Intelligent learning applied to multidimensional data streams has established itself as a rapidly expanding field, driven by the growth of ubiquitous computing and the Internet of Things. The complexity of these streams, characterized by their high d...
Data growth in today’s world is exponential, many applications generate huge amount of data streams at very high speed such as smart grids, sensor networks, video surveillance, financial systems, medical science data, web click streams, network...
In the last few decades, vehicles are equipped with a plethora of sensors which can provide useful measurements and diagnostics for both the vehicle’s condition as well as the driver’s behaviour. Furthermore, the rapid increase for transportation nee...
Drainage network analysis includes several operations that quantify the topological organization of stream networks. Network analysis operations are frequently performed on streams that are derived from digital elevation models (DEMs). While these me...
Continuous data stream analysis primarily focuses on the unanticipated changes in the transmission of data distribution over time. Conceptual change is defined as the signal distribution changes over the transmission of continuous data streams. A dri...
In recent years, the application and wide adoption of Internet of Things (IoT)-based technologies have increased the proliferation of monitoring systems, which has consequently exponentially increased the amounts of heterogeneous data generated. Proc...
The real-time analysis of Big Data streams is a terrific resource for transforming data into value. For this, Big Data technologies for smart processing of massive data streams are available, but the facilities they offer are often too raw to be effe...
Nowadays, ubiquitous technology makes life easier, especially devices that use the internet (IoT). IoT devices have been used to generate data in various domains, including healthcare, industry, and education. However, there are often problems with t...
Streaming data sequences arise from various areas in the era of big data, and it is challenging to explore efficient online models that adapt to them. To address the potential heterogeneity, we introduce a new online estimation procedure to analyze t...
With the continuous enrichment of big data technology application scenarios, the clustering analysis of a data stream has become a research hotspot. However, the existing data stream clustering algorithms usually have some defects, such as inability...
Conducted within the scope of geochemical exploration in eastern Thailand, this study aims to detect geochemical anomalies and potential mineral deposits. The objective was to interpret intricate spatial dispersion patterns and concentration levels o...
Using different statistical analysis methods to examine hydrologic time-series data is the basis of accurate hydrologic status analysis. With the wide application of the Internet of Things and sensor technologies, traditional statistical analysis met...
The functional linear model
In the present case study, the use of an advanced, efficient and low-cost technique for monitoring an urban stream was reported. Physicochemical parameters (PcPs) of Jungnangcheon stream (Seoul, South Korea) were assessed using an Internet of Things...
The journal retracts the article “Continual Learning Approach for Continuous Data Stream Analysis in Dynamic Environments” [...]
One of the most challenging tasks for network operators is implementing accurate per-packet monitoring, looking for signs of performance degradation, security threats, and so on. Upon critical event detection, corrective actions must be taken to keep...
In the current paper, we propose a machine learning forecasting model for the accurate prediction of qualitative weather information on winter precipitation types, utilized in Apache Spark Streaming distributed framework. The proposed model receives...
This study presents the first stream-sediment geochemical survey conducted in the western Oecusse enclave (Timor-Leste), aiming to identify geochemical anomalies associated with potential metallic mineralization in a region where mineral occurrences...
The large amount of programmable logic controller (PLC) sensing data has rapidly increased in the manufacturing environment. Therefore, a large data store is necessary for Big Data platforms. In this paper, we propose a Hadoop ecosystem for the suppo...
Future-oriented networking infrastructures are characterized by highly dynamic Streaming Data (SD) whose volume, speed and number of dimensions increased significantly over the past couple of years, energized by trends such as Software-Defined Networ...
Large numbers of job postings with complex content can be found on the Internet at present. Therefore, analysis through natural language processing and machine learning techniques plays an important role in the evaluation of job postings. In this stu...
The pervasive and increasing deployment of smart meters allows collecting a huge amount of fine-grained energy data in different urban scenarios. The analysis of such data is challenging and opening up a variety of interesting and new research issues...
In mobile networks, crowdsourcing in Quality of Experience (QoE) assessment phase involves collecting data from the user terminals or dedicated collection devices. A mobile operator or a research group may provide applications that can be run in diff...
In smart buildings, many different systems work in coordination to accomplish their tasks. In this process, the sensors associated with these systems collect large amounts of data generated in a streaming fashion, which is prone to concept drift. Suc...
Continuous water temperature data are important for understanding historical variability and trends of river thermal regime, as well as impacts of warming climate on aquatic ecosystem health. We describe a reconstructed daily water temperature datase...
