Data Mining Practical Machine Learning Tools and Techniques

Control of Discrete-event Systems provides a survey of the most important topics in the discrete-event systems theory with particular focus on finite-state automata, Petri nets and max-plus algebra. Coverage ranges from introductory material on the basic notions and definitions of discrete-event systems to more recent results. Special attention is given to results on supervisory control, state estimation and fault diagnosis of both centralized and distributed/decentralized systems developed in the framework of the Distributed Supervisory Control of Large Plants (DISC) project. Later parts of the text are devoted to the study of congested systems though fluidization, an over approximation allowing a much more efficient study of observation and control problems of timed Petri nets. Finally, the max-plus algebraic approach to the analysis and control of choice-free systems is also considered. Control of Discrete-event Systems provides an introduction to discrete-event systems for readers that are not familiar with this class of systems, but also provides an introduction to research problems and open issues of current interest to readers already familiar with them. Most of the material in this book has been presented during a Ph.D. school held in Cagliari, Italy, in June 2011. This book constitutes the refereed proceedings of the Third International Workshop on Tools and Algorithms for the Construction and Analysis of Systems, TACAS '97, held in Enschede, The Netherlands, in April 1997. The book presents 20 revised full papers and 5 tool demonstrations carefully selected out of 54 submissions; also included are two extended abstracts and a full paper corresponding to invited talks. The papers are organized in topical sections on space reduction techniques, tool demonstrations, logical techniques, verification support, specification and analysis, and theorem proving, model checking and applications. The refereed proceedings of the 24th International Conference on Applications and Theory of Petri Nets, ICATPN 2003, held in Eindhoven, The Netherlands, in June 2003. The 25 revised full papers presented together with 6 invited contributions were carefully reviewed and selected from 77 submissions. All current issues on research and development in the area of Petri nets are addressed, in particular concurrent systems design and analysis, model checking, networking, business process modeling, formal methods in software engineering, agent systems, systems specification, systems validation, discrete event systems, protocols, and prototyping. The contents of this volume are application oriented. The volume contains a de tailed presentation of 19 applications of CP-nets, covering a broad range of ap plication areas. Most of the projects have been carried out in an industrial set ting.

Coloured Petri Nets Basic Concepts, Analysis Methods and Practical Use

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Computers And Intractability A Guide To The Theory Of Np Completeness

Artificial intelligence (AI) is one of the most disruptive technologies of our time. Interest in the use of AI for urban innovation continues to grow. Particularly, the rise of smart cities—urban locations that are enabled by community, technology, and policy to deliver productivity, innovation, livability, wellbeing, sustainability, accessibility, good governance, and good planning—has increased the demand for AI-enabled innovations. There is, nevertheless, no scholarly work that provides a comprehensive review on the topic. This paper generates insights into how AI can contribute to the development of smarter cities. A systematic review of the literature is selected as the methodologic approach. Results are categorized under the main smart city development dimensions, i.e., economy, society, environment, and governance. The findings of the systematic review containing 93 articles disclose that: (a) AI in the context of smart cities is an emerging field of research and practice. (b) The central focus of the literature is on AI technologies, algorithms, and their current and prospective applications. (c) AI applications in the context of smart cities mainly concentrate on business efficiency, data analytics, education, energy, environmental sustainability, health, land use, security, transport, and urban management areas. (d) There is limited scholarly research investigating the risks of wider AI utilization. (e) Upcoming disruptions of AI in cities and societies have not been adequately examined. Current and potential contributions of AI to the development of smarter cities are outlined in this paper to inform scholars of prospective areas for further research.

https://www.mdpi.com/1996-1073/13/6/1473/pdf

Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature

Ontologies are the backbone of the Semantic Web, a semantic-aware version of the World Wide Web. To the end of making available large-scale, high quality domain ontologies, effective and usable methodologies are needed to facilitate the process of Ontology Building. Many of the methods proposed so far only partly refer to well-known and widely used standards from other areas, like software engineering and knowledge representation. In this paper we present UPON, a methodology for ontology building derived from the Unified Software Development Process. A comparative evaluation with other methodologies, as well as the results of its adoption in the context of the Athena Integrated Project, are also discussed.

