2,438 research outputs found

    The Theory and Practice of Online Learning

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    Every chapter in the widely distributed first edition has been updated, and four new chapters on current issues such as connectivism and social software innovations have been added. Essays by practitioners and scholars active in the complex, diverse, and rapidly evolving field of distance education blend scholarship and research; practical attention to the details of teaching and learning; and mindful attention to the economics of the business of education

    Immersive Telepresence: A framework for training and rehearsal in a postdigital age

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    Better e-Learning for innovation in education

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    This book is an output from the ERASMUS+ project number 2015-1-TR01-KA204-021954 under the name 'Better e-Learning for All' (Project acronym: Better-E)This book - "Better e-Learning for Innovation in Education" - intends to provide an overview of the most important issues that relate Education through e-Learning and Pedagogical Innovation.Acknowledgements: The research leading to these results has received funding from the European Community's ERASMUS+ PROGRAMME under grant agreement no. 2015-1-TR01-KA204-021954 “Better e-Learning for All”.info:eu-repo/semantics/publishedVersio

    Semantic discovery and reuse of business process patterns

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    Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

    Discrete and Continuous Optimization Methods for Self-Organization in Small Cell Networks - Models and Algorithms

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    Self-organization is discussed in terms of distributed computational methods and algorithms for resource allocation in cellular networks. In order to develop algorithms for different self-organization problems pertinent to small cell networks (SCN), a number of concepts from discrete and continuous optimization theory are employed. Self-organized resource allocation problems such as physical cell identifier (PCI) assignment and primary component carrier selection are formulated as discrete optimization problems. Distributed graph coloring and constraint satisfaction algorithms are used to solve these problems. The PCI assignment is also discussed for multi-operator heterogeneous networks. Furthermore, different variants of simulated annealing are proposed for solving a graph coloring formulation of the orthogonal resource allocation problem. In the continuous optimization domain, a network utility maximization approach is considered for solving different resource allocation problems. Network synchronization is addressed using greedy and gradient search algorithms. Primal and dual decomposition are discussed for transmit power and scheduling weight optimizations, under a network-wide power constraint. Joint optimization over transmit powers and multi-user scheduling weights is considered in a multi-carrier SCN, for both maximum rate and proportional-fair rate utilities. This formulation is extended for multiple-input multiple-output (MIMO) SCNs, where apart from transmit powers and multi-user scheduling weights, the transmit precoders are also optimized, for a generic alpha-fair utility function. Optimization of network resources over multiple degrees of freedom is particularly effective in reducing mutual interference, leading to significant gains in network utility. Finally, an alternate formulation of transmit power allocation is considered, in which the network transmit power is minimized subject to the data rate constraints of users. Thus, network resource allocation algorithms inspired by optimization theory constitute an effective approach for self-organization in contemporary as well as future cellular networks

    Intelligent Sensor Networks

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    In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts
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