Prior study suggests that VANET has two types of communications: Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communications. V2V is very important and ensures cooperative communications between vehicles and safety measures. It is als...
Nowadays there is a large amount of information at our disposal, which is increasing day by day, and right now the question is not whether we have a method to process it, but which method is most effective, faster and best. When processing large data...
Retailers managing large stock-keeping unit (SKU) catalogues need a compact, auditable view of how individual products behave in order to plan replenishment, assortment and promotions. We present an interpretable analytics pipeline that derives SKU-l...
As an important part of intelligent transportation systems, traffic state classification plays a vital role for traffic managers when formulating measures to alleviate traffic congestion. The proliferation of traffic data brings new opportunities for...
The aim of the study was to group the lactation curve (LC) of Holstein cows in several clusters based on their milking characteristics and to investigate physiological differences among the clusters. Milking data of 330 lactations which have a milk y...
A wireless sensor network (WSN) is an essential component of the Internet of Things (IoTs) for information exchange and communication between ubiquitous smart objects. Clustering techniques are widely applied to improve network performance during the...
A simple and fast k-medoids algorithm that updates medoids by minimizing the total distance within clusters has been developed. Although it is simple and fast, as its name suggests, it nonetheless has neglected local optima and empty clusters that ma...
We present a novel technique for cardinality-constrained index-tracking, a common task in the financial industry. Our approach is based on market graph models. We model our reference indices as market graphs and express the index-tracking problem as...
This paper proposes two algorithms for clustering data, which are variable-sized sets of elementary items. An example of such data occurs in the analysis of a medical diagnosis, where the goal is to detect human subjects who share common diseases to...
Climate classification plays a fundamental role in understanding climatic patterns, particularly in the context of a changing climate. This study utilized hourly meteorological data from 36 major cities in China from 2011 to 2021, including 2 m tempe...
Background: Infective endocarditis (IE) is characterized by marked heterogeneity in microbiological etiology, clinical presentation, valvular involvement, and patient complexity, which complicates risk stratification. Unsupervised machine learning ha...
In this study, the multi-criteria decision-making (MCDM) technique is used in collaboration with K-medoids clustering to establish a novel algorithm for extending the lifetime of wireless sensor networks (WSNs) in the presence of uncertainty. One of...
As the internet and complex network infrastructures continue to expand, so does the threat of sophisticated cyberattacks, compelling organizations to adopt advanced proactive defenses. A cornerstone of these defensive strategies is the honeypot. Howe...
Wireless sensor network (WSN) sensor nodes should have adequate energy. Reduced energy usage is essential to maximize the endurance of WSNs. Combining WSN with a more significant energy source, a cluster head (CH), is another effective strategy for e...
Modern applications are increasingly built around networking, collaboration, and automation. Drones, or Unmanned Aerial Vehicles (UAVs), are a key part of this shift. Many complex missions require multiple UAVs to work together as a team, which means...
Electrification of transport is advancing, yet debate continues over whether battery electric vehicles (EVs) are a like-for-like and affordable alternative to internal-combustion engine (ICE) cars. Positioned in a rapidly evolving mainstream market,...
In several industrial fields, environmental and operational data are acquired with numerous purposes, potentially generating a huge quantity of data containing valuable information for management actions. This work proposes a methodology for clusteri...
Large multi-UAV mission systems operate over time-varying communication graphs with heterogeneous platforms, where classical distributed task assignment may incur excessive message passing and suboptimal task–resource matching. To address these...
Clustered-based wireless sensor networks have been extensively used in the literature in order to achieve considerable energy consumption reductions. However, two aspects of such systems have been largely overlooked. Namely, the transmission probabil...
Data-driven approaches have emerged as powerful tools for analyzing process data. This study focuses on two data-driven methods: n-gram chi-square feature selection for extracting key action segments and K-medoids clustering combined with Dynamic Tim...
Stunting remains a significant public health issue in Aceh, Indonesia, and is influenced by various socio-economic and environmental factors. This study aims to address key challenges in accurately classifying stunting prevalence, predicting future t...
In multi-UAV cooperative tasks, dynamic communication topologies and resource heterogeneity present significant challenges for distributed task allocation, leading to high communication overhead and poor task-resource matching, which in turn increase...
Mexico is a diverse country in terms of culture and natural environments. For this reason, the delimitation of homogeneous basins with similar environmental, social, and economic attributes is important in order to facilitate the elaboration of high-...
The purpose of this research is to classify time-series data on the number of daily COVID-19 cases based on the dynamics. This research aims to evaluate the effectiveness of community activity restrictions in suppressing the number of new cases of CO...
Building energy modelling (BEM) is crucial for achieving energy conservation in buildings, but occupant energy-related behaviour is often oversimplified in traditional engineering simulation methods and thus causes a significant deviation between ene...
