Abstract:Demand responsive transit typically operates in chartered or ride-sharing modes. Due to the time-varying road information， using a single operation mode will reduce the operational efficiency. To maximize the use of vehicle resources， a flexible scheduling and fleet configuration method under limited bus resources and multiple operation modes is proposed. First， based on the characteristics of chartered and ride-sharing modes， combined with the new point-to-point ride-sharing mode and heterogeneous fleet characteristics， the above three modes are taken into account as a whole. By designing a double-layer time window and aiming to maximize the operational benefits， a multi-vehicle-type mixed operation scheduling model is constructed. Secondly， the heuristic algorithm of adaptive large neighborhood search algorithm is improved. By optimizing neighborhood search operations， the solution quality is enhanced. Finally， simulation experiments based on real road network data and travel data from Wuhan City are conducted. The results show that， compared with the chartered and ride-sharing models， when the fleet size reaches 100 vehicles， the multi-vehicle-type mixed operation model increases the operational revenue by 9% and 7%， improves the order response rates by 10% and 6%， and reduces the average passenger wait time by 30% and 25%， respectively. Overall， the model enhances both the operator’s and passengers’ benefits.

Abstract:In response to the problem of low accuracy of human digital models leading to significant simulation calculation errors in the safety of human electromagnetic dose inside automobiles， the strategy to improve the accuracy of human digital models is proposed from three aspects. Firstly， a high-resolution medical imaging human digital model that is superior to traditional simplified self-built models is adopted. Then， fully considering the dispersion characteristics of the dielectric parameters of biological tissues with frequency variation， the dielectric parameters of biological tissues measured by different scholars abroad （taking liver and anisotropic muscles as examples） were compared using MATLAB， and domestic and foreign literature data were compared to verify the accuracy of the measurement data. Finally， the smoothed rotation enhanced of as-rigid-as-possible （SR-ARAP） algorithm is introduced to transform the upright posture of the human digital model into a sitting posture， which matches the actual parameters of a certain type of car seat. The results indicate that the digital model of the human in medical imaging has high resolution of various organs and tissues， with around 2.1 million units in the 50th percentile model. The measured dielectric parameters of biological tissues by different scholars show good agreement in the mid-frequency range but poor consistency in the low-frequency and high-frequency ranges. Compared with the traditional as-rigid-as-possible （ARAP） algorithm， SR-ARAP improves the collapse of popliteal fossa formation， and the volume change of the main tissue in SR-ARAP is mostly less than 50% of ARAP， which has the advantage of low deformation distortion.

Abstract:To explore the aerodynamic performance of high-speed trains with lift airfoil when passing by each other， a model of a CRH high-speed train with a three-car formation was taken as the research object， and the influence of different train intersecting speeds on the aerodynamic performance of high-speed trains with lift airfoil was discussed. The results show that the first airfoil in the direction of travel experiences more lift. The lift on the intersecting side is more susceptible to the non-intersecting side. As the velocity increases， the lift generated by the lift airfoil device also increases， but its amplification decreases. The middle car is less affected by the lateral force than the head car and tail car. With the increase of the speed， the maximum lateral force of the train gradually increases， but the amplification decreases. The intersecting side is obviously subjected to stronger trackside pressure than the non-intersecting side. With the increase of the distance from the centerline of the intersection， the change of pressure gradually decreases， but the overall trend remains consistent， showing an overall trend of “positive-negative-negative-positive”.

Abstract:Using the gas-phase chemical reaction kinetics software CHEMKIN PRO， the basic reaction chain of the detailed chemical reaction kinetics model of n-butanol was numerically analysed， so as to find out the main reaction paths and intermediate products involved in the low-temperature and high-temperature reaction phases of n-butanol fuel. Based on the semi-decoupling methodology， the small molecule mechanism of C1/CO/H2 was taken as the kernel for n-butanol， and coupling the main mechanisms of low-temperature reaction and the transition reaction from large molecules to small molecules， a new reduced chemical reaction kinetic model of n-butanol with 70 species and 150 reactions was developed， which was validated by the tested data of basic reactors， such as the one-dimensional laminar flame speed and shock tube. The results show that the developed new reduced mechanism of n-butanol can both accurately calculate the ignition delay time， and reasonably predict the evolution trend of the laminar flame speed.

