Computational Methods in Science and Technology

Computational Methods in Science and Technology

Author: Sukhpreet Kaur

Publisher: CRC Press

Published: 2024-10-10

Total Pages: 595

ISBN-13: 1040260578

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This book contains the proceedings of the 4TH International Conference on Computational Methods in Science and Technology (ICCMST 2024). The proceedings explores research and innovation in the field of Internet of things, Cloud Computing, Machine Learning, Networks, System Design and Methodologies, Big Data Analytics and Applications, ICT for Sustainable Environment, Artificial Intelligence and it provides real time assistance and security for advanced stage learners, researchers and academicians has been presented. This will be a valuable read to researchers, academicians, undergraduate students, postgraduate students, and professionals within the fields of Computer Science, Sustainability and Artificial Intelligence.


IT Investment: Making a Business Case

IT Investment: Making a Business Case

Author: Dan Remenyi

Publisher: Routledge

Published: 2012-05-16

Total Pages: 210

ISBN-13: 1136390871

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Frequently not enough attention is given to producing a comprehensive business case or to producing an economic justification for an information systems investment. In fact many organizations are not clear as to what constitutes a sound business case and how to go about producing one. This Professional level book for the Computer Weekly Professional Series will show how to go about justification for I.T. spend. This book is designed for all those who are involved in the decision to invest in information systems. This book is especially relevant to senior business executives, senior financial managers and IT executives. Business consultants, computer and corporate advisors will also find the ideas and material addressed in this text of particular benefit as will anyone involved in corporate and strategic planning. In addition, senior students such as those working towards their MBAs will find this book of use. A business case is a statement or a series of statements that demonstrate the economic value of a particular intervention, a course of action or a specific investment. A business case is not simply a financial forecast of the hardware and software costs and the expected benefits. A business case for an information systems investment involves a comprehensive understanding of both the likely resources as well as the business drivers which will assist business managers improve their performance and thereby obtain a stream of benefits from the investment. In general there are approximately six steps in producing a business case for an information systems investment. 1. Determine the high-level business outcomes that will be clearly and comprehensively expressed as a set of opportunities the organization can take advantage of, or problems that need to be rectified. 2. Identify the corporate critical success factors that will be supported or enhanced by the operation of the completed information systems project or investment. 3. Create a list of specific and detailed outcomes or benefits, their appropriate metrics, measuring methods and responsibility points that are represented by the stakeholders. 4. Quantify the contribution made by the outcomes, which requires associating numbers or benefit values with outcomes where this is possible. 5. Highlight the risks associated with the project. Fundamental to this new approach to developing a business case for information systems investment is the fact that it incorporates much more than the financial numbers which are typically found in the standard approach to a feasibility study. This approach looks behind the financial numbers to the improvements in business performance which are facilitated by information systems and which are the real drivers of the benefits. Furthermore, this approach to developing a business case allows the organization to manage the process so that the required results are achieved.


Essential Ethnographic Methods

Essential Ethnographic Methods

Author: Jean J. Schensul

Publisher: Rowman Altamira

Published: 2012-10-01

Total Pages: 388

ISBN-13: 0759122040

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This is Book 3 of 7 in the Ethnographer's Toolkit, Second Edition. Essential Ethnographic Methods introduces the fundamental, face-to-face data collection tools that ethnographers and other qualitative researchers use on a regular basis. It provides ethnographers with tools to answer the principal ethnographic questions about setting, participants, activities, behavior, and more. The essential “mixed” methods for collecting data include open-ended and focused listening, questioning strategies, participant and non-participant observation, recording techniques, visual recall, mapping the environments and contexts in which participant behavior occurs, and engaging in ethnographically informed survey research. Because these data collection strategies require ethnographers to become involved in the local cultural setting and to acquire their experience through hands-on experience, the essential tools also allow them to learn about new situations from the perspective of an "insider.” With these detailed instructions, the quality and scope of the data ethnographers collect are sure to be improved. Other books in the set: Book 1: Designing and Conducting Ethnographic Research: An Introduction, Second Edition by Margaret D. LeCompte and Jean J. Schensul 9780759118690 Book 2: Initiating Ethnographic Research: A Mixed Methods Approach by Stephen L. Schensul, Jean J. Schensul, and Margaret D. LeCompte 9780759122017 Book 4: Specialized Ethnographic Methods: A Mixed Methods Approach edited by Jean J. Schensul and Margaret D. LeCompte 9780759122055 Book 5: Analysis and Interpretation of Ethnographic Data: A Mixed Methods Approach, Second Edition by Margaret D. LeCompte and Jean J. Schensul 9780759122079 Book 6: Ethics in Ethnography: A Mixed Methods Approach by Margaret D. LeCompte and Jean J. Schensul 9780759122093 Book 7: Ethnography in Action: A Mixed Methods Approach by Jean J. Schensul and Margaret D. LeCompte 9780759122116


Advances in Financial Machine Learning

Advances in Financial Machine Learning

Author: Marcos Lopez de Prado

Publisher: John Wiley & Sons

Published: 2018-01-23

Total Pages: 395

ISBN-13: 1119482119

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Learn to understand and implement the latest machine learning innovations to improve your investment performance Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest. In the book, readers will learn how to: Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.