Search Results (62)

Indoor location-based services and applications need to obtain information about the indoor spatial layouts and topological relationships of indoor spaces. The 3D city modeling data standard CityGML describes the indoor geometric and semantic information of buildings, but the surfaces composing a volume are discrete, leading to invalid volumes. Moreover, the topological adjacency relationships of adjacent indoor spaces have not yet been described, which makes it difficult to realize effective queries and analyses for indoor applications. In this paper, we present a 3D topological data model for indoor spaces that adopts five topological primitives, namely, node, edge, loop, face, and solid, to describe the topological relationships of indoor spaces. Then, by improving the existing face-sorting method according to vector products in 3D space, a method for constructing 3D topological relationships for indoor spaces is proposed, which successively constructs the topological hierarchical combination of volume and the topological adjacency relationships of adjacent volumes. The experimental results show that by using the improved face-sorting method proposed in this work, the relative positions of faces are directly determined to sort the faces set, which avoids relatively cumbersome calculations and improves the efficiency of constructing 3D topological relationships for indoor spaces. Full article

The advancement of the Internet of Autonomous Vehicles has facilitated the development and deployment of numerous onboard applications. However, the delay-sensitive tasks generated by these applications present enormous challenges for vehicles with limited computing resources. Moreover, these tasks are often interdependent, preventing parallel computation and severely prolonging completion times, which results in substantial energy consumption. Task-offloading technology offers an effective solution to mitigate these challenges. Traditional offloading strategies, however, fall short in the highly dynamic environment of the Internet of Vehicles. This paper proposes a task-offloading scheme based on deep reinforcement learning to optimize the strategy between vehicles and edge computing resources. The task-offloading problem is modeled as a Markov Decision Process, and an improved twin-delayed deep deterministic policy gradient algorithm, LT-TD3, is introduced to enhance the decision-making process. The integration of LSTM and a self-attention mechanism into the LT-TD3 network boosts its capability for feature extraction and representation. Additionally, considering task dependency, a topological sorting algorithm is employed to assign priorities to subtasks, thereby improving the efficiency of task offloading. Experimental results demonstrate that the proposed strategy significantly reduces task delays and energy consumption, offering an effective solution for efficient task processing and energy saving in autonomous vehicles. Full article

In this study, we examined how the nonlinearity $\alpha$ of the Langevin equation influences the behavior of extremes in a generated time series. The extremes, defined according to run theory, result in two types of series, run lengths and surplus magnitudes, whose complex structure was investigated using the visibility graph (VG) method. For both types of series, the information measures of the Shannon entropy measure and Fisher Information Measure were utilized for illustrating the influence of the nonlinearity $\alpha$ on the distribution of the degree, which is the main topological parameter describing the graph constructed by the VG method. The main finding of our study was that the Shannon entropy of the degree of the run lengths and the surplus magnitudes of the extremes is mostly influenced by the nonlinearity, which decreases with with an increase in $\alpha$. This result suggests that the run lengths and surplus magnitudes of extremes are characterized by a sort of order that increases with increases in nonlinearity. Full article

In this study, a graph-based method is implemented for sensor placement in a water distribution network (WDN) instead of using a hydraulic model. The proposed methodology determines the pressure sensors’ location based on the node betweenness centrality of nodes from their source, considering the WDN topology and assigning hydraulic-inspired edge weights. Furthermore, the Non-dominated Sorting Genetic Algorithm (NSGA-II) determines the end node of the WDN’s critical paths for sensor placement to maximize monitoring network efficiency to calibrate the model and avoid additional data collection. For different numbers of sensors, the NSGA-II algorithm is implemented 10 times and the final Pareto front is determined. The graph-based approach reduces the sensor placement problem complexity to an acceptable level and can be implemented as a surrogate approach for hydraulic-based sensor placement. Full article

