Big Data - Science topic

The book aims at presenting a multidisciplinary view meant to illustrate several significant efforts and results about the contribution of information technologies to make available new resources and enable rationally usage the existing ones in the context of the ever-growing trends to use ever more resources. Authors from various countries have be...

The chapter delves into the intricate interplay between open innovation, sustainability, and digital transformation within the contemporary business landscape. By exploring the principles that integrate open innovation with digital advancements, the chapter aims to elucidate how this fusion propels sustainable business growth and nurtures resilient...

The first edition of this book was published in 2018 with the aim of providing holistic and comprehensive material on the Internet of Things (IoT). The book has become a reference for various researchers and professional ICT practitioners. Some universities around the world, including those in Europe and North America, are also using this book as c...

This chapter examines how emerging technologies are transforming modern business operations. It focuses on how big data analytics, the Internet of Things (IoT), artificial intelligence (AI), and blockchain all work together to boost innovation, efficiency, and decision-making. The chapter demonstrates the advantages and disadvantages of technologic...

In this research, a combination of inspection and repeated deferred sampling is suggested utilizing the process capability index Cpk. This sampling approach can effectively evaluate the quality characteristics of normal distributions even when the mean and variance are unknown. Symmetrical and asymmetrical regions failing to meet optimal conditions...

Liver diseases rank among the most prevalent health issues globally, causing significant morbidity and mortality. Early detection of liver diseases allows for timely intervention, which can prevent the progression of such disease to more severe stages such as cirrhosis or liver cancer. To this end, many machine learning models have been previously...

Decision-making in medical diagnosis is often hampered by uncertainties due to incomplete, ambiguous, and evolving information. In reviewing the traditional methods for lung cancer detection, we found that crisp and logic values have more difficulties and challenges. These challenges related to the big data analytics, uncertainty values, and the...

Businesses have faced a variety of difficulties as a result of the global pandemic, and how they responded to this disruption has affected both their resilience and their ability to get through this crisis. Digital technologies have played a crucial role in addressing these issues and fostering resilience. It is, therefore, imperative to explore op...

Big Data Analytics are said to help in transforming huge amounts of raw data towards valuable information that can be used, but there are formidable challenges in feature selection and classification due to the complexity and high dimensionality of the data. Traditional methods are usually too weak to handle the built-in uncertainty, imprecision, a...

The main terrestrial carbon (C) fraction is soil organic carbon (SOC), which has a considerable effect on climate change and greenhouse gas emissions through the absorption and sequestration of carbon dioxide (CO 2). This has made SOC assessment very important from both economic and environmental viewpoints. The growing count of soil spectral libra...

This article presents a state-of-the-art review of machine learning (ML) methods and applications used in smart grids to predict and optimise energy management. The article discusses the challenges facing smart grids, and how ML can help address them, using a new taxonomy to categorise ML models by method and domain. It describes the different ML t...

In the last ten years, the integration of big data and artificial intelligence (AI) has introduced innovative smart technologies within the building and construction sectors. AI is increasingly being applied to fire detection, risk evaluation, and fire prediction. This chapter outlines a roadmap for incorporating AI into building fire safety engine...

p class="Abstract">Internet of things (IoT) systems have experienced significant growth in data traffic, resulting in security and real-time processing issues. Intrusion detection systems (IDS) are currently an indispensable tool for self-protection against various attacks. However, IoT systems face serious challenges due to the functional diversit...

The rapid growth of big data analytics has heightened concerns about data privacy, necessitating the development of advanced privacy-preserving techniques. This research addresses the challenge of optimizing privacy-preserving data mining (PPDM) for big data analytics through the innovative application of deep reinforcement learning (DRL). We propo...

The intensification of global heat wave events is seriously affecting residents' emotional health. Based on social media big data, our research explored the spatial pattern of residents' sentiments during heat waves (SDHW). Besides, their association with urban functional areas (UFAs) was analyzed using the Apriori algorithm of association rule min...

The challenge issue of Big data in security point of view to protect data against malicious users. Big data contains huge amounts of personal identifiable information stored data. The breaches affecting big data can have devastating consequences than potential affect. Large number of people are with consequences not only from reputational point of...

