nils-herrmann/clean_scirepeval huggingface dataset:
Information fusion in face identification

Information fusion of multi-modal biometrics has attracted much attention in recent years. However, this paper focuses on the information fusion in single models, that is, the face biometric. Two different representation methods, gray level intensity and Gabor feature, are exploited for fusion. We study the fusion problem in face recognition at both the face representation level and the confidence level. At the representation level, both the PCA feature fusion and the LDA feature fusion are considered, while at the confidence level, the sum rule and the product rule are investigated. We show through experiments on FERET face database and our own face database that appropriate information fusion can improve the performance of face recognition and verification. This suggests that gray level intensity and Gabor feature compensate for each other, based on the feasible fusion.
Content-aware layered compound video compression

Compound video compression is crucial for remote control and data assessment. In this paper, we propose a content-aware layered video coding scheme as an attempt to efficiently compress the compound video. In this scheme, the compound video is analyzed and processed progressively at three pyramid levels: block, object and layer. Firstly, the compound video is analyzed by a block type classification technique to access each block's spatial and temporal properties. Secondly, the natural video object is detected adaptively in each frame based on the block type. Finally, the compound video content is distributed into different layers and specifically designed video coding algorithms are employed to compress each layer. Experiments demonstrate that our proposed scheme can preserve the advantages of the employed compression algorithms for each layer and outperform each of them in the compound video compression.
Achieving consistence for cross-domain WAN control in Software-Defined Networks

When applying Software-Defined Networks (SDN) to WANs, the SDN flexibility enables the cross-domain control to achieve a better control scalability. However, the control consistence is required by all the cross-domain services, to ensure the data plane configured in consensus for different domains. Such consistence process is complicated by potential failure and errors of WANs. In this paper, we propose a consistence layer to actively and passively snapshot the cross-domain control states, to reduce the complexities of service realizations. We implement the layer and evaluate performance in the PlanetLab testbed for the WAN emulation. The testbed conditions are extremely enlarged comparing to the real network. The results show its scalability, reliability and responsiveness in dealing with the control dynamics. In the normalized results, the active and passive snapshots are executed with the mean times of 1.873s and 105ms in 135 controllers, indicating its readiness to be used in the real network.
Analytical trajectory extrapolation for power systems

Trajectory extrapolation is important for stability analysis and control of modern power systems. Many functions such as security warning and time-delay compensation for wide-area feedback control can be developed through trajectory extrapolation. But as of now, there are no effective methods to extrapolate power system trajectories except for time-consuming numerical integration methods. The difficulties for trajectory extrapolation in power systems lie within the fact that the underlying dynamic equations are nonlinear, and thus analytical solutions are not possible. In this paper, a method is proposed to approximate the analytical solution of power system dynamics, by which trajectories can be extrapolated. First, the dynamic equations of power system are modified to an equivalent set of equations by polynomial projection technique. Based on the modified equations, an approximate analytical solution is obtained using algebraic Picard iteration without integration operation. This solution depends on the initial values and can be used for on-line trajectory extrapolation. Following a disturbance, with values at the instant of disturbance clearance known (i.e. through PMU — measurements), one can easily extrapolate the system trajectory by extending the approximate analytical solution and updating initial values. Finally, some simulation results are presented to show the effectiveness of the method.
Group-Based Sparse Representation for Image Restoration

Traditional patch-based sparse representation modeling of natural images usually suffer from two problems. First, it has to solve a large-scale optimization problem with high computational complexity in dictionary learning. Second, each patch is considered independently in dictionary learning and sparse coding, which ignores the relationship among patches, resulting in inaccurate sparse coding coefficients. In this paper, instead of using patch as the basic unit of sparse representation, we exploit the concept of group as the basic unit of sparse representation, which is composed of nonlocal patches with similar structures, and establish a novel sparse representation modeling of natural images, called group-based sparse representation (GSR). The proposed GSR is able to sparsely represent natural images in the domain of group, which enforces the intrinsic local sparsity and nonlocal self-similarity of images simultaneously in a unified framework. In addition, an effective self-adaptive dictionary learning method for each group with low complexity is designed, rather than dictionary learning from natural images. To make GSR tractable and robust, a split Bregman-based technique is developed to solve the proposed GSR-driven ℓ0 minimization problem for image restoration efficiently. Extensive experiments on image inpainting, image deblurring and image compressive sensing recovery manifest that the proposed GSR modeling outperforms many current state-of-the-art schemes in both peak signal-to-noise ratio and visual perception.
Battery charging power electronics converter and control for plug-in hybrid electric vehicle

