiently compensate for the SNR loss without complexity increase, while receivers with eight-sector phase quantization can almost completely eliminate the SNR loss caused by IQ imbalances. In dense multipath channels, the effect of imbalances on monobit receivers is slight.
Distortion analysis of a stimulated Brillouin scattering-based microwave photonic bandpass filter

The signal distortions of the microwave photonic bandpass filter based on stimulated Brillouin scattering is presented in this paper for the first time. We assume that modulated signal pulse propagates through a continuous-wave-pumped Brillouin fiber gain medium, where the carrier angular frequency of the pulse is tuned so that it's near to Stokes resonance. The decibel gain and broadening factor of signal pulse are studied in the small-signal and gain-saturation region. Simulation results show that saturation effect of Brillouin microwave photonic filter restricts the linearity performance of relevant filter. In the small-signal region, both signal decibel gain and broadening factor increase linearly with increasing gain coefficient. In the gain-saturation region, both signal decibel gain and broadening factor decrease with increasing gain coefficient, and the pulse even achieves a compression. The signal decibel gain and the broadening factor are constant for a low pulse peak power and are reduced at a high peak power because of gain saturation. Longer pulses obtain both larger signal decibel gain and less broadening factor in pump-undepletion region, thus they are suitable for filtering processing of this type of stimulated Brillouin scattering-based microwave photonic bandpass filter.
Beckhoff based arm control system design for Elderly Assisting Robot

As a part of the Elderly Assisting Robot, we designed a Beckhoff based multi-motor controlling system for a four-DOF lightweight robot arm after comparing with present robot arm controlling methods and the market demand analysis. A gear-based two-DOF joint was chosen to realize the dexterity. Various types of PID regulators were implemented to improve the performance of motors. RS232, CANOpen and EtherCAT were used in hardware connections. We compelled the controlling program with error detecting and recovery abilities in IEC 61131–3 standard language in TwinCAT real-time industry PC system to coordinate the communication among different devices. The feasibility and stability is verified by a series of experiments. The research contents, method and results are meaningful to the following further researches in related areas and engineering applications.
Design and Management

Modern design was born in Europe at the beginning of 20th century. A series of factors led to its emerging under the background of historical and social change, in which the influences from industrial revolution, economical and social system's transformation were extremely striking. Therefore, the birth and development of modern design have been involved in the interactive relations with such historical and social elements. From which, the relationship between design and management was especially remarkable from the perspective of both scientific and historical research. Firstly, modern design has played a very important role in the business management, and again, it has a strong connection with macro-social management, or it gradually became a measure to achieve social objectives or to deal with social problems, where, for instance, the environmental issue or energy crisis were highly concerned. Within such a discussion, the significance of modern design's role in the modern management could have been revealed totally and would draw a necessary attention at any respect.
Electro Optical Terahertz Pulse Reflectometry — an innovative fault isolation tool

Electro Optical Terahertz Pulse Reflectometry (EOTPR), an innovative time domain reflectometry (TDR) system, has been successfully developed. This is the first system that applies terahertz technology to time domain reflectometry. The system has achieved 10 um resolution, 5.7ps rise time, 94dB signal/noise ratio and 150 mm testing range and it has been successfully integrated into fault isolation and failure analysis process flow.
Improved Drop Reliability Performance with Lead Free Solders of Low Ag Content and Their Failure Modes

Solder joint reliability of lead free solders (Sn-Ag-Cu) in drop testing has been an issue in mobile and handheld electronics. Since lead free solders have lower drop performance compared with Pb-Sn solders, many efforts have been reported to improve solder joint reliability with various lead free solders. In this study, standard JEDEC drop reliability tests were performed for a CSP (chip scale package) prepared with two different compositions of lead free solders (SAC405 alloy: Sn-4Ag-0.5Cu and SAC105 alloy: Sn-1Ag-0.5Cu). Lead free solders were assembled on substrates with a Au/Ni surface finish. It was seen that SAC 105 alloy solder demonstrated better drop reliability compared with SAC405 alloy solder and failure analysis conducted to understand the differences in failure modes & drop reliability performance.. The fundamental cause of improved drop reliability performance of SAC 105 solders and the advantages of using low Ag content SAC lead free solders for microelectronic devices is discussed. Finally, a finite element model was developed and validated with failure analysis to investigate the high stress concentration distribution and failure mode in solder joints for drop test stress conditions.
Video Summarization via Simultaneous Block Sparse Representation