This work mines big data in Sentinel-1 satellite images to unveil geographical patterns in offshore wind energy. We leverage unsupervised machine learning to extract insights from a 44GB open access dataset for decision support in wind farm orientations to guide stakeholders. It has broader impacts of overcoming climate change by enhancing renewabl...

With the booming of Big Data and the Internet of Things, various urban networks have been built based on intercity flow data, and how to combine them to learn a more comprehensive understanding of mega-city regions is becoming more and more indispensable. In this paper, we designed a graph-based multi-view clustering method based on graph learning...

Big data systems are essential for many businesses to grow, leveraging the vast amounts of data they generate and access. However, big data systems are plagued by significant sustainability challenges. Thus, this study aims to identify metrics that can measure the sustainability of big data systems. This research conducted a comprehensive literatur...

The fraudulent claims for Unemployment Insurance (UI) have also risen massively in the United States especially during the onset of COVID-19 pandemic with billions of dollars that were lost. These approaches applied formerly in fraud detection and prevention have been challenged by new and advanced fraud systems. For this reason, AI, Big Data and P...

China’s economic growth is increasingly being driven by the contemporary service industry in the context of a new economy. This study aims to examine the spatial heterogeneous relationship between various service industry activities and street network design configurations by integrating multisource big data and geospatial analysis to provide insig...

The banking sector has undergone significant transformation with the advent of technology, changing how assets are created, managed, and utilized. This research paper explores the evolving role of technology in creating banking assets. It examines the impact of various technological innovations, such as digital banking, fintech solutions, artificia...

In the evolving business landscape, accounting is increasingly recognized not only as a tool for financial management but also as a cornerstone for fostering interdisciplinary organizational and human development. Traditional accounting practices, while vital for financial reporting and compliance, often lack the flexibility to address the multifac...

Every few years, inexorably, a new buzzword captures the attention and imagination of top managers and eminent scholars alike, when not those of major policymakers, influential media outlets, marketing and PR professionals, and all stripes and varieties of lower cadres within public as much as corporate bureaucracies. Every few years, a fortiori, a...

The Beijing-Tianjin-Hebei integration plan rose to the status of a national-level strategy in 2014. This paper provides a deep analysis of the Beijing-Tianjin-Hebei area’s inter-city commuter big data. This research analyzed the overview of spatial structure, polycentric structure, hierarchical structure and clustering characteristics of the BTH ba...

In the contemporary business environment, the fusion of accounting practices with interdisciplinary approaches has emerged as a transformative strategy for achieving organizational growth and human development. Traditional accounting systems, while essential for financial reporting and compliance, often fall short in addressing the multifaceted cha...

Distance metric learning (DML) aims to find an appropriate way to reveal the underlying data relationship. It is critical in many machine learning, pattern recognition and data mining algorithms, and usually require large amount of label information (such as class labels or pair/triplet constraints) to achieve satisfactory performance. However, the...

The article aimed to identify the repercussions of artificial intelligence (AI) on the quality of creating media content. The research employed the qualitative analytical method, conducting semi-structured interviews with seven Jordanian journalists who work in various media institutions in Jordan. The results revealed that the fields in which AI i...

Guiding high school students toward suitable educational paths is a complex challenge, particularly influenced by academic performance. In Morocco, first-year high school students in the scientific branch face a crucial decision when selecting between science mathematics (SM), physics (SF), and Science of Life and Earth (SVT) paths. This decision i...

Artificial intelligence (AI) and machine learning (ML) are disruptive technologies nowadays. It is well known that many important organizations use them to improve their productivity and processes, and many new applications are being developed as well. In Latin America, the adoption of new technologies is slower than in other parts of the world, li...

Pre-trained large language models (PLMs) have the potential to support urban science research through content creation, information extraction, assisted programming, text classification, and other technical advances. In this research, we explored the opportunities, challenges, and prospects of PLMs in urban science research. Specifically, we discus...

Industry 4.0 represents a transformative shift in manufacturing and industrial practices, characterized by the integration of advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), big data analytics, and cyber-physical systems. This fourth industrial revolution enhances operational efficiency, flexibility, and cu...

