Achieving widely distributed feature matches using flattened-affine-SIFT algorithm for fisheye images.

Performing correction first is the most common methods to address feature matching issues for fisheye images, but corrections often result in significant loss of scene details or stretching of images, leaving peripheral regions without matches. In this paper, we propose a novel approach, named flattened-affine-SIFT, to find widely distributed feature matches between stereo fisheye images. Firstly, we establish a new imaging model that integrates a scalable model and a hemisphere model. Utilizing the extensibility of the imaging model, we design a flattened array model to reduce the distortion of fisheye images. Additionally, the affine transformation is performed on the flattened simulation images, which are computed using the differential expansion and the optimal rigidity transformation. Then feature matches are extracted and matched from the simulated images. Experiments on indoor and outdoor fisheye images show that the proposed algorithm can find a large number of reliable feature matches. Moreover, these matches tend to be dispersed over the entire effective image, including peripheral regions with dramatic distortion.

Transparent and Ultra-Thin Flexible Checkerboard Metasurface for Radar-Infrared Bi-Stealth.

This paper proposed a single-layer checkerboard metasurface with simultaneous wideband radar cross-section (RCS) reduction characteristics and low infrared (IR) emissivity. The metasurface consists of an indium tin oxide (ITO)-patterned film, a polyethylene terephthalate (PET) substrate and an ITO backplane from the top downwards, with a total ultra-thin thickness of 1.6 mm. This design also allows the metasurface to have good optical transparency and flexibility. Based on phase cancellation and absorption, the metasurface can achieve a wideband RCS reduction of 10 dB from 10.6 to 19.4 GHz under normal incidence. When the metasurface is slightly cylindrically curved, an RCS reduction of approximately 10 dB can still be achieved from 11 to 19 GHz. The polarization and angular stability of the metasurface have also been verified. The filling rate of the top ITO-patterned film is 0.81, which makes the metasurface have a low theoretical IR emissivity of 0.24. Both simulation and experimental results have verified the excellent characteristics of the proposed checkerboard metasurface, demonstrating its great potential application in radar-IR bi-stealth.

Photoinduced Nickel-Catalyzed Carbon-Heteroatom Coupling.

Herein, we report visible light-promoted single nickel catalysis for diverse carbon-heteroatom couplings under mild conditions. This mild, general, and robust method to couple diverse nitrogen, oxygen, and sulfur nucleophiles with aryl(heteroaryl)/alkenyl iodides/bromides exhibits a wide functional group tolerance and is applicable to late-stage modification of pharmaceuticals and natural products. On the base of preliminary mechanistic studies, a NiI /NiIII cycle via the generation of active NiI complexes that appear from homolysis of NiII -I rather than NiII -aryl bond was tentatively proposed.

LiDAR-assisted accuracy improvement strategy for binocular visual measurement.

The measurement model of binocular vision is inaccurate when the measurement distance is much different from the calibration distance, which affects its practicality. To tackle this challenge, we proposed what we believe to be a novel LiDAR-assisted accuracy improvement strategy for binocular visual measurement. First, the 3D points cloud and 2D images were aligned by the Perspective-n-Point (PNP) algorithm to realize calibration between LiDAR and binocular camera. Then, we established a nonlinear optimization function and proposed a depth-optimization strategy to lessen the error of binocular depth. Finally, the size measurement model of binocular vision based on the optimized depth is built to verify the effectiveness of our strategy. The experimental results show that our strategy can improve the depth accuracy compared to three stereo matching methods. The mean error of binocular visual measurement decreased from 33.46% to 1.70% at different distances. This paper provides an effective strategy for improving the measurement accuracy of binocular vision at different distances.

UAV system with trinocular vision for external obstacle detection of transmission lines.

