Microfluidic paper-based analytical devices (µPADs) are leading the field of low-cost, quantitative in-situ assays. However, understanding the flow behavior in cellulose-based membranes to achieve an accurate and rapid response has remained a c...
Distributed estimation of Gaussian mixtures has many applications in wireless sensor network (WSN), and its energy-efficient solution is still challenging. This paper presents a novel diffusion-based EM algorithm for this problem. A diffusion strateg...
The completeness and integrity of multimodal medical data are critical determinants of surgical success and postoperative recovery. However, because of issues such as poor sensor contact, small vibrations, and device discrepancies during signal acqui...
This paper introduces a novel framework for generating synthetic time-series data from turbine engine sensor readings using a text-conditioned diffusion model. The approach begins with dataset preprocessing, including correlation analysis, feature se...
Compressive sensing (CS)-based data gathering is a promising method to reduce energy consumption in wireless sensor networks (WSNs). Traditional CS-based data-gathering approaches require a large number of sensor nodes to participate in each CS measu...
Grouting technology is widely used in construction and civil engineering, where evaluating grouting effectiveness is crucial due to the uncertainty of subsurface conditions. Existing methods face drawbacks such as destructiveness, high cost, poor dur...
Energy-efficient clustering extends the lifetime of wireless sensor networks (WSNs). Conventional protocols such as LEACH and HEED primarily address communication energy and cluster head (CH) selection rather than area coverage under random deploymen...
The application of smartphone-based color evaluation of passive sampling devices for gases has only been sparsely reported. The present review aims to compile available publications with respect to the configuration of the passive samplers, condition...
Recent advances in nanotechnology, electronic technology and biology have enabled the development of bio-inspired nanoscale sensors. The cooperation among the bionanosensors in a network is envisioned to perform complex tasks. Clock synchronization i...
A very simple to realize, low-cost, and highly sensitive plasmonic sensor, based on a polymeric light-diffusing fiber (LDF), is presented. The proposed surface plasmon resonance (SPR) sensor is realized by sputtering a gold nanofilm on an LDF made of...
A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of...
In the published publication [...]
An important class of analytes are volatile organic carbons (VOCs), particularly aliphatic primary alcohols. Here, we report the straightforward modification of a commercially available carbon monoxide sensor to detect a range of aliphatic primary al...
Microfluidic paper-based analytical devices (µPADs) are a promising technology to enable accurate and quantitative in situ assays. Paper’s inherent hydrophilicity drives the fluids without the need for external pressure sources. However, controlling...
This paper presents Diff-GTISR, a novel diffusion-based model for achieving super-resolution in thermal images guided by a high-resolution visible image. Thermal sensors are widely used in surveillance, safety, and industrial inspection; however, the...
Estimation accuracy is the core performance index of sensor networks. In this study, a kind of distributed Kalman filter based on the non-repeated diffusion strategy is proposed in order to improve the estimation accuracy of sensor networks. The algo...
In the current work an experimental method is used in order to calculate the diffusivity
Deep learning models rely heavily on extensive training data, but obtaining sufficient real-world data remains a major challenge in clinical fields. To address this, we explore methods for generating realistic synthetic multivariate fall data to supp...
In this paper, a distributed cubature Gaussian mixture filter (DCGMF) based on an iterative diffusion strategy (DCGMF-ID) is proposed for multisensor estimation and information fusion. The uncertainties are represented as Gaussian mixtures at each se...
Imaging tasks today are being increasingly shifted toward deep learning-based solutions. Biomedical imaging problems are no exception toward this tendency. It is appealing to consider deep learning as an alternative to such a complex imaging task. Al...
We developed and optimized a new fiber optic sensor using palladium foils attached to optical fiber Bragg gratings (FBG) for hydrogen measurements. Fifteen in parallel processed sensors were characterized and qualified in two custom tailored experime...
Training fall detection systems is challenging due to the scarcity of real-world fall data, particularly from elderly individuals. To address this, we explore the potential of Large Language Models (LLMs) for generating synthetic fall data. This stud...
Remote sensing image dehazing presents substantial challenges in balancing physical fidelity with generative flexibility, particularly under complex atmospheric conditions and sensor-specific degradation patterns. Traditional physics-based methods of...
Non-invasive blood analysis has the power to completely change how doctors identify and track illnesses. This study presents a novel approach for the non-invasive monitoring of red blood cell (RBC) mobility and concentration within capillaries, using...
Data-driven quality control (QC) systems for the hot forming of steel parts increasingly rely on deep learning models deployed at the network edge, making multivariate sensor time series a critical asset for both local decisions and management inform...
Low-light image super-resolution aims to recover normal-light high-resolution images from dark low-resolution observations captured by image sensors, in which illumination attenuation, sensor noise, blur, and low resolution are entangled, making it m...
