nils-herrmann/clean_scirepeval huggingface dataset:
Depth recovery via decomposition of polynomial and piece-wise constant signals

This paper proposes a novel decomposition model for high-quality depth recovery (DMDR) from low quality depth measurement accompanied by high-resolution RGB image. We observe that depth patches extracted from the depth map containing smooth regions separated by curves, can be decomposed simultaneously by a low-order polynomial surface and a piece-wise constant signal. In our model, the polynomial surface component is regularized by least-square polynomial smoothing, while the piece-wise constant component is constrained by total variation filtering. The model is effectively solved by the alternating direction method under the augmented Lagrangian multiplier (ALM-ADM) algorithm. Experimental results show that our method is able to handle various types of depth degradation under the designed signal decomposition model, and produces high-quality depth recovery results.
Reconstruction of GPR Signals by Spectral Analysis of the SVD Components of the Data Matrix

This letter considers the problem of reconstructing total-time responses from noisy data collected by ground-penetrating radar (GPR). The well-known singularity expansion method (SEM) - a theory - for late-time response representation is generalized to establish a matrix model (data matrix) representing total-time responses of radar scattering waveforms. Using singular value decomposition of the data matrix - an intermediate processing technique, we present an approach to model-order determination and successfully reconstruct the total-time responses. The model order is quantitatively selected by spectral analysis of left singular vectors of the data matrix and of the emitted waveform. The most important discoveries in this letter are as follows: (1) the GPR upper frequency can be used as a criterion for the selection of left singular vectors of the data matrix, and (2) the left singular vectors of the data matrix, which should not be neglected, tend to be predominantly low-pass functions and also provide valuable information for model-order determination.
A Novel Tensor-Based Video Rain Streaks Removal Approach via Utilizing Discriminatively Intrinsic Priors

Rain streaks removal is an important issue of the outdoor vision system and has been recently investigated extensively. In this paper, we propose a novel tensor based video rain streaks removal approach by fully considering the discriminatively intrinsic characteristics of rain streaks and clean videos, which needs neither rain detection nor time-consuming dictionary learning stage. In specific, on the one hand, rain streaks are sparse and smooth along the raindrops direction, and on the other hand, the clean videos possess smoothness along the rain-perpendicular direction and global and local correlation along time direction. We use the l1 norm to enhance the sparsity of the underlying rain, two unidirectional Total Variation (TV) regularizers to guarantee the different discriminative smoothness, and a tensor nuclear norm and a time directional difference operator to characterize the exclusive correlation of the clean video along time. Alternation direction method of multipliers (ADMM) is employed to solve the proposed concise tensor based convex model. Experiments implemented on synthetic and real data substantiate the effectiveness and efficiency of the proposed method. Under comprehensive quantitative performance measures, our approach outperforms other state-of-the-art methods.
A hybrid algorithm based on simplex search and differential evolution for hybrid flow-shop scheduling

An effective hybrid algorithm by merging the searching mechanisms of Nelder-Mead (NM) simplex method and differential evolution (DE) is proposed to solve the hybrid flow-shop problem (HFSP) in this paper. By using a special encoding, the NM and DE methods can be used to solve permutation based combinatorial optimization problems. By combining the DE based global search and NM method based local search, the exploration and exploitation abilities are enhanced and well balanced for solving the HFSP. Numerical testing results and comparisons show that the proposed algorithm is effective, efficient and robust in solving the HFSP.
Enhanced Magnetic Field Sensitivity in Magnetoelectric Composite Based on Positive Magnetostrictive/Negative Magnetostrictive/Piezoelectric Laminate Heterostructure

Resonance magnetoelectric (ME) responses are investigated for the ME laminate heterostructure consisting of positive magnetostrictive material FeCuNbSiB, negative magnetostrictive material Ni and piezoelectric material PZT-8. On one hand, both a built-in magnetic field induced by the strong magnetic interactions between positive magnetostrictive and negative magnetostrictive materials and an intrinsic anisotropic field with obvious hysteresis and remnant magnetization in Ni layer result in a large zero-biased ME effect. The corresponding zero-biased ME voltage coefficient reaches 10.12 V/Oe (126.5 V/cm Oe), which is about 3 times larger than that of traditional Ni/PZT-8 (NP) laminate. On the other hand, the additional stress produced by the high magnetic permeability FeCuNbSiB layer enhances the magnetostriction of Ni layer and ME response. The corresponding maximum ME voltage coefficient (dV<sub>ME</sub>/dH<sub>ac</sub>) is 12.09 V/Oe (150.87 V/cm Oe) at bias magnetic field <inline-formula> <tex-math notation="LaTeX">$H_{\mathrm {dc}} = 4$ </tex-math></inline-formula> Oe. It is further found that even a step change of ac magnetic field less than 10<sup>−10</sup> T can be clearly distinguished by the proposed ME composite. The value of ME voltage sensitivity to dc magnetic fields (dV<sub>ME</sub>/dH<inline-formula> <tex-math notation="LaTeX">$_{\mathrm {dc}})$ </tex-math></inline-formula> reaches ~76.7 mV/Oe at <inline-formula> <tex-math notation="LaTeX">$H_{\mathrm {dc}}= 5$ </tex-math></inline-formula> Oe and <inline-formula> <tex-math notation="LaTeX">$H_{\mathrm {ac}} =0.1$ </tex-math></inline-formula> Oe. Correspondingly, the proposed laminate heterostructure is able to possess both strong ac and dc magnetic field sensitivities.
Analysis of the decorrelation effect under spatial smoothing techniques

