Wavelength modulation-tunable diode laser absorption spectroscopy (WM-TDLAS) is a critical tool for gas detection. However, noise in second harmonic signals degrades detection performance. This study presents a hybrid denoising algorithm combining Em...
A surface-acoustic-wave (SAW) gas sensor with a low detection limit and fast response for volatile organic compounds (VOCs) based on the condensate-adsorption effect detection is developed. In this sensor a gas chromatography (GC) column acts as the...
A polymer-coated surface acoustic wave (SAW)-based chemical sensor for organophosphorous compound sensing at extremely low concentrations was developed, in which a dual-delay-line oscillator coated with fluoroalcoholpolysiloxane (SXFA) acted as the s...
In the field of biomedical imaging, the use of Convolutional Neural Networks (CNNs) has achieved impressive success. Additionally, the detection and pathological classification of breast masses creates significant challenges. Traditional mammogram sc...
Background: Fetal Heart Quantification (FetalHQ) enables detailed assessment of fetal cardiac morphology and function using two-dimensional speckle-tracking echocardiography. However, previous studies have focused primarily on conventional reproducib...
Spectral features for natural stichtite at 1042, 1096, 1360, 1638, and 3482 cm−1 provide insights on mineral structure, with peaks consistent with OH− stretching modes bound to Mg or Cr, CO32− antisymmetric stretches and CO32−...
In order to evaluate the tracking capability of optoelectric tracking for an orbital target, the limit magnitude detection performance calculation model and its calculation method are studied. Combining the optical signal characteristics of the track...
Tracking-by-detection (TBD) frameworks for multi-object tracking (MOT) commonly employ fixed confidence thresholds for data association, making them sensitive to frame-level variations caused by camera motion, illumination changes, and object occlusi...
The constant false alarm rate (CFAR) process is essential for target detection in radar systems. Although the detection performance of the CFAR process is normally guaranteed in noise-limited environments, it may be dramatically degraded in clutter-l...
Virtual reality (VR) provides a flexible platform for investigating human perception of augmented bodily abilities. While motion scaling of virtual limbs has been explored in previous studies, psychophysical detection thresholds and embodiment have r...
Infrasound leakage signals, with low propagation energy loss, are ideal for long-distance and small leakage detection but suffer severe background noise interference. Existing wavelet denoising methods using traditional soft/hard threshold functions...
Cracks in concrete structures, caused by aging, adjacent construction, and seismic activity, pose critical risks to structural integrity, durability, and serviceability. Traditional monitoring methods based solely on absolute thresholds are inadequat...
Background: Non-targeted screening of food contact materials (FCM) for non-intentionally added substances (NIAS) reveals a great number of unknown and unidentified substances present at low concentrations. In the absence of toxicological data, the ap...
Spectrum-sensing algorithms are one of the effective solutions to the problem of the underwater spectrum resource constraint. However, because the underwater acoustic channel is one of the most complex channels, it has many characteristics, such as a...
The necessity for precise and current data concerning the dynamics of land cover change in Indonesia is crucial for efforts to reduce natural vegetation cover due to agricultural expansion. The functionality of monitoring systems that incorporate Ter...
Anomaly detection and degradation trend prediction are two pivotal tasks in system health management. However, most existing approaches treat them as independent problems and fail to exploit their intrinsic interdependence. In addition, the scarcity...
Spectrum-sensing technology is crucial for the development of underwater acoustic communication networks and plays a key role in detecting spectrum holes and channel occupancy. Energy detection technology, as the fundamental spectrum sensing technolo...
Drone ad-hoc networks are inherently vulnerable to performance-degradation attacks such as jamming, packet disruption, and routing interference due to dynamic topology changes and unstable wireless channels. In such environments, conventional thresho...
The anomaly detection of urban rail vehicle door systems is crucial for the security and reliability of rail vehicles, and unsupervised methods have received particular attention in anomaly detection due to the scarcity of anomaly data. However, exis...
Wideband spectrum sensing plays a crucial role in various wireless communication applications. Traditional methods, such as energy detection with thresholding, have limitations like detecting signals with low signal-to-noise ratio (SNR). This article...
Rare event detection in large tabular data remains a computationally challenging problem due to class imbalance, heterogeneous feature distributions, and unstable thresholds. Traditional machine learning approaches based on individual models and fixe...
Dust detection is essential for environmental protection, climate change assessment, and human health issues. Based on the Fengyun-4A (FY-4A)/Advance Geostationary Radiation Imager (AGRI) images, this paper aimed to examine the performances of two cl...
Threshold assessments for the reference odorant n-butanol are an integral part of various research, clinical, and environmental sensory testing procedures. However, the practical significance of a high or low threshold for n-butanol beyond a particul...
Food allergy has been on the increase for many years. The prevalence of allergy to different foods varies widely depending on type of food, frequency of consumption and geographic location. Data from the literature suggests that the prevalence of tre...
Trees play a vital role in urban environments by mitigating heat islands, floods, and pollution, while promoting public health and well-being. Acoustic tomography is an effective tool for assessing tree integrity, but its high-cost limits widespread...