Plug-in hybrid electric vehicles are gaining popularity because of the environmental consideration “Go green” factor. In this paper a battery charging system based on a three level ac-dc converter and bidirectional dc-dc converter has been proposed and associated control strategy for the battery charging/discharging has been presented. It has been shown that with direct duty cycle calculation technique that unity power factor is achieved and total harmonic distortion is minimized. The simulation has been performed using simulink. The plots are presented to show the battery charging/discharging and the converter characteristics.
Coke oven pushing plan optimization scheduling research based on improved ant colony algorithm

Coke oven pushing optimization scheduling plays a important role in coke oven productions, especially in the abnormal operating conditions where sequences disorder problem often happens. In order to solve the sequences disorder problem, Firstly, we establish a coke oven pushing optimization scheduling model by means of the target of achieving the least punishment caused by distance, time and pushing coefficient in restoring normal order process. Secondly, in order to avoid the stagnation of the search in ant colony algorithm, adaptive ant colony optimization algorithm wais used to solve optimization scheduling model. Finally, through the simulation of actual production data, experimental results verified the effectiveness of the algorithm. It has a wide application prospect.
Hybrid Zero Block Detection for High Efficiency Video Coding

In this paper we propose an efficient hybrid zero block early detection method for high efficiency video coding (HEVC). Our method detects both genuine zero blocks (GZBs) and pseudo zero blocks (PZBs). For GZB detection, we use a two sum of absolute difference bounds and a one sum of absolute transformed difference threshold to decrease the GZB detection complexity. A fast rate-distortion estimation algorithm for HEVC is proposed to improve the PZB detection rate. Experimental results on the HM platform show that the proposed method saves about 50% of the rate-distortion optimization (RTO) time, with negligible Bjøntegaard delta bit rate loss. Our method is faster than other state-of-the-art ZB detection methods for HEVC by 10%-30%.
Deformation analysis of transformer winding by structure parameter

Frequency Response Analysis can be used to detect the transformer winding deformation. Its reliability and standard are studied. A simulation model of transformer winding is developed. The transformer winding is equivalent to a network circuit, and electrical components in the circuit can describe distributed elements of the winding. The components in the model are determined by the geometric and electric data of the winding. If there is any deformation in the winding, circuit parameters in the model will be changed and thus the character of the whole circuit will be influenced. According to the common situations of winding deformation caused by short circuit, the variation of the circuit parameters are analyzed and simulation calculated. Transfer function is used to describe the character of the model. The original frequency spectrum is taken as reference and that after deformation is analyzed. Correlative Coefficient value is used to judge whether and how bad the deformation happens. Different kinds and levels of the deformation are simulated and the results can match the data from field experiments. Some guide criteria for the detection of winding deformation is presented.
Novel face recognition based on individual eigen-subspaces

In this paper, a novel method of face recognition based on individual eigen-subspaces is presented, which is expected to tackle such problems on face recognition as the ready availability of reference samples for each subject. In the proposed method, multiple face eigensubspaces are created, with each one corresponding to one known subject privately, rather than all individuals sharing one universal subspace as in the traditional eigenface method. Compared with the traditional single subspace face representation, the proposed method captures the extrapersonal difference to the most possible extent, which is crucial to distinguish between individuals, and on the other hand, it throws away the most intrapersonal difference and noise in the input. Our experiments strongly support the proposed idea, in which 20% improvement of performance over the traditional "eigenface" has been observed when tested on the same face base.
A robust method for unknown forms analysis

This paper proposes a strategy for analyzing unknown, filled forms. First, horizontal and vertical line segments are detected, extracted and filtered. A recursive splitting and merging algorithm eliminates overlapping segments, filters false segments, and groups the segments into lines. Based on the extracted lines, an algorithm for rectangle extraction is proposed. We define the constraints between rectangles and edges. In a process of scanning the horizontal and vertical lines, candidate edges are validated and rectangles are generated if its surrounding edges and their combination are all valid. The process is recursively applied. It can tolerate large breaks in form lines, ignore irrelevant segments and deal with embedded rectangles. Experiments on a collection of forms show that our approach works well on poor quality images.
Real-time scheduling supporting VCR functionality for scalable video streaming

Digital video cassette recording (VCR) functionality enables quick and user friendly browsing of multimedia content, thus is highly desirable in streaming video application. In this paper, we propose a layer-based implementation scheme and a layer-based soft real-time scheduling algorithm for efficient implementation of scalable streaming video system to provide full VCR functionality over a dynamic wireless network. Scalable streams provide a layer-based representation for transmitting media contents. Besides the real-time constraint, unequal priorities of scalable streams at different layers and frames are taken into account to support VCR functionality in the proposed algorithms. Thus, the better usage of available bandwidth and smoother playback can be achieved in the streaming system. Simulated results show that, with the proposed algorithms, the playback quality can be efficiently improved.
An active volumetric model for 3D reconstruction