The scientific and rational assessment of the evolution of node importance in rail transit line networks is important for the sustainability of transportation systems. Based on the complex network theory, this study develops a weighted network model using the Space L method. It first considers the network topology, the mutual influence of neighboring nodes of the transportation system, and the land use intensity in the station influence domain to construct a comprehensive index evaluation system of node importance. It then uses the covariance-weighted principal component analysis algorithm to more comprehensively evaluate the node importance evolution mechanism and analyzes the similarity and difference of the sorting set by adopting three different methods. The interaction mechanism between the distribution of important nodes and the evolution of land use intensity is explored in detail based on the fractal dimension theory. The Xi’an rail transit network is considered an example of qualitative and quantitative analysis. The obtained results show that the importance of nodes varies at different times of the day and the complexity of the morning peak is more prominent. Over time, articulated fragments with significance values greater than 0.5 are formed around the station, which are aligned with the direction of urban development, creating a sustainable mechanism of interaction. As the network’s crucial nodes in the center of gravity increase and the southern network expands, along with the increased intensity of the city’s land utilization, the degree of alignment in evolution becomes increasingly substantial. Different strategies for attaching the network, organized based on the size of $S_i$ can lead to the rapid damage of the network (reducing it to 0.2). The identification of crucial nodes highlighted in this paper serves as an effective representation of the functional characteristics of the nodes in transportation networks. The results obtained can provide a reference for the operation and management of metro systems and further promote the sustainable development of transportation networks. Full article

The two cryptic grasshopper species of the genus Stenobothrus, S. eurasius and S. hyalosuperficies, demonstrate different acoustic behavior despite a strong similarity in morphology. A hybridization between these species is possible in the contact zone; however, there are little molecular data about the relationships of these species. The analysis of the mtDNA control region (CR) reveals that haplotypes of S. hyalosuperficies have more in common with the more distant Stenobothrus species than with the closely related S. eurasius. In the contact zone, S. eurasius has mt-haplotypes shared with S. hyalosuperficies, which might indicate an introgression of mtDNA from S. hyalosuperficies to the S. eurasius gene pool. We also analyze the structure and evolutionary rate of the mtDNA CR for the Stenobothrus genus and estimate the time of divergence of the species within the genus. The phylogenetic tree of the tribe Stenobothrini reconstructed with either the CR or COI gave the same four groups. The phylogenetic tree of the Stenobothrus genus has a star-like topology with each mtDNA haplotype found in any analyzed species, except S. eurasius, which forms a separate branch. The maximum degree of incomplete lineage sorting can demonstrate either ancestral polymorphism or introgression. Full article

This study developed an optimization model for the strategic location of maintenance resource supply sites and the scheduling of multiple resources following failures in urban metro systems, with the objective of enhancing system resilience. The model employs a multi-objective optimization framework, focusing primarily on minimizing resource scheduling time and reducing costs. It incorporates critical factors such as spatial location, network topology, station size, and passenger flow. A hybrid method, combining the non-dominated sorting genetic algorithm III and the technique for order of preference by similarity to ideal solution, is used to solve the model, with its effectiveness confirmed through a case study of the Nanjing Metro system. The simulation results yielded an optimal number of 21 maintenance resource supply stations and provided their placement. In the event of large-scale failures, the optimal resource scheduling strategy ensures demand satisfaction rates exceed 90% at critical stations, maintaining an overall rate of 87.09%, therefore significantly improving resource scheduling efficiency and the system’s emergency response capabilities and enhancing the physical resilience and recovery capabilities of the urban metro system. Moreover, the model accounts for economic factors, striving to balance emergency response capabilities with production continuity and cost efficiency through effective maintenance strategies and resource utilization. This approach provides a systematic framework for urban metro systems to manage sudden failures, ensuring rapid recovery to normal operations and minimizing operational disruptions in scenarios of limited resources. Full article

