Digital media and reporting conflict : blogging and the BBC's coverage of war and terrorism / / Daniel Bennett

• Record Nr.: UNINA9910465689403321
• Autore: Bennett Daniel
• Pubbl/distr/stampa: New York ; ; London : , : Routledge, , 2013
• ISBN: 1-136-68800-5; 0-203-57647-0
• Descrizione fisica: 1 online resource (292 p.)
• Collana: Routledge research in journalism ; ; 6
• Disciplina: 070.4/3330941
• Soggetti: War - Press coverage - Great Britain - History - 21st century; Terrorism - Press coverage - Great Britain - History - 21st century; Online journalism - Great Britain - History - 21st century; Journalism - Objectivity - Great Britain; Blogs - Political aspects - Great Britain; Blogs - Social aspects - Great Britain; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Introduction: the impact of blogging on the BBC's coverage of war and terrorism -- The "war and terror" blogosphere. Blogs: "rumour, prejudice and gossip" or "standard" BBC source? -- Reporting conflict from news needles in digital haystacks -- Information overload, the 24/7 news cycle and the turn to twitter -- "Outside the BBC universe"? blogging at the BBC -- "Can you teach granddad how to dance"? involving the audience on BBC programme blogs -- "Live blogging" terror: the BBC's coverage of the attacks on Mumbai -- Reporting conflict: war in Gaza and the limits of the news revolution -- Conclusion: the two faces of Janus: the future of journalism.
• Sommario/riassunto: <P>This book explores the impact of new forms of online reporting on the BBC's coverage of war and terrorism. Informed by the views of over 100 BBC staff at all levels of the corporation, Bennett captures journalists' shifting attitudes towards blogs and internet sources used to cover wars and other conflicts. He argues that the BBC's practices and values are fundamentally evolving in response to the challenges of ; immediate digital publication. Ongoing challenges for journalism in the online media environment are identified: maintaining impartiality in the face of calls for more open personal

Introduction to stochastic search and optimization : estimation, simulation, and control / / James C. Spall

• Record Nr.: UNINA9910146070403321
• Autore: Spall James C.
• Pubbl/distr/stampa: Hoboken, N.J. : , : Wiley-Interscience, , 2003
• ISBN: 1-280-25282-0; 9786610252824; 0-470-34845-3; 0-471-44190-2; 0-471-72213-8
• Descrizione fisica: 1 online resource (620 pages)
• Collana: Wiley-Interscience series in discrete mathematics and optimization
• Disciplina: 519.23
• Soggetti: Stochastic processes; Search theory; Mathematical optimization
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. 558-579) and index.
• Nota di contenuto: 1. Stochastic Search and Optimization: Motivation and Supporting Results -- 2. Direct Methods for Stochastic Search -- 3. Recursive Estimation for Linear Models -- 4. Stochastic Approximation for Nonlinear Root-Finding -- 5. Stochastic Gradient Form of Stochastic Approximation -- 6. Stochastic Approximation and the Finite-Difference Method -- 7. Simultaneous Perturbation Stochastic Approximation -- 8. Annealing-Type Algorithms -- 9. Evolutionary Computation I: Genetic Algorithms -- 10. Evolutionary Computation II: General Methods and Theory -- 11. Reinforcement Learning via Temporal Differences -- 12. Statistical Methods for Optimization in Discrete Problems -- 13. Model Selection and Statistical Information -- 14. Simulation-Based Optimization I: Regeneration, Common Random ; Numbers, and Selection Methods -- 15. Simulation-Based Optimization II: Stochastic Gradient and Sample Path Methods -- 16. Markov Chain Monte Carlo -- 17. Optimal Design for Experimental Inputs.
• Sommario/riassunto: A unique interdisciplinary foundation for real-world problem solving Stochastic search and optimization techniques are used in a vast number of areas, including aerospace, medicine, transportation, and finance, to name but a few. Whether the goal is refining the design of a missile or aircraft, determining the effectiveness of a new drug, developing the most efficient timing strategies for traffic signals, or making investment decisions in order to increase profits, stochastic algorithms can help researchers and practitioners devise optimal solutions to countless real-world problems. Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control is a graduate-level introduction to the principles, algorithms, and practical aspects of stochastic optimization, including applications drawn from engineering, statistics, and computer science. The treatment is both rigorous and broadly accessible, distinguishing this text from much of the current literature and providing students, researchers, and practitioners with a strong foundation for the often-daunting task of solving real-world problems. The text covers a broad range of today’s most widely used stochastic algorithms, including: Random search Recursive linear estimation Stochastic approximation Simulated annealing Genetic and evolutionary methods Machine (reinforcement) learning Model selection Simulation-based optimization Markov chain Monte Carlo Optimal experimental design. The book includes over 130 examples, Web links to software and data sets, more than 250 exercises for the reader, and an extensive list of references. These features help make the text an invaluable resource for those interested in the theory or practice of stochastic search and optimization.