This systematic literature review explores the implementation and impact of digital leadership in education across various global contexts, focusing on the role of educational leaders in integrating digital technologies to enhance learning and institutional transformation. Digital leadership is essential for adapting to the rapidly evolving technol...

Rapid technological advancements have intensified user-content interactions, leading to complex regulation mechanisms such as A.I. filtering and user moderation. This study conducts a bibliometric analysis of 202 publications from 2016 to 2023, sourced from the Web of Science and Scopus databases, to explore contemporary topics in content moderatio...

A agricultura de precisão (AP) pode ser compreendida como um sistema de práticas agrícolas baseadas em tecnologias de informação, mecanização e automação, que consideram a variabilidade espacial e temporal das culturas para otimizar a produtividade e reduzir impactos ambientais (MOLIN; AMARAL e COLAÇO, 2015). O ciclo da AP começa com a coleta de da...

الملخص‬ ‫شبكات‬ ‫استخدام‬ ‫وزيادة‬ ‫اإلنترنت‬ ‫سوق‬ ‫في‬ ‫الهائل‬ ‫النمو‬ ‫مع‬ ‫تعقيدا‬ ‫وأكثر‬ ‫وأكبر‬ ‫أكبر‬ ‫األخيرة‬ ‫اآلونة‬ ‫في‬ ‫البيانات‬ ‫أصبحت‬ ‫التواصل‬ ‫االجتماعية،‬ ‫الهواتف‬ ‫واستخدامات‬ ‫البيانات‬ ‫الكتساب‬ ‫االستشعار‬ ‫وأجهزة‬ ‫مثل‬ ‫تكون‬ ‫ما‬ ‫عادة‬ ‫وغيرها.‬ ‫الذكية‬ ‫هذه‬ ‫البيانات‬ ‫غير‬ ‫منسقة‬ (unstructured data) ‫الضخمة‬ ‫با...

The integration of Artificial Intelligence [AI] and Big Data into financial markets has revolutionized their dynamics, offering unprecedented opportunities and posing complex challenges. This article examines the transformative impact of AI-driven financial systems on market operations, with a focus on algorithmic trading, market efficiency, and ec...

This paper presents a new Intelligent Anti-Money Laundering Transaction Pattern Recognition System based on Graph Neural Networks (GNNs). The proposed method addresses the limitations of anti-money laundering (AML) by using graphical representation and deep learning techniques. We introduce general methods for creating financial markets that are in...

With the advancement of digital transformation in the manufacturing industry, the industrial internet has become a key technology for improving production efficiency and product quality, and achieving intelligent manufacturing. This paper takes Foxconn Technology Group as an example to explore how it has utilized the industrial internet platform BE...

Talent scouting and fitness data standardization in professional football clubs have become central topics in recent research. This review aims to consolidate advancements in technology, big data, and data analytics, examining their roles in optimizing talent identification and fitness evaluation within football clubs. A systematic search strategy...

This narrative review explores the transformative role of data science and visualization in modern chemistry. It begins by contextualizing the importance of chemistry across various domains, highlighting the emergence of data-driven approaches as catalysts for innovation and discovery. Harnessing big data in chemistry is discussed, emphasizing the...

During the last few elections that occurred in the past decade, many polls are struggling to correctly predict election results, such instances could be seen in 2016's U.S. presidential election and the Brexit referendum in UK. These wrong predictions are forcing researchers to explore more effective methods, like big data analytics, to better unde...

The prevalence of social media usage is rapidly escalating. In January 2024, India alone recorded a total of 462 million social media users. The rise in online users has led to a corresponding surge in cybersecurity frauds. Cybersecurity experts can utilize big data analytic tools to identify, prevent, and mitigate cyber assaults, as these technolo...

The advent of big data has brought about significant opportunities and valuable insights to modern organizations. However, the proliferation of governance challenges is increasing dramatically, which necessitates searching for innovative approaches for managing, securing, and complying with government and organizational policies. This study conduct...

Big data auditing has become an ability that national auditing institutions must master and improve rapidly at present.It is an inevitable choice for national auditing institutions to meet the challenges of the times,fulfill auditing functions and break through auditing bottlenecks.Against this background,this paper takes the application research o...

