442 Results Found

This paper identifies patterns in total and per capita CO₂ emissions among 208 countries considering different emission sources, such as cement, flaring, gas, oil, and coal. This research uses linear and non-linear dimensional reduction techniques, c...

In recent decades, human brain tumor detection has become one of the most challenging issues in medical science. In this paper, we propose a model that includes the template-based K means and improved fuzzy C means (TKFCM) algorithm for detecting hum...

Accurate prediction of coal spontaneous combustion levels is crucial for preventing and controlling spontaneous combustion in goaf areas. To address the ambiguity in classification standards of coal spontaneous combustion warning levels, 21 groups of...

Accurate prediction of short-term rockburst has a significant role in improving the safety of workers in mining and geotechnical projects. The rockburst occurrence is nonlinearly correlated with its influencing factors that guarantee imprecise predic...

In mobile edge computing (MEC), it is difficult to recognise an optimum solution that can perform in limited energy by selecting the best communication path and components. This research proposed a hybrid model for energy-efficient cluster formation...

Emerging technology like the Internet of Things (IoT) has great potential for use in real time in many areas, including healthcare, agriculture, logistics, manufacturing, and environmental surveillance. Many obstacles exist alongside the most popular...

This study investigates the underlying mechanisms governing the evolution of tip vortices in the far field of a naval propeller wake. To achieve this, a novel approach utilizing data clustering applied to particle image velocimetry snapshots is emplo...

The Internet of things (IoT) enables a diverse set of applications such as distribution automation, smart cities, wireless sensor networks, and advanced metering infrastructure (AMI). In smart grids (SGs), quality of service (QoS) and AMI traffic man...

Prostate imaging analysis is difficult in diagnosis, therapy, and staging of prostate cancer. In clinical practice, Magnetic Resonance Imaging (MRI) is increasingly used thanks to its morphologic and functional capabilities. However, manual detection...

Circulation type classification (CTC) is an important method in atmospheric sciences, which reveals the relationship between atmospheric circulation and regional weather and climate. Accurate circulation classification helps to improve weather foreca...

This paper focuses on the selection and optimisation of a cryptoasset portfolio, using the K-means clustering algorithm and GARCH C-Vine copula model combined with the differential evolution algorithm. This integrated approach allows the construction...

Image segmentation is a fundamental task in computer vision in which an image is divided into many regions or segments, each of which corresponds to a separate object or part of an item within the image. Image segmentation’s major purpose is to...

Background/Objectives: Patients with headache experience depression, anxiety, and reduced quality of life, which are individually associated with pain intensity and painkiller use, but their comprehensive combined effect remains unclear. Methods: Com...

Population ageing is an important global issue. The Taiwanese government has used various Internet of Things (IoT) applications in the “10-year long-term care program 2.0”. It is expected that the efficiency and effectiveness of long-term care servic...

With the development and popular application of Building Internet of Things (BIoT) systems, numerous types of equipment are connected, and a large volume of equipment data is collected. For convenient equipment management, the equipment should be ide...

An unsupervised k-means/k-means++ clustering algorithm was implemented on daily images of standardized anomalies of brightness temperature $\left({\mathrm{T}}_{\mathrm{b}}\right)$ derived from the Geostationary Operational Environmental Satellite (GOES)-13 infrared data for the period...

In this work, we consider the problem of shape-based time-series clustering with the widely used Dynamic Time Warping (DTW) distance. We present a novel two-stage framework based on Sparse Gaussian Modeling. In the first stage, we apply Sparse Gaussi...

With the rapid growth of Internet-of-things (IoT) devices, IoT communication has become an increasingly crucial part of 5G wireless communication systems. The large-scale IoT devices access results in system overload and low utilization of energy eff...

Background: Type 2 diabetes (T2DM) is a chronic condition with a high disease burden worldwide, and individuals with T2DM often have other morbidities. Understanding the local multimorbidity profile of patients with T2DM will inform precision medicin...

Monitoring the spatial and temporal variability of yield crop traits using remote sensing techniques is the basis for the correct adoption of precision farming. Vegetation index images are mainly associated with yield and yield-related physiological...

The Chicago Array of Things (AoT) is a robust dataset taken from over 100 nodes over four years. Each node contains over a dozen sensors. The array contains a series of Internet of Things (IoT) devices with multiple heterogeneous sensors connected to...

Melasma management is challenged by heterogeneity in patient presentation, particularly among individuals with darker skin tones. This study applied k-means clustering, an unsupervised machine learning algorithm that partitions data into k distinct c...

Long Range (LoRa) communication is widely adapted in long-range Internet of Things (IoT) applications. LoRa is one of the powerful technologies of Low Power Wide Area Networking (LPWAN) standards designed for IoT applications. Enormous IoT applicatio...

(1) Background. Printed circuit board (PCB) inspection is increasingly constrained by the cost and latency of reliable labels, owing to tiny/low-contrast defects embedded in complex backgrounds and severe class imbalance. (2) Methods. We proposed a s...