In this paper, we present an active volumetric model (AVM) for 3D reconstruction from multiple calibrated images of a scene. The AVM is a physically motivated 3D deformable model which shrinks actively under the influence of multiple simulated forces towards the real scene by throwing away some of its voxels. It provides a computational framework to integrate several constraints in an intelligible way. In the current work, we use three forces derived respectively from the smooth constraint, the compulsory silhouette constraint, and the color consistency constraint. Based on the composition of the 3 forces, our algorithm can significantly restrain holes and floating voxels, which plague voxel coloring algorithms, and produce precise and smooth models. We test our algorithm by experiments based on both synthetic and real data.
An Edge-Based Median Filtering Algorithm with Consideration of Motion Vector Reliability for Adaptive Video Deinterlacing

Because of its ability to preserve signal edges while filtering out impulsive noises, median filtering is widely used in signal processing applications, e.g. deinterlacing. An edge-based median filtering (EMF) algorithm is proposed for adaptive deinterlacing. A criterion of motion vector reliability (MVR) is also introduced for better interpolation. For each motion compensated block, two motion vectors between opposite-parity fields and one between same-parity fields are taken into account. Experiments show that the proposed MVR and EMF are both very efficient. Outputs of the proposed EMF are much more similar to original progressive videos than those of objectively best EMF methods nowadays, without obvious visual distortions. Finally, the proposed EMF and MVR criterion are shown to be suitable for texture-based adaptive deinterlacing
A Compact Representation for Compressing Converted Stereo Videos

We propose a novel representation for stereo videos namely 2D-plus-depth-cue. This representation is able to encode stereo videos compactly by leveraging the by-product of a stereo video conversion process. Specifically, the depth cues are derived from an interactive labeling process during 2D-to-stereo video conversion-they are contour points of image regions and their corresponding depth models, and so forth. Using such cues and the image features of 2D video frames, the scene depth can be reliably recovered. Experimental results demonstrate that the bit rate can be saved about 10%-50% in coding a stereo video compared with multiview video coding and the 2D-plus-depth methods. In addition, since the objects are segmented in the conversion process, it is convenient to adopt the region-of-interest (ROI) coding in the proposed stereo video coding system. Experimental results show that using ROI coding, the bit rate is reduced by 30%-40% or the video quality is increased by 1.5-4 dB with the fixed bit rate.
Robust adaptive feedback linearization control for a class of MIMO uncertain nonlinear systems

A robust adaptive feedback linearization control (RAFLC) is proposed for a class of uncertain nonlinear MIMO systems. A radial basis function neural network (RBFNN) is used as an approximator for the system unknown nonlinear functions. The control input comprises of an adaptive feedback linearization controller, a sliding mode controller (SMC), an adaptive neural network compensation controller and an adaptive state feedback controller. And the robust adaptive control is used for the weight learning and compensation to the modeling error and extern disturbances. The adaptation law of neural networks weights and the design method of robust controller are given out based on the Lyapunov stability analysis. Furthermore, the proposed controller can guarantee not only global stability but also a good control performance. Simulation results show that the system can perform good tracking and has strong robustness.
A novel low-power readout structure with 1/2 sub-scan time-delay-integration and DLL-based A/D for 1024×6 infrared focal plane array

This paper presents a new low-power readout structure for 1024×6 infrared focal plane array with 1/2 sub-scan time-delay-integration (TDI) and delay-locked-loop-based (DLL-based) analog-to-digital (A/D) function. The circuit is of low power for its passive sampling, delay, and summation completed by capacitor array. Multiple-capacitor structure is also used to make the circuit suffer less from capacitor mismatch. 1/2 sub-scan function and the distribution of detector array contribute to higher resolution in the direction both along the track and across the track. And the TDI function is combined with A/D process in terms of circuit structure and timing sequence, reducing the noise and enhancing the frame rate. The 14-bit ADC is divided into coarse quantization part and fine quantization part. The former is a conventional 11-bit single-ramp ADC and the latter is realized by 8-phase clocks generated by DLL. This circuit also supports bidirectional scanning and two types of detectors whose photo-current flows into or out of the readout circuit.
Radiation detector readout circuit with two-stage charge sensitive amplifier

A two-stage charge sensitive amplifier structure suitable for silicon radiation detector with large capacitance is proposed. It has the advantage that the integration capacitor can be large to reduce the gain sensibility to detector capacitance variation without any stability problem. The feasibility of the proposed circuit is verified by comparing the simulation results with the conventional one-stage charge sensitive amplifier. A prototype of 16-channel readout circuit for electron collection has been taped out in a 0.35μm CMOS technology with a power supply of 5V. The area is 2.5×1.54mm2 with 42 pads and the power dissipation is 60mW.
A low-noise interface circuit for MEMS vibratory gyroscope

