Iris segmentation is an essential process of iris recognition. Iris segmentation plays an important role in maintaining the accuracy of iris based on recognition system by limiting the errors in the ...current stage. However, its performance is affected by non-ideal conditions caused by ambient light noise and user non-cooperation. The existing segmentation methods based on local features cannot find the real iris boundary under these non-ideal conditions, and the errors generated in the segmentation stage will traverse to all subsequent stages, resulting in decreased accuracy and reliability. In addition, real iris boundaries need to be divided without additional denoising costs. Aiming at the problems of existing algorithms in complex scenes and cross-device applications, an Iris segmentation algorithm based on Dense U-Net is presented in this paper. Combining Dense network with U-Net network, Iris is segmented by taking advantage of dense U-Net network, which is narrower and has fewer parameters, and taking advantage of U-Net in semantic segmentation. Dense connected path is derived from dense connected network (Dense U-Net), in which improved information and parameters are helpful to reduce the training difficulty of deep network. The final segmentation accuracy was 98. 36%. F1 is 97.07%. The experimental results prove the presented model can improve the accuracy, reduce the error rate, and assist doctors in the diagnosis of Iris Diseases effectively.
The oxygen reduction reaction (ORR) plays a crucial role in electrochemical energy conversion and storage devices such as alkaline fuel cells and metal–air batteries. These systems, which could ...employ non-platinum catalysts for oxygen reduction, are cheaper and stable alternatives to their expensive counterparts like proton exchange membrane fuel cells (PEMFCs) working on platinum based catalysts. Various binary and ternary silver nanoalloys have been reported to act as efficient electrocatalysts for the ORR in alkaline fuel cells and batteries. Herein, we present a critical review on the recent advances made in silver nanoalloy electrocatalysts for the ORR in alkaline media. The mechanism of ORR on nanoalloys is described; the effect of structure and composition of various silver nanoalloys (including Ag–Cu, Ag–Pd, Ag–Au, Ag–Co etc. ) on their ORR activity and stability is discussed. The rational design of electrocatalysts in order to maximize the number of catalytically active sites on the surface of the electrocatalysts for the ORR is also reviewed. Finally, we provide insights into the remaining challenges and directions for future perspectives and research.
Electrocatalytic reduction of nitrite (NO2−) to ammonia (NH3) can simultaneously achieve wastewater treatment and ammonia production, but it needs efficient catalysts. Herein, Cu2O particles ...self-supported on Cu foam with enriched oxygen vacancies are developed to enable selective NO2− reduction to NH3, exhibiting a maximum NH3 yield rate of 7510.73 μg h−1 cm−2 and high faradaic efficiency of 94.21% at −0.6 V in 0.1 M PBS containing 0.1 M NaNO2. Density functional theory calculations reveal the vital role of oxygen vacancies during the nitrite reduction process, as well as the reaction mechanisms and the potential limiting step involved. This work provides a new avenue to the rational design of Cu-based catalysts for NH3 electrosynthesis.
To prevent soil pollution caused by polyethylene (PE) films in the central region of Gansu, China, liquid mulching made from cow dung (CDLM) was trailed in silage maize fields. The degradation of ...CDLM and PE films, soil temperature, soil organic matter content, silage maize yield and water use efficiency (WUE) were evaluated for three years (2018–2020). The degradability of CDLM has been found to be much stronger than the one of PE films, with CDLM degrading 40–60 days after sowing and finishing around 100 days. CDLM had a lower insulating impact than PE films but a higher insulating effect than non-mulching films as the control (CK); CDLM could successfully increase soil organic matter, with a total increase of 1.01% over three years. CDLM increased silage maize yield by 6.2% compared to PE films and 17.2% compared to CK. Consequently, CDLM may be an interesting alternative to PE films for enhancing silage maize yield while decreasing soil contamination.
Maize is widely cultivated and planted all over the world, which is one of the main food resources. Accurately identifying the defect of maize seeds is of great significance in both food safety and ...agricultural production. In recent years, methods based on deep learning have performed well in image processing, but their potential in the identification of maize seed defects has not been fully realized. Therefore, in this paper, a lightweight and effective network for maize seed defect identification is proposed. In the proposed network, the Convolutional Block Attention Module (CBAM) was integrated into the pretrained MobileNetv3 network for extracting important features in the channel and spatial domain. In this way, the network can be focused on useful feature information, and making it easier to converge. To verify the effectiveness of the proposed network, a total of 12784 images was collected, and 7 defect types were defined. Compared with other popular pretrained models, the proposed network converges with the least number of iterations and achieves the true positive rate is 93.14% and the false positive rate is 1.14%.
With the development of prefabricated buildings in China, the demand for prefabricated components is also increasing. The construction schedule of prefabricated components has heterogeneity and ...timeliness, which makes the traditional scheduling models not applicable. In order to control the construction process and reduce costs, research is conducted on controlling the construction process of prefabricated components in prefabricated buildings. This study divides the construction process into three stages according to the construction characteristics of prefabricated buildings. The scheduling models of these three stages are established, namely assembly, production, and transportation stages scheduling models.. The scheduling model of the three stages are related to each other through the duration constraints. In addition, an improved genetic algorithm is developed to solve the scheduling model of the assembly stage. Then an improved particle swarm optimization is designed to solve the scheduling model in the production and transportation stages. The results show that the minimum duration of the assembly phase was 8 days. The duration and cost of the production phase cannot be minimized at the same time. The minimum carbon emission duration and transportation cost in the transportation phase are 93.8 hours and 22516 yuan, respectively. The improved genetic algorithm tended to flatten out after nearly 180 iterations. The maximum running time of the improved particle swarm algorithm on the training set is 4.23s, the maximum hyper volume is 0.736, and the maximum anti generation distance is 2.35×10 -3 . The scheduling models of different stages and corresponding solving algorithms are effective and provide technical support for the construction process control of assembly parts. The technical contribution of this study is to optimize the genetic algorithm based on weed invasion algorithm and improve the local search ability of genetic algorithm. Then, the differential evolution algorithm is used to improve the particle swarm optimization algorithm and continuously generate new particles to replace the optimal position.
