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［Objective］With the rapid development of urban rail transit, many cities have formed rail transit line networks with multiple operating entities, and have integrated around public transportation payment methods such as "one-card" and virtual QR codes to form a larger urban transportation network. As the core of connecting all kinds of transportation networks, the ticket clearing for urban rail transit line network is especially important. It is necessary to provide a more reasonable clearing method for the construction and design of ticket clearing systems for relevant cities in China. ［Method］Through an introduction to urban rail transit ticket clearing schemes in both domestic and foreign cities, the ticket clearing methods for multi-line travel in major Chinese cities are analyzed and compared, and the applicable ticket clearing method is selected through analyzing the advantages and disadvantages of the clearing models and algorithms. ［Result & Conclusion］The one-ticket transfer model commonly used in China relies only on OD (origin and destination) for checking records, making it difficult to fairly and reasonably distribute the fare to multiple operating entities that may be involved. A more scientific and reasonable clearing scheme needs to further strengthen big data research on the AFC (automatic fare collection) system, and more importantly, relying on existing technologies and computing models is required to strengthen the real-time analysis and overtime prediction accuracy of passengers′ path selection behavior, so as to enable the clearing mechanism accurately make adaptive dynamic adjustments according to actual operating conditions.

Objective With the expansion of urban rail transit line network, the system risks become more complicated and uncontrollable. In order to improve the emergency rescue capability of urban rail transit system, site selection of emergency rescue stations within the line network needs to be stu-died. Method The subway coverage area is divided into speed limit sections according to the urban road loop to obtain the speed matrix of any path. Combined with the distance matrix, the time matrix is obtained after transformation. On this basis, the shortest time-based path between any stations is calculated. Considering the constraints in time, rescue relationship and cost 3 aspects, the P- center model with the goal of minimizing the maximum rescue time of the system is established. Taking the site selection of emergency rescue stations of Wuhan rail transit line network as a case and applying this model, the adaptive genetic algorithm is used in MATLAB software for programming solution, and the optimal scheme for the site selection of emergency rescue stations in this line network is obtained. Result & Conclusion Compared with similar researches, this site selection scheme featuring less investment but greater benefits fully proves that the P-center model proposed in the paper is advanced.

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We analyze the problem of strong coordination over a multi-hop line network in which the node initiating the coordination is a terminal network node. We assume that each node has access to a certain amount of randomness that is local to the node, and that the nodes also have shared common randomness, which are used together with explicit hop-by-hop communication to achieve information-theoretic strong coordination. We derive the trade-offs among the required rates of communication on the network links, the rates of local randomness available at network nodes, and the rate of common randomness to realize strong coordination. We present an achievable coding scheme built using multiple layers of channel resolvability codes, and establish several settings in which this scheme offers the best possible trade-offs among network resources. [ABSTRACT FROM AUTHOR]

A multi-hop line network is considered, where each node can receive signals transmitted by its two neighbors. As such, the model embodies both the interference and broadcast aspects of wireless networks. The leftmost node wishes to send messages to the rightmost node, while keeping these messages confidential from all the intermediate relay nodes. In this setting where any or all of the relay nodes can be eavesdroppers, it is shown that end-to-end secure and reliable communication is possible. Notably, it is shown that an end-to-end secrecy rate that is independent of the number of hops, i.e., intermediate eavesdroppers, is achievable by means of a carefully designed transmission schedule, compute-and-forward relaying and coding strategy utilizing nested lattice codes. The achievable rate obtained indicates that imposing secrecy constraints penalizes the capacity by at most 1 bit per channel use. Therefore, it is concluded that information theoretic secrecy can be guaranteed for this model irrespective of eavesdropping relays and a fixed modest cost for the end-to-end rate. [ABSTRACT FROM PUBLISHER]

Line and star networks with both node and edge constraints are studied in the network coding framework. For line networks, the capacity region of the general multiple multicast problem is established. The coding theorem is based on a binary linear coding scheme, while the converse requires new upper bounds that improve on standard cut-based bounds. For star networks, the multiple unicast problem is examined. Capacity upper bounds are derived and a simple linear coding scheme is proposed which is based on the combinatorial optimization problem of cycle packing in directed graphs. The optimality of this scheme is established for a broad class of demands. The connection of node-constrained network coding in star networks, and index coding with side information is discussed and used to partially characterize the optimal linear code for general rates. [ABSTRACT FROM AUTHOR]

This work investigates the effect of finite buffer sizes on the throughput capacity and packet delay of line networks with packet erasure links that have perfect feedback. These performance measures are shown to be linked to the stationary distribution of an underlying irreducible Markov chain that models the system exactly. Using simple strategies, bounds on the throughput capacity are derived. The work then presents two iterative schemes to approximate the steady-state distribution of node occupancies by decoupling the chain to smaller queueing blocks. These approximate solutions are used to understand the effect of buffer sizes on throughput capacity and the distribution of packet delay. Using the exact modeling for line networks, it is shown that the throughput capacity is unaltered in the absence of hop-by-hop feedback provided packet-level network coding is allowed. Finally, using simulations, it is confirmed that the proposed framework yields accurate estimates of the throughput capacity and delay distribution and captures the vital trends and tradeoffs in these networks. [ABSTRACT FROM AUTHOR]

Vectorisation is the foundation in recognising engineering components from paper form drawings. Due to the complexity of problems and the difficulty of techniques, the vectorisation method relying merely on the image itself cannot get satisfactory results. It is now widely agreed that the knowledge must be applied more or less to aid the vectorisation. The capability of the vectorisation method itself should also be thus improved. This paper analyses the problems of existing vectorisation methods, introduces the complete concept of global vectorisation, and proposes a whole new line network oriented global vectorisation method. This method uses global information to vectorise a line in one step, and carries out the global vectorisation of line networks. Therefore, the problem of separating one line is solved, and a complex analysis of crossings is avoided. The performance of vectorisation is improved clearly. Furthermore, it can vectorise lines in any orientations well, and can vectorise a dashed line in one step. Aided by the related knowledge, local details of vectorisation are refined. A performance evaluation compared with other vectorisation methods is also included. [ABSTRACT FROM AUTHOR]

The availability of large spatial data geocoded at accurate locations has fueled a growing interest in spatial modeling and analysis of point processes. The proposed research is motivated by the intensity estimation problem for spatial point patterns on complex domains in R 2 (e.g., domains with irregular boundaries, sharp concavities, and/or interior holes due to geographic constraints) and linear networks, where many existing spatial point process models suffer from the problems of "leakage" and computation. We propose an efficient intensity estimation algorithm to estimate the spatially varying intensity function and to study the varying relationship between intensity and explanatory variables on complex domains. The method is built upon a graph regularization technique and hence can be flexibly applied to point patterns on complex domains such as regions with irregular boundaries and holes, or linear networks. An efficient proximal gradient optimization algorithm is proposed to solve the penalized composite likelihood problem for parameter estimations. Finally, we apply the method to study and visualize the intensity patterns of the accidents on the Western Australia road network, and the spatial variations in the effects of income, night light condition, and population density on the Toronto homicides occurrences. [ABSTRACT FROM AUTHOR]