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- 实验方案
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Fusion of Multi-Temporal Interferometric Coherence and Optical Image Data for the 2016 Kumamoto Earthquake Damage Assessment
摘要： Earthquakes are one of the most devastating types of natural disasters, and happen with little to no warning. This study combined Landsat-8 and interferometric ALOS-2 coherence data without training area techniques by classifying the remote sensing ratios of specific features for damage assessment. Waterbodies and highly vegetated areas were extracted by the modified normalized difference water index (MNDWI) and normalized difference vegetation index (NDVI), respectively, from after-earthquake images in order to improve the accuracy of damage maps. Urban areas were classified from pre-event interferometric coherence data. The affected areas from the earthquake were detected with the normalized difference (ND) between the pre- and co-event interferometric coherence. The results presented three damage types; namely, damage to buildings caused by ground motion, liquefaction, and landslides. The overall accuracy (94%) of the confusion matrix was excellent. Results for urban areas were divided into three damage levels (e.g., none–slight, slight–heavy, heavy–destructive) at a high (90%) overall accuracy level. Moreover, data on buildings damaged by liquefaction and landslides were in good agreement with field survey information. Overall, this study illustrates an effective damage assessment mapping approach that can support post-earthquake management activities for future events, especially in areas where geographical data are sparse.
关键词： damage assessment,Landsat-8,ALOS-2 interferometric coherence,urban damage area,liquefaction,landslides,Kumamoto earthquake
更新于2025-09-23 15:23:52
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Life Cycle Analysis of Double-Arm Type Robotic Tools for LCD Panel Handling
摘要： This study includes a life cycle assessment of double-arm type robotic tools made with three different materials. The robotic arms are used for Liquid Crystal Display (LCD) panel handling. The environmental impacts generated during all the life stages of the robots have been investigated. The study shows that composite materials have less environmental impact compared with metallic materials. It is also found that the most significant impact category generated by the robotic tools is carcinogen, while the use stage of the robotic tool's life cycle has the greatest environmental impact.
关键词： environmental impact,robotic tool,green manufacturing,life cycle assessment
更新于2025-09-23 15:23:52
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Assessment of concentrated solar power (CSP) technologies based on a modified intuitionistic fuzzy topsis and trigonometric entropy weights
摘要： Concentrated solar power (CSP) technology has shown considerable long-term growth with varying levels of peak development and stall phases over the years. More and more countries are finding CSP technology attractive for the production of electricity and other applications. CSP offers a variety of applications where solar power can be used appropriately, although the debate about which CSP technology has a better future perspective is still ongoing. This technology sector has seen a multitude of advancements and technological innovations. These improvements are primarily concerned with the design of the collectors and the related materials they are made from, the heat transfer processes, and the production and accumulation of energy. In order to assess these CSP technologies, in this paper we propose a fuzzy multi-criteria method. Then, Solar tower (ST), Parabolic solar trough (PST), Compact linear Fresnel reflector (CLFR), and Dish Stirling (DS) are evaluated using a modified intuitionistic fuzzy TOPSIS with a trigonometric entropy vector weight.
关键词： Sustainability,Concentrated solar power (CSP),Trigonometric entropy,Technological assessment,Intuitionistic fuzzy TOPSIS
更新于2025-09-23 15:23:52
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Blind Noisy Image Quality Assessment Using Sub-Band Kurtosis
摘要： Noise that afflicts natural images, regardless of the source, generally disturbs the perception of image quality by introducing a high-frequency random element that, when severe, can mask image content. Except at very low levels, where it may play a purpose, it is annoying. There exist significant statistical differences between distortion-free natural images and noisy images that become evident upon comparing the empirical probability distribution histograms of their discrete wavelet transform (DWT) coefficients. The DWT coefficients of low- or no-noise natural images have leptokurtic, peaky distributions with heavy tails; while noisy images tend to be platykurtic with less peaky distributions and shallower tails. The sample kurtosis is a natural measure of the peakedness and tail weight of the distributions of random variables. Here, we study the efficacy of the sample kurtosis of image wavelet coefficients as a feature driving an extreme learning machine which learns to map kurtosis values into perceptual quality scores. The model is trained and tested on five types of noisy images, including additive white Gaussian noise, additive Gaussian color noise, impulse noise, masked noise, and high-frequency noise from the LIVE, CSIQ, TID2008, and TID2013 image quality databases. The experimental results show that the trained model has better quality evaluation performance on noisy images than existing blind noise assessment models, while also outperforming general-purpose blind and full-reference image quality assessment methods.