Reliable air-quality monitoring is essential for urban exposure assessment and environmental policy, yet many downstream applications are hindered by sparse regulatory stations and noisy real-world measurements. While diffusion models have shown prom...
Sensor technology has enabled the development of portable low-cost monitoring kits that might supplement many applications in conventional monitoring stations. Despite the sensitivity of electrochemical gas sensors to environmental change, they are i...
This study evaluates the feasibility of continuous indoor pollutant monitoring as an indirect method for assessing extended ventilation performance in residential buildings. This research addresses key limitations of conventional short-term tracer-ga...
This work presents an in vivo stem-mounted sensor for Nicotiana tabacum plants and an in situ cell suspension sensor for Solanum lycopersicum cells. Stem-mounted sensors are mechanically stable and less sensitive to plant and air movements than the p...
Water is a basic necessity and one of the most valuable resources for human living. Sadly, large quantities of treated water get lost daily worldwide, especially in developing countries, through leaks in the water distribution network. Wireless senso...
Many sensor nodes have been widely deployed in the physical world to gather various environmental information, such as water quality, earthquake, and huge dam safety. Due to the limitation in the batter power, memory, and computational capacity, miss...
Reliable short-term freeway traffic forecasting is essential for proactive traffic management, including congestion warning, ramp metering support, and traveler information services. However, many existing forecasting models treat spatial dependencie...
Sensor-based environmental monitoring systems are often affected by missing, noisy, and unreliable measurements caused by sensor faults, sparse deployment, calibration drift, and communication interruptions. To address these challenges, this study pr...
Mirror segmentation is challenging because reflected contours can be difficult to distinguish from physical mirror boundaries. Depth provides complementary geometric cues, but active sensing can produce invalid or distorted measurements on reflective...
Soil moisture sensors deployed for long-term monitoring often suffer from prolonged data gaps caused by battery depletion, communication dropouts, or hardware failures. When such gaps overlap with irrigation events, key transient phases are obscured...
Change detection (CD) is a fundamental remote sensing task that identifies surface modifications from multi-temporal imagery of the same area, with applications in urban monitoring, agriculture, forest disturbance mapping, disaster assessment, and la...
Accurate forest soil organic carbon (SOC) monitoring is essential for forest soil quality assessment and carbon-sink evaluation. Visible-near-infrared (Vis–NIR) hyperspectral sensing provides rapid and information-rich measurements for SOC pred...
Deep learning (DL) has achieved significant attention in the field of infrared (IR) and visible (VI) image fusion, and several attempts have been made to enhance the quality of the final fused image. It produces better results than conventional metho...
This study evaluates the effectiveness of integrating a Residual Shifting (ResShift)-based deep learning super-resolution (SR) technique with the Robust Dense Feature Matching (RoMa) algorithm for high-precision inter-satellite image registration. Th...
We designed and realized a low cost relative humidity (RH) capacitive sensor having an interdigitated transducer coated with a cheap sensing material working at room temperature (polyimide). Thermally perturbed diffusion of water molecules into the p...
In this paper, a low cost optical flow sensor is combined with an external laser device to measure surface displacements and mechanical oscillations. The measurement system is based on applying coherent light to a diffuser surface and using an optica...
A design scheme of multi-element sensor which included electrical resistivity probes, multiple Cl− selective electrodes, and a steel corrosion monitoring system was proposed in this work. Embedding this multi-element sensor in concrete enables...
The influence of oxygen vacancy behaviors during a cooling process in semiconductor gas sensors is discussed by the numerical analysis method based on the gradient-distributed oxygen vacancy model. A diffusion equation is established to describe the...
We report on the spatial and temporal signaling properties of a yeast pheromone-based cell communication and amplifier system. It utilizes the Saccharomyces cerevisiae mating response pathway and relies on diffusion of the pheromone α–factor as key s...
Based on a multi-gas solution-diffusion problem for a dense symmetrical membrane this paper presents a transient theory of a planar, membrane-based sensor cell for measuring gas from both initial conditions: dynamic and thermodynamic equilibrium. Usi...
Hydrogels are of great importance for functionalizing sensors and microfluidics, and poly(ethylene glycol) dimethacrylate (PEG-DMA) is often used as a viscosifier for printable hydrogel precursor inks. In this study, 1–10 kDa PEG-DMA based hydr...
In digital holography, reconstructed image quality can be primarily limited due to the inability of a single small aperture sensor to cover the entire field of a hologram. The use of multi-sensor arrays in synthetic aperture digital holographic imagi...
Transferring laser-based sensors into industrial applications (for instance, for contact and destruction-free inline quality control of alumina alloys) is very challenging due to laser-safety regulations and the complex implementation requirements of...
Sensors that remotely track the displacement of a moving object have a wide range of applications from robotic control to motion capture. In this paper, we introduce a simple, small silicon integrated circuit sensor that tracks the angular displaceme...
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