Learning Analytics: Fundaments, Applications, and Trends: A View of the Current State of the Art to Enhance E-Learning, Peсa-Ayala Alejandro
Автор: Tian Ding; Deog-Hwan Oh; Donghong Liu Название: Electrolyzed Water in Food: Fundamentals and Applications ISBN: 981133806X ISBN-13(EAN): 9789811338069 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides fundamentals, highlights recent developments and offers new perspectives relating to the use of electrolyzed water (EW) as an emerging user- and environmental-friendly broad-spectrum sanitizer, with particular focus on the food industry. It addresses the generation, inactivation, pesticide degradation and safety of food by EW, illustrates the mechanism of the germicidal action of EW and its antimicrobial efficacy against a variety of microorganisms in suspensions. In addition, the sanitizing effects of combining EW with various chemical and physical sanitizing technologies have been evaluated, and recent developments and applications of EW in various areas including fruits and vegetables, meat, aquatic products, environment sterilization, livestock and agriculture has been described.
The book can be a go-to reference book of EW for: (1) Researchers who need to understand the role of various parameters in its generation, the bactericidal mecha
nism of EW and its wide applications for further research and development; (2) Equipment producers who need comprehensive understanding of various factors (e.g. type of electrolyte, flow rates of water and electrolyte) which govern the efficacy of EW and developing its generators; (3) Food processors who need good understanding of EW in order to implement it in the operations and supervisors who need to balance the advantages and limitations of EW and ensuring its safe use.
This book constitutes the refereed post-conference proceedings of the 6th International Symposium on Computational Modeling of Objects Presented in Images, CompIMAGE 2018, held in Cracow, Poland, in
July 2018.
The 16 revised full papers presented in this book were carefully reviewed and selected from 30 submissions. The papers cover the following topics: digital geometry; digital tomography; and methods and applications.
Описание: This book introduces a range of image color feature extraction techniques. In addition, the book can be used as an introduction to image color feature techniques for those who are new to the research field and software.
Автор: Bouarara Hadj Ahmed Название: Advanced Deep Learning Applications in Big Data Analytics ISBN: 1799827925 ISBN-13(EAN): 9781799827924 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 23199.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Explores architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is designed for engineers, data analysts, data scientists, IT specialists, marketers, researchers, academics, and students.
Автор: Alejandro Pe?a-Ayala Название: Learning Analytics: Fundaments, Applications, and Trends ISBN: 3319529765 ISBN-13(EAN): 9783319529769 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Learning Analytics in Higher Education.- A Literature Review.- Teaching and Learning Analytics to support Teacher Inquiry: A Systematic Literature Review.- A Landscape of Learning Analytics: An Exercise to Highlight the Nature of an Emergent Field.-A Review of Recent Advances in Adaptive Assessment.- Data-driven Personalization of Student Learning Support in Higher Education.- Overcoming the MOOC data deluge with learning analytic dashboards.- A Priori Knowledge in Learning Analytics.- Knowledge Discovery from the Programme for International Student Assessment.- A Learning Analytics Approach for Job Scheduling on Cloud Servers
Автор: Alejandro Pe?a-Ayala Название: Metacognition: Fundaments, Applications, and Trends ISBN: 3319110616 ISBN-13(EAN): 9783319110615 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: (3) introduces a conceptual model to describe the metacognitive activity as an autopoietic system.* Framework: offers three works concerned with: (4) stimulate metacognitive skills and self-regulatory functions; (12) metacognitive knowledge and metacognitive experiences are essential for teaching practices.
Автор: Mathar Rudolf, Alirezaei Gholamreza, Balda Emilio Название: Fundamentals of Data Analytics: With a View to Machine Learning ISBN: 303056830X ISBN-13(EAN): 9783030568306 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces the basic methodologies for successful data analytics. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.
Based on scientific understanding and empirical evidence of how humans understand and interact with robotic and autonomous systems, the author reviews the concerns that have been raised around the deployment of AI and robots in human society, and the potential for disruption. He explains why transparency ought to be a fundamental design consideration for Human Computer Interaction (HCI) and artificial intelligent systems. Starting with a survey of global research in the field and what transparency means in a wider context of trust, control and ethics, the author then introduces transparent robot control architecture, and the impact of transparency using real-time displays. He presents a case study on the Muttering Robot, and covers current and upcoming standards for transparency, as well as future perspectives for the manufacturing and operation of autonomous robotic systems.
Specifically, chapters cover transparency in the wider context of trust; a transparent robot control architecture, the impact of transparency using real-time displays, transparency using audio - the Muttering Robot, the effects of appearance on transparency, synthesis and further work, and several examples of Instinct commands.
This book provides key insights into transparency in robots and autonomous systems for industry and academic researchers and engineers working on intelligent autonomous system design, human robot interaction, AI, and machine ethics. It also offers points of interest for professionals developing governmental or organisational policies and standards for the design of intelligent autonomous and AI systems, and government and standard bodies working in the emerging applications of AI.
Автор: Kaizhu Huang; Amir Hussain; Qiu-Feng Wang; Rui Zha Название: Deep Learning: Fundamentals, Theory and Applications ISBN: 3030060721 ISBN-13(EAN): 9783030060725 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field. This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in studying or exploring the potential of exploiting deep learning algorithms. It will also be of special interest to researchers in the area of AI, pattern recognition, machine learning and related areas, alongside engineers interested in applying deep learning models in existing or new practical applications.
Описание: This book provides a comprehensive analysis of Brooks-Iyengar Distributed Sensing Algorithm, which brings together the power of Byzantine Agreement and sensor fusion in building a fault-tolerant distributed sensor network.
Описание: This book gathers the proceedings of the 8th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2020), held at NIT Surathkal, Karnataka, India, on 4-5 January 2020.
As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.
Here are just a dozen of the many questions answered within these pages:
What does quantitative analysis of a system really mean?
What is a system?
What are big data and analystics?
How do you know your numbers are good?
What will the future data science environment look like?
How do you determine data provenance?
How do you gather and process information, and then organize, store, and synthesize it?
How does an organization implement data analytics?
Do you really need to think like a Chief Information Officer?
What is the best way to protect data?
What makes a good dashboard?
What is the relationship between eating ice cream and getting attacked by a shark?
The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).
Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.
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