An Extension Collaborative Innovation Model In The Context Of Big Data
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An Extension Collaborative Innovation Model in the Context of Big Data by Xingsen Li,Yingjie Tian,Florentin Smarandache,Rajan Alex Pdf
The processes of generating innovative solutions mostly rely on skilled experts who are usually unavailable and their outcomes have uncertainty. Computer science and information technology are changing the innovation environment and accumulating Big Data from which a lot of knowledge is to be discovered.
Collected Papers. Volume V by Florentin Smarandache Pdf
This volum includes 37 papers of mathematics or applied mathematics written by the author alone or in collaboration.They were written during the years 2010-2014, about the hyperbolic Menelaus theorem in the Poincare disc of hyperbolic geometry, and the Menelaus theorem for quadrilaterals inhyperbolic geometry, about some properties of the harmonic quadrilateral related to triangle simedians and to Apollonius circles, etc.
Data Science by Jing He,Philip S. Yu,Yong Shi,Xingsen Li,Zhijun Xie,Guangyan Huang,Jie Cao,Fu Xiao Pdf
This book constitutes the refereed proceedings of the 6th International Conference on Data Science, ICDS 2019, held in Ningbo, China, during May 2019. The 64 revised full papers presented were carefully reviewed and selected from 210 submissions. The research papers cover the areas of Advancement of Data Science and Smart City Applications, Theory of Data Science, Data Science of People and Health, Web of Data, Data Science of Trust and Internet of Things.
Brain Informatics by Mufti Mahmud,M Shamim Kaiser,Stefano Vassanelli,Qionghai Dai,Ning Zhong Pdf
This book constitutes the refereed proceedings of the 14th International Conference on Brain Informatics, BI 2021, held in September 2021. The conference was held virtually due to the COVID-19 pandemic. The 49 full and 2 short papers together with 18 abstract papers were carefully reviewed and selected from 90 submissions. The papers are organized in the following topical sections: cognitive and computational foundations of brain science; investigations of human information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; and brain-machine intelligence and brain-inspired computing.
Big Data and Security by Yuan Tian,Tinghuai Ma,Qingshan Jiang,Qi Liu,Muhammad Khurram Khan Pdf
This book constitutes the refereed proceedings of the 4th International Conference on Big Data and Security, ICBDS 2022, held in Xiamen, China, during December 8–12, 2022. The 51 full papers and 3 short papers included in this book were carefully reviewed and selected from 211 submissions. They were organized in topical sections as follows: answer set programming; big data and new method; intelligence and machine learning security; data technology and network security; sybersecurity and privacy; IoT security.
Collaborative Innovation Networks by Yang Song,Francesca Grippa,Peter A. Gloor,João Leitão Pdf
Collaborative innovation networks are cyberteams of motivated individuals, and are self-organizing emergent social systems with the potential to promote health, happiness and individual growth in real-world work settings. This book describes how to identify and nurture collaborative innovation networks in order to shape the future working environment and pave the way for health and happiness, and how to develop future technologies to promote economic development, social innovation and entrepreneurship. The expert contributions and case studies presented also offer insights into how large corporations can creatively generate solutions to real-world problems by means of self-organizing mechanisms, while simultaneously promoting the well-being of individual workers. The book also discusses how such networks can benefit startups, offering new self-organizing forms of leadership in which all stakeholders are encouraged to collaborate in the development of new products.
Data Science and Productivity Analytics by Vincent Charles,Juan Aparicio,Joe Zhu Pdf
This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and data science, for the practically and theoretically important areas of ‘productivity analysis/data envelopment analysis’ and ‘data science/big data’. Data science is defined as the collection of scientific methods, processes, and systems dedicated to extracting knowledge or insights from data and it develops on concepts from various domains, containing mathematics and statistical methods, operations research, machine learning, computer programming, pattern recognition, and data visualisation, among others. Examples of data science techniques include linear and logistic regressions, decision trees, Naïve Bayesian classifier, principal component analysis, neural networks, predictive modelling, deep learning, text analysis, survival analysis, and so on, all of which allow using the data to make more intelligent decisions. On the other hand, it is without a doubt that nowadays the amount of data is exponentially increasing, and analysing large data sets has become a key basis of competition and innovation, underpinning new waves of productivity growth. This book aims to bring a fresh look onto the various ways that data science techniques could unleash value and drive productivity from these mountains of data. Researchers working in productivity analysis/data envelopment analysis will benefit from learning about the tools available in data science/big data that can be used in their current research analyses and endeavours. The data scientists, on the other hand, will also get benefit from learning about the plethora of applications available in productivity analysis/data envelopment analysis.