Digital disruption has fundamentally altered the landscape of supply chain management, presenting both challenges and opportunities for entrepreneurs. This paper examines the role of transformative technologies-such as artificial intelligence, blockchain, the Internet of Things (IoT), and big data analytics-in reshaping supply chains to enhance eff...

La transformación digital ha surgido como un impulsor esencial del cambio en la administración de empresas, permitiendo a las entidades incrementar su eficacia en las operaciones, ajustarse a un contexto global y cumplir con las expectativas de los consumidores y reguladores. No obstante, este procedimiento presenta retos importantes, tales como la...

In the era of big data and artificial intelligence (AI), optimizing data engineering practices is crucial for enhancing the efficiency and effectiveness of predictive analytics applications. This paper presents a case study focused on optimizing data engineering pipelines to support AI-driven predictive analytics. We explore strategies for improvin...

This paper explores the development of a persona-based recommendation system for enhancing tourism satisfaction in Saudi Arabia. By leveraging data analytics and machine learning, the system aims to provide tailored destination recommendations based on individual preferences. Through the use of big data, topic modeling techniques, and geolocation a...

Environmental big data and analytical models are increasingly informing conservation efforts to address global climate and biodiversity crises. Yet, the growing reliance on data‐driven approaches raises concerns regarding biases, uncertainties, and injustices in environmental decision‐making processes. This article presents ‘conservation data infra...

In recent years, traffic flow prediction technology has been transformed from statistics based parametric methods and machine learning driven non-parametric methods to big data driven deep learning methods. This paper summarizes and summarizes the existing methods and improvement measures of long and short term traffic flow prediction based on deep...

With the advancement in technology and big data in recent years, disciplinary systems present an increasing tendency towards digitization. Chinas digital Social Credit system, established to evaluate individuals, businesses, and local institutions trustworthiness, serves as a typical model. Through the lens of Michel Foucaults account of disciplina...

This paper examines the role of artificial intelligence (AI) and machine learning (ML) in enhancing threat intelligence and anomaly detection within cloud networks. As cloud environments become more complex and dynamic, traditional security methods struggle to keep pace with evolving threats. AI and ML offer a solution by automating the analysis of...

Call for papers for the Special Issue "Navigating Emerging Advancements and Challenges in AI and Big Data Technologies for Business and Society" in the SCOPUS Q2 ranked journal Data, for which I am the guest editor

Existe una considerable literatura crítica sobre las tecnologías de la información, los algoritmos, el big data y la inteligencia artificial. Ahí se enfatiza en la manera cómo tales herramientas han permitido el desarrollo de nuevas formas de poder y control sobre los individuos. No obstante, es menester también pensar las nuevas alternativas de em...

The purpose of this article is to explore the application of intelligent decision support system (DSS) in machinery manufacturing industry. Through the integration and innovation of big data processing technology, it provides efficient decision support for machinery manufacturing enterprises and promotes the intelligent transformation of the indust...

In the era of big data, the demand for efficient data retrieval in cloud databases has become increasingly critical. This paper explores AI-driven data indexing techniques designed to enhance retrieval speed and accuracy in cloud-based environments. By leveraging machine learning algorithms and advanced indexing structures, this research proposes a...

This paper provides an overview of the contribution of Health Information Technology (Health IT) to epidemiological research and public health: the Health IT Revolution in Epidemiology. From these findings, this paper critically assesses the role, opportunities, and difficulties that Health IT has made to epidemiological practices in the field. The...

This research employs multi-source data including big data, remote sensing raster data, and statistical vector data. Through the superposition of tourism activity points of interest with remotely sensed inversion raster data like human carbon emissions, net primary productivity, and kilometer-grid GDP, the carbon emissions, carbon sinks, and econom...

Turismo e inteligencia artificial. Big data. Netnografía y las Redes de hipermediación (Instagram, Facebook, etc.)

This study constructs a sales forecasting framework incorporating multi-source data based on beer category sales data from Supermarket X. The research collected beer sales data from 2020-2023, integrating temperature data, holiday information, and promotional activity data through an improved LSTM-based deep learning model. The study innovatively i...

