الصفحة 4
الصفحة 4
Cooperative Design, Visualization, and Engineering ; 17th International Conference, CDVE 2020, Bangkok, Thailand, October 25–28, 2020, Proceedings
This book constitutes the proceedings of the 17th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2020, held in Bangkok, Thailand, in October 2020.* The 33 full papers and 7 short papers presented were carefully reviewed and selected from 74 submissions. The achievement, progress and future challenges are reported in areas such as health care, industrial design, banking IT systems, cultural activities support, operational maritime cybersecurity assurance, emotion communication, and social network data analytics.
Contemporary Issues in Luxury Brand Management
Provides a comprehensive overview of the key themes surrounding luxury brand management and the core issues faced by luxury firms today. The luxury industry has undergone a series of dynamic changes in the past twenty years. Economic trends, digital transformation, and changing consumer habits are creating a new competitive landscape where traditional strategies will not necessarily provide continued growth and profitability. Approaching luxury from a realistic brand management perspective, this book works step-by-step through a typical luxury course structure, covering sustainability, heritage, emerging brands, digital marketing and analytics, curation, intellectual property, and start-ups.
Consumer Behaviour and Analytics
Consumer Behaviour and Analytics provides a consumer behaviour textbook for the new marketing reality. In a world of Big Data, machine learning and AI, this key text reviews the issues, research and concepts essential for navigating this new terrain. It demonstrates how we can use data-driven insight and merge this with insight from extant research to inform knowledge-driven decision making.
Conducting Quantitative Research In Education
provides a clear and straightforward guide for all those seeking to conduct quantitative research in the field of education, using primary research data samples. While positioned as less powerful and somehow inferior, non-parametric tests can be very useful where the research can only be designed to accommodate data structure which is ordinal, or scale but violates a normality assumption, which is required for parametric tests. Non-parametric data are a staple of educational research, and as such, it is essential that educational researchers learn how to work with these data with confidence and rigour.
Cognitive Computing in Human Cognition : Perspectives and Applications
This edited book designs the Cognitive Computing in Human Cognition to analyze to improve the efficiency of decision making by cognitive intelligence. The book is also intended to attract the audience who work in brain computing, deep learning, transportation, and solar cell energy. Due to this in the recent era, smart methods with human touch called as human cognition is adopted by many researchers in the field of information technology with the Cognitive Computing.
Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications ; 9th EAI International Conference, CloudComp 2019, and 4th EAI International Conference, SmartGIFT 2019, Beijing, China, December 4-5, 2019, and December 21-22, 2019
Constitutes the refereed proceedings of the 9thInternational Conference on Cloud Computing, CloudComp 2019, and the 4th International Conference on Smart Grid and Innovative Frontiers in Telecommunications, SmartGIFT 2019, both held in Beijing, China, in December 2019. The55 full papers of both conferences were selected from 113 submissions. CloudComp 2019 presents recent advances and experiences in clouds, cloud computing and related ecosystems and business support. The papers are grouped thematically in tracks on cloud architecture and scheduling; cloud-based data analytics; cloud applications; and cloud security and privacy. SmartGIFT 2019 focus on all aspects of smart grids and telecommunications, broadly understood as the renewable generation and distributed energy resources integration, computational intelligence applications, information and communication technologies.
Cloud Computing Enabled Big-Data Analytics in Wireless Ad-hoc Networks
Discusses intelligent computing through the Internet of Things (IoT) and Big-Data in vehicular environments in a single volume. It covers important topics, such as topology-based routing protocols, heterogeneous wireless networks, security risks, software-defined vehicular ad-hoc networks, vehicular delay tolerant networks, and energy harvesting for WSNs using rectenna.
Marketing metrics : Leverage analytics and data to optimize marketing strategies
Featuring examples from a range of organizations including Coca-Cola and Mercedes-Benz, it shows how to create a strategy which leverages consumer data for customer-centric marketing, establishes the ROI of channels and campaigns, strengthens brands and creates data-driven product strategies. Covering the range of new global laws that impact consumer privacy and data collection and usage, Marketing Metrics shows how to use data in a non-invasive, secure and ethical way.
Marketing effectiveness : Applying marketing science for brand growth
Contrary to popular belief marketing effectiveness is not just about the measuring of ROI. The lens of effectiveness must be applied to all marketing mix elements, from strategy to pricing and product, to media and advertising. It's a strategic shift that demands robust evidence-based decisions and consistent application in order to grow. Written by leading marketing practitioner, Sorin Patilinet, this book enables mid-senior level marketers to integrate the scientific methods and advanced measurements required for true marketing effectiveness into their marketing strategies, in order to reap the benefits of strong customer understanding and developing decision-making processes for growth. Covering everything from neuroscience and its application to marketing to advanced analytics and machine learning models, this book provides a comprehensive practical guide for marketers.
Marketing Analytics : A Practical Guide to Improving Consumer Insights Using Data Techniques
Simplifies intimidating data, segmentation and predictive analytics tools for everyday use in business, using real-world marketing problems to apply to a range of practical scenarios / Provides accessibility and insightful application of techniques regardless of experience level
Marketing analytics : A machine learning approach
Gives a comprehensive overview of marketing analytics, incorporating machine learning methods of data analysis that automates analytical model building. The volume covers the important aspects of marketing analytics, including segmentation and targeting analysis, statistics for marketing, marketing metrics, consumer buying behavior, neuromarketing techniques for consumer analytics, new product development, forecasting sales and price, web and social media analytics, and much more.
Managing Distributed Cloud Applications and Infrastructure : A Self-Optimising Approach
The emergence of the Internet of Things (IoT), combined with greater heterogeneity not only online in cloud computing architectures but across the cloud-to-edge continuum, is introducing new challenges for managing applications and infrastructure across this continuum.
Machine Learning Techniques and Analytics for Cloud Security
covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions
Machine Learning Approaches in Cyber Security Analytics
Introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.
Machine learning approach for cloud data analytics in IoT
Covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications. Elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
Machine learning and deep learning in medical data analytics and healthcare applications
Introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.
Machine learning and data mining for sports analytics ; 7th international workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings
Constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.
Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Machine Learning and Big Data Analytics Paradigms : Analysis, Applications and Challenges
Intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.
Machine Intelligence and Big Data Analytics for Cybersecurity Applications
Presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today’s IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field.