Line planning and timetabling play important roles in the design of urban rail transportation services. Due to the complexity of the integrated optimization of entire transportation plans, previous studies have generally considered line planning and timetabling design independently, which cannot ensure the global optimality of transportation services. In this study, the integrated design problem of line planning and timetabling was characterized as an equilibrium space–time network design problem and solved with a bi-objective nonlinear integer programming model. The model, in which train overtaking and passenger path choice behavior were considered, adjusted the network topology and link attributes (time and capacity) of the travel space–time network by optimizing the train service frequency, operation zone, stopping pattern, train formation, and train order to minimize the system life cycle cost and total passenger travel time perception. An algorithm was constructed using the non-dominated sorting genetic algorithm II combined with the self-adaptive gradient projection algorithm to solve the model. A real-world case was considered to evaluate the effectiveness of the proposed model and algorithm. The results showed that the model not only performed well in the trade-off between system cost and passenger travel efficiency, but it could also reduce the imbalance of train and station loads. Pareto front analysis of the model with different parameters showed that more types of trains did not correlate with a better performance, some line-planning strategies had a combination effect, and multi-strategy line planning was more suitable for scenarios with a high imbalance in the temporal and spatial distributions of passenger flow. Full article

This study focuses on the streets and spatial networks of the historic urban area in Changsha, the capital of Hunan Province, China, by mainly investigating the evolution of their geometric and topological characteristics. It draws on the theories and methods of urban morphology and space syntax, combines the digital historical maps at different times, and uses methods such as historical map spatial interpretation, geographic information system (GIS), sDNA tools, and urban morphological parameter analysis to explore and sort out the evolutionary process of the street and alley network in Changsha from the early modern period to the present. The paper constructs a parameter system for analyzing the street and alley network of historic urban areas from a geometric and topological perspective. It introduces the indicators of road density, road orientation, intersection density, and approaches such as closeness, betweenness, and intelligibility in space syntax into the parameter analysis framework of street and alley network morphology and spatial characteristics evolution. By comparing the changes in various parameters at different spatial scales, the process of the spatial order evolution of the street and alley network in the historic urban area is analyzed, and the evolutionary rules of the various periods’ morphological characteristics are extracted. Full article

Recently, the task of acquiring causal directed acyclic graphs (DAGs) from empirical data has been modeled as an iterative process within the framework of continuous optimization with a differentiable acyclicity characterization. However, learning DAGs from data is an NP-hard problem since the DAG space increases super-exponentially with the number of variables. In this work, we introduce the graph topological sorts in solving the continuous optimization problem, which is substantially smaller than the DAG space and beneficial in avoiding local optima. Moreover, the topological sorts space does not require consideration of acyclicity, which can significantly reduce the computational cost. To further deal with the inherent asymmetries of DAGs, we investigate the acyclicity characterization and propose a new DAGs learning optimization strategy based on QR factorization, named DAGOR. First, using the matrix congruent transformation, the adjacency matrix of the DAG is transformed into an upper triangular matrix with a topological sort. Next, using the QR factorization as a basis, we construct a least-square penalty function as constraints for optimization in the graph autoencoder framework. Numerical experiments are performed to further validate our theoretical results and demonstrate the competitive performance of our method. Full article

This paper comprehensively reviews several techniques that address the static and dynamic voltage balancing of series-connected MOSFETs. The effectiveness of these techniques was validated through simulations and experiments. Dynamic voltage-balancing techniques include gate signal delay adjustment methods, passive snubbers, passive clamping circuits, and hybrid solutions. Based on the experimental results, the advantages and disadvantages of each technique are investigated. Combining the gate-balancing core method with an RC snubber, which has proven both technically and commercially attractive, provides a robust solution. If the components are sorted and binned, voltage-balancing techniques may not be necessary, further enhancing the commercial viability of series-connected MOSFETs. An investigation of gate driver topologies yields one crucial conclusion: magnetically isolated gate drivers offer a simple and cost-effective solution for high-frequency (HF) applications (2.5–50 kHz) above 8 kV with an increased number of series devices. Below 8 kV, it is advantageous to move the isolation barrier from the gate drive IC to an optocoupler and isolated supply, allowing for a simple design with commercially available components. Full article

