Download or read book Big Data Algorithms and Food Safety written by Salvatore Sapienza and published by Springer Nature. This book was released on 2022-10-20 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book identifies the principles that should be applied when processing Big Data in the context of food safety risk assessments. Food safety is a critical goal in the protection of individuals’ right to health and the flourishing of the food and feed market. Big Data is fostering new applications capable of enhancing the accuracy of food safety risk assessments. An extraordinary amount of information is analysed to detect the existence or predict the likelihood of future risks, also by means of machine learning algorithms. Big Data and novel analysis techniques are topics of growing interest for food safety agencies, including the European Food Safety Authority (EFSA). This wealth of information brings with it both opportunities and risks concerning the extraction of meaningful inferences from data. However, conflicting interests and tensions among the parties involved are hindering efforts to find shared methods for steering the processing of Big Data in a sound, transparent and trustworthy way. While consumers call for more transparency, food business operators tend to be reluctant to share informational assets. This has resulted in a considerable lack of trust in the EU food safety system. A recent legislative reform, supported by new legal cases, aims to restore confidence in the risk analysis system by reshaping the meaning of data ownership in this domain. While this regulatory approach is being established, breakthrough analytics techniques are encouraging thinking about the next steps in managing food safety data in the age of machine learning. The book focuses on two core topics – data ownership and data governance – by evaluating how the regulatory framework addresses the challenges raised by Big Data and its analysis in an applied, significant, and overlooked domain. To do so, it adopts an interdisciplinary approach that considers both the technological advances and the policy tools adopted in the European Union, while also assuming an ethical perspective when exploring potential solutions. The conclusion puts forward a proposal: an ethical blueprint for identifying the principles – Security, Accountability, Fairness, Explainability, Transparency and Privacy – to be observed when processing Big Data for food safety purposes, including by means of machine learning. Possible implementations are then discussed, also in connection with two recent legislative proposals, namely the Data Governance Act and the Artificial Intelligence Act.

Download or read book Harnessing Big Data in Food Safety written by Jeffrey Farber and published by Springer Nature. This book was released on 2022-11-23 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data technologies have the potential to revolutionize the agriculture sector, in particular food safety and quality practices. This book is designed to provide a foundational understanding of various applications of Big Data in Food Safety. Big Data requires the use of sophisticated approaches for cleaning, processing and extracting useful information to improve decision-making. The contributed volume reviews some of these approaches and algorithms in the context of real-world food safety studies. Food safety and quality related data are being generated in large volumes and from a variety of sources such as farms, processors, retailers, government organizations, and other industries. The editors have included examples of how big data can be used in the fields of bacteriology, virology and mycology to improve food safety. Additional chapters detail how the big data sources are aggregated and used in food safety and quality areas such as food spoilage and quality deterioration along the supply chain, food supply chain traceability, as well as policy and regulations. The volume also contains solutions to address standardization, data interoperability, and other data governance and data related technical challenges. Furthermore, this volume discusses how the application of machine-learning has successfully improved the speed and/or accuracy of many processes in the food supply chain, and also discusses some of the inherent challenges. Included in this volume as well is a practical example of the digital transformation that happened in Dubai, with a particular emphasis on how data is enabling better decision-making in food safety. To complete this volume, researchers discuss how although big data is and will continue to be a major disruptor in the area of food safety, it also raises some important questions with regards to issues such as security/privacy, data control and data governance, all of which must be carefully considered by governments and law makers.

Download or read book Algorithms For Big Data written by Moran Feldman and published by World Scientific. This book was released on 2020-07-13 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique volume is an introduction for computer scientists, including a formal study of theoretical algorithms for Big Data applications, which allows them to work on such algorithms in the future. It also serves as a useful reference guide for the general computer science population, providing a comprehensive overview of the fascinating world of such algorithms.To achieve these goals, the algorithmic results presented have been carefully chosen so that they demonstrate the important techniques and tools used in Big Data algorithms, and yet do not require tedious calculations or a very deep mathematical background.

Download or read book Machine Learning and Big Data written by Uma N. Dulhare and published by John Wiley & Sons. This book was released on 2020-09-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.

