Image quality assessment (IQA) algorithms aim to predict perceived image quality by human observers. Over the last two decades, a large amount of work has been carried out in the field. New ...algorithms are being developed at a rapid rate in different areas of IQA, but are often tested and compared with limited existing models using out-of-date test data. There is a significant gap when it comes to large-scale performance evaluation studies that include a wide variety of test data and competing algorithms. In this work we aim to fill this gap by carrying out the largest performance evaluation study so far. We test the performance of 43 full-reference (FR), seven fused FR (22 versions), and 14 no-reference (NR) methods on nine subject-rated IQA datasets, of which five contain singly distorted images and four contain multiply distorted content. We use a variety of performance evaluation and statistical significance testing criteria. Our findings not only point to the top performing FR and NR IQA methods, but also highlight the performance gap between them. In addition, we have also conducted a comparative study on FR fusion methods, and an important discovery is that rank aggregation based FR fusion is able to outperform not only other FR fusion approaches but also the top performing FR methods. It may be used to annotate IQA datasets as a possible alternative to subjective ratings, especially in situations where it is not possible to obtain human opinions, such as in the case of large-scale datasets composed of thousands or even millions of images.
The effects of heat treatment before extrusion on the dynamic recrystallization (DRX) behavior, texture, and mechanical properties of the extruded Mg-9.8Gd-3.5Y-2.0Zn-0.4Zr (wt. %) alloy were ...comparatively investigated in this work. A large number of dendritic microstructures in as-homogenized alloy and intergranular block-shaped LPSO phases in as-aged alloy were found to promote the operation of particle-stimulated nucleation (PSN) and discontinuous dynamic recrystallization (DDRX) mechanisms, which further accelerate growth of dynamic recrystallized grains due to the lack of solute drag and dynamic precipitation. Also, we determined the nucleation of dynamic recrystallization affects little to the formation of abnormal texture, whereas the shear stress results from the flow velocity gradient and the pyramidal-2 slip during the growth of the dynamic recrystallized grains leading the formation of abnormal texture. However, the solution treatment before extrusion could effectively eliminate the dendritic microstructures and increase the solid solubility of the matrix, which would facilitate the occurrence of continuous dynamic recrystallization (CDRX) and dynamic precipitation during the hot extrusion process. Meanwhile, CDRX and dynamic precipitation co-contribute to the formation of a bimodal microstructure that composed of coarse deformed grains with basal orientation and fine dynamic recrystallized grains with random orientation. The observed bimodal microstructure, fine dynamic precipitations, strong fiber texture, and substructure thus well explained the improved strength and elongation of samples extruded with the solution treated materials.
Multi-area economic dispatch (MAED) characterized by high non-convexity and non-linearity is an important issue in power system operation. This paper presents an improved stochastic fractal search ...(ISFS) to solve the MAED problem considering the area load demands, the tie-line limits and various operating constraints. To balance exploration and exploitation, the ISFS introduces an opposition-based learning method for population initialization as well as for generation jumping. By combining with the differential evolution strategy, a hybrid diffusion process is developed and used as the local search technique to enhance the exploitation ability. Furthermore, a novel repair-based penalty approach is presented and incorporated into the ISFS to find feasible solutions more efficiently. The effectiveness and robustness of the ISFS is evaluated on several test systems consisting of 16–120 generating units. Computational results demonstrate the superiority of the proposed ISFS scheme over the state-of-the-art algorithms.
•An effective improved stochastic fractal search algorithm is proposed.•The proposed algorithm is applied to solve multi-area economic dispatch problem.•A novel repair-based penalty approach is presented to handle constraint violations.•Computational results demonstrate the effectiveness of the proposed algorithm.
Ammonia (NH3) synthesis is an important industrial chemical process. Recently, electrochemically converting the earth-abundant dinitrogen (N2) in the aqueous phase to NH3 at ambient conditions has ...been proposed as an alternative to the well-established Haber–Bosch process. Catalysts for the electrochemical N2 reduction to NH3 play crucial roles in realizing this NH3 synthesis route. Electrochemical N2 reduction has been studied for decades, and many studies have emerged in the past few years. Herein, we provide a comprehensive review to summarize various catalysts used for achieving electrochemical N2 reduction to NH3, including homogeneous, heterogeneous and biological catalysts, as well as relevant computational studies to understand their reaction mechanisms. We compare the advantages and shortcomings of these catalytic systems. Future research directions for realizing catalysts with low overpotentials, high energy efficiency, good scalability, and stability modularity are also proposed. This review provides an overview of this fast-growing research field and encourages more studies toward the rational design of catalysts for electrochemical N2 reduction to NH3 under ambient conditions.
The conversion of methane to upgraded fuels and higher-value chemicals such as hydrogen, methanol, and olefins is a promising technology in the supply of chemicals and energy. However, current ...commercial methane conversion technology suffers from intense energy consumption. It is highly desirable to develop novel technologies for methane conversion with improved efficiency and lower cost. Solar energy, the most abundant and clean renewable energy, has been utilized as a new stimulus to drive methane conversion under mild conditions. In this review, recent achievements in solar-energy-mediated catalytic methane conversion are highlighted. We focus on the photocatalytic conversion of methane in photocatalytic systems, photoelectrochemical systems, and photoenhanced thermocatalytic systems. We discuss the challenges and prospects of future research on solar-energy-mediated methane conversion and aim to acquire in-depth understanding of the photo-mediated activation of the C–H bond and provide guidelines for the design of highly efficient catalysts.
