Technological Solutions for Knowledge Management in Smart Cities

Nowadays huge volume of information, data and knowledge, that directly or indirectly relates to modern cities, their state and problems is gathered and stored. Effectiveness of its use significantly influences on effectiveness of city development. Due to constantly increasing amount of information and knowledge, for its best use special tools for knowledge management, including tools for knowledge systematization and building formalized descriptions as well as new algorithms for knowledge processing and application are required. In the paper a set of technological solutions focused on knowledge retrieval from multidimensional measurements provided by different sources of information is suggested. Use of developed technologies allow to organize operative processing of new measurements, taking into account all available knowledge. Dealing with measurements at the level of knowledge about measurements provides solutions of end user problems in terms of subject domain objects or situations but not separate measurements. Several subject domains and their tasks, that can be solved using the proposed set of technological solutions, are defined

Risk Assessment Model for Pluvial Flood Prediction Using Fuzzy-Based Classification Technique

Both developed and developing countries are promoting risk management and refining the ability to alleviate the effects of disaster both man-made and natural, which have become a threat to human life and the world’s economy. The variability in climate change, rapid urbanization and fast-growing socio-economic development has naturally increased the risk associated with flooding. A recent report showed that flood have affected more individuals than any other category of disaster in the 21st century with the highest percentage of 43% of all disaster events in 2019 and Africa been the second vulnerable continent after Asia. So, it is highly important to devise a scientific method for flood risk reduction since it cannot be eradicated. Machine learning can improve the risk management. The paper proposes a pluvial flood detection and prediction system based on machine learning techniques. The proposed model will employ a fuzzy rule-based classification approach for pluvial flood risk assessment. Keywords: Machine Learning, Pluvial Flood, Risk, Fuzzy Rule-Based, Prediction DOI: 10.7176/CEIS/12-1-07 Publication date: January 31st 202

Collaborative geographic visualization

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas AmbientaisThe present document is a revision of essential references to take into account when developing ubiquitous Geographical Information Systems (GIS) with collaborative visualization purposes. Its chapters focus, respectively, on general principles of GIS, its multimedia components and ubiquitous practices; geo-referenced information visualization and its graphical components of virtual and augmented reality; collaborative environments, its technological requirements, architectural specificities, and models for collective information management; and some final considerations about the future and challenges of collaborative visualization of GIS in ubiquitous environment

Data Science Technologies for Vibrant Cities

Smart Cities forced IT technologies make a significant step in their development. A new generation of agile knowledge based software applications and systems have been successfully designed and implemented. Wide capabilities of the agile applications were sufficient to meet the complete set of requirements of smart cities. Fast transformation of modern cities from smart cities to vibrant cities throws new even more complicated challenges to information technologies. While smart cities assumed wide usage of agile means and tools for solving applied tasks, applications for vibrant cities must provide agile environment for exploring and managing of all types of data, information and knowledge. Agile environment must be flexible enough to support iterative data processing and analyses procedures that can be easily reorganized or changed depending on context. The aim of agile environment creation and support is to extend a set of used mathematical, technological and program solutions. In the paper it is proposed to build applications for vibrant cities using agile data science methodologies and toolsets within the commonly used approaches for developing agile information systems

NASA SBIR abstracts of 1990 phase 1 projects

The research objectives of the 280 projects placed under contract in the National Aeronautics and Space Administration (NASA) 1990 Small Business Innovation Research (SBIR) Phase 1 program are described. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses in response to NASA's 1990 SBIR Phase 1 Program Solicitation. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 280, in order of its appearance in the body of the report. The document also includes Appendixes to provide additional information about the SBIR program and permit cross-reference in the 1990 Phase 1 projects by company name, location by state, principal investigator, NASA field center responsible for management of each project, and NASA contract number

Driving style recognition for intelligent vehicle control and advanced driver assistance: a survey

Driver driving style plays an important role in vehicle energy management as well as driving safety. Furthermore, it is key for advance driver assistance systems development, toward increasing levels of vehicle automation. This fact has motivated numerous research and development efforts on driving style identification and classification. This paper provides a survey on driving style characterization and recognition revising a variety of algorithms, with particular emphasis on machine learning approaches based on current and future trends. Applications of driving style recognition to intelligent vehicle controls are also briefly discussed, including experts' predictions of the future development

Adaptive and Re-adaptive Pedagogies in Higher Education: A Comparative, Longitudinal Study of Their Impact on Professional Competence Development across Diverse Curricula

This study addresses concerns that traditional, lecture-based teaching methods may not sufficiently develop the integrated competencies demanded by modern professional practice. A disconnect exists between conventional pedagogy and desired learning outcomes, prompting increased interest in innovative, student-centered instructional models tailored to competence growth. Despite this, nuanced differences in competence development across diverse university curricula remain underexplored, with research predominantly relying on students’ self-assessments. To address these gaps, this study employs longitudinal mixed-methods approaches with regard to theory triangulation and investigator triangulation to better understand how professional knowledge, skills, and dispositions evolve across varied curricula and contexts. This research emphasizes adaptive and re-adaptive teaching approaches incorporating technology, individualization, and experiential learning, which may uniquely integrate skill development with contextual conceptual learning. Specific attention is paid to professional education paths like design, media, and communications degrees, where contemporary competence models stress capabilities beyond core conceptual knowledge. Results from this study aim to guide reform efforts to optimize professional competence development across diverse academic areas

Building Smart Applications for Smart Cities – IGIS based Architectural Framework

To solve different kinds of complicated problems which arise in context of intensive development of modern cities a great number of various applications are constantly being developed. The most part of these applications are based on processing big volumes of heterogeneous data gathered from different types of available sources in real time. In the report an architectural framework oriented on building applications for smart cities in shortest time and with minimum spent of resources is suggested. The framework is based on intelligent geo information technologies and includes architectural and technological solutions along with many different computational libraries for building intelligent adaptive applications. Special attention is paid to information and knowledge organization. Different aspects of use of ontologies in the framework is discussed. Main directions of further development of proposed approach are defined