External obstacle detection is a significant task in transmission line inspection and is related to the safe operation of the power transmission grid. In recent years, unmanned aerial vehicles (UAVs) equipped with different devices have been widely used for transmission line inspection. However, because of the complex environment of transmission lines and weak power line textures in the obtained images, most existing methods and systems cannot meet the requirements for real-time and high-accuracy external obstacle detection of transmission lines. In this paper, a novel, to the best of our knowledge, UAV system integrated trinocular vision technology with remote sensing is developed to achieve better external obstacle detection of transmission lines in real time, which is composed of a DJ-Innovations (DJI) UAV equipped with a global positioning system (GPS), angle sensors, trinocular vision including three visible cameras with the same parameters, and a small processor with a pre-implanted software algorithm. In this paper, a new method for external obstacle detection of transmission lines is proposed to satisfy the requirements for real-time and high-accuracy practical inspection applications. First, the original trinocular images need to be rectified. Then, the rectified trinocular images are adopted to achieve three-dimensional reconstruction of power lines. Finally, based on trinocular vision, bag of feature, and GPS, the clearance distance measurement, obstacle classification, and obstacle location are realized. Experimental tests on 220 kV transmission lines reveal that our proposed system can be applied in practical inspection environments and has good performance.

Calibration of an underwater binocular vision system based on the refraction model.

Underwater measurement based on stereo vision attaches great importance to camera calibration. However, it is challenging to perform accurate calibration due to the significant refraction presented at the interfaces of air and water. To solve this problem, a calibration method for an underwater binocular vision system based on the optimized refractive model is proposed. First, conventional calibration is performed to obtain basic initial camera parameters using checkerboard images collected in the air. Then, an evolutionary multi-objective function is established according to Snell's law, the refractive light propagation path, and checkerboard geometric relationship. Finally, precise camera parameters and involved refraction parameters are both obtained for underwater target positioning and size measurement by the non-dominated sorting genetic algorithm of the reference point. A group of experiments is performed, and the validity and effectiveness of the proposed calibration algorithm is demonstrated.

Trinocular vision and spatial prior based method for ground clearance measurement of transmission lines.

It is an essential task to inspect ground clearance of transmission lines in time. However, the weak texture of transmission lines and high complexity of the background make it difficult to balance efficiency and accuracy. To solve the problem, a trinocular vision and spatial prior based method is proposed, which is specifically designed for ground clearance measurement of transmission lines with unmanned aerial vehicles (UAVs). In this novel method, a perpendicular double-baseline trinocular vision module is applied to improve the accuracy of transmission line reconstruction. Then the spatial prior information of geometric models under different shooting attitudes is analyzed in detail, and it is adopted to determine the ground crossing points and compute ground clearance efficiently. Also, an interactive software is developed and tested in the simulation environment of UAV inspection. Experimental results verify the feasibility of the measurement method. Finally, we discuss in detail how to apply the method effectively in practice and give a set of recommended camera parameters.

Defect inspection for underwater structures based on line-structured light and binocular vision.

Surface defect inspection for underwater structures is important. However, the inspection technologies based on passive vision cannot meet accuracy requirements. In this paper, we propose a two-stage method based on structured light images for defect detection. In the first stage, light stripes are extracted based on the analysis of hue, saturation, value (HSV) space and gray space. Then a hole-filling method is applied to ensure stripe integrity. In the second stage, depth information for all light stripes is calculated to synthesize a depth map, which is segmented for defect localization and measurement. Experimental results have verified the feasibility and effectiveness of our method.

A Reinforced Whale Optimization Algorithm for Solving Mathematical Optimization Problems.

The whale optimization algorithm has several advantages, such as simple operation, few control parameters, and a strong ability to jump out of the local optimum, and has been used to solve various practical optimization problems. In order to improve its convergence speed and solution quality, a reinforced whale optimization algorithm (RWOA) was designed. Firstly, an opposition-based learning strategy is used to generate other optima based on the best optimal solution found during the algorithm's iteration, which can increase the diversity of the optimal solution and accelerate the convergence speed. Secondly, a dynamic adaptive coefficient is introduced in the two stages of prey and bubble net, which can balance exploration and exploitation. Finally, a kind of individual information-reinforced mechanism is utilized during the encircling prey stage to improve the solution quality. The performance of the RWOA is validated using 23 benchmark test functions, 29 CEC-2017 test functions, and 12 CEC-2022 test functions. Experiment results demonstrate that the RWOA exhibits better convergence accuracy and algorithm stability than the WOA on 20 benchmark test functions, 21 CEC-2017 test functions, and 8 CEC-2022 test functions, separately. Wilcoxon's rank sum test shows that there are significant statistical differences between the RWOA and other algorithms.