The authors analyze the decorrelation effect of two spatial smoothing methods when incoming narrowband signals are correlated. The performance analysis is based on the magnitude of the correlation coefficient of two correlated sources. With the same array size, the forward-backward smoothing at least performs better than the forward-only in terms of a smaller smoothed correlation coefficient. From the results of computer simulations, it is shown that forward-backward smoothing outperforms forward-only smoothing in all circumstances and provides a better possibility to attain a full decorrelation, i.e. the correlation coefficient is zero.<<ETX>>
Error control and concealment for video communication: a review

The problem of error control and concealment in video communication is becoming increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks and the Internet. This paper reviews the techniques that have been developed for error control and concealment. These techniques are described in three categories according to the roles that the encoder and decoder play in the underlying approaches. Forward error concealment includes methods that add redundancy at the source end to enhance error resilience of the coded bit streams. Error concealment by postprocessing refers to operations at the decoder to recover the damaged areas based on characteristics of image and video signals. Last, interactive error concealment covers techniques that are dependent on a dialogue between the source and destination. Both current research activities and practice in international standards are covered.
A new algorithm for remotely sensed image texture classification and segmentation

We propose a new algorithm for remotely sensed image texture classification and segmentation in this paper. We observe that the traditional method LSE is unstable in practical applications. This motivates us to develop more stable method. We have proposed the regularization technique to suppress the instability of LSE in previous research. Our contribution in this paper is that we propose a new stable method, which is based on the total variation, abbreviated TV, for reducing instability in texture analysis, and apply which to remotely sensed image texture classification and segmentation. Experiment results on remotely sensed images demonstrate our new algorithm is superior to LSE and seems promising in applications.
Improved convolutional neural network based scene classification using long short-term memory and label relations

Convolutional neural network (CNN) is more and more important in pattern recognition. In this work, we adopt label relations and long short-term memory (LSTM) to develop an accurate CNN-based scene classification algorithm. Traditional scene classification algorithms assume that labels are mutually exclusive. However, this is not reasonable when an image has a variety of objects and hence has multiple labels. In this work, we apply two label relations, which are exclusive and hierarchy relations, to improve the accuracy of multiple-label scene classification. For example, it is impossible that an image has both the labels of “factory” and “garden”. If the label “factory” is assigned to an image, the probability that it has the label of “garden” should be lowered. We also use image captioning to construct a scene classification model and propose an LSTM based method to further explore label relations and obtain more accurate results for scenic image labeling.
Highly accurate SLC image coregistration in InSAR processing technique

In this paper, we present a linear and nonlinear joint algorithm for the InSAR image coregistration which could be used in highly decorrelated real scenes. First, a coarse coregistration is performed by using an improved consistency testing method which is based on integrating correlation coregistration and max-spectrum image coregistration. Second, we choose control points, and then select different sampling period by using the non-linear method based on coregistration quality parameter curved surface. Our initial results suggest that this approach can not only obtain highly accurate coregistration but also satisfy the requirement of the accurate coregistration for projects. (6 pages)
A novel cost-efficient on-line intermediate waveband-switching scheme in WDM mesh networks

Waveband switching (WBS) is an important technique to save switching and transmission cost in wavelength-division multiplexed (WDM) optical networks. A cost-efficient WBS scheme would enable network carriers to increase the network throughput (revenue) while achieving significant cost savings. We identify the critical factors that determine the WBS network throughput and switching cost and propose a novel intermediate waveband switching (IT-WBS) algorithm, called the minimizing-weighted-cost (MWC) algorithm. The MWC algorithm defines a cost for each candidate route of a call. By selecting the route with the smallest weighted cost, MWC balances between minimizing the call blocking probability and minimizing the network switching cost. Our simulations show that MWC outperforms other wavelength/waveband switching algorithms and can enhance the network throughput at a reduced cost
Automatic detection of fence completeness for high-speed railway

