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The action of any group on itself by conjugation and the corresponding conjugacy relation plays an important role in group theory. Generalizing the group theoretic notion of conjugacy to semigroups is one of the interesting problems, and semigroup theorists had produced substantial amount of research in this direction. The challenge to introduce a new notion of conjugacy in semigroups is to choose the suitable set of conjugating elements. A semigroup may contain a zero, and if zero lies in the conjugating set, then the relation reduces to the universal relation as can be seen in the notions ∼l, ∼p, and ∼o. To avoid this problem, various innovative notions of conjugacy in semigroups have been considered so far, and ∼n is one of these notions. ∼n is an equivalence relation in any semigroup, coincides with the usual group theoretic notion if the underlying semigroup is a group, and does not reduce to a universal relation even if S contains a zero. In this paper, we study ∼n notion of conjugacy in some classes of epigroups. Since epigroups are generalizations of groups, our results of this paper are innovative and generalize the existing results on other notions. After proving some fundamental results, we compare our results with existing ones and prove that they are worth contribution in the study of conjugacy in epigroups. [ABSTRACT FROM AUTHOR]

Source localization is widely used in many areas including GPS, but the influence of possible noises cannot be overlooked. Many optimization methods have been attempted to mitigate different kinds of noises. However, the stability of the solution, even the number of global solutions, is not fully known. Only local convergence or stability for the optimization problem is known in simple L1 or L2 settings. In this paper, we prove that the number of possible two‐dimensional source locations with three measurements in L2 setting is at most 5. We also showed the sufficient and necessary condition for the number of the solutions being 1, 2, 3, 4, and 5, where the measurement triangle is isosceles and the measurement distance for the two isosceles triangles is the same. [ABSTRACT FROM AUTHOR]

In order to solve the problem that the current image super‐resolution model has too many parameters and high computational complexity, this paper proposes a lightweight hybrid attention network (LHAN). LHAN consists of three parts: shallow feature extraction, lightweight hybrid attention block (LHAB), and upsampling module. LHAB combines multiscale self‐attention and large‐core attention. In order to make the network lightweight, multiscale self‐attention block (MSSAB) improves the self‐attention mechanism and uses windows of different sizes for group calculations. At the same time, in large‐core attention, we use depth‐based attention. Separate convolutions are used to reduce parameters. While keeping the receptive field unchanged, a normal convolution and a dilated convolution are used to replace the large kernel convolution. The four times super‐resolution experimental results on five data sets, including Set5 and Set14, show that our proposed method performs well in peak signal‐to‐noise ratio (PSNR) and structural similarity (SSIM). Specifically, in the benchmark data set on Urban, compared with SwinIR, the PSNR index of our method is improved by 0.10 dB. In addition, the parameter amount and calculation amount (floating point operations (FLOPs)) of our method are reduced by 315K and 16.4 G, respectively. Our proposed LHAN not only reduces the number of parameters and calculations but also achieves excellent performance in reconstruction quality. [ABSTRACT FROM AUTHOR]

This paper presents a method to invert the sea surface wind field from Sentinel‐1 synthetic aperture radar (SAR) interferometric wide swath (IW) band mode ground range detected (GRD) vertical polarization (VV) data based on the deep residual network (ResNet). Compared with the traditional algorithm (i.e., using geophysical model functions (GMFs)), the wind field inversion based on the ResNet deep learning method solves the problem of separate wind direction and wind speed inversion. The ResNet model is developed based on the results of 212 VV polarized IW images and cross calibrated multiplatform (CCMP) data collected in 2021 in the offshore waters of China. The root mean square error, standard deviation, and bias of the inverse wind direction of the ResNet model are 12.5°, 9.8°, and 7.4°, respectively, and the root mean square error, standard deviation, and bias of the inverse wind speed are 2.33, 1.495, and −1.375. The ResNet is better than the conventional local gradient and C‐band model models, further confirming the advantages shown by the deep learning algorithm in nonlinear fitting and its potential application in sea surface wind field inversion. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a general maximum principle for discrete fractional stochastic difference system of mean‐field type. The admissible control domain is nonconvex. We give Malliavin calculus for discrete‐time case to deal with the fractional terms. The maximum principle of general type is derived by classical variation and linear operator methods. In addition, a linear‐quadratic problem is solved to illustrate the main result and we also figure out a numerical result in this case. [ABSTRACT FROM AUTHOR]

