nils-herrmann/clean_scirepeval huggingface dataset:
Image Quality Assessment with Degradation on Spatial Structure

In this letter, we introduce an improved structural degradation based image quality assessment (IQA) method. Most of the existing structural similarity based IQA metrics mainly consider the spatial contrast degradation but have not fully considered the changes on the spatial distribution of structures. Since the human visual system (HVS) is sensitive to degradations on both spatial contrast and spatial distribution, both factors need to be considered for IQA. In order to measure the structural degradation on spatial distribution, the local binary patterns (LBPs) are first employed to extract structural information. And then, the LBP shift between the reference and distorted images is computed, because noise distorts structural patterns. Finally, the spatial contrast degradation on each pair of LBP shifts is calculated for quality assessment. Experimental results on three large benchmark databases confirm that the proposed IQA method is highly consistent with the subjective perception.
Low Delay Perfect Reconstruction Transmultiplexer with Coefficients in Low Dynamical Range

A method for designing low delay perfect reconstruction transmultiplexer (PR-TMUX) with coefficients in low dynamical range is presented in this paper. The design of PR-TMUX can be formulated as a factorization, which is based on an improvement of lifting scheme proposed by author for a nearly PR-CMFB. The factorization procedure is described as multi-ramose tree-structure. A heuristic-searching algorithm based on this structure was proposed to find the coefficients filter banks with low dynamical range. The given example shows the proposed method is effective.
Image denoising based on translation invariant Directional Lifting

Adaptive Directional Lifting (ADL) has been successfully implemented in image compression and denoising due to the feature of simple structure and flexible directional selectivity. However, image denoising by means of ADL introduces many visual artifacts caused by Gibbs phenomena due to the lack of translation invariance. In this paper, we propose a translation invariant directional lifting (TI-DL) by employing the cycle-spinning based technique to reduce artifacts in denoising results. Moreover, the inefficiency and high computational complexity of the orientation estimation technique in ADL strongly influences the performance. In order to achieve better denoising results, in this paper, 2-D Gabor filters are adopted for orientation estimation to achieve better orientation estimation results with lower complexity. Experimental results demonstrate that the proposed method achieves state-of-art denoising performance in terms of both objective (PSNR) and subjective (SSIM) evaluation.
A simple design method of linear-phase nonuniform filter banks with integer decimation factors

In this paper, we propose a simple method for designing linear-phase (LP) nonuniform filter banks (NUFBs) with integer decimation factors. The NUFBs are constructed in a direct structure. We derive a design criterion for the NUFB. With this criterion, the NUFBs can be designed simply and efficiently. By using the proposed method, near-perfect-reconstruction LP NUFBs with high stopband attenuation are obtained.
Learning-based recovery of compressive sensing with application in multiple description coding

The recently proposed compressive sensing (CS) theory provides a new solution for multiple description coding (MDC) with fine granularity, by treating each random CS measurement as a description. The performance of CS-based MDC (CS-MDC) depends on the efficacy of the CS recovery algorithm. Existing CS recovery algorithms recover the signal in a fixed space (e.g., Wavelet, DCT, and gradient spaces) for the entire duration of the signal, even though a typical multimedia signal exhibits sparsity in time/space variant spaces. To rectify this problem and develop a better CS recovery algorithm for CSMDC, we propose a learning-based framework to conduct the CS recovery in locally adaptive spaces, and carry out a case study on image MDC. A set of prior image models are learned offline from a training set to facilitate the CS recovery in local adaptive bases. Experiments show that the learning-based CS recovery algorithm can significantly improve the performance of the previous CS-MDC technique in both PSNR and visual quality.
A scheme of parallel arithmetic coding

This paper presents a parallel arithmetic coding scheme in which supports a large degree of parallelism with a marginal cost in terms of the coding efficiency. The parallelism is brought by coding the bits using multiple arithmetic coders. We identify two types of losses in coding efficiency by breaking the dependency among the data: the loss by breaking the probability prediction process and the loss by breaking the information for context decision at the starting of each slice. We further analyze these losses quantitatively and find that the loss by breaking probability adaptation process takes the most of losses. A coding method is proposed in this paper to compensate such a loss by sending additional data. Experimental results show that our proposed method can compensate the loss well, especially for large scale parallel, whereas the overhead is moderate.
Cauchy diversity measures: a novel methodology for enhancing sparsity in compressed sensing