In this paper, an automatic detection system of fence completeness for high-speed railway was proposed. This system uses two cameras installed on CIT (Composited Inspection Train) to shoot the fence on each side individually, and then transmit the images by optic fiber to a computer, which processes the images and recognizes the completeness of the fence automatically. The system will recode any loss or breakage as a reference for maintenance. The architecture of the system and the detection algorithm are introduced in this paper, at last the experiment results are given, which show that the system proposed in this paper detects the breakage of the fence efficiently with very few incorrect judgments.
Perceptually motivated pre-filter for speech enhancement using Kalman filtering

This paper proposes a novel pre-filter for Kalman filter based speech enhancement. Our aim is to reduce coloured noise, while retaining speech quality by exploiting the properties of the human auditory system. The proposed pre-filter uses temporal and simultaneous masking thresholds to shape the noisy speech spectrum in order to obtain a better estimate of the AR coefficients. These coefficients are then used to obtain a perceptual filter to weight the noise spectrum before applying the Kalman filter. The proposed noise reduction technique is compared to the Wiener filter, perceptual Wiener filter and the standard Kalman filter in 5 dB car noise environments. PESQ scores and subjective test results show that the proposed pre- filter based enhancement outperforms other common techniques.
Design and implementation of a high quality DV50-MPEG2 software transcoder

This paper describes the design and implementation of a high quality DCT-domain DV50 to MPEG2 (I only) real-time software transcoder. Such a transcoder facilitates the interoperability between the two video compression standards, widely adopted by both consumers and broadcasters. There are multiple challenges in implementing such a software-based real-time high quality transcoder, given the high data rates involved and the differences between the two compression formats in terms of code block structures and DCT formats. We outline several new video transcoding algorithms, including a novel parameter-based VLC bit count prediction algorithm that greatly improves the efficiency of DV transcoding/encoding.
Improvements to APSK constellation with gray mapping

Amplitude phase shift keying (APSK) constellation with gray mapping proposed in  provides considerable shaping gain compared with quadrature amplitude modulation (QAM). In this paper, some improvements to APSK Constellation with gray mapping are addressed. AP-SK constellation with gray mapping could be adjusted according to different SNR levels to increase its average mutual information (AMI). Two methods to improve AMI, on phase and on amplitude, are proposed. Both AMI of coded modulation (CM-AMI) and AMI of bit-interleaved coded modulation (BICM-AMI) are considered. The improvements are verified by bit error rate simulations in both independent and iterative demapping scenarios.
A release-on-demand wireless CMOS drug delivery SoC based on electrothermal activation technique

Recently, micro- and nano-technologies have enabled rapid progress in biomedical applications. Although in vitro analytical and diagnostic tools have been the focus of such technologies, in vivo therapeutic and sensing applications have received significant attention in the past few years. Novel implantable drug delivery devices, which can precisely control key therapy parameters, have the potential to increase the efficacy of drug therapy . This paper presents an implantable CMOS drug delivery SoC, in which a wireless controller/actuation circuitry and a drug delivery array are monolithically integrated. Compared with current technologies, the advantages of the proposed device include lower system cost, smaller device size and lower power consumption. This device can be implanted by minimally invasive surgery and is suitable for the localized diagnosis/therapy of cancers, or the immediate treatment of unpredictable heart attacks  by releasing drugs such as nonapeptide leuprolide acetate or nitroglycerin. Physicians can also make non-invasive therapy modification by using the wireless capability.
A hybrid simplex differential evolution algorithm

According to the disadvantage of slow convergence rate of the basic differential evolution (DE) algorithm, a hybrid optimization algorithm incorporated Nelder & Mead (NM) simplex method into the basic DE algorithm is presented in this paper. This hybrid procedure performed the exploration with DE and the exploitation with the NM simplex method. Sensitivity to the control parameters of the proposed approach is analyzed. The computational results on several classical Benchmarks nonlinear complex functions show that the hybrid optimization algorithm is superior to the two original search techniques (i.e. NM and DE) in terms of solution quality and convergence rate. Compared with other DE variants, the proposed algorithm has better convergence performance and robustness. The Wilcoxon non-parametric statistical tests also confirm the above claims.
Super-resolution reconstruction of hyperspectral images via low rank tensor modeling and total variation regularization

In this paper, we propose a novel approach to hyperspectral image super-resolution by modeling the global spatial-and-spectral correlation and local smoothness properties over hyperspectral images. Specifically, we utilize the tensor nuclear norm and tensor folded-concave penalty functions to describe the global spatial-and-spectral correlation hidden in hyperspectral images, and 3D total variation (TV) to characterize the local spatial-and-spectral smoothness across all hyperspectral bands. Then, we develop an efficient algorithm for solving the resulting optimization problem by combing the local linear approximation (LLA) strategy and alternative direction method of multipliers (ADMM). Experimental results on one hyperspectral image dataset illustrate the merits of the proposed approach.
Analyzing BTI effects on retention registers