关键词： sub-band,discrete wavelet transform (DWT),extreme learning machine (ELM),kurtosis,Blind noisy image quality assessment
更新于2025-09-23 15:23:52
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Hyperspectral imaging for non-destructive prediction of total nitrogen concentration in almond kernels
摘要： There is increasing awareness of the need to consume high-quality foods because of health concerns. Food safety and health awareness campaigns have provided an impetus for non-destructive and real-time methods for food quality assessment. Total nitrogen is used as an indicator of crude protein content in foods and we examined the potential of hyperspectral imaging to predict total nitrogen concentration in four brands of almonds purchased from commercial retailers. A hyperspectral imaging system in the wavelength range 400-1000 nm was used in the study. A partial linear squares regression (PLSR) model was developed, which predicted total nitrogen concentration with a determination coefficient (R2 p) of 0.82 and a root mean error square of calibration (RMSEC) of 0.16. These results indicated that hyperspectral imaging has great potential to predict total nitrogen concentration of almond kernels.
关键词： food quality,nuts,crude protein,nutritional composition,rapid assessment,almond
更新于2025-09-23 15:23:52
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Slide-free imaging of hematoxylin-eosin stained whole-mount tissues using combined third-harmonic generation and three-photon fluorescence microscopy
摘要： Intraoperative margin assessment of surgical tissues during cancer surgery is clinically important, especially in the case of tissue conserving surgery like Mohs micrographic surgery in which minimization of the surgical area is considered crucial. Frozen pathology is the gold standard of assessing excised tissues for signs of remaining cancerous lesions. The current protocol, however, is time-consuming and labor-intensive. Instead of the complex frozen sectioning, staining, and traditional white light microscopy imaging protocol, optically-sectioned histopathological imaging of hematoxylin-eosin stained whole-mount skin tissues with a sub-femtoliter resolution is demonstrated by using nonlinear microscopy in this study. With our proposed method, the reagents of staining and the contrast of imaging are fully consistent with the current clinical standard of frozen pathology, thus facilitating rapid intraoperative assessment of surgical tissues for future applications.
关键词： hematoxylin-eosin,three photon microscopy,third harmonic generation microscopy,surgical border,margin assessment
更新于2025-09-23 15:23:52
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Treatment of sanitary landfill leachate by the combination of photo-Fenton and biological processes
摘要： In this work, the pollutant reduction performance in landfill leachate by combining both photo-Fenton and biological processes was investigated. First, conventional biological treatment was performed, consisting of a decantation process, with centrifugation at 5000 rpm for 15 min, followed by the biological process conducted at 2.36 ± 0.1 mg mg?1 (BOD5/MLSS) and 0.571 ± 0.04 vvm (L L?1 min?1) for 40 h. At the same time, in the application of the photo-Fenton process, a central composite rotatable design (CCRD) was applied to evaluate the effect of main process variables. The quadratic models of chemical oxygen demand (COD) and 5 days biological oxygen demand (BOD5) removal were proposed and validated, being separately used as objective functions during the search for optimal operating conditions. After the application of the conventional biological process, removals of 87 ± 2% and 84 ± 2% were obtained for COD and BOD5, respectively. For the photo-Fenton process under optimum conditions (3400 mg H2O2 L?1, 80 mg Fe2? L?1, pH = 2.40 and 120 min), removals of 89 ± 3% COD and 75 ± 1% BOD5 were obtained. However, both processes did not meet effluent discharge standards. So, the optimized photo-Fenton process was then combined with the biological process, performed for 150 h with 1.571 ± 0.06 vvm and 4.41 ± 0.3 mg mg?1 (BOD5/MLSS). With the combined process, it was possible to treat an effluent with high organic load, achieving a removal of 98% COD and BOD5 and meeting the restrictive standards of release in recipient water bodies.