This manuscript's main goal is to examine the presence of fixed points in the context of controlled metric‐type spaces utilizing rational type Ćirić‐contractive conditions. We provide appropriate examples to support the validity and superiority of our conclusions. In the context of extended b‐metric space, b‐metric spaces, and standard metric spaces, our findings extrapolate and expand a number of well‐known research findings. As an application of our findings, we prove that a second‐order differential equation has a solution. The paper ends with a few open problems for further investigation of additional dimensions within this framework. [ABSTRACT FROM AUTHOR]

This paper is concerned with two generalized inverse eigenvalue problems for a kind of pseudo‐Jacobi matrix. From a non‐Hermite matrix, an r × r Jacobi matrix, two distinct real eigenvalues, and part of the corresponding eigenvectors, an n × n pseudo‐Jacobi matrix is constructed. Furthermore, an n × n pseudo‐Jacobi matrix can be made by two different eigenpairs and a positive definite diagonal matrix. It is shown that a unique pseudo‐Jacobi matrix can be recovered from partial eigenpairs and certain special mixed eigendata. Two algorithms are provided for the reconstruction of such a pseudo‐Jacobi matrix, and illustrative numerical examples are presented to verify the proposed algorithms. [ABSTRACT FROM AUTHOR]

To solve the problem of collaborative search mission planning (CSMP) for a heterogeneous unmanned aerial vehicle (UAV) swarm for dynamic targets, this paper proposes a new CSMP scheme for a heterogeneous UAV swarm. First, a new polar coordinate system motion method is used to establish the UAV motion model and decision input solution model, which effectively solves the path‐unified coding problem of a heterogeneous UAV swarm. Then, in the mission area, a dynamically updated multisearch situation map model is established. Finally, to improve the global searching capability of a UAV, an improved path optimization algorithm PSO‐Rolling Horizon Control (PSO‐RHC) is designed. Multiple Monte Carlo simulations are performed for three time‐sensitive moving target types and three constraint types. The simulation results show that the task execution efficiency indexes of the proposed scheme for the decision input solution model, pheromone update mechanism, and optimization algorithm are improved by 188%, 72%, and 102%, respectively, and the overall performance is improved by 227%. [ABSTRACT FROM AUTHOR]

This paper introduces a bilevel programming model for optimizing transit network departure frequency. In the upper-level model, user satisfaction is reflected by considering congestion effects in the cost function. The lower-level assignment model simulates passenger travel behavior more realistically by incorporating congestion effects. This problem is solved by a heuristic gradient descent algorithm, where an approximation of the gradient is obtained at each iteration by using sensitivity analysis for transit equilibrium problems. The effectiveness of the proposed model and algorithm is demonstrated through two test examples, one of which involves a real-world scenario comprising over 130 transit lines. Numerical results conclusively indicate that the incorporation of congestion effects in the proposed model leads to improved transit system performance and enhanced user satisfaction. [ABSTRACT FROM AUTHOR]

In the field of operation research, both linear and fractional programming problems have been more encountered in recent years because they are more realistic in expressing real-life problems. Fractional programming problem is used when several rates need to be optimized simultaneously such as resource allocation planning, financial and corporate planning, healthcare, and hospital planning. There are several techniques to solve the multiobjective linear fractional programming problem. However, because of the use of scalarization, these techniques have some limitations. This paper proposed two new mean and median techniques to solve the multiobjective linear fractional programming problem by overcoming the limitations. After utilizing mean and median techniques, the problem is converted into an equivalent linear fractional programming problem; then, the linear fractional programming problem is transformed into linear programming problem and solved by the conventional simplex method or mathematical software. Some numerical examples have been illustrated to show the efficiency of the proposed techniques and algorithm. The performance of these solutions was evaluated by comparing their results with other existing methods. The numerical results have shown that the proposed techniques are better than other techniques. Furthermore, the proposed techniques solve a pure multiobjective maximization problem, which is even impossible with some existing techniques. The present investigation can be improved further, which is left for future research. [ABSTRACT FROM AUTHOR]