Interrelationships among College Students' Perceptions of Smart Classroom Environments, Perceived Usefulness of Mobile Technology, Achievement Emotions, and Cognitive Engagement.

Cognitive engagement is a crucial factor that shapes successful learning outcomes, but our understanding of the factors that influence such engagement in the smart classroom context remains limited. This study aims to narrow this research gap by exploring the relationships among college students' perceptions of the smart learning environment, perceived usefulness of mobile technology, achievement emotions, and cognitive engagement. A total of 1293 college students completed an online questionnaire survey, and 1076 valid responses were received. Structural equation modeling was used to analyze the interrelationships among these factors. The results revealed that students' perceptions of the smart classroom environment and perceived usefulness of mobile technology as well as two achievement emotions (pride and anxiety) significantly impact cognitive engagement. Both pride and anxiety act as mediators in the relationships among perceptions of smart classroom environments, the perceived usefulness of mobile technology, and cognitive engagement, in which context the mediating effect of pride is stronger than that of anxiety. These findings have practical implications for instructors, who should focus on implementing strategies that promote positive achievement emotions when students use mobile technology in smart classrooms. Additionally, these findings can inform the design and construction of smart classroom environments. Moreover, our study has limitations due to reliance on online data collection and self-reported data, which may introduce biases and measurement errors. Future research should incorporate multimodal data and advanced technologies for a comprehensive assessment to better understand students' engagement in smart learning environments, while also considering individual factors and the educational context to enhance the effectiveness of mobile technology in supporting students' emotions and achievement.

Research on the spatial patterns and evolution trends of the coupling coordination between digital finance and sustainable economic development in the Yellow River Basin, China.

In the current global context, digital finance (DF) and sustainable economic development (SED) are important topics. The synergies between DF and SED have already been proven. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of DF and SED have not received sufficient attention to date. Based on data from 55 cities in the Yellow River Basin (YRB) from 2011 to 2021, this study constructs an evaluation index system of DF and SED and measures their level, respectively. The proposed CCD model is then used to measure the CCD between the two systems. In addition, kernel density estimation, Markov chain, σ-convergence, ß-convergence, and the quadratic assignment procedure (QAP) method are used to study the spatial pattern, distribution dynamic evolution trend, convergence, and influencing factors of the regional differences in the CCD. The results show that: (1) From 2011 to 2021, the CCD level showed a stable upward trend and regional heterogeneity, and the time stage characteristics were more obvious. (2) The center position and change interval of the overall distribution curve of the kernel density estimation gradually shifted to the right. The Markov transfer probability matrix shows that the CCD is more stable among different levels, indicating a phenomenon of "club convergence". (3) A convergence analysis shows that there are significant σ-convergence, absolute ß-convergence, and conditional ß-convergence. (4) The QAP regression shows that factors such as the regional differences in GDP per capita have a significant impact on the regional differences in the CCD. This study offers a comprehensive structure that can be used to examine the synergistic effects between DF and SED; the research findings can also provide perspectives for other areas.

In situ copper photocatalysts triggering halide atom transfer of unactivated alkyl halides for general C(sp3)-N couplings.

Direct reduction of unactivated alkyl halides for C(sp3)-N couplings under mild conditions presents a significant challenge in organic synthesis due to their low reduction potential. Herein, we introduce an in situ formed pyridyl-carbene-ligated copper (I) catalyst that is capable of abstracting halide atom and generating alkyl radicals for general C(sp3)-N couplings under visible light. Control experiments confirmed that the mono-pyridyl-carbene-ligated copper complex is the active species responsible for catalysis. Mechanistic investigations using transient absorption spectroscopy across multiple decades of timescales revealed ultrafast intersystem crossing (260 ps) of the photoexcited copper (I) complexes into their long-lived triplet excited states (>2 µs). The non-Stern-Volmer quenching dynamics of the triplets by unactivated alkyl halides suggests an association between copper (I) complexes and alkyl halides, thereby facilitating the abstraction of halide atoms via inner-sphere single electron transfer (SET), rather than outer-sphere SET, for the formation of alkyl radicals for subsequent cross couplings.