A CMOS ASIC has been designed and implemented for readout and control of MEMS vibratory gyroscopes. A low noise design is achieved by using the technique of sinusoidal chopper stabilization with a chopping frequency of 2MHz, which will effectively suppress the low frequency noise. A closed loop control method in driving mode is presented. The Chip is fabricated in a 0.35µm standard CMOS process with an area of 2.5×2.5mm2. The test is performed with a vibratory gyroscope on the condition of closed-loop control, and the measurement result shows a detecting resolution of 6aF in 100Hz bandwidth from a single 5V supply.
Gray-scale super-resolution for face recognition from low Gray-scale resolution face images

Today's camera sensors usually have a high gray-scale resolution, e.g. 256, however, due to the dramatic lighting variations, the gray-scales distributed to the face region might be far less than 256. Therefore, besides low spatial resolution, a practical face recognition system must also handle degraded face images of low gray-scale resolution (LGR). In the last decade, low spatial resolution problem has been studied prevalently, but LGR problem was rarely studied. Aiming at robust face recognition, this paper makes a first primary attempt to investigate explicitly the LGR problem and empirically reveals that LGR indeed degrades face recognition method significantly. Possible solutions to the problem are discussed and grouped into three categories: gray-scale resolution invariant features, gray-scale degradation modeling and Gray-scale Super-Resolution (GSR). Then, we propose a Coupled Subspace Analysis (CSA) based GSR method to recover the high gray-scale resolution image from a single input LGR image. Extensive experiments on FERET and CMU-PIE face databases show that the proposed method can not only dramatically increase the gray-scale resolution and visualization quality, but also impressively improve the accuracy of face recognition.
Quadratic ρ-domain based rate control algorithm for HEVC

In this paper, a novel quadratic ρ-domain frame layer rate control algorithm is proposed for Low Delay (LD) configuration in High Efficiency Video Coding (HEVC). Firstly, we propose a quadratic ρ-domain rate quantization (R-Q) model to establish the relationship between bit rate and quantization parameter. Subsequently, inspired by the specialized QP determination and reference picture set (RPS) mechanism, we design a RPS based hierarchical partition structure for rate control. Based on the hierarchical partition, an efficient hierarchical bit allocation scheme is provided. Finally, the quantization parameter (QP) is calculated via the proposed R-Q model after the bit allocation to meet the target bits. Experimental results demonstrate the proposed algorithm can significantly improve the R-D performance compared to the state-of-the-art rate control scheme for HEVC. Moreover, our proposed algorithm also provides smaller mismatch between the target bit rate and the actual bit rate.
Fast Intra-Mode and CU Size Decision for HEVC

The latest video coding standard High Efficiency Video Coding (HEVC) achieves about a 50% bit-rate reduction compared with H.264/AVC under the same perceptual video quality. For intra coding, a coding unit (CU) is recursively divided into a quadtree-based structure from the largest CU <inline-formula> <tex-math notation="LaTeX">$64 \times 64$ </tex-math></inline-formula> to the smallest CU <inline-formula> <tex-math notation="LaTeX">$8 \times 8$ </tex-math></inline-formula>. Also, up to 35 intra-prediction modes are allowed. These two techniques improve the intra-coding performance significantly. However, the encoding complexity increases several times compared with H.264/AVC intra coding. In this paper, fast intra-mode decision and CU size decision are proposed to reduce the complexity of HEVC intra coding while maintaining the rate-distortion (RD) performance. For fast intra-mode decision, a gradient-based method is proposed to reduce the candidate modes for rough mode decision and RD optimization. For fast CU size decision, the homogenous CUs are early terminated first. Then two linear support vector machines that employ the depth difference and HAD cost ratio (and RD cost ratio) as features are proposed to perform the decisions of early CU split and early CU termination for the rest of the CUs. Experimental results show that the proposed fast intra-coding algorithm achieves about a 54% encoding time reduction on average with only a 0.7% BD-rate increase for the HEVC reference software HM 14.0 under all-intra configuration.
A CMOS TDI readout circuit for infrared focal plane array

A new structure 288 × 4 CMOS time delay and integration (TDI) readout integrated circuit (ROIC) is presented in this paper. The TDI function is implemented using an integration and storage circuit array and a charge amplifier with the advantages of low power and compact layout. An experimental chip has been designed and fabricated in 0.5 ¿m double-poly-three-metal CMOS technology. Bi-directional TDI, defective element deselection and two-gain option (1.015 pC/2.03 pC) functions have been realized in the experimental chip and measurement results at liquid nitrogen temperature indicated that all functions were correct and performance satisfied the requirement of long waveform IRFPA. The readout speed of each out can reach 5 MHz and the dynamic range is 75.6 dB.