Research on the monitoring system for induced voltage and ground current of 27.5 kV cable sheath in railways

Purpose–The purpose of this study is to address the deficiency in safety monitoring technology for 27.5 kV high-voltage cables within the railway traction power supply by analyzing the grounding methods employed in high-speed railways and developing an effective monitoring solution.Design/methodology/approach–Through establishing a mathematical model of induced potential in the cable sheath and analyzing its influencing factors,the principle of grounding current monitoring is proposed.Furthermore,the accuracy of data collection and alarm function of the monitoring equipment were verified through laboratory simulation experiments.Finally,through practical application in the traction substation of the railway bureau on site,a large amount of data were collected to verify the stability and reliability of the monitoring system in actual environments.Findings–The experimental results show that the designed monitoring system can effectively monitor the grounding current of high-voltage cables and respond promptly to changes in cable insulation status.The system performs excellently in terms of data collection accuracy,real-time performance and reliability of alarm functions.In addition,the on-site trial results further confirm the accuracy and reliability of the monitoring system in practical applications,providing strong technical support for the safe operation of highspeed railway traction power supply systems.Originality/value–This study innovatively develops a 27.5kV high-voltage cable grounding current monitoring system,which provides a new technical means for evaluating the insulation status of cables by accurately measuring the grounding current.The design,experimental verification and application of this system in high-speed railway traction power supply systems have demonstrated significant academic value and practical significance,contributing innovative solutions to the field of railway power supply safety monitoring.

Identification and Prediction of Interdisciplinary Research Topics: A Study Based on the Concept Lattice Theory

Purpose: Formal concept analysis(FCA) and concept lattice theory(CLT) are introduced for constructing a network of IDR topics and for evaluating their effectiveness for knowledge structure exploration.Design/methodology/approach: We introduced the theory and applications of FCA and CLT, and then proposed a method for interdisciplinary knowledge discovery based on CLT. As an example of empirical analysis, interdisciplinary research(IDR) topics in Information & Library Science(LIS) and Medical Informatics, and in LIS and Geography-Physical, were utilized as empirical fields. Subsequently, we carried out a comparative analysis with two other IDR topic recognition methods.Findings: The CLT approach is suitable for IDR topic identification and predictions.Research limitations: IDR topic recognition based on the CLT is not sensitive to the interdisciplinarity of topic terms, since the data can only reflect whether there is a relationship between the discipline and the topic terms. Moreover, the CLT cannot clearly represent a large amounts of concepts.Practical implications: A deeper understanding of the IDR topics was obtained as the structural and hierarchical relationships between them were identified, which can help to get more precise identification and prediction to IDR topics.Originality/value: IDR topics identification based on CLT have performed well and this theory has several advantages for identifying and predicting IDR topics. First, in a concept lattice, there is a partial order relation between interconnected nodes, and consequently, a complete concept lattice can present hierarchical properties. Second, clustering analysis of IDR topics based on concept lattices can yield clusters that highlight the essential knowledge features and help display the semantic relationship between different IDR topics. Furthermore, the Hasse diagram automatically displays all the IDR topics associated with the different disciplines, thus forming clusters of specific concepts and visually retaining and presenting the associations of IDR topics through multiple inheritance relationships between the concepts.

Research on Application of Supply Chain Finance Based on Block Chain

Supply chain finance has played a positive role in solving the financing difficulties of small and medium-sized enterprises.However,in the actual implementation process,there are still problems such as information asymmetry,doubts about the authenticity of trade background,and high operational risks,which seriously restrict the development of supply chain finance.However,block chain technology has the characteristics of de-centralization,data transparency,common maintenance and non-tampering.Applying this technology to supply chain finance can effectively solve the existing problems.Based on the research on the development status of traditional supply chain finance,this paper puts forward a new development mode of supply chain finance based on block chain technology,and through the analysis of typical cases,finally gives some policy suggestions for the development of block chain supply chain finance.

Quantum Key Distribution Network： Optimal Secret- Key- Aware Routing Method for Trust Relaying

Since the QKD network can overcome the distance limitation and expand the point-to-point QKD system to a multi-user key distribution system, some testing QKD networks have been built. However, all of this previous research seldom focused on the routing mechanism of QKD network in detail. Therefore, this paper focuses on the routing issue in trust relaying QKD network, builds a model of the trust relaying QKD network and proposes a secret-key-aware routing method. In our method, a dynamic model for the residual local key is proposed to forecast the residual local key quantity of each QKD link more accurately, and the cost of QKD link and relaying path are defined by multiple affecting factors, e.g. the generation, consumption rate and the local key depletion index. The proposed method is implemented and evaluated in a simulation environment. The simulation results show that our routing method can increase the success rate of key exchange, make all the QKD links participate key exchange with almost equal opportunity to achieve load balance, and trade off the local key generation and consumption of each QKD link. Therefore, our proposed method can contribute to effectively improve the holistic performance of the trust relaying QKD network.

Finding map regions with high density of query keywords

We consider the problem of finding map regions that best match query keywords. This region search problem can be applied in many practical scenarios such as shopping recommendation, searching for tourist attractions, and collision region detection for wireless sensor networks. While conventional map search retrieves isolate locations in a map, users frequently attempt to find regions of interest instead, e.g., detecting regions having too many wireless sensors to avoid collision, or finding shopping areas featuring various merchandise or tourist attractions of different styles. Finding regions of interest in a map is a non-trivial problem and retrieving regions of arbitrary shapes poses particular challenges. In this paper, we present a novel region search algorithm, dense region search(DRS), and its extensions, to find regions of interest by estimating the density of locations containing the query keywords in the region. Experiments on both synthetic and real-world datasets demonstrate the effectiveness of our algorithm.