Theory of planned behavior (TPB) constructs and shopping routines are strong predictors of food waste behavior, while socio-demographic factors show mixed and weaker associations. We analyzed survey data from a nationally representative sample of 106...
Accurate load forecasting is crucial for the safe, stable, and economical operation of integrated energy systems. However, directly applying single models to predict coupled cooling, heating, and electric loads under complex influencing factors often...
Scenario generation and reduction based on a single variable (e.g., photovoltaic power or load forecasting) is a mainstream approach in current power system planning. However, such methods often overlook the temporal correlation between source and lo...
Hydrological prediction under climate change requires representative data selection and adaptable model architecture. This study proposes a two-part methodology to improve deep learning performance in hydrological prediction. The first component, the...
Many traffic conflicts on the roads are caused by a small proportion of drivers. Currently, there are few studies exploring the time-varying patterns of driving behavior among these drivers. This paper proposes a generic time-series analytical framew...
Land cover classification (LCC) using satellite images is one of the rapidly expanding fields in mapping, highlighting the need for updating existing computational classification methods. Advances in technology and the increasing variety of applicati...
Composite insulations, such as ceramics, are commonly utilized in the turbine system as a thermal coating barrier to protect the metal substrate against high temperatures and pressure. The presence of delamination in the composite insulations may cau...
Training-free video summarization tackles the challenge of selecting the most informative keyframes from a video without relying on costly training or complex deep models. This work introduces C2FVS-DPP (Contextual Feature Fusion Video Summarization ...
Objective: To identify distinct subtypes of ICU patients with Acute Kidney Injury (AKI) using serum electrolyte data and assess their associations with in-hospital mortality risk. Methods: This study used the eICU Collaborative Research Database (eIC...
The estimation of losses of distribution feeders plays a crucial guiding role for the planning, design, and operation of a distribution system. This paper proposes a novel estimation method of statistical line loss of distribution feeders using the f...
Air quality monitoring is important in the management of the environment and pollution. In this study, time series of PM10 from air quality monitoring stations in Malaysia were clustered based on similarity in terms of time series patterns. The ident...
Unpredictable climate patterns and mounting groundwater depletion are major challenges to sustainable agriculture. The purpose of this research is to improve predictive accuracy in IoT-based smart irrigation systems using machine learning models for...
A wireless sensor network (WSN) deploys hundreds or thousands of nodes that may introduce large-scale data over time. Dealing with such an amount of collected data is a real challenge for energy-constraint sensor nodes. Therefore, numerous research w...
The EU regional development policy aims to reduce through its cohesion policy the socio-economic development disparities between its most developed regions and peripheral regions. Research shows that despite this strategy, the economic development of...
The urban landscape is being affected by rapid urbanization, leading to a complexity of land features and a fragmentation of patches. However, many studies have focused on the prediction of land-use change with a lack of research on the landscape cha...
Clustering ensemble indicates to an approach in which a number of (usually weak) base clusterings are performed and their consensus clustering is used as the final clustering. Knowing democratic decisions are better than dictatorial decisions, it see...
The modern discrimination of sediment is based on acoustic intensity (backscatter) information from high-resolution multibeam echo-sounder systems (MBES). The backscattering intensity, varying with the angle of incidence, reveals the characteristics...
The emergence of geospatial big data has opened up new avenues for identifying urban environments. Although both geographic information systems (GIS) and expert systems (ES) have been useful in resolving geographical decision issues, they are not wit...
This study applied clustering algorithms to reveal latent structures in 9791 Brazilian civil aviation occurrences recorded from 2007 to 2023. We tested K-means, hierarchical clustering, and K-medoids, using aircraft type, flight phase, and severity a...
Energy determines the social, economic, and environmental aspects that enable the advancement of communities. For this reason, this paper aims to analyze the quality of the energy service in the Non-Interconnected Zones (NIZ) of Colombia. For this pu...
Galaxies are one of the most interesting and complex astronomical objects statistically due to their continuous diversification caused mainly due to incidents such as accretion, action, or mergers. Multivariate studies are one of the most useful tool...
The investor interest in multi-regional earthquake bonds may drop because high-risk locations are less appealing to investors than low-risk ones. Furthermore, a single parameter (earthquake magnitude) cannot accurately express the severity due to an...
The variability in generation introduced in the electrical system by an increasing share of renewable technologies must be addressed by balancing mechanisms, demand response being a prominent one. In parallel, the massive introduction of smart meters...
Spatial group recommendation refers to suggesting places to a given set of users. In a group recommender system, members of a group should have similar preferences in order to increase the level of satisfaction. Location-based social networks (LBSNs)...
Background/Objectives: Selecting candidate cross-docking locations is a critical strategic decision in early-stage logistics network design. Conventional approaches often aggregate all demand data into a single planning snapshot, hiding the differenc...
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