Janus Doping of Sulfur into Platinum Diselenide Ribbons.

2D platinum diselenide (PtSe2), a novel member of the transition metal dichalcogenides (TMDCs) family, possesses many excellent properties, including a layer-dependent bandgap, high carrier mobility, and broadband response, making it promise for applications in technologies like field-effect transistors and room-temperature photodetectors. Doping represents an effective method to modify the electrical properties of 2D TMDCs and to bestow upon them additional functions. However, to date, little research has been conducted on the successful doping of 2D PtSe2 for modification. In this study, sulfur (S) powder is utilized during the chemical vapor deposition growth process of 2D PtSe2 ribbons and successfully integrated into the PtSe2 lattice through substitutional doping. The Au substrate significantly decreases the substitution energy of Se atoms in the lower layer of PtSe2, resulting in the formation of the Janus PtSSe structure. S-doped PtSe2 ribbons demonstrate significant symmetry breaking and enhanced electrical properties, showcasing a strong nonlinear optical response and certain synaptic plasticity, further simulating some neuromorphological processes. This study not only demonstrates a viable method for controllable doping and modification of 2D PtSe2 but also establishes a platform for exploring the characteristics of Janus TMDCs.

Partitioning polar-slush strategy in relaxors leads to large energy-storage capability.

Relaxor ferroelectric (RFE) films are promising energy-storage candidates for miniaturizing high-power electronic systems, which is credited to their high energy density (Ue) and efficiency. However, advancing their Ue beyond 200 joules per cubic centimeter is challenging, limiting their potential for next-generation energy-storage devices. We implemented a partitioning polar-slush strategy in RFEs to push the boundary of Ue. Guided by phase-field simulations, we designed and fabricated high-performance Bi(Mg0.5Ti0.5)O3-SrTiO3-based RFE films with isolated slush-like polar clusters, which were realized through suppression of the nonpolar cubic matrix and introduction of highly insulating networks. The simultaneous enhancement of the reversible polarization and breakdown strength leads to a Ue of 202 joules per cubic centimeter with a high efficiency of ~79%. The proposed strategy provides a design freedom for next-generation high-performance dielectrics.

Carrier-phonon decoupling in perovskite thermoelectrics via entropy engineering.

Thermoelectrics converting heat and electricity directly attract broad attentions. To enhance the thermoelectric figure of merit, zT, one of the key points is to decouple the carrier-phonon transport. Here, we propose an entropy engineering strategy to realize the carrier-phonon decoupling in the typical SrTiO3-based perovskite thermoelectrics. By high-entropy design, the lattice thermal conductivity could be reduced nearly to the amorphous limit, 1.25 W m-1 K-1. Simultaneously, entropy engineering can tune the Ti displacement, improving the weighted mobility to 65 cm2 V-1 s-1. Such carrier-phonon decoupling behaviors enable the greatly enhanced µW/κL of ~5.2 × 103 cm3 K J-1 V-1. The measured maximum zT of 0.24 at 488 K and the estimated zT of ~0.8 at 1173 K in (Sr0.2Ba0.2Ca0.2Pb0.2La0.2)TiO3 film are among the best of n-type thermoelectric oxides. These results reveal that the entropy engineering may be a promising strategy to decouple the carrier-phonon transport and achieve higher zT in thermoelectrics.

Photoinduced Homolysis of the Ni-P Bond via Ligand to Metal Charge Transfer for C-P Bond Formation in Nickel Catalysis.

Photoinduced homolysis of NiII-carbon and -heteroatom bonds has been well studied for carbon-heteroatom couplings, but homolysis of the NiII-P bond is still undisclosed. Herein, we describe the homolysis of NiII-P bonds via ligand to metal charge transfer to access active nickel(I) complexes and phosphorus-centered radicals under visible-light irradiation for C-P couplings of diaryl phosphine oxides with aryl bromides. Experimental studies demonstrated that visible light enabled homolysis of the NiII-P bond and the NiI/NiIII self-sustained cycle was involved in C-P bond formation. Furthermore, homolysis of the NiII-P bond can be applied to the hydrophosphination of [1.1.1]propellane in single-nickel photocatalysis.

Harris hawks optimization based on global cross-variation and tent mapping.