Handbook on Alternative Theories of Innovation by Godin, Benoît,Gaglio, Gérald,Vinck, Dominique Pdf
This insightful Handbook scrutinizes alternative concepts and approaches to the dominant economic or industrial theories of innovation. Providing an assessment of these alternatives, it questions the absence of these neglected types of innovation and suggests diverse theories.
New Horizons for a Data-Driven Economy by José María Cavanillas,Edward Curry,Wolfgang Wahlster Pdf
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.
Improving Business Performance Through Innovation in the Digital Economy by Oncioiu, Ionica Pdf
In the 21st century, advancements in the digital world are bringing about rapid waves of change in organizational management. As such, it is increasingly imperative to discover ways for businesses to adapt to changes in the markets and seize various digital marketing opportunities. Improving Business Performance Through Innovation in the Digital Economy is an essential reference source for the latest research on the impact of digital computing. It investigates new economic and entrepreneurial approaches to enhancing community development. Featuring research on topics such as business ethics, mobile technology, and cyber security, this book is ideally designed for knowledge workers, business managers, executives, entrepreneurs, small and medium enterprise managers, academicians, researchers, students, and global leaders seeking coverage on the management of sustainable enterprises.
With the development of the aging society and the increased importance of emergency risk management in recent years, a large number of medical care challenges - advancing medical treatments, care & support, pharmacological treatments, greater health awareness, emergency treatments, telemedical treatment and care, the introduction of electronic charts, and rising costs - are emerging as social issues throughout the whole world. Hospitals and other medical institutions must develop and maintain superior management to achieve systems that can provide better medical care, welfare and health while enabling "support innovation." Key medical care, welfare and health industries play a crucial role in this, but also of importance are management innovation models that enable "collaborative innovation" by closely linking diverse fields such as ICT, energy, electric equipment, machinery and transport. Looking across different industries, Collaborative Innovation offers new knowledge and insights on the extraordinary value and increasing necessity of collaboration across different organizations in improving the health and lives of people. It breaks new ground with its research theme of building "health support ecosystems," focusing on protecting people through collaborative innovation. This book opens up new, wide-ranging interdisciplinary academic research domains combining the humanities with science across various areas including general business administration, economics, information technology, medical informatics and drug information science.
Smart Sustainable Cities of the Future by Simon Elias Bibri Pdf
This book is intended to help explore the field of smart sustainable cities in its complexity, heterogeneity, and breadth, the many faces of a topical subject of major importance for the future that encompasses so much of modern urban life in an increasingly computerized and urbanized world. Indeed, sustainable urban development is currently at the center of debate in light of several ICT visions becoming achievable and deployable computing paradigms, and shaping the way cities will evolve in the future and thus tackle complex challenges. This book integrates computer science, data science, complexity science, sustainability science, system thinking, and urban planning and design. As such, it contains innovative computer–based and data–analytic research on smart sustainable cities as complex and dynamic systems. It provides applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the underlying physical and informational landscapes. It offers contributions pertaining to the ongoing development of computer–based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to urban systems that will advance different aspects of sustainability. This book seeks to explicitly bring together the smart city and sustainable city endeavors, and to focus on big data analytics and context-aware computing specifically. In doing so, it amalgamates the design concepts and planning principles of sustainable urban forms with the novel applications of ICT of ubiquitous computing to primarily advance sustainability. Its strength lies in combining big data and context–aware technologies and their novel applications for the sheer purpose of harnessing and leveraging the disruptive and synergetic effects of ICT on forms of city planning that are required for future forms of sustainable development. This is because the effects of such technologies reinforce one another as to their efforts for transforming urban life in a sustainable way by integrating data–centric and context–aware solutions for enhancing urban systems and facilitating coordination among urban domains. This timely and comprehensive book is aimed at a wide audience across science, academia industry, and policymaking. It provides the necessary material to inform relevant research communities of the state–of–the–art research and the latest development in the area of smart sustainable urban development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of smart sustainable cities based on big data analytics and context–aware computing.