다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

https://re.public.polimi.it/bitstream/11311/1049863/2/Negri%20et%20al%202017%20FAIM.pdf

A Review of the Roles of Digital Twin in CPS-based Production Systems

The purpose of this paper is to conduct a state-of-the-art review of the ongoing research on the Industry 4.0 phenomenon, highlight its key design principles and technology trends, identify its architectural design and offer a strategic roadmap that can serve manufacturers as a simple guide for the process of Industry 4.0 transition.,The study performs a systematic and content-centric review of literature based on a six-stage approach to identify key design principles and technology trends of Industry 4.0. The study further benefits from a comprehensive content analysis of the 178 documents identified, both manually and via IBM Watson’s natural language processing for advanced text analysis.,Industry 4.0 is an integrative system of value creation that is comprised of 12 design principles and 14 technology trends. Industry 4.0 is no longer a hype and manufacturers need to get on board sooner rather than later.,The strategic roadmap presented in this study can serve academicians and practitioners as a stepping stone for development of a detailed strategic roadmap for successful transition from traditional manufacturing into the Industry 4.0. However, there is no one-size-fits-all strategy that suits all businesses or industries, meaning that the Industry 4.0 roadmap for each company is idiosyncratic, and should be devised based on company’s core competencies, motivations, capabilities, intent, goals, priorities and budgets.,The first step for transitioning into the Industry 4.0 is the development of a comprehensive strategic roadmap that carefully identifies and plans every single step a manufacturing company needs to take, as well as the timeline, and the costs and benefits associated with each step. The strategic roadmap presented in this study can offer as a holistic view of common steps that manufacturers need to undertake in their transition toward the Industry 4.0.,The study is among the first to identify, cluster and describe design principles and technology trends that are building blocks of the Industry 4.0. The strategic roadmap for Industry 4.0 transition presented in this study is expected to assist contemporary manufacturers to understand what implementing the Industry 4.0 really requires of them and what challenges they might face during the transition process.

https://www.emerald.com/insight/content/doi/10.1108/JMTM-02-2018-0057/full/pdf

The future of manufacturing industry: a strategic roadmap toward Industry 4.0

Digital twin can be defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision making. Recent advances in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, data processing and management tools bring the promise of digital twins and their impact on society closer to reality. Digital twinning is now an important and emerging trend in many applications. Also referred to as a computational megamodel, device shadow, mirrored system, avatar or a synchronized virtual prototype, there can be no doubt that a digital twin plays a transformative role not only in how we design and operate cyber-physical intelligent systems, but also in how we advance the modularity of multi-disciplinary systems to tackle fundamental barriers not addressed by the current, evolutionary modeling practices. In this work, we review the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective. Our aim is to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.

/pdf/digital-twin-values-challenges-and-enablers-from-a-modeling-3hpoelaogn.pdf

Digital Twin: Values, Challenges and Enablers From a Modeling Perspective

The recently introduced series of description logics under the common moniker 'DL-Lite' has attracted attention of the description logic and semantic web communities due to the low computational complexity of inference, on the one hand, and the ability to represent conceptual modeling formalisms, on the other. The main aim of this article is to carry out a thorough and systematic investigation of inference in extensions of the original DL-Lite logics along five axes: by (i) adding the Boolean connectives and (ii) number restrictions to concept constructs, (iii) allowing role hierarchies, (iv) allowing role disjointness, symmetry, asymmetry, reflexivity, irreflexivity and transitivity constraints, and (v) adopting or dropping the unique name assumption. We analyze the combined complexity of satisfiability for the resulting logics, as well as the data complexity of instance checking and answering positive existential queries. Our approach is based on embedding DL-Lite logics in suitable fragments of the one-variable first-order logic, which provides useful insights into their properties and, in particular, computational behavior.