Harris hawks optimization (HHO) is a new meta-heuristic algorithm that builds a model by imitating the predation process of Harris hawks. In order to solve the problems of poor convergence speed caused by uniform choice position update formula in the exploration stage of basic HHO and falling into local optimization caused by insufficient population richness in the later stage of the algorithm, a Harris hawks optimization based on global cross-variation and tent mapping (CRTHHO) is proposed in this paper. Firstly, the tent mapping is introduced in the exploration stage to optimize random parameter q to speed up the convergence in the early stage. Secondly, the crossover mutation operator is introduced to cross and mutate the global optimal position in each iteration process. The greedy strategy is used to select, which prevents the algorithm from falling into local optimal because of skipping the optimal solution and improves the convergence accuracy of the algorithm. In order to investigate the performance of CRTHHO, experiments are carried out on ten benchmark functions and the CEC2017 test set. Experimental results show that the CRTHHO algorithm performs better than the HHO algorithm and is competitive with five advanced meta-heuristic algorithms.

An Optically Transparent Metamaterial Absorber with Tunable Absorption Bandwidth and Low Infrared Emissivity.

A transparent metamaterial absorber (MMA) with both tunable absorption bandwidth and low infrared (IR) emissivity is proposed in this paper. The MMA is hierarchical, which consists of an infrared shielding layer (IRSL), two radar-absorption layers (RALs), an air/water layer, and an indium-tin-oxide (ITO) backplane from the top downwards. The IRSL and the RALs are made of ITO patterns etched on polyethylene terephthalate (PET) substrates. By changing the thickness of the water, the 90% absorption bandwidth can be tuned from 6.4-11.3 GHz to 12.7-20.6 GHz, while retaining good polarization and angular stability. An equivalent circuit model (ECM) is present, to reveal the physical mechanism of absorption. The proposed MMA has a low theoretical IR emissivity of about 0.24. A sample was fabricated and measured, and the experimental results are consistent with the simulation results, showing its potential applications in stealth glass and multifunctional radome.

Optimizing boiler combustion parameters based on evolution teaching-learning-based optimization algorithm for reducing NOx emission concentration.

How to reduce a boiler's NOx emission concentration is an urgent problem for thermal power plants. Therefore, in this paper, we combine an evolution teaching-learning-based optimization algorithm with extreme learning machine to optimize a boiler's combustion parameters for reducing NOx emission concentration. Evolution teaching-learning-based optimization algorithm (ETLBO) is a variant of conventional teaching-learning-based optimization algorithm, which uses a chaotic mapping function to initialize individuals' positions and employs the idea of genetic evolution into the learner phase. To verify the effectiveness of ETLBO, 20 IEEE congress on Evolutionary Computation benchmark test functions are applied to test its convergence speed and convergence accuracy. Experimental results reveal that ETLBO shows the best convergence accuracy on most functions compared to other state-of-the-art optimization algorithms. In addition, the ETLBO is used to reduce boilers' NOx emissions by optimizing combustion parameters, such as coal supply amount and the air valve. Result shows that ETLBO is well-suited to solve the boiler combustion optimization problem.

Modified Marine Predators Algorithm hybridized with teaching-learning mechanism for solving optimization problems.

Marine Predators Algorithm (MPA) is a newly nature-inspired meta-heuristic algorithm, which is proposed based on the Lévy flight and Brownian motion of ocean predators. Since the MPA was proposed, it has been successfully applied in many fields. However, it includes several shortcomings, such as falling into local optimum easily and precocious convergence. To balance the exploitation and exploration ability of MPA, a modified marine predators algorithm hybridized with teaching-learning mechanism is proposed in this paper, namely MTLMPA. Compared with MPA, the proposed MTLMPA has two highlights. Firstly, a kind of teaching mechanism is introduced in the first phase of MPA to improve the global searching ability. Secondly, a novel learning mechanism is introduced in the third phase of MPA to enhance the chance encounter rate between predator and prey and to avoid premature convergence. MTLMPA is verified by 23 benchmark numerical testing functions and 29 CEC-2017 testing functions. Experimental results reveal that the MTLMPA is more competitive compared with several state-of-the-art heuristic optimization algorithms.