As a new enchanting theory, compressed sensing (CS) demonstrates that a sparse signal can be recovered through a surprisingly small number of linear measurements by solving a problem of l 1 norm minimisation (which can be thought as a special case of the signomial diversity measures). However, the traditional CS model with l 1 norm minimisation can not fully exploit the sparsity especially when the degree of sparsity increases or the measurements number reduces. In this study, the Cauchy diversity measures is incorporated into the proposed model to deal with the above difficulties. The simulation results demonstrate that under the same condition, this new model offers a superior reconstruction precision compared with the common used signomial diversity measures.
An efficient strategy for compressive SAR imaging

In conventional CS-based SAR imaging scheme, the two-dimensional (2-D) scene is vectorized into a long vector, and the physical observation mechanism is represented by a high dimensional matrix. When the scene size increases, the dimensionality of the observation matrix, the computation complexity and the reconstruction time grow tremendously. To solve this problem, a novel separable compressive SAR imaging scheme, named as SCS-SAR, is proposed. In this proposed scheme, the above 2-D observation matrix is replaced by two separable observation matrixes, one in range dimension and the other in cross-range dimension. Then the high-dimensional observation matrix can be reduced to much fewer observation parameters. As a consequence, the computational complexity can be significantly reduced, and the scene of large size can be easily reconstructed with high accuracy. Experimental results demonstrate the superior capability of the proposed imaging scheme.
Constant Weight Codes From Constant Dimension Codes and Their Applications

This paper presents a geometric approach to the construction of constant weight codes from constant dimension codes. Two classes of constant weight codes are constructed based on the incidence structures in projective and Euclidean geometries, respectively. It is shown that some known optimal codes can be re-obtained in this way. As an application, the constructed codes are used in store-and-forward networks for packet loss recovery. Their decoding is translated into that of the corresponding constant dimension codes. The decoding capability is beyond that of the bounded-distance decoding. Remarkably, for constant weight codes from Koetter-Kschischang codes, the minimum-distance decoding is achieved.
Convex Combination Based Target Localization with Noisy Angle of Arrival Measurements

Target localization based on angle of arrival (AoA) is an important branch of location estimation research. Due to the noisy measurements from sensors and the non-linear inverse trigonometry function, the AoA-based localization induces a non-convex optimization that is difficult to solve with both high speed and accuracy simultaneously. To achieve a fast and accurate algorithm, we propose a convex combination scheme. By introducing a highly accurate linear approximation to the inverse trigonometric function, the objective is converted to a convex function, which can be solved efficiently with linear least-squares approach. The key point of the convex combination scheme is to express the coordinate of the target as the convex combination of a set of virtual anchors around its real position. Simulations demonstrate that the accuracy of this method is very close to the Cramer-Rao lower bound and that the comprehensive performance, including the accuracy and speed, is significantly improved compared to other state-of-the-art methods.
Design of M-channel uniform linear-phase filter banks with near-perfect-reconstruction property

In this paper, we propose a simple but effective method for the design of M-channel uniform linear-phase (LP) filter banks. We are mainly concerned with the significant aliasing caused by the two adjacent filters, leading to a near-perfect-reconstruction (NPR) system. With some assumptions, a matching condition is drived for efficient aliasing cancellation. By using the proposed design criteria to construct each filter, the requirements imposed on the entire filter bank become those on individual filters. It greatly simplifies the design of NPR uniform LP filter banks and no objective function in the optimization is explicitly required. In addition, the proposed method is more general with no limitation on the channel number and filter length. As illustrated by examples, the proposed method can provide a simple and efficient alternative for designing NPR uniform filter banks with the expected LP property.
Wideband DOA Estimation Based on Sparse Representation in 2-D Frequency Domain

In this paper, we propose a novel sparse representation (SR)-based model for wideband direction-of-arrival (DOA) estimation. Different from the classical SR-based DOA model, which only explores the sparsity of sources in spatial space, the proposed model exhibits the sparsity through the fact that any individual wideband source is characterized as a unique oblique line passing through the origin in the 2-D frequency plane of the temporal-spatial array data. To further reduce the computation complexity during the use of such sparse property, the 2-D direction information is projected into a 1-D space. Simulations show the superior performance of our approach, even in the noise corruption and less temporal samples condition.
A new approach for constructing match wavelet to signal detection

The paper proposes a technique for constructing a wavelet matched to a given signal. The design of the match wavelet can be formulated as finding a minimal or maximal projection of a given signal on to scaling subspace. The key development is to construct the match wavelet by a structural filter bank of the wavelet rather than by a scaling function. The method can reduce the cost of calculation when decomposing a signal by wavelet. The design procedures for the match wavelet and an example for matching to an ultrasound echo are also presented.
Simultaneous Depth and Spectral Imaging With a Cross-Modal Stereo System