/pdf/the-dl-lite-family-and-relations-4dq237sy63.pdf

The DL-lite family and relations

Streams of events appear increasingly today in various Web applications such as blogs, feeds, sensor data streams, geospatial information, on-line financial data, etc. Event Processing (EP) is concerned with timely detection of compound events within streams of simple events. State-of-the-art EP provides on-the-fly analysis of event streams, but cannot combine streams with background knowledge and cannot perform reasoning tasks. On the other hand, semantic tools can effectively handle background knowledge and perform reasoning thereon, but cannot deal with rapidly changing data provided by event streams.To bridge the gap, we propose Event Processing SPARQL (EP-SPARQL) as a new language for complex events and Stream Reasoning. We provide syntax and formal semantics of the language and devise an effective execution model for the proposed formalism. The execution model is grounded on logic programming, and features effective event processing and inferencing capabilities over temporal and static knowledge. We provide an open-source prototype implementation and present a set of tests to show the usefulness and effectiveness of our approach.

EP-SPARQL: a unified language for event processing and stream reasoning

Today, the Internet of Things (IoT) comprises vertically oriented platforms for things. Developers who want to use them need to negotiate access individually and adapt to the platform-specific API and information models. Having to perform these actions for each platform often outweighs the possible gains from adapting applications to multiple platforms. This fragmentation of the IoT and the missing interoperability result in high entry barriers for developers and prevent the emergence of broadly accepted IoT ecosystems. The BIG IoT (Bridging the Interoperability Gap of the IoT) project aims to ignite an IoT ecosystem as part of the European Platforms Initiative. As part of the project, researchers have devised an IoT ecosystem architecture. It employs five interoperability patterns that enable cross-platform interoperability and can help establish successful IoT ecosystems.

/pdf/enabling-iot-ecosystems-through-platform-interoperability-u1ryto3uas.pdf

Enabling IoT Ecosystems through Platform Interoperability

Addressing dynamics and notifications in the Semantic Web realm has recently become an important area of research. Run time data is continuously generated by multiple social networks, sensor networks, various on-line services and so forth. How to get advantage of this continuously arriving data events remains a challenge --that is, how to integrate heterogeneous event streams, combine them with background knowledge e.g., an ontology, and perform event processing and stream reasoning. In this paper we describe ETALIS --a system which enables specification and monitoring of changes in near real time. Changes can be specified as complex event patterns, and ETALIS can detect them in real time. Moreover the system can perform reasoning over streaming events with respect to background knowledge. ETALIS implements two languages for specification of event patterns: ETALIS Language for Events, and Event Processing SPARQL. ETALIS has various applicabilities in capturing changes in semantic networks, broadcasting notifications to interested parties, and creating further changes based on processing of the temporal, static, or slowly evolving knowledge.

Stream reasoning and complex event processing in ETALIS

Complex Event Processing (CEP) is concerned with timely detection of complex events within multiple streams of atomic occurrences. It has useful applications in areas including financial services, mobile and sensor devices, click stream analysis etc. Numerous approaches in CEP have already been proposed in the literature. Event processing systems with a logic-based representation have attracted considerable attention as (among others reasons) they feature formal semantics and offer reasoning service. However logic-based approaches are not optimized for run-time event recognition (as they are mainly query-driven systems). In this paper, we present an expressive logic-based language for specifying and combining complex events. For this language we provide both a syntax as well as a formal declarative semantics. The language enables efficient run time event recognition and supports deductive reasoning. Execution model of the language is based on a compilation strategy into Prolog. We provide an implementation of the language, and present the performance results showing the competitiveness of our approach.

/pdf/a-rule-based-language-for-complex-event-processing-and-p6dkqpedh0.pdf

A rule-based language for complex event processing and reasoning

Complex Event Processing (CEP) is concerned with timely detection of complex events within multiple streams of atomic occurrences, and has useful applications in areas including financial services, mobile and sensor devices, click stream analysis and so forth. In this chapter, we present ETALIS Language for Events. It is an expressive language for specifying and combining complex events. For this language we provide both a syntax as well as a clear declarative formal semantics. The execution model of the language is based on a compilation strategy into Prolog. We provide an implementation of the language, and present experimental results of our running prototype. Further on, we show how our logic rule-based approach compares with a non-logic approach in respect of performance.

Darko Anicic

Papers

EP-SPARQL: a unified language for event processing and stream reasoning

Enabling IoT Ecosystems through Platform Interoperability

Stream reasoning and complex event processing in ETALIS

A rule-based language for complex event processing and reasoning

ETALIS: Rule-Based Reasoning in Event Processing