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BackgroundMeteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the...

"Complex networks theory have gained wider applicability since methods for transformation of time series to networks were proposed and successfully tested. In the last few years, horizontal visibility graph has become a ...

IntroductionThe escalating frequency of infectious disease outbreaks underscores the urgent need for reliable forecasting systems to support timely public health interventions. Existing approaches—ranging from statisti...

"In this paper, we propose a formalism to query transportation networks that are equipped with sensors that produce time-series data. The core of the proposed query mechanism is a logic based language that is capable to...

Abstract Understanding and controlling the marine degradation of biodegradable polymers is crucial for sustainable materials engineering and pollution prevention. However, a unified interpretive method that links multisc...

Abstract The integration of large-scale distributed power sources complicates grid topology and intensifies spatiotemporal coupling in power data. This complicates the analysis of intrinsic correlations and makes predict...

The growth of variable renewable energy sources has increased the occurrence of curtailment in power systems, particularly in regions affected by transmission constraints and limited operational flexibility. Reliable for...

Multivariate time series forecasting is pivotal in real-world applications, ranging from energy consumption management and financial market trend analysis to traffic flow prediction and climate monitoring. Yet, it is cri...

Time series analysis is essential for finance, transportation, energy, healthcare, and climate research. While time-frequency domain representation underpins effective time series modeling, its holistic utilization and i...

The aim of this paper is to present and validate rain attenuation time series synthesizers relying on the Maseng-Bakken principle for terrestrial links in tropical areas. Data obtained in experimental measurements at fou...

BackgroundMaternal exposure to air pollutants are associated with congenital heart defects (CHDs), yet fundamental questions remain unclear: which pollutant matters most, which exposure window is most critical, and wheth...

Introduction and aims: Understanding the trend and associated factors are essential for enhancing equitable access to care, particularly given persistent disparities in healthcare utilisation across different population ...

ABSTRACT Background Tuberculosis (TB) remains a significant public health challenge, necessitating accurate forecasting methodologies to support effective control and prevention strategies. This paper explores the applic...

Time-series forecasting is fundamental to decision-making across numerous domains; however, systematic temporal delays in predictions remain a largely overlooked or unrecognised phenomenon. This phenomenon occurs when fo...

Materias / palabras clave: time-series classification; explainable AI; post-hoc explanations; SHAP; LIME; Anchor

"In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been...

"A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring values of a given data sequence, should be implemented before estimating the permutation entropy. Consequently, equalities i...

Abstract Groundwater is a central component of the Earth system. However, our understanding of how it is dynamically interlinked with the atmosphere, hydrosphere, cryosphere, biosphere, geosphere, and anthroposphere rema...

Importance: Medical time series constitute the largest data type in electronic health records and are often irregularly sampled in real-world clinical settings. Such irregularly sampled medical time series exhibit uneven...

Abstract Air-conditioning load forecasting is important for building energy scheduling and control. The task is difficult because load data show clear periodic patterns, and sudden changes caused by events such as holida...

This study examines whether active learning activities based on time series forecasting for engineering students yield statistically significant improvements with respect to performance and engagement. In this context, a...

Higher education becomes a level of further education after pursuing a secondary education program. Tidar University is one of the public higher education institutions located in Central Java Province. Since its inceptio...

This study analyzes five years of 1-min solar global horizontal irradiance (GHI) and direct normal irradiance (DNI) observations obtained at Petrolina (northeast Brazil). Quality-assured hourly and daily averages are obt...

Industry 4.0 has brought numerous advantages, such as increasing productivity through automation. However, it also presents major cybersecurity issues, such as cyberattacks affecting industrial processes. Federated Learn...