Transforming Yekaterinburg into a Safe, Resilient-Smart and Sustainable City

The initiative (since 2014) project described in this paper is a product of a joint innovative research and implementation effort of the Civil Engineering and Architecture Institute, Ural Federal University, the Science and Engineering Centre "Reliability and Safety of Large Systems and Machines", Ural Branch Russian Academy of Sciences (both Yekaterinburg), Start-up OptiCits, Barcelona, Spain and the Old Dominion University, Norfolk, VA, USA. The project is based on using the MAICS convergent technology [1] to create a versatile multi-purpose tool for optimizing the science and art of risk based governance of resilience-smart and sustainable city infrastructure and communities operating in usual and extreme conditions. The tool being developed is tailored to the needs of the City of Yekaterinburg-the capital of the Urals Region and allegedly the third most important and vibrant city of Russia. It is also being offered to the Yekaterinburg City Administration as an every-day decision-support work-tool and addendum to the Strategic Program "Yekaterinburg 2030 - a Safe City"[2] during preparation of the city for winning and conducting the World Expo-2025. Authors believe that the findings of this research would also be useful to the Sverdlovsk Oblast cities of every size and type of communities that inhabit them, including, first and foremost, Nizhny Tagil, Kamensk Uralsky, Serov, Pervouralsk, Revda, Verkhnyaya Pyshma, multiple mono-cities et al. The project also incorporates block-chain technology, smart contracts and digital currency as an effective tool for implementing the project. © 2018 Institute of Physics Publishing. All rights reserved

Adaptive User Interfaces for Intelligent E-Learning: Issues and Trends

Adaptive User Interfaces have a long history rooted in the emergence of such eminent technologies as Artificial Intelligence, Soft Computing, Graphical User Interface, JAVA, Internet, and Mobile Services. More specifically, the advent and advancement of the Web and Mobile Learning Services has brought forward adaptivity as an immensely important issue for both efficacy and acceptability of such services. The success of such a learning process depends on the intelligent context-oriented presentation of the domain knowledge and its adaptivity in terms of complexity and granularity consistent to the learner’s cognitive level/progress. Researchers have always deemed adaptive user interfaces as a promising solution in this regard. However, the richness in the human behavior, technological opportunities, and contextual nature of information offers daunting challenges. These require creativity, cross-domain synergy, cross-cultural and cross-demographic understanding, and an adequate representation of mission and conception of the task. This paper provides a review of state-of-the-art in adaptive user interface research in Intelligent Multimedia Educational Systems and related areas with an emphasis on core issues and future directions

Heuristics in Decision Making

Heuristics are simple rules of thumbs for problem solving that follow a logic that is quite different from consequential logic. They have long been regarded, as an inferior technique for decision making that is the source of irrational decision behavior. Recently, decision making researchers have demonstrated that some heuristics are highly efficient and can compete with complex decision models in some application domains. This paper explores the different streams of research, summarizes the state of the art decision making model, and discusses its implications for complex decisions in engineering and technology management

A MODIFIED FMEA APPROACH BASED INTEGRATED DECISION FRAMEWORK FOR OVERCOMING THE PROBLEMS OF SUDDEN FAILURE AND ACCIDENTAL HAZARDS IN TURBINE AND ALTERNATOR UNIT

The proposed work presents a novel integrated decision framework, based on Intuitionistic Fuzzy (IF)- Failure Mode & Effect Analysis (IF-FMEA), and IF-Technique for Order of Preference by Similarity to Ideal Solution (IF-TOPSIS) approaches for analysing the failure risk issues of Turbine and Alternator Unit (TAU) in a chemical treatment-based sugar process industry. The proposed novel IF-FMEA approach-based modelling overcomes the various demerits of traditional FMEA approaches which are faced during the identification of critical failure causes based on Risk Priority Number (RPN) outputs. On the basis of detailed qualitative information related to plant operation, FMEA sheet was developed and linguistic ratings were collected against three risk factors such as probability of Occurrence (O), Severity (S), and Detection (D). IF- Hybrid Weighted Euclidean Distance (IFHWED) score has been computed to rank all listed failure causes under three risk factors. The ranking results based on IF-FMEA approach has been compared with the well existed IF-TOPSIS approach for evaluating the accuracy of proposed modelling results. Sensitivity analysis has been also done for checking the robustness of the framework. The analysis results were provided to maintenance executives of the TAU unit to frame optimum maintenance plan for overcoming the problems of sudden breakdown. The analysis results are also applicable to TAU systems which are installed in other chemical process industries globally.

Robustness - a challenge also for the 21st century: A review of robustness phenomena in technical, biological and social systems as well as robust approaches in engineering, computer science, operations research and decision aiding

Notions on robustness exist in many facets. They come from different disciplines and reflect different worldviews. Consequently, they contradict each other very often, which makes the term less applicable in a general context. Robustness approaches are often limited to specific problems for which they have been developed. This means, notions and definitions might reveal to be wrong if put into another domain of validity, i.e. context. A definition might be correct in a specific context but need not hold in another. Therefore, in order to be able to speak of robustness we need to specify the domain of validity, i.e. system, property and uncertainty of interest. As proofed by Ho et al. in an optimization context with finite and discrete domains, without prior knowledge about the problem there exists no solution what so ever which is more robust than any other. Similar to the results of the No Free Lunch Theorems of Optimization (NLFTs) we have to exploit the problem structure in order to make a solution more robust. This optimization problem is directly linked to a robustness/fragility tradeoff which has been observed in many contexts, e.g. 'robust, yet fragile' property of HOT (Highly Optimized Tolerance) systems. Another issue is that robustness is tightly bounded to other phenomena like complexity for which themselves exist no clear definition or theoretical framework. Consequently, this review rather tries to find common aspects within many different approaches and phenomena than to build a general theorem for robustness, which anyhow might not exist because complex phenomena often need to be described from a pluralistic view to address as many aspects of a phenomenon as possible. First, many different robustness problems have been reviewed from many different disciplines. Second, different common aspects will be discussed, in particular the relationship of functional and structural properties. This paper argues that robustness phenomena are also a challenge for the 21st century. It is a useful quality of a model or system in terms of the 'maintenance of some desired system characteristics despite fluctuations in the behaviour of its component parts or its environment' (s. [Carlson and Doyle, 2002], p. 2). We define robustness phenomena as solution with balanced tradeoffs and robust design principles and robustness measures as means to balance tradeoffs. --