Cognitive map of the model for managing the sustainability of reproductive processes in industrial viticulture

The necessity of developing models for managing the sustainability of reproductive processes in long-term agrocenoses with the participation of grapes is substantiated. The main trends in the grapegrowing industry development in the Russian Federation and the Krasnodar Territory are revealed. The factors affecting the level of stability and efficiency of reproduction processes in long-term agrocenoses with the participation of grapes are determined. Methodological bases for the formation of cognitive models for managing the stability of reproductive processes in ampelocenoses are proposed. A cognitive map of the model for managing the sustainability of reproductive processes in long-term agrocenoses with the participation of grapes has been constructed, which allows to give a statistical assessment of the functional relationships between factorial and resultant indicators characterizing various types of functional and system-wide sustainability of agroecosystems with the participation of grapes. The tools for managing the sustainability of reproductive processes in complex natural and man-made systems are defined

A Methodology for Developing Computational Implementations of Scientific Theories

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”Computer programs have become a popular representation for scientific theories, particularly for implementing models or simulations of observed phenomena. Expressing a theory as an executable computer program provides many benefits, including: making all processes concrete, supporting the development of specific models, and hence enabling quantitative predictions to be derived from the theory. However, as implementations of scientific theories, these computer programs will be subject to change and modification. As programs change, their behaviour will also change, and ensuring continuity in the scientific value of the program is difficult. We propose a methodology for developing computer software implementing scientific theories. This methodology allows the developer to continuously change and extend their software, whilst alerting the developer to any changes in its scientific interpretation. We introduce tools for managing this development process, as well as for optimising the developed models

Influence of the Risk-Based Approach on the Development of the Management of Organizations

The current state, processes and development trends of national and world economic systems require the development of fundamentally new theoretical economic models adequate to the market, reflecting real changes in the world in the near future and in the long term. The purpose of this study was to find the right risk management tools. For this, cases were analysed in which various methods of managing the socio-economic sphere were used. Myths and stereotypes about the behaviour of people in this area were identified. The authors emphasized that macro-indicators of the state of economic systems are not canceled and are used in existing calculation models, but their predicted “strength” should be supplemented by a new model analysis based on a risk-based approach, taking into account the distinguished trend of assessing the current economic development

Uncertainty analysis in the Model Web

This thesis provides a set of tools for managing uncertainty in Web-based models and workflows.To support the use of these tools, this thesis firstly provides a framework for exposing models through Web services. An introduction to uncertainty management, Web service interfaces,and workflow standards and technologies is given, with a particular focus on the geospatial domain.An existing specification for exposing geospatial models and processes, theWeb Processing Service (WPS), is critically reviewed. A processing service framework is presented as a solutionto usability issues with the WPS standard. The framework implements support for Simple ObjectAccess Protocol (SOAP), Web Service Description Language (WSDL) and JavaScript Object Notation (JSON), allowing models to be consumed by a variety of tools and software. Strategies for communicating with models from Web service interfaces are discussed, demonstrating the difficultly of exposing existing models on the Web. This thesis then reviews existing mechanisms for uncertainty management, with an emphasis on emulator methods for building efficient statistical surrogate models. A tool is developed to solve accessibility issues with such methods, by providing a Web-based user interface and backend to ease the process of building and integrating emulators. These tools, plus the processing service framework, are applied to a real case study as part of the UncertWeb project. The usability of the framework is proved with the implementation of aWeb-based workflow for predicting future crop yields in the UK, also demonstrating the abilities of the tools for emulator building and integration. Future directions for the development of the tools are discussed

A Framework for Sustainability Decision Making System: A Proposal and an Implementation

Sustainability is a commitment to a new way of commissioning business activities that addresses balanced prosperity of social, economic and environmental dimensions of businesses. A sustainable business model is a roadmap for achieving sustainability and deals with the issues and dynamic relationships of sustainable dimensions of the businesses. A decision-making system that purports to support this sustainability commitment should facilitate development of sustainable business strategies, and translation of existing business operations into sustainable business processes. The system should also enable us capturing and managing sustainability related data for supporting the strategy development processes, business process reengineering processes and sustainability reporting processes. To achieve this goal we need a sustainable modelling and reporting framework that encapsulates different modelling processes e.g. decision support modelling, systems dynamics modelling, scenario modelling, simulation modelling, business process modelling, data modelling, and information modelling within a single framework. However, currently available sustainability modelling and reporting frameworks are neither integrated nor exhaustively backed by tools and technologies to support the sustainable business requirements; they also do not support the complete life cycle of a business transformation process. Therefore, businesses are facing increasing difficulty to develop, integrate and apply sustainable strategies and operations into their core business systems. This paper proposes a generic domain independent sustainability modelling and reporting framework that integrates various modelling processes for developing sustainable business models and sustainability reports. The framework encapsulates the sustainability models, modelling and reporting processes and aligns with the sustainable business framework

MODELING THE MACROECONOMIC TRANSMISSION ENVIRONMENT: PUBLIC SECTOR IMPACT USING THE MONEY AND FINANCIAL MARKET MODEL

Goal: The systemic macroeconomic environment is represented by economic and mathematical models that describe basic conditions for transmissions. Transmission mechanisms are formed not only by monetary policy instruments but also by other macroeconomic tools and factors that launch self-organizing processes, in particular, cyclicality and economic growth. Methods: To define such transmissions, the authors used the main macroeconomic models and functions that describe the institutional sectors of the economy; consumption and investment functions; arguments and functions underlying the balance of payments; and identity of national accounts. Results: An example of non-monetary transmissions is the influence of the public sector using the model of monetary and financial markets. The proposed methodological approach can be an economic and mathematical basis for developing software systems focused on forecasting economic dynamics, predicting monetary and financial crises, and managing the development of the national economy

