Automatic music composition has blossomed with the introduction of intelligent methodologies in computer science. Thereby, many methodologies for automatic music composition have been or could be described as “intelligent,” but what exactly is it that makes them intelligent? Furthermore, is there any categorization of intelligent music composition (IMC) methodologies that is both consistent and descriptive? This chapter aims to provide some insights on what IMC methodologies are, through proposing and analyzing a detailed categorization of them. Toward this perspective, methodologies that incorporate bioinspired intelligent algorithms (such as cellular automata, L-systems, genetic algorithms, swarm intelligence, among others) as well as their combinations are considered and briefly reviewed. At the same time, a consistent categorization of these methodologies is proposed, taking into account the utilization of their intelligent algorithm in accordance to their overall compositional aims. To this end, three main categories can be defined: the “unsupervised,” the “supervised,” and the “interactive” IMC methodologies.
The Caspian Sea and the Eastern Mediterranean are two regions with abundant energy resources. Their gas routes to Europe intersect and actors, exporters, pipeline owners and operators, transit states and downstream customers are connected to one another in a web of political and economic interdependencies. More significantly, these regions have been plagued by deep-seated ethnic conflicts and disputes: namely, the two oldest registered in the United Nations (the Cyprus and the Arab-Israeli Conflicts), the Nagorno-Karabakh problem, the Syria War and numerous tensions in the Eastern Mediterranean, the Caspian Sea and the Balkan regions. This book investigates what impact these energy resources have had on the respective conflicts and disputes, as well as their influence on the power game between the EU and Russia.
This work is a contribution to understanding multi-object traffic scenes from video sequences. All data is provided by a camera system which is mounted on top of the autonomous driving platform AnnieWAY. The proposed probabilistic generative model reasons jointly about the 3D scene layout as well as the 3D location and orientation of objects in the scene. In particular, the scene topology, geometry as well as traffic activities are inferred from short video sequences.
Automatic music composition has blossomed with the introduction of intelligent methodologies in computer science. Thereby, many methodologies for automatic music composition have been or could be described as “intelligent,” but what exactly is it that makes them intelligent? Furthermore, is there any categorization of intelligent music composition (IMC) methodologies that is both consistent and descriptive? This chapter aims to provide some insights on what IMC methodologies are, through proposing and analyzing a detailed categorization of them. Toward this perspective, methodologies that incorporate bioinspired intelligent algorithms (such as cellular automata, L-systems, genetic algorithms, swarm intelligence, among others) as well as their combinations are considered and briefly reviewed. At the same time, a consistent categorization of these methodologies is proposed, taking into account the utilization of their intelligent algorithm in accordance to their overall compositional aims. To this end, three main categories can be defined: the “unsupervised,” the “supervised,” and the “interactive” IMC methodologies.
Information flow is the foundation of any project. However, the major limiting factor is not the lack of information, but the inability to effectively integrate useful information into a project. By bringing together the fields of organizational science, organizational behavior, and information science, this book explores the interplay of social, technical, and technological factors influencing information flow. By understanding these concepts, managers can strategically leverage the social and technical characteristics of their project team, processes, and tools to enable positive iterations of trust and learning. These serve as the basis for effective information flow and result in significant improvements in information sharing, decision-making, and project outcomes. This unique perspective provides holistic insights regarding the management of team interactions, project planning, and the overarching structure and strategies used within the architecture, engineering, and construction (AEC) industry. These findings have significant implications for the: 1) The types of competencies and tools needed in the AEC industry; 2) How the industry approaches management and integration; and 3) The types of organizational structures and innovative strategies that will allow teams to make the best use of their valuable knowledge and realize their greatest collective potential.
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