We are surrounded by overwhelming big data, which brings substantial advances but meanwhile poses many challenges. A very large portion of big data contains geospatial information and hence geospatial big data, which is crucial for decision-making if being utilized strategically. Among others, volumes in size and high dimensions are two major chall...

The article examines the concept of intelligent supply chains in the context of the rapid development of information technologies. It describes the main characteristics of intelligent supply chains, including technology penetration, visualization and mobility functions, as well as environmental sustainability. Key elements of the integrated service...

Digital transformation has become a pivotal force in reshaping the logistics and energy sectors, driven by advancements in technology and the need to remain competitive in dynamic global markets. This review presents strategic frameworks to guide the integration of digital tools within these sectors, emphasizing the alignment of technology adoption...

Background Adolescent girls might suffer physical and psychological harm from early marriage. Meanwhile, a good education can make women more independent in making decisions for their good. The study analyzes the role of education level in early marriage among adolescents in Indonesia’s rural areas. Methods This cross-sectional study analyzed 4,36...

Spatiotemporal regression is a crucial method in geography for discerning spatiotemporal nonstationarity in geographical relationships and has found widespread application across diverse research domains. This study implements two innovative spatiotemporal intelligent regression models, i.e., Geographically Neural Network Weighted Regression (GNNWR...

Artificial intelligence (AI) and machine learning (ML) can assist in the effective development of the power system by improving reliability and resilience. The rapid advancement of AI and ML is fundamentally transforming energy management systems (EMSs) across diverse industries, including areas such as prediction, fault detection, electricity mark...

The construction industry is an important pillar industry of the national economy and one of the main industries of energy consumption. In recent years, the Internet, big data, artificial intelligence and other digital technologies have accelerated innovation, coupled with China 's strong call for ' double carbon ' policies, the transformation and...

Los procesos de turistificación de los centros urbanos han sido impulsados por políticas de regeneración y rehabilitación urbana, que han dotado a las ciudades de un enfoque de planificación y gestión neoliberal donde el turismo es uno de los motores económicos principales. Tras la crisis financiera de 2008, esta tendencia se intensificó como una e...

Information Systems (IS) are crucial to modern organizations, acting as the backbone for managing operations, decision-making, and achieving competitive advantages. These systems combine technology, people, and processes to collect, process, store, and distribute information. The core components of IS include hardware, software, data, people, and p...

Over the past more than ten years, big data technology has posed profound impacts to almost all sectors including education. This state-of-the-art technology prompts changes in educational notions, pedagogy, and the roles of teachers and students. Educational big data proliferates with the improvement of school digital infrastructure, popularizatio...

Parallelization has become a cornerstone technique for optimizing computing performance, especially in addressing the growing complexity and scale of modern computational tasks. By leveraging concurrent processing capabilities of multi-core processors, GPUs, and distributed systems, parallel computing enables the efficient execution of large-scale...

Dynamic graph data learning is an important data analysis technique. In the age of big data, the volume of data produced daily is immense, the data types are varied, the value density is low, and the data continues to accumulate over time. These characteristics make data processing more challenging. In particular, unstructured data, unlike structur...

GEOGRAPHIC INFORMATION SYSTEM (GIS) PROMOTES SMART URBAN DEVELOPMENT IN HO CHI MINH CITY-ADVANTAGES AND BARRIERS ABSTRACT Smart cities are understood as cities that apply the Internet of Things (IoT), big data and artificial intelligence (AI) to effectively manage social problems and towards sustainable development. Geographic information system (G...

Reproducing color–magnitude diagrams (CMDs) of star-resolved galaxies is one of the most precise methods for measuring the star formation history (SFH) of nearby galaxies back to the earliest time. The upcoming big data era poses challenges to the traditional numerical technique in its capacity to deal with vast amounts of data, which motivates us...

In the era of big data, technology is a catalyst for change in teaching modalities. Although the notion of precision teaching is not new to the education world, its application has faced a variety of constraints due to technical issues. The advent of big data technology and the proliferation of educational data are vital factors in diminishing thes...

Data analytics in the medical field has evolved significantly, transforming healthcare delivery and decision-making. Early efforts in the 20th century involved manual data collection and statistical analysis to understand disease patterns and public health trends. In the mid-1900s, the development of computing systems enabled hospitals and research...