关键词： Toxic effluent,Processes combination,Biodegradability,Processes performance assessment
更新于2025-09-23 15:23:52
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Blind Stereoscopic Image Quality Assessment Based on Hierarchical Learning
摘要： We proposed a blind image quality assessment model which used classification and prediction for three-dimensional (3D) image quality assessment (denoted as CAP-3DIQA) that can automatically evaluate the quality of stereoscopic images. First, in the classification stage, the model separated the distorted images into several subsets according to the types of image distortions. This process will assign the images with the same distortion type to the same group. After the classification stage, the classified distorted image set is fed into the image quality predictor that contains five different perceptual channels which predict the image quality score individually. Lastly, we used the regression module of support vector machine to evaluate the final image quality score where the input of the regression model is the combination of five channel's outputs. The model we proposed is tested on three public and popular databases, which are LIVE 3D Image Quality Database Phase I, LIVE 3D Image Quality Database Phase II and MCL 3D Image Quality Database. The experimental results show that our proposed model leads to significant performance improvement on quality prediction for stereoscopic images compared with other existing state-of-the-art quality metrics.
关键词： image quality assessment,stereoscopic images,Hierarchical learning,no reference
更新于2025-09-23 15:23:52
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A multi-order derivative feature-based quality assessment model for light field image
摘要： This paper presents an image quality assessment (IQA) model exploring the multi-order derivative feature, called Multi-order Derivative Feature-based Model (MDFM), for evaluating the perceptual quality of light field image (LFI). In our approach, for the input reference and distorted LFIs, the multi-order derivative features are extracted by using the discrete derivative filter to represent the image details in different degrees. Then, the similarities of the extracted derivative features are measured independently. Finally, the weight map is established through the maximum value of the second-order derivative feature of reference and distorted LFIs, which is further utilized to pool the similarity map for generating the final score. Extensive simulation results have demonstrated that the proposed MDFM is more consistent with the perception of the HVS on the evaluation of LFI than the classical and state-of-the-art IQA methods.
关键词： Multi-order derivative feature,Light field image,Image quality assessment
更新于2025-09-23 15:23:52
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Blind image quality assessment with hierarchy: Degradation from local structure to deep semantics
摘要： Though blind image quality assessment (BIQA) is highly desired in perceptual-oriented image processing systems, it is extremely difficult to design a reliable BIQA method. With the help of the prior knowledge, the human visual system (HVS) hierarchically perceives the quality degradation during the visual recognition. Inspired by this, we suggest different levels of distortion generate individual degradations on hierarchical features, and propose to consider the degradations on both low and high level features for quality prediction. By mimicking the orientation selectivity (OS) mechanism in the primary visual cortex, an OS based local structure is designed for low-level visual information representation. At the meantime, the deep residual network, which possesses multiple levels for feature integration, is employed to extract the deep semantics for high-level visual content representation. By fusing the local structure and the deep semantics, a hierarchical feature set is acquired. Next, the correlations between the degradations of image qualities and their corresponding hierarchical feature sets are analyzed, and a novel hierarchical feature degradation (HFD) based BIQA (HFD-BIQA) method is built. Experimental results on the legacy and wild image quality assessment databases demonstrate the prediction accuracy of the proposed HFD-BIQA method, and verify that the HFD-BIQA performs highly consistent with the subjective perception.
关键词： Local structure,Deep semantics,Hierarchical feature degradation,Blind image quality assessment
更新于2025-09-23 15:23:52