Early-stage stroke rehabilitation increasingly incorporates virtual reality (VR) systems to provide interactive motor training and positive reinforcement. However, the minimal voluntary plantar pressure activations generated during early recovery are...
Background: Obstructive sleep apnea (OSA) is one of the most prevalent yet underdiagnosed sleep disorders. We evaluated the diagnostic accuracy of radar-based systems and ranked frequency bands for the non-contact detection of OSA. Methods: A systema...
This study presents a healthy-only bearing fault detection framework in which a stacked long short-term memory (LSTM) predictor learns normal vibration dynamics through multi-step forecasting, and deviations between predicted and observed vibration s...
Canny edge detection is one of the most widely used edge detection algorithms due to its superior performance. However, it is a complex, time-consuming process and has a high hardware cost. To overcome these issues, an improved Canny algorithm is pro...
The application of the Phasor Measurement Unit (PMU) in the power system is expanding day by day since it provides a higher reliability through fast symmetrically monitoring and protection and assists in controlling power systems. For power systems,...
Background: B-type natriuretic peptide (BNP) is widely used in the diagnosis, risk stratification, and management of heart failure (HF). However, its diagnostic performance for detecting elevated left ventricular filling pressure, particularly at low...
Accurate, timely, and fine-resolution crop phenology is essential for determining the optimal timing of agronomic management practices supporting precision agriculture and food security. Synthetic Aperture Radar (SAR) methods, unaffected by cloud occ...
The odor detection threshold (ODT) of a compound is the lowest concentration at which individuals can reliably perceive a difference between a sample and its corresponding control, with 50% performance above chance. Wine is a complex matrix, and ODTs...
This paper proposes an innovative approach for detecting and quantifying concrete cracks using an adaptive threshold method based on Median Absolute Deviation (MAD) in images. The technique applies limited pre-processing steps and then dynamically de...
Printed product surface defect inspection faces critical challenges in real industrial production, including insufficient detection accuracy, poor robustness, and scarcity of labeled defective samples. This paper proposes an improved Siamese network...
In recent years, multi-temporal imagery from spaceborne sensors has provided a fast and practical means for surveying and assessing changes in terrain surfaces. Owing to the all-weather imaging capability, polarimetric synthetic aperture radar (PolSA...
This paper presents a grid-based distributed event detection scheme for wireless sensor networks. The network is divided into square-shaped grids of predefined grid size, where sensor nodes in each grid form a cluster with a cluster head. Event detec...
Backdoor attacks pose a critical security risk to pre-trained language models (PLMs) by utilizing concealed triggers to manipulate model outputs. Existing defense strategies largely depend on statistical thresholds, which often struggle to identify s...
Multiplexed detection of arboviruses using a 4 × 4 Si-based electrolyte-gated transistor (EGT) array functionalized with specific aptamers has been investigated. The Si-based EGTs were fabricated using conventional Si microfabrication processes. The...
Multiscale PCA (MSPCA) is a well-established fault-detection and isolation (FDI) technique. It utilizes wavelet analysis and PCA to extract important features from process data. This study demonstrates limitations in the conventional MSPCA fault dete...
Anomaly signals in the Attitude Determination and Control System (ADCS) of nanosatellites can significantly degrade mission performance, especially in the absence of robust Fault Detection, Isolation, and Recovery (FDIR) mechanisms. Thus, traditional...
A wall-dependent identification method for low-speed streamwise streaks in turbulent channel flows is presented to overcome a key limitation of uniform thresholds, which tend to produce either an excess of detected structures near the wall or an appa...
Spacecraft systems collect health-related data continuously, which can give an indication of the systems’ health status. While they rarely occur, the repercussions of such system anomalies, faults, or failures can be severe, safety-critical and...
Wastewater-based epidemiology (WBE) played a vital role during the COVID-19 pandemic by providing early warnings of outbreaks through SARS-CoV-2 RNA detection in sewage. Many rural communities did not benefit from WBE because limited centralized sewe...
Recently, we reported induced anoxia as a limiting factor for photodynamic tumor therapy (PDT). This effect occurs in vivo if the amount of generated singlet oxygen that undergoes chemical reactions with cellular components exceeds the local oxygen s...
The fast growth of hydrogen usage as a clean fuel in civil applications such as transportation, space technology, etc. highlights the importance of the reliable detection of its leakage and accumulation under explosion limit by sensors with a low pow...
Small-scale object detection remains a significant challenge in semi-supervised object detection (SSOD), particularly in panoramic dental X-rays. Due to the small lesion size, low contrast, and complex anatomical background, conventional teacher mode...
Robust detection of emergency vehicle sirens remains difficult due to modern soundproofing, competing audio, and variable traffic noise. Although many simulation-based studies have been reported, relatively few systems have been realized in hardware,...
Credit card fraud remains a major cause of financial loss around the world. Traditional fraud detection methods that rely on supervised learning often struggle because fraudulent transactions are rare compared to legitimate ones, leading to imbalance...
The growing complexity of software-defined automotive systems generates massive heterogeneous sensor and ECU data during real and virtual validation, and conventional rule-based analysis of such multivariate time series struggles under dynamic operat...
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