Abstract:To investigate the effect of the jet hole structure parameters and the flow field conditions on the drag reduction of the underwater jet， a biomimetic fish model is established with bonito fish as the biomimetic object. The jet model is established by adding a crescents jet hole to the side of the biomimetic fish model by simulating shark gills. The effects of air jet model and water jet model on drag reduction under different jet hole geometry parameters and different flow field conditions are analyzed by numerical simulation. In the range of conditions set in this paper， when the jet hole position X=20 mm， the aspect ratio k=2， the jet hole height h=15 mm， the velocity ratio is 0.5， and the mainstream field velocity is 10 m/s， the maximum drag reduction rate of the water jet model is obtained as 24.64 %， and the maximum drag reduction rate of the jet model is 10.17 %， which shows that the water jet model has a good drag reduction effect. In this paper， the effects of jet medium on the surface drag reduction of bionic fish is also analyzed by CFD simulation， which provides a basis for the design of new underwater vehicles.

Abstract:To address the technical bottleneck of traditional knurling processes failing to meet precision requirements for expected interference fit dimensions， an innovative arc-topped knurling structure was proposed. To systematically evaluate the mechanical characteristics and mating performance of the proposed structure， a comprehensive investigation combining theoretical modeling， finite element simulation， and experimental validation was conducted. Initially， the accuracy of the finite element model was verified through theoretical modeling of cylindrical interference fits. Subsequently， finite element models for both conventional knurling and arc-topped knurling were established to investigate the influence patterns of key geometric parameters （tooth height and pitch） on stress distribution characteristics. Building upon this foundation， comparative analysis of mechanical performance differences among cylindrical interference fits， conventional knurling interference fits， and arc-topped knurling interference fits was performed， with particular emphasis on analyzing variations in push-out to press-in ratios， accompanied by systematic experimental validation. The research demonstrates that the arc-topped knurling structure exhibits superior mechanical performance， achieving a push-out to press-in ratio of 1.979. This represents a 52.231% improvement over cylindrical interference fits （1.3） and a 16.412% enhancement compared with conventional knurling structures （1.7）， essentially approaching the performance level of axial-radial coupled knurled shafts （2.0）.

Abstract:There is little research on the aerodynamic force and galloping characteristics of iced conductors under skew wind. By considering the geometric relationship between elevation angle， yaw angle， and wind incidence angle， expressions for the aerodynamic forces （drag， lift， and torque） of conductors under skew wind were derived. These expressions accounted for the effects of relative attack angle， yaw angle， and relative wind speed changes on aerodynamic forces during the conductor’s motion. A balance connection device with adjustable tilt and attack angles was developed， and high-frequency balance wind tunnel tests were conducted to obtain the three-dimensional aerodynamic coefficients in the full range of wind attack angles of a crescent-shaped iced conductor under different yaw angles. The results show that the increase of yaw angle reduces the drag coefficient， but simultaneously weakens the sharp peaks of the lift and torque coefficients versus the wind attack angle； Both Den Hartog criterion and the system’s equivalent damping ratio reflect that increasing the yaw angle improves the conductor’s galloping stability. Numerical simulations of galloping responses for a 500 m span crescent-shaped iced conductor under different yaw angles show that the wind speed projection method is only applicable within a limited range of yaw angles （≤15°）； Increasing the yaw angle significantly lowers the aerodynamic negative damping value， thereby reducing the galloping divergence speed and amplitude. Moreover， there exists a critical yaw angle beyond which the conductor will not gallop under skew winds exceeding this angle. Therefore， in line design， reducing the angle between the line direction and the dominant wind direction during the ice-covered period can effectively reduce the risk of galloping.

Abstract:To reveal the factors influencing wind-induced vibration of transmission lines under complex mountain wind fields， a refined finite element model of “two towers and three lines” is established based on the actual line parameters of the 110 kV Lian’nan transmission line in Ningxia. The gravity self-balancing method was used for the shape-finding calculation of the transmission line. The harmonic superposition method is used to simulate the stochastic wind field where the line is located， and wind loads are applied to the tower-line system model to analyze the influencing factors of wind-induced vibration of mountain transmission lines. Results show that the acceleration effect of mountain wind fields is significant， with acceleration ratios reaching 1.3 to 1.4 when the wind incidence angle is 45° and the wind direction angle is 90°， which can easily induce severe line wind-induced vibrations. Compared to models without towers， the tower-line system model shows larger and more realistic wind vibration response amplitudes； when the initial tension of the conductor increases from 16 to 26 kN， its horizontal and vertical amplitudes are decreased by 31.1% and 23.4%， respectively. When the line damping ratio increases from 0.02 to 0.15， the conductor's horizontal and vertical amplitudes are decreased by 36.4% and 44.2%， respectively. Increasing the initial tension and damping ratio effectively suppresses wind-induced vibrations of the lines. This study reveals the collaborative mechanism of mountain wind field acceleration effects and tower-line dynamic coupling， quantitatively evaluating the impact of key parameters on line wind-induced vibration. The proposed initial tension optimization and damping ratio enhancement measures provide important technical support for the wind-resistant design of transmission lines in mountainous regions.