With the ever increasing volume of video content, efficient and effective video summarization (VS) techniques are urgently demanded to manage the large amount of video data. Recent developments on sparse representation based approaches have demonstrated promising results for VS. While most existing approaches treat each frame independently, in this paper, the block-sparsity, which means the keyframes or non-keyframes occur in blocks due to the content similarity in a same frame block, is taken into account. Therefore, the video summarization problem is formulated as a simultaneous block sparse representation model. For model optimization, simultaneous block orthogonal matching pursuit (SBOMP) algorithms are designed to extract keyframes. Experimental results on a benchmark dataset with various types of videos demonstrate that the proposed algorithms can not only outperform the state of the art, but also reduce the probability of selecting non-informative frames and "outlier"frames.
Voltage Balancing Approaches for Diode-Clamped Multilevel Converters Using Auxiliary Capacitor-Based Circuits

An auxiliary capacitor-based balancing approach is adopted in this paper to equalize the dc-link capacitor voltages of a diode-clamped multilevel converter (DCMC). Four balancing circuits, including the generalized, one-level-capacitor, one-capacitor, and simplified one-capacitor-based configurations are discussed for a five-level DCMC system. These configurations are different in connection of the auxiliary circuits and numbers of the capacitors and switches, but they work on the same principle called ping-pong operation by utilizing the auxiliary capacitor as an equalizer between the capacitors of different voltages. The unbalance phenomenon, ping-pong principle, circuit configurations, and their switching schemes are analyzed, respectively. The superiorities of the proposed approach include balancing operation regardless of load power factor and modulation index, control simplicity, and independence from main circuits when compared to the traditional approaches. Simulations and experimental results verified the performances using the proposed balancing circuits and control strategies.
Design and development of high-performance sliding electrical contact testing instrument

In order to research the carrying current-wear characteristics of pantograph slide and contact wire used in electrical locomotive and analyze the general rules existed in wear-steady state, a new kind of high-performance sliding electrical contact testing instrument was developed. The testing instrument can simulate actual carrying current-wear operating conditions of pantograph slide and contact wire used in electrical locomotive. All parameters need to be measured under different experiment conditions can be detected by the microcomputer embedded the instrument which can communicate with the supervisory control computer in series communication mode. The supervisory control computer was also used to record and analyze the experimental data, and get some necessary data curves. The results showed that the structural design of the experimental machine reasonable, parameter measurement accuracy. It can simulate a wide range of actual operating environment.
Resource restricted on-line Video Summarization with Minimum Sparse Reconstruction

Video Summarization (VS) techniques have been widely utilized to produce a concise video content representation, such that the video content can be quickly explored and the complexity of video based analysis and retrieval applications can be highly reduced. However, little attention has been paid for on-line applications, especially for resource restricted applications, such as onboard VS. In this paper, our previous on-line Minimum Sparse Reconstruction (OnMSR) based VS algorithm is improved for resources restricted applications by confining the size of keyframes for reconstruction. Specially, an on-line reconstruction keyframe set update strategy is designed to meet the requirement of real-time resource restricted situation. Experimental results on various types of videos demonstrate the performance of OnMSR does not vary much by imposing resource constraint in the proposed resource restricted OnMSR (RR-onMSR) algorithm. As a result, the proposed RR-onMSR is very effective for real-time onboard VS applications.
Atmospheric turbulence mitigation based on turbulence extraction

A video taken under the influence of atmospheric turbulence suffers from serious distortion caused by the variation of optical refractive index. In order to reduce geometric distortion and time-space-varying blur, and recover both coarse structure and fine details, a novel turbulence extraction based approach for recovering a latent image from an atmospheric turbulence degraded imagery sequence is proposed. Firstly, a non-rigid image registration method is applied as a preprocessing to reduce geometric deformation. Secondly, the registered image sequence is decomposed into a low-rank background scene component and a sparse turbulent component via matrix decomposition. Different from other approaches, which intend to remove turbulence directly, we manage to extract information of distortion position from the sparse turbulent component to indicate the sharpest turbulence patches. The selected sharpest turbulence patches are then enhanced and fused to generate an enhanced detail layer. Finally, the output image is generated by fusing the deblurred background scene layer and the enhanced detail layer together. Experiments indicate that our approach is capable of significantly alleviating atmospheric turbulence blur and geometric distortion.
Self-calibrated interferometric-intensity-based optical fiber sensors

