Improved Extreme Learning Machine and Its Application in Image Quality Assessment

Extreme learning machine (ELM) is a new class of single-hidden layer feedforward neural network (SLFN), which is simple in theory and fast in implementation. Zong et al. propose a weighted extreme learning machine for learning data with imbalanced class distribution, which maintains the advantages from original ELM. However, the current reported ELM and its improved version are only based on the empirical risk minimization principle, which may suffer from overfitting. To solve the overfitting troubles, in this paper, we incorporate the structural risk minimization principle into the (weighted) ELM, and propose a modified (weighted) extreme learning machine (M-ELM and M-WELM). Experimental results show that our proposed M-WELM outperforms the current reported extreme learning machine algorithm in image quality assessment

Machine Learning Based Crop Drought Mapping System by UAV Remote Sensing RGB Imagery

Water stress has adverse effects on crop growth and yield, where its monitoring plays a vital role in precision crop management. This paper aims at initially exploiting the potentials of UAV aerial RGB image in crop water stress assessment by developing a simple but effective supervised learning system. Various techniques are seamlessly integrated into the system including vegetation segmentation, feature engineering, Bayesian optimization and Support Vector Machine (SVM) classifier. In particular, wheat pixels are first segmented from soil background by using the classical vegetation index thresholding. Rather than performing pixel-wise classification, pixel squares of appropriate dimension are defined as samples, from which various features for pure vegetation pixels are extracted including spectral and color index (CI) features. SVM with Bayesian optimization is adopted as the classifier. To validate the developed system, a Unmanned Aerial Vehicle (UAV) survey is performed to collect high-resolution atop canopy RGB imageries by using DJI S1000 for the experimental wheat fields of Gucheng town, Heibei Province, China. Two levels of soil moisture were designed after seedling establishment for wheat plots by using intelligent irrigation and rain shelter, where field measurements were to obtain ground soil water ratio for each wheat plot. Comparative experiments by three-fold cross-validation demonstrate that pixel-wise classification, with a high computation load, can only achieve an accuracy of 82.8% with poor F1 score of 71.7%; however, the developed system can achieve an accuracy of 89.9% with F1 score of 87.7% by using only spectral intensities, and the accuracy can be further improved to 92.8% with F1 score of 91.5% by fusing both spectral intensities and CI features. Future work is focused on incorporating more spectral information and advanced feature extraction algorithms to further improve the performance

Astragaloside IV improves slow transit constipation by regulating gut microbiota and enterochromaffin cells

Purpose: Slow transit constipation (STC) is a common gastrointestinal disorder characterized by altered gut microbiota and reduced number of enterochromaffin cells (ECs). Astragaloside IV (AS-IV), a low drug permeability saponin, has showed beneficial effects on patients with STC. However, the specific mechanism by which AS-IV regulates STC remains unclear. In this study, we aimed to investigate the effect of AS-IV on STC and its associated mechanisms involving gut microbiota.Methods: The effect of AS-IV on STC was evaluated on STC mice induced with loperamide. We measured defecation frequency, intestinal mobility, ECs loss, and colonic lesions in STC mice treated with AS-IV. We also analyzed the changes in gut microbiota and metabolites after AS-IV treatment. Moreover, we investigated the relationship between specific gut microbes and altered fecal metabolites, such as 3-bromotyrosine (3-BrY). We also conducted in vitro experiments to investigate the effect of 3-BrY on caspase-dependent apoptosis of ECs and the activation of the p38 MAPK and ERK signaling pathways induced by loperamide.Results: AS-IV treatment promoted defecation, improved intestinal mobility, suppressed ECs loss, and alleviated colonic lesions in STC mice. AS-IV treatment also affected gut microbiota and metabolites, with a significant correlation between specific gut microbes and altered fecal metabolites such as 3-BrY. Furthermore, 3-BrY may potentially reduce caspase-dependent apoptosis of ECs and protect cell survival by inhibiting the activation of the p38 MAPK and ERK signaling pathways induced by loperamide.Conclusion: Our findings suggest that changes in gut microbiota and ECs mediated the therapeutic effect of STC by AS-IV. These results provide a basis for the use of AS-IV as a prebiotic agent for treating STC. The specific mechanism by which AS-IV regulates gut microbiota and ECs warrants further investigation

Limiting Performance of the Ejector Refrigeration Cycle with Pure Working Fluids

An ejector refrigeration system is a promising heat-driven refrigeration technology for energy consumption. The ideal cycle of an ejector refrigeration cycle (ERC) is a compound cycle with an inverse Carnot cycle driven by a Carnot cycle. The coefficient of performance (COP) of this ideal cycle represents the theoretical upper bound of ERC, and it does not contain any information about the properties of working fluids, which is a key cause of the large energy efficiency gap between the actual cycle and the ideal cycle. In this paper, the limiting COP and thermodynamics perfection of subcritical ERC is derived to evaluate the ERC efficiency limit under the constraint of pure working fluids. 15 pure fluids are employed to demonstrate the effects of working fluids on limiting COP and limiting thermodynamics perfection. The limiting COP is expressed as the function of the working fluid thermophysical parameters and the operating temperatures. The thermophysical parameters are the specific entropy increase in the generating process and the slope of the saturated liquid, and the limiting COP increases with these two parameters. The result shows R152a, R141b, and R123 have the best performance, and the limiting thermodynamic perfections at the referenced state are 86.8%, 84.90%, and 83.67%, respectively

