A geo-database for potentially polluting marine sites and associated risk index

The increasing availability of geospatial marine data provides an opportunity for hydrographic offices to contribute to the identification of Potentially Polluting Marine Sites (PPMS). To adequately manage these sites, a PPMS Geospatial Database (GeoDB) application was developed to collect and store relevant information suitable for site inventory and geo-spatial analysis. The benefits of structuring the data to conform to the Universal Hydrographic Data Model (IHO S-100) and to use the Geographic Mark-Up Language (GML) for encoding are presented. A storage solution is proposed using a GML-enabled spatial relational database management system (RDBMS). In addition, an example of a risk index methodology is provided based on the defined data structure. The implementation of this example was performed using scripts containing SQL statements. These procedures were implemented using a cross-platform C++ application based on open-source libraries and called PPMS GeoDB Manager

Decision Support Systems

Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року

Second International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2021). Kryvyi Rih, Ukraine, May 19-21, 2021.Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року

Design of a Sustainable Competitiveness Evaluation and Execution System (SuCEES)

To be competitive is the major reason why companies continuously improve their performance and innovate their processes, products and services. The recent decades revealed an increase number of companies that felt into bankruptcy, independently of their size, sector or market status. In fact, this is a phenomenon, which have been a concern among big companies and even start-ups. It is understood that to survive and to succeed, business leaders need to be aware about trends to be able to visioning future competitiveness environments, and to anticipate actions to respond to each daily challenges. In this context, the difference between successful or failed strategies lies on knowing, not only the trends, but also the actual performance of the company and its competitive strength. To do so, strategic planning and evaluation frameworks and models should be used in a systematic and integrated way, based on reliable data and appropriate indicators, to define suitable and timeless strategies, objectives and goals. However, this is not enough, one of the major failure modes of strategic planning is companies’ inability to implement proper actions to achieve those goals, fact known as the “execution gap”. The aim of this research is to contribute to the improvement of companies’ strategic planning process and, consequently, to boost their competitiveness and to reduce their exposure to bankruptcy. With this purpose, SuCEES (Sustainable Competitiveness Evaluation and Execution System) was designed, which is an integrated system founded on an alternative definition of sustainable competitiveness based on resilience, innovation and sustainability concepts. Composed by evaluation and execution frameworks it: i) allows the measurement of companies’ competitiveness positioning, competitive advantage and competitiveness risk, by scoring seven competitiveness drivers, and; ii) supports the definition of companies’ strategic objectives, their translation into operational targets and actions needed, as well as the achievement of results, through monitoring and control tools. SuCEES was validated by the participation of a pool of experts and through two case studies, conducted in companies Electrolux Poland and Visteon Portugal

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems

Geodetic infrastructure of Serbia

Geodetic reference systems and their realization at the territory of Serbia have been created and maintained since the end of 19th century. Until mid-80s a series of reference geodetic networks were established: trigonometric networks in four orders, two levelling networks of high accuracybut also a series of gravimetric networks. In the following period of 20 years, there were not any organized worksaiming to maintenance of existing networks and creating new ones. In 1996, works started again on developing a new geodetic infrastructure in the form of realizing: a passive geodetic network, a network of permanent stations (AGROS – the active geodetic reference network of Serbia) as well as basic gravimetric networks. In this paperwork, a short review of works aiming to establish and use said networks is given but also a series of suggestions for a future development of geodetic infrastructure of Serbia