As Bias Temperature Instability (BTI) effects increase the threshold voltage of transistors and decrease transistors speed, it has become a major problem for circuit reliability. Retention registers are the widely used storage cells in the power gating architecture. These registers can keep the current states in the always-on blocks. However, they suffer from significant BTl effects because the always-on block suffers from significant aging effects. This paper investigates the aging effect on various D-type retention registers. First, the paper analyzes the setup, hold and required times of retention registers under differing BTl effects. Second, because the always-on block always suffers from the BTl effects, the required time to store the data in an always-on block increases by between 0.6x-1.4x in 32nm technology. Finally, the selective transistor sizing technique is used to improve the setup, hold and required times of various D-type retention registers. Increasing the sizing of transistors between 20%-90% results in an improvement between 8.9%-41.2% in both setup and hold time.
Power plants Automatic Voltage and reactive power control system application analysis

Power quality is directly related to stability of grid security and product quality for power users, and reactive power is an important factor to affect the power quality. Therefore, power system reactive power balance is to ensure the basic conditions of the voltage quality. AVC system to adjust the reactive power output of power plants, so that the voltage deviation remains within the limits prescribed. This article describes the control strategy and operation of power plants AVC system, summed up the test and the implementation effect of the AVC system from power plants put into operation, and finally gives some technical problems that need attention in the AVC system from power plants put into operation.
Evaluation of different descriptors for identifying similar video shots

In this paper, three techniques for video sequence retrieval which use statistical measures of color patterns in shots are proposed and compared. The first technique is based on a correlation of the MPEG7 Dominant Color Descriptor (DC)  as single characteristic feature of a shot. The second approach is to model color pattern distribution in a shot with a codebook, obtained by VQ (Vector Quantization) of the frame blocks composing the shot. The last one models the color pattern distribution using a GMM (Gaussian Mixture Model). Such descriptors are used to establish correspondence between non consecutive camera records through an appropriately designed similarity measure. As such, a new distance measure is used in the comparison between the shot descriptors, by extending the metric proposed in . A comparison is made of the dissimilarity performance associated with each of the three proposed descriptors, demonstrating the superior results obtainable with the VQ based approach.
Fuzzy Rough Modeling Approach: Based on Fuzzy Clustering and GA Search Strategy

A method to construct fuzzy rough model is proposed. By means of adaptive Gaustafason-Kessel (G-K) clustering algorithm, fuzzy partition can be accomplished and corresponding fuzzy clusters are achieved in data space. Then based on the search of cluster number and attribute subsets through GA search strategy, optimal FRM will be found, and a decision model can be built. The experiment results indicate that FRM method is superior to traditional Bayesian and learning vector quantization (LVQ) methods, moreover, it has more powerful generalization ability. Also, experiment results show that it is favorable to obtain better FRM model if the search of reductive attribute subsets is considered.
Robust Regenerative Charging Control Based on T–S Fuzzy Sliding-Mode Approach for Advanced Electric Vehicle

This work presents a robust regenerative charging (RC) control scheme for the brushless dc (BLDC) motor drives in advanced electric vehicle (EV). After analyzing the equivalent circuit of the bidirectional ac-dc converter, we first derive the mathematical model under RC mode by using state-space averaging method. Then, we originally formulate the Tagaki-Sugeno (T-S) fuzzy model to represent its nonlinear dynamics. By combining the merits ofT-S fuzzy technique with sliding-mode control (SMC) method, we develop a T-S fuzzy SMC (TSFSMC)-based constant-voltage (CV) charging control to guarantee both high performance and robust stability. Moreover, comparing to conventional methods, we declare that TSFSMC does not need the input channel to be identical and can simultaneously achieve dual goals of electric braking and RC without any additional devices. We have implemented a control prototype to analyze and confirm the validity of TSFSMC. Results show that high charging performance and significant efficiency improvement are obtained.
A Bus-Encoding Scheme for Crosstalk Elimination in High-Performance Processor Design

A crosstalk effect leads to increases in delay and power consumption and, in the worst-case scenario, to inaccurate results. With the scale down of technology to deep-submicrometer level, the crosstalk effect between adjacent wires becomes more and more serious, particularly between long on-chip buses. In this paper, we propose a deassembler/assembler technique to eliminate undesirable crosstalk effects on bus transmission. By taking advantage of the prefetch process, where the instruction/data fetch rate is always higher than the instruction/data commit rate, the proposed method incurs almost no penalty in terms of dynamic instruction count. In addition, when the bus width is 128 b, the required number of extra bus wires is only 7 as compared to the 85 extra bus wires needed in the work of Victor and Keutzer.