Research on the influence of alignment error on coupling efficiency and beam quality for Gaussian beam to multimode fiber

The effect of alignment error on the coupling efficiency and beam quality of a Gaussian beam coupled into a large-core multimode fiber is studied in this paper. The equations for evaluating the effect of alignment error on the coupling efficiency are derived separately, and verified with the method of simulation. The calculation and simulation results obtained are highly consistent. In the same way, the effects of alignment error on the beam power distribution are discussed. The results show that the lateral error will change the path of partial light to a large extent, and have a greater influence on the power distribution of the Gaussian beam than the longitudinal error and angular error do. Keywords: Alignment error, Coupling efficiency, Beam quality, Multimode fibe

Harnessing the power of natural minerals: A comprehensive review of their application as heterogeneous catalysts in advanced oxidation processes for organic pollutant degradation

The release of untreated wastewater into water bodies has become a significant environmental concern, resulting in the accumulation of refractory organic pollutants that pose risks to human health and ecosystems. Wastewater treatment methods, including biological, physical, and chemical techniques, have limitations in achieving complete removal of the refractory pollutants. Chemical methods, particularly advanced oxidation processes (AOPs), have gained special attention for their strong oxidation capacity and minimal secondary pollution. Among the various catalysts used in AOPs, natural minerals offer distinct advantages, such as low cost, abundant resources, and environmental friendliness. Currently, the utilization of natural minerals as catalysts in AOPs lacks thorough investigation and review. This work addresses the need for a comprehensive review of natural minerals as catalysts in AOPs. The structural characteristics and catalytic performance of different natural minerals are discussed, emphasizing their specific roles in AOPs. Furthermore, the review analyzes the influence of process factors, including catalyst dosage, oxidant addition, pH value, and temperature, on the catalytic performance of natural minerals. Strategies for enhancing the catalytic efficiency of AOPs mediated by natural minerals are explored, mainly including physical fields, reductant addition, and cocatalyst utilization. The review also examines the practical application prospects and main challenges associated with the use of natural minerals as heterogeneous catalysts in AOPs. This work contributes to the development of sustainable and efficient approaches for organic pollutant degradation in wastewater

The research about high-dynamic and low-gray target image differential capture technology based on laser active detection

Abstract The extraction and capture of the target by the medium-long wave infrared optical system is mainly achieved based on the gray difference between the target image and the background image. Under complex background conditions, such as air-to-ground alarms or target detection and capture will be strongly disturbed by the background environment. Especially under dynamic conditions, the background and the target are in a rapid change, how to detect real-time ground-to-air missile seeker and other weak targets is very difficult. It is one of the technical difficulties in the current image processing field to quickly locate and extract from high-dynamic low-contrast grayscale images. In this paper, a fast differential capture method for cat eye echo images using a highly active and low-gray optical target such as a seeker using laser active illumination detection is proposed to achieve efficient capture and extraction of the target. Using a 3.5-um band, 1 W average power laser to illuminate medium-wave infrared-waveband seeker with a 100 mm aperture, to achieve echo imaging of 2–4 orders of magnitude higher than traditional diffuse reflection, using 500 Hz large frame rate medium-wave imaging to achieve quick alignment and fast differential imaging of the target background. From the simulation and experimental results, this image processing method can effectively improve the optical system’s detection capabilities and capture speed and effectively solve the problems of low-gray level dynamic target detection and high-precision positioning in complex background

Limiting Performance of the Ejector Refrigeration Cycle with Pure Working Fluids

An ejector refrigeration system is a promising heat-driven refrigeration technology for energy consumption. The ideal cycle of an ejector refrigeration cycle (ERC) is a compound cycle with an inverse Carnot cycle driven by a Carnot cycle. The coefficient of performance (COP) of this ideal cycle represents the theoretical upper bound of ERC, and it does not contain any information about the properties of working fluids, which is a key cause of the large energy efficiency gap between the actual cycle and the ideal cycle. In this paper, the limiting COP and thermodynamics perfection of subcritical ERC is derived to evaluate the ERC efficiency limit under the constraint of pure working fluids. 15 pure fluids are employed to demonstrate the effects of working fluids on limiting COP and limiting thermodynamics perfection. The limiting COP is expressed as the function of the working fluid thermophysical parameters and the operating temperatures. The thermophysical parameters are the specific entropy increase in the generating process and the slope of the saturated liquid, and the limiting COP increases with these two parameters. The result shows R152a, R141b, and R123 have the best performance, and the limiting thermodynamic perfections at the referenced state are 86.8%, 84.90%, and 83.67%, respectively