Download or read book Advances in Artificial Intelligence Big Data and Algorithms written by G. Grigoras and published by IOS Press. This book was released on 2023-12-19 with total page 1224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computers and automation have revolutionized the lives of most people in the last two decades, and terminology such as algorithms, big data and artificial intelligence have become part of our everyday discourse. This book presents the proceedings of CAIBDA 2023, the 3rd International Conference on Artificial Intelligence, Big Data and Algorithms, held from 16 - 18 June 2023 as a hybrid conference in Zhengzhou, China. The conference provided a platform for some 200 participants to discuss the theoretical and computational aspects of research in artificial intelligence, big data and algorithms, reviewing the present status and future perspectives of the field. A total of 362 submissions were received for the conference, of which 148 were accepted following a thorough double-blind peer review. Topics covered at the conference included artificial intelligence tools and applications; intelligent estimation and classification; representation formats for multimedia big data; high-performance computing; and mathematical and computer modeling, among others. The book provides a comprehensive overview of this fascinating field, exploring future scenarios and highlighting areas where new ideas have emerged over recent years. It will be of interest to all those whose work involves artificial intelligence, big data and algorithms.

Download or read book Artificial Intelligence for Big Data written by Anand Deshpande and published by Packt Publishing Ltd. This book was released on 2018-05-22 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.

Download or read book Building the Future of Food Safety Technology written by Darin Detwiler and published by Academic Press. This book was released on 2020-06-16 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building the Future of Food Safety Technology: Blockchain and Beyond focuses on evaluating, developing, testing and predicting Blockchain's impact on the food industry, the types of regulatory compliance needed, and other topics important pertaining to consumers. Blockchain is a technology that can be used to record transactions from multiple entities across a complex network. A record on a blockchain cannot be altered retroactively without the alteration of all preceding blocks and the consensus of the network. Blockchain is often associated with cryptocurrency, but it is being looked at more and more as a solution to food-supply problems. - Presents the latest information on Blockchain's impact in the food industry - Bridges food technology and food safety - Provides guidance and expert insights on the food supply chain

Download or read book Big Data Analytics for Sustainable Computing written by Haldorai, Anandakumar and published by IGI Global. This book was released on 2019-09-20 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.

Download or read book Data Science Algorithms in a Week written by Dávid Natingga and published by Packt Publishing Ltd. This book was released on 2018-10-31 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a strong foundation of machine learning algorithms in 7 days Key FeaturesUse Python and its wide array of machine learning libraries to build predictive models Learn the basics of the 7 most widely used machine learning algorithms within a weekKnow when and where to apply data science algorithms using this guideBook Description Machine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data. To address the complex nature of various real-world data problems, specialized machine learning algorithms have been developed. Through algorithmic and statistical analysis, these models can be leveraged to gain new knowledge from existing data as well. Data Science Algorithms in a Week addresses all problems related to accurate and efficient data classification and prediction. Over the course of seven days, you will be introduced to seven algorithms, along with exercises that will help you understand different aspects of machine learning. You will see how to pre-cluster your data to optimize and classify it for large datasets. This book also guides you in predicting data based on existing trends in your dataset. This book covers algorithms such as k-nearest neighbors, Naive Bayes, decision trees, random forest, k-means, regression, and time-series analysis. By the end of this book, you will understand how to choose machine learning algorithms for clustering, classification, and regression and know which is best suited for your problem What you will learnUnderstand how to identify a data science problem correctlyImplement well-known machine learning algorithms efficiently using PythonClassify your datasets using Naive Bayes, decision trees, and random forest with accuracyDevise an appropriate prediction solution using regressionWork with time series data to identify relevant data events and trendsCluster your data using the k-means algorithmWho this book is for This book is for aspiring data science professionals who are familiar with Python and have a little background in statistics. You’ll also find this book useful if you’re currently working with data science algorithms in some capacity and want to expand your skill set

Download or read book Data Intensive Computing Applications for Big Data written by M. Mittal and published by IOS Press. This book was released on 2018-01-31 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.

Download or read book Early warning tools and systems for emerging issues in food safety Technical background written by Food and Agriculture Organization of the United Nations and published by Food & Agriculture Org.. This book was released on 2023-12-28 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early warning (EW) systems have a critical role in the reduction of risks from various hazards. The capability and capacity to identify early signals and emerging food safety risks, and to provide on-time EW that would allow for the mitigation of related upcoming risks have therefore become vital for national and international authorities and organizations dealing with food safety. The developments in early warning systems show a shift from reactive towards proactive systems. With the rapid development of modern systems fed by numerous, real-time and diverse data, as well as the advancements achieved in artificial intelligence and machine learning techniques, increasingly tested and validated digital methods and models have become available for food safety early warning and analysis. This technical background report enhances the awareness of the available evidence-based innovative digital tools and provides technical background information to support their use for proactive food safety early warning.

Download or read book State of Threat written by Wil Hoverd and published by Massey University Press. This book was released on 2023-11-16 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasing US&– China tensions, Russia' s invasion of Ukraine, disruptions to supply chains and maritime trade, right-wing extremism, gangs and the drug trade . . . The international and domestic security environment is dynamic and fraught. In State of Threat, local and international academics and sector experts discuss the issues facing New Zealand across defence, diplomacy, intelligence, policy, trade and border management.This timely and up-to-date analysis of New Zealand' s most important security issues is a must-read for policy analysts, those working in risk management and industry leaders across all sectors of the economy.

