87,750 research outputs found
Technology Solutions for Developmental Math: An Overview of Current and Emerging Practices
Reviews current practices in and strategies for incorporating innovative technology into the teaching of remedial math at the college level. Outlines challenges, emerging trends, and ways to combine technology with new concepts of instructional strategy
Principles of Modeling in Information Communication Systems and Networks
The authors present in this entry chapter the basic rubrics of models, modeling, and simulation, an un-
derstanding of which is indispensible for the comprehension of subsequent chapters of this text on the
all-important topic of modeling and simulation in Information Communication Systems and Networks
(ICSN). A good example is the case of analyzing simulation results of traffic models as a tool for investigat-
ing network behavioral pattarns as it affects the transmitted content (Atayero, et al., 2013). The various
classifications of models are discussed, for example classification based on the degree of semblance to
the original object (i.e. isomorphism). Various fundamental terminologies without the knowledge of which
the concepts and models and modeling cannot be properly understood are explained. Model stuctures
are highlighted and discussed. The methodological basis of formalizing complex system structures is
presented. The concept of componential approach to modeling is presented and the necessary stages of
mathematical model formation are examined and explained. The chapter concludes with a presentation
of the concept of simulation vis-Ã -vis information communication systems and networks
Thought for Food: the impact of ICT on agribusiness
This report outlines the impact of ICT on the food economy. On the basis of a literature review from four disciplines - knowledge management, management information systems, operations research and logistics, and economics - the demand for new ICT applications, the supply of new applications and the match between demand and supply are identified. Subsequently the impact of new ICT applications on the food economy is discussed. The report relates the development of new technologies to innovation and adoption processes and economic growth, and to concepts of open innovations and living lab
Effects of innovation types on firm performance
Innovation is broadly seen as an essential component of competitiveness, embedded in the organizational structures, processes, products, and services within a firm. The objective of this paper is to explore the effects of the organizational, process, product, and marketing innovations on the different aspects of firm performance, including innovative, production, market, and financial performances, based on an empirical study covering 184 manufacturing firms in Turkey. A theoretical framework is empirically tested identifying the relationships amid innovations and firm performance through an integrated innovation-performance analysis. The results reveal the positive effects of innovations on firm performance in manufacturing industries
Early Warning Analysis for Social Diffusion Events
There is considerable interest in developing predictive capabilities for
social diffusion processes, for instance to permit early identification of
emerging contentious situations, rapid detection of disease outbreaks, or
accurate forecasting of the ultimate reach of potentially viral ideas or
behaviors. This paper proposes a new approach to this predictive analytics
problem, in which analysis of meso-scale network dynamics is leveraged to
generate useful predictions for complex social phenomena. We begin by deriving
a stochastic hybrid dynamical systems (S-HDS) model for diffusion processes
taking place over social networks with realistic topologies; this modeling
approach is inspired by recent work in biology demonstrating that S-HDS offer a
useful mathematical formalism with which to represent complex, multi-scale
biological network dynamics. We then perform formal stochastic reachability
analysis with this S-HDS model and conclude that the outcomes of social
diffusion processes may depend crucially upon the way the early dynamics of the
process interacts with the underlying network's community structure and
core-periphery structure. This theoretical finding provides the foundations for
developing a machine learning algorithm that enables accurate early warning
analysis for social diffusion events. The utility of the warning algorithm, and
the power of network-based predictive metrics, are demonstrated through an
empirical investigation of the propagation of political memes over social media
networks. Additionally, we illustrate the potential of the approach for
security informatics applications through case studies involving early warning
analysis of large-scale protests events and politically-motivated cyber
attacks
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