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Electromagnetic interference (EMI) on communication systems of unban rail transit can hardly be clarified because of complicated factors around railways. This paper aims to target this issue and extend experimental and theoretical analysis.

This paper take the Nanjing Dashengguan Bridge as an example, because it carries the most tracks in the world and bears three kinds of trains running through, providing a perfect complex environment. First, it investigates the three communication systems, terrestrial trunked radio, communications-based train control (CBTC) and passenger information system (PIS) that Nanjing Metro uses, and select appropriate devices accordingly. Second, it establishes a system level platform and conduct three tests to analyze their respective operating principles and performance difference under common electromagnetic environments. Third, it adopts theoretical formula to verify test results.

The experiment results and theoretical analysis mutually corroborate each other and present practical recommendations: an 8 m or more distance between two tracks will ensure no obvious EMI created by a passing train on communication systems; two certain communication systems should not share the same frequency band; interference level is more related to field strength than weathers and building materials; and CBTC DSSS waveguide mode as well as PIS LTE mode are preferred.

This research also provides a practical method of investigating EMI for other complex situations.

Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time. However, storing and processing large and varied datasets (known as big data) is challenging to do in real time. In machine learning, streaming feature selection has always been considered a superior technique for selecting the relevant subset features from highly dimensional data and thus reducing learning complexity. In the relevant literature, streaming feature selection refers to the features that arrive consecutively over time; despite a lack of exact figure on the number of features, numbers of instances are well-established. Many scholars in the field have proposed streaming-feature-selection algorithms in attempts to find the proper solution to this problem. This paper presents an exhaustive and methodological introduction of these techniques. This study provides a review of the traditional feature-selection algorithms and then scrutinizes the current algorithms that use streaming feature selection to determine their strengths and weaknesses. The survey also sheds light on the ongoing challenges in big-data research.

A recent study of the Minnesota Agriculture and Rural Leadership (MARL) program set out to determine the relationship between andragogical program design and increased levels of emotional intelligence (EI). Members of two cohorts in the MARL leadership development program received different levels of focused effort, peer coaching, individual action plans, disorienting dilemmas, self-reflection, and training in the area of emotional intelligence. We examined four years of data, including participants’ results on the Bar-On Emotional Quotient Inventory (EQ-i) before and after undergoing leadership development training, as well as their individual reflections on the EI components of their training. The intention is that this research will encourage practices that seek to increase emotional intelligence in leaders.

The purpose of this study is to quantify port efficiency assessment indicators to analyze the impact of COVID-19 on Chinese One Belt One Road (OBOR) ports.

This study utilized a grey prediction model GM(1,1) to forecast five relevant indicators for each of the 17 OBOR ports both with and without COVID-19 background conditions. Additionally, the data envelopment analysis (DEA) efficiency assessment approach was used to analyze the impact of COVID-19 on port efficiency.

The results indicate that cargo and container throughput growth rates during the COVID-19 pandemic are reduced by 1.7 and 2.1%, respectively. There was also a noticeable reduction in technological efficiency (TE) as well as pure technological efficiency (PTE), while scale efficiency (SE) remained largely unaffected. Furthermore, the dynamic efficiency MI was mainly negatively impacted by changes in overall efficiency change (EFFCH), where pure efficiency change (PECH) less than one contributed significantly towards overall regression of port efficiencies during this period.

This paper is unique in its use of a combination of the grey prediction model and DEA efficiency assessment to quantify changes in important indicators during pandemic periods. This approach not only provides a quantitative understanding of the impact on port-level efficiency through numerical quantification but also offers readers an intuitive understanding.

Library intelligence institutions, which are a kind of traditional knowledge management organization, are at the frontline of the big data revolution, in which the use of unstructured data has become a modern knowledge management resource. The paper aims to discuss this issue.

This research combined theme logic structure (TLS), artificial neural network (ANN), and ensemble empirical mode decomposition (EEMD) to transform unstructured data into a signal-wave to examine the research characteristics.

Research characteristics have a vital effect on knowledge management activities and management behavior through concentration and relaxation, and ultimately form a quasi-periodic evolution. Knowledge management should actively control the evolution of the research characteristics because the natural development of six to nine years was found to be difficult to plot.

Periodic evaluation using TLS-ANN-EEMD gives insights into journal evolution and allows journal managers and contributors to follow the intrinsic mode functions and predict the journal research characteristics tendencies.

The major marine functional zoning plan (MMFZP) and marine functional zoning (MFZ) are two important kinds of marine spatial planning (MSP) in China. Their developing and implementation are integral to rational marine utilization and sustainable marine development. The purpose of this research is to study how these two kinds of MSP work in coordination in China.

This paper reviewed the present status of MSP research in China and abroad and presented a comparative study of the MMFZP and MFZ from different aspects, analyzing the relationship between the two.

The study found obvious differences between the MMFZP and MFZ, with respect to their concept and connotation, purpose and goal, as well as zoning methods and zoning functions. MFZ provides reference with respect to data, zoning methods and partial zoning results for the MMFZP, which in turn takes measures for addressing issues faced by MFZ and promotes the national MSP work.

In the process of developing and implementing the two zoning plans, this paper emphasizes the necessity to strengthen data sharing, reference of zoning techniques and coordination in zoning work, which will help to improve China's marine spatial management.

In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.

By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions.

The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole.

Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system.

This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.