Physical Layer Components Security Risks in Optical Fiber Infrastructures

Optical fiber communications are essential for all types of long- and short-distance transmissions. The aim of this paper is to analyze the previously presented security risks and, based on measurements, provide the risk level evaluation. The major risk is the possibility of inserting a splitter into the optical distribution network and capturing a portion of the entire spectrum, i.e., all channels in the optical fiber. Another significant security risk is crosstalk on multiplexers in networks with wavelength division multiplexing. The paper covers the macrobend attenuation evaluation of fiber and back-reflection measurements. Based on the measurements, risks were evaluated for both point-to-point and point-to-multipoint networks and, lastly, the paper covers crosstalk measurements of an optomechanical switch. Finally, all individual risks are evaluated according to the severity, and a proposal for risk minimization is provided.

Academic Governance Arrangements

Governing the quality of academic activities at the institution level is a challenging task. Literature shows that the model of academic governance considers quality but still lacks proper standardization of academic functions and risk minimization in higher institutes. In the current chapter, the authors present a conceptual framework of academic governance, different arrangements settings, and exploring nexus of governance in education sector: how it operates to support the quality of academic activities. Using literature content and qualitative analysis, firstly the chapter explores a few factors of academic governance such as expectations of regulators, standards, and quality, and secondly, it presents influences due to pandemic on academic governance. At the last, this chapter draws inferences to act as a starting point for the study on academic governance, refers knowledge, infuses more research practices, and answers a few questions that might surface from the implementation of academic governance in assuring quality.

Anti-Corruption Tools of Financial Risk Management in Public Administration

Every country is concerned with the problem of corruption. Selfish misuse of public office undermines the people's confidence in government and institutions, makes public policies less effective and fair, and misuses taxpayer funds that could be used to build schools, roads and hospitals. Financial risk management in public administration is based on risk assessments and finding tools to help influence them. To develop practical tools for financial risk management, the authors studied the economic practises that determine the features of financial risk assessment. They identified the elements that can motivate financial risks, including three stages of identification and analysis of risks, analyzed the main stages and indicators of assessing an organization's financial condition based on the balance sheet, produced a risk assessment algorithm and risk minimization methods in managing financial activities, and conducted a comparative analysis of financial risk assessment methods. Based on the Professional Integrity Framework proposed by the Organization for Economic Cooperation and Development, the authors developed basic measures to mitigate the potential negative consequences and proposed seven financial risk management tools for public administration. The proposed anti-corruption tools will help significantly reduce financial risks in public administration and corruption in general.

Formation of a new industrial landscape in the context of innovative risks

The problem of risk management, especially in the new conditions associated with global challenges and threats and the transformation of the economy, is of an urgent nature. The aim of the study is to expand the possibilities of minimizing risks for enterprises in the conditions of the formation of a new industrial landscape. The object of the study is the risks of industrial enterprises. The subject of the study is the features of minimizing the risks of industrial enterprises in the conditions of economic transformation. The methodology of the study consisted of the following general scientific and private scientific methods and approaches: the method of analysis and synthesis for studying the features of management and risk minimization in organizations of different levels, methods of classification and generalization for expanding the typologies of risks of industrial enterprises, structural and functional, systemic and situational approaches for risk analysis and the development of proposals for their minimization, as well as mathematical and statistical methods of analysis of open empirical data. The results of the study. The paper presents theoretical and applied aspects of using platform solutions and artificial intelligence elements to minimize the risks of industrial enterprises in the development of a new economic landscape. Conclusions. The author of the article supplemented the typologies of risks of industrial enterprises and proposed solutions to minimize them. Application. The results of the study can be used for further studies of this problem.

Encoding-dependent generalization bounds for parametrized quantum circuits

A large body of recent work has begun to explore the potential of parametrized quantum circuits (PQCs) as machine learning models, within the framework of hybrid quantum-classical optimization. In particular, theoretical guarantees on the out-of-sample performance of such models, in terms of generalization bounds, have emerged. However, none of these generalization bounds depend explicitly on how the classical input data is encoded into the PQC. We derive generalization bounds for PQC-based models that depend explicitly on the strategy used for data-encoding. These imply bounds on the performance of trained PQC-based models on unseen data. Moreover, our results facilitate the selection of optimal data-encoding strategies via structural risk minimization, a mathematically rigorous framework for model selection. We obtain our generalization bounds by bounding the complexity of PQC-based models as measured by the Rademacher complexity and the metric entropy, two complexity measures from statistical learning theory. To achieve this, we rely on a representation of PQC-based models via trigonometric functions. Our generalization bounds emphasize the importance of well-considered data-encoding strategies for PQC-based models.

ROLE OF 3PL ON FINANCIAL AND STRATEGIC PERFORMANCE OF MEXICANS MAQUILADORAS

This paper presents the effects between Logistics Network and Value-Added activities 3PL environments and its effect on the Financial and Strategic Performance of Mexican Maquiladoras companies. The significant increase in outsourcing transportation services in freight transport at the border Mexico-United States has inspired this research. The paper presents four hypotheses, tested with data from 158 responses to a questionnaire applied to engineers from the manufacturing industry in Ciudad Juarez (Mexico). The hypotheses were tested statistically using the partial least squares technique. Results indicate that a good design of a Logistics Network has a positive effect on Strategic Performance through transport logistics planning to reduce distribution times and costs. Additionally, the Value-Added services offered by a 3PL positively affect Strategic Performance through labeling-marking, packaging, and reassembling of products. Also, the Strategic Performance has a positive effect on Financial Performance through flexibility and risk minimization of 3PL provider, and this is the enormous effect that arguing theoretically and demonstrating empirically that the outsourcing of 3PL incremented the economic benefits to the quantity of 76.20% between Financial Performance and provides a reference to make decisions according to strategies to incorporate 3PL in such maquiladora industries. Keywords: 3PL, strategic performance, financial performance, structural equations