Download or read book Data Science in the Medical Field written by Seifedine Kadry and published by Elsevier. This book was released on 2024-09-30 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: ata science has the potential to influence and improve fundamental services such as the healthcare sector. This book recognizes this fact by analyzing the potential uses of data science in healthcare. Every human body produces 2 TB of data each day. This information covers brain activity, stress level, heart rate, blood sugar level, and many other things. More sophisticated technology, such as data science, allows clinicians and researchers to handle such a massive volume of data to track the health of patients. The book focuses on the potential and the tools of data science to identify the signs of illness at an extremely early stage. • Shows how improving automated analytical techniques can be used to generate new information from data for healthcare applications• Combines a number of related fields, with a particular emphasis on machine learning, big data analytics, statistics, pattern recognition, computer vision, and semantic web technologies• Provides information on the cutting-edge data science tools required to accelerate innovation for healthcare organizations and patients by reading this book

Download or read book Intelligent Computing and Communication written by M. Seetha and published by Springer Nature. This book was released on 2023-09-19 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features a collection of high-quality, peer-reviewed papers presented at the Sixth International Conference on Intelligent Computing and Communication (ICICC 2022) organized by Department of Computer Science and Engineering, G. Narayanamma Institute of Technology and Science (for women) Autonomous, Hyderabad, India, on November 18–19, 2022. It focuses on innovation paradigms in system knowledge, intelligence, and sustainability that can be applied to provide practical solutions to a number of problems in society, the environment, and industry. Further, the book also addresses the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology, and healthcare.

Download or read book Biosensing and Micro Nano Devices written by Pranjal Chandra and published by Springer Nature. This book was released on 2022-07-03 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews applications of nanomaterial and nanodevices in the food industry. It also discusses the advanced bioanalytical techniques, including Enzyme-Linked Immunosorbent Assay (ELISA), immunoanalytical techniques, and monoclonal antibody-based immunological techniques for detecting food adulterations and allergens. It comprehensively covers electrode modification and nano-engineered fabrication of biosensors to enhance their functionalities for utilization in food industries. The book highlights the utilization of nanobiosensors for food safety and quality analysis, such as detection of toxin, food-borne pathogen, allergen, evaluation of toxicity etc. Further, it also summarizes the recent advances in nanodevices such as nano-systems, nano-emulsions, nanopesticides, and nanocapsules and their applications in the food industry. Lastly, it covers nanomaterial-based sensors for drug analysis in diverse matrices. It serves as an invaluable source of information for professionals, researchers, academicians, and students related to food science and technology.

Download or read book Food Safety Management written by Veslemøy Andersen and published by Academic Press. This book was released on 2023-03-28 with total page 1160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Food Safety Management: A Practical Guide for the Food Industry, Second Edition continues to present a comprehensive, integrated and practical approach to the management of food safety throughout the production chain. While many books address specific aspects of food safety, no other book guides you through the various risks associated with each sector of the production process or alerts you to the measures needed to mitigate those risks. This new edition provides practical examples of incidents and their root causes, highlighting pitfalls in food safety management and providing key insights into different means for avoiding them. Each section addresses its subject in terms of relevance and application to food safety and, where applicable, spoilage. The book covers all types of risks (e.g., microbial, chemical, physical) associated with each step of the food chain, making it an ideal resource. - Addresses risks and controls at various stages of the food supply chain based on food type, including a generic HACCP study and new information on FSMA - Covers the latest emerging technologies for ensuring food safety - Includes observations on what works and what doesn't on issues in food safety management - Provides practical guidelines for the implementation of elements of the food safety assurance system - Explains the role of different stakeholders of the food supply

Download or read book AI in Food Industry for Food Products Quality Inspection written by Dr Syeda Sumera Ali and published by Blue Rose Publishers. This book was released on 2022-05-24 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) is a branch of science & engineering that deals with machine learning (ML) and Deep Learning (DL) are the commonly used algorithms in the field of Artificial Intelligence namely. Models learn from data available and used by customers, government agencies & companies for sake of analysis. In food industries, the design of standard reliable procedures to inspect & control the quality of products is a major objective. The deployment of AI to achieve better customer experience, supply chain, management, improve operational efficiency, reduction in material movements , vehicle activity, and better results in the business . Automation in the food industry for sake of control a process at optimum level, reducing costs & time, monitor food processing, minimize the error, respond to production issues, safety, tracking & improving quality . AI has various applications includes sorting fresh produce, effective cleaning, consumer preference, saving time and resources.