Abstract:Based on the spherical fuzzy hierarchy method， this paper proposes a method for evaluating and selecting capacity increasing conductors for a 500 kV transmission line in central China， taking into account practical application scenarios. The evaluation indicators are based on the basic characteristics of the capacity increasing wire， and they are analyzed from four aspects： electrical performance， thermal performance， mechanical performance， and economy. The spherical fuzzy analytic hierarchy process is used to construct the hierarchical analysis system structure， and the influence of practical application scenarios is considered. The fuzzy analysis theory is applied to the comparison matrix construction process to establish a spherical fuzzy comparison matrix that meets the engineering requirements. The scoring is based on the spherical fuzzy scoring function. The case calculation results show that in areas with high transportation capacity demand， aluminium clad steel core heat-resistant aluminium alloy wire is superior to other wires. In the cross mountain scenarios， carbon fiber composite core soft aluminium stranded wire is superior to other wires.

Abstract:To improve the prediction accuracy of photovoltaic power， an EGO-CEEMDAN-VMD-BiGRU short-term photovoltaic power prediction model is proposed based on the dual data decomposition method of parameter optimization. Initially， the eel and grouper optimizer （EGO） algorithm is employed to determine the optimal parameters for complete ensemble empirical mode decomposition with adaptive noise （CEEMDAN）， thereby performing an initial decomposition of the photovoltaic dataset. Subsequently， the K-means clustering algorithm is utilized to categorize the modal components into high-frequency， medium-frequency， and low-frequency groups， effectively reducing redundancy among the components. Then， the EGO algorithm is used to optimize the parameters of variational mode decomposition （VMD）. Following this， the high-frequency component is decomposed for the second time to mitigate the non-stationarity of the sequence. Finally， bidirectional gated recurrent unit （BiGRU） is applied to predict the components derived from the two-stage decomposition process， with the final prediction result obtained through summation. Based on the dataset from a photovoltaic power plant in Ningxia， the EGO-CEEMDAN-VMD-BiGRU model was compared with the BiGRU， VMD-BiGRU， and CEEMDAN-VMD-BiGRU models. Under three distinct weather conditions， the average MAE was reduced by 68.93%， 55.84%， and 44.56%， respectively， while the RMSE was decreased by 68.23%， 53.38%， and 41.03%， respectively. The experimental results demonstrate that the proposed photovoltaic power prediction model exhibits high accuracy and stability， thereby holding practical significance for ensuring the safe and reliable operation of power systems.

Abstract:The phase circulation problem of low-voltage microgrid parallel inverter system seriously affects the power quality and conversion efficiency of the output side of micro-grid. Therefore， sliding mode control （SMC） was introduced to design a compound suppression strategy of phase circulation （CSSPC）. Firstly， according to the generation mechanism of phase circulation in parallel system， the inter-phase circulation and intra-phase circulation are modeled， and the inhibition mechanism of different phase circulation is analyzed and given. Then， for the inter-phase circulation of the parallel system， combined with the traditional virtual impedance droop control （VIDC）， the robust droop SMC controller was obtained by improving the design： bus voltage response， droop loop output accuracy and virtual induced reactance regulation， in order to improve the power distribution accuracy of the parallel system and restrain the inter-phase circulation； The parametric stability of the robust droop SMC controller is analyzed based on the theory of small signal perturbation. For the intra-phase circulation of parallel system， a zero-sequence voltage SMC suppressor is designed to dynamically adjust the action time of zero vector in space vector pulse width modulation （SVPWM） and to indirectly suppress the intra-phase circulation of parallel system by eliminating zero sequence voltage. Finally， simulations are designed， and the results to show that the CSSPC strategy can control the system inter-phase and intra-phase circulation coefficients within 1.49% and 0.72% respectively， which proves the effectiveness of the proposed strategy.