Support in decision-making under uncertainty: a project risk assessment tool development and supplementary advances

A foremost dispute that persists on the contemporary world’s agenda is change. The on-going social/technological/economic changes create a competitive and challenging environment for companies to endure. To benefit from these changes, world economies partially depend on emerging Small and Medium Enterprises (SMEs) and their adaptability skills, and subsequently the development of an integrated capability to innovate has become the prime strategy for most of SMEs to subsist and grow. However, innovation and change are always somewhat bonded to an inherent risk development, which subsequently brings on the necessity of a revision of risk management approaches in innovative processes, whose importance SMEs tend to disregard. Additionally, little efforts have been made to improve and create empirical models, metrics and tools to assist SMEs managing latent risks in their innovative projects. This work seeks to present and discuss a solution to support SMEs in engaging on systematic risk management practices, which consists on an integrated risk assessment and response support web-based tool - Spotrisk® - designed for SMEs. On the other hand, an inherent subjectivity is linked with risk management and identification processes, due to uncertainty trait of its nature, for each individual perceives situations according to his own idiosyncrasy, which brings complications in normalizing risk profiles and procedures. This essay aims to bring insights concerning the support in decision-making processes under uncertainty, by addressing issues related with the risk behavior character among individuals. To address such issues, subjects of neuroscience or psychology are explored and models to identify such character are proposed, as well as models to improve presented tool. This work attempts to go beyond the restrictive aim of endeavoring on technical improvement dissertation, and in embraces an exploratory conceptualization concerning micro, small and medium businesses’ traits regarding risk characters and project risk assessment tools

TITAN: A knowledge-based platform for Big Data workflow management

Modern applications of Big Data are transcending from being scalable solutions of data processing and analysis, to now provide advanced functionalities with the ability to exploit and understand the underpinning knowledge. This change is promoting the development of tools in the intersection of data processing, data analysis, knowledge extraction and management. In this paper, we propose TITAN, a software platform for managing all the life cycle of science workflows from deployment to execution in the context of Big Data applications. This platform is characterised by a design and operation mode driven by semantics at different levels: data sources, problem domain and workflow components. The proposed platform is developed upon an ontological framework of meta-data consistently managing processes and models and taking advantage of domain knowledge. TITAN comprises a well-grounded stack of Big Data technologies including Apache Kafka for inter-component communication, Apache Avro for data serialisation and Apache Spark for data analytics. A series of use cases are conducted for validation, which comprises workflow composition and semantic meta-data management in academic and real-world fields of human activity recognition and land use monitoring from satellite images.Universidad de Málaga. Andalucía TECH

Catalogue and Toolbox of Risk Assessment and Management Tools

The ENHANCE project is concerned with analysing and working towards improved public-private partnerships for managing risks from natural hazards. An important issue for such partnerships is the methods, tools and processes available for assessing risk and risk management options. Risk analysis has long provided useful input to decision-making. At the same time, the field of risk analysis is in motion and an enhanced framing of risk analysis and risk management is being embraced following an iterative cycle organized around notions of learning, innovation and transformation. This broadened vision on risk analysis is a key issue for the ENHANCE project as well, which takes many and different perspectives on analysing, understanding, communicating and managing risk. This report lays out the status quo at the outset of the project regarding risk analytical tools, methods and data that are currently used by project partners in ENHANCE. The task overall develops a catalogue of existing risk assessment and management tools and methods to describe the concepts of iterative risk management and further sets up a toolbox, containing individual models and tools to be used by the case studies in their analyses. While work in the cases study, including methodological development, is in process, we find that ENHANCE partners and cases employ a multitude of models, tools and data ranging from impact analysis, different risk modelling techniques to various decision-support methods. A number of tools that encapsulate these methods are also available with the consortium. We suggest the tools and methods in use can be useful starting points for working towards a broader vision of iterative risk management. While the work so far, and this deliverable, have focussed on populating the technical stages of the risk analytical cycle (visually identified as the inner circle), we suggest in the next phase of ENHANCE, additional efforts should be dispensed to better understand adaptive management aspects associated with using these methods and tools, such as learning, innovation and transformation, which we exhibit visually in an outer circle. This report proceeds as follows: We start with laying out key elements of risk analysis and management in section 2, which also describes the new framing organized around the iterative risk-management concept. Methods for assessing risk and evaluating risk management are discussed in section 3. Then we consider methods, models and datasets that are in use in the ENHANCE case studies at the moment (section 4), before section 5 concludes. Finally and importantly, the annex lists more information on cases studies, for which detailed information was received from the project partners

A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors

Electrochemical energy storage systems play an important role in diverse applications, such as electrified transportation and integration of renewable energy with the electrical grid. To facilitate model-based management for extracting full system potentials, proper mathematical models are imperative. Due to extra degrees of freedom brought by differentiation derivatives, fractional-order models may be able to better describe the dynamic behaviors of electrochemical systems. This paper provides a critical overview of fractional-order techniques for managing lithium-ion batteries, lead-acid batteries, and supercapacitors. Starting with the basic concepts and technical tools from fractional-order calculus, the modeling principles for these energy systems are presented by identifying disperse dynamic processes and using electrochemical impedance spectroscopy. Available battery/supercapacitor models are comprehensively reviewed, and the advantages of fractional types are discussed. Two case studies demonstrate the accuracy and computational efficiency of fractional-order models. These models offer 15–30% higher accuracy than their integer-order analogues, but have reasonable complexity. Consequently, fractional-order models can be good candidates for the development of advanced b attery/supercapacitor management systems. Finally, the main technical challenges facing electrochemical energy storage system modeling, state estimation, and control in the fractional-order domain, as well as future research directions, are highlighted