T K Ganesh (94 results)

Hardcover. Condition: New. ISBN:8189012118 N.A.

Hardbound. Condition: As New. New. Contents Preface. 1. News media in digital age. 2. Digital news media opportunities and challenges. 3. Independent media in digital environment. 4. Online media and the interactivity. 5. Digital future of mass media. 6. Audience participation in journalism. 7. News values in digital age. 8. Ethical issues of digital new media. Bibliography. Index. Traditionally centralised news gathering and distribution is being augmented by what's happening at the edges of increasingly ubiquitous networks. People are combining powerful technological tools and innovative ideas fundamentally altering the nature of journalism in this new century. There are new possibilities for everyone in the process journalist newsmaker and the active audience of news who isn't satisfied with today's product or who wants to make some news too. The venerable profession of journalism finds itself at a rare moment in history where for the first time its hegemony as gatekeeper of the news is threatened by not just new technology and competitors but potentially by the audience it serves. Armed with easy to use web publishing tools always on connections and increasingly powerful mobile devices the online audience has the means to become an active participant in the creation and dissemination of news and information. This book gives a very thorough overview to the modern trends in the media environment. It details the important considerations when exploring a collaborative effort between audience and media organisations. It will be an incredibly useful resource for media professionals online communities webbloggers teachers students researchers and anyone who is serious about learning how new technologies are changing the media landscape and building the global audience. 210 pp.…

Hardcover. Condition: New. ISBN:8189012045 N.A.

Hardbound. Condition: As New. New. Contents Preface. 1. Nature of the news. 2. Sources of news. 3. Responsibilities of a news reporter. 4. The art of interviewing. 5. Political reporting. 6. Sports reporting. 7. Computer assisted reporting. 8. Copy editing. 9. Structure of the news story. 10. Electronic editing. 11. Digital photo editing. 12. Writing for the press. 13. Writing for electronic media. 14. Journalistic ethics in digital age. Bibliography. Index. A century and a half ago covering news was straights forward searching the news stories observing the scene waiting for public meetings or press conferences interviewing the people related with the news then run as fast as possible back to the newsroom and try to beat the competition to print. Journalism has changed dramatically since then as new media technologies starting with the telegraph and telephone to internet and web logs has made it possible to find out about events without actually being on the site. The innovation broad diffusion and rapid adoption of new media technologies have brought dramatic transformational changes in the way journalism is practised conducted and disseminated. The present publication is comprehensive textbook which can teach students how to report write and edit for new media including print broadcast and internet based media. It leads readers through the myriad ways in which digital technologies have had an impact on the practice of journalism from the way reporters gather information and present news stories to how newsrooms structure themselves and do business. It provides the practical techniques and theoretical knowledge that underpin the fundamental skills of reporters and editors. It will be an essential reading for students on journalism courses and media professionals looking for a reference that covers the skill technology and knowledge required for the digital age. 294 pp. …

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Paperback. Condition: New. A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system's perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems.Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book's website.Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarterThis book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which include both basic and advanced concepts.…

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Paperback. Condition: Brand New. 232 pages. 9.18x6.12x9.21 inches. In Stock.

Paperback. Condition: Brand New. 136 pages. 8.66x5.91x0.31 inches. In Stock.

Paperback. Condition: Brand New. 136 pages. 8.66x5.91x0.31 inches. In Stock.

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Condition: New. Dr Shadi Mohamed is an Associate Professor at Heriot-Watt University, Scotland, UK.Dr Ganesh Diwan is a practising acoustics engineer in UKIn computational acoustics, standard Finite Element Methods (FEM) face severe limit.

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Paperback. Condition: New. A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system's perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems.Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book's website.Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarterThis book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which include both basic and advanced concepts.…

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Hardcover. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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