Abstract:This article focuses on the distribution characteristics of rain film on the surface of roof insulators in high humidity environments. Based on the aerodynamic calculation model of insulator flow field， combined with the discrete phase model and Enlerian wall film model methods， the process of high-speed airflow rain film generation and development on the surface of insulators is simulated. The system studies the influence of different wind speeds， rainfall intensities， and structural parameters such as the uptilt angle， dip angle， and spacing between insulator sheds on the distribution of rain film. And a high-speed droplet flow roof insulator power frequency withstand voltage test platform is built to analyze the impact of uneven distribution of rain film on the electrical performance of insulators. The research results show that under the condition of maximum wind speed and maximum rainfall intensity， the time for the average rain film thickness on the windward side of the insulator reaching the stability is the shortest. At the same time， the windward side of the insulator is directly affected by rain， and the average rain film thickness is greater than that of the crosswind side and the leeward side. Raindrops mainly collide with inertia on the windward and crosswind sides of insulators， while vortex collisions are predominant on the leeward side. At a high voltage of 27.5 kV and a wind speed of 40 m/s， there is droplet flow and discharge arc between the sheds on the leeward side of the insulator， and obvious droplet scattering can be observed near the edges of the sheds. As the uptilt angle of the shed increases， the thickness of the rain film gradually decreases. The influence of the dip angle of the shed on the thickness of the rain film is not significant. Considering the requirement for mechanical strength， it is recommended to use 0° dip angle. In addition， choosing a smaller shed spacing is beneficial for reducing the thickness of the rain film on the insulator surface.

Abstract:To improve the transient characteristics of the output-capacitor less low-dropout linear regulator （LDO）， a load detection circuit and overshoot/undershoot suppression circuits are designed and optimized to realize a output-capacitor less LDO with low power consumption and high transient characteristics. By utilizing the high-proportion current mirror to sample and follow the change of the LDO load current， the load detection circuit can adaptively change the tail current of the error amplifier to improve the system’s bandwidth and slew rate， thereby enhancing the transient response speed of the LDO. When overshoot occurs in the output voltage， the overshoot suppression circuit utilizes the high-pass network to detect the change of the gate voltage of the power transistor， enabling a discharge path for the load current to reduce its change in the output stage， so as to suppress the overshoot. When the output voltage undershoot occurs， the undershoot suppression circuit can rapidly increase the output current of the power transistor by opening the discharge path for the gate-drive current of the power transistor， and then effectively suppress the undershoot. Based on 0.5 μm CMOS process， the circuit is designed and tested. The results show that the input voltage of the LDO is 2~5.5 V， and the output voltage is 1.2 V； the maximum load current is 150 mA， with the linear regulation of 1.7×10-3； when there is no load， the quiescent current is less than 6.16 μA； when the load current varies in 1~150 mA@ 1 μs， both the undershoot and overshoot voltages are less than 300 mV. The LDO has the advantages of low power consumption and high transient characteristics， which can meet the application needs of portable electronic devices.

Abstract:Although modern information technology provides real-time and visual management convenience for commodity supply chains， digital information circulation brings privacy security issues. To address this problem， an ownership transfer and tracking scheme is proposed through using RFID， blockchain and modern cryptography technology. Specifically， we first establish a formal model of the ownership transfer and tracking scheme. Then， we define the security of the ownership transfer and tracking scheme from two aspects： unforgeability and privacy. Finally， we design ordered aggregate signature based on which an efficient， secure and privacy-protected ownership transfer and tracking scheme （OTT） is presented. The tags of OTT are only required to have basic computing and storage capabilities， so the OTT scheme can be applied to lightweight tags. The ordered aggregate signature not only compresses the data of blockchain but also provides a way to characterize the circulation path.

Abstract:In the simultaneous localization and mapping method of robots， the visual scheme has poor stability in indoor scenes with insufficient texture， and the use of structured assumptions can alleviate the above problems. However， if the indoor scene does not strictly meet the structured assumptions， it will lead to greater pose drift. More general structural assumptions and more reliable loopback detection methods can help solve the above problems and improve the robustness of indoor scene visual positioning. To this end， this paper proposes a robust multi-layer spatial structure assumption visual SLAM method. This method makes full use of the structured information in the scene， uses the main direction constraint to define the scene to assist the positioning， and uses a lightweight structured hypothesis loopback to reduce the cumulative drift， so as to construct a high robustness and low drift simultaneous localization mapping algorithm. We conduct a large number of experiments on real vehicle data and open source data sets. The experimental results show that the proposed method has higher positioning robustness and accuracy performance than other open source methods. The loopback detection method has a higher detection rate， and the positioning accuracy in the closed-loop scene is improved by 31.8% on average.