For electrical machines with complex structures, the design space of parameters can be large with high dimensions during optimization. Considering the calculation cost and time consumption, it is hard to optimize all the design parameters at the same time. Therefore, in that situation, sensitivity analysis of these design parameters is usually used to sort out crucial parameters. In this paper, the sensitivity analysis-based Taguchi method is applied to optimize the axial-flux permanent magnet (AFPM) machine with yokeless and segmented armature (YASA) topology for an in-wheel traction system. According to the key parameters and their sensitivity analysis, the optimal machine scheme to meet the performance requirements can be formed. In this case study, the machine performance is improved significantly after optimization. Lastly, the experimental results verify the accuracy of the model used in this study. Full article

The recognition, decoding and tracking of vortex patterns is of increasing importance in many fields, ranging from the astronomical observations of distant galaxies to turbulence phenomena in liquids or gases. Currently, coherent light beams with orbital angular momentum (OAM) are of particular interest for optical communication, metrology, micro-machining or particle manipulation. One common task is to identify characteristic spiral patterns in pixelated intensity maps at real-world signal-to-noise ratios. A recently introduced combination of polar mapping and Fast Fourier Transform (FFT) was extended to novel sampling configurations and applied to the quantitative analysis of the spiral interference patterns of OAM beams. It is demonstrated that specific information on topological parameters in non-uniform arrays of OAM beams can be obtained from significantly distorted and noisy intensity maps by extracting one- or two-dimensional angular frequency spectra from single or concatenated circular cuts in either spatially fixed or scanning mode. The method also enables the evaluation of the quality of beam shaping and optical transmission. Results of proof-of-principle experiments are presented, resolution limits are discussed, and the potential for applications is addressed. Full article

Acoustic imaging technology has the advantages of non-contact and intuitive positioning. It is suitable for the rapid positioning of defects such as the mechanical loosening, discharge, and DC bias of power equipment. However, the existing research lacks the optimization design of microphone array topology. The acoustic frequency domain characteristics of typical power equipment are elaborately sorted out. After that, the cut-off frequencies of acoustic imaging instruments are determined, to meet the needs of the full bandwidth test requirements. Through a simulation calculation, the circular array is demonstrated to be the optimal shape. And the design parameters affect the imaging performance of the array to varying degrees, indicating that it is difficult to obtain the optimal array topology by an exhaustive method. Aimed at the complex working conditions of power equipment, a topology optimization design method of an acoustic imaging array for power equipment is proposed, and the global optimal solution of microphone array topology is obtained. Compared with the original array, the imaging performance of the improved LF and HF array is promoted by 54% and 49%, respectively. Combined with the simulation analysis and laboratory test, it is verified that the improved array can not only accurately locate the single sound source but also accurately identify the main sound source from the interference of the contiguous sound source. Full article

Aiming at the shortcomings of the existing machine vision pose measurement technology, a pose measurement method based on monocular vision and a cooperative target is proposed. A planar target designed with circles and rings as the main body is dedicated to object pose measurement, and a feature point coordinate extraction and sorting algorithm is designed for this target to effectively extract image features on the target. The RANSAC algorithm and topology-based fitting for the intersection method are used to optimise data processing, further improving the accuracy of feature point coordinate extraction and ultimately achieving high-precision measurement of object poses. The experimental results show that the measurement accuracy of the roll angle perpendicular to the optical axis can reach 0.02°, and the repeatability can reach 0.0004° after removing the systematic error; the measurement accuracy of the pitch angle can reach 0.03°, and the repeatability can go to 0.002° after removing the systematic error. The measurement range of the pitch angle is [−30°, +30°]; the measurement range of the roll angle is [−179°, +179°]. The experimental results show that the system has high measurement accuracy and meets the requirements of high-precision measurement. Full article