Search results

In the continuous development of high-speed railways, ensuring the safety of the operation control system is crucial. Electromagnetic interference (EMI) faults in signaling equipment may cause transportation interruptions, delays and even threaten the safety of train operations. Exploring the impact of disturbances on signaling equipment and establishing evaluation methods for the correlation between EMI and safety is urgently needed.

This paper elaborates on the necessity and significance of studying the impact of EMI as an unavoidable and widespread risk factor in the external environment of high-speed railway operations and continuous development. The current status of research methods and achievements from the perspectives of standard systems, reliability analysis and safety assessment are examined layer by layer. Additionally, it provides prospects for innovative ideas for exploring the quantitative correlation between EMI and signaling safety.

Despite certain innovative achievements in both domestic and international standard systems and related research for ensuring and evaluating railway signaling safety, there’s a lack of quantitative and strategic research on the degradation of safety performance in signaling equipment due to EMI. A quantitative correlation between EMI and safety has yet to be established. On this basis, this paper proposes considerations for research methods pertaining to the correlation between EMI and safety.

This paper overviews a series of methods and outcomes derived from domestic and international studies regarding railway signaling safety, encompassing standard systems, reliability analysis and safety assessment. Recognizing the necessity for quantitatively describing and predicting the impact of EMI on high-speed railway signaling safety, an innovative approach using risk assessment techniques as a bridge to establish the correlation between EMI and signaling safety is proposed.

The growth in cryptomarkets has reinvigorated the research on illicit drug distribution due to the availability of large-scale data. This data has enabled researchers to ask new and detailed questions about how participants in these markets trust each other enough for the market not to collapse. This question deserves more attention because it has become a taken-for-granted notion that repeated transactions and social categories create trust. Whether online or on the street, economic exchanges under illegality are more uncertain than transactions in the legal economy. This puts higher demands on trust, as there is less information and the stakes are higher. In this chapter, the author presents definitions, typologies, and disciplinary contributions to the study of trust and examine how it has been operationalised in a sample of 13 peer-reviewed articles. These articles focus on three dimensions of trust: process-based trust that derives from repeated transactions with known partners; character-based trust measured by the networked reputation scores; and institutional-based trust in the platform and its administrators. In practice, the trust bases are intertwined. Drawing on the broader social science literature on trust, a mesolevel operationalisation that centres on networked reputation scores as embedded in processes and institutions can draw the research together in a multidisciplinary framework.

Ground Penetrating Radar is a multidisciplinary Nondestructive Evaluation technique that requires knowledge of electromagnetic wave propagation, material properties and antenna theory. Under some circumstances this tool may require auxiliary algorithms to improve the interpretation of the collected data. Detection, location and definition of target’s geometrical and physical properties with a low false alarm rate are the objectives of these signal post-processing methods. Basic approaches are focused in the first two objectives while more robust and complex techniques deal with all objectives at once. This work reviews the use of Artificial Neural Networks and Machine Learning for data interpretation of Ground Penetrating Radar surveys. We show that these computational techniques have progressed GPR forward from locating and testing to imaging and diagnosis approaches.