Low-altitude inspection technology is evolving into a key component of modern inspection systems due to its significant advantages in cost reduction and efficiency improvement.The efficient operation of unmanned aerial vehicle(UAV)inspections relies on a well-structured top-level planning system,whose core challenges can be summarized into three closely related decision-making layers:site selection,task allocation,and path planning.This paper systematically reviews the current research status and modeling methodologies of this integrated plan-ning framework.Firstly,task characteristics are classified and analyzed from multiple dimensions,including inspec-tion targets,operational scenarios,and task combinations.Subsequently,the modeling approaches,optimization ob-jectives,and constraint systems of the three core layers—site selection,task allocation,and path planning—are elaborated in detail.By establishing a three-tier analytical framework,the review provides a more systematic and hi-erarchical analytical perspective for the field.Finally,addressing current research bottlenecks in system coordina-tion,real-time responsiveness,and environmental adaptability,future research directions are outlined.These in-clude three-level integrated optimization,cloud-edge-device collaborative computing,and robust planning through the integration of data-driven and physics-based models.The goal of this study is to offer a comprehensive refe-rence for both theoretical research and engineering practice in the advancement of intelligent planning systems for UAV inspection.
In the linear control of cantilever construction for long-span continuous rigid-frame bridge,existing pre-diction methods exhibit systemic deficiencies in both model construction and learning mechanisms.The traditional methods suffer from weak nonlinear fitting capabilities,while machine learning models are prone to local optima or insufficient generalization performance.In addition,most methods adopt a static modeling paradigm characterized by offline training and fixed parameters,which makes it difficult to dynamically adapt to the time-varying characte-ristics of structural responses and the accumulation of errors during construction.To overcome this problem,this study proposes a COA-BP model combining crayfish optimization algorithm(COA)and BP neural network,and in-novatively introduces an incremental learning mechanism.Firstly,based on FEA NX,a refined solid finite element model was established.Considering the variability of key parameters such as concrete unit weight,elastic modulus and prestressed tension control stress,the Latin hypercube sampling was used to generate the input parameter com-bination,and the theoretical formwork elevation of each beam section was inversely calculated.The measured ele-vation was obtained after the completion of the site construction,and the difference between the two was used as the output target of the model.Then,the COA algorithm was used to optimize the initial weights and thresholds of the BP network,effectively improving the model's convergence speed and global search capability.On this basis,a phased learning strategy was designed:segments No.3,4,and 5 were used for the static learning phase,where the model is initialized using the differences between measured and theoretical elevations.From block 6 onwards,the incremental learning phase begins,during which the model guides the adjustment of formwork placement elevations based on prediction results.After each construction phase,the elevation differences corresponding to newly mea-sured data were incorporated into the training set,enabling a dynamic closed loop of"construction,learning,and op-timization in parallel."The proposed method is validated using an actual continuous rigid-frame bridge project.The results show that after the correction at segment No.6,the maximum error is reduced to-1.8 mm,and the pre-diction errors for subsequent beam segments converge continuously,with a smoothly declining prediction curve.This performance is significantly superior to that of traditional methods,demonstrating the effectiveness of the pro-posed COA-BP model in improving the accuracy and adaptability of linear prediction.
To improve the efficiency of urban last-mile logistics distribution and promote the development of the low-altitude economy,this study proposes a site location method for hierarchical UAV takeoff and landing sites tai-lored to urban low-altitude logistics demands.First,a conditional Logit model was utilized to identify key influen-cing factors and evaluate urban low-altitude logistics demand.Second,the polygon intersection point set method for multi-level facilities was applied to determine the candidateset of UAV takeoff and landing sites.Finally,a multi-objective maximal coverage location model for hierarchical UAV takeoff and landing sites was established,with opti-mization objectives of maximizing demand coverage and minimizing construction costs and the rate of redundant de-mand coverage.An improved NSGA-Ⅲ algorithm was designed to solve the model.The results show that the per-formance of facilities is optimal when the number of vertiport sites and points respectively reach 53 and 107 in Shanghai,with a demand coverage rate of 85.6%,construction costs amounting to 9.59 million CNY,and a redun-dant demand coverage rate of 33.7%.The location scheme demonstrates high rationality and feasibility.In addi-tion,the study reveals that economic development level and transportation accessibility significantly influence the spatial distribution of UAV takeoff and landing sites.Setting sites in areas with high GDP and abundant transporta-tion facilities can further enhance demand coverage,although it may lead to increased construction costs and ser-vice range redundancy.The research can provide scientific decision-making support for the planning and imple-mentation of urban low-altitude logistics systems.
The rapid development of quantum computing poses a threat to existing public-key cryptographic systems,and isogeny-based cryptography has become an important component in advancing post-quantum cryptographic research.The CSIDH protocol,owing to its balance of security and efficiency,is one of the few practical isogeny-based key exchange protocols available today.This paper investigates and accelerates CSIDH-like protocols by utilizing Montgomery supersingular elliptic curves defined over a prime field with p≡7(mod 8),whose endomorphism ring is isomorphic to O=Z[√-p].And a new isogeny-based key exchange protocol called CSIDH-G is constructed.The paper establishes a one-to-one correspondence between the coefficients of Montgomery supersingular elliptic curves and their isomorphism classes,hereby preserving the advantage of low public key size.Furthermore,it is proved that the proposed protocol avoids the key collisions of order 3 present in CSIDH and those of order 1 in CSURF,and a compact interval for user private key selection is proposed.Finally,experiments on protocol efficiency are conducted.By optimizing the key selection interval,specifically,by expanding the exponent selection ranges for low-degree isogenies such as 3-isogenies and 5-isogenies,the proposed protocol achieves about a 5.95%improvement in operational efficiency over the original CSIDH protocol,validating its accuracy and effectiveness.This algorithm offers multiple advantages,including improved efficiency of isogeny-based key exchange protocols,simplicity in the public key verification process,avoidance of private key collisions existing in current CSIDH-like protocols,and increased diversity in Diffie-Hellman-style post-quantum cryptographic systems.
To assess the performance of isolated stairs in self-centering frame structures,the controlled rocking re-inforced concrete frame(CR-RCF)was selected for analysis.A finite element model of a four-story self-centering frame structure was established,and stairs with different configurations were incorporated to compare and analyze the dynamic responses of four models under frequent and rare earthquakes.The findings reveal that under frequent earthquakes,compared to the fixed staircase model,the maximum inter-story drift ratios of the sliding stairs and rubber-isolated stairs are approximately twice that of fixed stairs,while the base shear forces are reduced by 37%and 43%,respectively.Under rare earthquakes,the base shear reductions of the two types of isolated stairs reduce 45%and 34%,indicating their effectiveness in reducing the structural seismic dynamic response of the structure.Additionally,under rare earthquakes,the inter-story drift ratios of sliding stairs and rubber-isolated stairs can reach up to 3.8 and 3.47 times that of fixed stairs on the same floor,respectively.However,the maximum sliding dis-placement remains below the design limit,verifying their safety and reliability under extreme seismic conditions.This research offers an initial investigation into stair selection in self-centering frame structures and confirms that rubber-isolated stairs and sliding stairs are well-suited to self-centering frame structures,effectively protecting the main structure from severe damage and thereby enhancing the overall seismic performance and safety of the buil-ding.Therefore,it is recommended that rubber-isolated stairs or sliding stairs be given priority in the design of self-centering frame structures to improve the seismic safety level of the structure.