This letter presents a novel approach for simultaneous depth and spectral imaging with a cross-modal stereo system. Two images of the target scene are captured at the same time: one compressively sampled hyperspectral measurement and one panchromatic measurement. The underlying hyperspectral cube is first reconstructed by leveraging the compressive sensing theory, during which a self-adaptive dictionary is learned from the panchromatic measurement to facilitate the reconstruction. The depth information of the scene is then recovered by estimating a disparity map between the hyperspectral cube and the panchromatic measurement through stereo matching. This disparity map, once obtained, is used to align the hyperspectral and panchromatic measurements to boost the hyperspectral reconstruction in an iterative manner. Through hardware experiments, for the first time to our knowledge, we demonstrate a snapshot system that allows for simultaneous depth and spectral imaging. The proposed system is capable of recording depth and spectral videos of dynamic scenes.
A parallel sampling scheme for ultra-wideband signal based on the random projection

High-rate analog-to-digital converters (ADC's) are ubiquitous and critical components in advance signal processing, such as software radio and ultra wideband (UWB) radar system. In this paper, we propose an alternative parallel sampling scheme, which is based on random projection, for an ultra- wideband analog to digital conversion. The sampling rate by using proposed scheme can be reduced to 1/m Nyquist sampling rate where m is the number of parallel channel. Compared with conventional ADCs based on pulse code modulation (PCM), the proposed method makes the sub-Nyquist sampling possible. And compared with other parallel sampling scheme methods, it can be easy implemented without any apriori knowledge about the signal. And it is very suitable for sampling UWB signals with short time support. Additionally, the detail implementation structure, performance analysis and simulation results of proposed method are given.
Double-channel compressive spectral imaging via complementary code patterns

With a single shot via 2D sensors Coded Aperture Snapshot Spectral Imaging (CASSI) system can restore 3D spatial-spectral images by solving a compressive sensing problem. But the shortage of measurements may lead to unfaithful reconstruction of 3D images. In addition due to the usage of random code aperture half of the energy is blocked which makes the imaging task more challengeable. In this paper we propose a double-channel spectral imaging system. The new framework adopts a beam splitter incorporated with two original CASSI systems employing a set of novel complementary code patterns. Complementary CS measurements are acquired in this framework. Furthermore to enhance the intensity of captured light we propose a more effective alternative solution based on digital-micromirror-device (DMD). All the incident light energy is captured by the sensors in the DMD-based framework. Simulation result shows that the proposed method significantly improves the performance of compressive spectral imaging.
IMM-IPDA based maneuvering target tracking with Mobile Robot in unknown clutter environments

This paper presents a novel approach for maneuvering target tracking with mobile robot in unknown clutter environments. This issue involves both simultaneous localization and mapping (SLAM) in dynamic environments and maneuvering objects tracking (MOT), and it is referred to as the SLAMMOT problem. Our approach derived by Integrating the full covariance extend Kalman filter based SLAM(EKFSLAM) algorithm and interacting multiple model (IMM) estimation algorithm with integrated probabilistic data association (IPDA) filters. The IMM portion of our algorithm is consisted of several filters based on different object motion models to handle maneuvering objects tracking with mobile robot in unknown environment, and each filter is an IPDA to deal with the problem of clutter in object observations. Both real robot and simulation experiments are presented to show the effectiveness of this approach.
Fault Diagnosis On Power Transformers Using Non-electric Method

This paper discussed four different no-electric methods for diagnosis and troubleshooting of the large power transformers, including electron microscopy, infrared thermograph (IRT), ICP plasma emission spectrum and biological technology used for oil analysis. Practice concluded that these approaches were effective in identifying the specific faults in the transformer tanks. Successful application of these approaches also showed that interdisciplinary collaboration is a good path to resolve complex technical problems on site.
Development of Frequency Variable Inverter Based on SOPC and Nios II

Based on the technology of system on a programmable chip (SOPC), a frequency variable inverter is developed and implemented, and the field-programmable gate array (FPGA) in the series of Cyclone III manufactured by Altera Co. is utilized. By the simulation tool Matlab/Simulink, the proposed inverter is simulated. In addition, an experimental platform, by which the frequency of inverter's output voltage can be continuously regulated within the range from 5 Hz to 50 Hz, is constructed, and thus the effectiveness and feasibility of the frequency variable inverter system are verified.
Research on the over-voltage of 220kV power system caused by traction transformer's commissioning