To solve the problem of jitter and low network throughput caused by the impact of background flows on IQ traffic in mobile fronthaul network, this paper proposed a new scheduling model for background flows, named hierarchical crossover traffic scheduling mechanism based on time-aware shaper (HC-TAS) by improving the traditional counterpart. Then, in this new model, we designed an inbound scheduling algorithm based on frame length matching and an outbound scheduling algorithm based on queue status, making sure that smaller data frames will not be blocked by large data frames. This greatly improves the utilization of timeslots in the scheduling process and reduces the jitter impact of background flows. To verify its performance, we conducted experiments in a simulated fronthaul network conforming to IEEE 802.1CM. The experimental results show that, under the condition that the jitter is guaranteed to be zero, compared with two mainstream scheduling schemes, Comb-FITting and TAS + Preemption, our proposed scheme can achieve lower maximum end-to-end delay and higher link utilization. The proposed HC-TAS meets the requirements of low jitter and high bandwidth utilization in 5G fronthaul network, and the research results provide a technical basis for the application and development of general time-sensitive networks as well. [ABSTRACT FROM AUTHOR]

Bolted connections are widely used in assembly structures, and their dynamic characteristics are often affected by stiffness, damping, excitation, and other factors. In order to solve the problems of low computational efficiency of fine modeling and large computational error of linearized equivalent modeling of bolted structures, this paper proposes a dynamic characteristic parameter identification method for bolted structures based on the multiscale method and considering the influence of nonlinear factors. In this method, the bolted connection characteristics are simulated in the form of a combination of shear stiffness, torsional stiffness, nonlinear stiffness, and viscous damping coefficient and identified according to the test measurement frequency and frequency response function. At the same time, by establishing the nonlinear dynamic model of bolted structure, the influence of different bolt preloads and excitation forces on the dynamic characteristics of bolted structure is studied. [ABSTRACT FROM AUTHOR]

In this paper, an efficient new technique is used for solving nonlinear fractional problems that satisfy specific criteria. This technique is referred to as the double conformable fractional Laplace-Elzaki decomposition method (DCFLEDM). This approach combines the double Laplace-Elzaki transform method with the Adomian decomposition method. The fundamental concepts and findings of the recently suggested transformation are presented. For the purpose of assessing the accuracy of our approach, we provide three examples and introduce the series solutions of these equations using DCLEDM. The results show that the proposed strategy is a very effective, reliable, and efficient approach for addressing nonlinear fractional problems using the conformable derivative. [ABSTRACT FROM AUTHOR]

This paper proposes modified model predictive control (MMPC) for coordinated signals, aiming to enhance a model's fidelity to the realistic traffic environment by relaxing typical assumptions. We focus on the arterial, where every intersection is equipped with a dual-ring-barrier signal controller that complies with the standards of the National Electric Manufacturers Association. MMPC employs the store-and-forward model to describe traffic flow, thereby transforming the signal control problem into a model-based rolling-horizon optimization problem, in which the prediction horizon is composed of several future sample intervals, commonly equal to the cycle length. A radar detector is used to collect vehicle data upstream of the stop line at every sampling instant. The optimization problem is solved to minimize the number of vehicles within the prediction horizon, and the next timing plan is determined based on the optimization results. Constraints are added and modified in order to incorporate the typical relaxed assumptions in the optimization process. For this purpose, MMPC introduces a transition-free ring-barrier structure, vehicle distribution ratio, and percent arrival before the end of green. Simulation results indicate that coordination can be maintained by MMPC without the need for transitions, and the estimation of current and future traffic states can be improved with the assistance of modified constraints. Compared with benchmark techniques, MMPC offers superior vehicle progression for coordinated movement and significant improvements in delays, number of stops, and total travel time from a system-wide perspective, with an acceptable small increase in runtime. [ABSTRACT FROM AUTHOR]

In recent years, solar photovoltaic (PV) energy, as a clean energy source, has received widespread attention and experienced rapid growth worldwide. However, the rapid growth of PV power deployment also brings important challenges to the maintenance of PV panels, and in order to solve this problem, this paper proposes an innovative algorithm based on PA-YOLO. First, we propose to use PA-YOLO's asymptotic feature pyramid network (AFPN) instead of YOLOv7's backbone network to support direct interactions of nonadjacent layers and avoid large semantic gaps between nonadjacent layers. For the occlusion problem of dense targets in the dataset, we introduce a repulsive loss function, which successfully reduces the occurrence of false detection situations. Finally, we propose a customized convolutional block equipped with an EMA mechanism to enhance the perceptual and expressive capabilities of the model. Experimental results on the dataset show that our proposed model achieves excellent performance with an average accuracy (mAP) of 94.5%, which is 6.8% higher than YOLOv7. In addition, our algorithm also succeeds in drastically reducing the model size from 71.3 MB to 48.4 MB, which well demonstrates the effectiveness of the model. [ABSTRACT FROM AUTHOR]

