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A Practical Guide to SysML: The Systems Modeling Language is a comprehensive guide for understanding and applying SysML to model systems. The Object Management Group's OMG SysML is a general-purpose graphical modeling language for representing systems that may include combinations of hardware, software, data, people, facilities, and natural objects. SysML supports the practice of model-based systems engineering (MBSE) used to develop system solutions in response to complex and often technologically challenging problems. The book is organized into four parts. Part I provides an overview of sys

Systems engineering --- Computer simulation --- SysML (Computer science) --- Systems engineering. --- OMG SysML (Computer science) --- Systems Modeling Language (Computer science) --- Computer software --- Modeling languages (Computer science) --- UML (Computer science) --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- Development --- Design and construction

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Model-driven software architecture. --- Systems engineering. --- SysML (Computer science) --- OMG SysML (Computer science) --- Systems Modeling Language (Computer science) --- Computer software --- Modeling languages (Computer science) --- UML (Computer science) --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- MDA (Model-driven software architecture) --- Software architecture --- Development --- Design and construction

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UML, the Universal Modeling Language, was the first programming language designed to fulfill the requirement for ""universality."" However, it is a software-specific language, and does not support the needs of engineers designing from the broader systems-based perspective. Therefore, SysML was created. It has been steadily gaining popularity, and many companies, especially in the heavily-regulated Defense, Automotive, Aerospace, Medical Device and Telecomms industries, are already using SysML, or are planning to switch over to it in the near future. However, little information is curr

Systems engineering. --- SysML (Computer science) --- UML (Computer science) --- Unified Modeling Language (Computer science) --- Computer software --- Modeling languages (Computer science) --- Object-oriented methods (Computer science) --- OMG SysML (Computer science) --- Systems Modeling Language (Computer science) --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- Development --- Design and construction --- Information Technology --- General and Others

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The most important environmental challenge today's society is facing is to reduce the effects of CO2 emissions and global warming. Such an ambitious challenge can only be achieved through a holistic approach, capable of tackling the problem from a multidisciplinary point of view. One of the core technologies called to play a critical role in this approach is the use of energy storage systems. These systems enable, among other things, the balancing of the stochastic behavior of Renewable Sources and Distributed Generation in modern Energy Systems; the efficient supply of industrial and consumer loads; the development of efficient and clean transport; and the development of Nearly-Zero Energy Buildings (nZEB) and intelligent cities. Hybrid Energy Storage Systems (HESS) consist of two (or more) storage devices with complementary key characteristics, that are able to behave jointly with better performance than any of the technologies considered individually. Recent developments in storage device technologies, interface systems, control and monitoring techniques, or visualization and information technologies have driven the implementation of HESS in many industrial, commercial and domestic applications. This Special Issue focuses on the analysis, design and implementation of hybrid energy storage systems across a broad spectrum, encompassing different storage technologies (including electrochemical, capacitive, mechanical or mechanical storage devices), engineering branches (power electronics and control strategies; energy engineering; energy engineering; chemistry; modelling, simulation and emulation techniques; data analysis and algorithms; social and economic analysis; intelligent and Internet-of-Things (IoT) systems; and so on.), applications (energy systems, renewable energy generation, industrial applications, transportation, Uninterruptible Power Supplies (UPS) and critical load supply, etc.) and evaluation and performance (size and weight benefits, efficiency and power loss, economic analysis, environmental costs, etc.).

high gain converters --- power systems modeling --- load flow analysis --- pumped storage --- shipboard power systems --- storage --- hybrid energy storage systems (HESSs) --- buck-boost converter --- state of charge --- active power control --- rail transportation power systems --- lithium-ion batteries --- microgrids --- energy storage --- microgrid --- power-line signaling --- battery energy storage system (BESS) --- power electronic converters --- single-phase --- load modeling --- ultracapacitors --- smart home (SH) --- fault ride-through capability --- renewable energy sources --- battery management system --- multiport --- photovoltaic --- fuel cell (FC) --- DC power systems --- hybrid --- energy storage system --- micro combined heat and power (micro-CHP) system --- power quality --- solar photovoltaic --- electric vehicle (EV) --- energy storage technologies --- hybrid storage systems --- real coded genetic algorithm (RCGA) --- storage operation and maintenance costs

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Modern biology is rapidly becoming a study of large sets of data. Understanding these data sets is a major challenge for most life sciences, including the medical, environmental, and bioprocess fields. Computational biology approaches are essential for leveraging this ongoing revolution in omics data. A primary goal of this Special Issue, entitled “Methods in Computational Biology”, is the communication of computational biology methods, which can extract biological design principles from complex data sets, described in enough detail to permit the reproduction of the results. This issue integrates interdisciplinary researchers such as biologists, computer scientists, engineers, and mathematicians to advance biological systems analysis. The Special Issue contains the following sections:•Reviews of Computational Methods•Computational Analysis of Biological Dynamics: From Molecular to Cellular to Tissue/Consortia Levels•The Interface of Biotic and Abiotic Processes•Processing of Large Data Sets for Enhanced Analysis•Parameter Optimization and Measurement

n/a --- inosine --- immune checkpoint inhibitor --- geometric singular perturbation theory --- simulation --- BioModels Database --- ADAR --- calcium current --- bifurcation analysis --- bacterial biofilms --- nonlinear dynamics --- explanatory model --- turning point bifurcation --- oscillator --- workflow --- bioreactor integrated modeling --- modeling methods --- elementary flux modes visualization --- multiscale systems biology --- evolutionary algorithm --- metabolic model --- differential evolution --- reduced-order model --- computational model --- gut microbiota dysbiosis --- canard-induced EADs --- computational biology --- metabolic modelling --- methods --- SREBP-2 --- mechanistic model --- systems modeling --- biological networks --- macromolecular composition --- provenance --- flux balance analysis --- immunotherapy --- compartmental modeling --- immuno-oncology --- metabolic network visualization --- mechanism --- bistable switch --- Clostridium difficile infection --- bioreactor operation optimization --- microRNA targeting --- CFD simulation --- biomass reaction --- RNA editing --- ordinary differential equation --- metabolic modeling --- mass-action networks --- hybrid model --- multiple time scales --- quantitative systems pharmacology (QSP) --- mathematical modeling --- microRNA --- cancer --- parameter optimization --- Hopf bifurcation --- breast