The over-voltage of 220kV power system appeared during the commissioning of several traction transformers in Jilin Province. Analysis showed that the electromagnetic oscillating of the system caused the over-voltage of the feeding phases. After setting up an accurate simulating model used in ATP-EMTP, the adverse influence on the electric power system and the character of the oscillation over-voltage had been studied. Results showed that under the environment of these substations the amplitude of the over-voltage couldn't exceed 2.0p.u and would have little influence on electric power system.
A hierarchical approach to color image segmentation using homogeneity

In this paper, a novel hierarchical approach to color image segmentation is studied. We extend the general idea of a histogram to the homogeneity domain. In the first phase of the segmentation, uniform regions are identified via multilevel thresholding on a homogeneity histogram. While we process the homogeneity histogram, both local and global information is taken into consideration. This is particularly helpful in taking care of small objects and local variation of color images. An efficient peak-finding algorithm is employed to identify the most significant peaks of the histogram. In the second phase, we perform histogram analysis on the color feature hue for each uniform region obtained in the first phase. We successfully remove about 99.7% singularity off the original images by redefining the hue values for the unstable points according to the local information. After the hierarchical segmentation is performed, a region merging process is employed to avoid over-segmentation. CIE(L*a*b*) color space is used to measure the color difference. Experimental results have demonstrated the effectiveness and superiority of the proposed method after an extensive set of color images was tested.
Measuring RPC traffic in an OS/2 DCE environment

Distributed computing involves systems that operate across networks transparently, using the resources of multiple machines. The Open Software Foundation's Distributed Computing Environment (DCE) has evolved to address the need for a vendor-neutral platform to which distributed applications can be developed, and upon which they can run. Central to the design philosophy of DCE is its reliance on the remote procedure call (RPC) to facilitate communication among the entities in the distributed environment. Since it profoundly affects the performance of both the DCE environment and applications running on top of it, the performance of RPCs is very much a concern of both application developers and system managers in a DCE installation. This paper reports some results from an ongoing empirical investigation of the OS/2 DCE RPC facility. Our interest in this project is the effect on end-to-end RPC performance of protocol processing, flow control mechanisms within DCE, other load on the network, and interoperation with multiple DCE platforms.
Beam space-time block coding with beamforming based on cyclic statistics for wireless communications

This paper presents an approach for beamforming based on third-order cyclic statistics. The approach has fairly well accuracy. Further, a new scheme joint beamforming and space-time block coding is suggested that dual antenna arrays transmit at base station and multi-antenna elements receive at mobile terminal. This scheme improves the receiving error performance of mobile terminal and increases the capacity of the entire wireless communication system. The computer simulation validates that the aforementioned scheme is superior and effective.
Multi-agent Behavior Evolutionary Analysis on Building Energy Efficiency Economic Incentive System in China Based on Cellular Automata

Building energy efficiency (BEE) economic incentive system is an enormous system of multi-agent, which includes government departments, design institutes, construction units, real estate development enterprises, purchasers and energy service companies etc. It has a widely internal relationship and a character of multi-layer, multi-function, dynamic, open and mutually learning, so it is conformed that this system has the basic character of complex system. As a rational method to solve the problem of complex system, cellular automata (CA) can analyze the grid dynamic model which is not only discrete in temporal and spatial aspects but also partial in temporal consequence and spatial mutual relationship. Under some certain simple units and regulations, CA can simulate the complex system veritably. With the bottom-up modeling method of CA, this study establishes an evolutionary model of multi-agent for BEE economic incentive system in China through analyzing the complex character of this system. Based on the analytic result of evolving processes, it is recognized that the influence factors of promoting BEE economic incentive policy involves behavior preference, macro environment factors and different actual conditions of local regions
Research on a intelligent dual temperature box

A intelligent dual temperature box is researched in this paper. The dual temperature box utilizes cascade refrigeration system. R<sub>22</sub> is the refrigerant of high temperature circle system, and R<sub>13</sub> is the refrigerant of low temperature circle system. The R<sub>22</sub> system can operate alone or with the R<sub>13</sub> system. So the dual temperature box can achieve two vapor temperatures of -65°C and -20°C. And the refrigerant system of it can operate stable while the temperature is -65°C.
PHENOM 2000: An undergraduate project in medical instrumentation for integrated design across the curriculum

This paper describes an undergraduate design project in medical instrumentation. PHENOM stands for Personal HEart fuNctiOn Monitor. This portable, microcontroller-based device measures electrocardiogram (ECG) and photoplethysmogram (PPG). The project provides hands-on experiences for students to integrate their engineering skills in analog and digital design, microprocessor, software development, and digital signal processing and to work in a setting analogous to industrial R&D.