The variation of frequency is a significant indicator of the operation status of rotating machinery. Generally, the frequency is extracted and tracked in real-time based on the vibration signal produced by the rotating machinery. However, various interferences generated from contact sampling and transmitting result in difficulty in obtaining the frequency correctly in real-time from the vibration. To solve this problem, this paper presents an interpolated Kalman filter (IKF) based on the vibration and surface noise signals for real-time frequency tracking. First, the cross-correlation operation is performed on the vibration and surface noise signals sampled synchronously to enhance the energy concentration. After that, a frequency search procedure is carried out to calculate the input of the tracking task. Finally, an IKF-based frequency lock procedure is applied to eliminate the interferences and track the frequency in real time. Besides, a correction procedure is added to prevent the measurement process from tracking the frequency incorrectly. The performance of the proposed method is verified by the experiments based on an ARM-based test bench using standard signals and actual test signals. [ABSTRACT FROM AUTHOR]

Adjusting generator output and cutting off load can effectively solve the problem of continuous overload and disconnection of power lines caused by power flow transfer. To suppress large-scale power outages caused by overload-dominant cascading failures, a blocking method for overload-dominant cascading failures in the power grid based on source and load collaborative regulation is proposed. The shortest path algorithm was used to identify loads and generators with shorter electrical distances from overloaded lines. Under the premise of meeting the static safety constraints of the power grid, considering the regulation of generator output and the removal of interruptible loads, a multiobjective cascading failure blocking model is established with the minimum overall control cost of the system and the minimum probability coefficient of line failure. Use the NSGA-II algorithm to solve the model and obtain the optimal plan for adjusting generator output and cutting off load. Through example verification, the proposed method can effectively alleviate the phenomenon of line overload, thereby blocking the continuation of overload-dominant cascading failures. [ABSTRACT FROM AUTHOR]

As important disaster-bearing bodies, buildings are the focus of attention in seismic disaster risk assessment and emergency rescue. It is of great practical significance to extract buildings quickly and accurately with complex textures and variable scales and shapes from high-resolution remote sensing images. We proposed an improved TransUnet model based on multiscale grouped convolution and attention named MATUnet to retain more local detail features and enhance the representation ability of global features, while reducing the network parameters. We designed the multiscale grouped convolutional feature extraction module with attention (GAM) to enhance the representation of detailed features. The convolutional positional encoding module (PEG) was added to redetermine the number of transformer, it solved the problem of local feature information loss and the difficulty of convergence of the network. The channel attention module (CAM) of the decoder enhanced the salient information of the features and solved the problem of information redundancy after feature fusion. We experimented through MATUnet on the WHU building dataset and Massachusetts dataset. MATUnet achieved the best IOU results of 92.14% and 83.22%, respectively, and achieved better than the other generalized and state-of-the-art networks under the same conditions. We also have achieved good segmentation results on the GF2 Xichang building dataset. [ABSTRACT FROM AUTHOR]

In this article, a uniformly convergent numerical scheme is developed to solve a singularly perturbed convection‐diffusion equation with a small delay having a boundary layer along the left side. A priori bounds of continuous solution and its derivatives are discussed. To solve the problem, the Crank–Nicolson scheme in the time direction and the exponentially fitted finite difference scheme in the space direction are used. The stability of the method is analyzed. It is proved that the developed scheme converges uniformly with first order in space and second order in time. To validate the applicability of the theoretical finding of the developed scheme, numerical experiments are carried out by considering two test examples. [ABSTRACT FROM AUTHOR]

In this research, we present an expanded hp‐method for solving time delay optimal control (TDOC) problems, applicable to issues with both smooth and nonsmooth solutions. The method discretizes the time domain using an adaptive grid with unknown switch points. Subsequently, we use the operational integration matrix to approximate the problem's state variable derivative. Next, we approximate the state and control variables using the Legendre–Gauss–Lobatto points and Legendre spectral collocation. This formulation transforms the original problem into a nonlinear programming problem, solvable using relevant techniques. To demonstrate the efficacy of the proposed method, we solve numerical examples and compare the obtained results with those of several exiting methods. [ABSTRACT FROM AUTHOR]