Abstract
Realization of highly tunable second-order nonlinear optical responses, e.g., second-harmonic generation and bulk photovoltaic effect, is critical for developing modern optical and ...optoelectronic devices. Recently, the van der Waals niobium oxide dihalides are discovered to exhibit unusually large second-harmonic generation. However, the physical origin and possible tunability of nonlinear optical responses in these materials remain to be unclear. In this article, we reveal that the large second-harmonic generation in NbO
X
2
(
X
= Cl, Br, and I) may be partially contributed by the large band nesting effect in different Brillouin zone. Interestingly, the NbOCl
2
can exhibit dramatically different strain-dependent bulk photovoltaic effect under different polarized light, originating from the light-polarization-dependent orbital transitions. Importantly, we achieve a reversible ferroelectric-to-antiferroelectric phase transition in NbOCl
2
and a reversible ferroelectric-to-paraelectric phase transition in NbOI
2
under a certain region of external pressure, accompanied by the greatly tunable nonlinear optical responses but with different microscopic mechanisms. Our study establishes the interesting external-field tunability of NbO
X
2
for nonlinear optical device applications.
The double-disc straight-groove (DDSG) grinding method is a new precision machining method for the rolling surface of bearing cylindrical rollers by using a flat grinding disc and a straight-groove ...grinding disc as machining tools. The machining principle of bearing cylindrical rollers based on the DDSG grinding method is experimentally investigated in this study. A circulating grinding platform has been constructed. The grinding test of the cylindrical rollers was performed with W40 white corundum abrasive. Under the experimental conditions of the grinding disc rotation speed of 7.5 rpm, the machining load of 110 N, and the eccentricity of the straight groove of 6 mm, 2000 cylindrical rollers (AISI 52100) were synchronously ground by the DDSG grinding method. The average diameter, surface roughness, and roundness of the ground rollers were investigated. Experimental results show that the material removal rate of the rollers is uniform. After 270 grinding cycles, the average diameter decreased from 5.99082 to 5.94135 mm, with an average material removal rate of 0.183 microns per cycle. The average roundness of ground cylinders reduced from 9.64 to 2.78 μm. The diameter variation decreased significantly from 14.5 to 6.0 μm. The average roughness reduced from 0.258 to 0.137 μm, and the fluctuation range of the roughness decreased from 0.143 to 0.033 μm. Experimental results demonstrate that the DDSG grinding method can improve the bearing cylindrical rollers’ dimensional consistency, roundness, and surface quality.
Artificial Z‐scheme, a tandem structure with two‐step excitation process, has gained significant attention in energy production and environmental remediation. By effectively connecting and matching ...the band‐gaps of two different photosystems, it is significant to utilize more photons for excellent photoactivity. Herein, a novel one‐photon (same energy‐two‐photon) Z‐scheme system is constructed between rGO modified boron‐nitrogen co‐doped‐WO3, and coupled CdSe quantum dots‐(QDs). The coctalyst‐0.5%RhxCr2O3(0.5RCr) modified amount‐optimized sample 6%CdSe/1%rGO3%BN‐WO3 revealed an unprecedented visible‐light driven overall‐water‐splitting to produce ≈51 µmol h−1 g−1 H2 and 25.5 µmol h−1 g−1 O2, and it remained unchanged for 5 runs in 30 h. This superior performance is ascribed to the one‐photon Z‐scheme, which simultaneously stimulates a two photocatalysts system, and enhanced charge separation as revealed by various spectroscopy techniques. The density‐functional theory is further utilized to understand the origin of this performance enhancement. This work provides a feasible strategy for constructing an efficient one‐photon Z‐scheme for practical applications.
The design of a novel Z‐scheme system based on a band gap adjusted visible‐light responsive 0.5RCr/6CdSe/1rGO/3BN‐WO3 nanocomposite is successfully constructed via hydrothermal method. This work demonstrates a promising approach to synthesize nanophotocatalysts based on WO3 for visible‐light driven solar energy application.
This paper addresses the energy-efficient scheduling and real-time control of flexible job shop that requires rescheduling affected operations and updating the scheduling. For energy-efficient ...scheduling shop floor efficiently, we propose a metaheuristic algorithm called PN-ACO algorithm, which combines a timed transition Petri nets (TTPN) based representation tool and an ant colony optimization (ACO) heuristic search method. To address the real-time control problem in energy-efficient scheduling of the shop floor, we apply the Internet of Things (IoT) technology to product production to form an Internet of Manufacturing Things environment (IoMT). In the IoMT environment, there are usually many abnormal event disturbances, including machine breakdown and urgent order arrival. To quickly handle the disturbance problem of abnormal events, the distributed control system architecture is proposed, the core of which is the negotiation and cooperation between manufacturing resources based on the wireless communication network. The proposed approach is further illustrated by a case energy-efficient of scheduling for a flexible job shop through which the optimal scheduling and correct supervisory control instructions can be obtained easily and quickly. In sum, the proposed optimization algorithm obtains a good effect in engineering applications while the validity of optimization is proved.
PDF