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The conversion of methane to value-added fuels and chemicals is a promising route in the supply of chemicals and energy, which has received intense attention recently. The industrial route for methane conversion via steam reforming requires high temperatures (typically >700°C), consumes massive energy, and results in high capital costs. The development of novel technologies for methane conversion with improved efficiency and lower cost is highly demanded. Solar energy, an abundant and renewable energy, has been utilized as a new stimulus to drive methane conversion.
In this review, we focus on recent progress of solar-energy-mediated methane conversion under mild conditions. We first present the fundamentals of photoactivation of methane from photocatalytic, photoelectrochemical, and photothermal aspects. The semiconductors and nanometals with noteworthy C–H bond activation performance for direct methane conversion are highlighted. The recent advances in photocatalytic, photoelectrocatalytic, and photoenhanced thermocatalytic methane conversion at low temperature by solar energy are then introduced. Finally, we summarize the major challenges and opportunities in the catalyst design, utilization of solar light, inhibition of over-oxidation of methane, and mechanistic study of methane activation, etc.
Solar energy is capable of producing active species at low temperature over semiconductors and nanometals with unique photophysical properties. The recent progress of solar-energy-mediated methane conversion in photocatalytic systems, photoelectrocatalytic systems, and photoenhanced thermocatalytic systems is reviewed. Major opportunities and challenges in this field are discussed as well. This review aims to acquire in-depth understanding of the photo-mediated activation of the C–H bond and provide guidelines for the design of highly efficient catalysts.
Reduced-reference image quality assessment (RR-IQA) provides a practical solution for automatic image quality evaluations in various applications where only partial information about the original ...reference image is accessible. In this paper, we propose an RR-IQA method by estimating the structural similarity index (SSIM), which is a widely used full-reference (FR) image quality measure shown to be a good indicator of perceptual image quality. Specifically, we extract statistical features from a multiscale multiorientation divisive normalization transform and develop a distortion measure by following the philosophy in the construction of SSIM. We find an interesting linear relationship between the FR SSIM measure and our RR estimate when the image distortion type is fixed. A regression-by-discretization method is then applied to normalize our measure across image distortion types. We use six publicly available subject-rated databases to test the proposed RR-SSIM method, which shows strong correlations with both SSIM and subjective quality evaluations. Finally, we introduce the novel idea of partially repairing an image using RR features and use deblurring as an example to demonstrate its application.
The great content diversity of real-world digital images poses a grand challenge to image quality assessment (IQA) models, which are traditionally designed and validated on a handful of commonly used ...IQA databases with very limited content variation. To test the generalization capability and to facilitate the wide usage of IQA techniques in real-world applications, we establish a large-scale database named the Waterloo Exploration Database, which in its current state contains 4744 pristine natural images and 94 880 distorted images created from them. Instead of collecting the mean opinion score for each image via subjective testing, which is extremely difficult if not impossible, we present three alternative test criteria to evaluate the performance of IQA models, namely, the pristine/distorted image discriminability test, the listwise ranking consistency test, and the pairwise preference consistency test (P-test). We compare 20 well-known IQA models using the proposed criteria, which not only provide a stronger test in a more challenging testing environment for existing models, but also demonstrate the additional benefits of using the proposed database. For example, in the P-test, even for the best performing no-reference IQA model, more than 6 million failure cases against the model are "discovered" automatically out of over 1 billion test pairs. Furthermore, we discuss how the new database may be exploited using innovative approaches in the future, to reveal the weaknesses of existing IQA models, to provide insights on how to improve the models, and to shed light on how the next-generation IQA models may be developed. The database and codes are made publicly available at: https://ece.uwaterloo.ca/~k29ma/exploration/.
We investigate closed-loop supply chains (CLSCs) under four reverse channel structures where a central planner, a manufacturer (M), a retailer (R) or a third party (T), respectively, serves as the ...collector of used product and demand depends on R's marketing effort. We derive supply chain profitability under both the centralised and decentralised CLSCs and furnish the optimal marketing effort, collection rate and pricing decisions for the supply chain members. We then extend the base models along two directions: the first extension incorporates R's distributional fairness concerns into the M collection model and the second extension considers potential recycle cost advantages by R and T compared to the M collection model.
•The MVO algorithm is deeply studied by integrating several novel local search heuristics.•A hybrid algorithm called HMVO is proposed for solving the FFJSP.•The performance of the HMVO is evaluated ...by using three benchmark sets.•New best solutions are obtained by the proposed hybrid scheme.
In this paper, a novel algorithm called hybrid multi-verse optimization (HMVO) is proposed to address the fuzzy flexible job-shop scheduling problem (FFJSP). Firstly, path relinking technique is introduced to mimic the process of swapping objects through the black/white holes. Secondly, a mixed phase which integrates insertion-based heuristic and path relinking technique is incorporated into the algorithm to enlarge the search space. Thirdly, pairwise-based local search is proposed as a hybrid strategy to improve the solution quality. Finally, extensive experiments are conducted on three benchmark sets to investigate the performance of the proposed HMVO. Computational results and comparisons with some existing meta-heuristics demonstrate the competitive efficiency and effectiveness of the proposed algorithm.
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