Background. Most frontline nurses lack sufficient readiness for effective disaster response. Therefore, designing a disaster management training program (DMTP) to promote nurses' readiness for disaster response is imperative. Aim. This study aimed to evaluate the effectiveness of a structured DMTP on nurses' readiness for response to disasters. Methods. A randomized controlled trial was conducted. One hundred eligible nurses, recruited using convenience sampling from a medical centre in northern Taiwan, were randomly assigned to either the experimental (EG, n = 50) or control (CG, n = 50) group. Both groups received regular continuous nursing education. The EG received an extra two‐day (16 h) structured DMTP delivered by transdisciplinary collaborations through multiple teaching strategies (lectures, simulations, problem‐solving lessons, demonstrations, tabletop exercises, discussions, group presentations, and reflections). Readiness for disaster response, consisting of four subscales (emergency response, clinical management, self‐protection, and personal preparation), was assessed at baseline and 12 weeks after the intervention. Generalized estimating equations were used as the primary method of data analyses to evaluate the intervention effects. Results. Ninety‐four nurses (94%) completed the study, and 100 nurses were included in the intention‐to‐treat analysis. While participants in the EG had increased readiness for disaster response after training and at the 12‐week follow‐up, those in the CG exhibited no differences between baseline and 12‐week follow‐up. When the group × time interaction was examined, the EG had a greater increase in readiness for disaster response and its four domains, including emergency response, clinical management, self‐protection, and personal preparedness after 12 weeks, than the CG. Conclusion. A two‐day structured DMTP utilizing multiple teaching strategies through transdisciplinary collaborations is recommended to enhance hospital nurses' readiness for disaster response. Implications for Nursing Management. Nursing leaders should consider incorporating such a structured DMTP into ongoing nursing training as a critical component of professional development programs, thereby strengthening nurses' disaster readiness in hospital settings. [ABSTRACT FROM AUTHOR]

Functions in nonlinear programing optimization are sometimes not easily differentiable. When such kinds of functions are present in the optimization problem, then the process of obtaining the solution can sometimes become quite lengthy. Traditional and classical methods cannot be used to solve such optimization problems because such methods assume the functions to be differentiable. Smoothing of nondifferentiable functions is thus required to tackle such difficulties. In this study, we introduce the concept of constructing a technique to smooth such nondifferentiable functions. We begin with the smoothing of the penalty function. On the basis of it, we come up with an algorithm to find the best way to solve an optimization problem with inequality constraints. We also talk about how to figure out the error for a certain smooth penalty function. We also provide numerical examples to demonstrate that the suggested approach is practical and usable. [ABSTRACT FROM AUTHOR]

Flexible screen possessing a high-contrast ratio to accomplish high-definition display can be attributed to the accuracy of polarizer assembly. Different from the existing polarizer attached onto a flexible screen, resulting in low-accuracy and nonalignment attaching behaviors, a unique approach of underactuated bionic scorpion robot arms can be developed to explore the stable capture and accurate alignment motion operations. Overall structure design and D–H kinematic simulation of bionic scorpion robot arm can be conducted to analyze virtual three-key typical motions. Motion optimization of structural parameters and corresponding motion workspaces verification can be adopted to evaluate motion range and ability. Experiments can be utilized to verify the rationality of theoretical modeling and optimization simulation of bionic scorpion robot arm. Experimental results illustrate that it is evident to demonstrate that the motion behaviors of bionic scorpion robot arm can be verified to be consistent with three key states of virtual theoretical motions. The key joints possessing minor errors may also be utilized to illustrate the relatively excellent dynamic motions existing in bionic scorpion robot arm. Further, advancing the stable motion behaviors of bionic scorpion robot arm may solve the problems of low-accuracy and misalignment polarizer attachments. [ABSTRACT FROM AUTHOR]

In order to accurately and efficiently assess the impact of tunnel excavation on overlying existing pipeline, an analytical method is proposed to solve this problem. First, the vertical free displacement of the surrounding soil due to tunnel excavation can be derived by the Loganathan formula. Next, the overlying existing pipeline can be treated as a Timoshenko beam resting on the Vlasov foundation model, and the influence of the surrounding soil on the both sides of the existing pipeline is taken into consideration. Finally, an analytical solution for the longitudinal deformation of the existing pipeline can be obtained by using the integral method. Case analysis results demonstrate that the calculated results of this method closely in line with measured data. Compared to the degenerate analytical solution given by this method, the result from this method is more consistent with the measured data. Further parameter studies show that the volume loss rate, diameter of new tunnel, skew angle, and vertical distance between tunnel and pipeline are significant factors affecting the existing pipeline response due to tunneling underlying. [ABSTRACT FROM AUTHOR]

