Generic Analysis Framework for Modular Multilevel Converter HVDC with Multi-Infeed Line-Commutated Converter HVDC System

This paper proposes a generic analysis framework for a grid supporting modular multilevel converter (MMC)-high voltage DC (HVDC) in a multi-infeed of line commutated converter (LCC) and MMC (MILM) system. MMC-HVDC can support the grid by compensating for the exact reactive power consumptions within the MMC-HVDC system and the varying power system conditions in the MILM system. Maximum active/reactive power capability (MPQC) curve and PQ loading curve comparison process is introduced to properly design a grid supporting MMC-HVDC. While the MPQC curve presents the maximum PQ range of the MMC-HVDC system based on the submodule capacitance value and the modulation index, the PQ loading curve presents the reactive power requirement from the power system that MMC-HVDC needs to compensate. Finally, the comparison of these two curves yields the proper value of submodule capacitance and the modulation index for sufficiently supporting the MILM system. The proposed framework is validated with detailed PSCAD/EMTDC simulation; it demonstrated that it could be applied to various power system conditions.

Research on Differentiation of Accidents at Work Considering Demographic Features of Workers in Steel Sector in Poland

This article focuses on the number of accidents at work in enterprises in the steel industry. Accidents have a significant effect on the operations of enterprises due to the social and economic costs they generate. This article presents the dependence between the number of accidents at work, demographic characteristics (sex, age) and work experience of injured persons, which allows for the identification of risk groups based on to the tested feature. The scope of the analysis covers the structure of accidents at work in the steel industry in the years 2009-2015. The aim of this article is to present the dependence between the number of accidents at work and the demographic characteristics and work experience of workers employed in the industry under examination. The conducted analysis led to the conclusion that there is a relation between the number of accidents at work and the demographic characteristics of persons sustaining an accident at work. In the period between 2009-2015, male workers aged 30-39 were involved in accidents at work the most frequently. The research methodology applied in this article consists of: absolute and generic analysis of work accidents, ratio analysis and statistical analysis of the relation between the number of accidents at work and the demographic characteristics of workers injured in accidents. The applied methodology of analysis of accidents at work may be used for a benchmark analysis of various industry sectors in any country or the same sectors in various countries.

Abuse of Right: Historical and Theoretical Research

Abuse of right is one of the most complex phenomena in legal science, the study of which requires the use of a wide range of methods of cognition, both general scientific and private law. The author of the article makes a generic analysis of the concept “abuse of right”, disclosing the history of its appearance and development. However, special attention is paid to the discussion of scientists about the essence of abuse of right, in which, as in a “multi-layered cake”, more and more narrow subjects of the discussion are layered, but at the same time, they are all permeated with a common goal – to determine the place and role of the phenomenon in the modern legal order. Historically, the first debate arose on the validity of the very concept of abuse of right, caused by a combination of two words that were opposite in meaning: “right” and “abuse”. This discussion has been going on for more than a century and takes place both in Russian civil law and in foreign legal doctrine. There is also no consensus among supporters of the concept of abuse of right: some attribute abuse of right to a variety of lawful behavior, others call it an offense. This problem is currently urgent and complex. Finally, there are disagreements about the branch of abuse of law: is this concept inter-branch in nature or is it exclusively inherent in the civil law branch? As a result of comparing all points of view, the author in each of the above discussions reasonably takes this or that position. As a result, a complete understanding of the phenomenon under study is formed.

Radio Network Planning towards 5G mmWave Standalone Small-Cell Architectures

The 5G radio networks have introduced major changes in terms of service requirements and bandwidth allocation compared to cellular networks to date and hence, they have made the fundamental radio planning problem even more complex. In this work, the focus is on providing a generic analysis for this problem with the help of a proper multi-objective optimization algorithm that considers the main constraints of coverage, capacity and cost for high-capacity scenarios that range from dense to ultra-dense mmWave 5G standalone small-cell network deployments. The results produced based on the above analysis demonstrate that the denser the small-cell deployment, the higher the area throughput, and that a sectored microcell configuration can double the throughput for ultra-dense networks compared to dense networks. Furthermore, dense 5G networks can actually have cell radii below 400 m and down to 120 m for the ultra-dense sectored network that also reached spectral efficiency 9.5 bps/Hz/Km2 with no MIMO or beamforming.

Higher-Ranked Annotation Polymorphic Dependency Analysis

The precision of a static analysis can be improved by increasing the context-sensitivity of the analysis. In a type-based formulation of static analysis for functional languages this can be achieved by, e.g., introducing let-polyvariance or subtyping. In this paper we go one step further by defining a higher-ranked polyvariant type system so that even properties of lambda-bound identifiers can be generalized over. We do this for dependency analysis, a generic analysis that can be instantiated to a range of different analyses that in this way all can profit.We prove that our analysis is sound with respect to a call-by-name semantics and that it satisfies a so-called noninterference property. We provide a type reconstruction algorithm that we have proven to be terminating, and sound and complete with respect to its declarative specification. Our principled description can serve as a blueprint for making other analyses higher-ranked.

Data-Driven GENERIC Modeling of Poroviscoelastic Materials

Biphasic soft materials are challenging to model by nature. Ongoing efforts are targeting their effective modeling and simulation. This work uses experimental atomic force nanoindentation of thick hydrogels to identify the indentation forces are a function of the indentation depth. Later on, the atomic force microscopy results are used in a GENERIC general equation for non-equilibrium reversible–irreversible coupling (GENERIC) formalism to identify the best model conserving basic thermodynamic laws. The data-driven GENERIC analysis identifies the material behavior with high fidelity for both data fitting and prediction.

A comprehensive framework to capture the arcana of neuroimaging analysis

Mastering the “arcana of neuroimaging analysis”, the obscure knowledge required to apply an appropriate combination of software tools and parameters to analyse a given neuroimaging dataset, is a time consuming process. Therefore, it is not typically feasible to invest the additional effort required generalise workflow implementations to accommodate for the various acquisition parameters, data storage conventions and computing environments in use at different research sites, limiting the reusability of published workflows.We present a novel software framework, Abstraction of Repository-Centric ANAlysis (Arcana), which enables the development of complex, “end-to-end” workflows that are adaptable to new analyses and portable to a wide range of computing infrastructures. Analysis templates for specific image types (e.g. MRI contrast) are implemented as Python classes, which define a range of potential derivatives and analysis methods. Arcana retrieves data from imaging repositories, which can be BIDS datasets, XNAT instances or plain directories, and stores selected derivatives and associated provenance back into a repository for reuse by subsequent analyses. Workflows are constructed using Nipype and can be executed on local workstations or in high performance computing environments. Generic analysis methods can be consolidated within common base classes to facilitate code-reuse and collaborative development, which can be specialised for study-specific requirements via class inheritance. Arcana provides a framework in which to develop unified neuroimaging workflows that can be reused across a wide range of research studies and sites.