Streaming feature selection has always been an excellent method for selecting the relevant subset of features from high-dimensional data and overcoming learning complexity. However, little attention is paid to online feature selection through the Mar...
In the last decade, technological advancements in the cyber-physical system have set the basis for real-time and context-aware services to ease human lives. The citizens, especially travelers, want to experience a safe, healthy, and timely journey to...
This article develops a method for detecting malware based on the multi-scale recurrent architecture (time-aware multi-scale LSTM) with salience gating, multi-headed attention, and a sequential statistical change detector (CUSUM) integration. The res...
Autonomous vehicles (AVs) rely heavily on multi-modal sensors to perceive their surroundings and make real-time decisions. However, the increasing complexity of these sensors, combined with the computational demands of AI models and the challenges of...
Scalable real-time processing of large amounts of data has become a research topic of particular importance due to the continuously rising amount of data that is generated by devices equipped with sensing components. While existing approaches allow f...
Due to the rise of continuous data-generating applications, analyzing data streams has gained increasing attention over the past decades. A core research area in stream data is stream classification, which categorizes or detects data points within an...
Smartphones with the Android operating system can acquire Global Navigation Satellite System (GNSS) raw pseudorange and carrier phase observations, which can provide a new way for the general public to obtain precise position information. However, on...
Decision making in modern supply chain management relies heavily on data-driven decision support. Companies show a growing interest in building insights not only on data from within the company’s own boundaries, but also from collaborators and...
Directed graphs can be prepared from big data containing peoples’ interaction information. In these graphs the vertices represent people, while the directed edges denote the interactions among them. The number of interactions at certain intervals can...
Today, advanced websites serve as robust data repositories that constantly collect various user-centered information and prepare it for subsequent processing. The data collected can include a wide range of important information from email addresses,...
In modern industrial environments, data-driven decision-making plays a crucial role in ensuring operational efficiency, predictive maintenance, and process optimization. However, the effectiveness of these decisions is highly dependent on the quality...
Data science is currently one of the most promising fields used to support the decision-making process. Particularly, data streams can give these supportive systems an updated base of knowledge that allows experts to make decisions with updated model...
The emergence of social media, the worldwide web, electronic transactions, and next-generation sequencing not only opens new horizons of opportunities but also leads to the accumulation of a massive amount of data. The rapid growth of digital data ge...
This paper presents a comprehensive model for detecting and addressing concept drift in network security data using the Isolation Forest algorithm. The approach leverages Isolation Forest’s inherent ability to efficiently isolate anomalies in h...
High-resolution online sensors are now common in environmental process systems, yet turning their non-stationary, heterogeneous observation streams into reliable predictions of the underlying process state remains difficult. The statistical distribut...
As a reflection of shifting and fluid experiences in time and space, live streaming can reduce losses in the tourism industry associated with travel restrictions during the COVID-19 pandemic. Compared with the use of live streaming activities in ente...
The urban rail transit stations are an important part of an urban transit system. Scientific and reasonable location of rail transit station can greatly alleviate traffic pressure. The number of people in the surrounding area of a rail transit statio...
In recent years, with the development of various types of public transportation, they are also more and more closely connected. Among them, subway transportation has become the first choice of major cities. However, the planning of subway stations is...
Traditional retrieval-augmented generation (RAG) methods struggle with hierarchical documents, often causing semantic fragmentation, structural loss, and inefficient retrieval due to fixed strategies. To address these challenges, this paper proposes...
To achieve the full analytical potential of the streaming data from the internet of things, the interconnection of various data sources is needed. By definition, those sources are heterogeneous and their integration is not a trivial task. A common ap...
This paper presents an efficient approach for subsequence search in data streams. The problem consists of identifying coherent repetitions of a given reference time-series, also in the multivariate case, within a longer data stream. The most widely a...
Adaptive machine learning has increasing importance due to its ability to classify a data stream and handle the changes in the data distribution. Various resources, such as wearable sensors and medical devices, can generate a data stream with an imba...
With the rapid growth of live-streaming e-commerce and digital marketing, abnormal marketing behaviors have become increasingly concealed, coordinated, and intertwined across heterogeneous data modalities, posing substantial challenges to data-driven...
Predictive industrial maintenance promotes proactive scheduling of maintenance to minimize unexpected device anomalies/faults. Almost all current predictive industrial maintenance techniques construct a model based on prior knowledge or data at build...
In order to improve the effect of path planning in emergencies, the missing position imputation and velocity restoration in vehicle trajectory provide data support for emergency path planning and analysis. At present, there are many methods to fill i...
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