The urban blue-green space landscape ecology is an important component that supports the urban landscape ecosystem. In this study, a combination model of the grey system theory (GST), analytic hierarchy process (AHP), and technique for order of preference by similarity to ideal solution (TOPSIS) was used to construct criteria layers from the following four aspects: green space vegetation coverage, ecosystem diversity, air and water quality, social participation, and health. The GST method was employed to screen evaluation indicators, the AHP method was used to calculate the weight of each indicator, and finally, TOPSIS was applied for weighted ranking to verify the scientific and rationality of the evaluation system. The results indicated the following: (1) out of 36 indicator factors, 10 were not selected through the GST method; (2) the weight ranking of the criteria layer was as follows, from highest to lowest: D 2 ecosystem diversity 0.4816 > D 1 green space vegetation coverage 0.2608 > D 3 air and water quality 0.1864 > D 4 social participation and health 0.0713; and (3) the relative closeness and ranking of different regions in Jinan city were as follows: Da Ming Hu area > Shan Da Lu area > Gu Cheng area > Shang Bu area. This study can help avoid decision-making errors caused by subjective factors and provide new approaches for the assessment of the ecological health of urban blue-green space landscapes. [ABSTRACT FROM AUTHOR]

Background. As nursing interns enter challenging clinical settings, evaluating their preparation and readiness is vital for adaptation success. Sufficient real-world experience and patient care are crucial preparation components that enable effective practice and higher competencies. Aim. This study aimed to assess nurse interns' perception of clinical preparation and readiness for clinical internship experiences. Methods. A self-administered questionnaire was distributed, comprising three sections on demographics, clinical preparation requirements, and the Casey–Fink Readiness for Practice Survey. Descriptive statistics as the mean and standard deviation, numbers and percentages, linear regression model, and Pearson correlation coefficient were used for reporting normal distribution, categorical variables, and relationship between a scalar response and one or more explanatory variables and to calculate statistics between two continuous variables. Results. The participants were 130 nurse interns who were involved in an internship between 2016 and 2020, 50% of the nurse interns. They had a moderate level of clinical preparation, and 28.5% of them exhibited a low level. In addition, 53.8% were found to be moderately ready for practice, while 22.3% had a low level of readiness Conclusion. The observed significant positive correlation between perceived preparation and readiness underscores the pivotal role of clinical preparation in influencing practice readiness. Implications. These findings emphasize the importance of targeted interventions aimed at enhancing clinical preparation to directly bolster overall readiness for professional practice among nurse interns. [ABSTRACT FROM AUTHOR]

The key objective of this article is to introduce the innovative idea of a complex intuitionistic hesitant fuzzy set (CIHFS), which blends the intuitionistic hesitant fuzzy set with the complex fuzzy set to address the uncertain information in real-life complex problems. In CIHFS, the range of the membership functions is extended from the subset of the real number to the unit disc under the hesitant environment. To determine how well the CIHFSs can be distinguished from one another, we first propose generalized distance measures and weighted generalized distance measures based on the Hamming, Euclidean, and Hausdorff metrics. Some interesting properties and their relationships are thoroughly discussed. Furthermore, a decision-making framework for selecting the optimal option from the feasible set has been proposed, which is grounded in these distance metrics. For the purpose of proving the method's efficacy, we included examples from pattern recognition and medical diagnostics. [ABSTRACT FROM AUTHOR]

Accurate identification of apple leaf diseases is of great significance for improving apple yield. The lesion area of the apple leaf disease image is small and vulnerable to background interference, which easily leads to low recognition accuracy. To solve this problem, a lightweight bilinear convolutional neural network (CNN) model named BLSENet based on attention mechanism is designed. The model consists of two subnetworks, and each subnetwork is embedded with a Squeeze-and-Excitation (SE) module. By using the feature extraction ability of the two subnetworks and combining the bilinear feature CONCAT operation, the multiscale features of the image are obtained. Compared with the unimproved model LeNet-5 (84.63%), BLSENet has higher accuracy in the test set, which indicates that SE module and bilinear feature fusion have a positive effect on the performance of the model, and BLSENet has the ability to identify apple leaf diseases. The model has achieved the expected goal and can provide technical support for accurate identification and real-time monitoring of apple disease images. [ABSTRACT FROM AUTHOR]