A proposal for a unified process for ontology building : UPON

For contemporary software systems, security is considered to be a key quality factor and the analysis of IT security risk becomes an indispensable stage during software deployment. However, performing risk assessment according to methodologies and standards issued for the public sector or large institutions can be too costly and time consuming. Current business practice tends to circumvent risk assessment by defining sets of standard safeguards and applying them to all developed systems. This leads to a substantial gap: threats are not re-evaluated for particular systems and the selection of security functions is not based on risk models. This paper discusses a new lightweight risk assessment method aimed at filling this gap. In this proposal, Fuzzy Cognitive Maps (FCMs) are used to capture dependencies between assets, and FCM-based reasoning is performed to calculate risks. An application of the method is studied using an example of an e-health system providing remote telemonitoring, data storage and teleconsultation services. Lessons learned indicate that the proposed method is an efficient and low-cost approach, giving instantaneous feedback and enabling reasoning on the effectiveness of the security system.

/pdf/a-new-lightweight-method-for-security-risk-assessment-based-16gzylfwxl.pdf

A new lightweight method for security risk assessment based on fuzzy cognitive maps

Intelligent Transportation Systems (ITS) aim to improve safety, mobility and environmental performance of road transport. The INSIGMA project provides a fresh look at the possible innovations in this field, by enhancing the functionality and accuracy of ITS in urban environments. This paper describes the architecture, sensors, processing algorithms, output modules and advantages of the developed system. A comparison of existing ITS systems has been provided as background. Special attention has been given to performance and privacy issues, as the system includes social aspects such as location monitoring.

/pdf/insigma-an-intelligent-transportation-system-for-urban-51l5ywgrkb.pdf

INSIGMA: an intelligent transportation system for urban mobility enhancement

Map-matching algorithms aim at establishing a vehicle location on a road segment based on positioning data from a variety of sensors: GPS receivers, WiFi or cellular radios They are integral part of various Intelligent Transportation Systems (ITS) including fleet management, vehicle tracking, navigation services, traffic monitoring and congestion detection Our work was motivated by an idea of developing an algorithm that can be both utilized for tracking individual vehicles and for monitoring traffic in real-time We propose a new incremental map-matching algorithm that constructs of a sequence of Hidden-Markov Models (HMMs) Starting from an initial HMM, the next models are developed by alternating operations: expansion and contraction In the later, the map-matched trace is output We discuss results of initial experiments conducted for 20 GPS traces, which to test algorithm robustness, were modified by introduction of noise and/or downsampled

/pdf/an-incremental-map-matching-algorithm-based-on-hidden-markov-4q48tbdo65.pdf

An Incremental Map-Matching Algorithm Based on Hidden Markov Model

Use case diagrams play an important role in modeling with UML. Careful modeling is crucialin obtaining a correct and efficient system architecture. The paper refers to the formalanalysis of the use case diagrams. A formal model of use cases is proposed and its constructionfor typical relationships between use cases is described. Two methods of formal analysis andverification are presented. The first one based on a states’ exploration represents a modelchecking approach. The second one refers to the symbolic reasoning using formal methodsof temporal logic. Simple but representative example of the use case scenario verification isdiscussed.

/pdf/formal-analysis-of-use-case-diagrams-4a405x2032.pdf

Formal analysis of use case diagrams

For various IT systems security is considered a key quality factor. In particular, it might be crucial for video surveillance systems, as their goal is to provide continuous protection of critical infrastructure and other facilities. Risk assessment is an important activity in security management; it aims at identifying assets, threats and vulnerabilities, analysis of implemented countermeasures and their effectiveness in mitigating risks. This paper discusses an application of a new risk assessment method, in which risk calculation is based on Fuzzy Cognitive Maps (FCMs) to a complex automated video surveillance system. FCMs are used to capture dependencies between assets and FCM based reasoning is applied to aggregate risks assigned to lower-level assets (e.g. cameras, hardware, software modules, communications, people) to such high level assets as services, maintained data and processes. Lessons learned indicate, that the proposed method is an efficient and low-cost approach, giving instantaneous feedback and enabling reasoning on effectiveness of security system.

/pdf/risk-assessment-for-a-video-surveillance-system-based-on-pot29bxub4.pdf

Piotr Szwed

Papers

A new lightweight method for security risk assessment based on fuzzy cognitive maps

INSIGMA: an intelligent transportation system for urban mobility enhancement

An Incremental Map-Matching Algorithm Based on Hidden Markov Model

Formal analysis of use case diagrams

Risk assessment for a video surveillance system based on Fuzzy Cognitive Maps