Recently, Asia has experienced significant damage from extreme precipitation events caused by climate change. Improving the accuracy of quantitative precipitation forecasts over wide regions is essential to mitigate the damage caused by precipitation...

Finding real-time anomalies in any network system is recognized as one of the most challenging studies in the field of information security. It has so many applications, such as IoT and Stock Markets. In any IoT system, the data generated is real-tim...

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...

Intrusion detection of IoT-based data is a hot topic and has received a lot of interests from researchers and practitioners since the security of IoT networks is crucial. Both supervised and unsupervised learning methods are used for intrusion detect...

High-grade Gastroenteropancreatic Neuroendocrine neoplasms (H-NENs) comprehend well-differentiated tumors (NET G3) and poorly differentiated carcinomas (NEC) with proliferative activity indexes as mitotic count (MC) >20 mitoses/10 HPF and Ki-67 &g...

This paper is devoted to investigating the problem of finite-time (FnT) adaptive cluster synchronization for heterogeneous fractional-order dynamic networks (FODNs) with community structure and co-competition interactions. By designing a suitable ada...

In this paper, we present a framework for exploring the spare capacity of IoT devices for clustered execution of multimedia applications. Applications of this type are usually framed with specific quality parameters that enable a desirable level of s...

In recent years, breast cancer detection is an important area of concentration towards curative image dispensation and exploration. Detection of a disease at an early stage is an important factor in taking it to the next level of treatment. Accuracy...

Molecular assembly in a complex cellular environment is vital for understanding underlying biological mechanisms. Biophysical parameters (such as single-molecule cluster density, cluster-area, pairwise distance, and number of molecules per cluster) r...

As the Internet of Things (IoT) continues to grow, a vast amount of data is generated. The IoT environment is quite sensitive to security challenges because personal information may be leaked or sensor data may be manipulated, which could cause accid...

Sensor-based food intake monitoring has become one of the fastest-growing fields in dietary assessment. Researchers are exploring imaging-sensor-based food detection, food recognition, and food portion size estimation. A major problem that is still b...

The objective of this research is to determine the meteorological drought index and the effective rainfall model that exhibit the highest correlation with the yield of rainfed wheat in the Karkheh watershed. Additionally, using spatial statistics ana...

Due to their maneuverability, unmanned aerial vehicles (UAVs) have grown into a promising enabler of the Internet of Things (IoTs). In addition to the benefits of the bandwidth and communication quality of millimeter-wave (mmWave) systems, a UAV-aide...

The role of the concomitant intake of zinc, potassium, calcium, and magnesium in the glycemic control of individuals with type 2 diabetes mellitus (T2DM) has not been extensively discussed. We evaluated the relationship between the dietary intake of...

Obtaining accurate global motion is a crucial step for video stabilization. This paper proposes a robust and simple method to implement global motion estimation. We don’t extend the framework of 2D video stabilization but add a “plug and play” module...

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...

In this paper, a wind turbine anomaly detection method based on a generalized feature extraction is proposed. Firstly, wind turbine (WT) attributes collected from the Supervisory Control And Data Acquisition (SCADA) system are clustered with k-means,...

In post-disaster scenarios, Unmanned Aerial Vehicles (UAVs) acting as Mobile Aerial Base Stations (MABSs) offer a flexible means of restoring communication for isolated user equipment (UE) when conventional infrastructure is unavailable. More broadly...

Internet of Things (IoT), a strong integration of radio frequency identifier (RFID), wireless devices, and sensors, has provided a difficult yet strong chance to shape existing systems into intelligent ones. Many new applications have been created in...

This study explores burnout among nursing students in Bangalore, India, focusing on Exhaustion and Disengagement scores. A cross-sectional design was applied using the Oldenburg Burnout Inventory modified for nursing students, collecting data using a...

Type 2 diabetes (T2D) is associated with increased cardiovascular morbidity, mortality, and hospital admissions. This study aimed to analyze how the differences in delivered care (variability of glycosylated hemoglobin (HbA1c) achieved targets) affec...

Data classification is an important research topic in the field of data mining. With the rapid development in social media sites and IoT devices, data have grown tremendously in volume and complexity, which has resulted in a lot of large and complex...

The delineation of precipitation regions is to identify homogeneous zones in which the characteristics of the process are statistically similar. The regionalization process has three main components: (i) delineation of regions using clustering algori...

Examining boiler failure causes is crucial for thermal power plant safety and profitability. However, traditional approaches are complex and expensive, lacking precise operational insights. Although data-driven approaches hold substantial potential i...

This work presents a structural health monitoring (SHM) approach for the detection and classification of structural changes. The proposed strategy is based on t-distributed stochastic neighbor embedding (t-SNE), a nonlinear procedure that is able to...

The resource management in wireless networks with massive Internet of Things (IoT) users is one of the most crucial issues for the advancement of fifth-generation networks. The main objective of this study is to optimize the usage of resources for Io...