This paper presents self-calibrated interferometric-intensity-based optical fiber sensors, which combine for the first time fiber interferometry and intensity-based devices into a single sensor system. The sensor involves an extrinsic Fabry-Perot (FP) interferometric cavity. The broadband light returned from the FP cavity is split into two channels in such a way that one channel has a coherence length much longer than the doubled air-gap separation in the sensor so the FP generates effective interference, while the coherence length in the other channel is so short that no effective interference takes place. As a result, the optical signal in the channel with a long coherence length yields information about the FP cavity length while the signal in the other channel is proportional only to the source power, fiber attenuation, and other optical loss factors in the optical path. To eliminate fringe direction ambiguity and relative measurement limitations associated with interferometric sensors, the sensor is designed such that it is operated over the linear range between a valley and a peak of one interference fringe in the first channel. Moreover, the ratiometric signal-processing method is applied for the signals in the two channels to obtain self-calibrating measurement to compensate for all unwanted factors, including source power variations and fiber bending losses. Various pressure and temperature sensors based on the self-calibrated interferometric/intensity-based scheme are designed, fabricated, and tested. Experimental results show that a resolution as high as 0.02% of full scale can be obtained for both the pressure and temperature measurements.
Measuring semantic similarity between concepts in visual domain

Concept similarity has been intensively researched in the natural language processing domain due to its important role in many applications such as language modeling and information retrieval. There are few studies on measuring concept similarity in visual domain, though concept based multimedia information retrieval has attracted a lot of attentions. In this paper, we present a scalable framework for such a purpose, which is different from traditional approaches to exploring correlation among concepts in image/video annotation domain. For each concept, a model based on feature distribution is built using sample images collected from the Internet. And similarity between concepts is measured with the similarity between their models. Hereby, a Gaussian mixture model (GMM) is employed to model each concept and two similarity measurements are investigated. Experimental results on 13,974 images of 16 concepts collected through image search engines have demonstrated that the similarity between concepts is very close to human perception. In addition, the entropy of GMM cluster distributions can be a good indication of selecting concepts for image/video annotation.
Mixture Analysis by Multichannel Hopfield Neural Network

Due to the spatial-resolution limitation, mixed pixels containing energy reflected from more than one type of ground objects are widely present in remote sensing images, which often results in inefficient quantitative analysis. To effectively decompose such mixtures, a fully constrained linear unmixing algorithm based on a multichannel Hopfield neural network (MHNN) is proposed in this letter. The proposed MHNN algorithm is actually a Hopfield-based architecture which handles all the pixels in an image synchronously, instead of considering a per-pixel procedure. Due to the synchronous unmixing property of MHNN, a noise energy percentage (NEP) stopping criterion which utilizes the signal-to-noise ratio is proposed to obtain optimal results for different applications automatically. Experimental results demonstrate that the proposed multichannel structure makes the Hopfield-based mixture analysis feasible for real-world applications with acceptable time cost. It has also been observed that the proposed MHNN-based mixture-analysis algorithm outperforms the other two popular linear mixture-analysis algorithms and that the NEP stopping criterion can approach optimal unmixing results adaptively and accurately.
Design of snubber circuit for the 4500 V/4000 A GTOs in a 20 MVA STATCOM

This paper analyzes the generation process of the overvoltages V/sub DSP/ V/sub DM/ and V/sub R/ during the turn-off process of GTO and the measures to suppress the overvoltages. Through analyses of the features of conventional RCD snubber circuit and three kinds of low-loss snubber circuit, the snubber circuit for the 4500  A GTOs in a 20 MVA STATCOM installation is proposed. The snubber circuit is the low-loss /spl Delta/-type snubber circuit with a clamping capacitor. Experimental results demonstrate that the proposed snubber circuit is very effective for large capacity two-level GTO inverter.
Performance Analysis of Different Modulation Schemes for Coherent Optical OFDM System

Without optical dispersion compensation, the performances of different modulation schemes are analyzed and comparison of their transmission distance, transmission capacity, band width efficiency and their resistance to BER are made in Coherent optical orthogonal frequency division multiplexing (CO-OFDM) system in this paper. Then some simulation results are given using Matlab software. Simulation results show that: in the same conditions, the relationship of transmission capacity, transmission distance and bit error rate of the system is contradictory. The anti-BER ability of 2PSK is best, but its bandwidth efficiency is lower than other modulation methods. The bandwidth efficiency of 4QAM is as twice as the 2PSK, and the BER of the system is smaller than 10-3 and the required OSNR is about 9dB. When the OSNR is 12dB, the transmission distance is up to 1600km. Although the bandwidth efficiency of 8QAM is higher than other two kinds of modulation methods, its performance of anti-BER is relatively poor. Therefore, we should choose the specific scheme modulation depending on the actual needs of the system when we design communication.