Big Data and Artificial Intelligence in Digital Finance

This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance

Big Data and Artificial Intelligence in Digital Finance

This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance

IDEAS-1997-2021-Final-Programs

This document records the final program for each of the 26 meetings of the International Database and Engineering Application Symposium from 1997 through 2021. These meetings were organized in various locations on three continents. Most of the papers published during these years are in the digital libraries of IEEE(1997-2007) or ACM(2008-2021)

Pacific Symposium on Biocomputing 2023

The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Surgical Management of Gastroesophageal Reflux in Children: Risk Stratification and Prediction of Outcomes

Introduction: Since the 1980s fundoplication, an operation developed for adults with hiatus hernia and reflux symptoms, has been performed in children with gastroesophageal reflux disease (GORD). When compared to adult outcomes, paediatric fundoplication has resulted in higher failure and revision rates. In the first chapter we explore differences in paradigm, patient population and outcomes. Firstly, symptoms are poorly defined and are measured by instruments of varying quality. Secondly, neurological impairment (NI), prematurity and congenital anomalies (oesophageal atresia, congenital diaphragmatic hernia) are prevalent in children. / Purpose: To develop methods for stratifying paediatric fundoplication risk and predicting outcomes based on symptom profile, demographic factors, congenital and medical history. / Methods: Study objectives are addressed in three opera: a symptom questionnaire development (TARDIS:REFLUX), a randomised controlled trial (RCT) and a retrospective database study (RDS). TARDIS: REFLUX: In the second chapter, digital research methods are used to design and validate a symptom questionnaire for paediatric GORD. The questionnaire is a market-viable smartphone app hosted on a commercial platform and trialed in a clinical pilot study. / RCT: In the third chapter, the REMOS trial is reported. The trial addresses the subset of children with NI and feeding difficulties. Participants are randomized to gastrostomy with or without fundoplication. Notably, pre- and post-operative reflux is quantified using pH-impedance. / RDS: In the fourth chapter, data mining and machine learning strategies are applied to a retrospective paediatric GORD database. Predictive modelling techniques applied include logistic regression, decision trees, random forests and market basket analysis. / Results and conclusion: This work makes two key contributions. Firstly, an effective methodology for development of digital research tools is presented here. Secondly, a synthesis is made of literature, the randomised controlled trial and retrospective database modelling. The resulting product is an evidence-based algorithm for the surgical management of children with GORD

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Scanning the European Ecosystem of Distributed Ledger Technologies for Social and Public Good: What, Why, Where, How, and Ways to Move Forward

Distributed Ledger Technologies (DLTs), such as blockchains, are primarily tamper-resistant and time-stamped databases. They allow multiple parties to record, verify and share data on a peer-to-peer basis across a network, in decentralised, synchronised and transparent ways, with limited human intervention and reduced intermediate steps. These technologies are mostly known for business use cases, from cryptocurrencies to asset track and tracing. But there are numerous organisations nowadays searching for alternative ways to harness the potential of DLTs in the pursuit of public and social good, from local to global challenges, and towards more inclusive, cooperative, sustainable, ethical or accountable digital and physical worlds. This Science for Policy report explores the current status of this particular field both theoretically and empirically, in the framework of the project #DLT4Good: Co-creating a European Ecosystem of DLTs for Social and Public Good. Part I offers a conceptual overview of the connections between main features of DLTs and their potential for social and public good goals. Emphasis is placed on different approaches to decentralisation, and on core building blocks of DLTs linked with values such as trust, privacy, self-sovereignty, autonomy, inclusiveness, transparency, openness, or the commons. Part II comprises a scanning of the current European ecosystem of DLT projects with activities in this field. It contains a summarized version of a database published online with 131 projects, and a quantitative review of main trends. It also includes a qualitative assessment of 10 projects selected from the larger sample to showcase this field and its diversity. Part III concludes with six independent position papers and recommendations from experts and advisors of the #DLT4Good project. The main topics addressed range from decentralized governance to collaborative economies, with highlights on issues such as trust, verifiability, transparency, privacy or bottom-up coordination.JRC.I.2-Foresight, Modelling, Behavioural Insights & Design for Polic