Abstract:In complex environments， traditional infrared detection methods are severely limited， necessitating the fusion of polarization technology with infrared technology. This fusion is aimed at existing convolutional neural network methods， which lack the capacity to extract multi-scale information and fuse subnetworks adequately. The objective is to enhance the quality of infrared polarization fusion images and improve the target recognition capability of infrared imaging technology in complex backgrounds. This paper proposes a progressive infrared polarization image fusion method （PIPFuse） based on multi-scale features. Firstly， the feature extraction component employs a semantic extraction module and a multiscale dense block， which are utilized to extract semantically enhanced multiscale depth features. Secondly， to reduce the information loss and enhance the salient information， the fusion subnetwork incorporates a progressive difference information enhancement fusion module for the feature fusion. Finally， the final fused image is obtained by decoding the fused features. In comparison to nine classical image fusion methods， this method demonstrates superior performance in six evaluation indexes. Furthermore， the subjective visualization of the target texture is more distinct and exhibits higher contrast.

Abstract:As the world’s largest strawberry producer country， accurate detection of strawberry diseases in China is an effective measure to ensure the quality and yield of strawberries. To address the issues of low detection accuracy under complex backgrounds and difficulty in detecting subtle diseases， an improved real-time detection transformer （RT-DETR） network-based strawberry disease detection method is proposed. First， the backbone feature extraction network is reconstructed using the AdditiveBlock-CGLU module to enhance the model’s ability to represent deep critical features under complex background interference. Second， a multi-scale cross-layer block feature fusion pyramid network （MS-CBFPN） is proposed to optimize the feature fusion part of the model， enabling more effective integration of information across different layers and fully capturing the contextual information of images， thus improving the model’s ability to detect subtle disease features. Finally， a progressive re-parameterized batch normalization （PRepBN） structure is introduced into the attention-based intra-scale feature interaction （AIFI）， enabling dynamic adjustment of the learning rate and re-parameterization methods so that the model can better adapt to changes at different training stages， further enhancing the model’s disease detection capability. Experimental results show that the improved model improves accuracy， recall， mAP@0.5， mAP@0.5：0.95， and F1 score by 3.4， 7.6， 3.3， 8.0， and 5.6 percentage points， respectively， and also outperforms other models， indicating that the improved RT-DETR model is an effective strawberry disease detection model in complex scenarios.

Abstract:Coverage is an important index to test the completeness of chip verification， especially functional coverage， which can measure whether the functional characteristics of the design are fully verified. At present， for the collection of function coverage， the general practice is to set function points in the coverage group， divide the test scene into a specific number of bins according to complexity， and then run the simulation to determine whether each bin is hit. Its implementation is relatively simple， but due to the existence of various factors， the hit situation of each bin in a function point is often unbalanced， resulting in insufficient coverage of some scenes. To solve this problem， a verification method based on machine learning algorithm to achieve uniform coverage distribution is proposed. By training neural networks， various excitation vectors can be accurately predicted. In this method， the reverse network prediction method and the forward network real-time fitting method are designed respectively for small and large number of covered bins， which can realize the balanced hit of each bin easily. The experimental results show that， compared with the case where the difference between the maximum and the minimum hit times of random test coverage points is several orders of magnitude， the small point bins can basically achieve the average distribution and the large point bins can reduce the extreme value ratio to less than 1.5 times， thus significantly reducing the verification risk of some cases.

Abstract:To solve the problem of spacecraft static random access memory data error caused by single event effect， the static random access memory online error detection method and circuit implementation technology， based on the combination of error checking and correcting circuit and integrity detector， are studied in this paper. The error checking and correcting circuit is designed using （39，32） Hamming code to realize automatic error detection， and error correction of volatile single-bit when data is accessed. The integrity detector is designed based on the principle of hash function verification to realize periodic cyclic checking of data. Data online error detection circuit is fabricated in CMOS 0.18 μm process. Simulation results show that the circuit can actively periodically check the memory data， correct single-bit errors and detect multi-bit errors， and effectively improve data reliability.

Abstract:To address the challenges of excessive pilot overhead and limited adaptability in cascade channel estimation for reconfigurable intelligent surface （RIS） assisted wireless communication systems，this paper proposes an improved whale optimization algorithm integrated with a dual-structure sparse stagewise weak orthogonal matching pursuit algorithm （IWOA-DS-SWOMP）. The framework employs an adaptive threshold-controlled SWOMP mechanism to iteratively select multiple highly correlated atoms for constructing atomic support sets， while the atomic selection threshold via IWOA is dynamically optimized to adapt to real-time channel variations. This dual optimization strategy enhances atomic support set extraction accuracy， improves channel estimation precision， and reduces algorithm runtime. Simulation results demonstrate that the proposed scheme achieves superior normalized mean square error （NMSE） performance compared to conventional RIS cascade channel estimation methods， attaining higher channel estimation accuracy with reduced pilot overhead while exhibiting enhanced adaptability and robustness under diverse channel conditions.